animal biodiversity and conservation issue 28.1 (2005)

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AnimalBiodiversity Conservation28.1

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Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretària de redacció / Secretaria de redacción / Managing EditorMontserrat Ferrer

Consell assessor / Consejo asesor / Advisory BoardOleguer EscolàEulàlia GarciaAnna OmedesJosep PiquéFrancesc Uribe

Editors / Editores / EditorsPere Abelló Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, SpainJavier Alba–Tercedor Univ. de Granada, Granada, SpainAntonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, SpainXavier Bellés Centre d' Investigació i Desenvolupament–CSIC, Barcelona, SpainJuan Carranza Univ. de Extremadura, Cáceres, SpainLuís Mª Carrascal Museo Nacional de Ciencias Naturales–CSIC, Madrid, SpainMichael J. Conroy Univ. of Georgia, Athens, USAAdolfo Cordero Univ. de Vigo, Vigo, SpainMario Díaz Univ. de Castilla–La Mancha, Toledo, SpainXavier Domingo–Roura inst. de Recerca i Tecnologia Agroalimentàries, Cabrils, SpainJosé Antonio Donazar Estación Biológica de Doñana–CSIC, Sevilla, SpainGary D. Grossman Univ. of Georgia, Athens, USADamià Jaume IMEDEA–CSIC, Univ. de les Illes Balears, SpainJordi Lleonart Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, SpainJorge M. Lobo Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Pablo J. López–González Univ de Sevilla, Sevilla, SpainJuan José Negro Estación Biológica de Doñana–CSIC, Sevilla, SpainVicente M. Ortuño Univ. de Alcalá de Henares, Alcalá de Henares, SpainMiquel Palmer IMEDEA–CSIC, Univ. de les Illes Balears, SpainFrancisco Palomares Estación Biológica de Doñana–CSIC, Sevilla, SpainFrancesc Piferrer Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, SpainMontserrat Ramón Inst. de Ciències del Mar CMIMA –CSIC, Barcelona, SpainIgnacio Ribera Nacional de Ciencias Naturales–CSIC, Madrid, SpainPedro Rincón Museo Nacional de Ciencias Naturales–CSIC, Madrid, SpainAlfredo Salvador Museo Nacional de Ciencias Naturales–CSIC, Madrid, SpainJosé Luís Tellería Univ. Complutense de Madrid, Madrid, SpainFrancesc Uribe Museu de Ciències Naturals de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial BoardJosé A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, SpainJean C. Beaucournu Univ. de Rennes, Rennes, FranceDavid M. Bird McGill Univ., Québec, CanadaMats Björklund Uppsala Univ., Uppsala, SwedenJean Bouillon Univ. Libre de Bruxelles, Brussels, BelgiumMiguel Delibes Estación Biológica de Doñana–CSIC, Sevilla, SpainDario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, SpainAlain Dubois Museum national d’Histoire naturelle–CNRS, Paris, FranceJohn Fa Durrell Wildlife Conservation Trust, Jersey, United KingdomMarco Festa–Bianchet Univ. de Sherbrooke, Québec, CanadaRosa Flos Univ. Politècnica de Catalunya, Barcelona, SpainJosep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, SpainEdmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The NetherlandsFernando Hiraldo Estación Biológica de Doñana–CSIC, Sevilla, SpainPatrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, FranceSantiago Mas–Coma Univ. de Valencia, Valencia, SpainJoaquín Mateu Estación Experimental de Zonas Áridas–CSIC, Almería, SpainNeil Metcalfe Univ. of Glasgow, Glasgow, United KingdomJacint Nadal Univ. de Barcelona, Barcelona, SpainStewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, SpainTaylor H. Ricketts Stanford Univ., Stanford, USAJoandomènec Ros Univ. de Barcelona, Barcelona, SpainValentín Sans–Coma Univ. de Málaga, Málaga, SpainTore Slagsvold Univ. of Oslo, Oslo, Norway

