Animal Biodiversity and Conservation issue 28.1 (2005) by Museu Ciències Naturals de Barcelona MCNB

Formerly Miscel·lània Zoològica

2005

and

Animal Biodiversity Conservation 28.1

"Le platax d'Ehrenberg (Platax Ehrenbergii, Cav. Nat.)" Le Règne Animal par Georges Cuvier; Paris: Fortin, Masson et Cie, Librairies; Pl. 42 Poissons Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de redacció / Secretaría de redacción / Editorial Office

Secretària de redacció / Secretaria de redacción / Managing Editor Montserrat Ferrer

Museu de Ciències Naturals Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail abc@mail.bcn.es

Consell assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Editors / Editores / Editors Pere Abelló Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Javier Alba–Tercedor Univ. de Granada, Granada, Spain Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, Spain Xavier Bellés Centre d' Investigació i Desenvolupament–CSIC, Barcelona, Spain Juan Carranza Univ. de Extremadura, Cáceres, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Michael J. Conroy Univ. of Georgia, Athens, USA Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Xavier Domingo–Roura inst. de Recerca i Tecnologia Agroalimentàries, Cabrils, Spain José Antonio Donazar Estación Biológica de Doñana–CSIC, Sevilla, Spain Gary D. Grossman Univ. of Georgia, Athens, USA Damià Jaume IMEDEA–CSIC, Univ. de les Illes Balears, Spain Jordi Lleonart Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Jorge M. Lobo Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Pablo J. López–González Univ de Sevilla, Sevilla, Spain Juan José Negro Estación Biológica de Doñana–CSIC, Sevilla, Spain Vicente M. Ortuño Univ. de Alcalá de Henares, Alcalá de Henares, Spain Miquel Palmer IMEDEA–CSIC, Univ. de les Illes Balears, Spain Francisco Palomares Estación Biológica de Doñana–CSIC, Sevilla, Spain Francesc Piferrer Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Montserrat Ramón Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Ignacio Ribera Nacional de Ciencias Naturales–CSIC, Madrid, Spain Pedro Rincón Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Alfredo Salvador Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Ciències Naturals de Barcelona, Barcelona, Spain Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana–CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle–CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Jersey, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana–CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Estación Experimental de Zonas Áridas–CSIC, Almería, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway Animal Biodiversity and Conservation 28.1, 2005 © 2005 Museu de Ciències Naturals, Institut de Cultura, Ajuntament de Barcelona Autoedició: Montserrat Ferrer Fotomecànica i impressió: Sociedad Cooperativa Librería General ISSN: 1578–665X Dipòsit legal: B–16.278–58 The journal is freely available online at: http://www.bcn.cat/ABC

Animal Biodiversity and Conservation 28.1 (2005)

Osmoderma eremita (Coleoptera, Scarabaeidae, Cetoniinae) in Europe T. Ranius, L. O. Aguado, K. Antonsson, P. Audisio, A. Ballerio, G. M. Carpaneto, K. Chobot, B. Gjurašin, O. Hanssen, H. Huijbregts, F. Lakatos, O. Martin, Z. Neculiseanu, N. B. Nikitsky, W. Paill, A. Pirnat, V. Rizun, A. Ruicănescu, J. Stegner, I. Süda, P. Szwałko, V. Tamutis, D. Telnov, V. Tsinkevich, V. Versteirt, V. Vignon, M. Vögeli, P. Zach Ranius, T., Aguado, L. O., Antonsson, K., Audisio, P., Ballerio, A., Carpaneto, G. M., Chobot, K., Gjurašin, B., Hanssen, O., Huijbregts, H., Lakatos, F., Martin, O., Neculiseanu, Z., Nikitsky, N. B., Paill, W., Pirnat, A., Rizun, V., Ruicănescu, A., Stegner, J., Süda, I., Szwałko, P., Tamutis, V., Telnov, D., Tsinkevich, V., Versteirt, V., Vignon, V., Vögeli, M. & Zach, P., 2005. Osmoderma eremita (Coleoptera, Scarabaeidae, Cetoniinae) in Europe. Animal Biodiversity and Conservation, 28.1: 1–44. Abstract Osmoderma eremita (Coleoptera, Scarabaeidae, Cetoniinae) in Europe.— Research, monitoring and development of preservation strategies for threatened species are often limited by national borders even though a global perspective would be more appropriate. In this study, we collected data on the occurrence of a threatened beetle, Osmoderma eremita, associated with tree hollows in 2,142 localities from 33 countries in Europe where it is or has been present. The larvae develop in tree hollows and very few observations of larvae have been observed in dead logs on the ground. As long as there is a suitable tree hollow, it appears that O. eremita may use any tree species. Oaks (Quercus spp.) are the trees mainly used by O. eremita, followed by lime (Tilia spp.), willow (Salix spp.), beech (Fagus sylvatica) and fruit trees (Prunus spp., Pyrus spp., Malus domestica). O. eremita is still found in some remnants of natural forest, but is mainly observed on land that has long been used by man, such as pasture woodlands, hunting parks, avenues, city parks and trees around agricultural fields and along streams. The occurrence of O. eremita seems to have decreased in all European countries. Relatively high densities of O. eremita localities occur in Central Europe (northern Italy, Austria, Czechia, southern Poland and eastern Germany), some parts of Northern Europe (south–eastern Sweden, Latvia) and France. In some regions in north–western Europe, the species is extinct or may occur at some single sites (Norway, Danish mainland, The Netherlands, Belgium, north–eastern France). There are few data from south–eastern Europe. Many local extinctions of O. eremita are to be expected in the near future, especially in regions with recent habitat loss and fragmentation. O. eremita is useful as an indicator and umbrella species for the preservation of the entire invertebrate community associated with hollow trees in Europe. A preservation plan for O. eremita should include three aspects that are of general importance in nature conservation in Europe today: (1) preservation of remnants of natural forests with old, broad–leaved trees, (2) preservation and restoration of habitats related to traditional agricultural landscapes and (3) preservation of remaining "islands" of nature in urban areas. Key words: Saproxylic, Cavity, Habitat Directive, Pollarding, Bioindicator, Scarabaeoidea. Resumen Osmoderma eremita (Coleoptera, Scarabaeidae, Cetoniinae) en Europa.— La investigación, el control y el desarrollo de estrategias de conservación de especies amenazadas en peligro de extinción están habitualmente confinadas por fronteras nacionales aunque sería más apropiado una perspectiva más global. En este trabajo se recogen datos sobre la presencia de un escarabajo en peligro de extinción, Osmoderma eremita, asociado a huecos de árboles en las 2.142 localidades de 33 regiones de Europa donde se ha encontrado. La larva se desarrolla en los huecos de los árboles y se ha observado pocas veces en troncos muertos en el suelo. Parece ser que O. eremita es capaz de utilizar cualquier especie de árbol siempre que tenga un hueco disponible. Los árboles más utilizados por O. eremita son los robles (Quercus spp.), seguidos del tilo (Tilia spp.), el sauce (Salix spp.), el haya (Fagus sylvatica) y los árboles ISSN: 1578–665X

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frutales (Prunus spp., Pyrus spp., Malus domestica). O. eremita se encuentra todavía en algún remanente de bosque natural, pero se observa principalmente en tierras que han sido usadas por el hombre como zonas de bosques aclarados, cotos de caza, avenidas, parques urbanos y en árboles alrededor de campos agrícolas y a lo largo del curso de ríos. Parece ser que la presencia de O. eremita ha disminuido en todas las regiones europeas. Las mayores concentraciones de localidades con presencia de O. eremita aparecen en Europa central (norte de Italia, Austria, República Checa, sur de Polonia y Alemania del este), en algunas partes del norte de Europa (sureste de Suecia, Latvia) y en Francia. En algunas regiones del noroeste de Europa, se ha extinguido o puede encontrarse de forma aislada (Noruega, Dinamarca, Países Bajos, Bélgica, noreste de Francia). Hay pocos datos del sureste europeo. Se prevén algunas extinciones locales de O. eremita en un futuro inmediato, especialmente en regiones con una pérdida y fragmentación del hábitat. O. eremita es una especie útil como indicador y paraguas para la preservación de toda la comunidad de invertebrados asociados a los agujeros de árboles en Europa. Un plan de preservación de O. eremita debería incluir tres aspectos que son de importancia general en la conservación de la naturaleza en Europa hoy en día: (1) preservación de los remanentes de bosques naturales con árboles viejos, (2) preservación y restauración de hábitats relacionados con los paisajes agrícolas tradicionales y (3) preservación de las "islas" de naturaleza que se mantienen en áreas urbanas. Palabras clave: Saprófito, Cavidad, Directiva de Hábitats, Desmoche, Bioindicadores, Scarabeoidea. (Received: 15 IX 03; Conditional acceptance: 17 XII 03; Final acceptance: 5 III 04) Thomas Ranius, Swedish Univ. of Agricultural Sciences, Dept. Entomology, P. O. Box 7044, SE–750 07 Uppsala, Sweden. E–mail: thomas.ranius@entom.slu.se.– Luís Oscar Aguado, Aptdo. 498, E–47001 Valladolid, Spain. E–mail: luisoscaraguado@wanadoo.es.– Kjell Antonsson, Environmental Dept., The County Administration Board of Östergötland, SE – 581 86 Linköping, Sweden. E–mail: kjell.antonsson@e.lst.se.– Paolo Audisio, Dipt. di Biologia Animale e dell’Uomo, Univ. of Rome "La Sapienza", viale dell’Università 32, I–00185 Rome, Italy. E–mail: paolo.audisio@uniroma1.it.– Alberto Ballerio, Viale Venezia 45, I–25123 Brescia, Italy. E–mail: alberto.ballerio.bs@numerica.it.– Giuseppe M. Carpaneto, Dipt. di Biologia, Univ. of Rome "Roma Tre", Viale G. Marconi 446, I–00146 Rome, Italy. E–mail: carpanet@uniroma3.it.– Karel Chobot, Agency for Nature Conservation and Landscape Protection of the Czech Republic, Kališnická 4–6, CZ–130 23 Praha 3, Czechia. E–mail: chobot@nature.cz.– Branimir Gjurašin, Croatian Natural History Museum, Demetrova 1, HR– 10000 Zagreb, Croatia. E–mail: Branimir.gjurasin@hpm.hr.– Oddvar Hanssen, Norwegian Inst. for Nature Research (NINA), Tungasletta 2, N–7485 Trondheim, Norway. E–mail: oddvar.hanssen@nina.no.– Hans Huijbregts, National Museum of Natural History Naturalis, P.O. Box 9517, 2300 RA Leiden, The Netherlands. E–mail: Huijbregts@naturalis.nnm.nl.– Ferenc Lakatos, Inst. of Forest and Wood Protection, Univ. of W– Hungary, School of Forestry, H–9400 Sopron, Bajcsy–Zs. u. 4., Hungary. E–mail: flakatos@emk.nyme.hu.– Ole Martin, Zoological Museum, Universitetsparken 15, DK–2100 Copenhagen Ø, Denmark. E–mail: oomartin@zmuc.ku.dk.– Zaharia Neculiseanu, or. Chisinau, str. Drumul Schinoasei 1/3, ap. 40, 2019 Moldova. E–mail: zneculiseanu@yahoo.com.– Nikolai B. Nikitsky, Zoological Museum of Moscow, Lomonosov State Univ., Bolshaya Nikitskaya 6, 125009 Moscow, Russia. E–mail: Nikitsky_NB@mtu–net.ru.– Wolfgang Paill, Ökoteam, Inst. for Faunistics and Animal Ecology, Bergmanngasse 22, A–8010 Graz, Austria. E–mail: oekoteam@sime.com.– Alja Pirnat, Centre for Scientific Research of the Slovenian Academy of Sciences and Arts, Inst. of Biology, Novi trg 2, SI–1000 Ljubljana, Slovenia. E–mail: alja@zrc–sazu.si.– Volodymyr Rizun, State Museum of Natural History NASU, 18, Teatralna Str., L’viv, 79008, Ukraine. E–mail: rizun@museum.lviv.net.– Adrian Ruicănescu, Inst. of Biological Research, Cluj–Napoca, 48 Republicii Str. RO–3400, Romania. E–mail: a_ruicanescu@yahoo.co.uk.– Jan Stegner, Vitzthumallee 20a, D–04509 Schönwölkau, Germany. E–mail: Osmoderma@eremit.net.– Ilmar Süda, Estonian Agricultural Univ., Forest Research Inst., F. R. Kreutzwaldi 5, 51014 Tartu, Estonia. E–mail: isyda@eau.ee.– Przemys»aw Szwałko, Museum of Natural History, Inst. of Systematics and Evolution of Animals, Polish Academy of Sciences, Sebastiana 9, PL 31–049 Kraków, Poland. E–mail: szwalko@muzeum.pan.krakow.pl.– Vytautas Tamutis, Plant Protection department, Lithuanian Univ. of Agriculture, Studentu 11 Akademija LT – 4324, Kaunas, Lithuania. E–mail: dromius@yahoo.com.– Dmitry Telnov, Coleopterology Section, The Entomological Society of Latvia, c/o: Fac. of Biology, 4, Kronvalda Blvd., LV–1586 Riga, Latvia. E–mail: telnov@parks.lv.– Vadim Tsinkevich, Dept. of Zoology, Belarus State Univ., F. Scorina Avenue, 4, 220050, Minsk, Belarus. E–mail: tsinkevichva@mail.ru.– Vincent Vignon, OGE – Office de Génie Ecologique, 5, Boulevard de Créteil – F–94100, Saint–Maur–des–Fossés, France. E–mail: v.vignon@oge.fr.– Veerle Versteirt, Royal Belgian Inst. of Natural Sciences, Dept. of Entomology, Vautierstraat 29, 1000 Brussel, Belgium. E–mail: Veerle.Versteirt@natuurwetenschappen.be.– Matthias Vögeli, Professur für Natur– und Landschaftsschutz, ETH Zürich, HG F 27.6, 8092 Zürich, Switzerland. E–mail: matthias@ebd.csic.es.– Peter Zach, Inst. of Forest Ecology, Slovak Academy of Sciences, Sturova 2, Zvolen, Slovakia. E–mail: zach@sav.savzv.sk. Corresponding author: T. Ranius, Swedish Univ. of Agricultural Sciences, Dept. Entomology, P.O. Box 7044, SE–750 07 Uppsala, Sweden. E–mail: thomas.ranius@entom.slu.se.

Animal Biodiversity and Conservation 28.1 (2005)

Introduction In temperate and Mediterranean regions of Europe, old trees are now scarce and many species dependent on this habitat seem to be confined to small remnants with no possibility for dispersal between the populations (e.g. Harding & Rose, 1986; Speight, 1989). This is because old–growth deciduous forests have declined to a very small proportion of their original extent (Hannah et al., 1995). Up until the nineteenth century, old trees were also widespread in pasture woodlands and wooded meadows, but abandoned management and changes of land use have severely reduced these habitats (e.g. Nilsson, 1997; Kirby & Watkins, 1998). When trees age, hollows with wood mould often form in the trunks. Wood mould is loose wood colonised by fungi, often with remains from bird nests and insects. Trunk hollows with wood mould harbour a specialised fauna mainly consisting of beetles, flies, mites, pseudoscorpions and ants. Many invertebrate species associated with hollow trees are threatened (e.g. Ehnström & Waldén, 1986; Warren & Key, 1991), and therefore the protection of this fauna should be an important goal for nature conservation in Europe. A strategy for nature conservation should be based on knowledge about which sites should be given priority. Which habitat types are most valuable for invertebrates living in tree hollows? How are these habitats distributed in Europe? As neither time, economical resources or taxonomic expertise are available to carry out detailed surveys of saproxylic invertebrates throughout Europe, we need to find surrogates that provide clues about the conservation values but are easier to survey. One possibility is to measure the amount of habitat (in this case, large or hollow trees), while another is to survey indicator species. Surveys of old trees have been conducted with different protocols in Britain (e.g. Clifton, 2000) and Sweden (e.g. Hultengren & Nitare, 1999; Ranius et al., 2001). Lists with saproxylic insects that may be used as indicators have been compiled by Speight (1989), Rundlöf & Nilsson (1995) and Nilsson et al. (2001). One weak point with these surrogates is that they have usually been developed based on personal experience from a restricted region; the lists of indicator species and suggested methods to survey old trees are adopted to the researcher’s study area, and do not necessarily suit the whole of Europe. Another problem is that to count all hollow and large trees (as in Ranius et al., 2001) or to survey presence or absence of tens of saproxylic insect species (as in Rundlöf & Nilsson, 1995; Nilsson et al., 2001) is expensive and time– consuming. It will therefore take a long time until there are sufficient data of this kind to allow comparisons between different parts of Europe. A simple measure of conservation values could be achieved by collecting data about the presence of a single species. One beetle species, Osmoderma eremita (Scopoli, 1763; Coleoptera: Cetoniidae), has been more studied in ecological research than any

other invertebrate species associated with tree hollows (see Ranius, 2002b, for a review). This species has a high priority according to the European Union’s Habitats Directive (Luce, 1996), and has therefore been surveyed in many countries in recent years. It is also listed by the Bern convention. A study in south–eastern Sweden showed that in sites with tree hollows, those with O. eremita present have a higher species richness of other threatened beetle species associated with tree hollows (Ranius, 2002a). The fact that this species is easy to survey also improves its suitability as an indicator species (Ranius & Jansson, 2002). In this paper we compile data on the occurrence of O. eremita in Europe. It is written by 28 co–authors each responsible for one or more European countries. Information has been compiled from museums and private collections, literature and field surveys. The paper is based on a private initiative, based on the belief that entomology and nature conservation would do better with stronger co–operation between conservationists from all European countries. Taxonomy Osmoderma species occur in northern America, Europe, Turkey, south–eastern Siberia, north–eastern China, Korea and Japan (Shaffrath, 2003a). Taxonomists’s opinions differ about the forms of Osmoderma in Europe. According to Tauzin (1994a, 1994b, 1996, 2002), there are two Osmoderma species in Europe: O. eremita (Scopoli) in Western Europe and O. lassallei Baraud & Tauzin in Eastern Europe. Sparacio (1994) described a third species, O. cristinae, endemic for Sicily. Later, Krell (1996) treated these three European forms of Osmoderma as different subspecies of O. eremita. However, in a recent review of the European Osmoderma, Sparacio (2001) considered again both O. lassallei and O. cristinae as distinct species, and described a fourth possible separate species of this complex, O. italica (recently emended O. italicum by Audisio et al., 2003), considered endemic to the southern mainland of Italy. A new, but partly questionable, nomenclatorial and taxonomic scenario of the European Osmaderma was finally recently introduced by Gusakov (2002). An ongoing genetic study by P. Audisio and coll., based on comparison of mtDNA genes sequences, will probably provide greater insight in the taxonomy of the species complex. For simplicity, in this paper we do not distinguish between Osmoderma forms, but provisionally apply the name O. eremita to all Osmoderma in Europe. Life history Normally, the adults of O. eremita are found from July to September, but in some regions (Germany, Slovenia and Italy) there have been several observations in June and even a few in April and May (Stegner, 2002; Schaffrath, 2003a; P. Audisio, pers. obs.; G. Carpaneto, pers. obs.; A. Pirnat, pers. obs.).

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The adults normally die in autumn; nevertheless, a hibernating adult female has once been found in January in the forest of Fontainebleau, France (Tauzin, 1994b). When rearing the species in the laboratory, Tauzin (1994b) observed adult males to have a lifetime of 10–20 days, while females lived for more than 90 days. Schaffrath (2003a) fed isolated males which reached lifetimes of 90 days. In a field study in Sweden, males and females seemed to have the same life–time, with a maximum of about one month (Ranius, 2001). During a research project conducted over several years in Sweden, O. eremita was only found active at daytime (T. Ranius, pers. obs.), while in Russia, active adults have also been observed at dusk and night time (N. Nikitsky, pers. obs.) and in Germany and France at dawn (Schaffrath, 2003a; Stegner, 2002). Flying individuals have mainly been seen in the early afternoon on warm, sunny days. According to Luce (1996), O. eremita females lay 20–80 eggs. When Jönsson (2003) reared the beetle in the laboratory, he searched for larvae one–two months after the eggs were laid, and found 12– 18 larvae produced by each female. Egg incubation lasts 14–20 days: initially the eggs are dull white, they then become yellowish and redouble their size, up to a diameter of 5 mm. First instar larvae have a length of 6 mm, but at complete development they can reach 60 mm and have a weight of more than 12 g (Schaffrath, 2003a). Before metamorphosis, the larvae construct an oval cocoon made of their excrements and wood mould (Tauzin, 1994b). From laboratory studies, we know that cocoons are made in autumn (September), but metamorphosis takes place in the following spring (May–June) (Tauzin, 1994b). However, in Italy, D. Baratelli (pers. comm.) observed that two larvae found in February developed into adults in April and May of the same year. In laboratory and field studies in Poland, Pawłowski (1961) found the generation time to be three or four years. The larval feeding period was between 65 and 93 weeks. Feeding activity took place when the average daily temperature exceeded 13°C, which means that in Poland the larvae are active about 30 weeks per year. Developing time and hibernation depend on the temperature of the wood mould, which varies between years and localities. In Germany, Russia and Latvia, the development time in the field is also usually either three or four years (Nikitsky et al., 1996; Schaffrath, 2003a; D. Telnov, pers. obs.). The population size varies widely between trees (Ranius, 2001). In an area in southeastern Sweden there were, on average, 11 adult beetles per hollow oak and year (Ranius, 2001), and a similar population size per tree has been reported from Hallands Väderö, southwestern Sweden (Jönsson, 2003). At both these sites, there were almost 100 adult beetles per year in some trees. Circumstantial records suggest that the population size per tree is of the same magnitude in other parts of Europe. For instance, in chestnut and willow trees in Lovero Valtellino (Lombardia, Italy) normally 5 to 30, but

sometimes more, individuals per tree were observed (P. Audisio, pers. obs.). Also in Latvia, oaks and lime trees have been found harbouring populations of the same magnitude (D. Telnov & F. Savich, pers. obs.). Schaffrath (2003b) counted the larvae and cocoons in three oaks and one beech in Germany and found 30–120 individuals, which implied that there was about one larva per litre of wood mould. In France, Prunier (1999) counted the larvae in the trunk of an old oak from 1 to 7 m from the ground and found more than 150 larvae. Males of O. eremita emit a characteristic odour that French entomologists have called "odeur de prune" (= odour of plums) or "odeur de cuir de Russie" (= odour of Russian hide) (Tauzin, 1994b). German entomologists have called the beetle "Aprikosenkäfer" because it smells like apricots (Eisenach, 1883), even though "Eremit" and "Juchtenkäfer" (from Juchtenleder = Russian hide) are more commonly used names. The odour can be perceived by humans several metres from the beetle. Chemical analyses have revealed that the males emit the same compound (a decalactone) that is emitted by apricots and plums, and that the compound works as a pheromone that attracts female O. eremita (Larsson et al., 2003). Only on a few occasions have O. eremita adults been seen feeding. In Croatia, B. Gjurašin has collected O. eremita adults on flowers (Leucanthemum sp. and Viburnum sp.) on two occasions, and in Spain, there has been a sighting on flowers of Sambucus nigra (L. O. Aguado, pers. obs.). From Germany, M. Bahn (Schnitter in litt.) has reported two specimens from umbelliferous plants. Schaffrath (2003a) has collected a few reports of observations from flowers and sap flows. In Poland, Russia and Estonia, the beetle has been observed feeding on sap flows (Tenenbaum, 1913; Pawłowski, 1961; N. Nikitsky, pers. comm.; I. Süda, pers. obs.). Entomologists frequently search this source for insects although only a few O. eremita individuals have been encountered, suggesting that O. eremita visit these habitats only rarely. P. Szwałko (unpublished data) has once observed a female O. eremita feeding on a ripe yellow plum (Prunus sp.). In the laboratory, Schaffrath (2003b) has found that adult beetles feed on bananas and apples. Habitat requirements Most findings of O. eremita have been made in hollow but still living, standing trees. The beetle has also been found in dead, standing trees, but probably such trees are often unsuitable because they are too dry. On some occasions (for instance, we know one tree in Sweden, one in Poland, three in Latvia and one in Estonia), living adults or larvae have been found in downed tree trunks. A few times, the species have been found in old stubs (Latvia: D. Telnov, pers. obs.; Russia: N. Nikitsky, pers. obs.; Germany: Stegner, 2002). At many localities, hollows suitable for O. eremita occur only in very large trees, but at other sites the species

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has also been found at relatively thin, slow–growing trees. For instance, the species has been found in Sweden in a hollow oak (Q. robur), growing on a hill, with a diameter of 22 cm (Ranius & Nilsson, 1997), in central Italy in a beech (Fagus sylvatica) with a diameter of 25 cm (P. Audisio, pers. obs.), and in Germany in a hornbeam (Carpinus betulus) of 25 cm diameter (J. Stegner, pers. obs.). We believe that most oak trees with the beetle present are 150–400 years, while trees of rapid–growing species may often harbour O. eremita when they are younger; poplars (Populus spp.) and willow trees (Salix spp.) may harbour O. eremita when they are only a few decades old (Schaffrath, 2003a). The beetle inhabits fruit trees that are 80–100 years old (Stegner, 2002). Pollarded oaks in France harbour O. eremita when they are only 70–140 years (V. Vignon, pers. obs.). Also in Latvia, the species has been found in many seemingly younger oaks, especially in urban habitats (D. Telnov, pers. obs.). The species mainly inhabits trunk hollows containing large amounts of wood mould. This has been shown in studies in pasture oaklands in Sweden (Ranius, 2000; Hedin & Mellbrand, 2003). Observations from chestnuts, willows and oaks in Italy confirm this (P. Audisio, pers. obs.). Also Luce (1995) found that hollows of an intermediate to large size were used by O. eremita to a higher extent than smaller hollows. Moreover, the body size of the adult beetles has been found to be larger in trees with more wood mould (Hedin & Smith, 2003). O. eremita inhabits trees with entrance holes situated a few (2–5) metres from the ground more frequently than those with holes near the ground (Hedin & Mellbrand, 2003). However, the beetle occurs over a wide range of heights; it has been found in several tree hollows situated 15–25 m from the ground (V. Vignon, P. Orabi & J.–M. Luce, pers. obs.) but on some occasions also at or even below the ground level (Prunier, 1999; V. Vignon, pers. obs.). The larvae usually dig between the wood mould and the internal wall of the trunk hollow (Palm, 1959; Pawłowski, 1961; D. Baratelli, pers. comm.). There, they eat the wall and increase the tree hollow and the amount of wood mould. Often the frass from O. eremita larvae is a dominating part of the tree hollow content. In this way O. eremita may improve the habitat for other species living in tree hollows (Ranius, 2002a). Elater ferrugineus L. and other click beetles, Tenebrio spp. and alleculids such as Prionychus spp. are beetle species that often occur together with O. eremita [reported from France (Brustel , 2001), Denmark (Martin, 1993), Germany (Schaffrath, 2003b), Poland (Pawłowski, 1961) and Sweden (Ranius, 2002a)]. The most important predator on O. eremita larvae is probably the larvae of the click beetle Elater ferrugineus (Schaffrath, 2003b). Other enemies are less known. Vertebrates predating on O. eremita have only occasionally been reported. However, in Kozienice Forest (central Poland), several adults

of O. eremita have been preys of the roller Coracias garrulus L. (Rębiś, 1998). Mites and nematodes are other possible enemies, which so far have only beeen described anecdotally. Larvae infested by mites (deutonymphs of Gamasina), collected in winter (southern Poland) in a hollow stump of alder, died in the laboratory during the following summer killed by these mites (Szwałko, pers. obs.). There is one record of larvae infested by a nematod (Martin, 1993). Protaetia lugubris (Herbst) is a Scarabaeid beetle that seems to have similar habitat requirements as O. eremita (Luce, 1995), and therefore it has been suggested that they may be competitors (Ranius, 2002c). Tree species Oak (Quercus spp.) is the most important tree for O. eremita, followed by lime trees (Tilia spp.), willows (Salix spp.), beech (Fagus sylvatica) and fruit trees (Prunus spp., Pyrus spp, Malus spp.) (fig. 1). In many regions, ash (Fraxinus spp.), elm (Ulmus spp.), chestnut tree (Castanea sativa), aspen and poplars (Populus spp.), birch (Betula spp.) and maple (Acer platanoides) are also important host trees. Mulberry trees (Morus spp.), common alder (Alnus glutinosa), plane trees (Platanus spp.) walnut trees (Juglans regia) and hornbeam (Carpinus betulus) are other tree species which the beetle has been found in. Findings from needle trees are more rare; however, the species has been found in silver fir (Abies spp.) in Greece and Denmark, in yew trees (Taxus baccata) of France (Caillol, 1913 in Tauzin, 1994b), and in Scots pine (Pinus sylvestris) in Slovakia and Poland. The species has been found in exotic tree species such as false acacia (Robinia pseudoacacia) (for instance, in France, Germany, Italy and Austria), Japanese honeysuckle (Lonicera nipponica) (Janssens, 1960), silver maple (Acer saccharinum) (in Germany: Stegner, 2002) and horse chestnut (Aesculus hippocastanum) (in Denmark, Sweden, Poland and Austria). Most localities today occur on land that has been used by man for a long time. Only in some regions, such as Spain, southern Italy and the Balkans, more or less natural forests are reported to be the major habitat of O. eremita. Perhaps the beetle is to a higher extent associated with man–made, more open habitats in Northern Europe (even though the beetle may occur in shaded situations also in Scandinavia), but occurs in denser forests further south. This could be a compensation for the climate (cf. Thomas, 1993); in regions with colder climate the species tends to avoid the most shaded situations (Ranius & Nilsson, 1997), while in regions with warm and dry climate, free–standing trees perhaps tend to be too dry. However, it is difficult to achieve hard evidence for this hypothesis. In Scandinavia, pasture woodlands and deer parks with broadleaved trees are the most important habitat. Also in Germany, the largest O. eremita localities are on land that has been used for grazing or hunting (Schaffrath, 2003b).

Ranius et al.

The species inhabits urban habitats such as parks and alleys. For instance in Banska Bystrica (Franc, 1997), Strasbourg, Rome, Florence, Dresden, Leipzig, Salzburg, and Kaunas, O. eremita occurs in the city centres. In several regions, such as Hungary, Slovakia, some parts of Russia and south–eastern Germany, the O. eremita localities are concentrated to floodplain areas, where the habitat may be forests or smaller woods in agricultural land. Old orchards may be important habitats, especially in central Europe (e.g. Eastern Germany, Austria and Slovenia). In some regions, the beetle mainly uses pollarded trees. Pollarding implies that tree branches are repeatedly cut in order to increase the productivity of wickers, poles and fuel–wood. In parts of France, there are extensive networks of hedgerows where O. eremita inhabits pollarded oaks. In the intensively cultivated Po river basin of northern Italy, pollarded willows along riversides are the most important habitat for O. eremita. Abandoned practice of pollarding constitutes a threat to O. eremita in these areas. Metapopulation ecology In a study in Sweden, the occupancy rate of O. eremita per tree was positively correlated with the number of hollow trees per stand (Ranius, 2000; fig. 2). The positive correlation is consistent with what metapopulation ecologists refer to as Levin’s rule (Hanski & Gilpin, 1997). Ecological studies of O. eremita support the view that each tree possibly sustains a local population and that the populations in stands together form a metapopulation (Ranius, 2002b). For instance, the species has been found to have a restricted dispersal (Ranius & Hedin, 2001; Hedin et al., 2003), and the population fluctuations in individual trees take place asynchronously (Ranius, 2001). A survey of an area in southeastern Sweden revealed that O. eremita still occurs in almost all larger stands, but the occupancy pattern did not indicate any connectivity between stands (Ranius, 2000). This could be because the density of hollow oaks historically has been much higher than today. Over the last two centuries, old oaks have severely declined in Sweden (Eliasson & Nilsson, 2002; Hedin, 2003). Thus, most hollow tree stands were probably colonized by O. eremita long ago and, lately, the beetle has been confined to small stands without connectivity. In the area surveyed in southeastern Sweden, O. eremita was systematically absent from single trees and very small stands, probably because of extinctions from these stands (Ranius, 2002c). This is consistent with the underlying reasoning of the minimum viable metapopulation size (MVM) concept (Hanski et al., 1996). MVM is an estimate of the minimum number of interacting local populations (in this case hollow trees inhabited by O. eremita) that is necessary for long–term survival of a metapopulation. Computer simulations of O.

eremita show that its metapopulation dynamics are slow, in the sense that it may take centuries from the decrease of the number of hollow trees until the small O. eremita population finally become extinct (Ranius & Hedin, 2004). Therefore, in many smaller stands which still harbour a population today, we should not expect O. eremita to be able to survive in the long run (Ranius & Hedin, 2004). Survey methods As O. eremita rarely leave the tree hollows, the species must be actively searched for. Where no surveys targeting O. eremita have been conducted, we should expect that many localities with O. eremita remain unknown. The most efficient methods to survey O. eremita are pitfall trapping (Ranius, 2001; fig. 3) and searching for larvae (Martin, 2002) or remains of adult beetles and excrements in the wood mould (Ranius & Jansson, 2002). Pitfall trapping is carried out during late summer (July–August), when the adults are active. If the traps are emptied at least every second day and the beetles are released, the method is not destructive. By marking, releasing and recapturing the adults, population sizes may be calculated (Ranius, 2001). Martin (2002) has searched for larvae in the wood mould. This is preferably done in late autumn when the larvae occur higher up in the wood mould and are easier to find than at other times of the year. Ranius & Jansson (2002) have searched for remains (pronotum, elytra and heads) of adult beetles and excrements from larvae in a certain amount of wood mould from each tree. In Eastern Germany, excrements have been searched for at trunk–bases and many new occurences were found in this way (Stegner, 2002). Several Scarabaeid species have similar excrements, however, the shape and size make it possible to determine O. eremita excrements (Stegner, 2002). These methods can be used throughout the year and are appropriate when large areas should be systematically surveyed. As excrements and remains of adults may persist for many years, their presence does not ascertain that there is presently a living population in the tree. For this reason it is useful to combine the methods with pitfall trapping: first excrements and remains of beetles are searched for, and then pitfall traps are set only in those trees where excrements or remains of beetles have been found. This is a much more efficient way to search for localities with living adults in comparison to solely using pitfall traps. Another method to record the presence of the species is to smell for the unmistakable scent of the species. This should be done in July or August, on warm days or afternoons. It is usually necessary to be very near the entrance hole, but sometimes it is possible to smell the beetles from a distance of up to tens of metres. Window trapping is not an appropriate method to survey O. eremita (Ranius & Jansson, 2002). Hand–collecting of adult beetles is possible, but

Jan Stegner

Jens Johannesson

Vincent Vignon

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Fig. 1. Typical trees harbouring Osmoderma eremita for different parts of Europe: A. Pollarded oaks in hedgerows in western France; B. Oaks in a historical pond–region in Eastern Germany; C. Pastured oak–land in southern Sweden; D. Beech forest in Germany, the tree harboured O. eremita before it was storm–felled; E. An alley with willow trees in a park in Germany. Fig. 1. Árboles típicos que cobijan a Osmoderma eremita de distintas partes de Europa: A. Robles desmochados en zonas de setos en el oeste de Francia; B. Robles en una región con charcas de Alemania del Este; C. Tierras de pastoreo con robles en el sur de Suecia; D. Hayedo de Alemania, el árbol cobijaba a O. eremita antes de que fuera cortado por una tormenta; E. Un paseo con sauces en un parque de Alemania.

because the beetles rarely leave the tree hollows, it is not very efficient. O. eremita does not seem to be attracted by baits such as red wine and molasses, normally used for cetonid beetles. Known localities with O. eremita may be monitored, either by studying the beetle population

itself or by studying its habitat. The beetle population may be monitored by pitfall trapping. The field work must be done at the correct period (which differs between years), pitfall traps must be set in a sufficiently number of trees, and the data must be statistically analysed (Ranius,

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2001). The habitat may be monitored by revisiting the localities, checking that the inhabited trees are alive and not suffering from competition of neighbouring trees or any other threat. This is much cheaper than monitoring the beetle population, and may generate advice about which management measures are needed. The potential to get new hollow trees in the future should also be evaluated and planned for. Both these kinds of monitoring may be conducted, for instance, every five years. Occurrence in individual countries The occurrence of O. eremita in each country where it occurs (fig. 4) is described below. Lists with localities (those mapped in the figures) are given in the Appendix. Updated information about projects dealing with O. eremita are available at the web site www.eremit.net.

Albania (fig. 5) Most records are from the northern part of Albania. The only information obtained regarding host tree concerns an adult found in Tamara on a beech (Fagus sylvatica) (W. Schwienbacher, pers. com.). The species has been found both in lowland (Shkodër) and mountain areas (Maja e Ragamit, Maja e Poliçanit).

(Pyrus spp.) orchards seem to be important habitats in some areas. Occasionally O. eremita has been reported from introduced tree species such as horse chestnut (Aesculus hippocastanum), black poplar (Populus nigra var. pyramidalis) and false acacia (Robinia pseudoacacia). Our present knowledge on the distribution of O. eremita is mainly due to coincidential collecting. Reports for many localities are old and the species may have become extinct due to habitat loss.

Belarus (fig. 7) O. eremita is a rare, local species in Belarus, and is included in the Red Data Book (Lapitsin, 1993). In total, O. eremita has been found at 14 localities (Arnol’d, 1902; Alexandrovich & Pisanenko, 1991; Alexandrovich et al., 1996; Rubchenya & Tsinkevich, 1999; Solodovnikov, 1999; Lukashenya et al., 2001). All findings are from old forests or parks, mainly in lime tree (Tilia spp.), oak (Quercus spp.), elm (Ulmus glabra) and ash (Fraxinus excelsior), but also aspen (Populus tremula) and poplar (Populus spp.). During the last few years, several new localities with O. eremita have been discovered. One locality is the park of Priluki in the Minsk district. This is an ancient park with old lime, ash and oak trees. There are many similar parks in Belarus where O. eremita would possibly be found if the species was surveyed.

Belgium (fig. 8) Austria (fig. 6) O. eremita is regarded as a highly endangered species (Franz & Zelenka, 1994). However, it has been recorded from more than one hundred localities dispersed over a wide part of Austria. The distribution has its centre on the thermically advantaged Eastern Lowland and extends to the inner–alpine Low Mountain Range, 800–1,000 m a.s.l. Previously, the species was found in wood and parkland landscapes managed with a low intensity, but today the species is restricted to old fruit plantations, trees along paths and streams, and at estates and animal parks with protected woodland. Some of the localities are large and only managed with a low intensity by humans. The inhabiting O. eremita populations therefore probably have a low extinction risk here. Such localities are the parks of Laxenburg (B. Dries & J. Roppel, pers. comm.) and Purgstall (F. Ressl, pers. comm.) in Lower Austria, the Lainzer Tiergarten in Vienna (Zabransky, 1998), and the old fruit plantations in the smallholdings in Upper Austria and in the western parts of Styria (Kreissl, 1974; Mitter, 2001). Oak (Quercus spp.), willow (Salix spp.) and lime trees (Tilia spp.) are the most important tree species, whereas beech (Fagus sylvatica), ash (Fraxinus excelsior), elm (Ulmus glabra) and birch (Betula spp.) are more rarely used. Apple (Malus spp.) and pear

The last confirmed record of O. eremita in Belgium dates back to 1944, and the species has therefore been regarded as regionally extinct. However, a recent record has been reported from the valley of "la Berwinne" (near Visé). O. eremita has been recorded from 15 localities in three different provinces: Brabant (central Belgium), Limburg (eastern Belgium) and Luik (southeastern Belgium). It has been found in old trees in woodlands (mainly oak (Quercus robur)), river–sides, pastures (mainly willows (Salix spp.)), and orchards (apple (Malus domestica), cherry, prune (Prunus spp.) and pear trees (Pyrus spp.) (Janssens, 1960). O. eremita in Belgium is classified as endangered and is protected. Belgium has a long history of forest fragmentation and remaining forests have been intensively managed, with a huge impact on fauna and flora (described by Desender et al., 1999). Especially in the northern part of Belgium (Flanders), forests have totally disappeared (e.g. Tack & Hermy, 1998), while in Wallonia, natural forests have been converted to intensively managed tree plantations. Old trees have been removed, and are still being removed, not only from forests but also from agricultural areas. As a result, the chance for beetles dependent on tree hollows to persist has severely decreased. No survey specifically targeting O. eremita or any other saproxylic insects has been conducted during the last few decades other than two recent surveys

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Presence / tree (%)

100 80 60 40 20 0 1–3

4–6 7–10 11–61 Stand size

Fig. 2. Frequency of occurrence / tree of the beetle Osmoderma eremita in relation to stand size in localities in the province of Östergötland (from Ranius 2002a, n = 155), southeastern Sweden. Stand size is defined as the number of hollow oaks within a cluster with a distance of < 250 m from one hollow oak to another. Fig. 2. Frecuencia de presencia / árbol del escarabajo Osmoderma eremita en relación con el tamaño de la parcela en localidades de la provincia de Östergötland (de Ranius 2002a, n = 155), sureste de Suecia. El tamaño de la parcela se define como el número de huecos en robles dentro de un grupo con una distancia de < 250 m de un hueco a otro.

Fig. 3. Osmoderma eremita and a pitfall trap. The trap consists of a jar placed inside a hollow oak with the opening on the level with the wood mould surface. Fig. 3. Osmoderma eremita y una trampa. La trampa consiste en un recipiente situado dentro del hueco del roble con la abertura a nivel de la superficie de la madera desmenuzada.

know the habitat only for two single specimens: one has been flying in an orchard (M. Mazur, pers. comm.) and another collected in "xerothermic scrub" (E. Migliaccio, pers. comm.).

Croatia (fig. 9) of saproxylic beetles in a few forests (Versteirt et al., 2000; Heirbaut et al., 2002). Old localities where the species has been found have not been revisited for the study of O. eremita.

Bosnia and Herzegovina (fig. 9) There are old records of O. eremita from a wide range of Bosnia–Herzegovina. The altitudinal range is from 50 (Mostar) to 1,350 m a.s.l. (Igman and Treskavica). Localities with the species present are almost certainly still widespread throughout the country. However, owing to the civil war, it seems no surveys have been conducted over the last few years.

Bulgaria (fig. 5) In Bulgaria, O. eremita has been recorded from the large mountain area of Stara Planina (which extends in the centre of the country from W to E), from the southwestern mountains (Rila and Pirin Mts.) and from the Black Sea coast. Nüssler (1986) has reported the species from locality 1,400 m a.s.l. We

In Croatia, O. eremita has a broad range, but is rare. There are records from 31 localities, made between 1892 and 2000. O. eremita is not a protected species but some localities with O. eremita are protected areas (such as Mt. Velebit, Mt. Učka, Mt. Papuk, Mt. Medvednica, Žumberak and Plitvice). No surveys focusing on O. eremita have ever been conducted in Croatia.

Czechia (fig. 6) O. eremita is local and rare in the Czech republic; in the Red Data Book of the Czech and Slovak Republics it is regarded as endangered (Škapec, 1992). Most of the O. eremita localities are situated in southern and eastern Bohemia and most– southern and north–eastern Moravia, but there are a few localities also in other parts of Czechia. Numerous suitable habitats have been lost during the last fifty years. Nevertheless, some habitats, for instance, parks near castles and alleys, have been preserved as isolated fragments with local O. eremita populations still present. Some O. eremita populations inhabit preserved lowland

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forests with large broadleaved trees, especially in southern Moravia. Many populations seem to be small and isolated, so the risk of local extinctions in many cases is probably high. Another endangering factor in Czechia is the ongoing removal of "unhealthy" hollow trees, especially in anthropogenic habitats which host the majority of the O. eremita populations. Most findings have been made in oak (Quercus spp.), elm (Ulmus spp.), lime (Tilia spp.), willow (Salix spp.) and fruit trees (Balthasar, 1956). According to Kollar (2000), the localities in Czechia are mainly in the lowland (up to 500 m, rarely 600 m a.s.l.). The distribution of O. eremita is relatively well known, with over 500 findings from about 200 localities. This is due to a high number of entomologists in the Czech Republic; the species has never been systematically surveyed. The first published survey of distribution of O. eremita in Czechia was a grid map by Jelínek (1992). More recently, Kollar (2000) summarized O. eremita records. During the last two years, mapping has been conducted within the scope of NATURA 2000. A more detailed survey is in preparation by K. Chobot.