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Animal Biodiversity and Conservation 28.1, 2005© 2005 Museu de Ciències Naturals, Institut de Cultura, Ajuntament de BarcelonaAutoedició: Montserrat FerrerFotomecànica i impressió: Sociedad Cooperativa Librería GeneralISSN: 1578–665XDipòsit legal: B–16.278–58

The journal is freely available online at: http://www.bcn.cat/ABC

"Le platax d'Ehrenberg (PlataxEhrenbergii, Cav. Nat.)" Le Règne Animal par Georges Cuvier; Paris: Fortin, Masson et Cie, Librairies; Pl. 42 Poissons

http://bcnweb13.bcn.es:81/NASApp/wprmuseuciencies/Museu.GeneradorPagines?idioma=3&seccio=11_1

1Animal Biodiversity and Conservation 28.1 (2005)

© 2005 Museu de Ciències NaturalsISSN: 1578–665X

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) inEurope. Animal Biodiversity and Conservation, 28.1: 1–44.

AbstractOsmoderma eremita (Coleoptera, Scarabaeidae, Cetoniinae) in Europe.— Research, monitoring anddevelopment of preservation strategies for threatened species are often limited by national borders eventhough a global perspective would be more appropriate. In this study, we collected data on the occurrenceof a threatened beetle, Osmoderma eremita, associated with tree hollows in 2,142 localities from 33countries in Europe where it is or has been present. The larvae develop in tree hollows and very fewobservations of larvae have been observed in dead logs on the ground. As long as there is a suitable treehollow, it appears that O. eremita may use any tree species. Oaks (Quercus spp.) are the trees mainlyused 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, huntingparks, 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. eremitalocalities occur in Central Europe (northern Italy, Austria, Czechia, southern Poland and eastern Ger-many), some parts of Northern Europe (south–eastern Sweden, Latvia) and France. In some regions innorth–western Europe, the species is extinct or may occur at some single sites (Norway, Danishmainland, The Netherlands, Belgium, north–eastern France). There are few data from south–easternEurope. Many local extinctions of O. eremita are to be expected in the near future, especially in regionswith recent habitat loss and fragmentation. O. eremita is useful as an indicator and umbrella species forthe preservation of the entire invertebrate community associated with hollow trees in Europe. A preserva-tion plan for O. eremita should include three aspects that are of general importance in nature conserva-tion 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) preservationof remaining "islands" of nature in urban areas.

Key words: Saproxylic, Cavity, Habitat Directive, Pollarding, Bioindicator, Scarabaeoidea.

ResumenOsmoderma eremita (Coleoptera, Scarabaeidae, Cetoniinae) en Europa.— La investigación, el control y eldesarrollo de estrategias de conservación de especies amenazadas en peligro de extinción estánhabitualmente confinadas por fronteras nacionales aunque sería más apropiado una perspectiva másglobal. 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 Europadonde se ha encontrado. La larva se desarrolla en los huecos de los árboles y se ha observado pocasveces en troncos muertos en el suelo. Parece ser que O. eremita es capaz de utilizar cualquier especie deárbol 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