Denmark (fig. 10) O. eremita is rare in Denmark, and has only been found on Eastern Jutland (Jylland) and the islands Zealand (Sjælland), Lolland, and Falster (Martin, 2000). It seems to have become rarer in Zealand over the last 100 years, and has probably disappeared from Jutland, whereas its presence in several localities on Lolland have been discovered during the last few decades. There are records from 28 localities. However, when these were recently revisited, the species were only found in 9 of them, even though hollow trees are still present at all localities. O. eremita was searched for in every tree whenever possible. However, some entrance holes were too small or situated too high to reach by ladder. At the largest locality (Bognæs Storskov, Zealand) O. eremita was found in 16 trees, while at the other localities the species was found in 2– 10 trees. This means that the survival of the O. eremita in Denmark is uncertain in the very near future as the populations are small and very isolated. The species has been found breeding in several different deciduous trees, and once also in a conifer tree: silver fir (Abies alba). The most important habitat is privately–owned deer parks or forests situated near old estates and manors. There, the species occurs mainly in oak (Quercus robur) beech (Fagus sylvatica), and ash (Fraxinus excelsior). Outside the forests, it has especially been found in avenue trees: lime (Tilia cordata), elm (Ulmus glabra) and horse chestnut (Aesculus hippocastanum). Specimens from 28 localities were registered, when museums and private collection were re-

viewed in 1990–1991. These 28 localities were surveyed, and living specimens were found at 10 localities (Martin, 1993). When these ten localities were inventoried in 1999 (Martin, 2002), O. eremita was found in 61 hollow trees (46 oaks (Quercus robur), 10 beeches (F. sylvatica), 3 horse chestnuts (A. hippocastanum) and 2 ashes (F. excelsior)). Of these trees, 49 were alive, although several later fell during a hurricane in December 1999.

Estonia (fig. 11) Until recent years, O. eremita was known in Estonia only from an undated record from Tartu, probably originating from the 19th century. In 1995, the species was found in an oak in a wooded meadow in Koiva woodland in southern Estonia. The beetles have since been found there repeatedly, once feeding on a flow of oak sap. A cocoon including remains of an adult has also been found in a hollow maple (Acer platanoides) stub in an avenue at Koikküla, a village situated nearby (Süda, 1998, 2003). Starting in 1999, the Estonian Seminatural Community Conservation Association performed so– called bush clearing in the woodland. The aesthetic aspect was over–emphasized in the work and a large amount of dead or broken trees were burnt or removed, including large oak trees (Süda, 2003). Despite this, O. eremita is still present at woodlands along the Koiva river, although the number of suitable trees is small. The existing population and possible new populations were searched for in 2000–2002 within the Estonian NATURA 2000 program. Despite the extensive search, no new records of O. eremita were recorded, although suitable habitats can be found at other places in Estonia, e.g. on Saaremaa Island.

Finland (fig. 11) O. eremita is only known from one locality in Finland: the island of Ruissalo (Runsala) in Turku. This is however a large locality; in an area of about 5 x 2 km, living specimens have been found in 117 trees, remains from adults occurred in 62 trees, and excrements were found in another 155 trees (Landvik, 2000).

France (fig. 8) In France, more than 300 localities with O. eremita are known. Thus, O. eremita is widely distributed in France, but most existing sites are relatively remote from each other, leaving wide empty spaces, particularly in forest regions. The species seems to have decreased severely, especially in the northern part of the country. In the southern part of France, there are probably still many localities that have not been discovered (J.–M. Luce, pers. comm.).

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Fig. 4. Distribution of Osmoderma eremita in Europe: {. Last record before 1950, or the time unknown; . Last record 1950–1989; z. Last record in 1990 or later. Larger circles represent records in German federal states where we do not have data for the individual localities. Fig. 4. Distribución de Osmoderma eremita en Europa: {. Último registro anterior a 1950, o fecha desconocida; . Último registro entre 1950 y 1989; z. Último registro de 1990 o posterior. Los círculos más grandes representan registros en Alemania Federal de donde no disponemos de datos de localidades por separado.

Most of the localities are not in forests but in agricultural landscapes. Forests with O. eremita are normally only small localities situated far (often more than 100 km) from each other. These forests have a different history, for instance: (1) old forests planted by Colbert in the 17th century in the Forest of Bercé (Sarthe Department) and in the Forest of Tronçais (Allier Department); (2) forests conserved by the Barbizon School of Painters in the Fontainebleau forest during the 19th century; (3) ancient castle parks (such as Forest of Compiègne in the Oise Department); (4) very old urban parks with old trees (for instance, Strasbourg and Mulhouse); (5) forests that have been grazed by cattle, for instance the Forest of Massane (Pyrénées Orientales) (Garrigue & Magdalou, 2000) and the Forest of Sare (Pyrénées Atlantiques) (Van Meer, 1999); and (6) religious sites, such as the beech grove on the pilgrim site of the Sainte–Baume (Var Department) in the Provence region. In contrast with these isolated forest habitats, there are often many more hollow trees in hedge-

row networks where O. eremita exists. There, the species mainly inhabit old, pollarded oaks. Examples of such networks are, for instance: (1) in the north of the Aveyron Department in an area of more than 500 km²; (2) in Bourbonnais in the Allier and Cher Departments in an area about 2,000 km²; and (3) in the west part of France in an area about 30,000 km², in the Ille–and–Vilaine, Indre–and–Loire, Loire–Atlantique, Maine–and– Loire, Morbihan, Mayenne, Orme and Sarthe Departments (Vignon & Orabi, 2003a, 2003b). Before land consolidation (in the sixties), O. eremita occurred probably continuously in landscapes with hedgerow networks. Today, the hedgerow networks have become more fragmented. Oak is the most important tree species, followed by chestnut (Castanea sativa), ash (Fraxinus excelsior) and beech (Fagus sylvatica). O. eremita has also been found in common alder (Alnus glutinosa), birch (Betula spp.) (Prunier 1999), wild cherry (Prunus avium), poplar (Populus spp.), apple (Malus spp.) [rather fre-

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quently in the Orne Department, (J.–F. Asmodé & V. Vignon, pers. obs.)], willow (Salix spp.) and plane tree (Platanus hybrida) (especially in towns). In the Mediterranean beech grove of Sainte–Baume, O. eremita has also been found in yew trees (Taxus baccata). A pollarded oak grows relatively fast; a tree with a diameter of 50 cm is normally between 70 to 120 years old (Brin, 1999), and such a tree may harbour O. eremita. Pollarded trees over 300 years old are very rare, and trees over 140 years seem to die relatively fast. Very old, dying trees are normally cut down to be used as firewood, partly for aesthetic reasons. Only a few sites have been subject to detailed surveys of hollow trees and O. eremita. When trees were mapped in the forest of Massanne, there were on average 60 hollow trees per hectare. The occupancy rate of O. eremita was about 6% (Garrigue & Magdalou, 2000). Two hedgerow network regions in the western part of France, that may form the largest locality for O. eremita in France, have also been surveyed. In an 8,500 hectares site in the Sarthe Department, one hollow tree per hectare was found. Even in this fragmented site, O. eremita was present. In the Orne Department, a hedgerow network was found to have 5 hollow trees per hectare in an area of 5,000 hectares. The highest density observed in hedgerow networks is 10 hollow trees per hectare in 200 hectares which have never been subjected to land consolidation (J.–F. Asmodé & V. Vignon, pers. obs.). O. eremita occurs in 2 to 20 % of the hollow trees in different parts of the hedgerow network in the Sarthe and Orne Departments (J.–F. Asmodé & V. Vignon, pers. obs.). A higher occupancy rate, 26%, has been observed in a hedgerow network in the Aveyron Department (Brustel, pers. comm.). The low occupancy rate in the hedgerow networks implies that there is a long distance between trees harbouring O. eremita. Therefore, the habitat fragmentation is at many places probably too high for long–term survival of the species. We assume that in more than 80% of the localities where O. eremita is present today, there is a substantial risk of extinction within 50 to 100 years. A study of a Carabid beetle in a hedgerow network indicated that its current distribution was better correlated with characteristics of the landscape 50 years ago than the present situation (Petit & Burel, 1998). Perhaps the situation is similar in O. eremita, and in which case we should expect local extinctions in the future due to the habitat destruction over the last few decades. At many sites, there are no younger trees to take over the role as hollow trees in the future. As it will take a long time before new hollow trees are generated, survival of insects in hollow trees is possible only as long as the present old trees are preserved. The hedgerow networks, which constitute the most important habitat for O. eremita, have been subject to severe fragmentation since the 1960's. The decrease in numbers of hollow trees is not

only due to the reduction of hedgerows, but also to the lower density of trees in the hedgerows. Today, the hollow trees are very old, and renewal of the habitat is difficult. The traditional practice of pollarding trees has been abandoned because it no longer serves any economic function. This development is also a consequence of the agricultural policy favouring intensive farming of cereals, for example, rather than cattle rearing and horse–breeding. Forests with high densities of hollow trees are small and rare. It takes longer for hollows to form in forest trees than in pollarded trees. Therefore, the renewal of hollow trees in forests is in many cases difficult. Planning for the maintenance and the renewal of hollow trees has to be conducted in cooperation with administrators of the countryside and foresters.

Germany (fig. 6) More than 1,000 records of O. eremita (both recent and historical) are known from Germany. They are mainly from lower regions (less than 400 m a.s.l.) (Schaffrath, 2003b). O. eremita occurs in all federal states in Germany. According to Schaffrath (2003b), there are at present 111 localities with O. eremita. However, investigations in recent years have resulted in a growing additional number (see Stegner, 2002; Ringel et al., 2003). The highest density of localities are in parts of Baden– Württemberg and Hessen and Niedersachsen and in Eastern Germany (Mecklenburg–Vorpommern, Brandenburg, Sachsen–Anhalt, Sachsen). In Mecklenburg, Brandenburg, Berlin and Baden– Württemberg, the localities are often wide, open forests. In Sachsen and Sachsen–Anhalt, O. eremita is widespread, especially in great flood plain areas around Elbe, Mulde and Saale which contain remnants of old forests and pasture lands. O. eremita also occurs in landscape parks, orchards (especially known in Sachsen) or historical pond regions, where oaks have been planted around the ponds (Stegner, 2002). On the outskirts of villages there are often pollarded trees, especially willows, that may be used by the beetle. In cities, sometimes even in the city centres, O. eremita regularly live in alleys, city parks and cemeteries. The most important trees are oak (Quercus spp.) and lime–trees (Tilia spp.), followed by willows (Salix spp.), beech (Fagus sylvatica) fruit trees (Malus spp., Prunus spp.) and ash (Fraxinus excelsior). Changes in land use, both in agriculture land and in forests which affect O. eremita, took place in Western Germany several decades earlier than in the East (Schaffrath, 2003b). Old–growth forests have been cut down, and forests with lime trees, oaks, hornbeams and beeches have been replaced by conifer plantations. Where deciduous forests remain, trees are usually cut down long before tree hollows can be generated. In

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Fig. 6. Distribution of Osmoderma eremita in Eastern Germany, Poland, Czechia, Slovakia, Austria and Hungary: {. Last record before 1950, or the time unknown; . Last record 1950–1989; z. Last record in 1990 or later. Fig. 6. Distribución de Osmoderma eremita en Alemania del este, Polonia, República Checa, Eslovaquia, Austria y Hungría: {. Último registro anterior a 1950, o fecha desconocida; . Último registro entre 1950 y 1989; z. Último registro de 1990 o posterior.

Fig. 5. Distribution of Osmoderma eremita in Serbia, Montenegro, Macedonia, Albania, Greece, Rumania, Moldova and Bulgaria: {. Last record before 1950, or the time unknown; . Last record 1950–1989; z. Last record in 1990 or later. Fig. 5. Distribución de Osmoderma eremita en Serbia, Montenegro, Macedonia, Albania, Grecia, Rumania, Moldavia y Bulgaria: {. Último registro anterior a 1950, o fecha desconocida; . Último registro entre 1950 y 1989; z. Último registro de 1990 o posterior.

pasture landscapes and parks, free–standing trees have become scarcer for several reasons, for instance due to ceased removal of underwood (Vera, 2000). On agricultural fields and in alleys trees have been removed. Besides, a wide relinquishing of old fruit plantations has led to a massive lost of suitable habitats in Western Germany (Stegner, 2002). A problem, which today is mainly "eastern", is the loss of large trees due to the development of housing and trade areas and new highways (Saxony: Lorenz, 2001; Schaffrath, 2003b). For instance, many trees with O. eremita were lost due to the building of an automobile factory in Dresden.

In Germany, the conservation of O. eremita should be ensured by the Federal Nature Protection Act, but due to the safety regulations based on civil law, liability laws and insurance laws, hollow trees in cities and villages are often cut much earlier than necessary. Possible safeguards for trees are rarely considered. Many localities with O. eremita are included in NATURA 2000 sites (according to EU’s Habitats Directive), but especially trees in towns are usually not included in such sites. This means that some important localities for O. eremita in Germany do not have any site protection by NATURA 2000 (Schaffrath, 2003b; Stegner, 2002). Many findings in Germany occur in isolated trees or very small stands where it is unlikely the species will be able to survive in the long term. In the 19th century, O. eremita was probably common all over Germany (Horion, 1958). In the 1950s, Horion (1958) described the beetle as "...only local and not common; in the west and southwest a rarity...". Schaffrath (2003b) published the first grid–based distribution map for Germany, based on historical and recent records available from museums and private collections. A coordinate–based map of Sachsen (Saxony) was published by Stegner (2002) and is continued under www.eremit.net. A grid–based map of Mecklenburg–Vorpommern was published by Ringel et al. (2003).

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According to a new focus of nature protection on O. eremita, numerous investigations have recently been accomplished, collecting a lot of new data. The preparation of management plans for NATURA 2000 sites in the next few years as well as the demand for monitoring by Habitats Directive will give us even better knowledge about the occurrence of this species.

Great Britain O. eremita does not occur in Great Britain (Alexander, 2002).

Greece (fig. 5) O. eremita seems to be widespread in Greece, but not common. It has been found from the low hills of the Peloponnese (Elis) to 1,700 m a.s.l. (Katara Pass). Most findings have been made in mountain forests of beech (Fagus sylvatica), chestnut (Castanea sativa), and Grecian fir (Abies cephalonica) (G. Gobbi, A. Liberto & D. Baiocchi, pers comm.). In Thessaly, the species occurs in beech, oak, and willows in the deciduous forests of Mount Ossa and Mount Olympus, between 100 and 1,200 m a.s.l. (Dutru in Tauzin, 1994b).

Hungary (fig. 6) Endrödi (1956) stated that O. eremita was rare in Hungary, but distributed throughout the whole country. This was confirmed when we went through insect collections. Most findings are from floodplain areas, mostly in willow trees (Salix spp.). However, the species also occurs at other places, for instance on Kékes, the highest mountain peak in Hungary. O. eremita is on the National Biodiversity Monitoring Program (Merkl & Kovács, 1997) as a relevant species when monitoring very old trees or forests. However, so far no detailed studies have been conducted on the species in Hungary.

Ireland O. eremita does not occur in Ireland (Alexander, 2002).

Italy (fig. 9) O. eremita is distributed throughout most of Italy. Most of the known localities in Northern Italy are in low altitude areas (up to 700 m a.s.l.), while in Southern Italy and Sicily, the species has been found up to 1,500 m a.s.l. The host trees for O. eremita are, in decreasing order of importance: deciduous and evergreen oaks (especially Quercus robur, Q. ilex, Q. petraea, Q. frainetto), chestnut (Castanea

sativa), willows (Salix spp.), beech (Fagus sylvatica), mulberry (Morus spp.), lime (Tilia cordata), maple (Acer spp.), elm (Ulmus spp.), plane–tree (Platanus orientalis), aspen (Populus tremula) and walnut (Juglans regia). Along the Aterno river valley (Pile and Preturo) and the Peligna river valley (Sulmona), as well as at the springs of Pescara river (Popoli), O. eremita occurs mainly in woods of white willow Salix alba (Marotta et al., 1997). Also in Pianura Padana (Po Valley), a large and intensively cultivated lowland, O. eremita is mainly found in planted willows. Further south, the distribution of O. eremita ranges from the remnants of evergreen Mediterranean forests, which stretch along the Tyrrhenian coast up to the belt of montane beech forest. Several O. eremita localities are in the submontane and low montane belt of central and southern Apennines, while others are in beech forests of Abruzzo, Basilicata and Calabria. Along the central Tyrrhenian coast, the species has only been found in two adjacent natural reserves: Castelfusano and Castelporziano, both situated 20–30 km from Rome. Despite intensive search, O. eremita has never been found in the Circeo National Park, which includes large areas of forests with old trees. During the last few decades, several records of O. eremita have been made in old trees (mainly oaks) situated in parks or avenues in urban areas (e.g. Florence and Rome). An example of such a locality is "Villa Borghese", a historical park situated in the centre of Rome, where the beetles live in old holm oaks (Quercus ilex). At such places the old hollow trees are threatened due to conflicts with public safety. We have more information about the species from northern Italy, due to the large number of entomologists there. Surveys focused on O. eremita have been carried out only recently and are still in progress (P. Audisio and G. Carpaneto in Central Italy and A. Ballerio and D. Baratelli in northern Italy). Latvia (fig. 11) O. eremita is known throughout Latvia, but most of the populations are small and isolated. Today more than 302 findings are known from 83 localities. 95% of the localities have been discovered during the last four years. This species is protected in Latvia and included in the Red Data Book of Latvia (Spuris, 1998). The species mainly inhabits old parks, avenues, old broad–leafed forests, and pasture woodlands (Spuris, 1998; Šternbergs, 1988; Telnov, 2001, 2002; Telnov & Kalninš, 2003). Sixty percent of all records are from agricultural and urban areas, mainly city parks and alleys. In forests, the species has only been observed in very old trees, while in agricultural and urban landscapes O. eremita often inhabits trees that seem to be comparatively younger. Lime tree (Tilia cordata), oak (Quercus robur) and maple (Acer

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Fig. 7. Distribution of Osmoderma eremita in Belarus, Russia and Ukraine: {. Last record before 1950, or the time unknown; . Last record 1950–1989; z. Last record in 1990 or later. Fig. 7. Distribución de Osmoderma eremita en Bielorrusia, Rusia y Ucraína: {. Último registro anterior a 1950, o fecha desconocida; . Último registro entre 1950 y 1989; z. Último registro de 1990 o posterior.

platanoides) are the most important tree species (Telnov, 2001, 2002). In forests, the localities are usually small (often 1–3 trees) and situated several kilometres from each other. Some old parks and avenues harbour tens of suitable trees. The species is monitored since 2000 by revisiting localities and observing species presence/absence. The only extinctions observed so far have been the result of felling old trees regarded as dangerous in the city of Riga and other places. Because many populations are so small and isolated, the risk for local extinctions is high during the following few decades. Data from literature and insect collections (museums and private) have been compiled. In the collections there were only about 55 specimens collected during the last 155 years. Field surveys have been conducted mostly during the last four years.

Fig. 8. Distribution of Osmoderma eremita in The Netherlands, Belgium, France and Spain: {. Last record before 1950, or the time unknown; . Last record 1950–1989; z. Last record in 1990 or later. Fig. 8. Distribución de Osmoderma eremita en Países Bajos, Bélgica, Francia y España: {. Último registro anterior a 1950, o fecha desconocida; . Último registro entre 1950 y 1989; z. Último registro en 1990 o posterior.

platanoides) and ash (Fraxinus excelsior), both in parks and forests. There are only two localities, both near Kaunas, where O. eremita has been recorded several times: Kaunas Oakery (Azuolynas) Park (in the city center of Kaunas), where there are many oak and lime trees, and a mixed forest near Kaunas. No survey focused on O. eremita has ever been conducted in Lithuania.

Macedonia (fig. 5) In the literature, we found one record of O. eremita from in Macedonia (Mikšić, 1955); it was from 1941.

Lithuania (fig. 11)

Moldova (fig. 5)

In Lithuania, O. eremita is rare and regarded as vulnerable (Pileckis & Monsevičius, 1992) with most findings being from the central part of the country (Pileckis & Monsevičius, 1995). The species has been found in oak (Quercus spp.), maple (Acer

In Moldova, O. eremita is regarded as critically endangered (CR) (Neculiseanu & Dănilă, 2000). We know only one specimen from Moldova, collected near Bender, in eastern Moldova, in 1917 (Miller & Zubovski, 1917; Medvedev & Shapiro, 1957).

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In 2001, surveys revealed the presence of several saproxylic beetles regarded as indicator by species (Speight, 1989). However, O. eremita was not found (Neculiseanu et al., 2001). More surveys are to be conducted and these will hopefully also provide records on O. eremita.

The Netherlands (fig. 8) O. eremita is considered extinct in the Netherlands. The last specimen was collected in 1946 in Wijnandsrade, in the extreme south of the country. The very few specimens in Dutch collections suggest that O. eremita has been extremely rare over the last 200 years. Most of the Netherlands has been deforested for centuries and localities with a long–term supply of decaying large trees have been particularly scarce since a long time ago. As a result, many saproxylic insects occurred in isolated populations and eventually became extinct. No specific surveys focused on O. eremita have been conducted. Many skilled amateur coleopterists have been active there during the last century and it seems most unlikely that they have overlooked O. eremita during this time.

Norway (fig. 10) Live specimens of O. eremita have not been found in Norway during the last 100 years. During the 19th century, the species was noted from Drammen (Siebke, 1875) and Asker (Strand, 1960; Kvamme & Hågvar, 1985). There are no specimens from Drammen or Asker in the zoological museums of Norway today, but an adult specimen in the collection of Zoological Museum in Oslo is labelled "Ex. Coll. Norway. Einar Fischer" (Karsten Sund, pers. comm.). During the last few decades only fragments of adult specimens, probably of very old origin, have been found. They have all been collected in hollow oaks at a third locality, on Rauer Island near Fredrikstad (Strand, 1960; Zachariassen, 1981; Hanssen & Hansen, 1998). Several collectors have searched for the species during the last twenty years, but the negative result has led to the assumption that the species has probably disappeared from Norway (Zachariassen, 1981, 1990; Hanssen et al., 1985). On the Norwegian Red List (Anonymous, 1999) the species has been given the category "Extinct?". O. eremita was one of ten invertebrate species proposed for protection nation–wide according to the Nature Conservation Act (Anonymous, 1994). However, finally O. eremita was not protected according to this act, because it was assumed to be regionally extinct (Øystein Størkersen, Directorate for Nature Management, pers. comm.). Suitable habitats for O. eremita, such as hollow trees of oak (Quercus robur), beech (Fagus sylvatica) and lime (Tilia cordata), occur mainly in

the agriculture landscape in the county of Østfold and Vestfold. In addition, there are a few areas with stands of old oaks in woodland, especially in the hilly landscape around Lake Farrisvannet in Vestfold. The areas around Drammen and Asker are today, like all urban areas around the Oslofjord, heavily exploited and very few localities with hollow trees are left. During the last decades, it is mainly huge oaks with great openings near the ground that have been investigated (Zachariassen, 1981; Hanssen et al., 1985; Hanssen & Hansen, 1998; Hanssen, 1999). Trees with entrance holes that are small or higher up are less studied in Norway and may possible contain undiscovered populations of O. eremita.

Poland (fig. 6) The distribution area covers the whole of Poland, except for mountainous areas. The highest altitude where the species has been found is 885 m (Zakopane; Oleksa et al., 2003). In the east, where the species’ occurrence is better known, it occurs in old trees in small groups along river banks, field roads, property borders, and sometimes in old orchards and parks. It has also been found relatively often in urban habitats such as old avenues, city parks and cementeries. In broadleaved and mixed forest, O. eremita is rare but probably still present in older stands and wood margins, especially at sites difficult to reach. When saproxylic beetles were inventoried in thirteen nature reserves of Upper Silesia (former Katowice Province), O. eremita was found in three reserves (Szafraniec & Szołtys, 1997; J. Michalcewicz, pers. comm.). In 10 x 10 km squares in the Niepołomice Forest (southern Poland), O. eremita was present in at least three out of six squares (P. Szwałko, pers. obs.). In northern Poland, an inventory from 1999–2003 between Elbląg, Iława, Susz, and the river Pasłęka (northern Poland), revealed that O. eremita occurred in 24 out of 37 investigated 10 x 10 km squares (A. Oleksa & R. Gawroński, unpubl. data). Oak (Quercus robur) is the most important host tree for O. eremita in Poland. Willows (Salix spp.) and lime trees (Tilia spp.) are often used and, rarely, fruit trees or common alders (Alnus glutinosa) are used, while there are only single reports from beech (Fagus sylvatica), ash (Fraxinus excelsior) and horse chestnut (Aesculus hippocastanum) (Pawłowski, 1961). In the Niepołomice forest, cocoons containing remains of larvae and adults of O. eremita have been found in Scots pine (Pinus sylvestris) (Oleksa et al., 2003). In the second half of 19th century, O. eremita was probably still abundant and frequent in Poland. Contemporary authors (e.g. Letzner, 1871) reported it as being found relatively often. For that reason they did not list localities for O. eremita, in contrast with other beetle species that are more common today. O. eremita has lost most of its

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Fig. 10. Distribution of Osmoderma eremita in Norway, Denmark and Sweden: {. Last record before 1950, or the time unknown; . Last record 1950–1989; z. Last record in 1990 or later. Fig. 9. Distribution of Osmoderma eremita in Switzerland, Italy, Slovenia, Croatia and Bosnia–Herzegovina: {. Last record before 1950, or the time unknown; . Last record 1950–1989; z. Last record in 1990 or later. Fig. 9. Distribución de Osmoderma eremita en Suiza, Italia, Eslovenia, Croacia, y Bosnia Herzegovina, Italy, Slovenia, Croatia and Bosnia–Herzegovina: {. Último registro anterior a 1950, o fecha desconocida; . Último registro entre 1950 y 1989; z. Último registro en 1990 o posterior.

habitats today and is extinct in some areas (Szwałko, 1992b). The species is included in local and national red lists (Szwałko, 1992b; Pawłowski et al., 2002). Old trees have been removed in managed forests, along roads and in urban areas, regarded as a source of "pests and pathogenic fungi" or a danger for humans and vehicles. Many monumental trees, which are specially protected by law, have been "cured" by mechanical cleaning of the hollows and impregnating of the wood surface with pesticides (Szwałko, 1992a). Such methods of "conservation" have been restricted due to Polish implementation of the Bern Convention and EU’s Habitat Directive. New forest management methods promote preservation of some old, especially hollow, trees wherever possible. Localities where the species still exists have already been or will be protected under the recently started NATURA 2000. On the other hand, in many managed forests (including some forest

Fig. 10. Distribución de Osmoderma eremita en Noruega, Dinamarca y Suecia: {. Último registro anterior a 1950, o fecha desconocida; . Último registro entre 1950 y 1989; z. Último registro en 1990 o posterior.

nature reserves) the wrongly understood "aesthetic mind" gives rise to further elimination of O. eremita habitats (Gutowski & Buchholz, 2000). As a result, other habitats, such as woods along fields, streams and lakes become more important for the survival of the species. About 170 localities in Poland are known. Much of the information has originated from entomologists working mainly in the eastern part of Poland, which at least partly explains the lower density of findings from north–western Poland. To get a better picture of the whole situation in Poland, investigations in the western part of the country are desirable.

Portugal O. eremita has never been recorded in Portugal (Tristão Branco, pers. comm.).

Rumania (fig. 5) In Rumania, 27 localities with O. eremita are known. At ten of these, records have not been made since 1911 (Fleck, 1904–1906; Petri, 1912), which can be explained by the low search effort.

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O. eremita occurs, for instance, in oak or mixed forests along the Danube alluvial plain and in beech or hornbeam mixed forests at the foot of the Carpathians. In many forests, trees with hollows are often removed because they are considered a potential danger.

Data from specimens in museums and private collections have been collected. In most of these localities, we know that O. eremita is still present.

Serbia and Montenegro (fig. 5) Russia (fig. 7) In western Russia, O. eremita has been found in the zone of nemoral and boreo–nemoral forest, in 18 different regions and in 6 republics. The species occurs mainly in hollow oak trees (Quercus robur), and less frequently in willow (Salix spp.), aspen and poplar (Populus spp.), lime (Tilia cordata), ash (Fraxinus excelsior), apple (Malus spp.), pear (Pyrus communis) and elm (Ulmus laevis) trees. Larvae have occasionally been found to develop in stubs. For most parts of Russia we have only limited knowledge about the species’ occurrence, but more is known regarding a few regions, such as Chuvashiya. At least 70 specimens were observed in Chuvashiya between 1988 and 2002. The species occurs mainly in oak woods along the Volga banks, from the western to the eastern border of the republic, in floodland oak woods along the Sura and in oak woods in the central and east– central parts of Chuvashiya. The height ranges from 70–200 m a.s.l. O. eremita has almost never been found in those wide areas in southern and south–western Chuvashiya that are covered with mixed forests, and it has not been found in the steppes in the south–west and south–east. In floodland oak woods near the Sura River in the protected zone of the Prisursky State Nature Reserve, Alatyr district, it is relatively easy to observe the beetle in hollow trees, which occur abundantly there. O. eremita is decreasing in Russia because old broad–leaved trees are cut down. Some local populations (e.g., in some parts of Cuvashiya and Udmurtiya) are more or less safe because they are in reserves or other areas where the trees are not being felled. In all unprotected areas, the species is vulnerable due to mass cutting of old oaks. The species has been included in the Red Data Book of the Russian Federation (Nikitsky, 1983, 2001), USSR (Lopatin, 1984) and in some regional Red Data Books, e.g. of Bashkirsky ASSR (Boev et al., 1987), Tatarstan Republic (Muravickij & Kanitov, 1995), Moscow region (Kompantsev, 1998), Adygeya republic (Cherpakov & Bibin, 2000), Kirov region (Yuferev, 2001), Ryazan region (Ananyeva & Blinushov, 2001), Udmurtiya republic (Borisovsky, 2001), Leningrad region (Krivokhatsky, 2002), Mari El republic (Baldaev, 2002), and Stavropol region (Sigida, 2002). To preserve O. eremita and other species associated with ancient trees, regional branches of the Ministry of Natural Resources of Russia should restrict the permits to cut down old trees, especially oaks.

O. eremita is known from twelve localities in Serbia and five in Montenegro, at an altitude of 70– 1,140 m a.s.l. Ecological data are scarce, but we know that in the protected area of Kapaonik, at Šanac, an adult beetle was collected on an oak (Janković, 1972).

Slovakia (fig. 6) As early as 50–70 years ago, O. eremita was reported to be declining in the present territory of the Czech and Slovak Republics (Fleischer, 1927–1930; Pfeffer et al., 1954). However, the beetle occurred at many sites in southern and central Slovakia and was locally not rare (Roubal, 1936). Since that time, nature in Slovakia has been modified by human activity, and changes in the landscape have mainly occurred in easily accessible lowlands and foothills. Numerous valuable habitats such as pasture woodlands, old trees growing in small groups, alleys and hedges as well as trees bordering rivers and streams have been lost. Nevertheless, this was not excessive compared to the rest of Europe (Zach, 2003); some habitats have been retained in the form of isolated fragments and local O. eremita populations have survived. A distribution map of O. eremita was compiled by Jelínek (1992) using data from J. Roubal and L. Korbel and archive material from the Faunistic Section of the Czecho–Slovak Entomological Society. According to this map, there were 20 localities up to 1960. Most of them (16) were located in western, southern and central Slovakia. In the period 1960– 1990, seven sites in southern and western Slovakia were recorded on a map, while there were no localities in central and eastern Slovakia. This might indicate a strong decrease in the number of O. eremita localities in Slovakia. However, when we compiled information about the present range of O. eremita, the beetle was recorded from more than 30 localities. Obviously, some of them were not included in the study by Jelínek (1992). The explanation for this can simply be that more information has been obtained since that time, although no one is currenty studying the beetle in detail. O. eremita occurs mainly in the following habitats: (1) oak pasture woodlands with scattered groups of trees or solitary trees; (2) floodplain forests with large trees. It mainly breeds in large willows, poplars and oaks —the latter in drier situations; (3) parks and alleys; (4) abandoned orchards, today a very scarce habitat; (5) mixed oak and pine forests; and (6) forest edges with large trees growing on south–facing slopes.

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Oak (Quercus robur), lime (Tilia spp.), beech (Fagus sylvatica), birch (Betula spp.), hornbeam (Carpinus betulus), elm (Ulmus spp.), walnut (Juglans regia), chestnut (Castanea sativa), willow (Salix spp.) and fruit trees are known as host trees (Roubal, 1936). The beetle has also been found developing in Scots pine (Pinus sylvestris) at Zahorska nizina lowland, western Slovakia (T. Olsovsky, pers. obs.). The advantage of polyphagy for Slovakian forest beetles in general (Whitehead, 2000) is, in the case of O. eremita, eroded by the ongoing removal of dying and dead trees. Large dead trees are not often being replaced by younger ones. This will cause local extinctions of O. eremita populations. In town parks, tree hollows in "unhealthy" trees are cleaned, and this may destroy populations. In the Slovakian Red–List, the species is categorized as "endangered" (Holecová & Franc, 2001). Further data may be available from museums and private collections. Co–operation with researchers involved in bat studies carried out in tree hollows may reveal new O. eremita localities.

Slovenia (fig. 9) O. eremita was first described by Scopoli (1763) when he was a physician in Idrija (Eastern Slovenia). Since that time it has been mentioned in faunas of different regions of Slovenia as infrequent (Scopoli, 1763; Siegel, 1866; Brancsik, 1871; Martinek, 1875). It seems that the species is distributed all over Slovenia where suitable habitats are present. Old willows (Salix spp.) are reported as the most common finding place, but also oak (Quercus spp.) and fruit trees are mentioned as habitat for the species (Scopoli, 1763; Siegel, 1866; Brancsik, 1871; Martinek, 1875). In the collections there are many very old specimens, but recent records are few, suggesting that the species has decreased. The reason is probably the same as in the rest of Europe —old fruit orchards as well as other old trees have become much rarer. The species is considered endangered by the Slovenian Red List (Anonymous, 2002). O. eremita has never been surveyed systematically in Slovenia.

Spain (fig. 8) O. eremita seems to be very rare in Spain. It has been found along a narrow band in the northern part of the country running from the Picos de Europa in the west to Montseny (Barcelona) in the east. Apparently suitable habitats are found further west from its known Spanish distribution area but the species has not been reported there. The main habitat for O. eremita in Spain is humid deciduous forest. Most records come from beech (Fagus sylvatica) forest in the mountains of the Pyrenees or Picos de Europa. In Navarra it

Fig. 11. Distribution of Osmoderma eremita in Finland, Estonia, Latvia, Lithuania and Kaliningrad (Russia): {. Last record before 1950, or the time unknown; . Last record 1950–1989; z. Last record in 1990 or later. Fig. 11. Distribución de Osmoderma eremita en Finlandia, Estonia, Latvia, Lituania y Kaliningrado (Rusia): {. Último registro anterior a 1950, o fecha desconocida; . Último registro entre 1950 y 1989; z. Último registro en 1990 o posterior.

has been found in old forests of oak (Quercus robur and Q. humilis). In most cases, adults have been found walking on old beech or oak trunks, in shaded and humid parts of the forest (Montada Brunet, 1946, San Martín et al., 2001; C. González, pers. comm.; G. Aguado & L. O. Aguado, pers. obs.). In a single case, an adult was found on an inflorescence of Sambucus nigra (Bahillo de la Puebla et al., 2002). The species seems to be absent from more anthropogenic environments such as bocages and urban parks. Adults have been observed mainly in the daytime but some captures have been obtained at night, using artificial light (San Martín et al., 2001). In 1995–96, the information about all Spanish arthropods listed in the Habitat Directive of EU was gathered and distribution maps and available

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biological information on O. eremita were published (Galante & Verdú, 2000). However, no comprehensive revision of entomological collections seems to have been carried out. Since then, new records have been published that extend the Spanish distribution area to the West (Bahillo de la Puebla et al., 2002; Ugarte San Vicente & Ugarte Arrue, 2002) and South (San Martín et al., 2001). These new records suggest that the species has been overlooked in the past, due to inefficient sampling methods or low sampling effort.

locality is defined as a site with records of living adults, larvae, fragments of adult body parts, or excrements situated at least 1 km from other localities. In a recent paper, data were compiled from field inventories conducted in 1993–2003 (Antonsson et al., 2003). Totally, pitfall traps had been used at 401 localities and wood mould sampling at 104 localities. O. eremita was found at about 30% of these localities. All larger Swedish museum collections have been gone through (Antonsson et al., 2003). Research on the ecology of the beetle has been conducted (e.g. Ranius, 2002b).

Sweden (fig. 10) The highest concentration of known O. eremita localities in the world occurs in south–eastern Sweden. O. eremita occurs only in the southern part of Sweden, up to the northern limit for oak pastures. The main habitat is pasture woodlands with old oaks, especially near castles, estates and churches (Ranius, 2000). There are also some records from parks, avenues and deciduous forests (Antonsson et al., 2003). Oak (Quercus robur) is by far the most important tree species. Especially in the very south of Sweden, O. eremita has also been found in several other tree species, such as beech (Fagus sylvatica), ash (Fraxinus excelsior), lime (Tilia chordata), common alder (Alnus glutinosa) and horse chestnut (Aesculus hippocastanum) (Antonsson et al., 2003). Old oaks were very common in the Swedish agricultural landscape until 200 years ago, but for a few decades in the early 19th century, farmers removed hundreds of thousands of old oaks from their land (Eliasson & Nilsson, 2002). It was mainly on land owned by the nobility where oaks were left. Today, ceased grazing is a severe threat to the oaks on pasture woodlands, mainly because the old trees suffer from competition and shading from the younger ones. Forest regrowth also changes the microclimate in the trees and many saproxylic beetles suffer from this (Ranius & Jansson, 2000). About 30% of the localities are protected as nature reserves, and it is mainly the largest localities that are protected (Antonsson et al., 2003). The majority of localities are small, with only a few suitable trees situated more than one kilometre from other localities. At these sites the risk for local extinctions during the following decades is substantial. There are, however, a few localities with more than 100 suitable trees (e.g. Bjärka–Säby, Sturefors and Hallands Väderö). At these sites, measures are taken to preserve the hollow tree habitat. Therefore the extinction risk for O. eremita at a national level is probably low. However, there is still no long–term planning to maintain or increase the amount of habitat when the hollow trees present today become too old. Ten years ago, 25 localities with O. eremita were known, while currently this figure is 270, if a

Switzerland (fig. 9) During the last few decades, all but one record of O. eremita in Switzerland are from the town of Solothurn. There, the species has been found in lime trees (Tilia spp.) in alleys and in a park near a castle (Vögeli, 2002). There are still many old trees in alleys and parks in the locality, but some are threatened due to conflicts with public safety. One recent record is from the region of Brusio, near the Italian border, where there are hollow willows (Salix spp.) and chestnut trees (Castanea sativa) (P. Audisio, pers. obs.). There are several old records from other localities in Switzerland (Allenspach, 1970). In the early 20th century the species was described as "rare, although present throughout the lowlands of Switzerland" (Stierlin, 1900). Data on the specimens in Switzerland’s museums and many private collections have been collected. There were no more than 80 specimens collected in Switzerland during the last 150 years. No inventories focused on O. eremita have ever been conducted.

Turkey (fig. 5) We only know one record of O. eremita from Turkey: in 1994, Dr. Sobotan found the beetle in Keșan, in the European part of Turkey.