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

2 Ranius et al.

frutales (Prunus spp., Pyrus spp., Malus domestica). O. eremita se encuentra todavía en algún remanentede bosque natural, pero se observa principalmente en tierras que han sido usadas por el hombre comozonas de bosques aclarados, cotos de caza, avenidas, parques urbanos y en árboles alrededor de camposagrícolas y a lo largo del curso de ríos. Parece ser que la presencia de O. eremita ha disminuido en todas lasregiones europeas. Las mayores concentraciones de localidades con presencia de O. eremita aparecenen Europa central (norte de Italia, Austria, República Checa, sur de Polonia y Alemania del este), en algunaspartes del norte de Europa (sureste de Suecia, Latvia) y en Francia. En algunas regiones del noroeste deEuropa, 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 deO. 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 deinvertebrados asociados a los agujeros de árboles en Europa. Un plan de preservación de O. eremitadebería incluir tres aspectos que son de importancia general en la conservación de la naturaleza en Europahoy en día: (1) preservación de los remanentes de bosques naturales con árboles viejos, (2) preservación yrestauración 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 07Uppsala, Sweden. E–mail: [email protected].– Luís Oscar Aguado, Aptdo. 498, E–47001 Valladolid,Spain. E–mail: [email protected].– Kjell Antonsson, Environmental Dept., The County Adminis-tration Board of Östergötland, SE – 581 86 Linköping, Sweden. E–mail: [email protected].– PaoloAudisio, Dipt. di Biologia Animale e dell’Uomo, Univ. of Rome "La Sapienza", viale dell’Università 32, I–00185Rome, Italy. E–mail: [email protected].– Alberto Ballerio, Viale Venezia 45, I–25123 Brescia, Italy.E–mail: [email protected].– Giuseppe M. Carpaneto, Dipt. di Biologia, Univ. of Rome "RomaTre", Viale G. Marconi 446, I–00146 Rome, Italy. E–mail: [email protected].– Karel Chobot, Agency forNature Conservation and Landscape Protection of the Czech Republic, Kališnická 4–6, CZ–130 23 Praha 3,Czechia. E–mail: [email protected].– Branimir Gjurašin, Croatian Natural History Museum, Demetrova 1, HR–10000 Zagreb, Croatia. E–mail: [email protected].– Oddvar Hanssen, Norwegian Inst. for NatureResearch (NINA), Tungasletta 2, N–7485 Trondheim, Norway. E–mail: [email protected].– HansHuijbregts, National Museum of Natural History Naturalis, P.O. Box 9517, 2300 RA Leiden, The Netherlands.E–mail: [email protected].– 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: [email protected].– OleMartin, Zoological Museum, Universitetsparken 15, DK–2100 Copenhagen Ø, Denmark. E–mail:[email protected].– Zaharia Neculiseanu, or. Chisinau, str. Drumul Schinoasei 1/3, ap. 40, 2019 Moldova.E–mail: [email protected].– Nikolai B. Nikitsky, Zoological Museum of Moscow, Lomonosov StateUniv., 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:[email protected].– Alja Pirnat, Centre for Scientific Research of the Slovenian Academy of Sciences andArts, 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: [email protected].–Adrian Ruicănescu, Inst. of Biological Research, Cluj–Napoca, 48 Republicii Str. RO–3400, Romania. E–mail:[email protected].– Jan Stegner, Vitzthumallee 20a, D–04509 Schönwölkau, Germany. E–mail:[email protected].– Ilmar Süda, Estonian Agricultural Univ., Forest Research Inst., F. R. Kreutzwaldi 5,51014 Tartu, Estonia. E–mail: [email protected].– Przemys»aw Szwałko, Museum of Natural History, Inst. ofSystematics and Evolution of Animals, Polish Academy of Sciences, Sebastiana 9, PL 31–049 Kraków,Poland. E–mail: [email protected].– Vytautas Tamutis, Plant Protection department, Lithua-nian Univ. of Agriculture, Studentu 11 Akademija LT – 4324, Kaunas, Lithuania. E–mail: [email protected].–Dmitry Telnov, Coleopterology Section, The Entomological Society of Latvia, c/o: Fac. of Biology, 4, KronvaldaBlvd., LV–1586 Riga, Latvia. E–mail: [email protected].– Vadim Tsinkevich, Dept. of Zoology, Belarus StateUniv., F. Scorina Avenue, 4, 220050, Minsk, Belarus. E–mail: [email protected].– Vincent Vignon, OGE –Office de Génie Ecologique, 5, Boulevard de Créteil – F–94100, Saint–Maur–des–Fossés, France. E–mail:[email protected].– Veerle Versteirt, Royal Belgian Inst. of Natural Sciences, Dept. of Entomology,Vautierstraat 29, 1000 Brussel, Belgium. E–mail: [email protected].– Matthias Vögeli,Professur für Natur– und Landschaftsschutz, ETH Zürich, HG F 27.6, 8092 Zürich, Switzerland. E–mail:[email protected].– Peter Zach, Inst. of Forest Ecology, Slovak Academy of Sciences, Sturova 2, Zvolen,Slovakia. E–mail: [email protected].