Ukraine (fig. 7) In Ukraine, O. eremita is rare and local, and included in the Red Data Book (Yermolenko, 1994). The species has been found at 30 localities (Belke, 1859; Hildt, 1893; Łomnicki, 1875, 1886, 1903; Rybiński, 1903; Savchenko, 1933, 1934; Medvedev, 1960; Yermolenko, 1994; Chumak, 1997; Kapeliukh, 1999; Rizun et al., 2000). The majority of findings are from the zone of broad– leaved Central–European forests and the forest– steppe zone. Only at six localities do we know that O. eremita is still present: (1) an oak–dominated (Quercus robur) forest with lime (Tilia cordata), maple (Acer platanoides), ash (Fraxinus excelsior) and elm

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(Ulmus glabra) trees near the town of Sambir, (2) Kamianec’–Podil’s’kyi, which is a broad–leaved forest dominated by oak (Quercus robur) and hornbeam (Carpinus betulus) with cis–mediterranean species such as Sorbus torminalis, Viburnum lanatana and Scutellaria altissima, (3) Slovianohors’k, in an oak (Quercus robur) forest with ash (Fraxinus excelsior), Acer campestre, lock elm (Ulmus carpinifolia var. minor) and cis– mediterranean and steppe species, (4) at Kuzij, in the Carpathian Biosphere Reserve, in a beech (Fagus sylvatica) forest with silver fir (Abies alba), Norway spruce (Picea abies), sycamore (Acer pseudoplatanus), hornbeam (Carpinus betulus) and durmast oak (Quercus petraea), (5) four localities near the town Chernihiv in the northern part of Ukraine, (6) near the town Kiliia in the Odesa region, where a few beetles have been observed flying around old Salix trees. Conclusions: the future for O. eremita In this study, we have collected records of O. eremita from 2,142 localities in Europe (fig. 4). However, O. eremita has probably already become extinct from many of these; the beetle has been found since 1990 only at 919 of the localities. Out of these 919, at 79 only excrements have been found and at 96 only remains from dead beetles have been found. For these 175 localities we can not rule out the possibility that the species has already become extinct. On the other hand, there are many unknown localities that have yet to be discovered. Everywhere in Europe it seems that the majority of localities with O. eremita are small and isolated. For that reason we should expect many local extinctions in the future, even though the hollow trees that are left will be protected. This is especially the case in regions where habitat loss and fragmentation have occurred recently (for instance in France, Eastern Germany, Slovakia and Czechia); in Sweden, where the main loss of suitable trees occurred in the 19th century, O. eremita has already disappeared from some, but not all, of the smaller sites (fig. 2). In some countries (such as Denmark), all localities are small and the risk for regional extinction is considerable. In other countries (e.g. France, Sweden, Latvia and Austria) there are also a few larger localities where O. eremita may also survive in the long term if the sites are properly managed. O. eremita still occurs in almost all European countries but is absent from the boreal region, the British Isles and most of the Iberian peninsula. O. eremita seem to have decreased in all European countries. Relatively high densities of localities occur in Central Europe (northern Italy, Austria, eastern Germany, Czechia and southern Poland), some parts of Northern Europe (south–eastern Sweden, Latvia) and France. Perhaps there are also many localities in the Balkans, but searching efforts have been very low there during the last few

decades. In some regions in north–western Europe, the species has become extinct or may occur at a single locality (Norway, Danish mainland, the Netherlands, Belgium, north–eastern France). Bearing in mind the severe loss of old trees in Europe, it is perhaps surprising that O. eremita has not become extinct from larger regions. However, the species can survive in small relict populations over decades, and even if it is doomed to extinction it will take time before the species totally disappears from a region (Ranius, 2000). O. eremita mainly occurs in habitats that have been used by man for a long time. However, there are also O. eremita localities in forests, such as in Spain, France, southern Italy, the Balkans, Slovakia and Germany. Many of the man–made habitats are destroyed due to changes in agriculture. In Sweden as an example, pasture woodland suffers from forest regrowth due to ceased management, while the abandoned pollarding of oaks in France makes it difficult to produce suitable new trees for O. eremita. The beetle can also obviously survive in urban areas, but in many cases there are conflicts with public safety. Our compilation of data supports the view that O. eremita is useful as an indicator and umbrella species as everywhere it is confined to hollow trees — a threatened habitat. There are a few observations of the beetle in stubs, but there is no indication that O. eremita populations could survive at localities with no tree hollows present. Moreover, the presence of O. eremita indicates a high species richness with many threatened species associated with old trees (Ranius, 2002a). The preservation of O. eremita involves three tasks that are of general importance for nature conservation in Europe today: (1) to preserve those small remnants of natural forest that still exist, (2) to preserve and restore habitats connected with historic agricultural landscapes and (3) to preserve any remaining small pieces of nature in urban areas. Thus, taking the measures needed to protect O. eremita will also contribute to solving many other current problems in nature conservation in Europe. Acknowledgements The following persons kindly provided valuable information on O. eremita: Ainars Auninš (Latvian Fund for Nature, Riga, Latvia), Pablo Bahillo de la Puebla (Spain), Danilo Baratelli (Varese), Enrico Barbero (Torino), Massimo Bariselli (Bologna), Arvids Barševskis (Baltic Institute of Coleopterology, Daugavpils, Latvia), Luca Bartolozzi (Firenze), Luigi Beretta (Vicenza), Detlef Bernhard (Leipzig Univ.), Alexandro Biscaccianti (Roma), Luca Bodei (Bedizzole), Marco Bognolo (Trieste), Pierluigi Boschin (Rome), Tristão Branco (Porto, Portugal), Pietro Brandmayr (Arcavacata di Rende, Cosenza), Marek Bunalski (Poznań), Franco Callegari (Ravenna), Achille Casale (Sassari), Oreste Cavallo (Alba), Cornelia Chimisliu, Zbigniew Chrul (Poland),

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Loris Colacurcio (Bologna), Andrea Colla (Trieste), Ettore Contarini (Bagnacavallo), Gianfranco Curletti (Carmagnola, Torino), Giovanni & Marco Dellacasa (Genova), Roland Dobosz (Bytom), Bruno Dries (Austria), Moreno Dutto (Verzuolo), Andrea Fabbri (Tambre, Belluno), Roberto Fabbri (Ferrara), Dusan Farbiak (Protected Landscape Area Stiavnicke vrchy, Banska Stiavnica), Massimo Forti (Milano), Frank Fritzlar (Thüringer Landesanstalt für Umwelt und Geologie, Jena), Janis Gailis (Entomological Society of Latvia, Riga), Robert Gawroński (Bydgoszcz), Roberto Giannatelli (Grugliasco), Giovanni Gobbi (Roma), César González (Spain), Brigitte Grimm (Austria), Jerzy M. Gutowski (Białowieża), Jonas Hedin (Lund Univ., Sweden), Klaus Hellrigl (Brixen), Nicklas Jansson (The County Administration Board of Östergötland, Sweden), Tomas Jaszay (Sarisske museum, Bardejov), Manfred Kahlen (Innsbruck), Martinš Kalninš (State Nature Inspection, Riga, Latvia), Krzysztof Karwowski (Pieniny National Park), Stanislav Kaluz (Inst. of Zoology, Slovak Academy of Sciences), Bernhard Klausnitzer (Dresden), Alois Kofler (Austria), Mieczysław Kosibowicz (Kraków), Anton Kristin (Inst. of Forest Ecology, SAS, Zvolen), Daniel Kubisz (Kraków), Andrea Liberto (Roma), Jörg Lorenz (Naturschutzinstitut AG Dresden), Paolo Maltzeff (Rome), Franco Marozzini (Rome), Arrigo Martinelli (Rovereto), Vladimir Martynov (Donec'k), Bruno Massa (Palermo), Mieczysław Mazur (Kraków), Luigi Melloni (Bagnara di Romagna), Otto Merkl (curator for Coleoptera, Natural History Museum of Hungary), Jakub Michalcewicz (Kraków), Vittorino Monzini (San Giuliano Milanese), Carlo Morandini (Udine), Sven G. Nilsson (Lund Univ., Sweden), Andrzej Oleksa (Bydgoszcz), T. Olsovsky (Prievaly), Otars Opermanis (Latvian Fund for Nature, Riga), Walter Pagliacci (Cervia), Andrzej Palaczyk (Kraków), Anila Paparisto (Tirana), Katia Parolin (Pordenone), Fabio Penati (Morbegno), Giancarlo Perazzini (Rimini), Giancarlo Pesarini (Milano), Luigi Petruzziello (Remedello), Emanuele Piattella (Rome), Riccardo Pittino (Milano), Roberto Poggi (Genova), Ljiljana Protić (Beograd), Giulia Rasola (Bolzano), Enrico Ratti (Venezia), Franz Ressl (Austria), Antonio Rey (Genova), Joachim Roppel (Austria), Robert Rossa (Kraków), Ivo Rychlik (Slovak Entomological Society, Bratislava), S. K. Ryndevich (Baranovichi, Belarus), Lucio Saltini (Carpi), Fabrizio Santi (Bologna), Ulrich Schaffrath (Kassel), Peer Schnitter (Landesamt für Umwelt Sachsen–Anhalt, Halle), Werner Schwienbacher (Auer), Leonardo Senni (Ravenna), Pavlov Sheshurak (Nizhyn), Vladimir Smetana (Tekovske museum, Levice), Claudio Sola (Guiglia), Ignazio Sparacio (Palermo), Voldemars Spungis (LU Faculty of Biology, Riga, Latvia), Fabio Stoch (Trieste), Aleksandar Stojanović (Beograd, Serbia), Milan Strba (Inst. of Zoology, SAS), Maciej Szwałko (Kraków), Maurizio Tacchetti (Brescia), Federico Tagliaferri (Piacenza), Pierre Tauzin (Vanves), Andrzej Trzeciak (Poland), Marco Uliana (Rosara di Codevigo), Dante Vailati (Brescia), Roberto Valdinazzi (Valle San Bartolomeo), Marco Valle (Bergamo), Kristaps Vilks (LU Institute of Biol-

ogy, Salaspils, Latvia), Mauro Villa (Abbiategrasso), Vincenzo Vomero (Rome), Barbara Waga (Kraków), Andreas Weigel (Wernburg), Paul F. Whitehead (Moore Leys, Little Comberton, U.K.), Mauro Zanini (Montichiari), Pietro Zandigiacomo (Udine), Carlo Zanella (Vicenza), Iuri Zappi (Bologna), Marko Zdešar (Ljubljana), Stefano Ziani (Forlì), Witold Ziebura (Poland), Sławomir Zieliński (Poland), Stefano Zoia (Milano), Ulrich Zöphel (Sächsisches Landesamt für Umwelt und Geologie, Dresden). We also thank Daniela Ottaviani (Rome), Alessio De Biase (Rome), Emiliano Mancini (Rome), Giorgia Coletti (Rome), Emmanuelle Brunet (France) for help with compiling data and mapping and Hervé Brustel for the great exchanges concerning saproxylic insects. Ms Silke Heckenroth and Marcos Méndez helped us with translations. We thank Monika Štambergová (AOPK ČR, leader of mapping project in Czechia), for help with the data and all Czecian collectors who sent information to a mapping project. Individual co–authors were financially supported by Anne–Frid Lyngstads miljöfond (to Thomas Ranius), VEGA, Slovak Grant Agency for Science, grant No 2/3006/23 and 2/2001/22 (to Peter Zach), the Austrian Federal Environmental Agency (to Wolfgang Paill). References Alexander, K. N. A., 2002. The invertebrates of living and decaying timber in Britain and Ireland. A provisional annotated checklist. English Nature Research Reports No. 467. English Nature, Peterborough. Alexandrovich, O. R., Lopatin, I. K., Pisanenko, A. D., Tsinkevich, V. A. & Snitko, S. M., 1996. A catalogue of Coleoptera (Insecta) of Belarus. Fund of Fundamental Investigations of the Republic of Belarus, Minsk. [In Russian, English Summary]. Alexandrovich, O. R. & Pisanenko, A. D., 1991. Scarabaeid beetles (Coleoptera, Scarabaeidae) of the fauna of Belorussia. In: Fauna and ecology of the Coleoptera of Belarus: 79–94. Navuka i tekhnika, Minsk. [In Russian]. Allenspach, V., 1970. Coleoptera. Scarabaeidae, Lucanidae. Catalogus Insecta Helvetica, Band 2. Entomological Inst. der ETH, Zürich. [In German]. Ananyeva, S. I. & Blinushov, A. Ye., 2001. Osmoderma eremita (Scopoli, 1763). Krasnaya kniga Ryazanskoy oblasti. Zhivotnyye. Uzorechye, Ryazan. [In Russian]. Anikin, V. V., 1996. Redkiye vidy nasekomykh (Insecta). Fauna Saratovskoy oblasti. Poblemy sokhraneniya redkikh i ischezayushchikh vidov. Izdatelstvo Gosudarstvennogo nauchno–uchebnogo tsentra "Kolledzh", Saratov: 97–106. [In Russian]. Anonymous, 1994. Truete arter i Norge. Verneforslag. DN–rapport 1994–2: 1–56. Directorate for Nature Management, Oslo. [In Norwegian]. – 1999. Nasjonal rødliste for truete arter i Norge 1998. Norwegian Red List 1998. DN–rapport

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Appendix. Localities with O. eremita recorded. In parenthesis, year for the latest record, type of finding (a. Alive, as larva or adult; r. Remains from adult body parts; e. Excrements). If the specimen was found alive, only "a" is written, and if remains from a dead adult but no living specimens were found, only "r", independent of whether there were other kinds of findings. Data from central and southern Italy were separated into the two questionable species O. italicum and O. cristinae. Apéndice. Localidades en las que se ha registrado O eremita. Entre paréntesis, el año del último registro y tipo de hallazgo (a. Vivo, como larva o adulto; r. Restos de partes del cuerpo de un adulto; e. Exrementos). Si se encontró el especimen vivo, se indica con una "a", y si permanecen en un individuo adulto muerto pero no se encontraron individuos vivos, se indica con una "r" independientemente de otro tipo de hallazgos. Datos del norte y sur the Italia se han separado en dos especies custionables, O. italicum y O. cristinae.

Albania Maja e Kogamit (1936/a), Maja e Polocanit (1937/a), Okol (1939/a), Qafe Molle, near Tirana (1961/a), Qafe Shtame, between Tirana to Kruja (1959/a), Shkodër (Piani di Scutari) (1931/a), Tamara (1995/a), Theth, near Shkodër (1959/a). Based on literature (Schulze, 1963; Murraj, 1962; Sparacio, 2001), specimens in the natural history museums in Trieste and Vienna and unpublished records by entomologists. Austria Burgenland: Geschriebenstein (before 1937), Zurndorf (before 1964); Wien/Niederösterreich: Feichsen near Purgstall (1954), Gars/Kamp (1974), Gries near Oberndorf (1964), the vicinity of Hainburg (2001), Herzogenburg (old, undated), Katzelsdorf near Neudörfl (1998), Laxenburg (2000), Mank near Melk (1961), Mistelbach (2002), Neunkirchen (old, undated), Obernberg/Inn (old, undated), Oberndorf/Melk (1964), Petzelsdorf near Purgstall (1987), Pitten near Aspang (old, undated), Plank/Kamp (1909), Pressbaum (old, undated), Purgstall (1992), the vicinity of Purgstall (1992), Purkersdorf near Wien (old, undated), Retz (before 1943), Sommerau near Wallsee (old, undated), Wien–Ebersdorf (old, undated), Wien–Lainzer Tiergarten (2002), the vicinity of Wien (old, undated), Wiener Neustadt (old, undated), Ybbsitz (1916); Oberösterreich: Alharting near Linz (1936), Alkoven near Eferding (1907), Aschach near Steyr (1945), Enns (1947), Freinberg near Linz (before 1879), Freistadt (before 1879), Grein (before 1879), Klendorf near Katsdorf (1994), Koppl near Leonding (1963), Kremsmünster (1940), Leonding (old, undated), Letten near Sierning (1970), Linz (1932), Linz–Donauauen (1944), Linz–Ebelsberg (1964), Linz–Scharlinz (1932), Linz–Kleinmünchen (1957), Linz–St. Florian (before 1879), Linz–St. Peter (before 1879), Linz–Treffling (1942), the vicinity of Linz (1943), Sierning (1963), St. Georgen/Gusen (1991), Stein near Steyr (1995), Steyr (1903), the vicinity of Steyr (1907), Steyregg near Linz (1952), Treffling near Linz (1942), Unterweitersdorf (before 1974), the vicinity of Urfahr (1952), Wels (1972), the vicinity of Wels (1973), Zell near Zellhof (1936); Steiermark: Frauental (1974), Gleichenberg (1963), Groß St. Florian (1973), Hollenegg (1977), Mureck (1913), Radkersburg (before 1875), Rassach near Stainz (1963), Schwanberg (1963), St. Johann near Herberberstein (2003), St. Lambrecht (before 1865), Unterjahring near St. Nikolai (1995), Weniggleinz (1973); Kärnten: Ebenthal near Klagenfurt (before 1899), Ferlach (before 1854), Gailtal (before 1865), the vicinity of Hermagor (before 1936), Himmelberg near Feldkirchen (before 1886), Klagenfurt (before 1876), Kleblach (old, undated), Ledenitzen (1970), Metnitztal (before 1903), Rosegg/Drau (2002), Sattnitz (before 1899), Vellachtal (before 1855), Viktring (1952), Waidischgraben (1959), Wolfsberg (old, undated), Zellwinkel (1970); Salzburg: Anif near Salzburg (1990), Salzburg– Freisaal (1988), Salzburg–Gneis (1963), Salzburg–Hellbrunn (1936), Salzburg–Lehen (1964), Salzburg–Leopoldskron (old, undated), Salzburg–Maxglan (1931), Salzburg–Mönchsberg (1960), Salzburg–Morzg (1994), Salzburg–Nonntal (1929); Tirol: Dölsach near Lienz (1995), Dölsach–Gödnach (1983), Dölsach–Kapaunerwirt (1966), Dölsach–Stribach (1995), Lienz (1984), Nikolsdorf/Drau (1984), Oberlienz (1960), Ried im Zillertal (1960); Vorarlberg: Feldkirch (before 1912), Tisis (before 1912). Based on an extensive literature search. Very old reports, dating back to the 19th century are incorporated, together with data from relatively recent faunistic catalogues (e.g. Franz, 1974; Geiser, 2001). Kreissl (1974), Zabransky (1998) and Mitter (2001) are the only coleopterological works that give specific information on O. eremita in Austria. Additional data have been obtained from numerous public and private collections.

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Appendix. (Cont.)

Belarus Brest region: Brest (1998), lake Beloe (2000); Gomel region: Meleshkovichi (1986); Khvoyensk (1987); Grodno region: near Volkovysk, near Novogrudok (1989), near Smorgon’ (Zales’ye) (1991), Lunno (1998); Minsk region: Prusino (1984), Priluki (1987), Zhodino; Mogilev region: Gorki (1894); Sen’kovo (1887); Vitebsk region: near Vitebsk (1985). Based on casual records that have either been published (Arnol’d, 1902; Alexandrovich & Pisanenko, 1991; Alexandrovich et al., 1996; Rubchenya & Tsinkevich, 1999; Solodovnikov, 1999; Lukashenya et al., 2001) or are findings preserved at museums in Minsk and St. Petersburg (Russia) and in private collections. Belgium Brabant: Vollezeel (1887), Wellen (1950); Limburg: Hasselt, Wideux, Sint–Truiden, Hoesselt, Maeseyck (1885); Liege: Tihange, Jemeppe, Grâce–Berleur, Waremme (1887), Loën (1926), Julémont (1932), Saint–André (1944), Warsage, Visé (1928), Vallée de la Berwinne (2002). Based on the specimens in the collection of the Royal Belgian Institute of Natural Sciences and a record published by Janssens (1960). Other specimens collected during the last decades are in private collections. Bosnia and Herzegovina Babin Potok (before 1956), Drvar (1955), Foča (1913), Igman (before 1956), Ivan planina (before 1956), Knežinski Palež near Sarajevo (1957), Knježina (1949/a), Laništa, Mostar (1929), Prenj Planina (1936), Prenj–Konjic (1969/a), Sarajevo (before 1956), Travnik (before 1956), Treskavica (1951), Tuhalska Bjelina (year?). Based on old publications (HOrion, 1958; Mikšić, 1955, 1957, 1959). Bulgaria Lozen (published in 1906), Melnik (1987/a), Rila (published in 1906), Stara Mountains (published in 1906), Vraca (published in 1906), Pirin Mts (1961), Nessebar, S. of Burgas (1961–63), Rilski Monastir, Rila (1963), Sofia (1966). Based on literature (Nedelkov, 1906; Nüssler, 1986) and single specimens in private and museum collections. Croatia Istra: Štalije (1982), Opatija (before 1914), Učka (1928); Primorje: Rijeka (before 1900), Draga (near Rijeka, 1905), Crikvenica (before 1957), Velebit (probably Paklenica glen, 1899), Paklenica (Mt. Velebit, 1892); Otoci (Quarner islands): Cres (Porozoni, 1976, Cres, 2000), Krk (2002); Gorski kotar: Zapeć (1910), Moravice (before 2002), Lokve (1957), Plitvice lakes (2000); Dalmacija: Sinj (1902), Siverić (1920), Konavle (Radović, 1918); Zagorje & Prigorje: Klanjec (1904), Trnovec (1981), Zagreb (1953), Medvednica (1998), Paukovec (about 1900), Mraclin (1916), Pešćenica (1961), Japetić (1996); Slavonija: Jankovac (1916), Pleternica (1906), Dilj (before 1906), Vinkovci (before 1906), Padež (2000). Based on specimens in Croatia’s museums, literature (Depoli, 1938; Dobiasch, 1889; Koča, 1906; Mikšić, 1955, 1957, 1959; Müller, 1902; Novak, 1952; Sparacio, 2001) and personal communication with entomologists. Czechia Jihomoravský: Adamov (1991), Vyškov (1956), Slavkov u Brna (2002), Želešice (1970), Nosislav (1978), Bítov (1964), Vranovice (1979), Znojmo (1949), Bulhary (1986), Lednice (2001), Břeclav (2000), Valtice (1989), Lanžhot (2002), Ladná (2001), Pohansko (1995), Nové Mlýny (2000), Židlochovice (1985), Bítov– č eský: Blatná (1999), Písek (1977), Libětice (1954), Vodňany (1951), Veselí nad Kopaniny (1990); Jihoč

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Appendix. (Cont.)

Lužnicí (1989), Hluboká nad Vltavou (2000), Vlkov (2001), Ševětín (1997), Lomnice nad Lužnicí (1956), Lužnice (1989), Třeboň (2001), České Budějovice (2002), Chlum u Třeboně (1998), Majdalena (2002), Nové Hrady (1982), Bavorovice (1998), Stará Hlína (1994), Vondrov (1998), České Budějovice–České č ina: Chotěboř (1998), Lučice (1976), Náměšt' nad Oslavou (1992), Senorady (1938); Vrbné (1996); Vysoč Karlovarský: Stráž nad Ohří (1996); Královehradecký: Mladějov (1998), Sobotka (1949), Samšina (1995), Jičín (1999), Libáň (1991), Česká Skalice (1969), Kopidlno (1989), Sběř (1997), Bohuslavice (1979), Dohalice (1951), Hradec Králové (2000), Opočno (1990), Chlumec nad Cidlinou (2001), Libčany (1979), Třebechovice pod Orebem (1995), Týniště nad Orlicí (2002), Žd'ár nad Orlicí (2000), Bědovice (1999), Chábory (1993), Petrovice (1997), Ratibořice (1995), Brodek (1940), Hrádek (2001), Mokré– Městec (1997), Železnice (2002); Liberecký: Stvolínky (1979), Mimoň (1967), Ralsko (1980), Holany (1994), Zahrádky (2002), Doksy (1996), Bezděz (1999), Rovensko pod Troskami (1977), Hrubá Skála (1982); Olomoucký: Přerov (1988), Prostějov (1997), Tovačov (1953), Kojetín (1971), Liboš (1990); Moravskoslezský: Osoblaha (2000), Opava (1990), Kravaře (1986), Dolní Lutyně (2002), Ostrava (1992), Karviná (1992), Orlová (1930), Šenov (1962), Havířov (1967), Paskov (2000), Třinec (1963), Příbor (1987), Hukvaldy (1998), Antošovice (1990), Linhartovy (1993), Dolní Suchá (1965), Lučina (1966), Střítež (1959), Bohumín–Starý Bohumín (2002), Dolní Bludovice (1993), Ostrava–Šilheřovice (1995), Ostrava–Třebovice (1990), Louky nad Olší (1990); Pardubický: Vysoké Chvojno (1999), Sezemice (1956), Kunětice (1999), Pardubice (1999), Žamberk (1987), Zdechovice (1979), Újezd u Chocně (2001), Přelouč (2001), Choltice (1998), Lipoltice (1932), Choceň (1984), Uhersko (1931), Chrudim (1997), Heřmanuv Městec (1996), Vysoké Mýto (1960), Třemošnice (1997), Luže (1944), Nasavrky (1997), Běstvina (1995), Litomyšl (1954), Svitavy (1951), Moravská Třebová (2000), Brteč (1978), Kochánovice (2000), Slatiňany (1988), Postolov ň ský: Žihle (1961), Plzeň (1999), Kornatice (1991), Horšovský Týn (1991), Diana (1985), (1946); Plzeň č eský: Bělá pod Bezdězem Plzeň–Zábělá (1998), Lopata u Št'áhlav (1992); Praha: Lochkov (1956); Stredoč (1983), Liběchov (1971), Býkev (1998), Hořín (1971), Velvary (1997), Kutrovice (2001), Veltrusy (2002), Kvílice (2000), Slaný (1985), Jabkenice (1994), Žižice (1998), Rožd'alovice (2001), Loučeň (1994), Smečno (2001), Ruda (2001), Lány (1995), Nymburk (1941), Písty (2001), Skryje (1989), Bernardov (1996), Dobříš (1992), Hluboš (1980), Sobělšín (1994), Vlašim (2001), Drchkov (1999), Nové Ouholice (1983), Pamětník (1976), Podkost (1970), Kačina (1997); Ústecký: Osek (2002), Telnice (1959), Teplice (1990), Liběšice (1975), Ploskovice (2001), Litoměřice (2000), Chomutov (1996), Terezín (1981), Klášterec nad Ohří (1973), Třebenice (1953), Údlice (1981), Droužkovice (1988), Krásný Dvur (2001), Petrohrad (2000), Ředhošt' (1975), Dubí (1980), Mšené (1909), Červený Hrádek (1965); Zlínský: Chropyně (1976), Tlumačov (1974), Kněžpole (2002), Postoupky (1914). Presented data are based on material deposited in collections of larger museums and private collectors, records published in regional literature and made complete with records mentioned by Kollar (2000). Denmark Falster: Korselitse (1938/a); Lolland: Keld Skov (1980/a); Bremersvold (1910/a), Kristianssæde (1981/a), Maribo–area (1881/a), Krenkerup Haveskov (1999/a), Maltrup Skov (1999/ a), Halstedkloster Dyrehave (1999/a); Zealand: Oreby Skov (1999/a), Lekkende Dyrehave (1999/a), Nysø at Præstø (1901/a), Vemmetofte Strandskov (1953/a), Herlufsholm (before 1850/a), Vemmetofte Dyrehave (1999/a), Suserup Skov (1848/a), Vallø Dyrehave (1999/a), Egevang at Sorø (1991/a), Sorø Sønderskov (1999/a), Svenstrup Dyrehave (1859/a), Lerchenborg (before 1850/a), Boserup Skov (before 1850/a), Bognæs Storskov (1999/a), Charlottenlund Skov (1965/a), Jægerspris Slotshegn (1890/a), Fredensborg–area (1879/a), Gribskov, Ostrup Kobbel (about 1970/a), Hellebæk Skov (1990/a); Jutland: Fussingø Skov (1886/a). Based on specimens in museums and private collections and recent inventories (Martin, 1993, 2002). In the collections, there were about 150 specimens which have been collected since 1850 at 28 localities. Estonia Tartu (19th century/a), Koikküla (1997/r), Koiva woodland (Tsirgumäe, 2002/a; Vaitka, 2003/a). Based on literature (Süda, 1998; 2003), private collections (I. Süda, H. Õunap) and the collection of the Institute of Zoology and Botany, Estonian Agricultural University.

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Appendix. (Cont.)

Finland Ruissalo, near Turku (2002, a). Based on a report by Landvik (2000) and personal communication with Finnish entomologists. France This list is not complete, but presents some localities that are large or recently recorded. Oise department: Forest of Compiègne (1980); Orne department: hedge network of La Cochère (2001/a), apple orchards of Gacé (2003/r), hedges network of Godisson (2002/a), hedges network of Barville (2000/r); Mayenne department: hedge network of Pré en Pail (2001/r), hedge network of Evron (2001/r), hedge network of Torcé Vivier en Charnie (2001/r); Sarthe department: hedge network of Chassé (2000/r), chestnut orchards of Ecommoy (2003/r), chestnut orchards of Pontvallain (1999/r), hedge network of Vaas (2001/r), forest of Bercé (1996); Indre et Loire department: hedge network of Villebourg (2000/r); Maine et Loire department: hedge network of Blaison Gohier (2000/ r); Seine et Marne department: forest of Fontainebleau (2003); Bas–Rhin department: forest of Herrenwald (year?); La Bruche (Strasbourg; 2003/a); Indre department: hedge network of Saint Benoît du Sault (2002/r); Allier department: Forest of Tronçais (1980); Corrèze department: Meymac (2001); Aveyron department: hedge network of Salles la Source (2002/a), hedge network of Cannet de Salars (2002/r); hedge network of Pierrefiche (2002/r); Hérault department: Cévennes (1998/a), Rousses (1998/a), forest of Marquaïres, (2002/a); Pyrénées Atlantiques department: forest of Sare & Saint Pée (1999/a); Landes department: forest of Landes (partly also in Pyrénées Atlantiques, Gironde, Lot et Garonne departments, 1970); Pyrénées Orientales department: forest of Massane & Albères orientales (1999/a); Var department: forest of Maures (2000), forest of Sainte Baume (partly also in Bouches du Rhône department, 2003/a). The localities on the map are based on published records (compilation by J. M. Luce in Blandin et al., 1999; Landemaine, 2003; Tauzin, 2000; 2002), surveys conducted by H. Brustel in 2002 in the Aveyron department, the Entomological Society of Limousin (Corrèze department), and Office de Génie Ecologique by J. F. Asmodé, P. Orabi and V. Vignon (Indre–et–Loire, Mayenne, Orne, Sarthe departments) and personal communication with many entomologists (e.g. L. Baliteau, J. J. Bignon, L. Chabrol, R. Dohogne, F. Hunault, C. Jarentowski, L. Malthieux, P. Stallegger, L. Valladares and Y. Vasseur). Germany Sachsen (Saxony): southern Dresden (Pirna, Heidenau–Großsedlitz, Pillnitz, 2000/a), Dresden (city, Dresdener Heide, Pesterwitz, Weißig, 2003/a), Radebeul (Hermsdorf, Moritzburg, 2003/a), between Dresden and Meißen (different side valleys of Elbe river, 2003/a), Meißen (city, Robschütz, Miltitz, 2003/a), between Meißen and Lommatzsch, mainly in fruit plantations (Leutewitz, Sieglitz, Käbschütz, Seebschütz, Seilitz, Piskowitz, Zehren, Zöthain, Niedermuschütz, Zscheilitz,2003/a), northern Meißen (Diesbar–Seußlitz, 2003/a), Zeithain (1990/a), Zabeltitz (2001/a), southern Torgau (Graditz, 2003 r), Delitzsch (Storkwitz, 2003/r, Wölkau, 2000/r, Jesewitz, 2002/a, Gotha [Sachsen] 2002/r), Leipzig (city, floodplain forest, Burgaue, Dösen, 2001/a), Lindenthal (2003/a), Dübener Heide (Pressel, 2002/r, Falkenberg, 2002/a, Weidenhain, 1993/a, Trossin, 2003/r, Roitzsch, 2003/r), Dahlener Heide (Dahlen 2003/a), Mutzschener Wasser (Mutzschen 2002/a, Gastewitz 2002/r, Wiederoda, 2002/a), Mulde floodplain between Wurzen and Bad Düben (Thallwitz 1998/a, southern Eilenburg 1993/a, Zschepplin, 2002/r, Hohenprießnitz, 2003/r, Bad Düben, 2003/r), southern Leipzig (Zwenkau, 2003/r), Niederlausitz (Niederspreer Teichgebiet, 2002/a), Weißwasser (1986/a). Based on information from Detlef Bernhard (pers. comm.), Jörg Lorenz (pers. comm.), Angela Mann (pers. comm.), Stegner (2002) and Ulrich Zöphel (Sächsisches Landesamt für Umwelt und Geologie). Sachsen–Anhalt (Saxony–Anhalt): Gatersleben (1952), Rothenförde (1981), Stackelitz/Fläming (1989/r), Steckby (NSG ‘Steckby–Lödderitzer Forst’, 1995/a), Zerbst (city, 1995/a), Bernburg (Kesselbusch, 1988/ a), Brucke (Wiese nahe Saale, 2000/a), Kustrena (Pfuhlscher Busch, 1988/r), Plötzkau (NSG Plötzkauer Auenwald, 1996/a, near Autobahn, 2000/a, near the sport ground, 2000/a), Bad Kösen (1934), Freyburg/ Unstrut (Schloßberg an der Neuenburg, 1968/a), Naumburg (oberer Rand vom Mordtal, 1934, Hallischer Anger, 1934, around Naumburg, 1944), Marke (1955), Dessau (several years, Luisium 1995/a, Kornhaus

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Appendix. (Cont.)

1988/r, Mosigkauer Heide 1950, Sieglitzer Berg 1989/r, Leiner Berg 1999, Becker Bruch 2000/r, Kühnauer Heide 1978/a, Dessau–Waldersee 1988/r), Roßlau (near Elbe river 1996), Halle (city, 1950/ a, Dölauer Heide, 1988/a, Peißnitz 1998, Halle–Neustadt, Saaleaue, 1987/a), Burg (NSG Bürger Holz, 1993/a), Cöthen (=Köthen 1889), Köthen (city, 1993/r), Diebzig, 1995/r), Diesdorf (Mosigkauer Heide, 1992/r), Magdeburg (1950, Magdeburg–Pechau: NSG Kreuzhorst, 1992/a), Eisleben (Landwehr, Amsdorf, 1912, Himmelshöhe, 1950), Frankleben (1983), Ballenstedt (1987/a), Quedlinburg (city, 1975, Brühl, 1982/a, Altenburg 1988/a), Schönebeck (Glinde, 1927, Grünewalde, 1925), Iden (1978), Stendal– Wahrburg (city, 1995/a), Dieskau (1900), Döllnitz (1987), Röpzig (1898), Wettin (1900), Pretzsch (Dübener Heide, 1942), Althaldensleben (2000, the landscape park, 1997/), Breitenbach near Zeitz (1982), Haldensleben (Alteichenbestand, 1998/e), Hundisburg (Barockgarten, 1997/r), Trebnitz near Zeitz (Pötewitz–Ahlendorf, 1987/a). Based on information from Peer Schnitter (Landesamt fur Umwelt, pers. comm). Thüringen: Ummerstadt (1905), Burgk/Saale (Schloss, 2002), Meiningen (1851), Greiz (1910), Gössnitz/Schmölln (1932), Schmölln (1987/a, Sprotteaue, 2002/r), Posterstein (2002/a), Ronneburg (1936), Gera (1983/r), Gösdorf/Altenburg (2002/a), Großmecka (Tautenhain, 2002/r), Ziegelheim (1999), Altenburg (1998/a), Breesen/Altenburg (2002), Lossen/Altenburg (Deutscher Bach, 2002/r), Mockzig (2002/a), Nobitz/Altenburg (1978), Zschaschelwitz/Altenburg (1999), Mehna (Kleiner Gerstenbach, 2003/a), Tegkwitz (2003/a), Göhren (2003/a), Lossen (2003/a), Breesen (2003/a), Schwanditz (2003/a), Gimmel/Schmölln (2002), Starkenberg (1971), Bad Köstritz 1990/a), Gera (Milbitz, 1937, Roschütz, 1995/a; Stublach, 1951, Thieschitz, 1996/r, Tinz, 1931/a), Pohlitz (1993/a), Bad Klosterlausnitz (1995/a), Eisenberg (Beuche, 1966, Rodigast, 1968), Etzdorf/Eisenberg (1955/ a), Gösen (1988/a), Hainspitz (1996/a), Krossen/Eisenberg (1993/a), Bürgel (1993/a), Ilmsdorf/ Bürgel (1993/a), Tautenburg, Hohe Lehde (1997), Waldeck (Schloßgrund, 1986), Jena (city, 1979, Löbstädt, 1999/a, Paradies, 1921/a; Zwätzen, 1994), Weimar (Webicht 1934/a), Erfurt (1843), Gotha [Thüringen] (Großer Seeberg, 1896), Eisenach (1894), Eisenach–Siebenborn (1958), Saaleck/Bad Kösen (Saaleaue, 2002), Harras/Schmücke (1909/a), Schlotheim (1862/a), Volkenroda/Mühlhausen (1873/a), Mühlhausen (1862/a), Ichstedte (2001/a), Bad Frankenhausen (1900, Kl.Wipper, 1963), Kyffhäuser (Südabfall, 1934/a), Sondershausen (1854), Krimderode/Nordhausen (1934), Nordhausen (1934), Rüdigsdorf (1934). Based on information from Frank Fritzlar (Thüringer Landesanstalt für Umwelt und Geologie, pers comm.) and Andreas Weigel (1995; 1996; 2000, pers. comm). Mecklenburg–Vorpommern (Mecklenburg–Western Pomarania): Rostocker Heide (NSG Heiligensee, 1992/r), Schlemmin (2002/r), Groß Markow (2001/a), Pohnstorf near Teterow (2001/a), Hohenbüssow near Alt Tellin (2002/a), Klein Wokern (2002/r), Teterow (1993/a), Hagensruhm near Teterow (1991/a), Hohen Mistorf (1991/a), Rothspalk near Langhagen (2001/a), Karstorf (2001/a), Basepohl (2001/r), Ivenacker Eichen (2001/a), Burg Schlitz near Teterow (2001/a), Rothenmoor near Teterow (2001/a), Müritzer See, Waren near Blücherhof (1994/l), Kittendorf (2001/a), Neuenkirchener Wald near Luisenhof (1997/a), Heinrichsruh (Park, 2002/a), Christiansberg near Ahlbeck (2001/a), Crivitz east from Schwerin (2002/a), Torgelow near Waren (2002/l/r), Neubrandenburg (Broder Holz, 1970/a, Fünf Eichen, 1985/a, Markt, 2002/a), Viereck (2001/a), Eulenspiegel west from Wendfeld (2003/r), Pritzier (2001/a), Ludwigslust (Schlossgarten, 1996/a), Neustrelitz (Tiergarten, 2001/a), Weisdin (2001/a), Serrahn (1990/a), Heilige Hallen (2002/r), Groß Mohrsdorf (1984/r), Devener Holz near Demmin (1985/a), Mueß near Schwerin (Reppin, 1980/a), Brantensee (1998/r), Bennin near Hagenow (1988/a), Banzin near Hagenow (1981/a), Kuppentin (1988/a), Hohenzieritz (Schlosspark, 2002/r), Burg Stargard (Klüschenberg, Burgberg, 1988/a), Usadel (2002/r), Feldberg (2002/r), Sprockfitz–See (am Staugraben, 2002/r), Wokuhl 2001/r), Prosnitz near Stralsund (19th century/a), Bad Doberan (1918/a), Teufelsmoor near Sanitz (1977/l), Greifswald (Elisenhain, 1966/a), Ückeritz (Insel Usedom, 1971/a), Bützow (Linden am Wall, 1907/a), nördlich Kamminke (Golm, 1974/a), Vollrathsruhe (Schlosspark, 1882/a), Zettemin near Malchin (1941/a), Gallin (1969/a), Feisneck–See near Waren (1979/a), Rothemühl (Forst, 1937/a), Grabow (1874/a), Insel Vilm (1999/r to be proved). Based on Ringel et al. (2003). Brandenburg: many localities with findings since 1990, especially in the northern part (Uckermark). Some localities with recent records in southern Berlin around Potsdam (Sanccouci) (Möller & Schneider, 1992; Schaffrath, 2003b).

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Appendix. (Cont.)

Berlin: localites with recent records (since 1990) in the southwest (Grunewald) (Müller, 2001; Schaffrath, 2003b). Schleswig–Holstein: several localities in the eastern part before 1980, only one since 1990 (Schaffrath, 2003b). Hamburg: only records before 1980 (Schaffrath, 2003b). Niedersachsen (Lower Saxony): several localities in northeastern Lower Saxony (Göhrde region) since 1990, some localities with recent records in central Lower Saxony (Schaffrath, 2003b). Bremen: some localities since 1990 (Schaffrath, 2003b). Nordrhein–Westfalen (North Rhine–Westphalia): several localities before 1980, only a few localities in the Rhine region with records between 1980 and 1989 (Schaffrath, 2003b). Rheinland–Pfalz: only at a few localities in western parts before 1980 and some between 1980 an 1989 (Schaffrath, 2003b). Saarland: at two localities since 1990 (Schaffrath, 2003b). Hessen (Hesse): many localities before 1980, and also at many localities since 1990 especially in the north and the south (Rhine–Main–region) (Schaffrath, 2003b). Baden–Württemberg: many of localities with recent (since 1990) records in central Baden– Württemberg (around Stuttgart, Neckar region). One locality in the south (Rhine valley) (Schaffrath, 2003b). Bayern (Bavaria): some recently discovered localities (since 1990) in regions with river valleys (Main, Donau). A big area with O. eremita is situated in the Spessart region (Schaffrath, 2003b). Greece Aisimi (= Essimi) (1963/a), Akarnanika Ori (before 1886), Elis (before 1886), Euboea (before 1886), Katara Pass (1998/a), Katerini, Meteore (1996), Mount Athos (1994), Mount Mavrovouni (1994), Mount Olympos (1994), Mount Ossa (1994), Mount Ossa, NE slope, near Kokkinonero (1979), Mount Taygetos (before 1886), Pessani, near Alexandhroupolis (1994), Vrondou (1996), Nomos Larisis (Spilia, 2003/a, Omolion, 1991/a, Stomion, 2003/a), Nomos Ioanninon (Vrosina, 2003/a), Nomos Pierias (Katerini, 1991/a). Based on published records (Oertzen, 1886; Mikšić, 1959; Tauzin, 1994b; Sparacio, 2001) and unpublished records by e.g. H. Brustel (pers. comm.). Hungary Baranya: Bár (1964/a); Bács–Kiskun: Bátya (1939/a), Fokto (1945/a), Kalocsa (a); Borsod–Abaúj– Zemplén: Dédestapolcsány (1949/a); Gyõr–Moson–Sopron: Gyor (1988/a), Gyorzámoly (1973/a), Hédervár (1949/a); Heves: Gyöngyös, Kékes (1953, a); Nógrád: Diósjenö (a); Pest: Budapest, Pestimre (a), Kemence (1954/a), Szigetcsép (a); Zala: Zalaszántó (1957/a). Based on specimens in the Natural History Museum of Hungary (about 20 specimens). We also went through collections of other institutions (e.g. Inst. of Forest and Wood Protection, Univ. of West– Hungary) and private collections (e.g. Vida’s). They contained a few specimens; however, most of them were unlabelled or only from the neighbourhood. Italy Osmoderma eremita Valle D’Aosta: Aosta (Aosta, year?/a); Piemonte: Torino (1968/a, Baudenasca, loc. Paglieri near Pinerolo, 1968/a, Macello, year?/a, Buriasco, year?/a, Carmagnola, 1995/a, Moncalieri, 1977/a, Leinì, 1974/a, Mirafiori, 1949/a, Stupinigi, 1944/a, Santa Margherita, 1924/a), Vercelli (1914/a), Novara (1983/a, Cameri, 1983/a), Alessandria (Frugarolo, 1906/a, Serravalle Scrivia, 1945/a, Piovera, 1945/a, Cassano Spinola, 1905/a, Alessandria, 1982/a, Pontecurone, 1984/a, Spinetta Marengo, 1993/a, Rivalta Scrivia, 1971/a, Vignole Borbera, 1967/a, Cabella Ligure, 1989/a, Acqui Terme, year?/a), Cuneo (1987/a, Canale, 1998/a, Entracque, 1965/a, Saluzzo, 1978/a, Borgo San Dalmazzo, 1958, Cherasco, 1989/a, Mondovì, 1977/a, Ormea, 1993/a, Genola, year?/a, Verzuolo, 2000/a, Fossano, 2001/a, Salmour, 2002/a) Cicogna (Verbania; 1997/a); Liguria: Genova (Val d’Aveto, Magnasco, 1986/a), Savona (Toirano, 1984/a); Lombardia: Sondrio (Lovero Valtellino, 2000/a, Tovo di Sant’Agata, 1997/a, near Grosio, 2000/a, Tirano, 1995/a), Brescia (1982/a, Alfianello, 1977/a, Leno, 2001/a,

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Appendix. (Cont.)

Remedello, 1995/a, Visano, 2000/a, Gottolengo, 1996/a, Gambara, 1993/a), Bergamo (1941/a, Casazza, 1971/a), Lecco (Mount Barro above Galbiate, 1978/a), Como (1931/a, Erba, 1987/a), Varese (Palude Brabbia, year?/a, Cocquio Trevisago, 2000/a), Milano (1966/a, Meda, 1897/a, Turate, 1931/a, Baggio, 1928/a, Gessate, 1980/a, Monza, year?/a, Paderno Dugnano, 1962/a, Corbetta, 1990/a), Cremona (1987/a, Ostiano, 1994/a, Robecco, 1979/a, Pandino, 1972/a), Mantova (1950/a, Bosco Fontana, 1949/a, San Biagio near Bagnolo S. Vito, year?/a), Pavia (1975/a, Voghera, 1965/a, Stradella, 1987/a, Mirabello di Pavia, 1972/a, Villalunga, 1975/a, San Genesio, 1972/a); Trentino– Alto Adige: Bolzano (probably 1890, Brunico, probably 1930), Prato allo Stelvio (probably 1890), Trento (1933/a, Borgo Valsugana, 1930/a, Ischia Podetti near Pergine Valsugana, 1929/a, Val Sugana, 1930/a, Val d’Adige Inferiore, 1927/a, Vela di Trento, 1960/a, Pinzolo, 1940/a, Vigo Anaunia near Ton, 1934/a, Lago di Terlago, 1965/a, Rovereto, year?/a, Pergine, year?/a, Cles, year?/a, Rallo, 1934/a, Villa–Agnedo, 1933/a, Nogaré, 1880’s/a, Madrano, 1880’s/a), Bolzano (probably 1890, Brunico, probably 1930, Prato allo Stelvio, probably 1890, Appiano, 1930/a, Varna, 1984/a, Ora, 1984/ a, Val Venosta, Silandro, 1951/a, Seiser Alm (= Alpe di Siusi), 1996/a, Salorno, 1880’s/a, Bronzolo, 1860’s/a, Lana, 1860’s/a, Gudon, 1860’s/a, Ciardes, 1860’s/a); Veneto: Venezia (Mestre, 1973/a, Carpenedo, 1971/a, Chirignago, 1936/a, Marghera, 1955/a, Sega di Gruaro, Reghena river, 1993/a, Giai di Gruaro, year?/a), Padova (1972/a, Rosara di Codevigo, 2002/a, Codevigo, 2002/a, Lovertino, 1986/a, Montagnana, 1925/a), Vicenza (La Rotonda, 2000/a, La Commenda, 1992/a, Arcugnano, 1974/a, Lago di Fimon, 1972/a, Altavilla Vicentina, 1999/a, Monteviale, loc. Biron, 1959/a, Albettone, year?/a), Treviso (Mogliano Veneto, 1972/a, Asolo, year?/a, Il Montello above Giavera, year?/a), Belluno (loc. Mussoi, 1973/a), Verona (Boschetto, 1926/a, Bosonetto, 1928/a, Mambrotta, 1926/a); Friuli–Venezia Giulia: Trieste (Boschetto near Longera (=Bosco Farneto), 1953/a, Valle delle Noghere near Aquilinia, 1921/a, Cattinara, year?/a), Udine (Pontebba, 1895/a, Parco delle Prealpi Giulie near Resia, 1995/a); Emilia Romagna: Bologna (2000/a, Sala Bolognese, 1978/a), Reggio Emilia (Campegine, 1989/a, Calerno, 1986/a, Castelnuovo, 1986/a, Cadelbosco di Sotto, 1989/a, Massenzatico, 1990/a), Modena (Sestola, 2000/a), Ravenna (Bagnacavallo, 2000/a, Massa Lombarda, 1974/a, Lugo, 1977/a, Fusignano, 1968/a, Barbiano, 1992/a, Russi, 1973/a, Granarolo Faentino, 1956/a, Faenza, 1984/a, Sant’Agata sul Santerno, 1984/a, Cotignola, 1897/a), Ferrara (Argenta, 1995/a), Piacenza (2001/a, Ferriere, year?/a, Olmo near Bettola, 1989/a, Castel San Giovanni, 1970/ a, Piacenza, Le Mose, 1963/a), Parma (1990/a, Collecchio, 1980/a, Fontanellato, 1981/a, Calestano, 1891/a), Forlì (Balze di Verghereto, 1990/a, Monte Fumaiolo, year?/a, Verghereto, 1976/a, Alpe di San Benedetto, above San Benedetto in Alpe, 1990/a); Toscana: Firenze (1972/a, Firenze, Parco Le Cascine, 1954/a, Firenze, Badia Della Valle, 1985/a, Panzano, 1925/a, Marradi, 1971/a), Prato (La Badia, 1996/a), Livorno (a), Lucca (year?/a, Porreta, 1942/a), Grosseto (Poggio Cavallo, 1932/a, Semproniano, 1976/a); Umbria: Perugia (Norcia, 1954/a, Avendita, 1966/a); Lazio: Viterbo (Vignanello, 1998/a), Rieti (Cittaducale, 1966/a, Poggio Mirteto, 1920/a), Roma (Roma, Bufalotta, 1970/a, Roma, Villa Doria Pamphili, 1987/a, Roma, Villa Borghese, 2001/a, Castel Porziano, 2001/a, Castel Fusano, 1970/a, Olevano Romano, 1919/a; Abruzzo: L’Aquila (Fontavignone, near Rocca di Mezzo, 1971/a, Pescasseroli, 1971/a, Tagliacozzo, 1954/a, Pizzoli, 1980/a, Monti Simbruini, Intermesoli, between Pereto and Cappadocia, 1965/a, Pereto, 1996/a, Val Dogana near Camporotondo di Cappadocia, 1996/a, Zompo dello Schioppo falls above Morino, 1997/a, Pile, 1972/a, Costa Masciarelli, 1991/a, Preturo, year?/a, Sulmona, 1990/a, Parco Nazionale d’Abruzzo, between Opi and La Camosciara, year?/a, Gran Sasso, Vallone Venacquaro, 1991/a), Pescara (Valle Peligna, Popoli, 1990/a), Chieti (Scerni, 1964/a, Parco Nazionale della Majella, Montenerodomo, 2003/a). Osmoderma ’"italicum" Campania: Caserta (Vitulazio, 1911/a), Napoli (Isola di Procida, 1975/a), Salerno (Vallo Lucano, S. Biase, 1912/a); Puglie: Foggia (Anzano, 1987/a); Basilicata: Potenza (Terranova di Pollino, 1983/a), Potenza (San Severino Lucano, 1998/a, Pietrapertosa, 1971/a, Viggiano, 1964/a, Monte Pollino, La Catusa, year?/a); Calabria: Cosenza (Timpone del Vaccaro between Morano Calabro and Orsomarso, 2001/a, Decollatura, 1992/a, Serra San Bruno, 1988/a), Reggio Calabria (Delianova, 1989/r). Osmoderma "cristinae" Sicilia: Palermo (Madonie, Piano Zucchi, 1992/a, near Castelbuono, 1860/a, Gibilmanna, 1997/a). Based on specimens in Italian museums and many private collections. We have gathered information on 500 specimens collected during the last 150 years.

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Appendix. (Cont.)

Latvia Aizkraukles raj.: Daudzese env., Baibas house 1 km W (2002/e); Erberge, parks (2002/a); Bauskas raj.: Budberga, aleja (2001/rs); Jaunsaule (2001/e); Ozoldarzs NPA (2002/ a); Cesu raj.: Gaujas NP, Ieriki, aleja (2001/a); Gaujas NP, Raiskums–Auciems (2003/a); Gaujas NP; Ungurmuiža (2002/a); Gaujas NP, Skalupes (2003/a); Daugavpils raj.: Bebrene (parks, 2002/a); Daugavas loki NPA (2002/ a, Naujene, Jezupovas parks, 2002/a), Dinaburgas pilskalns 3,5 km no Naujenes (2002/a); Eglaines meži NPA (2002/a); Naujene, gravis (2000/a); Pilskalnes Siguldina NPA (2002/a); Silenes NPA, Ilgas, muižas parks (2001/a); Vabole, parks (2001/a); Viški (2001/a); Dobeles raj.: Benes vm. (kv 103, nog. 1, 2001/e, kv 121, nog. 18, 2001/e, kv 127, nog. 9, 2001/e, kv 129, nog. 8, 2001/e, kv 131, nog. 16, 2001/e, kv 131, nog. 17, 2001/e), Dobele (kv 113, nog. 7, 2001/e); Gulbenes raj.: Jaungulbenes vm. (kv 852, nog. 2–3, 2001/a, kv 871, nog. 12, 2001/a), Litenes vm. (kv 159, nog. 19, 2001/a), Pededzes lejtece NPA (at Vikšni vill., 2003/a, Silinieki, 2003/a), Pededzes ozolu audze NPA (2002/a), Pirtsliča– Lika atteka NPA (2002/a), Sitas un Pededzes sateka NPA (2002/a); Jekabpils raj.: Abeli NPA (2001/a), Dunava, parks (2002/a), Rubeni, parks (Rubenes pagasts) (2002/a), Sauka NPA (2002/e), Slates vm. (kv 20, nog. 11, 2001/e); Jelgavas raj.: Jelgava (Ozolpils parks, 2001/rs); Kuldigas raj.: Edole (parks, 2002/a), Rudbaržu vm., kv 316, nog. 10 (2001/e); Liepajas raj.: Dunika NPA (2001/a), Pape ž u raj.: Augstroze NPA (2001/a); NPA, Pape (2001/a), Priekules vm., kv 397, nog. 8 (2001/e); Limbaž Birinu pils parks (2002/a), Burlaku plavas NPA (2002/e), Salacas ieleja NPA (2002/a), Svetupes ozolu audze NPA (2002); Ludzas raj.: Istras ezers NPA (2002/a), Ludzas vm. (kv 126, nog. 5, 2001/e); Madonas raj.: Kalsnavas vm., kv 167, nog. 14 (2001/a); Ogres raj.: Lielie Kangari NPA (2001/a); Riga city: center, kanalmalas parks (1995/a), Arkadija parks (1999/a), Jaunciems NPA (2002, rs), Mežaparks (1994/a), Saulesdarzs (2002/a); Rigas raj.: Doles sala NPA (2001/a), Gaujas NP (Krimulda, sanatorija, 2001/a, Krimuldas bazn§ca, parks, 2001/a, Sigulda, at Siguldas castle (1991/a), Liela Baltezera salas NPA (2001/e), Inčukalna apk., Krustini; Talsu raj.: Dundaga (2000/a), Rakupes ieleja NPA (2001/a), Sliteres NP, Slitere (2000/a), Talsu pauguraine NPA (2002/a); Tukuma raj.: Abavas ieleja NPA (2002/a), Irlavas vm., kv 200, nog. 9 (2001/e); Valkas raj.: Valkas vm., kv 105, nog. 1 (2001/e), Vijciema vm., kv 234, nog. 9 (2001/e), Ziemelgaujas paliene PNV (2002/a); Valmieras raj.: Mazsalaca, skolas parks (1970/a); Ventspils raj.: Moricsala SNR (2001/a), Popes vm. (kv 66, nog. 3, 2001/e, kv 90, nog. 32, 2001/e), Usma (Usmas tautas skola, 2001/a). Based on literature, insect collections (museums and private) and field surveys. In the collections there were about 55 specimens collected during the last 155 years. Field surveys have mostly been conducted during the last four years. Lithuania Ignalina: Didžiagirio forest (2000); Kaiš š iadoriai: Kruonis (1988); Strevininkå forest (2002); Kaunas: Gervenupis (1997); Kaunas (2001); Kleboniškis (1976); Lapes (1963); Kedainiai: (1963); Lazdijai: ž ys: Gringaliu forest (1987); Pasvalys: Joniškelis (1983); Meteliai (1980); Marijampole (1963); Panevež š iai; Trakai: (1978). Plunge; Šilale; Telš Based on specimes in Kaunas T. Ivanauskas Zoological Museum at The Lithuanian University of Agriculture and many private collections. 27 specimens were recorded from the last 80 years. Macedonia Tetovo (1941). Based on Mikšić (1955). The specimen is preserved in the Natural History Museum of Beograd (L. Protić, pers. comm.). Moldova Bender: settlement Bender (1917). Based on Neculiseanu & Dănilă (2000). The Netherlands Gelderland: Arnhem (1897), Beek (before 1910), Nijmegen (1886), Wehl (before 1887), Wisch (before 1926), Zutphen (1853); Zuid–Holland: Den Haag (dubious record, before 1893); Limburg:

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Appendix. (Cont.)

Gronsveld (1907), Houthem (1904), Limmel (before 1892), Maastricht (1876–1903), Oud–Vroenhoven (before 1887), Valkenburg (1902), Wijnandsrade (1946). Based on examination of the major Dutch private and museum collections. Also the faunistic literature was checked for additional data (Huijbregts, 2003). In total, 23 O. eremita specimens from 14 localities were collected between 1870 and 1946. Norway Akershus: Asker (19th century/a); Buskerud: Drammen (before 1875/a); Østfold: Rauer near Fredrikstad (1997/r). Based on literature, summarized in Hanssen (1999). Poland ż e Bałł tyku (Baltic Coast): Woliński National Park (before 1951), Puck (1979/a), Wejherowo Pobrzeż (about 1995/a), Sopo (turn of 19th/20th century), Oliwa (turn of 19th/20th century), Gdańsk (turn of 19th/ 20th century), Elbląg (turn of 19th/20th century), Kadyny (1957/a); Pojezierze Pomorskie (Pomerania Lake Region): Bierzwnik near Choszczno (1954/a), Bielinek nad Odrą reserve near Cedynia (1985/r); Pojezierze Mazurskie (Masurian Lake Region): Area between Elbląg, Iława, Susz and the river Pasłęka (2003/a); Wąbrzeźno (turn of 19th/20th century), Brodnica forest district (before 1961), Morąg (before 1945/a), Ostróda, Jedwabno, Kętrzyn (turn of 19th/20th century), Gładysze near Młynary (1993/a), Bartoszyce (1995/a), Lipowo near Piecki (2000/a); Nizina Wielkopolsko–Kujawska (Wielkopolska– Kujawy Lowland): Kostrzyn (1918/a), Rawicz, Poznań–Dębina (before 1922/a), Rogalin, Krajkowo near Mosina (1993/a), Sułów near Milicz (1962/a), Ostromecko (2002), Toruń (turn of 19th/20th century), Las Piwnicki reserve near Toruń (2002/a), Ciechocinek vicinity (1967/a); Nizina Mazowiecka (Mazovian Lowland): Warszawa (Las Młociński, Las Bielański, 1956/a), Saska Kępa (before 1962), Ursynów (before 1993/a), Sękocin near Piaseczno (before 1963), Sucha Szlachecka near Białobrzegi (1995/a), Józefów (before 1975/a), Trzebień near Magnuszew (1994/a), Puszcza Kozienicka (before 1998/r), Zosin near Ułęż (before 1975/a); Podlasie (Podlasie): Sitniki near Siemiatycze (about 1980/a), ż a Primeval Forest): Świnoroje Liszna near Sławatycze (1995/a); Puszcza Białł owieska (Białł owież ą sk (Lower Silesia): Wrocław near Narewka (1988/a), Białowieski National Park (1987/a); Dolny Ś lą (before 1929), Brzeg (1982/a) Ziemiełowice near Namysłów (19th century), Pokój (1992/a); Wzgórza ą sk (Upper Trzebnickie (Trzebnickie Hills): Topolno (19th century), Trzebnica (1975/a); Górny Ś lą Silesia): Zawadzkie (1931/a), Racibórz, Łubowice near Racibórz, Rudy near Kuźnia Raciborska (before 1856), Łężczak reserve (1996/a), Rudziniec (2003/a), Tworków near Krzyżanowice (1949/a), Baranowice near Żory (1983/a), Murcki (before 1945/a), Pszczyna (1986/a), Chełmek (1923/a), Zaborze near Oświęcim (1903/a), Bukowica reserve (2002/a), Lipowiec reserve (2001/a), Płaza near ń Upland): Złoty Potok (about ż yna Krakowsko–Wieluń ń ska (Kraków–Wieluń Chrzanów (1974/a); Wyż 1976/a), Blachownia near Częstochowa (before 1908), Krzeszowice (1988/a), Czerna k. Krzeszowic (1907/a), Karniowice near Zabierzów (before 1945/a), Ojców (1974/a), Modlnica (1977/a), Skała Kmity near Szczyglice (1970/a), Piekary near Liszki (1997/a), Skawina (1925/a), Michałowice near Kraków (1937/a), Kraków (1928/a), Kraków: Bielany (1968/a), Las Wolski (1952/a), Salwator (1994/a), ż yna Małł opolska (Małł opolska Upland): Las Zwierzyniec (1917/a), Płaszów (before 1950); Wyż Łagiewnicki reserve near Łódź–Smolarnia (1996/a), Subina near Koluszki (1984/a), Spała near Inowłódz (1949/a), Zagnańsk (1991/a), Jędrzejów (1990/a), Książ Wielki (1985/a), Mianocice near Miechów (1872), Miechów forest district (before 1961), Kocmyrzów near Luborzyca 1953/a), Nowe Brzesko (1985/a), Zięblice near Kazimierza Wielka (before 1975/a), Czyżowice near Kazimierza ę tokrzyskie Wielka (1999/a), Bronowice near Puławy (before 1950/a), Puławy (before 1915); Góry Ś wię Ś wię ę tokrzyskie Mountains): Świętokrzyski National Park (before 1958); Wyż ż yna Lubelska (Lublin (Ś Upland): Parchatka near Puławy (before 1950/a); Roztocze (Roztocze): Zwierzyniec (1908/a), Kosobudy (1943/a), Ulów (published 1913/a), Hrebenne (1988/r); Nizina Sandomierska (Sandomierz Lowland): Kraków (Rakowice, 1912/a), Grzegórzki (1937/a), Puszcza Niepołomicka (near Koło reserve, 1999/a), Ispina (1993/a), Lipówka reserve (1999/a), near Hysne (1997/a), Dąbrowa (1993/a), Lubasz near Szczucin (1937/a), Bukowiec near Szczucin (1938/a), Tarnów (before 1950), Kotowa Wola near Zaleszany (1879), Rozwadów near Stalowa Wola (before 1950), Rzeszów and vicinity (before 1869), Jarosław (1973/a), Przemyśl (1985/a); Sudety Zachodnie (West Sudetes): Jelenia Góra–Cieplice (1999/r); Beskid Zachodni (West Beskid): Skoczów (2001/a), Pierściec near Skoczów (2000/a), Żywiec (1985/a), Jeleśnia (1967/a), Śleszowice (1990/a), Brzeźnica near Wadowice (1982/a),

Ranius et al.

Appendix. (Cont.) Kalwaria Zebrzydow. (1944/a), Kraków (Rżąka, 1998/a), Sieraków near Dobczyce (1909/a), Fałkowice near Gdów (1927/a), Stadniki (1992/a), Melsztyn (1997/a), Lipnica Murowana (1994/a), Bieśnik (about 1970/a), Zakliczyn vicinity (1966/a), Roztoka near Zakliczyn (1987/a), Wróblowice near Zakliczyn (1977/a), Janowice near Pleśna (1986/a), Ciężkowice (1987/a), Nowy Sącz (1933), Popowice near Stary Sącz (2000/a), Tarnowiec (1996/a); Kotlina Nowotarska (Nowy Targ Valley): Zakopane (1922/a); Beskid Wschodni (East Beskid): Kołaczyce (1986/a), Markowa near Łańcut (1984/a), Dukla (1991/a), Barwinek near Dukla (1988/a), Sanok (1970), Przemyśl (before 1885/a). Based on former published data compiled by Burakowski et al. (1983) and Szwałko (1992b), recent literature (Borowski, 1993; Chmielewski et al., 1996; Burakowski, 1997; Kalisiak, 1997; Krell, 1997; Szafraniec & Szołtys, 1997; Kowalczyk & Zieliński, 1998; Rębiś, 1998; Zając, 1998; Byk, 1999) recent field inventories (Oleksa et al., 2003), and surveys of museums (Museum and Institute of Zoology PAS, Warszawa; Museum of Natural History, Institute of Systematics and Evolution of Animals PAS, Kraków; Upper Silesian Museum, Bytom; Department of Forest Entomology, Agricultural University, Poznań) and private collections. Rumania Braș ș ov: Brașov (before 1912), Cincu (before 1912); Cluj: Cheile Turzii (1969), Baciu (Cluj–Napoca, 1994); Dolj: Caracal (1969), Bucovăţ (1968), Lintesti (1967), Leamna (1969), Racoviţă (1985), Craiova (1968, Banu Mărăcine, 1968), Negoiu (1966), Salcia (1970); Gorj: Cărbunești (1967), Cheile Sohodol (1999), Tismana (1965); Hunedoara: Haţeg (before 1912), Deva (before 1912), Brad ș : Sighișoara (before 1912), (before 1912); Mehedinţţ i: Olănești (1954), Schitu Topolniţei (1992); Mureș Reghin (before 1912), Sibiu: Sibiu (before 1912), Făgăraș (before 1912), Mediaș (before 1912). Based on literature (Petri, 1912; Fleck, 1904–1906; Tauzin, 1994b; Sparacio, 2001) and unpublished records. Russia Kaliningrad region: Kaliningrad (1992/a), Pravdinskyi district (Podlipovo village, 1994/a), Chernjakhovsk (1997), Polessk district (1985–1995/a); Leningrad region: Luga district (Ploskoye Manor, 1916/a, Preobrazhenskaya railway station, 8 km down the Luga River, 1915/a, Tolmachyovo railway station, 1995/a), Apraksin Bor village near the border to the Novgorod region (1960–80); Novgorod region: Chudovo (1975/a); Moscow region: Podolsk district (Drovnino, 1950/a), Pokrovskoye village (1930–1950/a), Serpukhov (1935–1955/a), Serpukhov district (Luzhki village vicinities, 1993/a), Serpukhov district (Prioksko–Terrasny Reserve, 1992–93/a), Ozyory district (near Belyye Kolodezi village, ?1993), Kashira (1986); Kaluga region: Kaluga (1912/a), Krasnaya Gorodnya (mid–1930’s/a), Tarusa (1954/a), Kozelsk district (Podborki village vicinities on the right bank of the Zhizdra River near the border of Tula region, 2002/a), Petrovskoye village (1929/a); Tula region: Tula (1920’s/a ), Mishnevo (1950–2000/a), Okorokovo (1950–2000/a), Cherepet (1950–2000/a), Orlovo (1950–2000/a), Selivanovo (1950–2000/a), Kosaya Gora (1950–2000/a), Yasnaya Polyana (1950– 2000/a), Leninsky (1950–2000/a), Dalmatovka (1950–2000/a), Yegnyshevka (1950–2000/a), Velegozh (1950–2000/a), Khoroshevka (1950–2000/a), Komarki (1950–2000/a), Rassvet (1950–2000/a), Bolshoye Triznovo village vicinities, north from Krapivna (1950–2000/a), Yefremov district (south from Koltsovo, 1930’s/a), Plavsk district (Molochnyye Dvory village, 1984/a); Ivanovo region: Yuzha district (Kholuy settlement, 1987/a); Pestyaki district (the Lukh River bank, Demidovo village vicinities, 1997/a); Ryazan region: Ryazan (1970/a), Ranenburg district (St. Kassatkina, 1900–1950), Dankov district (Gremyachka, 1930–60/a), Oksky Reserve (1990–2000/a), Shatsk district (Kashirino village, 1985– 2000/a); Mordoviya republic: Mordovsky Reserve (1950–1990a); Tatarstan republic: Kazan (1900– 1950/a), Zelenodolsk district (Raifskoye Forestry, 1980–1995/a), Laishefsk district (Saralovskoye Forestry, 1995/a); Nizhny Novgorod region: Vetluga district (Kaksha River, 1950–80/a); Ulyanovsk region: Bolshoy Kuvay village vicinities, in a floodland wood on the Sura River bank (1967/a), Poljanki village (1950–1990/a), Inzenskij district (Argash village, 1950–1990/a); Voronezh region: Ostrogozhsk district (Shubnoe village vicinities, 1963/a), Borisoglebsk and Tellerman forestry, 1970– 1997/a); Penza region: Penza (1900–1950/a), Nizhnelomskyi district (3 km NW from Golitsino, 1999); Samara region: Zhigulyovsky Reserve (Bakhilova Polyana village vicinities, 1999/a,); Saratov region: northwestern parts of the region near the borders of Voronezh, Tambov and Penza regions (1980–1995/a); Bashkortostan republic: Ufa district (1989/a), Birsk (1918/a), Nagayevo village

Animal Biodiversity and Conservation 28.1 (2005)

Appendix. (Cont.)

(1988/a); Voronezh region: Ostrogozhsk district (Shubnoe village vicinities, 1963/a), Borisoglebsk and Tellerman forestry, 1970–1997/a); Belgorod region: reserve "Belorechiye", 1985–2002/a, vicinity of Valujki, 1975/a; Chuvashiya republic: Morgaushi district (Kadikasy village, 1900–1950/a), Shemursha district (Asanovo village vicinities (1900–1950/a), Transvolga, Cheboksary district (Kuvshinka, 1900–1950/a, Khyrkasy village vicinities, 1900–1950/a, Cheboksary city and its vicinities, 1960–1985/a, Proletarsky settlement vicinities, 1980–2000, Tokhmeyevo village vicinities, 1980– 2000/a, Shomikovo village vicinities, 1980–2000/a), Novocheboksarsk city and its vicinities (1980– 2000/a), Morgaushi district (Ilyinka village vicinities, 1980–2000); Shumerlya district (Lake Urgul vicinities,1980–2000/a), Alatyr district (4.5 km SWW from Atrat village, 1980–2000/a, Ivankovo– Lenino village vicinities, 1980–2000/a, Alatyr vicinities, 1980–2000/a, across the river near Sursky Maydan village, 1980–2000/a, 7 km SE Ivankovo–Lenino village, 1980–2000/a, Mezhdurechye village, 1980–2000), Kozlovka district (village Kurochkino vicinities, 1980–2000), Yantikovo district (Indyrchi village vicinities, 1980–2000/a, Chuteyevo village vicinities,1980–2000/a), Tsivilsk district (Taushkasy village vicinities, 1980–2000/a), Kanash city vicinities (1980–2000/a), Mariinsky Posad city (1980–2000/a), Mariinsky Posad district (8 km east from Novocheboksarsk city, 1980–2000/a), Mariinsky Posad district (Sotnikovo village vicinities, 1980–2000/a), Mariinsky Posad district (Yuryevka village vicinities, 1980–2000/a) Mariinsky Posad district (Anatkasy village vicinities, 1980–2000/a), Poretskoye village vicinities, across the Sura River (1980–2000/a); Mari El republic: the "prisurskikh" broad–leaved forests near the lake Tair (1991), flood–lands of the river of Bolshaya Kokshaga, lower Storozhilsk (2000), Gornomariysky district (Novaya Sloboda village vicinities, 1985–2002/a), Transvolga, 2 km south from Kokshamary (1985–2002); Udmurtiya republic: Vavozh district (Gulyayevskoye village, the Vala River floodland, 1990–2002/a, Vavozh village, the Vala River floodland, 1990–2002/a), Kizner district (Krymskaya Sludka village, the Vyatka River floodland, 1990–2002/a), Alnashi district (Kuzebayevo village southern slope, 2002), Malaya Purga district (Malaya Purga village, the Postolka and the Izh common floodland (1990–2002/a), Izhevsk city (1960’s); Kirov region: Kilmez district (Tautovo village, floodland in the Kilmez River valley, 1990–2000, Karmankino village, floodland near the mouth of the Vala, 1990–2000), Malmyzh (1900–1950); Orenburg region: Buzuluk district (Beloyarka vicinities, 1900–1950/a); Krasnodar region: Yeysk (1900–1950); Adygeya republic: Maykop region (1900–1950); Stavropol region: southern part of the region (1980–2000). When time intervals are given it means that time for the last finding is uncertain. Based on data from specimens in museums (especially Zoological Museum of Moscow Lomonosov state University, Zoological Institute RAN in St. Petersburg) and private collections compiled in 1982–2002. There were about 200 specimens collected from 112 localities since 1870. Data also from literature: Ananyeva & Blinushov ( 2001), Anikin (1996), Baldaev (2002), Bolshakov & Dorofeev (2002), Borisovsky (2001), Kozlov & Oliger (1960), Krasnobayev et al. (1992), Krivokhatsky (2002), Lebedev (1906), Medvedev (1960), Muravickij & Kanitov (1995), Sigida (2002), Egorov (1994, 1995, 1996a, 1996b, 1996c, 1997, 1998a, 1998b, 1999, 2000a, 2000b, 2000c, 2001), Gusakov (unpubl. data) and Dedukhin (unpubl. data.) Serbia and Montenegro Serbia: Avala (1941), Fruška gora (year?), Kopaonik–Šanac (1956), Kragujevac (1948), Majdanpek (before 1956), Peć (1909), Rogot (1905), Ruma (year?), Valjevo (1963), Veliko Gradište (1956), Paraćin (1918), Zlatibor (1929); Montenegro: Radović (1918), Sutorman (before 1956), Vuča (1951), Glavatičići (1977). Based on literature (Mikšić, 1955, 1957; Sparacio, 2001). Slovakia (Recent records include a few specimens of both adults and larvae) Banska Bystrica: Banska Bystrica town (1986); Banska Stiavnica: Banska Stiavnica town (1992); Bratislava: B–Petrzalka–Lido (1992–1993), B–Lamac (1995–2002), B – Raca (1995–2002), Devinska Kobyla (1995–2002), Kopac (1995–2002), Ivanka pri Dunaji (1995–2002), Jur pri Bratislave (1995– 2002), NR Jursky Sur (1995–2002); Dunajska Streda: Gabcikovo (1977), Dunajska Streda (1995– 2002); Galanta: Galanta (1995–2002); Krupina: Krupina (1936), Dobra Niva (1995–1997); Levice: Batovce (1936), Kalna nad Hronom (1974, 1 spec. coll. Levice museum), Levice (1995–2002), Cajkov (1995–2002); Lucenec: Lucenec (1936), Filakovo (1994); Malacky: Plavecky Stvrtok (1990), Malacky

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Appendix. (Cont.)

(1995–2002), surroundings of Morava river (1995–2002); Nitra: surroundings of Nitra (1990–1995); Pezinok: Pezinok (1995–2002), Modra (1995–2002), Pila (1995–2002); Rimavska Sobota: Rimavska Sobota (1994), Gemer (1936); Sahy: Plastovce (1995–2002); Senec: Senec (1995–2002); Sladkovicovo: Sladkovicovo (1995–2002), Puste Ulany (1995–2002); Smolenice: surrounding forests (1995–2002); Solosnica: Plavecke Podhradie (1995–2002), Plavecky hrad (1995–2002), Plavecky Mikulas (1995– 2002), Prievaly (1995–2002); Stupava: (1995–2002); Sturovo: Muzla (1936), Kamenica nad Hronom (1995–2002); Trencin: Motesice (1936); Velky Krtis: Modry Kamen (1936). Older records are based on the literature (Roubal, 1936), the latest records come from nine Slovakian entomologists. Especially Milan Strba has given much information. Slovenia Trenta (1967), Koper (1932), Trnovo ob Soči (1990), Ajdovščina (1900), Kodreti (2003/a), Bohinj (1923), Bohinj (Ukanc, 1996/a), Bohinj (Ribčev Laz, 1934, Voje valley, 1930, Bohinjska Češnjica, 1931), Nomenj (1877), Mojstrana (Kot, 1936), Radovljica (1886), Brezje pri Dobrovi (1980/a), Ljubljana (1953), Ljubljana–Tivoli (1991), Ljubljana–Mestni log (1890), Dragomelj (Lukovica pri Brezovici, 1988), Kamnik–Center (2000/r), Kamnik–Graben (1999/r), Zgornji Tuhinj (1957), Dolenjske Toplice (Soteska, 1912), Mokronog (1952), Rekštanj (1911), Brežice (1933), Kalobje (1927), Podčetrtek (1931), Gornja Radgona district (1875); Records with no detailed locality given: "Carniolia" (1763, 1866, 1911), "Steiermark" (1871). Based on specimens in the Slovenian Museum of Natural History (PMSL) and collection of the Institute of Biology ČSR SASA. The data were obtained also from literature (Scopoli, 1763; Siegel, 1866; Brancsik, 1871; Martinek, 1875; Mikšić, 1955) and personal communications with several entomologists. Spain Álava: Heredia (2001); Barcelona: Macizo del Montseny (1945); Cantabria: Camaleño (Llaves, 1996); Gerona: mentioned for the province without giving any specific locality; Huesca: Valle de Ansó (1983), Valle de Hecho (1982), San Juan de la Peña (1960); León: Soto de Sajambre (1980); Lérida: Valle de Arán (1962); Navarra: Andía, Aralar, Valle de Lana, Valle de Santesteban, Regata del Bidasoa; La Rioja: Villoslada de Cameros; Guipuzcoa: Aralar Natural Park near Beasain (Ezkalusoro, 2003/a). Based on literature (Montada Brunet, 1946; Baguena Corella, 1967; Galante & Verdú, 2000; Bahillo de la Puebla et al., 2002; Ugarte San Vicente & Ugarte Arrue, 2002; San Martín et al., 2001; Martinez de Murguia et al., 2003). Sweden Blekinge: Karlshamn: Stensnäs (1997/a), Tärnö (2001/e); Karlskrona: Agdatorp (1998/e), Arpö (1997/a), Gullberna (1997/a), Haglö (2000/a), Karlskrona stad (2000/e), Lorentsberg (2000/a), Lyckeby ekbacke (2000/a), Kummelns gravfält, Augerum (1998/a), Marielund (2000/e), Stora Boråkra (1997/e), Stora Vörta, Skärva NR (1998/a), Verkö (2001/a); Ronneby: Almö (1995/a), Aspan (1997/r), Blötö (1998/r), Förkärla–Vambåsa (1998/r), Grindstugan (2001/a), Göhalvön (1998/a), Kvalmsö (1998/e), Vångsö (1997e), Hundsören (1997/e), Johannishus–åsarna (2001/ a), Slädö (1998/a), Tromtö (2001/a), Östra Råholmen (2000/r), Vagnö (1998/a), Vambåsanäs (2001/a), Vermansnäs (1998/a); Sölvesborg: Valje halvö (1998/a). Halland: Kungsbacka: Börsås, Rossared (1999/a); Laholm: Hasslöv (1758/a); Jönköpings län: Tranås: Ekberget, Tranås (1998/ e), Näs, Valen (1998/e), Åbonäs (1998/e), Botorp at Noen (1997/a); Kalmar: Borgholm: Böda prästgård (1995/e), Halltorps hage (1997/a), Högsrum, Ekerum (1940/a); Emmaboda: Vissefjärda kyrkby (1999/a): Högsby: Barnebo–Böta kvarns area (1999/a), Fagerhults prästgård (1999/r), Flasgölerum (1999/a), Hultsnäs inäga, Hornsö kronopark (2001/r), Hornsö (Hundströmmen–Strömsholm) (2001/r), Långemåla kyrka (1999/a), Långemåla (Ruda lund–Åsebo) (1999/a), Sjötorp, Hornsö (2000/a), Ullefors, Hornsö (2001/r), Värlebo (1999), Sadeshult (2000/e): Kalmar: Björnö (1995/a), Halltorp (1947), Kristinelund (1996/e), Lindö (1996/a), Värnanäs (1996/e), Värsnäs (2000/a): Nybro: Madesjö area (1999/a), Nygård–Koppekull (2000/r); Oskarshamn: Oskarshamn (1997/r): Mönsterås: Ems herrgård (1995/a), Strömserum (1997/a), Södra Skärshult (1995/a): Västervik: Sandvik–Lövvik (1998/e), Forsby (1998), Ankarsrums säteri

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Appendix. (Cont.)

(1997/a), Blekhem (1997/e), Dynestad (1998/a), Garpedansberget, Gamleby (1998), Vinäs, SE from Ukna (1998/e), Grundemar (1997/r), Gränsö (1997/a), Hammarbadet, Gamleby (1997/e), Helgerums slott (1997/a), Hjortkullen (1998/e), Hummelstad gård (1997/r), Kasimirsborg, Gamleby (1997/a), Norringe, Odensviholm (1997/a), Piperskärr, Gränsö (1998/a), Holmhult, Rånestad (1997/a), Stjärneborg, Blankaholm (1998/e), Värmvik, Segersgärde (1997/e),: Kronoberg: Ljungby: Toftaholm (1998/a), Engaholms gods (1996/r), Hovmantorps säteri (2000/a), Byvärma (1987/e), Yxkullsund (1997/a); Skåne: Båstad: Hallands Väderö (2002/a): Eslöv: Vedelsbäck, Stehag (1897/a); Hässleholm: Mölleröds kungsgård (1998/e), Sörbytorp (1998/a); Hörby: Fulltofta (1995/r); Höör: Bosjökloster (1994/r); Klippan: Herrevadskloster (1850/r); Kristiansstad: Hanaskog (1998/a), Torsebro (1998/a), Vanås gods (1998/a), Trolle–Ljungby (1881); Lund: Degerberga gård, SV Häckeberga (1998/a); Simrishamn: Esperöd (1860/a); Sjöbo: Bellinga gods (1970’s/a, 1998/e), Övedskloster (1998/a); Svedala: Kråkenäs, Torup (1998/r); Tomelilla: Örup (1936/a); Stockholm: Värmdö: Stäksjön, Gustafsberg å Werdön (1884/a); Södermanland: Flen: Lagmansö (1998/a), Sparreholm (1996/a), Mjälby kvarn (1994/a), Tuna (1995/a); Strängnäs: Aspö (2001/a); Harpsund (2001/a), Hjorthagen, Gripsholm (1997/a), Strängnäs (a); Gnesta: Herröknanäs (1997/a); Nyköping: Djurgården, Åboö at Båven (1997/r); Uppsala: Enköping: Fånö (2000/e), Hacksta, Sävsta äng (2000/r), Sisshammarsviken (1998/e), Strömsta (2001/r); Håbo: Hjulsta säteri (1996/a), Biskops Arnö (2002/a): Uppsala: Viks slott, Balingsta (2001/r): Västmanland: Hallstahammar: Billingen, Strömsholm (1960’s/a), Österängen, Strömsholm (1997/r), Tidö slott (1960’s/a); Kungsör: Kungsör (1996/r); Västerås: Fullerö (1969/a), Ryttern (1952/r), Ängsö slott (2000/r); Västra Götaland: Alingsås: Alingsås (1884), Vikaryd (1996/e), Östad (2001/r); Borås: Backa NR, Ljushult (1996/r); Götene: Hjälmsäter, Kinnekulle (1997/r), Munkängarna, Kinnekulle (1997/r); Härryda: Råda säteri (1978/r); Lerum: Gullringsbo, Aspens station (1998/a), Lerum (1999/a), Nääs, Öjared and Kärrbogärde (1998/a), Östra Öjared, (1996/r); Skara: Öglunda (a); Skövde: Lilla Kulhult, Lerdala (1997/r), Lerdala gård (1997/e), Sparresäter (1995/r); Tanum: Krageröd (1996/a): Tranemo: Hofsnäs–Torpa (1998/a), Länghem (1955/a); Trollhättan: Häggsjöryr (1996/r); Uddevalla: Gullmarsbergs säteri (1996/r); Vänersborg: Fristorps Gransjö, Hunneberg (1996/r), Storeklev, Hunneberg (1996/e), Västra Tunhem (1995/a); Örebro: Hallsberg: Broby äng (2000/a), Geråsen, Viby (1998/r), Nalaviberg (1996/a), Värnsta (1998/a), Ekåsen, Bärstad (1996/a); Lekeberg: Trystorps ekäng (1998/r); Östergötland: Boxholm: Boxholms säteri 2000/e), Lagnebrunna (1997/r), near Svartån–Lillån (2000/e); Finspång: Ekön (1998/a); Kinda: Västra Eneby (1997/a), Söderö (1996/a), Kisa (1931/a), Kleven, south from Ämmern (2000/r), Vada (1996/a), Kopperarp (1997/e), Stormtorna and Väsby, Oppeby (1996/a), Norrö (1996/a), Valla and Aska, Hägerstad (1996/a), Ryttaresten, Medelö (1996/a), Råsö (1996/a), Räckeskog, Hamra and Bällinge (1997/a), Röberga (1996/r), Sommenäs ekängar (1934/a), Tempelkullen (2002/a); Linköping: Smedstad (1996/a), Bestorp (1949/a), Bjärka–Säby (1998/a), Brokinds skola (1998/a), Gunnarsbo (1994/e), Kvillabro (1995/e), Labbenäs, Stafsäter (1995/a), Sätra, Göttorp and Mårstorp) (1998/a), Norrhagen, Örtomta (1997/e), Norrängen, Bestorp (1998/e), Ringetorp (1990/e), Skaggebo (1998/a), Skeda (1952/a), Sturefors (1998/a), Sveden, Landeryd (1999/a), Tinnerö (1997/a), Tomåla (1990/e), Vårdnäs (1995/a); Mjölby: Solberga (1995/a); Norrköping: Borg (1996/a), Ryttaretorpet (1997/e), Bråborg (1995/a), Roteberg (1997/e), Kimstad (1997/e), Stora Runken (1997/e), Händelö (1995/a), Hästö, Arkö (1990/a), Norrköping (Ingelsta, Vilhelmsberg) (1997/a), Norrköping (Ektorp, Fiskeby and Leonardsberg) (1995/e), Jämjö (1999/e), Krusenhov (1998/a), Kvillinge (1997/e), Ljusfors, Skärblacka (1996/a), Löfstad slott (2000/a), Mauritzberg (1997/e), Malmölandet (2001/a), Mem (1890/a), Viaborg (1997/e), Norsholm (1996/a), Ravsnäs (1999/a), Rundstorp (1997/a), Almstad, Tingstad (1997/e), Ugglö, Kättinge (1997/e), Ågelsjön (2001/e), Asplången (1997/e); Söderköping: Djursö (1997/a), Drothem (1952/e), Eknön (1997/a), Gäverstad (1999/r), Jätteberget (1998/e), Korsnäs (1998/a), Ramsdalskorset (1997/e), Torönsborg (1956/a), Simpholmen (2002/r), Stegeborg (1998/a), Ängelholms gods (1997/a); Valdemarsvik: Breviksnäs (1995/e), Ekeberga, Östra Ed (1997/e), Fyllingarum (1997/e), Fågelvik, Finntorps borgruin (1997/a), Gryt (1997/e), Gusum (19th century/a), Harsbo–Sverkersholm (1997/a), Kvädö–Åsvikelandet (2002/r); Ydre: Rosebo, Torpön (1997/a), Smedstorp (1997/e), Sund (1996/a), Torpa (1997/a): Åtvidaberg: Bredal, Hannäs (1997/r), Ekhult– Skärdala (1997/a), Hägerstad slott (1997/a), Orräng (1995/a), Torp (1996/a), Åtvidaberg (Adelsnäs, Slefringe and Åtvidsnäs) (1997/a), Östantorp, Yxnerum (1997/e): Ödeshög: Älvarums udde, Omberg (1994/a, 1997/r). Based on a recent publication (Antonsson et al., 2003) which collects data from field inventories, literature, specimens in Swedish museums and personal communication.

Ranius et al.

Appendix. (Cont.)

Switzerland Basel–Landschaft: Allschwil (1960); Basel–Stadt: Basel (1847); Bern: Siselen; Fribourg: Fribourg (1935), Genève: Chêne–Bougeries (1906), Chêne–Bourg (1916), Collonge–Bellerive (1947), Dardagny (1961), Compesières near Genève, Malagnou near Genève (1956), Cologny near Genève (1918), Jussy, Plan les Ouates, Vernier (1921); Graubünden: Campascio near Brusio (1998), Chur (1864); Schaffhausen: Neuhausen–Rheinfall; Solothurn: Solothurn (2002), Langendorf (1967); St. Gallen: St. Gallen (before 1870), Sargans (before 1870), Werdenberg (before 1870); Ticino: Chiasso (1907), Lugano, Sonogno (1967); Vaud: Lausanne, Commugny (1947), Cudrefin, Gimel, Ollon (1887); Valais: Valère near Sion (1855), Brig–Glis; Zürich: Sihlfeld near Zürich (1862), Bülach (1893), Zürich (1919). Based on data from the specimens in Switzerland’s museums and many private collections. There have been no more than 80 specimens collected in Switzerland during the last 150 years. Turkey Edirne Ili: KeÕan (1994/a). Ukraine Chernihiv region: Khlopianyky (year?), Kozlianychi (2003), Novi Mlyny (1987), Yaduty (2001); Donec’k region: Donec’k (1935), Slovianohors’k (2003); Ivano–Frankivs’k region: Kolomyia (before 1900), Kolomyia (year?), Kosiv (year?); Kharkiv region: Merefa (1957); Khmel’nyts’kyi region: Kamianec’’– Podil’s’’kyi (1995); L’viv region: Hordynia near Sambir (1933), L’’viv (before 1914), Mostys’ka (1883), Sambir (before 1900), Zavadivka near Sambir (1933).; Odesa region: near Kiliia (2003); Ternopil’ region: Berezhany (1933), Ivankiv (1907), Kulachkivci (year?), Skala–Podil’s’’ka (1906), Ternopil’ (before 1900), Ustia Zelene (1930’s), Zalishchyky; Zakarpats’ka region: Kuzij near Dilove (2000). Based on literature data, specimens in Ukrainian and Polish museums and personal communications.

Animal Biodiversity and Conservation 28.1 (2005)

Identification and conservation application of signal, noise, and taxonomic effects in diversity patterns E. Fleishman

Fleishman, E., 2005. Identification and conservation application of signal, noise, and taxonomic effects in diversity patterns. Animal Biodiversity and Conservation, 28.1: 45–58. Abstract Identification and conservation application of signal, noise, and taxonomic effects in diversity patterns.— Ongoing research on butterflies and birds in the Great Basin has identified biogeographic patterns while elucidating how dynamic measures of diversity (species richness and turnover) affect inferences for conservation planning and adaptive management. Nested subsets analyses suggested that processes influencing predictability of assemblage composition differ among taxonomic groups, and the relative importance of those processes may vary spatially within a taxonomic group. There may be a time lag between deterministic environmental changes and a detectable faunal response, even for taxonomic groups that are known to be sensitive to changes in climate and land cover. Measures of beta diversity were sensitive to correlations between sampling resolution and local environmental heterogeneity. Temporal and spatial variation in species composition indicated that spatially extensive sampling is more effective for drawing inferences about biodiversity responses to environmental change than intensive sampling at relatively few, smaller sites. Key words: Adaptive management, Beta diversity, Great Basin, Monitoring, Nestedness, Species richness. Resumen Identificación y aplicación en la conservación de los efectos señal, ruido y taxonómicos en patrones de diversidad.— Los estudios de mariposas y aves en el Great Basin han identificado patrones biogeográficos que permiten evaluar cómo las medidas dinámicas de biodiversidad (riqueza específica y renovación de especies) pueden afectar la planificación y la gestión adaptativa de la conservación. El análisis de subgrupos anidados sugiere que los procesos que influyen en la predicibilidad de la composición de los grupos difieren entre los distintos grupos taxonómicos. Asimismo la importancia relativa de estos procesos puede variar espacialmente dentro de un grupo taxonómico. Puede haber un retraso en el tiempo entre los cambios ambientales deterministas y una respuesta faunística detectable, incluso para los grupos taxonómicos que se sabe que son sensibles a los cambios del clima y de la cubierta del suelo. Las medidas de diversidad beta eran sensibles a las correlaciones entre la resolución del muestreo y la heterogeneidad ambiental local. La variación espacial y temporal en la composición de especies indicó que el muestreo extensivo en el espacio es más efectivo, para obtener inferencias sobre cómo responde la biodiversidad a cambios ambientales, que el muestreo intensivo, en relativamente pocos sitios y más pequeños. Palabras clave: Gestión adaptativa, Diversidad beta, Great Basin, Control, Anidamiento, Riqueza específica. (Received: 5 II 04; Conditional acceptance: 12 V 04; Final acceptance: 25 V 04) Erica Fleishman, Center for Conservation Biology, Dept. of Biological Sciences, Stanford Univ., Stanford, CA 94305–5020 U.S.A. E–mail: efleish@stanford.edu

ISSN: 1578–665X

Introduction Conservation planning is motivated and directed by evidence that native species, assemblages, and ecological functions are responding to deterministic environmental change (Scott et al., 1987, 1993; Stein et al., 2000). Human land uses such as urbanization and agriculture frequently drive the environmental changes of greatest concern to conservation biologists (Czech et al., 2000; Lockwood & McKinney, 2001). In order to implement adaptive management, we also must evaluate the biological effects of landscape reconstruction, restoration, and directed efforts to conserve species and ecosystems (Meretsky et al., 2000; Lake, 2001). Meanwhile, in the decision–making arena, credible data on ecological responses to climate change have proven essential for influencing environmental policy (Easterling et al., 2000; Schär et al., 2004). Survey and monitoring data sometimes reveal substantial changes in measures of biodiversity and ecosystem function across space or time, but those changes may reflect dynamic processes rather than observational or experimental treatments per se. Diversity metrics (including species richness, abundance, evenness, and so forth) are infamously dependent on the spatial and temporal scale of measurement and on life history. For example, the size of each sampling unit (sampling resolution), the configuration of sampling units across the landscape, and the spatial extent of the area from which samples are drawn affect inferences regarding number of species (henceforth, species richness) and identity of species (henceforth, species composition) (Noss, 1983; Wilson & Shmida, 1984; Conroy & Noon, 1996). Geographic coordinates and context also matter. For instance, species richness often increases along ecotones (Risser, 1995), at intermediate levels of disturbance (Petraitis et al., 1989), and at intermediate points along abiotic environmental gradients (Fleishman et al., 1998; Colwell & Lees, 2000). Scale dependencies in diversity patterns bear on a wide range of conservation applications, from identification of mechanisms that generate and maintain species richness to exploration of relationships between species diversity and ecological function (Waide et al., 1999; Willis & Whittaker, 2002). Scaling issues related to species richness and composition also have a taxonomic component. Species perceive and react to their environment as a function of life–history characteristics including resource requirements, mobility, and body size (Addicott et al., 1987; Kotliar & Wiens, 1990; Mac Nally, 2005). In theory, therefore, the spatial and temporal resolution and extent of sampling should be dictated by the ecology of the taxa under investigation. In reality, however, sampling designs frequently reflect logistic constraints. The resolution and extent of sampling for multi–taxonomic studies commonly is established using a single survey design bounded by human conventions, such as administrative boundaries or land–use types. But a

Fleishman

uniform sampling framework is unlikely to be meaningful for understanding diversity patterns in all taxonomic groups of interest because it confounds the components of diversity. For some species a given sampling resolution will estimate only the alpha component of richness (the mean number of species within a local community) while for other species it will estimate both the alpha and beta (between–habitat diversity) components. Nonetheless, empirical ecological and biogeographical research can be designed to quantify effects of scale and life history in addition to effects of environmental change. For the past decade, my colleagues and I have quantified diversity patterns in assemblages of butterflies and birds in the Great Basin and Mojave Desert in order to elucidate deterministic and stochastic influences on patterns of species richness and composition, dependence of those patterns on temporal and spatial scale and life history, and practical sampling approaches most likely to provide valid inferences about ecological responses to an array of environmental changes. Butterflies and birds also are well–known ecologically, relatively easy to study and monitor, and popular with the general public. In addition, various measures of the species diversity or occurrence of butterflies and birds frequently have been proposed as a surrogate measure of the status of each other, of other taxonomic groups, and of environmental variables (Temple & Wiens, 1989; New et al., 1995; Chase et al., 1998; Blair, 1999; Swengel & Swengel, 1999; O’Connell et al., 2000). The Great Basin and Mojave are well suited for examining issues of scale and sampling associated with many types of diversity patterns. Desert ecosystems are thought to be highly responsive to major environmental changes including shifts in temperature and precipitation, invasion by non– native species, and altered disturbance regimes (Sala et al., 2000; Smith et al., 2000). In addition, approximately 75% of the Great Basin and Mojave is managed by federal and state resource agencies for sustained multiple uses ranging from conservation to recreation to production of renewable and non–renewable commodities. In this paper, I present a synopsis of several approaches we have taken to identify biogeographic patterns and trends in the fauna of the Great Basin while elucidating how dynamic measures of diversity affect interpretation of ecological data in the context of conservation and management. First, I describe our use of nested subsets analyses to determine whether the composition of local assemblages is predictable and to identify abiotic and biotic factors that may be associated with the order in which species are likely to appear and disappear. Second, I summarize how we have addressed the probability of detecting faunal responses to deterministic environmental changes over time. Third, I review our work on the effects of sampling resolution and proximity of sampling locations on inferences about species richness and turnover.

Animal Biodiversity and Conservation 28.1 (2005)

117º 30' 0'' W

117º 0' 0'' W

39º 0' 0'' N

0 5 10

40 km

117º 30' 0'' W

117º 0' 0'' W

38º 30' 0'' N

39º 0' 0'' N

39º 30' 0'' N

Fig. 1. Location of (west to east) the Shoshone Mountains, Toiyabe Range, and Toquima Range in the Great Basin (black rectangle, see inset) and inventory canyons in the three mountain ranges (thick black lines). Two pairs of canyons in the Toiyabe Range and three pairs of canyons in the Toquima Range connect at the crest of the range. Fig. 1. Localización (de oeste a este) de los montes Shoshone, de la cordillera Toiyabe, y de la cordillera Toquima en el Great Basin (rectángulo negro, ver el recuadro) y la relación de cañones de las tres cordilleras montañosas (lineas negras finas). Dos pares de cañones de la cordillera Toiyabe y tres pares de cañones de la cordillera Toquima conectan en la cima de la cordillera.

Methods Our data collection incorporates well–established techniques that reliably detect species presence and permit assessment of distributional trends across space and time. Because these methods have been described in considerable detail in previous publications, along with discussion of sampling adequacy (e.g., Fleishman et al., 1998; Mac Nally et al., 2004), I provide just a brief overview here. Data for our analyses in the Great Basin were collected from 1996–2003 in three adjacent mountain ranges in central Nevada, the Shoshone Mountains, Toiyabe Range, and Toquima Range (Lander and Nye counties) (fig. 1). These mountain ranges have similar regional climate, biogeographic past and ancestral biota, and human land–use histo-

ries (Grayson, 1993). Inventories for breeding birds were conducted in five canyons in the Shoshone Mountains, five canyons in the Toiyabe Range, and six canyons in the Toquima Range. Inventories for resident butterflies were conducted in eight canyons in the Shoshone Mountains, 15 canyons in the Toiyabe Range, and 11 canyons in the Toquima Range. Distances between canyons in these three mountain ranges, and particularly between the canyons we sampled, usually were much greater than the territory or home range sizes of resident butterflies (Fleishman et al., 1997) and birds during the breeding season (Ryser, 1985; Dobkin & Wilcox, 1986). We have collected data on both species occurrence (presence / absence) and abundance; only the occurrence data are presented in this paper.

We divided canyons into multiple contiguous sites (segments) from base to crest. Each site was 100–150 m wide and long enough to span a 100–m change in elevation (Fleishman et al., 1998, 2001b). Mean site length was 1.5 km; more than two–thirds of the sites were longer than 1 km. Inventories for butterflies were conducted from 1995–2003 in 39 sites in the Shoshone Mountains, 102 in the Toiyabe Range, and 54 in the Toquima Range. Inventories for birds were conducted from 2001– 2003 in 24 sites in the Shoshone Mountains, 31 in the Toiyabe Range, and 28 in the Toquima Range. Our sampling locations covered an elevational range of 1872–3272 m and areas from 1.5 ha to 44.4 ha. Using walking transects, a standard, dependable method for temperate regions (Pollard Yates, 1993; Harding et al., 1995), we recorded 65 resident species of butterflies from our study sites. Birds were sampled using point counts (three per season) that spanned the range of dominant vegetation types (Bibby et al., 2000; Siegel et al., 2001; Poulson, 2002). Point counts have been shown to be an effective method of sampling birds in riparian areas in the Great Basin (Dobkin & Rich, 1998; Betrus, 2002). We recorded 79 species of breeding birds from our study sites. Lists of species are available on request. We partitioned the landscape into three hierarchical spatial levels: sites within canyons, canyons, and mountain ranges. Our finest sampling resolution (smallest sampling grain) was the site. A given site was located within a particular canyon within one of the three mountain ranges. To produce species lists at the whole canyon level, our intermediate sampling resolution or grain, we compiled species lists for all contiguous sites within a given canyon. On average, the area of a canyon was six times larger than the area of a site. To produce species lists at the mountain range level, our coarsest sampling resolution or largest grain, we compiled species lists for all canyons that were visited in a given mountain range. Predictability of assemblage composition Nestedness analyses have greatly expanded our capacity to understand biotic patterns across networks of terrestrial or aquatic "islands" of resources or habitat (Wright et al., 1998). A nested biota is one in which the species present in relatively depauperate locations are subsets of the species present in locations that are richer in species (Patterson & Atmar, 1986). Nestedness is a property of assemblages or communities, not of individual species (Wright et al., 1998), and has been interpreted as a measure of biogeographic order in the distribution of species (Atmar & Patterson, 1993). Numerous studies have demonstrated that nested distributional patterns are common across taxonomic groups and ecosystems. Biotas rarely are perfectly nested. Nestedness analyses often cannot identify critical thresholds

Fleishman

of environmental variables with respect to system state or reliably predict the order of species extirpation or colonization. Nonetheless, nestedness analyses are useful as conservation tools because they quantify a widespread ecological pattern and —more importantly— highlight processes, including nonrandom extinction, differential colonization, and nestedness of critical resources, that affect not only species richness but also species composition (Patterson & Atmar, 1986; Simberloff & Martin, 1991; Cook & Quinn, 1995; Lomolino, 1996; Baber et al., 2004). Although even strong correlations between mechanisms or variables and distributional patterns cannot be interpreted as cause– and–effect relationships, those correlations can, at minimum, help refine hypotheses that can be tested with further observations or manipulative experiments (Cook & Quinn, 1995; Kadmon, 1995; Fleishman & Mac Nally, 2002). This aspect of nestedness analysis is especially pertinent to conservation planning because it may help to elucidate whether certain land uses may be responsible for local extinction or colonization events (Hecnar & M’Closkey, 1997; Fleishman & Murphy, 1999; Jonsson & Jonsell, 1999). Presence/absence matrices for nestedness analysis typically are assembled by listing locations as rows in order of decreasing species richness and species as columns in order of decreasing ubiquity. This ordering provides a description of assemblage composition but contributes little toward understanding agents that drive assemblage structure and help us predict species composition across space and time. If one wishes to test whether a particular environmental variable may be related to a nested distributional pattern, then rows instead may be ordered with respect to that variable (Fleishman & Mac Nally, 2002). For example, listing rows in order of decreasing area quantifies the degree to which faunas are nested by area. If an assemblage is nested with respect to a selected environmental variable —or if an assemblage is more nested with respect to one environmental variable than another— it suggests that the variable in question has a non–trivial influence on species occurrence in the assemblage. To test whether assemblages were nested with respect to alternative ordering variables, we computed the relative nestedness index C (Wright & Reeves, 1992) with the program NESTCALC (Wright et al., 1990). We estimated statistical significance using Cochran’s Q statistic (Wright & Reeves, 1992). Values of C vary between 0 and 1.0, approaching 1.0 for perfectly nested matrices. A key advantage of this metric is that it allows for statistical comparison of degree of nestedness among matrices or data sets. Moreover, C is not highly sensitive to matrix size (Wright & Reeves, 1992; Bird & Boecklen, 1998), although nestedness may be more variable when matrices are relatively small (Wright et al., 1998). We used Z scores (standard–Normal variates) to test whether significant differences existed in relative nestedness among matrices (Wright & Reeves, 1992).

Animal Biodiversity and Conservation 28.1 (2005)

Table 1. Relative nestedness of butterflies. Values are one–tailed Z–scores for matrices ordered by different criteria: area and topographic heterogeneity (topo). Values represent the relative nestedness of the row versus the column; positive values indicate higher nestedness and negative values indicate lower nestedness. For example, the Shoshone Mountains matrix ordered by area was significantly less nested than the Toiyabe Range matrix ordered by area: SH. Shoshone Mountains; TY. Toiyabe Range; TQ. Toquima Range; * P [ 0.05; ** P [ 0.01; *** P [ 0.001. Tabla 1. Anidamiento relativo en mariposas. Los valores son puntuaciones–Z de una sola cola para matrices ordenadas con distintos criterios: área y heterogeneidad topográfica (topo). Los valores representan el anidamiento relativo de filas respecto a columnas; valores positivos indican un mayor anidamiento y los negativos, menor anidamiento. Por ejemplo la matriz de los montes Shoshone ordenada por áreas fue significativamente menos anidada que la matriz de la Cordillera Toiyabe ordenada por áreas: SH. Montañas Shoshone; TY. Cordillera Toiyabe; TQ. Cordillera Toquima; * P [ 0,05; ** P [ 0,01; *** P [ 0,001.

SH area SH area TY area

4.68***

TQ area

–3.27***

SH topo

1.31

TY topo

–9.03***

TY area

TQ area

SH topo

–4.68***

3.27***

1.31

9.12***

TY topo

TQ topo

9.03***

–9.12***

–6.67*** 3.89*** –3.89***

TQ topo

Initially, we tested whether nestedness of butterflies and birds in the Shoshone Mountains, Toiyabe Range, and Toquima Range appeared to be influenced by the same environmental variables and whether those patterns were consistent in space. Although the distributional pattern of both taxonomic groups was strongly nested, the environmental variables most closely associated with the nested pattern differed between butterflies and birds (Fleishman et al., 2002a). For example, topography (elevation and local topographic heterogeneity) may help generate nested distributions of butterflies (Fleishman & Mac Nally, 2002). Varied topography tends to create a full gradient of microclimatic conditions, which in turn promotes high species richness of plants that serve as resources for larval and adult butterflies. Varied topography also provide numerous locations for seeking mates (Scott, 1975, 1986) and shelter from extreme weather events. However, topography did not appear to be a reliable correlate of assemblage structure of birds. This result may reflect differences in the specific resource requirements of birds and butterflies in the montane Great Basin. For instance, species richness of birds frequently corresponds to vegetation structure, whereas species richness of butterflies may be more closely associated with vegetation composition (but see Rotenberry, 1985; Mac Nally, 1990). Comparative resource requirements of butterflies and birds in this landscape are addressed in greater detail in the section on beta diversity.

6.67***

–1.51

–6.12*** 1.51

6.12***

Contrary to widespread biogeographic assumptions (Doak & Mills, 1994; Boecklen, 1997), the association between area and nestedness of both butterflies and birds was relatively slight. If area is positively correlated with species richness and a biota is perfectly nested, then species richness should be greater in an extensive, contiguous site than in a collection of smaller sites. Virtually all real biotas have presences and absences that deviate from perfect nestedness, however, and area may or may not be an important correlate of species richness of a nested system (Brown, 1978; Doak & Mills, 1994; Kadmon, 1995; Rosenzweig, 1995; Ricklefs & Lovette, 1999). In an region as climatically erratic and topographically heterogeneous as the Great Basin, critical resources for both butterflies and birds may not be strongly correlated with area. Also contrary to fundamental biogeographic assumptions, we found limited evidence that nestedness of either group was affected by selective dispersal (Fleishman et al., 2002a; see also Bird & Boecklen, 1998). If colonization tends to decrease nestedness (i.e., counter the effects of selective extinction), then less vagile taxonomic groups should be more nested than comparatively vagile groups. But if colonization tends to generate nestedness (Loo et al., 2002), then the more vagile taxonomic groups should be more nested. Results of the relatively few previous comparisons have been mixed (Cook & Quinn, 1995; Wright et al., 1998). There are several potential explanations why

correlations between nestedness and dispersal ability were weak. One possibility is that the spatial resolution of our bird analyses was too small. Limited dispersal of birds between study sites would dilute the effect of differential colonization in generating nestedness in our analyses. Analyses at a larger spatial resolution (full canyons rather than sites), however, produced virtually identical results (Fleishman et al., 2002a). Another possibility is that most resources used by butterflies and birds are present in the majority of the locations that we inventoried, at least during their peak periods of activity. For butterflies (but not for birds), the rank order of mountain ranges with respect to nestedness was sensitive to which environmental variable was used to order the matrices (Fleishman et al., 2002a) (table 1). Order of species occurrence in the Shoshone Mountains and Toquima Range was more closely associated with topography than with area per se, whereas nestedness of butterflies in the Toiyabe Range was better explained by area than as a function of topography. Ecologically, this suggests that the influence of area and topography on species composition of butterflies varies among mountain ranges. The importance of local microclimatic conditions may increase as the availability of water decreases and vegetational resources become less widespread and abundant. We also tested whether distribution patterns of butterfly and bird assemblages appeared to be sensitive to human use of riparian areas, a dominant anthropogenic stressor in the Great Basin (Kauffman & Krueger, 1984; Armour et al., 1991; Dobkin & Rich, 1998). Livestock grazing, recreation, and other activities that reduce water availability and degrade riparian vegetation had little detectable effect on nestedness of butterflies and birds (Fleishman et al., 2002a). At least three explanations seem plausible (Fleishman & Murphy, 1999). First, human modification of riparian areas may not be sufficiently severe to cause local extirpations. Second, species with high vulnerability to changes in the structure and composition of riparian vegetation may already have disappeared. Third, the magnitude of riparian disturbance may not be arranged in a predictable (nested) manner across the region (Hecnar & M’Closkey, 1997). Few studies of nestedness explicitly have compared data on multiple taxonomic groups at the same locations. Our results suggest that the processes influencing even such prevalent assemblage– level distribution patterns as nestedness vary among taxonomic groups. We also found that the relative importance of selected processes can vary spatially, both within and among taxonomic groups. These conclusions serve as a reminder that taxonomic groups are not interchangeable for conservation planning, for monitoring the biological effects of known environmental changes, or for assessing the relative influence of natural and anthropogenic disturbances on native species (Niemi et al., 1997; Simberloff, 1998; Andelman & Fagan, 2000; Fleishman et al., 2001a; Rubinoff, 2001).

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Signal and noise in logitudinal measures of biodiversity Contemporary climate change, invasion of non– native species, and biotic homogenization are motivating efforts to understand the resilience of ecological systems (Easterling et al., 2000; Olden & Poff, 2003). Detection of faunal responses to known environmental changes on the order of years to decades typically is based on longitudinal field surveys in which selected taxonomic groups are monitored across large areas; data on temporal trends are used to guide and adjust land management. Because time and money for biological surveys and monitoring inevitably are limited, it is important to examine whether short–term measures or “snapshots” of species richness and occurrence accurately reflect longer–term patterns (Hanski, 1999; Moilanen, 2000). We used up to six years of survey data from two mountain ranges, the Toquima Range and Shoshone Mountains, to examine whether annual variation in butterfly assemblages over consecutive years reflected an ecologically meaningful trend as opposed to stochastic system dynamics (Fleishman & Mac Nally, 2003). In essence, we aimed to document the apparent signal–to–noise ratio in these assemblages over time. Because our study area did not encompass species’ full geographic ranges, we did not attempt to determine whether the ranges of individual species had expanded or contracted (e.g., Parmesan et al., 1999; Thomas et al., 2001). Instead, we focused on among–site and among–year variation in species richness and species composition, two measures that likely will remain the focus of much biological monitoring on public and private land. We calculated similarity of species composition using the Jaccard index, CJ = j / (a + b – j), where j is the number of species found in all sites and a and b are the number of species in sites A and B, respectively. CJ approaches 1.0 when species composition is identical between sites and 0.0 when two sites have no species in common (Magurran, 1988). A "time lag" refers to the number of years that elapsed between inventories. We calculated similarity of species composition for time lags of one to six years in the Toquima Range and of one or two years in the Shoshone Mountains. For a more detailed description of methods and analyses, see Fleishman & Mac Nally (2003). Mean similarity of species composition of butterflies (i.e., the mean of the site–level values for each mountain range) varied little as a function of time lag (fig. 2). In the Toquima Range, for example, mean similarity of species composition varied by only 0.06 (range 0.43 to 0.49) among time lags of one to six years. Much less of the difference in species composition of butterflies was attributable to turnover of species composition within sites over time than to spatial differences among sites. This pattern was illustrated most clearly in the Shoshone Mountains, where 3% of the difference in species composition was attributable to turnover of species

Animal Biodiversity and Conservation 28.1 (2005)

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Fig. 2. Mean similarity of species composition of butterflies in the Toquima Range (a) and Shoshone Mountains (b) among time lags of one to six years. Error bars are standard error. Fig. 2. Similitud media de la composición específica de mariposas en la cordillera Toquima (a) y los montes Shoshone (b) entre periodos de tiempo de uno a seis años. Las barras de error indican los errores estándard.

composition within sites whereas 74% was attributable to spatial differences among sites. Our results demonstrate that extraction of biotic "signals" from the "noise" of background variation in arid ecosystems is complicated by the severity and unpredictability of weather patterns and various environmental disturbances (Houghton et al., 1975; Rood et al., 2003). Whether measurements of biodiversity at two or more points in time are likely to reflect a bona fide temporal trend as opposed to stochasticity largely depends on two related factors: the extent of deterministic environmental change and the degree of variability characteristic of the biotic assemblage. One potential explanation for the lack of a detectable temporal trend in our data on species composition and species richness of butterflies (despite considerable variability, especially in species composition, between any two given years, Fleishman et al., 2003a) is that during the relatively short duration of our study, there were few if any ecologically significant changes in climate or land cover. For example, in five of the six years of our study, annual precipitation was 20% to 60% below the mean for the past century. However, precipitation from year to year was erratic. For instance, precipitation in 2000 was nearly double that in 1999, despite the fact that both years were relatively dry.

Further, although information on species richness and species composition are among the most practical data to collect in managed landscapes, these measures may not be highly sensitive to environmental changes over years to decades as compared with demographic parameters like abundance and reproduction (Parmesan et al., 1999; Thomas et al., 2001). Population–level measures, however, may be even more prone to random fluctuations than assemblage–level variables. By 2100, substantial environmental changes in the Great Basin are anticipated, ranging from anthropogenic climate change to modified disturbance regimes to expansion of non–native invasive species (Chambers & Miller, 2004). But detection of faunal responses to such changes is likely to be complicated by high background levels of local turnover in species composition. Moreover, biological responses to environmental change may depend in part on the speed at which those changes occur (Grayson, 2000) and whether variance in environmental conditions also increases (McLaughlin et al., 2002). Our work emphasizes that at minimum, there may be a time lag between deterministic changes in climate or land cover and a detectable faunal response that can be used to guide management.

Response of beta diversity to spatial scale Most work on scaling issues associated with diversity patterns has concentrated on species richness. In part because counting species is logistically more feasible than collecting detailed demographic data, species richness has been used as a variable to help prioritize conservation efforts (Scott et al., 1987; Myers et al., 2000) and to measure biological responses to natural disturbance processes, human land use, and alternative management actions at numerous spatial extents (Chapin et al., 2000). Beta diversity (betweenâ&#x20AC;&#x201C;habitat diversity), which increases as a function of turnover in species composition among communities, most often has been considered in terms of its contribution to species richness of a heterogeneous landscape (MacArthur, 1966; Whittaker, 1977; Lande, 1996). For example, the technique of additive partitioning uses a hierarchical model of landscape organization (Allen & Starr, 1982) to represent species richness at each nested level of a landscape as the sum of alpha diversity (the mean number of species within a local community) and beta diversity at the next lower level (Lande, 1996; Wagner et al., 2000; Gering et al., 2003). After discovering that turnover of species composition within sites over time accounted for much less of the difference in species composition of butterflies in the Great Basin than did spatial differences among sites (Fleishman & Mac Nally, 2003), we decided it would be useful to explore relationships between beta diversity and spatial scale more thoroughly. Accordingly, we focused directly on whether beta diversity of butterflies and birds in the Great Basin depended on sampling resolution and the proximity of sampling units across the landscape (Mac Nally et al., 2004). We also examined the taxonomic component of scaling issues by comparing how species composition of butterflies and birds responded to sampling resolution and proximity. We calculated mean similarity of species composition, using the Jaccard index, for each sampling grain in turnâ&#x20AC;&#x201C; sites, canyons, and mountain ranges. We found that variation in species composition of butterflies and of birds could be explained as functions of both spatial resolution of sampling and relative distances among sampling units across the landscape (Mac Nally et al., 2004). Similarity of species composition increased as the sampling resolution decreased (i.e., as grain increased), with more than 85% of the variation in similarity values for both taxonomic groups attributable to sampling resolution. This result almost certainly reflects the effect of local environmental heterogeneity on species composition. Highâ&#x20AC;&#x201C;resolution sampling in a relatively heterogeneous landscape tends to emphasize differences in species composition along gradients of resource availability, topography, or microclimate. As sampling resolution increases, species composition may reflect emerging similari-

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ties in terms of regional climate, land cover, and land use, and biotic assemblages will appear more homogeneous. Irrespective of sampling resolution or taxonomic group, similarity of species composition decreased as the biogeographic separation between sampling units increased. Although the effect of relative proximity was statistically substantial, however, the absolute difference in species composition in response to relative proximity was modest. For example, assemblages of birds were 14% more similar, and assemblages of butterflies were 8% more similar, when canyons were located in the same mountain range than when canyons were located in different mountain ranges. These results probably reflect the extraordinarily high variability in topography in our study system. Although there are relatively few major land cover types in the Great Basin, they are distributed in a remarkable array of local vegetational mosaics. Almost every canyon remains an "island" with a distinct character. Thus, a randomly selected pair of canyons within the same mountain range may not be much more similar than a randomly selected pair of canyons from two nearby mountain ranges. The effects of relative proximity of sampling units across the landscape were not uniformly greater for either butterflies or birds (Mac Nally et al., 2004). As we compared the effects of spatial grain on beta diversity of butterflies and birds, however, two differences immediately were apparent (fig. 3). First, at all sampling resolutions, species composition of butterflies was more similar than species composition of birds. Second, the effect of sampling resolution was greater for birds than for butterflies, especially when the intermediate sampling resolution was compared to the smallest sampling resolution. In other words, the difference in mean similarity values at the resolution of mountain ranges versus sites, and at the resolution of canyons versus sites, was greater for birds than for butterflies. Birds in our study system typically have territory sizes or home ranges about an order of magnitude larger than those of butterflies. If home range size is the primary influence on species composition, then we would expect beta diversity of birds in our study system to be lower than beta diversity of butterflies. But previous work suggested, to the contrary, that resource specialization was more strongly associated with structure of bird assemblages than territory size (Fleishman et al., 2002a). If ecological specialization and geographic distribution are negatively correlated (Rabinowitz, 1981; Kunin & Gaston, 1997), then beta diversity of taxonomic groups with relatively general resource needs should be lower than beta diversity of groups with more specialized needs. Although in many instances one might assume that birds have more general requirements than butterflies, this may not be the case in the Great Basin. Butterflies often are considered "specialists" because as larvae

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they are restricted to one or a few closely related host plants (Ehrlich & Raven, 1964; Scott, 1986). In many ecosystems, however, the resource requirements of adult butterflies are fairly general (Holl, 1995; Pullin, 1995), and species composition of butterflies may be more closely associated with distribution of an array of potential nectar sources than with distribution of specific larval host plants. Availability of nectar is positively correlated with spatial distribution of adults and larvae (Gilbert & Singer, 1973; Murphy, 1983; Murphy et al., 1984) and may reduce the probability of local emigration (Kuussaari et al., 1996, Moilanen & Hanski, 1998). Many adult butterflies in the Great Basin can exploit virtually any source of nectar, from flowering shrubs to native forbs to non–native invasive species. Thus, it may be appropriate to classify butterflies in our study system as relative generalists. Species composition of birds traditionally was thought to be more closely associated with vegetation structure (physiognomy) than with vegetation composition (floristics) (MacArthur et al., 1966, Rotenberry & Wiens, 1980). However, some evidence suggests that vegetation composition is more influential than vegetation structure (Tomoff, 1974; Wiens & Rotenberry, 1981), especially at relatively fine spatial resolution (Rotenberry, 1985; Wiens et al., 1987). In the Great Basin, species composition of breeding birds may be affected by the patchy distribution of various species of trees, which provide nesting sites that differ in their suitability for particular species or guilds (Fleishman et al., 2003a). In particular, Neotropical migrant birds, which account for about one–third the assemblage in our study system (Gough et al., 1998), are thought to be relatively selective in choosing nesting sites because of the physical stress they undergo during migration and the limited temporal window available for establishing a breeding territory and reproducing (Robbins et al., 1989; Martin, 1992, 1995). Two of the most common trees in our study system, piñon (Pinus monophylla) and juniper (Juniperus osteosperma), are relatively widespread and sometimes form large stands, especially in drier areas. However, dominant riparian trees and shrubs such as cottonwood and aspen (Populus spp.), willow (Salix spp.), birch (Betula occidentalis), and rose (Rosa woodsii) have comparatively patchy distributions. Ecologists are well aware that measures of biodiversity, and inferences about diversity patterns, depend on spatial and temporal scale. Our results, which did not support the assumption that species turnover largely is a function of relative home range size, emphasize the relevance of empirical tests of diversity theories to conservation and management. Further, as our understanding of relationships between species diversity and various components of “scale” increases, so should our ability to recognize underlying mechanisms and to maintain native biodiversity and ecological processes.

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Fig. 3. Beta diversity (mean community similarity) of butterflies and birds at different spatial resolutions of sampling. Spatial extent of sampling was constant. Error bars are one standard deviation. Values are parameter means. Fig. 3. Diversidad beta (similaridad media en la comunidad) de mariposas y aves de muestreos realizados a distintas resoluciones espaciales. La extensión espacial de la muestra fue constante. Las barras de errores son una desviación estándard. Los valores son medias paramétricas.

Discussion Around the world, climate change, urbanization and other land uses, and invasive species are modifying ecosystem processes, species distributions, and population dynamics of native species. Understanding how assemblages of native plants and animals respond and evolve to these environmental changes is critical to development of effective, practical strategies for ecological restoration and maintenance. Yet the trinity of time, money, and information is elusive for conservation biologists and practitioners. Knowledge of the extent to which measures of biological diversity vary in space and time in the absence of deterministic “treatments” is essential for making accurate inferences and taking appropriate conservation action, especially when the consequences of those actions may be irreversible. In virtually all of our work in the Great Basin, irrespective of geographic location or taxonomic group, we have been struck by the considerable variation in species composition across space and time. At our finest sampling resolution (site level), for example, mean similarities of species composi-

tion of butterflies and birds were 0.397 and 0.295; at the mountain range level, mean similarities were 0.875 for butterflies and 0.662 for birds (Mac Nally et al., 2004). As a consequence, our work suggests strongly that spatially extensive sampling may be a more effective strategy for drawing inferences about regional species composition than sampling small areas scattered across the landscape. Similarly, recent work has shown that even after accounting for differences in detection probability, annual site–level turnover rates of many species of butterflies and birds in the Great Basin are as high as 50%. Despite considerable turnover in species composition, however, species richness of butterflies and birds in our study system has tended to be relatively consistent between years, especially at the landscape level (Fleishman & Mac Nally, 2003; Fleishman et al., 2003b). Brown et al. (2001) likewise found that species richness of birds in northern Michigan and rodents in the Chihuahuan Desert remained fairly constant over the long term (22 years and 50 years, respectively) notwithstanding substantial changes in species composition, climate, and other environmental conditions. In related work, we examined whether relatively limited spatial and temporal sampling can provide valid inferences about biological responses to variables that are affected by conservation and restoration actions, including dominance of non–native invasive plants (Mac Nally et al., 2004; Fleishman et al., 2005). In the Mojave Desert, both invasion of salt–cedar (Tamarix ramosissima) and human efforts to eradicate salt– cedar have altered vegetational communities and some measures of faunal diversity. We examined whether similar inferences about relationships between plants and butterflies in the Muddy River drainage could have been obtained by using data from a subset of the 85 locations included in the study, by sampling less intensively in time (fewer visits per site), or by sampling over a shorter period of time. We found that similar inferences about the importance of six vegetation–based predictor variables on species richness of butterflies, and about occurrence rates of individual species of butterflies, could be obtained by sampling as few as 10% of sites and by sampling less intensively or extensively in time. Collectively, our ongoing research in arid environments in the western United States suggests that relatively limited data sets may allow us to draw reliable inferences for adaptive management in the context of ecological restoration and rehabilitation. Integrating studies of biogeographic patterns with examination of how study design itself affects ecological inferences may be one of the most productive avenues for developing adaptive management strategies that will conserve both biodiversity and the processes that sustain it. Acknowledgements R. Blair, J. Fay, R. Mac Nally, and D. Murphy have been integral participants in the research described here. Thanks to G. Austin, C. Betrus, L. Bulluck, J.

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Bulluck, D. Dobkin, and the Great Basin Ecosystem Management Project for collaboration and assistance. J. Seoane and an anonymous reviewer provided helpful comments on the manuscript. Support for this work was provided by the Nevada Biodiversity Research and Conservation Initiative and by the Joint Fire Sciences Program via the Rocky Mountain Research Station, Forest Service, U.S. Department of Agriculture. References Addicott, J. F., Aho, J. M., Antolin, M. F., Padilla, D. K., Richardson, J. S. & Soluk, D. A., 1987, Ecological neighborhoods: scaling environmental patterns. Oikos, 49: 340–346. Allen, T. F. H. & Starr, T. B., 1982. Hierarchy: perspectives for ecological complexity. Univ. of Chicago Press, Chicago, Illinois. Andelman, S. J. & Fagan, W. F., 2000. Umbrellas and flagships: efficient conservation surrogates, or expensive mistakes? Proceedings of the National Academy of Sciences, 97: 5954–5959. Armour, C. L., Duff, D. A. & Elmore, W., 1991. The effects of livestock grazing on riparian and stream ecosystems. Fisheries, 16: 7–11. Atmar, W. & Patterson, B. D., 1993. The measure of order and disorder in the distribution of species in fragmented habitat. Oecologia, 96: 373–382 Baber, M. J., Fleishman, E., Babbitt, K. J. & Tarr, T. L., 2004. The relationship between wetland hydroperiod and nestedness patterns in assemblages of larval amphibians and predatory macroinvertebrates. Oikos, 107: 16–27. Betrus, C. J., 2002. Refining the umbrella index complex: an application to bird and butterfly communities in montane canyons in the Great Basin. M.S. thesis, Miami Univ., Oxford, Ohio. Bibby, C. J., Burgess, N. D., Hill, D. A. & Mustoe, S., 2000. Bird census techniques. Academic Press, London. Bird, B. M. & Boecklen, W. J., 1998. Nestedness and migratory status of avian assemblages in North America and Europe. Biodiversity and Conservation, 7: 1325–1331. Blair, R. B., 1999. Birds and butterflies along an urban gradient: surrogate taxa for assessing biodiversity. Ecological Applications, 9: 164–170. Boecklen, W. J., 1997. Nestedness, biogeographic theory, and the design of nature reserves. Oecologia, 112: 123–142. Brown, J., 1978. The theory of insular biogeography and the distribution of boreal mammals and birds. Great Basin Naturalist Memoirs, 2: 209–228. Brown, J. H., Morgan Ernst, S. K., Parody, J. M. & Haskell, J. P., 2001. Regulation of diversity: maintenance of species richness in changing environments. Oecologia, 126: 321–332. Chambers, J. C. & Miller, J. R., Eds., 2004. Great Basin riparian ecosystems—ecology, management, and restoration. Island Press, Washington, DC.

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Climate change and amphibians P. S. Corn

Corn, P. S., 2005. Climate change and amphibians. Animal Biodiversity and Conservation, 28.1: 59–67. Abstract Climate change and amphibians.— Amphibian life histories are exceedingly sensitive to temperature and precipitation, and there is good evidence that recent climate change has already resulted in a shift to breeding earlier in the year for some species. There are also suggestions that the recent increase in the occurrence of El Niño events has caused declines of anurans in Central America and is linked to elevated mortality of amphibian embryos in the northwestern United States. However, evidence linking amphibian declines in Central America to climate relies solely on correlations, and the mechanisms underlying the declines are not understood. Connections between embryo mortality and declines in abundance have not been demonstrated. Analyses of existing data have generally failed to find a link between climate and amphibian declines. It is likely, however, that future climate change will cause further declines of some amphibian species. Reduced soil moisture could reduce prey species and eliminate habitat. Reduced snowfall and increased summer evaporation could have dramatic effects on the duration or occurrence of seasonal wetlands, which are primary habitat for many species of amphibians. Climate change may be a relatively minor cause of current amphibian declines, but it may be the biggest future challenge to the persistence of many species. Key words: Amphibians, Amphibian decline, Breeding phenology, Global climate change. Resumen Cambio climático y anfibios.— Las historias vitales de los anfibios son sumamente sensibles a la temperatura y a la precipitación, y hay una clara evidencia que el reciente cambio climático ha tenido como resultado para algunas especies una anticipación del periodo de cría a lo largo del año. También se cree que el aumento reciente en la ocurrencia de fenómenos de El Niño ha causado el descenso de anuros en América Central y está relacionado con la mortalidad elevada de embriones de anfibios en el noroeste de los Estados Unidos. Sin embargo, la evidencia que relaciona el descenso de anfibios en América Central con el clima está basado únicamente en correlaciones, y no se entienden los mecanismos fundamentales que provocan este descenso. No se han podido demostrar las conexiones entre la mortalidad de embriones y el descenso de abundancia. El análisis de los datos generalmente falla a la hora de encontrar una conexión entre descensos de anfibios y el clima. Es probable, sin embargo, que posteriores cambios climáticos puedan causar descensos adicionales de algunas especies de anfibios. La humedad reducida de la tierra podría reducir las especies presa y eliminar el habitat. La reducción de nevadas invernales y el incremento de la evaporación en verano podrían tener efectos dramáticos en la duración u ocurrencia de pantanos estacionales, que es el habitat principal para muchas especies de anfibios. El cambio del clima puede ser una causa relativamente secundaria de los descensos actuales de anfibios, pero en el futuro puede ser el desafío más grande a la persistencia de muchas especies. Palabras clave: Anfibios, Descenso de anfibios, Fenologia de cría, Cambio climático global. (Received: 9 III 04; Conditional acceptance: 22 IV 04; Final acceptance: 18 V 04) Paul Stephen Corn, U.S. Geological Survey, Aldo Leopold Wilderness Research Inst., P. O. Box 8089, Missoula, MT 59807 U.S.A. ISSN: 1578–665X

Introduction Considerable progress has been made in the past decade in documenting the nature and extent of amphibian declines (Waldman & Tocher, 1998; Alford & Richards, 1999; Corn, 2000; Houlahan et al., 2000; Hero & Shoo, 2003). Declines of amphibian species have been documented in most of the world, including Spain (Márquez et al., 1995; Bosch et al., 2001; Martínez–Solano et al., 2003). Knowledge of the status of amphibians is incomplete, but it appears that declines are most severe in Australia (Laurence et al., 1996), Central America (Pounds et al., 1997; Lips, 1998, 1999), and the western United States (Drost & Fellers, 1996; Fisher & Shaffer, 1996; Sredl et al., 1997). There is also a better understanding of at least some of the causes of amphibian declines, compared to 1990, when the issue of declining amphibians first gained widespread attention (Collins & Storfer, 2003). Habitat destruction or alteration, contaminants, introduced predators, and disease have all been identified as potential or likely causes of declines (Stebbins & Cohen, 1995; Sparling et al., 2000; Linder et al., 2003; Semlitsch, 2003). Global change as a cause of amphibian declines has also been studied from two main perspectives: increasing temperatures and increasing ultraviolet–b radiation (UV–B) due to thinning of stratospheric ozone. Although field and laboratory experiments have shown that ambient UV–B may cause mortality or deformities in some amphibian species (Blaustein et al., 1998; 2003b), the UV–B hypothesis is controversial and has been the subject of a series of contentious critiques and rebuttals (Licht & Grant, 1997; Corn, 2000; Cummins, 2002; Kats et al., 2002; Blaustein et al., 2003b, 2004; Blaustein & Kats 2003; Licht, 2003). Support for the hypothesis that increasing UV–B has contributed to amphibian declines is undermined by a lack of evidence linking results from experimental studies to changes in abundance or distribution (Corn & Muths, 2002) and by the general lack of evidence that amphibians have been exposed to increased doses of UV–B (Corn & Muths, 2004). There is increasingly strong evidence, however, that recent climate change has affected the biology of numerous species worldwide. Global average temperature has increased by about 0.6°C during the past century, which is the warmest period of the preceding millennium (Jones et al., 2001). This increase in temperature is largely attributable to increasing greenhouse gasses (Crowley, 2000). Warming spring temperatures have resulted in measurable shifts in phenology (e.g., timing of budding, flowering, emergence, breeding) to earlier dates, and distributions of some plants and animals have shifted pole–ward and higher in elevation (Walther et al., 2002; Parmesan & Yohe, 2003; Root et al., 2003). The effects on amphibians observed so far mainly involve changes in the timing of breeding of some species (Blaustein et al., 2003a; Carey & Alexan-

Corn

der, 2003), and not changes in distribution. For example, Livo & Yeakley (1997) failed to detect any directional change in elevation associated with declines of Boreal Toads (Bufo boreas) in the Rocky Mountains in Colorado, USA. However, Martínez–Solano et al. (2003) attributed the increase in occurrence of Iberian Green Frogs (Rana perezi) in Peñalara National Park in Spain to recent climate warming. Thomas et al. (2004) estimated changes in distribution for a number of species based on predicted changes in their climate envelopes, and by applying the relationship between area and diversity, predicted that 18–35% of the species they examined (which included 23 frogs from Queensland, Australia) will have a high risk of extinction by 2050. Because amphibian decline is already a significant problem, the potential for greatly increased risk of extinction makes it important to understand how climate change affects amphibians. Amphibians are ectotherms, and all aspects of amphibian life history are strongly influenced by the external environment, including weather and climate. Temperature is a particularly important factor affecting aquatic amphibian larvae. Ultsch et al. (1999) provided a concise statement: "…environmental temperature dramatically affects the time taken to reach metamorphosis, which can be critical to the survival of an individual faced with a drying habitat or the onset of winter. Temperature also affects differentiation and growth rates, body size at metamorphosis, mechanisms of gas exchange, rates of energy metabolism, and undoubtedly many other physiological parameters documented in ectothermic vertebrates. Moreover, the limits of temperature tolerance and temperature–dependent life history traits of anuran larvae are generally related to the geographic distribution of a species." Ovaska (1997) and Donnelly & Crump (1998) described how changes in temperature and precipitation regimes could result in changes in the distribution and abundance of amphibian populations. Direct effects include changes in movements, phenology, and physiological stress. Indirect effects include changes in predators, competitors, food supply, and habitat. Most research to date has emphasized direct effects of climate change. Indirect effects, particularly the links to population dynamics, are notoriously difficult to document. The consequences of climate change are diverse, and effects can be beneficial as well as detrimental (Ovaska, 1997; McCarty, 2001). A shift in breeding activity to earlier in the season may provide additional time for growth and development. Larger individuals may survive over winter better and may have increased reproductive fitness than small ones (Reading & Clarke, 1999). Breeding earlier reduces exposure to UV–B (Merilä et al., 2000; Corn & Muths, 2002; Cummins, 2003). On the other hand, earlier breeding could bring increased risk of exposure to extreme temperatures

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from more variable early spring weather (Corn & Muths, 2002). The effects of changes in temperature and precipitation on hydrology and hydroperiod (the length of time a temporary pond retains water) may have large effects on amphibians. Early drying of temporary ponds may result in less time available to complete metamorphosis (Semlitsch, 1987; Pechmann et al., 1989, Rowe & Dunson, 1995). Changes in breeding phenology and pond hydrology may affect growth rates of larvae (Rowe & Dunson, 1995; Reading & Clarke, 1999; Boone et al., 2002), and because much predation on amphibian larvae is related to size, this may alter the relationships between amphibians and their predators. Several recent papers have reviewed the effects of climate change on amphibians (Blaustein et al., 2003a; Boone et al., 2003; Carey & Alexander, 2003). However, few studies have addressed the effects of climate change on amphibians in montane or boreal habitats with persistent winter snow cover, where the timing of snowmelt is the primary influence on breeding phenology. Thomas et al. (2004) predicted the smallest increase in extinction risk in alpine and boreal forest habitats, but warming temperatures in the next 50–100 years are predicted to drastically alter the characteristics of mountain snow packs. Numerous questions still need answers if we are to predict how climate change will affect the distribution and abundance of amphibians. Effects of climate change on amphibians Changes in breeding phenology Several studies have demonstrated trends towards breeding earlier by some species of amphibians. Terhivuo (1988) used the longest time series for amphibians, 140 years of observations collected by volunteers in Finland, and found that Common Frogs (Rana temporaria) bred 2 to 13 days earlier in the 1980s than in the 1840s, depending on latitude. Gibbs & Breisch (2001) compared data on the dates of first calling by anurans near Ithaca, NY collected 1900–1912 (Wright, 1914) to data gathered by the during 1990–1999 by the New York State Amphibian and Reptile Atlas Project. Four species began breeding activity significantly earlier (by 10–14 days) during the last decade, compared to the first 12 years of the 20th Century. Over the same period, significant increases in mean daily temperatures (1.2–2.3°C) also occurred in 5 of the 8 months important to gametogenesis in these species. In Poland, the dates of first spawning by R. temporaria and Common Toads (B. bufo) shifted 8–9 days earlier between 1978 and 2002 and were correlated with warmer spring temperatures (Tryjanowski et al., 2003). The most dramatic shifts in the shortest time were found in England, where two anuran species deposited eggs 2–3 weeks earlier and the three species of salamander arrived at breeding ponds 5–7 weeks earlier in 1990–1994

compared to 1978–1982 (Beebee, 1995). These changes result from warmer spring temperatures associated with the North Atlantic Oscillation (Forchhammer et al., 1998). The trend toward earlier breeding by amphibians in recent years is not universal. There are about an equal number of cases in England and North America where there is no significant trend toward earlier breeding as there are cases of significant trends (Beebee, 1995; Reading, 1998; Blaustein et al., 2001; Gibbs & Breisch, 2001; Corn & Muths, 2002). Most of these cases use time series of < 20 years, which may be too short to demonstrate significant trends in the face of large interannual variation in the timing of breeding. For example, Blaustein et al. (2001) found a non–significant trend toward earlier breeding in one of three populations of B. boreas in the Cascade Mountains in Oregon, USA for 1982–1999. Corn (2003) analyzed these data using the relationship between the timing of breeding and the size of the winter snow pack to model the timing of breeding. Predicted breeding in the one population showed a much more pronounced trend toward breeding earlier by about 20 days between 1950 and 2000. Long time series (>50 years) are probably necessary to separate the effects of anthropogenic warming from multi–decadal cycles on changes in breeding phenology. That Beebee (1995) and Tryjanowski et al. (2003) found greater shifts in phenology after about 30 years than did Terhivuo (1988) after 140 years may reflect this phenomenon. For example, snow accumulation in the northwest United States is strongly influenced by the Pacific Decadal Oscillation (PDO), Selkowitz et al., 2002). Because the 1950s were a period of higher than average snowfall, the trend toward earlier breeding by the population of B. boreas in Oregon (Corn, 2003) is likely to have been strongly influenced by the PDO. Changes in populations Climate change has been considered a potential cause of population declines since the beginning of the current spate of concern about the status of amphibians (Wyman, 1990), but the role of climate change in the decline of anurans in the cloud forest of Costa Rica has received the most attention. About half of the 50 species expected to occur in the Monteverde region had disappeared by 1990 (Pounds et al., 1997). These included the distinctive Golden Toad (B. periglenes). The decline of this species was first observed in 1987, and is not been observed since 1989 and is likely extinct (Crump et al., 1992). Pounds & Crump (1994) described the 1987 crash of B. periglenes as resulting from above average temperatures and below average precipitation that were associated with a strong El Niño/ Southern Oscillation (ENSO). This event killed eggs and tadpoles by premature drying of breeding ponds, but the explanation for the subsequent disappearance of adult toads was not apparent. Pounds and

Crump discussed hypotheses for how adults may have been affected, including physiologic stress, impaired immune system function leading to disease, and contaminants. They also described the decline of the Harlequin Frog (Atelopus varius) in the same region. This species congregates in moist refugia, such as the splash zones of waterfalls, during dry periods, and becomes more susceptible to predation and parasitism (Pounds & Crump, 1987; Donnelly & Crump, 1998). Pounds et al. (1999) described continuing population fluctuations of anurans at Monteverde in the 1990s, with significant declines involving about 20 species in 1994 and 1998. These more recent declines were also correlated with warm and dry conditions associated with decreasing dry season mist frequency. The retreat of the cloud bank to higher elevations is a product of global warming and is accentuated during strong ENSO events (Still et al., 1999). Pounds et al. (1999) also observed changes in other animals, in addition to declines of anurans. In a cloud–forest study plot, there has been an increase in the frequency of bird species that normally breed at lower elevations below the cloud forest, and two species of anoline lizards, endemic to the highlands of western Costa Rica and Panama, declined and disappeared by 1996. Although the changes in the cloud forest fauna were strongly correlated with climatic events, our understanding of the mechanisms underlying the declines of anurans and lizards has not progressed beyond the hypotheses presented by Pounds et al. (1997). Middleton et al. (2001) used satellite–based observations to estimate surface UV–B exposure at Central and South American sites, including Monteverde, where amphibian declines have been observed. They found increasing trends from 1979 to 1998, in annual averaged UV– B exposure and the number of days per year with high UV–B, that were strongest in Central America. However, most of the declining amphibian species at Monteverde are forest–floor dwellers that have limited exposure to sunlight. According to Pounds & Crump (1994: p 73), B. periglenes, "…normally hide in retreats about 95% of the time, emerging to breed beneath the forest canopy, typically under heavy cloud cover." Middleton et al. (2001) were unable to describe a plausible mechanism for how increasing UV–B could affect such species. The trends of increasing UV–B may be a by–product of decreased cloudiness (Still et al., 1999) and not related to the amphibian declines that have been observed to date. Kiesecker et al. (2001) described a mechanism by which climate change and UV–B radiation could directly affect the abundance of B. boreas in the Pacific Northwest. ENSO events result in low winter precipitation in the Cascade Mountains, and in the following spring, toad embryos develop in shallower water than in years with high winter precipitation. Kiesecker et al. found a significant regression between depth at which embryos develop and mortality. At depths less than 20 cm, infection by the

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pathogenic water mold Saprolegnia ferax was greater than 50%. Kiesecker & Blaustein (1995) demonstrated experimentally that B. boreas embryos were susceptible to S. ferax only in the presence of UV– B radiation. Kiesecker et al. (2001) exposed B. boreas embryos to ambient sunlight and sunlight with UV–B removed by mylar filters at 3 depths (10, 50, and 100 cm). Mortality of embryos exposed to ambient sunlight exceeded mortality of embryos protected from UV–B only in the shallowest treatment. Kiesecker et al. (2001) concluded that in ENSO years, embryos develop in shallower water, are exposed to higher doses of UV–B radiation, and consequently suffer catastrophic mortality from infection by S. ferax. Analyzing global change as an explanation for amphibian declines Although Pounds et al. (1999) provide correlations between decline of anurans in Costa Rica and ENSO events, the mechanisms causing the declines are still a matter of speculation. The lifting cloud bank hypothesis (Still et al., 1999) is a computer simulation, and temperature data collected by Pounds et al. (1999) are not consistent with its predictions. Pounds et al. recorded a decrease in the difference between daytime and nighttime temperatures, but clear skies should result in lower nighttime temperatures and an increase in the difference. Pounds et al. did record greater frequency of dry season days without precipitation from mist during ENSO years, so it may be that precipitation is much more important that temperature as a factor in the declines of amphibians in the Monteverde region. However, Alexander & Eischeid (2001) point out that the ENSO event in 1982–1983 was stronger than the 1986–1987 event, but it was not coincident with amphibian declines at Monteverde. The study of B. boreas by Kiesecker et al. (2001) shifted one of the emphases in the study of causes of amphibian declines from direct effects of increasing UV–B radiation (Blaustein et al., 1998) to more complex interactions (Blaustein & Kiesecker, 2002). Pounds (2001) stated that Kiesecker et al. (2001), "…identify a complete chain of events whereby climate change causes wholesale mortality in an amphibian population." However, this is a significant overstatement. Kiesecker et al. (2001) linked climate change, UV–B radiation, and disease with excessive mortality of embryos. It has not been demonstrated that this has affected the abundance of adult toads. Kiesecker et al. (2001) stated, "If bouts of high embryo mortality occur with greater regularity and intensity, they may result in population declines." However, the populations of toads studied by Kiesecker et al. have not declined (Olson, 2001), and sensitivity analysis suggests that abundance is not strongly related to changes in embryo mortality (Biek et al., 2002; Vonesh & De la Cruz, 2002). Furthermore, the mechanism of embryo mortality

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proposed by Kiesecker et al. (2001) is open to question. In the mountains of the western U.S., amphibian breeding phenology is controlled by snowmelt, and low winter precipitation results in earlier breeding (Corn & Muths, 2002; Corn, 2003). Earlier breeding reduces exposure of embryos to UV–B (Merilä et al., 2000; Corn & Muths, 2002). Lost Lake, the primary study site of Kiesecker et al. (2001) is among the most transparent to UV–B of any amphibian breeding site in the Cascades (Palen et al., 2002). Therefore, it may not be appropriate to generalize based on results of studies at this site. Population declines associated with infection by the pathogenic fungus Batrachochytrium dendrobatidis have been documented in amphibians in many regions, including Spain (Bosch et al., 2001), and Daszak et al. (2003) consider chytridiomycosis to be an emerging infectious disease (EID). An EID may be caused by a common pathogen that increases in range and virulence following an environmental change (Daszak et al., 2001), and because B. dendrobatidis suvives best at moderate temperatures (23° C) and dies at 30° C (Longcore et al., 1999), it is tempting to hypothesize that climate change may be playing a role in chytridiomycosis as an EID. There have been several attempts to relate amphibian declines, some of which may be caused by chytridiomycosis, to recent weather patterns and climate data, none of which have been very successful. Numerous species of rainforest frogs have disappeared or declined in eastern Australia, primarily in the mountains of eastern Queensland and northeastern New South Wales (Laurance et al., 1996; Mahony, 1996). Laurance (1996) analyzed weather data, and although wet season rainfall was reduced in the 5 years preceding declines, he concluded this was not out of the range of normal variation and was insufficient to have caused the declines. Alexander & Eischeid (2001) examined climate data for regions with documented amphibian declines (Colorado, Puerto Rico, Central America, and Queensland), and found results similar to Laurance (1996). There were few similarities in weather among areas before the declines occurred, and although warmer temperatures occurred during the onset of declines in Puerto Rico and Queensland, these were not extreme. Alexander and Eischeid concluded that abnormal temperature and precipitation were unlikely to have caused the declines directly. Because the chytrid fungus may survive better at cooler temperatures, and is likely to be transmitted among amphibians by a motile aquatic stage, warmer and drier climate trends seem unlikely to promote outbreaks of chytridiomycosis. However, we need considerably more information before rejecting a link between climate change and disease. Davidson et al. (2001, 2002) examined the geographic patterns of the declines of several amphibian species in California, related to climate, UV–B radiation, urbanization, and agriculture. They hypothesized that climate change would be mani-

fested in declines related to related to latitude, elevation, and precipitation. Specific predictions were more declines at lower latitudes and elevations and at drier sites. However, they found no evidence to support this hypothesis. Declines of several species occurred downwind of agricultural areas, suggesting that airborne contaminants might be the greatest threat. Future effects of climate change on amphibians The relationship between current amphibian declines and climate change may be ambiguous, but it is fairly easy to predict serious consequences to amphibian abundance and distribution if predictions of climate change during the next century come to pass. MacCracken et al. (2001) and Hulme & Viner (1998) describe potential outcomes for the United States and the tropics, respectively. MacCracken et al. (2001) describe outcomes of climate models based on increasing atmospheric CO2 concentrations. Global mean temperatures would rise 1.2–3.5°C, but increases would be higher at mid to high latitudes and greater over continents than over oceans. Warming over the U.S. would be between 2.8 and 5°C and result from higher winter and nighttime temperatures. Global precipitation will increase, but predicting local patterns is difficult. Less snow is expected, reducing the area of snow cover during winter. Higher summer temperatures will increase evaporation, reducing soil moisture. Extreme precipitation events will become more frequent. In the tropics, the predictions described by Hulme & Viner (1998) are qualitatively similar: increased temperature, increased length of the dry season, decreased soil moisture, and greater interannual variation in rainfall. Donnelly & Crump (1998) predict that tropical amphibians will suffer reduced reproductive success, reduced food supply, and a disruption in breeding behavior and periodicity. They predict that the effects will be greatest on endemic species, those species restricted to a specific location and which usually have specialized ecological requirements. Donnelly and Crump note that if all the endemic amphibians were lost in three Central American countries, Costa Rica, Panama, and Honduras, amphibian diversity in those countries would decrease by 17 to 26%. Thomas et al. (2004) forecast similar changes in a suite of tropical anurans in Australia by the year 2050, based on shrinkage of available habitat resulting from predicted changes in temperature and precipitation. Teixeira & Arntzen (2002) used a similar approach to predict reduced distribution of the Golden–striped Salamander, Chioglossa lusitanica, in Spain and Portugal between 2050 and 2080. Thomas et al. (2004) predicted the smallest risk of extinction for species inhabiting boreal and alpine habitats. However, several species of amphibians in the mountains of the western U.S. have

declined in the past 20–30 years (Corn, 2000), and climate models predict that rising winter temperatures will dramatically reduce the extent and duration of mountain snow packs in most of this region in the next 50–100 years (McCabe & Wolock, 1999; Leung et al., 2004; Stewart et al., 2004). If true, this will result in earlier breeding by most montane amphibians (Corn & Muths, 2002; Corn, 2003), increasing the strain on populations that may already be in decline. The consequences of earlier breeding may include more frequent exposure to killing frosts (Inouye et al., 2001). The duration of the larval period may increase, because water temperatures warm more slowly in early spring. Amphibians breeding in lentic water typically have high larval mortality, and there is strong selection for reducing the time spent as larvae (Berven, 1982). Reduced water storage as snow, earlier runoff, and an increase in evaporation due to warmer summer temperatures will likely reduce the hydroperiod of temporary ponds, but specific predictions are complex and require linking hydrologic models to climate change predictions. Any significant change in occurrence or hydroperiod of temporary ponds could have serious effects on amphibian diversity. Several amphibian species use temporary ponds as their primary breeding habitat. Predators and competition from other amphibians restricts the ability of these species to switch to more permanent water (Wellborn et al., 1996; Snodgrass et al., 2000). Threats to montane amphibians may be more severe than predicted generally for boreal and alpine species by Thomas et al. (2004). Finally, an increase in the frequency of severe weather events is likely to cause problems for amphibians. Drought has been documented several times as a serious challenge to population persistence (Corn & Fogleman, 1984; Weygoldt, 1989; Kagarise Sherman & Morton, 1993; Pounds & Crump, 1994; Stewart, 1995; Osborne et al., 1996). Other extreme events, such as floods, frosts, and hurricanes, have been implicated as causes of declines at regional scales (Heyer et al., 1988; Woolbright, 1997; Corn, 2000). Increases in catastrophic mortality are difficult for stable populations to cope with, but for those amphibian species already in decline, increases in severe weather events could make survival extremely difficult. Acknowledgements The initial draft of this paper was written in 2001 for a book resulting from the University of Georgia State–of–the–Art Conference: The Big Unknowns in Global Change: Climatic, Biotic, Human Systems. Although the book was never published, I thank Elgene Box and Lynn Usery for inviting me to participate. I thank Mo Donnelly, Rafael Márquez, Juliet Pulliam, and an anonymous reviewer for comments on earlier drafts.

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"La tortue greque" Oeuvres du Comte de Lacépède comprenant L'Histoire Naturelle des Quadrupèdes Ovipares, des Serpents, des Poissons et des Cétacés; Nouvelle édition avec planches coloriées dirigée par M. A. G. Desmarest; Bruxelles: Th. Lejeuné, Éditeur des oeuvres de Buffon, 1836. Pl. 7

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

Consell Assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Editors / Editores / Editors Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, Spain Xavier Bellés Centre d' Investigació i Desenvolupament CSIC, Barcelona, Spain Juan Carranza Univ. de Extremadura, Cáceres, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales CSIC, Madrid, Spain Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Xavier Domingo Univ. Pompeu Fabra, Barcelona, Spain Francisco Palomares Estación Biológica de Doñana, Sevilla, Spain Francesc Piferrer Inst. de Ciències del Mar CSIC, Barcelona, Spain Ignacio Ribera The Natural History Museum, London, United Kingdom Alfredo Salvador Museo Nacional de Ciencias Naturales, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Zoologia de Barcelona, Barcelona, Spain Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Trinity, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Estación Experimental de Zonas Áridas CSIC, Almería, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway

Animal Biodiversity and Conservation 24.1, 2001 © 2001 Museu de Zoologia, Institut de Cultura, Ajuntament de Barcelona Autoedició: Montserrat Ferrer Fotomecànica i impressió: Sociedad Cooperativa Librería General ISSN: 1578–665X Dipòsit legal: B–16.278–58

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Does intruder group size and orientation affect flight initiation distance in birds? C. Geist, J. Liao, S. Libby & D. T. Blumstein

Geist, C., Liao, J., Libby, S. & Blumstein, D. T., 2005. Does intruder group size and orientation affect flight initiation distance in birds? Animal Biodiversity and Conservation, 28.1: 69–73. Abstract Does intruder group size and orientation affect flight initiation distance in birds?— Wildlife managers use flight initiation distance (FID), the distance animals flee an approaching predator, to determine set back distances to minimize human impacts on wildlife. FID is typically estimated by a single person; this study examined the effects of intruder number and orientation on FID. Three different group size treatments (solitary person, two people side–by–side, two people one–behind–the–other) were applied to Pied Currawongs (Strepera graculina) and to Crimson Rosellas (Platycerus elegans). Rosellas flushed at significantly greater distances when approached by two people compared to a single person. This effect was not seen in currawongs. Intruder orientation did not influence the FID of either species. Results suggest that intruder number should be better integrated into estimates of set back distance to manage human visitation around sensitive species. Key words: Flight initiation distance, Intruder group size, Intruder orientation, Human disturbance, Set–back distances. Resumen ¿El tamaño y la orientación del grupo intruso afecta a la distancia de iniciación al vuelo en aves?— Los gestores de la fauna utilizan la distancia de iniciación al vuelo (FID), la distancia a la que los animales huyen cuando se les acerca un depredador, para determinar las distancias de respuesta a fin de minimizar el impacto humano en la fauna. La FID es estimada típicamente por una sola persona; este estudio examinó los efectos del número y de la orientación del intruso en la FID. Se aplicaron tres tratamientos distintos de tamaño del grupo (persona solitaria, dos personas una al lado de la otra, dos personas una detras de la otra) a currawongs cálidos (Strepera graculina) y a pericos elegantes (Platycerus elegans). Los pericos elegantes huían a distancias perceptiblemente mayores cuando se le acercaban dos personas que cuando se le acercaba una sola. Este efecto no fue observado en los currawongs pálidos. La orientación del intruso no influenció en la FID de ninguna especie. Los resultados sugieren que el número de intrusos debería ser considerado en las estimaciones de las distancias de respuesta, para poder gestionar las visitas de personas cerca de especies sensibles. Palabras clave: Distancia de iniciación al vuelo, Tamaño del grupo intruso, Orientación del intruso, Molestia humana, Distancias de respuesta. (Received: 26 II 04; Conditional acceptance: 2 VI 04; Final acceptance: 15 VII 04) C. Geist, J. Liao, S. Libby & D. T. Blumstein, Dept. of Ecology and Evolutionary Biology, 621 Young Drive South, Univ. of California, Los Angeles, CA 90095–1606, U.S.A. Corresponding author: D. T. Blumstein. E–mail: marmots@ucla.edu

ISSN: 1578–665X

Introduction The distance at which an animal begins to flee an advancing predator is commonly referred to as "flight–initiation distance" (Ydenberg & Dill, 1986) or "flush distance" (Holmes et al., 1993). There should be strong selection for successful animals to flee at an optimal FID. Early flight might reduce foraging efficiency, while late flight could end with accidental predation. Successful individuals should balance the costs of flight with the benefits of remaining. Ydenberg & Dill (1986) developed an economic model to qualitatively predict optimal flight distances from approaching predators. Subsequent studies have demonstrated that optimal FID can be influenced by many variables (e.g., species –Blumstein et al., 2003; flock size –Burger & Gochfeld, 1991; speed of predator –Cooper, 2003; distance from protection –Dill & Houtman, 1989; type of disturbance –Rodgers & Smith, 1997; intruder starting distance –Blumstein, 2003; dangerousness of the predator –McLean & Godin, 1989; availability of cover –LaGory, 1987). Ecotourism and outdoor activities have grown increasingly popular, but the effects of humans are not entirely benign to wildlife (Wearing & Neil, 1999; Christ et al., 2003). Wildlife managers try to reduce human disturbance by assuming that approaching humans are perceived as predators (e.g., Frid & Dill, 2002), and then using FID to develop set back distances –the minimum distance that a human may approach before the bird is disturbed (e.g., Holmes et al., 1993; Rodgers & Smith, 1995). Such distances are often used to establish seasonal tourist limits and to restrict recreational access (Fernández– Juricic et al., 2001). Tourist numbers vary considerably, yet we are aware of no experimental studies studying whether there is an effect of intruder number on FID. This study examined whether birds modified their FID when faced with one or two approaching humans. By increasing the number of advancing intruders, we generated an effect similar to increasing predator density. Theory is not clear on how increased predator densities affect antipredator behavior in prey because the effects of predator density may vary with ecological circumstances (Abrams, 1994). FID was used as a quantitative measurement of a bird’s assessment of risk (Ydenberg & Dill, 1986; Frid & Dill, 2002). If intruder number increased the perception of risk, then it was expected that more intruders would result in larger FIDs. This study also examined how birds assessed risk when two humans approached side–by–side, or directly behind one another. The side–by–side orientation treatment was executed with one intruder approaching tangentially while another intruder approached directly. Previous studies have found that prey perceive tangential approaches as less evocative than direct approaches (e.g., great black–backed gulls (Larus argentus) –Burger & Gochfeld, 1981; black iguanas (Ctenosaura similis) –Burger &

Geist et al.

Gochfeld, 1990; broad–headed skinks (Eumeces laticeps) –Cooper, 1997). This evidence suggests that some animals can perceive subtle differences in intruder behavior and adjust their responses accordingly (Burger & Gochfeld, 1990). In order for the prey to react, the intruder must be within the prey’s field of view (Cooper, 1997). If the prey and predator look at each other, then there is a greater probability that the predator has detected the prey and poses a greater risk to the prey. If birds can detect and make eye contact with two intruders side–by–side better than two intruders directly behind one another, then the side–by–side orientation approach would be expected to have a higher FID. Methods Study sites The study focused on two common Australian birds, (Pied Currawongs, Strepera graculina; Rosellas, Platycerus elegans) found in the forests of Booderee National Park (150º 43’ N, 35º 8’ W), 200 km S of Sydney. From 23 X–6 XI 03, the effects of intruder number and orientation on FID were studied by walking towards these two species at ten locations around the park. The locations included a commonly visited beach (Murray Beach), camping areas (Bristol Point, Cave Beach, Green Patch, Iluka Beach), native bush land (Hole in the Wall, Steamers Beach, Telegraph Creek), a managed natural garden (The Booderee Botanic Gardens), and an Australian naval college (HMAS Creswell). The sites were chosen because they contained hiking trails surrounded by moist forests and woodlands. At each of these locations, data were collected while walking along the trail. Locations were geographically grouped into six regions to study for location effects. Data collection To measure FID, perched or foraging subjects that were not initially disturbed by the observer’s presence were identified. Highly vigilant or nesting birds were not approached. The subject was then flushed by walking towards it at a constant pace of approximately 1.0 m/s, while maintaining eye contact. Before data were collected, observers trained themselves to maintain a consistent stride length and a constant pace. Paces were converted to meters for analysis. Observers recorded the distance from the focal bird at the start of the experimental approach, the height off the ground at the start of the approach, and the distance the bird initiated flight. Each flush was conducted using one of three different treatments listed below: (1) one person directly approached a bird, (2) two people, separated by 1.5 m, and oriented side– by–side approached a bird, and (3) two people, separated by 1.5 m, and oriented directly behind one another approached a bird.

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The location and distance to vegetation cover was also noted because these additional factors could influence FID (Burger & Gochfeld, 1991). Subjects at the same site were selected if it was not possible for them to have seen previous experimental approaches, because previous exposure could have influenced their response (e.g., Runyan & Blumstein, in press). Data analysis For each species, general linear models were fitted to study the effect of treatment on FID. We used the "direct" FID, calculated with the Pythagorean Theorem, as our measure of FID because, for some birds, FID is influenced by the height a bird is in a tree (Blumstein et al., in press). The effect of FID was determined based on the direct distance between the prey and the predator. Moreover, because FID typically is influenced by intruder starting distance (Blumstein, 2003), starting distance must be included in models. Such models must be forced through the origin because, logically, a starting distance of 0 m must have a FID of 0 m. Doing so, however, makes the main effect of treatment uninterpretable. Hence, to understand the effect of treatment on the expected relationship between starting distance and FID, the interaction between starting distance and treatment was examined. Analyses focused on flushes with starting distances that ranged between 10 m and 50 m. The currawong data set contained 23 single, direct approaches, 19 paired, side–by–side approaches, and 20 paired, one–behind–another approaches. The rosella data set contained 20 single, direct approaches, 20 paired, side–by–side approaches, and 27 paired, one–behind–another approaches. Other factors could influence FID. The effect of the regions where the birds were flushed, and the distance a subject was from vegetation on FID were examined by fitting general linear models and examining the interaction of these factors with starting distance. No significant interactions were found (location effect: P Currawong = 0.605, adjusted R 2 Currawong = 0.830, model P Currawong = 0.0001 PRosella = 0.979, adjusted R2Rosella = 0.759, model PRosella = 0.0001; distance to vegetative cover: PCurrawong = 0.239, adjusted R2Currawong = 0.839, model P Currawong = 0.0001; P Rosella = 0.810, adjusted R2Rosella = 0.766, model PRosella = 0.0001), and we therefore do not believe that our main results (discussed below) are confounded by their effect. Results Currawongs Variation in FID was not significantly explained by the interaction of treatment type and starting distance (P interaction = 0.337, adjusted R2 = 0.837, Pmodel = 0.0001), intruder number and starting dis-

tance (P interaction= 0.121, adjusted R 2 = 0.841, Pmodel = 0.0001), or between the two, two–person approaches ( Pinteraction = 0.279, adjusted R2 = 0.846, Pmodel = 0.0001; fig. 1A). Rosellas Variation in the FID was significantly explained by the interaction of treatment and starting distance (Pinteraction= 0.0009, adjusted R2 = 0.843, Pmodel = 0.0001), intruder number and starting distance (Pinteraction = 0.0004, adjusted R2 = 0.843, Pmodel = 0.0001), but there was no difference between the two, two–person approaches (Pinteraction = 0.220, adjusted R2 = 0.860, Pmodel = 0.0001; fig. 1B). Discussion The objective of this study was to determine whether intruder number and orientation had an affect on birds’ decision to flee approaching humans. While neither studied species responded to variation in the orientation of the paired intruders, rosellas flushed at significantly greater distances when approached by two intruders, than by a single intruder. This finding suggests that rosellas assessed a higher risk of predation when approached by two intruders than by one. More importantly, the finding that intruder number effects flight decisions has important implications for the estimation of set back distances as well as for strategies to reduce human disturbance on vulnerable wildlife. Our results were likely not influenced by habituation; at our sites, both species appeared reasonably habituated to humans. Rather, variation in response may result from variation in the species’ natural history. Crimson Rosellas are seedeaters and Pied Currawongs are omnivores (Higgins, 1999; Fagg, 2002). Foraging for non–plant items is relatively time consuming (Naoki, 2003) and, for a given level of risk, currawongs may experience a greater cost of flight. In contrast, animals foraging on seeds could always return. Hence, currawongs might be more tolerant of intruders and less sensitive to variation in risk. To properly evaluate this natural history hypothesis, more species with variable diets must be studied in a formal comparative analysis (e.g., Blumstein et al., in press). While an effect of intruder orientation was expected, none was found. Further experiments must be conducted to determine why, but it is likely that the intruders were too close together to reflect distinctly different risks. More generally, developing a fundamental understanding of how birds perceive groups of humans will be important to better manage human disturbance. This study demonstrated that birds may respond differently to multiple intruders. Somewhat remarkably, the effect was present with the addition of a single person. Future studies conducted with larger group sizes would be needed to determine the precise shape of the function of this

Geist et al.

Flight initiation distance (m)

40 30 20 10 0 0

10 20 30 40 Starting distance (m)

50 40 30 20 10 0 0

20 30 40 Starting distance (m)

Fig. 1. The relationship between starting distance and treatment on FID for Pied Currawongs (A) and Crimson Rosellas (B): single flushes, diamonds and small dashed line; side–by–side flushes, squares and solid line; one–behind the other, triangles and large dashes. Fig. 1. Relación entre la distancia de inicio y el trato en FID para currawongs pálidos (A) y pericos elegantes (B): aproximaciones solitarias, rombos y líneas de puntos pequeños; aproximaciones lado a lado, cuadrados y líneas continuas; aproximaciones uno detras de otro, triángulos y lineas de puntos grandes.

effect. Coordinating larger groups in an experiment will be difficult, but it is essential to document the size beyond which effects of additional people are no longer experienced. Such findings could assist in establishing acceptable visitor densities in buffer areas. A first step towards determining whether visitor number might be important could be obtained by replicating our experimental design on vulnerable species. Acknowledgements Research was conducted with permission from the Wreck Bay Aboriginal Community, Environment Australia (BDR03/00012), and the HMAS Cresswell. We thank Matt Hudson, Arthur Georges, and the Commander of the HMAS Cresswell for assistance obtaining relevant permits. Research was partially supported by the UCLA Office of Instructional Development, the Department of Ecology and Evolutionary Biology, and the Lida Scott Brown Ornithology Trust. We thank Brenda Larison and Michael Mitchell for statistical advice, and Ken and Patti Nagy for logistical support. References Abrams, P. A., 1994. The fallacies of "ratio–dependent" predation. Ecology, 75: 1842–1850. Blumstein, D. T., 2003. Flight–initiation distance in birds is dependent on intruder starting distance. Journal of Wildlife Management, 67: 852–857. Blumstein, D. T., Anthony, L. L., Harcourt, R. &

Ross, G., 2003. Testing a key assumption of wildlife buffer zones: is flight initiation distance a species–specific trait? Biological Conservation, 110: 97–100. Blumstein, D.T., Fernández–Juricic, E., LeDee, O., Larsen, E., Rodriguez–Prieto, I. & Zugmeyer, C., 2004. Avian risk assessment: effects of perching height and detectability. Ethology, 110: 273–285. Burger, J. & Gochfeld, M., 1981. Discrimination of the threat of direct versus tangential approach to the nest by incubating herring and great black– backed gulls. Journal of Comparative and Physiological Psychology, 95: 676–684. – 1990. Risk discrimination of direct versus tangential approach by basking iguanas (Ctenosaura similis): variation as a function of human exposure. Journal of Comparative Psychology, 104: 388–394. – 1991. Human distance and birds: tolerance and response distances of resident and migrant species in India. Environmental Conservation, 18: 158–165. Christ, C., Hillel, O., Matus, S., & Sweeting, J., 2003. Tourism and biodiversity: mapping tourism’s global footprint. Conservation International. Washington/Durban. Cooper, W. E. Jr., 1997. Threat factors affecting antipredatory behavior in the broad–headed skink (Eumeces laticeps): repeated approach, change in predator path, and predator’s field of view. Copeia, 3: 613–619. – 2003. Risk factors affecting escape behavior by the desert iguana, Dipsosaurus dorsalis: speed and directness of approach, degree of cover, direction of turning by a predator, and temperature. Canadian Journal of Zoology, 81: 979–984.

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35: 20–25. McLean, E. B. & Godin, J.–G. J., 1989. Distance to cover and fleeing from predators in fish with different amounts of defensive armour. Oikos, 55: 281–290. Naoki, K., 2003. The relative importance of arthropods and fruits in foraging behavior of omnivorous tanagers (Thraupidae): the comparison of three methods. Condor, 105: 135–139. Rodgers, J. A. Jr. & Smith, H. T., 1995. Set–back distances to protect nesting bird colonies from human disturbance in Florida. Conservation Biology, 9: 89–99. – 1997. Buffer zone disturbances to protect foraging and loafing waterbirds from human disturbance in Florida. Wildlife Society Bulletin, 25: 139–145. Runyan, A. M. & Blumstein, D. T., 2004. Do individual differences influence flight initiation distance? Journal of Wildlife Management, 68: 1124–1129. Wearing, S. & Neil, J., 1999. Ecotourism: impacts, potentials and possibilities. Butterworth Heinmannn, Oxford. Ydenberg, R. C. & Dill, L. M., 1986. The economics of fleeing from predators. Advances in the Study of Behavior, 16: 229–249.

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

Consell Assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Animal Biodiversity and Conservation 28.1 (2005)

Long–term trends of native and non–native fish faunas in the American Southwest J. D. Olden & N. L. Poff

Olden, J. D. & Poff, N. L., 2005. Long–term trends of native and non–native fish faunas in the American Southwest. Animal Biodiversity and Conservation, 28.1: 75–89. Abstract Long–term trends of native and non–native fish faunas in the American Southwest.— Environmental degradation and the proliferation of non–native fish species threaten the endemic, and highly unique fish faunas of the American Southwest. The present study examines long–term trends (> 160 years) of fish species distributions in the Lower Colorado River Basin and identifies those native species (n = 28) exhibiting the greatest rates of decline and those non–native species (n = 48) exhibiting the highest rates of spread. Among the fastest expanding invaders in the basin are red shiner (Cyprinella lutrensis), fathead minnow (Pimephales promelas), green sunfish (Lepomis cyanellus), largemouth bass (Micropterus salmoides), western mosquitofish (Gambussia affinis) and channel catfish (Ictalurus punctatus); species considered to be the most invasive in terms of their negative impacts on native fish communities. Interestingly, non–native species that have been recently introduced (1950+) have generally spread at substantially lower rates as compared to species introduced prior to this time (especially from 1920 to 1950), likely reflecting reductions in human–aided spread of species. We found general agreement between patterns of species decline and extant distribution sizes and official listing status under the U.S. Endangered Species Act. "Endangered" species have generally experienced greater declines and have smaller present–day distributions compared to "threatened" species, which in turn have shown greater declines and smaller distributions than those species not currently listed. A number of notable exceptions did exist, however, and these may provide critical information to help guide the future listing of species (i.e., identification of candidates) and the upgrading or downgrading of current listed species that are endemic to the Lower Colorado River Basin. The strong correlation between probability estimates of local extirpation and patterns of native species decline and present–day distributions suggest a possible proactive conservation strategy of implementing management actions for declining species prior to extreme rarity and imperilment. Key words: Lower Colorado River, Desert fishes, Extinction, Extirpation, Invasions, Biotic homogenization. Resumen Tendencias a largo plazo de la fauna piscícola autóctona y alóctona en el sudoeste americano.— La degradación ambiental y la proliferación de especies de peces alóctonas amenazan la fauna endémica, y única, de peces del sudoeste americano. El presente estudio examina las tendencias a largo plazo (> 160 años) de las distribución de especies de peces en la cuenca inferior del río Colorado e identifica las especies autóctonas (n = 28) que exhiben los índices más altos de disminución y las especies alóctonas (n = 48) que muestran los índices más altos de dispersión. Entre los invasores de la cuenca que se dispersan más rápido encontramos la carpa roja (Cyprinella lutrensis), la carpita cabezona (Pimephales promelas), el pez sol (Lepomis cyanellus), la perca americana (Micropterus salmoides), la gambusia (Gambussia affinis) y el pez gato (Ictalurus punctatus), especies consideradas las más invasivas por su impacto negativo en las comunidades autóctonas de peces. Las especies alóctonas introducidas recientemente (1950+), en general se han dispersado en tasas substancialmente más bajas que las introducidas con anterioridad (especialmente desde 1920 a 1950), probablemente reflejando una reducción en la dispersión de especies relacionada con el hombre. Encontramos concordancias entre los patrones de disminución de las especies y el tamaño de la zona de distribución existente, y el estatus en ISSN: 1578–665X

Olden & Poff

las listas oficiales del Acta de Especies Amenazadas de EE.UU. Las especies "en peligro de extinción", en general, han disminuido más y presentan una área de distribución menor que las especies "amenazadas", que a su vez muestran mayor disminución y menor área de distribución que las especies no incluidas en la lista. Hay, sin embargo, un número de excepciones notable, que pueden proporcionar información crítica para la confección de futuras listas de especies (es decir, identificando candidatos), y para el cambio de estatus de las especies endémicas en la cuenca inferior del río Colorado. La gran correlación entre la probabilidad estimada de extirpación local, y los patrones de disminución de las especies autóctonas y las distribuciones existentes sugieren una estrategia activa de conservación para implementar acciones de control de las especies en disminución antes de que lleguen a ser extremadamente escasas y amenazadas. Palabras claves: Cuenca inferior del río Colorado, Peces del desierto, Extinción, Extirpation, Invasiones, Homogeneización biótica. (Received: 22 IV 04; Conditional acceptance: 23 VI 04; Final acceptance: 23 VIII 04) Julian D. Olden, TNC David H. Smith Postdoctoral Fellow, Center for Limnology, Univ. of Wisconsin, Madison, WI 53706, U.S.A.– N. LeRoy Poff, Dept. of Biology and Graduate Degree Program in Ecology, Colorado State Univ., Fort Collins, CO 80523, U.S.A. Corresponding author: J. D. Olden. E–mail: olden@wisc.edu

Animal Biodiversity and Conservation 28.1 (2005)

Introduction "The Colorado [River], along the greater part of its lonely and majestic way, shall be forever unvisited and undisturbed." Lieutenant Joseph C. Ives (1857) Undeterred by legends of earlier expeditions that had failed, in 1868 John Wesley Powell was successful in his first historic journey down the treacherous Colorado River. Shortly thereafter, he stated his strong belief that, although considerably remote, the western resources were meant to be "redeemed" from a state of idleness for societal use (deBuys, 2001). During the next 130 years Powell’s vision was realized, and the waters of the Colorado River played a pivotal role in the settlement, growth and economic development of the American Southwest (Carlson & Muth, 1989). Efforts to tame the Colorado River began soon after the arrival of western Europeans, and today hundreds of dams and diversion structures have created one of the most controlled rivers on Earth (Fradkin, 1981). The Colorado River now provides irrigation water for more than 3.7 million acres (1.5 hectares) of farmland and delivers water and electrical power to 30 million people in the United States and Mexico (Mueller & Marsh, 2002). The Colorado River ecosystem has been greatly changed during the last century both by environmental alterations and by the introduction and spread of non–native fish species. The construction of water development projects began in the early 1900s (Fradkin, 1981; Carlson & Muth, 1989), and by the 1960s much of the mainstem river had been converted into a system of dams and diversions. Such changes continue to compromise the efficiency of life–history adaptations that have evolved to allow native fishes to thrive in the historically harsh, fluctuating environment of the Colorado River Basin (Miller, 1961; Minckley & Deacon, 1968, 1991). These dramatic environmental alterations have also facilitated the widespread and human–assisted invasion of non– native fish species that prey on and compete with native fishes (Minckley, 1991; Douglas et al., 1994; Marsh & Douglas, 1997; Marsh & Pacey, 2003). The case for conservation for the Lower Colorado River Basin is most urgent as the distributions of native fish species continue to decline at unprecedented rates and the spread of non–native fishes accelerate at an unparalleled speed (Minckley et al., 2003). Of the 31 native fish species in the Lower Colorado Basin, 25 are extinct, extirpated, listed under the US Endangered Species Act (USFWS, 1999), or believed to have suffered significant declines in distribution (Minckley, 1991). Remnant native populations are highly fragmented, compounding the problem of recovery and further elevating the probability of extinction (Fagan et al., 2002). In contrast, the deliberate introduction of non–indigenous fishes in the Lower Colorado River Basin began in the late 1800s (Minckley, 1999) and today more than 90 species have been introduced,

over half of which are considered established (Rinne & Janisch, 1995). Long–term conservation and management strategies for the Lower Colorado River Basin require knowledge about rates of change in the distribution of native and non–native species over time. Such strategies should be based on the analysis of large–scale, long–term datasets, which when combined with small–scale experimental studies, will provide complementary approaches to better understanding distributional shifts of native and non–native species and their association with altered environmental regimes. Broad–scale studies provide the foundation for proactive conservation by identifying native species declines prior to extreme rarity so that management efforts can be implemented before imperilment (Anderson et al., 1995; Patton et al., 1998). To date, evidence for the widespread replacement of native fish communities by non–native species in the Lower Colorado River Basin has been largely anecdotal and has lacked rigourous quantification. This is not to say that species’ distributions have not, and are not continuing to change. Rather the extent to which species’ distributions have decreased or increased over time has only been investigated for a limited number of species (mainly mainstem "big–river" species) and therefore remains largely unknown (and not quantified) for the majority of the species pool. We address this research need by presenting a historical perspective on long–term trends of native and non– native freshwater fish species distributions in the Lower Colorado River Basin using an unparalleled dataset containing tens of thousands of records collected over a century and a half. By conducting a broad, spatio–temporal assessment of changes in patterns of species’ occurrences, we shed important insight into rates of native species decline and non–native species expansion for the entire, present– day species pool of Lower Colorado River Basin. We address the question of whether long–term distribution trends can act as a surrogate for local extirpation risk of native species and "test" the biological component of the United States Endangered Species Act by comparing these trends to species’ official status. This comparison may help address the question of whether governmental legislation is, in fact, helping identity (and conserve) those rare, endemic species that have experienced substantial declines in their distributions and are currently rare in the Lower Colorado River. Material and methods The Colorado River is the primary waterway and lifeline of the American Southwest. Our study focused on the lower basin of the Colorado River (hereafter called Lower CR Basin), which includes ca. 26,000 km of streams and rivers between Glen Canyon Dam (located at the border between Arizona and Utah, U.S.A.) and the Gulf of California, and drains ca. 362,750 km2 from five states of the

United States and northwestern Mexico (fig. 1). To examine long–term temporal trends in native and non–native freshwater fish faunas we used the SONFISHES database (Desert Fishes Council, http:/ /www.desertfishes.org/na/gis/index.html). This database was developed by the tireless efforts of the late ichthyologist W. L. Minckley and contains > 38,000 occurrence records for 132 freshwater fish species from over 150 years of research throughout the Lower CR Basin. SONFISHES contains incidence, identity, and collection data for the complete holdings of major regional museum collections, numerous smaller holdings, and records from peer–reviewed and gray literature sources. Records are geo–referenced to within 1 km of their collecting site in a Geographic Information System (see Unmack, 2002 for details). Using ArcGIS (Environmental Services Research Inc., v. 8.3) we plotted 28,755 locality records from 1840 to 2000 (excluding occurrence records resulting from artificial translocations and reintroductions) for 28 native species and 48 non– native species from the SONFISHES database onto a digital coverage of streams and rivers in the Lower CR Basin (U.S. Geological Survey Enhanced River Reach File 2.0: http://www.usgs.gov/). We summarized the dataset in several ways to address the objectives of the study. Based on the large size and high temporal frequency of locality records in the dataset (see table 1) we were able to examine species patterns for 5 time periods: pre–1960; 1960–69; 1970–79; 1980–89; and 1990– 1999. Following Fagan et al. (2002), historical locality records for native species were considered to be those collected prior to 1980, whereas modern (or extant) native records were collected between 1980 and 1999. For native species, historical presences and extant absences constitute true extirpation events because modern records in the dataset are almost exclusively the result of intensive efforts by federal or state agencies to determine species’ complete distributions prior to listing decisions under the U.S. or Mexican Endangered Species Acts (Fagan et al., 2002). For each time period, we calculated the total river kilometres that each species was present by summing the length of the river segments (defined as a section of river delineated by two confluences) in which the species was recorded. Importantly, if a species was collected multiple times in the same river segment in the same time period, the length of the river segment was counted only once when calculating total river kilometres. Species’ distributions were estimated by dividing the total river kilometres that a species was present by the total river kilometres where all species were present during the specified time period (see table 1). This approach attempts to account for the influence of differential sampling effort (assumed to be proportional to the number of records) through time. Distributions were represented as a percentage and are assumed to provide an approximation for the total size of the species distribution in the entire Lower CR Basin.

Olden & Poff

For native species, distributional changes were calculated by subtracting extant range size (1980– 1999) from historical range size (pre–1980) and dividing by historical range size. Regression analyses with curve estimation (SPSS, v.11) were conducted to assess relationships between extant distribution size (%), percent distributional change and the estimated probability of local extirpation (as given for 25 species in table 1 of Fagan et al., 2002). Pairwise t–tests were used to compare distributional change and extant distributions between species with different official statuses under the U.S. Endangered Species Act (data obtained from the United States Fish and Wildlife Service: Threatened and Endangered Species System, http:// endangered.fws.gov, as of July 2004). For non– native species, dates of introduction were estimated using both table 6 of Mueller & Marsh (2002) and year of first occurrence in the SONFISHES database. Extant distributions were divided by the number of years since introduction (calculated from 2000) to estimate the rate of non–native species spread in the basin (km·year–1). Regression analyses were conducted to assess relationships between date of introduction, extant distribution size, and rate of spread for each species. Results Temporal patterns of native fish distributions Over the past century and a half, native fishes have predominantly decreased in their spatial distributions throughout the Lower CR Basin. Native fish species typically showed dramatic declines in the size of their distributions; a trend, however, that varied among species from 100% range reduction to 14% range expansion (table 2). In total, the distribution of 23 species decreased and 5 species slightly increased. Distribution trends over time illustrate that species have exhibited differential patterns of change. Gila trout, Virgin River spinedace and Gila topminnow, for example, have shown gradual reductions in their distribution, whereas Colorado pikeminnow, bonytail, razorback sucker, spikedace and Gila chub (among others) have shown punctuated declines. Other species appear to be occupying relatively constant ranges in the basin, including roundtail chub, bluehead sucker and Sonora sucker. Extant native fishes range from being completely absent (i.e., 0%) to occupying an estimated two– fifths of the basin (table 2). According to our results using modern locality records, five species have been extirpated (only Santa Cruz pupfish is truly extinct) and 15 species currently occupy extremely small distributions in the basin (< 5%), whereas other species still exhibit relatively broad distributions (> ca. 30%), e.g., specked dace, longfin dace, desert sucker and Sonora sucker. With respect to identifying those species that warrant special concern and targeted conservation efforts, it is necessary to examine associations

Animal Biodiversity and Conservation 28.1 (2005)

N W Colorado

E S

Little Colorado Salt Gila Sonora

United States

Fig. 1. Map of the Lower Colorado River Basin showing the 28,755 locality records from the SONFISHES database used in this study. Inset shows locations of major river drainages. Fig. 1. Mapa de la cuenca inferior del río Colorado mostrando los 28.755 registros de localidades de la base de datos SONFISHES utilizada en este estudio. El recuadro muestra la situación de los principales drenajes del río.

between the probability of local extirpation and broad–scale temporal trends in their distributions. We obtained estimates of local extirpation for 25 native species from table 1 of Fagan et al. (2002), who calculated these probabilities using the SONFISHES database as the proportion of historic records at a 5–km reach scale having no modern records (e.g., if an extinct species was present in 50 of 1000 pre–1980 records, its extinction probability would be 0.95). We found a significant positive and linear relationship between percent distributional decline and the probability of extirpation (R2 = 0.807, P < 0.001), indicating that native species exhibiting greater declines in their distributions at the whole basin scale also have a greater risk of local extirpation (fig. 2A). By examining deviations from this relationship we see that humpback chub (code X) and Virgin River spinedace (L), for example, have a higher estimated local extirpation risk compared to what is expected according to their basin–level decline over time (large positive residual). In contrast, desert pupfish (B), spikedace (N), loach minnow (R) and desert sucker (U) have a much lower extirpation risk as predicted from their level of distributional decline (large negative residual). Additionally, we found a significant negative and non–linear relationship between extant distribution size and the probability of local extirpation (R2 = 0.571, P < 0.001, quadratic curve), indicating that species with smaller present–day distributions have a greater estimated risk of local extirpation (fig. 2B). Species such as roundtail chub (V) and

Table 1. Diagnostic properties of the SONFISHES database used in this study. Reported fields include the number of locality records (i.e., fish observations) and total river kilometres during different time periods (T): N. Native; nN. Non–native; TRkm. Total river kilometres where all species were observed. Tabla 1. Propiedades de diagnóstico de la base de datos SONFISHES utilizada en este estudio. Los campos que se presentan incluyen el número de registros de localidad (observaciones de peces) y el total de kilómetros de río a lo largo de distintos períodos de tiempo (T): N. Autóctonos; nN. Alóctonos; TRkm. Kilómetros totales de río donde se observaron todas las especies.

Records T

TRkm

Pre–1960

1,463

462

6,496

1960–1969

3,106

1,671

6,875

1970–1979

2,772

1,400

7,839

1980–1989

3,033

4,125

7,918

1990–1999 Total

5,389

5,334

6,491

15,763

12,992

14,380

Olden & Poff

Probability of local extirpation

A 1.0 0.8 0.6 0.4 0.2 0.0 –20

0 20 40 60 80 100 Reduction in species distribution (%)

1.0 0.8 0.6 0.4 0.2 0.0 –5

5 10 15 20 25 30 35 40 45 Extant species distribution (%)

Fig. 2. Comparisons of percentages of distributional decline (A), extant distribution size (B) and probability of local extirpation of native fishes in the Lower Colorado River Basin. Least–squares regression lines are represented. Letter codes refer to native species in table 2. Fig. 2. Comparaciones entre porcentajes de disminución distribucional (A), tamaño de la distribución existente (B) y probabilidad de extirpación local de peces autóctonos en la cuenca inferior del río Colorado. Se representan las líneas de regresión de mínimos cuadrados. Los códigos de letras se refieren a las especies autóctonas de la tabla 2.

Sonora sucker (Y) have greater probability of extirpation than that expected from their present distributions in the basin, whereas the local extirpation probabilities of loach minnow (R), headwater chub (AA) and Little Colorado spinedace (BB) are much lower than is suggested from their current distributions. Visual examination of this figure suggests a threshold relationship where species with extant distributions greater than 10% are at much lower risk to local extirpation (probability < 0.5) compared to those species will extremely small distributions. Comparisons of species distributional change and extant distribution size with categories of official status under the U.S. Endangered Species Act (provided in table 2) also revealed interesting findings (fig. 3). With increasing risk category (i.e., not listed–threatened–endangered), we found average distributional decline to become larger and extant distribution size to become markedly smaller. Endangered species exhibit significantly greater distributional declines compared to threatened species (t1,15 = 2.93, P = 0.01) and to those species not listed (t1,20 = 4.33, P < 0.001). Similarly, endangered species exhibit significantly smaller extant distributions compared to threatened species (t1,15 = –4.78, P < 0.001) and to those species not listed (t1,20 = –4.30, P < 0.001). Extant distributions of threatened species were marginally smaller than species not listed (t1,11 = –1.90, P = 0.08), although the rate of distributional decline did not differ. For illustrative purposes figure 4 shows historical and extant distributions of three native species that exhibit markedly different % decline over time

and have different ESA statuses – bonytail (Endangered, 87.5% decline), spikedace (Threatened, 45.9% decline) and specked dace (Not Listed, 16.5% decline). Historical populations of bonytail in the Salt River, Gila River and mainstem Colorado River have been lost, and present–day distributions are restricted to Lake Mohave above Davis Dam. Spikedace populations were once present in the rivers Salt, Verde, Gila and San Pedro, but are now confined to only small stretches of the Gila River and Verde River. Specked dace was historically abundant and continuous throughout the basin, but its present–day distribution is greatly reduced and highly fragmented (e.g., Virgin River). Temporal patterns of non–native fish distributions In contrast to native fishes, the majority of non– native fishes showed substantial increases in the size of their distributions over time (table 3). At the extreme, fathead minnow, green sunfish and red shiner exhibit the greatest rates of invasion, spreading at over 50 km·year–1 since their dates of introduction. As expected, we found a strong, positive relationship between the rate of spread and extant distribution size (R2 = 0.874, P < 0.001), indicating that fast spreading non–native species are generally more broadly distributed in the basin (fig. 5A). A number of non–native species are much more broadly distributed in the basin as what is expected based their rate of spread, e.g., channel catfish (code 8), yellow bullhead (10) and common carp (11) (all introduced prior to 1900). In contrast, the

Animal Biodiversity and Conservation 28.1 (2005)

Table 2. Temporal patterns of native fish distributions in the Lower Colorado River Basin expressed as a percentage of the total kilometres of rivers where all species were observed for each time period. Nomenclature follows Nelson et al. (2004): C. Code, labels in figure 2; S. Species' official federal status under the U.S. Endangered Species Act (X. Extinct; E. Endangered; T. Threatened; PE. Proposed for listing as endangered; and no status means it is a species not listed); ER. Extant range, species distribution percentaje based on 1981–1999 records; and D. Decline, percent change in species’ distribution. Note that P. lucius, C. macularius, M. coriacea and G. robusta jordani are not extinct from the lower basin, but are estimated as exhibiting a 100% decline because the database does not contain recent records of their occurrence. Tabla 2. Patrones temporales de distribución de peces autóctonos en la cuenca inferior del río Colorado, expresadas en porcentajes del total de kilómetros de río donde se observaron todas las especies durante cada periodo de tiempo. La nomenclatura es según Nelson et al. (2004): C. Código, letras en la figura 2; S. Estatus federal oficial según el Acta de Especies Amenazadas de EE.UU. (X. Extinguida; E. En peligro de extinción; T. Amenazada; PE. Propuesta para que conste como especie en peligro; si no hay estatus la especie no se encuentra en la lista); ER. Rango existente en porcentaje de distribución de las especies basada en registros entre 1981–1999; D. Disminución, cambio de porcentaje en la distribución de las especies. Nótese que P. lucius, C. macularius, M. coriacea and G. robusta jordani no están extinguidos en la cuenca inferior del río, pero se estima que presentan una disminución del 100% debido a que la base de datos no contiene registros recientes de su presencia.

Temporal trends Species

S <1960 1960s 1970s 1980s 1990s ER

Colorado pikeminnow (Ptychocheilus lucius)

4.4

0.0

0.0 100.0

Desert pupfish (Cyprinodon macularius)

3.2

0.0

0.0 100.0

Moapa dace (Moapa coriacea)

1.0

0.9

0.0

0.0 100.0

Pahranagat roundtail chub (Gila robusta jordani)

1.2

1.1

1.0

0.0

0.0 100.0

Santa Cruz pupfish (Cyprinodon arcuatus)

0.7

0.0

0.0 100.0

Bonytail (Gila elegans)

8.1

2.4

2.0

0.6

0.8

0.5

87.7

Gila trout (Oncorhynchus gilae gilae)

1.9

2.0

1.7

0.4

0.0

0.3

84.0

Woundfin (Plagopterus argentissimus)

3.5

2.0

0.8

0.5

0.2

0.6

78.9

White River spinedace (Lepidomeda albivallis)

4.2

1.9

0.0

0.7

0.0

0.6

74.3

White River springfish (Crenichthys baileyi)

5.5

6.1

0.0

1.2

0.0

1.0

71.1

Flannelmouth sucker (Catostomus latipinnis)

5.5

7.3 11.0

4.0

1.1

4.0

62.2

Virgin River spinedace (Lepidomeda mollispinis) L

4.9

5.0

5.9

2.2

1.4

2.2

55.1

Razorback sucker (Xyrauchen texanus)

E 11.9

2.4

4.0

3.5

2.9

3.7

49.7

Spikedace (Meda fulgida)

T 12.9

2.8

4.5

3.4

4.9

4.2

45.9

Virgin River roundtail chub (Gila seminuda)

2.6

2.8

1.0

0.7

1.6

1.4

42.5

Gila topminnow (Poeciliopsis occidentalis)

8.3

2.5

1.7

3.6

3.9

3.7

36.8

Apache trout (Oncorhynchus gilae apache)

4.0

6.1

5.7

2.1

4.6

4.5

26.9

Loach minnow (Rhinichthys cobitis)

9.8

3.8

7.0

5.3

6.8

5.8

17.9

Speckled dace (Rhinichthys osculus)

32.2 40.6 40.6

16.5

52.8 50.3 42.6

Gila chub (Gila intermedia)

7.7

15.9

Desert sucker (Catostomus clarkii)

45.4 43.6 39.8

40.4 37.0 38.3

13.5

Roundtail chub (Gila robusta)

18.4 16.2 12.9

16.6 15.6 17.7

6.2

Bluehead sucker (Catostomus discobolus)

Humpback chub (Gila cypha)

Sonora sucker (Catostomus insignis)

Longfin dace (Agosia chrysogaster)

Headwater chub (Gila nigra)

PE 14.0

Little Colorado spinedace (Lepidomeda vittata) BB

4.0

4.6

6.2 10.4

5.6

7.9 13.2

6.0 13.0 11.1

0.6

1.5

3.0

1.4

3.5

2.5

–6.1

25.9 28.5 25.4

28.5 29.5 29.3

–8.2

34.9 28.1 33.5

45.4 46.2 40.9 –11.4

3.1

2.2

1.9

2.3

2.3 –12.6

1.5

3.0

1.4

3.0

3.9

3.6 –14.1

Discussion Distributions of native and non–native fishes have changed dramatically over the past century (Courtenay et al., 1984; Moyle, 1986; Gido & Brown, 1999), resulting in the biotic homogenization of fish faunas throughout North America (Rahel, 2000; Olden & Poff, 2004; Taylor, 2004). Biogeographic studies that explore long–term trends in species distributions can provide important insight into predicting the identity of those species declining in their distribution and under risk of extinction (e.g., Williams et al., 1989; Reinthal & Stiassny, 1991; Anderson et al., 1995; Patton et al., 1998). More generally, such studies can help understand how temporal changes in native species distributions relate to patterns of non–native species distributions, thus providing correlative insight into broad– scale implications of biological invasions. Temporal patterns of native fish distributions The American Southwest contains among the most threatened aquatic systems in North America, and despite early warnings (Dill, 1944; Miller, 1946), the unique, highly endemic, native fish fauna of the Lower Colorado River Basin have become increasingly imperilled over time. Our study provides quantitative estimates of distributional trends in native fishes and show significant declines of many species over both historical and recent times. These findings provide empirical support for the observa-

100

% Reduction in species distribution

% Extant species distribution

80 Percentage

two latest invaders to the basin, blue tilapia (9) and flathead catfish (6), were found to have very fast rates of spread, although they are still limited in their distribution due to their short invasion history. Although we expected the positive relationship in figure 5A because extant distribution size was used to calculate spread, the unexplained variation in this relationship can be attributed, in part, to the lack of a significant negative relationship between the year of introduction and rate of spread (R2 = 0.051, P = 0.124) (fig. 5B). Interestingly, we found a significant negative relationship between year of introduction and extant distribution size (R2 = 0.243, P < 0.001) (fig. 5C). Visual examination of this figure suggests a threshold relationship where non–native species introduced after 1950 have limited distributions (< 10%) whereas species will longer invasion histories in the basin have a broad range of distribution sizes (10–45%). Further, a number of species deviate from this relationship, indicating that species with long invasion histories do not necessarily have large extant distributions in the basin, e.g., yellow bass (35), white crappie (36), brown bullhead (42). Of note is that the top 5 fastest spreading non–native species (species 1–5 in table 3) were all introduced between 1920 and 1950 (fig. 5B) and have much greater present–day distributions than expected based on their length of invasion history (fig. 5C).

Olden & Poff

60 40 20 0 Nl T E Nl T U.S. Endangered Species Act Official status

Fig. 3. Comparisons of percentages of distributional decline and extant distribution size of native species classified as classified under the U.S. Endangered Species Act: Nl. Not listed; T. Threatened; E. Endangered. (Bars represent means and whiskers represent 1 standard error.) Fig. 3. Comparaciones entre los porcentajes de disminución y de tamaño de la distribución existente de peces autóctonos clasificados según el Acta de Especies en peligro de Extinción de EE.UU.: Nl. No están en la lista; T. Amenazadas; E. En peligro. (Las barras representan las medias y las prolongaciones representan un error estándar igual a 1.)

tional hypothesis of Mueller & Marsh (2002) who postulated that native fishes rapidly declined between 1890 and 1935 because of intensive water management practices and the introduction of common carp, bullhead and channel catfish, which was then followed by a prolonged period when remnant communities gradually disappeared after the construction of Roosevelt, Hoover, Imperial, and a number of other dams that caused remarkable hydraulic and physical change to the basin. Our results indicate the highest rate of declines in a number of native fish species that have previously identified as imperilled in the basin, including a number of "big–river" fishes such as Colorado pikeminnow, razorback sucker, bonytail and flannelmouth sucker; and species inhabiting marginal spring and stream habitats such as the desert pupfish and Gila topminnow (Minckley & Deacon, 1991; Mueller & Marsh, 2002). The last wild Colorado pikeminnow was caught in 1975 in the Lower Colorado River; bonytail likely persist only in Lake Mohave; and although annual spawning occurs, razorback sucker populations consist largely of old

Animal Biodiversity and Conservation 28.1 (2005)

Table 3. Temporal patterns of non–native fish distributions in the Lower Colorado River Basin expressed as the percentage of the total kilometres of rivers where all species were observed for each time period. Nomenclature follows Nelson et al. (2004): C. Code, labels in figure 5; I. Year of introduction or first observed in the basin; ER, Extant range, percentage of species distribution based on 1980– 1999 records; S. Rate of spread in km/year. Tabla 3. Patrones temporales de distribución de peces alóctonos en la cuenca inferior del río Colorado expresadas como el porcentaje del total de kilómetros de río donde se observaron todas las especies en cada período. La nomenclatura es según Nelson et al. (2004): C. Código, números en la figura 5; I. Año de introducción o primera observación en la cuenca; ER. Rango existente, porcentaje de distribución de las especies basada en los registros de 1980–1999; S. Tasa de dispersión en km/año.

Temporal trends Species

<1960 1960s 1970s 1980s 1990s 1.9

Fathead minnow (Pimephales promelas)

1950

7.7

21.8

28.7

39.2

39.3

74.1

Green sunfish (Lepomis cyanellus)

1937 11.4 16.9

19.8

30.9

44.1

42.0

62.9

Red shiner (Cyprinella lutrensis)

1950

0.9 17.4

18.7

27.4

27.9

28.9

54.6

Western mosquitofish (Gambusia affinis)

1922 15.4 16.5

19.2

28.1

27.5

31.3

37.9

Largemouth bass (Micropterus salmoides)

1935

9.2 15.3

11.6

20.6

19.9

23.6

34.2

Flathead catfish (Pylodictis olivaris)

1962

1.0

0.6

3.1

9.3

9.5

23.7

Bluegill (Lepomis macrochirus)

1937

8.0

8.2

7.2

12.8

12.7

15.6

23.4

Channel catfish (Ictalurus punctatus)

1892 11.2 15.1

14.6

27.5

15.4

25.2

22.0

Blue tilapia (Oreochromis aureus)

1978

0.0

0.3

5.9

1.0

4.8

20.7

Yellow bullhead (Ameiurus natalis)

1899

5.7

7.6

10.9

16.3

21.8

21.9

20.4

Common carp (Cyprinus carpio)

1881 14.0 16.5

15.8

21.7

21.2

25.1

19.9

Smallmouth bass (Micropterus dolomieui) 12

1942

3.5

5.2

10.8

10.1

11.1

18.0

Rainbow trout (Oncorhynchus mykiss)

1900 12.4 18.7

2.8

23.3

16.7

20.3

19.1

18.0

Threadfin shad (Dorosoma petenense)

1953

1.3

6.3

3.5

8.4

2.3

7.9

15.8

Golden shiner (Notemigonus crysoleucus) 15

1953

0.3

2.4

2.3

4.0

7.0

6.3

12.7

Striped bass (Morone saxatilis)

1959

0.4

0.8

1.6

5.6

1.5

5.2

11.9

Brown trout (Salmo trutta)

1924

2.4

7.3

8.6

7.1

10.3

8.9

11.0

Goldfish (Carassius auratus)

1944

0.1

6.8

1.4

5.5

2.4

6.3

10.6

Plains killifish (Fundulus zebrinus)

1950

0.0

1.3

4.6

4.3

2.2

4.8

9.0

Black crappie (Pomoxis nigromaculatus)

1936

7.5

2.5

4.4

4.7

2.9

5.6

8.3

Black bullhead (Ameiurus melas)

1904

9.3 11.2

6.8

7.7

6.7

8.2

8.1

Sailfin molly (Poecilia latipinna)

1950

1.0

2.7

1.4

5.1

0.7

4.2

7.9

Brook trout (Salvelinus fontinalis)

1920

2.6

4.2

3.9

4.3

7.6

6.3

7.4

Walleye (Sander vitreus)

1971

0.0

0.1

0.3

0.8

1.5

1.8

5.7

Rio Grande cichlid (Herichthys cyanoguttatus) 25

1996

0.0

0.3

0.2

5.5

Arctic grayling (Thymallus arcticus)

1965

0.0

0.9

0.8

2.2

2.0

5.3

Cutthroat trout (Oncorhynchus clarkii)

1937

1.3

0.6

2.2

3.2

3.3

5.0

Northern pike (Esox lucius)

1969

0.0

1.3

1.5

0.1

1.3

4.0

Redside shiner (Richardsonius balteatus)

1950

0.0

0.8

1.1

2.4

0.0

2.0

3.8

Redear sunfish (Lepomis microlophus)

1951

2.2

1.7

2.7

1.8

0.7

1.9

3.6

Mozambique tilapia (Oreochromis mossambica) 31

1965

0.0

1.0

3.4

1.5

0.0

1.2

3.2

Redbelly tilapia (Tilapia zilli)

1965

0.0

0.3

1.4

1.0

1.1

3.1

Rock bass (Ambloplites rupestris)

1962

0.0

0.4

0.5

0.7

1.8

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Table 3. (Cont.) Temporal trends Species

Guppy (Poecilia reticulata)

1950

<1960 1960s 1970s 1980s 1990s 0.0

1.3

0.5

0.8

0.4

0.9

1.6

Yellow bass (Morone mississippiensis)

1931

0.4

0.3

1.2

0.1

1.1

1.5

White crappie (Pomoxis annularis)

1934

1.8

0.4

0.0

0.1

0.7

0.6

0.8

Shortfin molly (Poecilia mexicana)

1950

0.0

3.7

0.5

0.3

0.0

0.2

0.4

Rio Grande sucker (Catostomus plebeius) 38

1950

1.9

0.9

0.8

0.0

0.2

0.1

0.3

White bass (Morone chrysops)

1960

0.0

0.1

0.0

0.1

0.0

0.1

0.2

Bigmouth buffalo (Ictiobus cyprinellus)

1964

0.0

0.5

0.2

0.1

0.2

Smallmouth buffalo (Ictiobus bubalus)

1950

0.0

0.5

0.3

0.0

0.1

Brown bullhead (Ameiurus nebulosus)

1910

6.6

1.5

0.0

Convict cichlid (Archocentrus nigrofasciatus)

1955

0.0

1.5

0.0

Grass carp (Ctenopharyngodon idellus)

1976

0.0

1.8

0.0

Black buffalo (Ictiobus niger)

1966

0.0

0.4

0.2

0.0

Warmouth (Lepomis gulosus)

1958

0.2

0.0

Spotted bass (Micropterus punctulatus)

1956

0.6

0.5

0.1

0.0

Yellow perch (Perca flavescens)

1951

0.6

0.2

0.0

adults with no evidence of recruitment (Minckley, 1991). Other, comparatively less studied, species also experienced significant declines over time, including spikedace and woundfin. Similarly, loach minnow has seen dramatic declines when compared to historical records, although there is some evidence that its distribution has remained fairly constant over the recent decades. This finding is supported by recent work showing the local stability of remnant loach minnow populations in Arizona (Marsh et al., 2003). In contrast to the many species that have exhibited significant declines in their distributions, longfin dace, desert sucker and Sonora sucker are presently abundant throughout the basin and appear to have maintained relatively stable distributions over time. Finally, temporal trends and present–day sizes of species’ distributions were highly correlated to estimates of local extirpation risk for the native fishes. This suggests that long–term studies conducted at the drainage scale might provide a coarse–level surrogate for identifying those species that are most likely to extirpated at the local reach scale. In summary, a number of explanations are possible to describe the distributional changes observed in our study. By explicitly linking patterns of environmental degradation and non–native species distributions to patterns of native species distributions, we could gain greater insight into potential mechanisms of native imperilment and thus better tease apart the synergistic manner in which these stresses are threatening native faunas in the Lower Colorado River Basin (Olden et al., in press).

Temporal patterns of non–native fish distributions The establishment of non–native fish species has substantially changed native fish community structure in southwestern rivers (Minckley & Deacon, 1968, 1991; Meffe, 1985; Rinne & Minckley, 1991). While the total number of non–native fishes continues to increase across the U.S. (Gido & Brown, 1999; Rahel, 2000; Meador et al., 2003), quantitative estimates of distributional changes are lacking for most fish, and such analyses are rarely conducted at large temporal and spatial scales that are required to properly understand these processes. Our study contributes to a better understanding of the shear magnitude in which non–native species have spread throughout the Lower Colorado River Basin over the past century and points to those invaders that have exhibited considerable rates of expansion since their introduction. This information provides a scientific basis for the management of fast spreading species and enhanced education targeted specifically to reducing their future introduction by humans. Perhaps our most striking result is that red shiner, fathead minnow, green sunfish, largemouth bass, western mosquitofish and channel catfish are the among the fastest expanding invaders in the basin, and these species have also been identified by expert ichthyologists as having the greatest negative impacts on native fish communities (Hawkins & Nesler, 1991; J. D. Olden, unpublished survey data). Recent studies have further supported the significant ecological effects of these

Animal Biodiversity and Conservation 28.1 (2005)

Historical (pre–1980)

Extant (1980–1999)

Fig. 4. Maps of historical and extant distributions of three native fishes exhibiting markedly different percentage of decline over time and having different statuses under U.S. Endangered Species Act: A. Bonytail (Gyla elegans), endangered, 87.7% decline; B. Spikedace (Meda fulgida), threatened, 45.9% decline; C. Specked dace (Rhinichthys osculus), not listed, 16.5% decline. Thicker lines represent river segments where the species was recorded present during the time period. See inset of figure 1 for locations of major river drainages. Fig. 4. Mapas de las distribuciones históricas y existentes de tres peces autóctonos mostrando porcentajes distintos de disminución a lo largo del tiempo y con distintos estatus reconocidos en el Acta de Especies Amenazadas de EE.UU.: A. Carpita elegante (Gyla elegans), en peligro, 87,7% de disminución; B. Charal espinoso (Meda fulgida), amenazado, 45,9% de disminución; C. Carpa pinta (Rhinichthys osculus), no listada, 16,5% de disminución. Las líneas gruesas representan las secciones del río donde se registró la especie a lo largo del periodo de estudio. Ver el recuadro de la figura 1 para las localizaciones de los principales drenajes del río.

non–native species on native fishes (e.g., Courtenay & Meffe, 1989; Douglas et al., 1994; Marsh & Douglas, 1997; Dudley & Matter, 2000; Marsh & Pacey, 2003), in addition to their role as vectors of exotic parasites, including the Asian fish tapeworm (Clarkson et al., 1997). Of particular interest is that non–native species introduced after 1950 have generally spread at substantially lower rates as compared to non– native introduced prior to this time (especially 1920–1950), and consequently occupy much smaller distributions. The most optimistic explanation for this threshold pattern is that recent decades have seen declines in U.S. government–sanctioned

introductions of gamefish or forage species outside their native ranges (Courtenay & Moyle, 1996), a pattern that reflects both a saturation of gamefish species in many drainages and a heightened awareness by fisheries biologists of the problems associated with non–native species (Rahel, 1997). However, inadvertent introductions (e.g., aquarium trade releases: Padilla & Williams, 2004) and unauthorized introductions (Rahel, 2004) by the public continue, which likely explain the notable exceptions to this general pattern – blue tilapia and flathead catfish – both species exhibiting very high faster rates of spread since its introduction in recent decades.

Olden & Poff

B Rate of spread (km/year)

50 40 30 20 10 0 0

20 30 40 50 60 70 Rate of spread (km/year) Extant species distribution (%)

Extant species distribution (%)

80 70 60 50 40 30 20 10 0 1880

1900 1920 1940 1960 1980 Year of introduction

2000

50 40 30 20 10

0 1880

1900 1920 1940 1960 1980 Year of introduction

2000

Fig. 5. Comparisons of extant distribution size percentages, rate of spread (km/year) and year of introduction of non–native fishes in the Lower Colorado River Basin. Least–squares regression lines are represented. Numbers refer to non–native species in table 3. Fig. 5. Comparaciones entre el porcentaje del tamaño de distribución existente, la tasa de dispersión (km/año) y año de introducción de peces alóctonos el la cuenca inferior del río Colorado. Se representan las líneas de regresión de mínimos cuadrados. Los números indican las especies alóctonas de la tabla 3.

Results from our study show both similarities and differences to other long–term studies of fish invasions conducted in Great Plains streams of Wyoming (Patton et al., 1998) and Oklahoma and Kansas (Gido et al., 2004). Great Plains stream are similar to desert streams in the American Southwest in that they present harsh environmental conditions and disturbance regimes (Dodds et al., 2004), and they have been invaded by a relatively large number of non–native species as compared to other regions of the United States (Gido & Brown, 1999), thus making it suitable to compare rates of spread between these regions. Based on species common to all three regions, our study found that red shiner, fathead minnow, green sunfish, largemouth bass, channel catfish and black bullhead exhibit relatively high rates of spread, whereas Patton et al. (1998) found that these species’ distributions were declining in Wyoming. However, similar patterns were found

for common carp (range expansion) and white crappie, rock bass and yellow perch (range declines or low rates of spread). In contrast to distributional changes, comparisons of extant distribution sizes showed remarkable similarity for 15 species shared by the Lower Colorado River basin and plain streams in Oklahoma and Kansas (Gido et al., 2004). In summary, these comparisons suggest that a number of non–native species exhibit similar distribution sizes in these different ecoregions, yet the rate at which they have spread to obtain their distributions differs (likely a result of different rates and timing of human introductions). Conservation and management implications for native fishes The United States Endangered Species Act (ESA) of 1973, together with other environmental legisla-

Animal Biodiversity and Conservation 28.1 (2005)

tion, has played an important role in the effort to conserve native fishes in the Lower Colorado Basin (Minckley et al., 2003). Although in principle ESA decisions are based on the best biological information, many factors other than biology, including socioeconomic and political issues, influence most plans and projects. We believe our study provides some new insight into the biological component of the listing process for the Lower Colorado River by relating long–term species’ distributional trends to their federal status under the ESA. This comparison may help address the question of whether the ESA is, in fact, helping identity (and conserve) those rare species experiencing substantial declines in their distributions. Our results show good agreement between patterns of species decline and extant distribution sizes and expectations based on their official status. "Endangered" species have generally experienced greater declines in their distributions compared to "threatened" species, which in turn have shown greater declines than those species not currently listed. Likewise, non–listed species have three times larger extant distributions than "threatened" species, which in turn have two time larger distributions than "endangered" species. These patterns are reassuring, in that they support the biological underpinnings of the ESA for the native species of this region. Interestingly, although general patterns were in agreement we did find a number of notable exceptions, which we believe can provide critical information to help guide the future listing of species (i.e., identification of candidates) and the upgrading or downgrading of current listed species that are endemic to this region. For example, based on temporal trends and extant distribution sizes alone, our results suggest that 3 non–listed species might merit consideration for listing under ESA: headwater chub could be a candidate for threatened status (on the basis of extant distribution), and flannelmouth sucker and Virgin River spinedace could be candidates for endangered status. Our results also suggest that Apache trout have experienced significant declines and exhibit extant distributions that correspond more closely with “endangered” species and therefore could be considered for upgrading from its threatened status. Other factors not evident from distributional data support these ideas, e.g., Apache trout are also at high risk to the effects of intensive hybridization with non–native trout (Dowling & Childs, 1992) as well as those arising from hatchery practices. It is very interesting to note that Apache trout was formerly listed as endangered but was downlisted in 1975 to threatened status to facilitate a management program that included recreational angling (Behnke, 1992). This is an excellent example where socioeconomic issues have likely outweighed species biology in the ESA listing process. Concerning potential data limitations When analyzing compiled data that has not been systematically collected, as is the case in this study,

it is important to consider the effects of sampling bias, spatial scale and data resolution when interpreting the results. Sampling intensity (i.e., as indicated by the number of records) increased through time for both native and non–native species. Consequently, our study provides minimum estimates of native species decline because sampling intensity in recent decades always exceeded that of previous decades, whereas the opposite is true for non–native species where rates of spread may be over–estimated. Spatial scale must also be considered when using historic data to examine species declines. Patton et al. (1998) found greater changes in species distributions at the reach scale compared to the drainage scale for 37 species in Wyoming, which suggests that smaller–scale analyses of temporal trends may provide an over–estimates of species declines. Lastly, although species presence data are not as informative as abundance data for assessing temporal trends, local population fluctuations may confound trend interpretations, especially in for highly variable desert streams characteristic of the American Southwest (Eby et al., 2003). While we acknowledge the above data limitations and issues of sampling and spatial scale, we believe our analyses are appropriate for this region at a scale of study relevant to broad–scale conservation and management planning. Indeed, a number of studies have already illustrated the utility of the SONFISHES database for addressing pressing fish conservation issues in the American Southwest (e.g., Fagan et al., 2002; Unmack & Fagan, 2004) and our study is the first to use this powerful dataset to address broad–scale changes in fish distributions. Conclusion The extensive regulation of the Lower Colorado River Basin threatens native fish faunas by drastically altering natural flow, temperature and sediment regimes, and promoting the establishment and spread of non–native species. Results from this study provide a reach–scale examination of distributional trends of the fishes of the Lower Colorado River Basin over the past century. These trends indicate high priorities for conservation and management efforts by identifying declining species before they are lost forever. However, before management plans can be implemented we must first recognize and quantify the degree to which native species are declining and non–native species are spreading across riverine landscapes. Acknowledgements This research would not of been possible without the tireless efforts of the late W. L. Minckley, who dedicated his life to the conservation of desert fishes in the American Southwest. We thank Peter Unmack for graciously providing the SONFISHES database and Kevin Bestgen for his continued insights on Colorado

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the people? In: Propagated Fishes in Resource Management: in press. Proceedings of a Symposium by the American Fisheries Society. Reinthal, H. F. & Stiassny, M. L. J., 1991. The freshwater fishes of Madagascar: a study of an endangered fauna with recommendations for a conservation strategy. Con. Biol., 5: 231–243. Rinne, J. N. & Janisch, J., 1995. Coldwater fish stocking and native fishes in Arizona: past, present, and future. Amer. Fish. Soc. Sym., 15: 397–406. Rinne, J. N. & Minckley, W. L., 1991. Native fishes of arid lands: a dwindling resource of the desert Southwest, p. 45. General Technology Report RM–206, U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station, Fort Collins, CO. Taylor, E. B., 2004. An analysis of homogenization and differentiation of Canadian freshwater fish faunas with an emphasis on British Columbia. Can. J. Fish. Aq. Sci., 61: 68–79. Tyus, H. M. & Saunders, J. F., 2000. Nonnative fish control and endangered fish recovery: Lessons from the Colorado River. Fisheries, 25: 17–24. Unmack, P. J., 2002. Arizona State University. GIS Manual for use with the Lower Colorado Basin Fish Database. Biology Department, Arizona State University, Tempe, Arizona. w w w. p e t e r. u n m a c k . n e t / g i s / f i s h / c o l o r a d o / gismanual.pdf. Unmack, P. J. & Fagan, W. F., 2004. Convergence of differentially invaded systems toward invader– dominance: time–lagged invasions as a predictor in desert fish communities. Biol. Invas., 6: 233–243. United States Fish and Wildlife Service (USFWS), 1999. Endangered and Threatened Wildlife and Plants, 50 CFR 17.11 and 17.12. U.S. Fish and Wildlife Service, Washington, DC. Williams, J. E., Johnson, J. E., Hendrickson, D. A., Contreras–Bladeras, S., Williams, J. D., Navarro– Mendoza, M. McAllister, D. E. & Deacon, J. E., 1989. Fishes of North America: endangered, threatened, or of special concern. Fisheries, 14: 2–20.

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

Consell Assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Animal Biodiversity and Conservation 28.1 (2005)

Ctenolepisma almeriensis n. sp. of Lepismatidae (Insecta, Zygentoma) from south–eastern Spain R. Molero–Baltanás, M. Gaju–Ricart & C. Bach de Roca

Molero–Baltanás, R., Gaju–Ricart, M. & Bach de Roca, C., 2005. Ctenolepisma almeriensis n. sp. of Lepismatidae (Insecta, Zygentoma) from south–eastern Spain. Animal Biodiversity and Conservation, 28.1: 91–99. Abstract Ctenolepisma almeriensis n. sp. of Lepismatidae (Insecta, Zygentoma) from south–eastern Spain.— Ctenolepisma almeriensis n. sp., from the south–eastern part of the Iberian Peninsula is described. This species was determined previously as Ctenolepisma lineata (Fabricius, 1775), which is widespread over the south–western Palaeartic region. The main difference between the two species is the setation of thoracic sternites. In each bristle–comb of the mesosternum and the metasternum, macrosetae are arranged in a single row in C. lineata and in two parallel rows in C. almeriensis n. sp. In the prosternum, the first species shows 1–2 irregular lines of macrosetae per comb, and the new species shows 2–3 lines. Based on other parameters of setation, a discriminant analysis was carried out to separate a group of Spanish specimens of C. lineata from another group of specimens of the new species. This analysis demonstrated the validity of the occurrence of double or single lines of macrosetae in thoracic sternites to distinguish between the two species. Key words: Ctenolepisma almeriensis n. sp., Ctenolepisma lineata, Spain, Thysanura, New species, Arid regions fauna Resumen Ctenolepisma almeriensis sp. n. de Lepismatidae (Insecta, Zygentoma) de España suroriental.— Se describe Ctenolepisma almeriensis sp. n., distribuida por el sureste de la Península Ibérica. Previamente esta especie se había identificado como Ctenolepisma lineata (Fabricius, 1775), extendida por el Paleártico suroccidental. La principal diferencia entre ambas especies reside en la quetotaxia de los esternitos torácicos: las macroquetas de cada peine de meso– y metasterno forman una sola fila en C. lineata, mientras que se disponen en dos líneas paralelas en C. almeriensis sp. n. En el prosterno, cada peine de C. lineata consta de 1–2 líneas irregulares, por 2–3 filas en la nueva especie. Se ha realizado un análisis discriminante para separar, con base en otros parámetros de la quetotaxia, un grupo de especímenes españoles de C. lineata de otro grupo encuadrable a priori en la nueva especie, demostrándose que la presencia de filas simples o dobles de macroquetas en los esternitos torácicos representa una característica válida para la diferenciación entre ambas especies. Palabras clave: Ctenolepisma almeriensis sp. n., Ctenolepisma lineata, España, Thysanura, Especie nueva, Fauna de zonas áridas. (Rebut: 31 I 04; Acceptació condicional: 30 VII 04; Acc. definitiva: 15 X 04) Rafael Molero Baltanás & Miguel Gaju Ricart, Dept. de Zoología, C–1 Campus de Rabanales, Univ. de Córdoba. 14014–Córdoba, España (Spain); Carmen Bach de Roca, Dept. de Biología Animal, Vegetal y Ecología, Fac. de Ciencias, Univ. Autónoma de Barcelona, 08193–Bellaterra (Barcelona), España (Spain). Corresponding author: R. Molero Baltanás. E–mail: ba1mobar@uco.es ISSN: 1578–665X

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Introduction Ctenolepisma lineata (Fabricius, 1775) is a widespread species of Lepismatidae native to the south of Europe and introduced in other regions and continents. Following revision of material that had been determined as this taxon from different countries, notable variability has been detected, to the point that it is reasonable to state that C. lineata is not one but a group of species. Several forms have been found within the Iberian Peninsula, the most widespread considered here as the typical C. lineata. A different form which occurs in the south–east Spain is described here as a new species. Material and methods As usual in this order, specimens were fixed in alcohol, and many were dissected and mounted in Tendeiro medium for microscopic observation to verify identification. The studied material is deposited in the following institutions: MNCN. Museo Nacional de Ciencias Naturales (Madrid, Spain); UCO. Dept. de Zoología, Univ. of Córdoba (Córdoba, Spain). Some specimens have been studied and published previously: (a) included in Molero–Baltanás

et al. (1992) as C. lineata; (b) included in Molero– Baltanás et al. (1994), also as C. lineata. To compare the new species with C. lineata, a total of 100 specimens were selected, 50 from each species (25 males and 25 females), each from a different sample and locality. Statistical analysis included six quantitative variables in each specimen, resulting in a total of 600 data. A standardized principal component analysis was performed to obtain combinations of the six variables which account for most variability in the data. The most useful variables were then included in a discriminant analysis to determine whether C. lineata and C. almeriensis were significantly different. Mann–Whitney U–tests were also conducted to compare medians of the four groups. Variables and their abbreviations used in the discriminant analysis for the differentiation between C. lineata and C. almeriensis: N–notum. Number of macrosetae of a posterolateral comb of the metanotum; N–pros. Number of macrosetae of a posterolateral comb of an antedistal comb of the prosternum; N–meso. Number of macrosetae of a posterolateral comb on the mesosternum; N–meta. Number of macrosaeta of a posterolateral comb on the metasternum; N–uro. Number of macrosetae of a lateral comb of the urosternite IV; D/a[Mt]. Ratio distance between lateral combs of urosternite IV / width of a comb.

0.2 mm 0.2 mm

4 0.2 mm

5 0.2 mm

6 0.2 mm 0.2 mm

Figs. 1–6. Ctenolepisma almeriensis n. sp., holotype: 1. Maxillary palp; 2. Distal article of the labial palp; 3. Prosternum; 4. Mesosternum; 5. Metasternum; 6. Metasternum of a paratypus from Valencia. Figs. 1–6. Ctenolepisma almeriensis sp. n., holotipo: 1. Palpo maxilar; 2. Artejo distal del palpo labial; 3. Prosterno; 4. Mesosterno; 5. Metasterno; 6. Metasterno, de un paratipo de Valencia.

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Results and discussion Description of Ctenolepisma almeriensis n. sp. Studied Material Holotype: Almería, Dalías, Dos Hermanas Peak, Gádor Mountains, 1,800 m, 23 III 89, one male (MNCN, ref. 9493). Allotype: 1 female collected in the same locality and date, with 1 male, 2 females and a young specimen, all paratypes (UCO, ref. 0413) (a). Other material studied (all paratypes): Albacete: Hellín, 30 IV 92, 1 male (UCO, ref. Z1177). Alicante: Alicante, Albatera (Crevillente mountains), 11 IV 92, 2 males and 1 female, (UCO, ref. Z1326); Jijona, 14 IV 92, 1 female (UCO, ref. Z1401). Almería: Adra, Puente del Río, 23 III 89, 2 females (UCO, ref. Z0420); Alcolea, 19 III 92, 4 males (UCO, ref. Z0999); Mazarrulleque, 23 III 89, 6 males and 4 females (UCO, ref. Z0426) (a); Berja, 17 VIII 88, 1 male (UCO, ref. Z0375) (a); Berja (500 m), 23 III 89, 1 male and 4 females (UCO, ref. Z0437) (a); Berja (Gádor mountains, 1,150 m), 23 III 89, 2 males and 3 females (UCO, ref. Z0433) (a); El Ejido (Punta Sabinal), A. Tinaut leg., 06 X 92, 1 female (UCO, ref. Z1973); Enix (750 m), 23 III 89, 1 male and 1 female, ref. Z0432 (a); Gérgal (Filabres mountains, 900 m), 17 VI 91, 1 male, ref. Z0557; Huércal–Overa, 14 IV 76, 2 males and 4 females (UCO, ref. Z0478) (a); Lucainena de las Torres (500 m), 24 III 89, 1 young specimen (UCO, ref. Z0411) (a); Mojácar, near the beach, 10 IV 92, 3 males and 4 females (UCO, ref. Z0915); Nacimiento to Abla, 17 VIII 88, 1 female (UCO, ref. Z0379) (a); Níjar, Cabo de Gata, 20 V 86, 3 males and 1 female (UCO, ref. Z0317) (a); Níjar, Cabo de Gata, 23 III 89, 16 males and 10 females (UCO, ref. Z0430) (a); Níjar (300 m), 24 III 89, 2 males (UCO, ref. Z0412) (a); Níjar, San José, 24 III 89, 2 males and 4 females (UCO, ref. Z0424) (a); Níjar, Pozo de los Frailes, 24 III 89, 4 males and 1 female (UCO, ref. Z0505) (a); Níjar, Cabo de Gata, 30 III 89, 1 male (UCO, ref. Z1990); Níjar, Rodalquilar, 17 VI 91, 2 males and 3 females (UCO, ref. Z0561); Purchena, 21 VI 86, 2 males and 1 female (UCO, ref. Z0211) (a); Roquetas de Mar, 06 IV 85, 1 female (UCO, ref. Z0506); Serón to Los Menas, Filabres mountains, 25 III 89, 1 female (UCO, ref. Z0408) (a); Tabernas Desert, 15 IV 76, 1 male and 2 females (UCO, ref. Z0474) (a); Tabernas Desert, 17 VIII 88, 2 females (UCO, ref. Z0376) (a); Uleila del Campo (Filabres mountains), 17 VIII 88, 1 female (UCO, ref. Z0377) (a); Uleila del Campo (650 m), 24 III 89, 2 males and 1 female (UCO, ref. Z0399) (a); Uleila del Campo to Cantoria, Filabres mountains, 25 III 89, 1 male (UCO, ref. Z0401) (a); Dalías, Dos Hermanas Peak, Gádor Mountains (1,800 m), 23 III 89, 1 male, 3 females and 1 young specimen (UCO, ref. 0413) (a). Murcia: Blanca, Pila mountains, 30 III 93, 1 male and 1 female (UCO, ref. Z2038); Mazarrón, 21 VI 86, 3 males and 2 females (UCO, ref. Z1417) (b); Mazarrón to Águilas, 21 VI 86, 1 female (UCO, ref. Z1421).

Valencia: Albaida, 2 XI 91, 2 females (UCO, ref. Z1469); Bicorp to Quesa, 26 IV 92, 2 males (UCO, ref. Z1543); Mogente, 28 V 88, 1 female (UCO, ref. Z1316); Mogente, 2 XI 91, 1 female (UCO, ref. Z1409); Mogente, 31 III 93, 3 females (UCO, ref. Z2039); pine–tree forest of El Saler, 11 IX 78, 10 males and 8 females (UCO, ref. Z1317). Habitat and distribution This species is found under stones and bark, at the base of pine–trees or Juniperus shrubs. The habitat is similar to that of C. lineata in Spain, but the new species appears to tolerate a higher degree of aridity. It is found from sea level to 2,000 m at Sierra de Gádor and Sierra de los Filabres in the province of Almería. C. almeriensis n. sp. is mainly seen in the arid bio–geographic province named "Murciano— Almeriense" (Rivas–Martínez, 1987) in south–eastern Spain, being more frequent in the south (province of Almería) where the rainfall is lower. It spreads over the Spanish provinces of Almería, Murcia, Alicante and Valencia, always on the Mediterranean slope. The species takes its name from the province where it is most abundant. Description Body length of females up to 13.2 mm, males up to 12 mm. Fusiform and relatively robust body, thorax slightly wider (up to 3.5 mm) than the abdomen base. Faint to distinct epidermic pigment, usually violet–brown, with a variable pattern of distribution; this pigment can be more intense on the hind part of body, on the basal or distal parts of the articles of the appendages, and on the head, or it can be nearly uniformly extended (except for a lighter tonality ventrally). Scales dorsally brown, yellowish brown, dark greyish, silvery grey or greyish–brown, darkish and often with iridescence; they can draw an almost uniform pattern of distribution or can be arranged in alternately light (yellowish brown) and dark (greyish) longitudinal lines, as in other species of the genus. Setation of head as usual for the genus. Eyes black, composed of about 12–13 ommatidia. Antennae longer than body, up to 15 mm (maximum preserved). Maxillary palp with long articles, the distal one 0.9–1.2 times longer than the antedistal and 4.7–9 times longer than wide (fig. 1). Distal article of the labial palp more or less unilaterally dilated, shorter to slightly wider at the apex than long; it always bears five sensory papillae arranged in a single row (fig. 2). Pronotum with 8–9 + 8–9, mesonotum with (9)10–11 pairs and metanotum with 9–10 + 9–10 lateral bristle–combs of 3–7 macrosetae each. Trichobothrial areas of the nota situated on the last and penultimate lateral combs in meso– and metanotum, and on the last and the antepenultimate combs in the pronotum. Posterolateral bristle–combs usually with 7–12 macrosetae each.

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0.2 mm 0.2 mm

0.2 mm

Figs. 7–9. Ctenolepisma almeriensis n. sp., holotype. Tibiae showing distribution of plumose macrosetae and acute spines: 7. Tibia I; 8. Tibia II; 9. Tibia III. Figs. 7–9. Ctenolepisma almeriensis sp. n., holotipo. Tibias mostrando la distribución de las macroquetas plumosas y de las espinas agudas: 7. Tibia I; 8. Tibia II; 9. Tibia III.

Thoracic sterna as shaped in figs. 3–6, very similar to those of C. lineata, except for the features observed in their fields of macrosetae. The word "field" of macrosetae is used here instead of comb, to emphasize that the setae are not arranged in a single row. In the prosternum they are arranged in 2–3 irregular almost parallel lines (fig. 3), and on the meso– and metasternum there are usually two more or less parallel and very close rows (figs. 4–5). The number of setae per "comb" is variable, but on the average it ranges from 8 to 20. The highest numbers of macrosetae are often observed in the antedistal combs. The number of combs on each sternite is also variable; there are usually 4–5 pairs in the prosternum, 2–3 pairs in the mesosternum and two pairs in the metasternum. However, the extension of these combs can produce a juxtaposition of the contiguous fields of macrosetae and therefore the number of perceptible combs is reduced. Consequently, in the metasternum it is possible to count only 1+1 large combs with more than 20 macrosetae each (fig. 6). Tibiae I (fig. 7) 2.2–3.4 times longer than wide; metatibiae 3.4–4.5 times. Apart from usual setae, there are some plumose macrosetae whose length is shorter or equal to the diameter of the tibia. The number of such macrosetae is usually 2–4 dorsal and 3–6 ventral in all tibiae. On the inner side there are many lanceolate scales that are absent on the outer side. These scales have also been detected in the proximal article of the tarsi. Hyaline short spines are usually present ventrally on the outer side of the article (figs. 7–9), as in many specimens of C. lineata from the Iberian Peninsula, although these spines are more numerous and even shorter and stronger in this new species. Up to 25 spines have

been observed on a hind tibiae (fig. 9), but in other specimens the spines are absent. Apex of the outer side of the femora covered by elongate and lanceolate scales, the inner side with many scales shortened and with truncate or emarginated apex. Urotergite I with 1+1 combs, II–VII with 3+3 combs and VIII with 2+2 combs. Submedian bristle–combs with 7–9 macrosetae each, lateral combs with 6–10 and sublateral with 7–15 macrosetae. Urotergite X subtriangular, short, with a rounded apex that can show an angled or rounded point, more or less prolonged (figs. 10–13). Urosternites I and II without setae, III–VIII with 1+1 lateral bristle–combs usually with 14–27 macrosetae each; young specimens may bear fewer than 14 and the largest specimens may bear more than 27 macrosetae, but this is not usual. In relation with the high number of setae per comb, the distance between the lateral combs of a urosternite is 2.7–5 times wider than the width of a comb. Both sexes with two pairs of stylets. In males the inner process of the IXth coxite is slightly longer than wide (ratio length/width = 1.1–1.2) and about 3–3.5 times longer than the outer process (fig. 15). These two ratios are 2.5 and 2.5–4 in females. The stylets IX are about 2.6 times longer than the inner process of the coxites IX in males and about 2.3 times in females (fig. 14). Ovipositor very long, with 55–57 segments, reaching beyond the apex of the stylets IX up to 2–2.5 times the latter’s length (fig. 16). Apices of gonapophises unsclerotized. Caudal filaments as long as body length or slightly longer (maximum preserved in a paracercus: 13.5 mm; cerci a bit shorter).

Animal Biodiversity and Conservation 28.1 (2005)

12 0.2 mm 0.2 mm

13 0.2 mm 0.2 mm

0.2 mm

Figs. 10–16. Ctenolepisma almeriensis n. sp. Types: 10–13. Xth urotergites of different specimens showing the variability of the shape; 14. IXth coxite and stylet of the female. 15. Ibid, of the male; 16. Ovipositor in relation with IXth coxite and stylet. Figs. 10–16. Ctenolepisma almeriensis sp. n. Tipos: 10–13. Uroterguitos X de varios especímenes mostrando la variabilidad de su forma; 14. Coxito IX y estilo de la hembra; 15. Idem, del macho; 16. Ovipositor en relación con el coxito IX y el estilo.

Comparing C. almeriensis n. sp. with other Ctenolepisma species The main feature to distinguish this species from the other Ctenolepisma Escherich, 1905 from Europe, is the occurrence of double combs, i.e., fields of macrosetae on the thoracic sternites that are composed of two more or less parallel rows of plumose setae; in the prosternum these rows are more irregular and three rows can be observed in some fields. Some previously known species from other continents show these "double combs"; this finding is mentioned in the descriptions of South African C. weberi and C. pretoriana by Wygodzinsky (1955), and in that of C. saxeta (Irish, 1987), but no taxonomic significance was given to this feature. This character has been also detected in undescribed taxa from North Africa and the Near East (probably identified as C. lineata, without a fuller involving dissection of the specimens). C. almeriensis sp. n. is the only one of the available specimens from the West–Palaeartic region with double combs that bears only two pairs of stylets in both sexes. However, the occurrence of a double or single row in the aforementioned combs is specially useful for distinguishing between C.

almeriensis n. sp. and C. lineata (respectively), two very similar taxa from the Iberian Peninsula (see figs. 17 and 18). The validity of this feature for distinguishing between both species is confirmed with a discriminant analysis (see below). More attention should therefore be paid to this feature for the future diagnosis of species of this genus. Comparison of Ctenolepisma lineata and the new species In comparison with the other European species belonging to the lineata–group, the new species described here is most similar to C. lineata as its tenth urotergite has the same shape, its legs show the same cover of scales and its abdominal setation is similar. For this reason, a detailed comparison of these two taxa is carried out here to elucidate the validity of the aforementioned character that is used to separate these two species. Other differences can be found between specimens with double and single sternal combs, such as the number of macrosetae on the lateral and posterolateral combs of the nota, and on the combs of urotergites, thoracic sterna and urosternites. Even

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100

Figs. 17–18. SEM photos of the apical part of the metasternum in Ctenolepisma lineata (17), showing a single row of macrosetae, and Ctenolepisma almeriensis n. sp. (18), with a double row (mainly insertions of macrosetae can be seen). Figs. 17–18. Fotografías de MEB de la parte apical del metasterno en Ctenolepisma lineata (17), mostrando una línea sencilla de macroquetas, y en Ctenolepisma almeriensis sp. n. (18), con una doble fila (se aprecian fundamentalmente las inserciones de las macroquetas).

the ratio distance between combs / width of a comb in the metasternum and in the urosternites may differ. However, in these features the margins of variability overlap, so in some cases it is difficult to ascribe a certain specimen to C. lineata or to C. almeriensis if we do not see the combs of the thoracic sternites. A discriminant analysis may demonstrate whether C. lineata and C. almeriensis

are significantly different on the basis of these variable features, thereby proving the validity of the "single/double rows of macrosetae" in the sternal combs. The variables selected are detailed in Material and methods and were measured in 50 specimens of C. lineata and the same number of specimens belonging to the new species.

Ctenolepisma lineata Ctenolepisma almeriensis

Fig. 19. Map showing the localities of Spain where the typical form of Ctenolepisma lineata and C. almeriensis n. sp. were collected. Fig. 19. Mapa donde se indican las localidades de España donde se recogieron tanto la forma típica de Ctenolepisma lineata como C. almeriensis sp. n.

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All the specimens of C. lineata were from Spain (localities nearest to the area where C. almeriensis is found, see map in fig. 19) and only specimens with two pair of stylets were selected, as it has been recently suggested that the variety pilifera (Lucas, 1840) with three pair of stylets is a different species (Molero–Baltanás, 1995). As a result of a standardized principal component analysis (fig. 20), two components, 1 and 2, account for more than the 90% of variability. All the variables selected show a significant weight to explain this variability and therefore all of them are included in the discriminant analysis. Taking into account the 600 data obtained from the total of 100 specimens (25 per predefined group), the following discriminant analyses were carried out: (1) comparison between males of the two predefined species; (2) comparison between females of the two predefined species; (3) and (4) Comparison between males and females within each one of the two species; and (5) comparison between the four groups The results are shown in table 1 and in fig. 21. This multivariate analysis forms two groups of specimens that exactly fit with the two predefined species, as can be seen in the biplot of the discriminant functions 1 and 2 (fig. 21), and in the classification variables (see material and methods). The analysis finds significant differences between species, but these differences are not found between sexes of a given species. The results of the Mann–Whitney U–tests to compare the medians of the four groups are shown in table 2. They are highly significant when different predefined species were compared, and not significant when both sexes within a species were compared (except for one variable in C. lineata, which could have a significant value for sexual dimorphism).

Table 1. Classification table of the discriminant analysis: A. Actual SPSEX; S. Group size. Predicted SPSEX groups are the same as in fig. 21. Tabla 1. Tabla de clasificación del análisis discriminante: A. SPSEX actual; S. Tamaño del grupo. Los grupos predefinidos SPSEX son los mismos que en la fig. 21.

Predicted SPSEX A

These conclusions justify the differentiation between the two species and the validity of the double combs of macrosetae on thoracic sternites as a clear character to distinguish between them. The specimens belonging to the new species have never been found within the area occupied by the typical C. lineata. The two species compared have never been found together in the same locality (they are probably vicarious; see fig. 19). The distribution area of C. almeriensis is mainly inside the limits of the biogeographic sector called “murciano–almeriense”, which is known in faunistic works for its importance as a centre of endemic species. The Penibetic mountain range

Table 2. Z values calculated by two–sample Mann–Whitney rank sum tests (U–tests): Sp1. Ctenolepisma lineata predefined groups; Sp2. C. almeriensis n. sp. predefined groups; M. Males; F. Females; * Significant evidence for different median values between the two groups compared (P value < 0.05). Tabla 2. Valores Z calculados por los tests U de Mann–Whitney para dos muestras: Sp1. Grupos predefinidos como Ctenolepisma lineata; Sp2. Grupos predefinidos como C. almeriensis sp. n.; M. Machos; F. Hembras; * Diferencia significativa entre los valores medios de los dos grupos comparados (valor de P < 0.05).

Z adjusted value N–notum N–pros

Sp1M–Sp1H

Sp2M–Sp2H

Sp1M–Sp2M

Sp1H–Sp2H

–2,77*

0,08

6,18*

5,91*

–0,66

–0,47

6,17*

6,06*

N–meso

0,33

–1,27

6,01*

6,12*

N–meta

0,26

–1,15

5,86*

6,10*

N–uro

–1,37

1,28

5,38*

4,76*

D/a[Mt]

–0,76

–0,37

–4,29*

–5,88*

Molero–Baltanás et al.

Component 2

d_a[Mt] 4

N_uro N_not N_pros 0 N_meso N_meta –2 –4.3

–2.3

–0.3 Component 1

1.7

Fig. 20. Biplot of component principal analysis. Names of the variables are given in Material and methods. Fig. 20. Gráfico del análisis de componentes principales. Los nombres de las variables se indican en Material and methods.

SPSEX groups

2.8

C. lineata, males

Function 2

1.8

C. lineata, females C. almeriensis, males

0.8

C. almeriensis, females –0.2

centroids

–1.2 –2.2 –3.2 –3.6

–1.6

0.4 Function 1

2.4

4.4

6.4

Fig. 21. Biplot of the discriminant analysis: SPSEX groups are established on the basis of sex and predefined species Ctenolepisma lineata and C. almeriensis. Fig. 21. Gráfico del análisis discriminante: grupos SPSEX se han establecido en base al sexo y a la especie predefinida Ctenolepisma lineata y C. almeriensis.

acts as a barrier for the wet western winds and originates an arid region in this corner of the Peninsula. Therefore, the new form of Ctenolepisma seems to be geographically isolated. Such geographic evidence also justifies the differentiation between the two species. This may be supported by molecular evidence in the

future but for the time being the findings in this work appear to be sufficient to maintain C. almeriensis as a good species, and subsequently to demonstrate the validity of the double combs of thoracic sternites as an anatomic characteristic with taxonomic importance in the genus Ctenolepisma.

Animal Biodiversity and Conservation 28.1 (2005)

References Irish, J., 1987. Revision of the genus Ctenolepisma Escherich (Thysanura:Lepismatidae) in Southern Africa. Cimbebasia (A) 7 (11): 147–207. Molero–Baltanás, R., Bach de Roca, C. & Gaju– Ricart, M., 1992. Los Zygentoma de Andalucía (Insecta: Apterygota). Zool. Baetica, 3: 93–115. Molero–Baltanás, R., Gaju–Ricart, M., Bach de Roca, C. & Mendes, L. F., 1994. New faunistic data on the Lepismatidae of Spain (Insecta,

Apterygota, Zygentoma). Acta Zool. Fennica, 195: 107–110. Molero–Baltanás, R., 1995. Estudio taxonómico de los Zygentoma de España (Insecta: Apterygota). Ph. D. Thesis, Univ. of Cordoba. Rivas–Martínez, S., 1987. Nociones sobre Fitosociología, Biogeografía y Bioclimatología. In: Peinado, M., Rivas–Martínez, S., Eds. La vegetación de España. Serv. de Publicaciones Univ. de Alcalá de Henares. Madrid: 19–45. Wygodzinsky, P., 1955. Thysanura. South. afr. anim. Life, 2: 83–190.

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

Consell Assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Animal Biodiversity and Conservation 28.1 (2005)

Animal Biodiversity and Conservation

Manuscrits

Animal Biodiversity and Conservation (abans Miscel·lània Zoològica) és una revista interdisciplinària publicada, des de 1958, pel Museu de Zoologia de Bar celona. Inclou articles d'investigació empírica i teòrica en totes les àrees de la zoologia (sistemàtica, taxonomia, morfologia, biogeografia, ecologia, etologia, fisiologia i genètica) procedents de totes les regions del món amb especial énfasis als estudis que d'una manera o altre tinguin relevància en la biología de la conservació. La revista no publica catàlegs, llistes d'espècies o cites puntuals. Els estudis realitzats amb espècies rares o protegides poden no ser acceptats tret que els autors disposin dels permisos corresponents. Cada volum anual consta de dos fascicles. Animal Biodiversity and Conservation es troba registrada en la majoria de les bases de dades més importants i està disponible gratuitament a internet a http://www.bcn.es/ABC, de manera que permet una difusió mundial dels seus articles. Tots els manuscrits són revisats per l'editor execu tiu, un editor i dos revisors independents, triats d'una llista internacional, a fi de garantir–ne la qualitat. El procés de revisió és ràpid i constructiu. La publicació dels treballs acceptats es fa normalment dintre dels 12 mesos posteriors a la recepció. Una vegada hagin estat acceptats passaran a ser propietat de la revista. Aquesta es reserva els drets d’autor, i cap part dels treballs no podrà ser reproduïda sense citar–ne la procedència.

Els treballs seran presentats en format DIN A–4 (30 línies de 70 espais cada una) a doble espai i amb totes les pàgines numerades. Els manuscrits han de ser complets, amb taules i figures. No s'han d'enviar les figures originals fins que l'article no hagi estat acceptat. El text es podrà redactar en anglès, castellà o català. Se suggereix als autors que enviïn els seus treballs en anglès. La revista els ofereix, sense cap càrrec, un servei de correcció per part d'una persona especialitzada en revistes científiques. En tots els casos, els textos hauran de ser redactats correctament i amb un llenguatge clar i concís. La redacció del text serà impersonal, i s'evitarà sempre la primera persona. Els caràcters cursius s’empraran per als noms científics de gèneres i d’espècies i per als neologis mes intraduïbles; les cites textuals, independentment de la llengua, seran consignades en lletra rodona i entre cometes i els noms d’autor que segueixin un tàxon aniran en rodona. Quan se citi una espècie per primera vegada en el text, es ressenyarà, sempre que sigui possible, el seu nom comú. Els topònims s’escriuran o bé en la forma original o bé en la llengua en què estigui escrit el treball, seguint sempre el mateix criteri. Els nombres de l’u al nou, sempre que estiguin en el text, s’escriuran amb lletres, excepte quan precedeixin una unitat de mesura. Els nombres més grans s'escriuran amb xifres excepte quan comencin una frase. Les dates s’indicaran de la forma següent: 28 VI 99; 28, 30 VI 99 (dies 28 i 30); 28–30 VI 99 (dies 28 a 30). S’evitaran sempre les notes a peu de pàgina.

Normes de publicació Els treballs s'enviaran preferentment de forma elec trònica (abc@mail.bcn.es). El format preferit és un document Rich Text Format (RTF) o DOC que inclogui les figures (TIF). Si s'opta per la versió impresa, s'han d'enviar quatre còpies del treball juntament amb una còpia en disquet a la Secretaria de Redacció. Cal incloure, juntament amb l'article, una carta on es faci constar que el treball està basat en investiga cions originals no publicades anteriorment i que està sotmès a Animal Biodiversity and Conservation en exclusiva. A la carta també ha de constar, per a aquells treballs en que calgui manipular animals, que els autors disposen dels permisos necessaris i que compleixen la normativa de protecció animal vigent. També es poden suggerir possibles assessors. Quan l'article sigui acceptat, els autors hauran d'enviar a la Redacció una còpia impresa de la versió final acompanyada d'un disquet indicant el progra ma utilitzat (preferiblement en Word). Les proves d'impremta enviades a l'autor per a la correcció, seran retornades al Consell Editor en el termini de 10 dies. Aniran a càrrec dels autors les despeses degudes a modificacions substancials introduïdes per ells en el text original acceptat. El primer autor rebrà 50 separates del treball sense càrrec a més d'una separata electrònica en format PDF. ISSN: 1578–665X

Format dels articles Títol. El títol serà concís, però suficientment indicador del contingut. Els títols amb designacions de sèries numèriques (I, II, III, etc.) seran acceptats previ acord amb l'editor. Nom de l’autor o els autors. Abstract en anglès que no ultrapassi les 12 línies mecanografiades (860 espais) i que mostri l’essència del manuscrit (introducció, material, mètodes, resultats i discussió). S'evitaran les especulacions i les cites bibliogràfiques. Estarà encapçalat pel títol del treball en cursiva. Key words en anglès (sis com a màxim), que orientin sobre el contingut del treball en ordre d’importància. Resumen en castellà, traducció de l'Abstract. De la traducció se'n farà càrrec la revista per a aquells autors que no siguin castellanoparlants. Palabras clave en castellà. Adreça postal de l’autor o autors. (Títol, Nom, Abstract, Key words, Resumen, Pala bras clave i Adreça postal, conformaran la primera pàgina.)

Introducción. S'hi donarà una idea dels antecedents del tema tractat, així com dels objectius del treball. Material y métodos. Inclourà la informació pertinent de les espècies estudiades, aparells emprats, mèto des d’estudi i d’anàlisi de les dades i zona d’estudi. Resultados. En aquesta secció es presentaran úni cament les dades obtingudes que no hagin estat publicades prèviament. Discusión. Es discutiran els resultats i es compa raran amb treballs relacionats. Els suggeriments de recerques futures es podran incloure al final d’aquest apartat. Agradecimientos (optatiu). Referencias. Cada treball haurà d’anar acompanyat de les referències bibliogràfiques citades en el text. Les referències han de presentar–se segons els models següents (mètode Harvard): * Articles de revista: Conroy, M. J. & Noon, B. R., 1996. Mapping of spe cies richness for conservation of biological diversity: conceptual and methodological issues. Ecological Applications, 6: 763–773. * Llibres o altres publicacions no periòdiques: Seber, G. A. F., 1982. The estimation of animal abundance. C. Griffin & Company, London. * Treballs de contribució en llibres: Macdonald, D. W. & Johnson, D. P., 2001. Dispersal in theory and practice: consequences for conserva tion biology. In: Dispersal: 358–372 (T. J. Clober, E. Danchin, A. A. Dhondt & J. D. Nichols, Eds.). Oxford University Press, Oxford. * Tesis doctorals: Merilä, J., 1996. Genetic and quantitative trait vari ation in natural bird populations. Tesis doctoral, Uppsala University. * Els treballs en premsa només han d’ésser citats si han estat acceptats per a la publicació: Ripoll, M. (in press). The relevance of population studies to conservation biology: a review. Anim. Biodivers. Conserv. La relació de referències bibliogràfiques d’un treball

serà establerta i s’ordenarà alfabèticament per autors i cronològicament per a un mateix autor, afegint les lletres a, b, c,... als treballs del mateix any. En el text, s’indicaran en la forma usual: “...segons Wemmer (1998)... ”, “...ha estat definit per Robinson & Redford (1991)...”, “...les prospeccions realitzades (Begon et al., 1999)...” Taules. Les taules es numeraran 1, 2, 3, etc. i han de ser sempre ressenyades en el text. Les taules grans seran més estretes i llargues que amples i curtes ja que s'han d'encaixar en l'amplada de la caixa de la revista. Figures. Tota classe d’il·lustracions (gràfics, figures o fotografies) entraran amb el nom de figura i es numeraran 1, 2, 3, etc. i han de ser sempre ressen yades en el text. Es podran incloure fotografies si són imprescindibles. Si les fotografies són en color, el cost de la seva publicació anirà a càrrec dels au tors. La mida màxima de les figures és de 15,5 cm d'amplada per 24 cm d'alçada. S'evitaran les figures tridimensionals. Tant els mapes com els dibuixos han d'incloure l'escala. Els ombreigs preferibles són blanc, negre o trama. S'evitaran els punteigs ja que no es reprodueixen bé. Peus de figura i capçaleres de taula. Els peus de figura i les capçaleres de taula seran clars, concisos i bilingües en la llengua de l’article i en anglès. Els títols dels apartats generals de l’article (Intro ducción, Material y métodos, Resultados, Discusión, Conclusiones, Agradecimientos y Referencias) no aniran numerats. No es poden utilitzar més de tres nivells de títols. Els autors procuraran que els seus treballs originals no passin de 20 pàgines (incloent–hi figures i taules). Si a l'article es descriuen nous tàxons, caldrà que els tipus estiguin dipositats en una institució pública. Es recomana als autors la consulta de fascicles recents de la revista per tenir en compte les seves normes.

Animal Biodiversity and Conservation 28.1 (2005)

Animal Biodiversity and Conservation Animal Biodiversity and Conservation (antes Miscel·lània Zoològica) es una revista inter disciplinar, publicada desde 1958 por el Museo de Zoología de Barcelona. Incluye artículos de investigación empírica y teórica en todas las áreas de la zoología (sistemática, taxonomía, morfología, biogeografía, ecología, etología, fisiología y genéti ca) procedentes de todas las regiones del mundo, con especial énfasis en los estudios que de una manera u otra tengan relevancia en la biología de la conservación. La revista no publica catálogos, listas de especies sin más o citas puntuales. Los estudios realizados con especies raras o protegidas pueden no ser aceptados a no ser que los autores dispongan de los permisos correspondientes. Cada volumen anual consta de dos fascículos. Animal Biodiversity and Conservation está re gistrada en todas las bases de datos importantes y además está disponible gratuitamente en internet en http://www.bcn.es/ABC, lo que permite una difusión mundial de sus artículos. Todos los manuscritos son revisados por el editor ejecutivo, un editor y dos revisores independientes, elegidos de una lista internacional, a fin de garan tizar su calidad. El proceso de revisión es rápido y constructivo, y se realiza vía correo electrónico siem pre que es posible. La publicación de los trabajos aceptados se realiza con la mayor rapidez posible, normalmente dentro de los 12 meses siguientes a la recepción del trabajo. Una vez aceptado, el trabajo pasará a ser propie dad de la revista. Ésta se reserva los derechos de autor, y ninguna parte del trabajo podrá ser reprodu cida sin citar su procedencia.

Normas de publicación Los trabajos se enviarán preferentemente de forma electrónica (abc@mail.bcn.es). El formato preferido es un documento Rich Text Format (RTF) o DOC, que incluya las figuras (TIF). Si se opta por la versión im presa, deberán remitirse cuatro copias juntamente con una copia en disquete a la Secretaría de Redacción. Debe incluirse, con el artículo, una carta donde conste que el trabajo versa sobre investigaciones originales no publicadas anteriormente y que se somete en exclusiva a Animal Biodiversity and Conservation. En dicha carta también debe constar, para trabajos donde sea necesaria la manipulación de animales, que los autores disponen de los permisos necesa rios y que han cumplido la normativa de protección animal vigente. Los autores pueden enviar también sugerencias para asesores. Cuando el trabajo sea aceptado los autores de berán enviar a la Redacción una copia impresa de la versión final junto con un disquete del manuscrito preparado con un procesador de textos e indicando el programa utilizado (preferiblemente Word). Las pruebas de imprenta enviadas a los autores deberán ISSN: 1578–665X

III

remitirse corregidas al Consejo Editor en el plazo máximo de 10 días. Los gastos debidos a modifica ciones sustanciales en las pruebas de imprenta, intro ducidas por los autores, irán a cargo de los mismos. El primer autor recibirá 50 separatas del trabajo sin cargo alguno y una copia electrónica en formato PDF. Manuscritos Los trabajos se presentarán en formato DIN A–4 (30 líneas de 70 espacios cada una) a doble espacio y con las páginas numeradas. Los manuscritos deben estar completos, con tablas y figuras. No enviar las figuras originales hasta que el artículo haya sido aceptado. El texto podrá redactarse en inglés, castellano o catalán. Se sugiere a los autores que envíen sus trabajos en inglés. La revista ofrece, sin cargo ningu no, un servicio de corrección por parte de una persona especializada en revistas científicas. En cualquier caso debe presentarse siempre de forma correcta y con un lenguaje claro y conciso. La redacción del texto deberá ser impersonal, evitándose siempre la primera persona. Los caracteres en cursiva se utilizarán para los nombres científicos de géneros y especies y para los neologismos que no tengan traducción; las citas textuales, independientemente de la lengua en que estén, irán en letra redonda y entre comillas; el nombre del autor que sigue a un taxón se escribirá también en redonda. Al citar por primera vez una especie en el trabajo, deberá especificarse siempre que sea posible su nombre común. Los topónimos se escribirán bien en su forma original o bien en la lengua en que esté redactado el trabajo, siguiendo el mismo criterio a lo largo de todo el artículo. Los números del uno al nueve se escribirán con letras, a excepción de cuando precedan una unidad de medida. Los números mayores de nueve se escribirán con cifras excepto al empezar una frase. Las fechas se indicarán de la siguiente forma: 28 VI 99; 28, 30 VI 99 (días 28 y 30); 28–30 VI 99 (días 28 al 30). Se evitarán siempre las notas a pie de página. Formato de los artículos Título. El título será conciso pero suficientemente explicativo del contenido del trabajo. Los títulos con designaciones de series numéricas (I, II, III, etc.) serán aceptados excepcionalmente previo consen timiento del editor. Nombre del autor o autores. Abstract en inglés de 12 líneas mecanografiadas (860 espacios como máximo) y que exprese la esencia del manuscrito (introducción, material, métodos, resulta dos y discusión). Se evitarán las especulaciones y las citas bibliográficas. Irá encabezado por el título del trabajo en cursiva. Key words en inglés (un máximo de seis) que especifiquen el contenido del trabajo por orden de importancia. © 2005 Museu de Ciències Naturals

Resumen en castellano, traducción del abstract. Su traducción puede ser solicitada a la revista en el caso de autores que no sean castellano hablantes. Palabras clave en castellano. Dirección postal del autor o autores. (Título, Nombre, Abstract, Key words, Resumen, Palabras clave y Dirección postal conformarán la primera página.) Introducción. En ella se dará una idea de los ante cedentes del tema tratado, así como de los objetivos del trabajo. Material y métodos. Incluirá la información referente a las especies estudiadas, aparatos utilizados, me todología de estudio y análisis de los datos y zona de estudio. Resultados. En esta sección se presentarán úni camente los datos obtenidos que no hayan sido publicados previamente. Discusión. Se discutirán los resultados y se compara rán con otros trabajos relacionados. Las sugerencias sobre investigaciones futuras se podrán incluir al final de este apartado. Agradecimientos (optativo). Referencias. Cada trabajo irá acompañado de una bibliografía que incluirá únicamente las publicaciones citadas en el texto. Las referencias deben presentarse según los modelos siguientes (método Harvard): * Artículos de revista: Conroy, M. J. & Noon, B. R., 1996. Mapping of spe cies richness for conservation of biological diversity: conceptual and methodological issues. Ecological Applications, 6: 763–773 * Libros y otras publicaciones no periódicas: Seber, G. A. F., 1982. The estimation of animal abundance. C. Griffin & Company, London. * Trabajos de contribución en libros: Macdonald, D. W. & Johnson, D. P., 2001. Dispersal in theory and practice: consequences for conserva tion biology. In: Dispersal: 358–372 (T. J. Clober, E. Danchin, A. A. Dhondt & J. D. Nichols, Eds.). Oxford University Press, Oxford. * Tesis doctorales: Merilä, J., 1996. Genetic and quantitative trait vari ation in natural bird populations. Tesis doctoral, Uppsala University.

* Los trabajos en prensa sólo se citarán si han sido aceptados para su publicación: Ripoll, M. (in press). The relevance of population studies to conservation biology: a review. Anim. Biodivers. Conserv. Las referencias se ordenarán alfabéticamente por autores, cronológicamente para un mismo autor y con las letras a, b, c,... para los trabajos de un mismo autor y año. En el texto las referencias bibliográficas se indicarán en la forma usual: "... según Wemmer (1998)...", "...ha sido definido por Robinson & Redford (1991)...", "...las prospecciones realizadas (Begon et al., 1999)..." Tablas. Las tablas se numerarán 1, 2, 3, etc. y se reseñarán todas en el texto. Las tablas grandes deben ser más estrechas y largas que anchas y cortas ya que deben ajustarse a la caja de la revista. Figuras. Toda clase de ilustraciones (gráficas, figuras o fotografías) se considerarán figuras, se numerarán 1, 2, 3, etc. y se citarán todas en el texto. Pueden incluirse fotografías si son imprescindibles. Si las fotografías son en color, el coste de su publicación irá a cargo de los autores. El tamaño máximo de las figuras es de 15,5 cm de ancho y 24 cm de alto. Deben evitarse las figuras tridimensionales. Tanto los mapas como los dibujos deben incluir la escala. Los sombreados preferibles son blanco, negro o trama. Deben evitarse los punteados ya que no se reproducen bien. Pies de figura y cabeceras de tabla. Los pies de figura y cabeceras de tabla serán claros, concisos y bilingües en castellano e inglés. Los títulos de los apartados generales del artículo (Introducción, Material y métodos, Resultados, Discusión, Agradecimientos y Referencias) no se numerarán. No utilizar más de tres niveles de títulos. Los autores procurarán que sus trabajos originales no excedan las 20 páginas incluidas figuras y tablas. Si en el artículo se describen nuevos taxones, es imprescindible que los tipos estén depositados en alguna institución pública. Se recomienda a los autores la consulta de fascículos recientes de la revista para seguir sus directrices.

Animal Biodiversity and Conservation 28.1 (2005)

Animal Biodiversity and Conservation

Manuscripts

Animal Biodiversity and Conservation (formerly Miscel·lània Zoològica) is an interdisc ip lin ary journal which has been published by the Zoologi cal Museum of Barcelona since 1958. It includes empirical and theoretical research in all aspects of Zoology (Systematics, Taxonomy, Morphology, Biogeography, Ecology, Ethology, Physiology and Genetics) from all over the world with special emphasis on studies that stress the relevance of the study of Conservation Biology. The journal does not publish catalogues, lists of species (with no other relevance) or punctual records. Studies about rare or protected species will not be accepted unless the authors have been granted all the relevant permits. Each annual volume consists of two issues. Animal Biodiversity and Conservation is registered in all principal data bases and is freely available online at http://www.bcn.es/ABC, thus assuring world–wide access to articles published therein. All manuscripts are screened by the Executive Edi tor, an Editor and two independent reviewers in order to guarantee the quality of the papers. The process of review is rapid and constructive. Once accepted, papers are published as soon as practicable, usually within 12 months of initial submission. Upon acceptance, manuscripts become the prop erty of the journal, which reserves copyright, and no published material may be reproduced without quoting its origin.

Manuscripts must be presented on A–4 format page (30 lines of 70 spaces each) with double spacing. Number all pages. Manuscripts should be complete with figures and tables. Do not send original figures until the paper has been accepted. The text may be written in English, Spanish or Catalan. Authors are encouraged to send their con tributions in English. The journal provides a FREE service of correction by a professional translator specialized in scientific publications. Care should be taken in using correct wording and the text should be written concisely and clearly. Wording should be impersonal, avoiding the use of the first person. Italics must be used for scientific names of genera and species as well as untranslatable neologisms. Quotations in whatever language used must be typed in ordinary print between quotation marks. The name of the author following a taxon should also be written in small print. The common name of the species should be writ ten in capital letters. When referring to a species for the first time in the text, both common and scientific names must be given when possible. Place names may appear either in their original form or in the language of the manuscript, but care should be taken to use the same criteria throughout the text. Numbers one to nine should be written in full in the text except when preceding a measure. Higher numbers should be written in numerals except at the beginning of a sentence. Dates must appear as follows: 28 VI 99, 28,30 VI 99 (days 28th and 30th), 28–30 VI 99 (days 28th to 30th). Footnotes should not be used.

Information for authors Electronic submission of papers is encouraged (abc@ mail.bcn.es). The preferred format is a document Rich Text Format (RTF) or DOC, including figures (TIF). In the case of sending a printed version, four copies should be sent together with a copy on a computer disc to the Editorial Office. A cover letter stating that the article reports on original research not published elsewhere and that it has been submitted exclusively for consideration in Animal Biodiversity and Conservation is also necessary. When animal manipulation has been necessary, the cover letter should also especify that the authors follow current norms on the protection of animal species and that they have obtained all relevant permissions. Authors may suggest referees for their papers. Once an article has been accepted, authors should send a printed copy of the final version together with a disc. Please identify software (preferably Word). Proofs sent to the authors for correction should be returned to the Editorial Board within 10 days. Expenses due to any substantial alterations of the proofs will be charged to the authors. The first author will receive 50 reprints free of charge and an electronic version of the article in PDF format.

ISSN: 1578–665X

Formatting of articles Title. The title must be concise but as informative as possible. Part numbers (I, II, III, etc.) should be avoided and will be subject to the Editor’s consent. Name of author or authors. Abstract in English, no longer than 12 typewritten lines (840 spaces), covering the contents of the article (introduction, material, methods, results and discussion). Speculation and literature citation must be avoided. Abstract should begin with the title in italics. Key words in English (no more than six) should express the precise contents of the manuscript in order of importance. Resumen in Spanish, translation of the Abstract. Summaries of articles by non–Spanish speaking authors will be translated by the journal on request. Palabras clave in Spanish. Address of the author or authors. (Title, Name, Abstract, Key words, Resumen, Palabras clave and Address should constitute the first page.) Introduction. The introduction should include the historical background of the subject as well as the aims of the paper.

Material and methods. This section should provide relevant information on the species studied, materials, methods for collecting and analysing data and the study area. Results. Report only previously unpublished results from the present study. Discussion. The results and their comparison with related studies should be discussed. Suggestions for future research may be given at the end of this section. Acknowledgements (optional). References. All manuscripts must include a bibliogra phy of the publications cited in the text. References should be presented as in the following examples (Harvard method): * Journal articles: Conroy, M. J. & Noon, B. R., 1996. Mapping of spe cies richness for conservation of biological diversity: conceptual and methodological issues. Ecological Applications, 6: 763–773. * Books or other non–periodical publications: Seber, G. A. F., 1982. The estimation of animal abundance. C. Griffin & Company, London. * Contributions or chapters of books: Macdonald, D. W. & Johnson, D. P., 2001. Dispersal in theory and practice: consequences for conserva tion biology. In: Dispersal: 358–372 (T. J. Clober, E. Danchin, A. A. Dhondt & J. D. Nichols, Eds.). Oxford University Press, Oxford. * Ph. D. Thesis: Merilä, J., 1996. Genetic and quantitative trait vari ation in natural bird populations. Ph. D. Thesis, Uppsala University. * Works in press should only be cited if they have been accepted for publication: Ripoll, M. (in press). The relevance of population studies to conservation biology: a review. Anim. Biodivers. Conserv. References must be set out in alphabetical and

chronological order for each author, adding the letters a, b, c,... to papers of the same year. Bibliographic citations in the text must appear in the usual way: "... according to Wemmer (1998)...", "...has been defined by Robinson & Redford (1991)...", "...the prospections that have been carried out (Begon et al., 1999)..." Tables. Tables must be numbered in Arabic numerals with reference in the text. Large tables should be narrow (across the page) and long (down the page) rather than wide and short, so that they can be fitted into the column width of the journal. Figures. All illustrations (graphs, drawings or photographs) must be termed as figures, num bered consecutively in Arabic numerals (1, 2, 3, etc.) and with reference in the text. Glossy print photographs, if essential, may be included. Colour photographs may be published but its publication will be charged to authors. Maximum size of figures is 15.5 cm width and 24 cm height. Figures will not be tridimensional. Both maps and drawings must include scale. The preferred shadings are white, black and bold hatching. Avoid stippling, which does not reproduce well. Legends of tables and figures. Legends of tables and figures must be clear, concise, and written both in English and Spanish. Main headings (Introduction, Material and methods, Results, Discussion, Acknowledgements and Refe rences) should not be numbered. Do not use more than three levels of headings. Manuscripts should not exceed 20 pages including figures and tables. If the article describes new taxa, type material must be deposited in a public institution. Authors are advised to consult recent issues of the journal and follow its conventions.

VII

Animal Biodiversity and Conservation 28.1 (2005)

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Les cites o els abstracts dels articles d’Animal Biodiversity and Conservation es resenyen a / Las citas o los abstracts de los artículos de Animal Biodiversity and Conservation se mencionan en / Animal Biodiversity and Conservation is cited or abstracted in: Abstracts of Entomology, Agrindex, Animal Behaviour Abstracts, Anthropos, Aquatic Sciences and Fisheries Abstracts, Behavioural Biology Abstracts, Biological Abstracts, Biological and Agricultural Abstracts, Current Primate References, Directory of Open Acces Journals, Ecological Abstracts, Ecology Abstracts, Entomology Abstracts, Environmental Abstracts, Environmental Periodical Bibliography, Genetic Abstracts, Geographical Abstracts, índex de Sumaris Electrònics del Consorci de Biblioteques de Catalunya, Índice Español de Ciencia y Tecnología, International Abstracts of Biological Sciences, International Bibliography of Periodical Literature, International Developmental Abstracts, Marine Sciences Contents Tables, Oceanic Abstracts, Recent Ornithological Literature, Referatirnyi Zhurnal, Science Abstracts, Serials Directory, Ulrich’s International Periodical Directory, Zoological Records.

Índex / Índice / Contents Animal Biodiversity and Conservation 28.1 (2005) ISSN 1578–665X

1–44 Ranius, T., Aguado, L. O., Antonsson, K., Audisio, P., Ballerio, A., Carpaneto, G. M., Chobot, K., Gjurašin, B., Hanssen, O., Huijbregts, H., Lakatos, F., Martin, O., Neculiseanu, Z., Nikitsky, N. B., Paill, W., Pirnat, A., Rizun, V., Ruic|nescu, A., Stegner, J., Süda, I., Szwa»ko, P., Tamutis, V., Telnov, D., Tsinkevich, V., Versteirt, V., Vignon, V., Vögeli, M. & Zach, P. Osmoderma eremita (Coleoptera, Scarabaeidae, Cetoniinae) in Europe 45–58 Review Fleishman, E. Identification and conservation application of signal, noise, and taxonomic effects in diversity patterns 59–67 Review Corn, P. S. Climate change and amphibians

69–73 Geist, C., Liao, J., Libby, S. & Blumstein, D. T. Does intruder group size and orientation affect flight initiation distance in birds? 75–89 Olden, J. D. & Poff, N. L. Long–term trends of native and non–native fish faunas in the American Southwest 91–99 Molero–Baltanás, R., Gaju–Ricart, M. & Bach de Roca, C. Ctenolepisma almeriensis n. sp. of Lepismatidae (Insecta, Zygentoma) from south– eastern Spain