Corresponding author: T. Ranius, Swedish Univ. of Agricultural Sciences, Dept. Entomology, P.O. Box 7044,SE–750 07 Uppsala, Sweden. E–mail: [email protected].

mailto: [email protected]

mailto:[email protected]




























Animal Biodiversity and Conservation 28.1 (2005) 3

Introduction

In temperate and Mediterranean regions of Europe,old trees are now scarce and many species de-pendent on this habitat seem to be confined to smallremnants with no possibility for dispersal betweenthe populations (e.g. Harding & Rose, 1986; Speight,1989). This is because old–growth deciduous for-ests have declined to a very small proportion of theiroriginal extent (Hannah et al., 1995). Up until thenineteenth century, old trees were also widespreadin pasture woodlands and wooded meadows, butabandoned management and changes of land usehave severely reduced these habitats (e.g. Nilsson,1997; Kirby & Watkins, 1998).

When trees age, hollows with wood mould of-ten form in the trunks. Wood mould is loose woodcolonised by fungi, often with remains from birdnests and insects. Trunk hollows with wood mouldharbour a specialised fauna mainly consisting ofbeetles, flies, mites, pseudoscorpions and ants.Many invertebrate species associated with hollowtrees are threatened (e.g. Ehnström & Waldén,1986; Warren & Key, 1991), and therefore the pro-tection of this fauna should be an important goalfor nature conservation in Europe.

A strategy for nature conservation should be basedon knowledge about which sites should be givenpriority. Which habitat types are most valuable forinvertebrates living in tree hollows? How are thesehabitats distributed in Europe? As neither time, eco-nomical resources or taxonomic expertise are avail-able to carry out detailed surveys of saproxylic inver-tebrates throughout Europe, we need to find surro-gates that provide clues about the conservation val-ues but are easier to survey. One possibility is tomeasure the amount of habitat (in this case, large orhollow trees), while another is to survey indicatorspecies. Surveys of old trees have been conductedwith different protocols in Britain (e.g. Clifton, 2000)and Sweden (e.g. Hultengren & Nitare, 1999; Raniuset al., 2001). Lists with saproxylic insects that maybe used as indicators have been compiled by Speight(1989), Rundlöf & Nilsson (1995) and Nilsson et al.(2001). One weak point with these surrogates isthat they have usually been developed based onpersonal experience from a restricted region; thelists of indicator species and suggested methodsto survey old trees are adopted to the researcher’sstudy area, and do not necessarily suit the wholeof Europe. Another problem is that to count allhollow and large trees (as in Ranius et al., 2001)or to survey presence or absence of tens ofsaproxylic insect species (as in Rundlöf & Nilsson,1995; Nilsson et al., 2001) is expensive and time–consuming. It will therefore take a long time untilthere are sufficient data of this kind to allow com-parisons between different parts of Europe.

A simple measure of conservation values couldbe achieved by collecting data about the presence ofa single species. One beetle species, Osmodermaeremita (Scopoli, 1763; Coleoptera: Cetoniidae), hasbeen more studied in ecological research than any

other invertebrate species associated with tree hol-lows (see Ranius, 2002b, for a review). This spe-cies has a high priority according to the EuropeanUnion’s Habitats Directive (Luce, 1996), and hastherefore been surveyed in many countries in recentyears. It is also listed by the Bern convention. A studyin south–eastern Sweden showed that in sites withtree hollows, those with O. eremita present have ahigher species richness of other threatened beetlespecies associated with tree hollows (Ranius,2002a). The fact that this species is easy to surveyalso improves its suitability as an indicator species(Ranius & Jansson, 2002).

In this paper we compile data on the occur-rence of O. eremita in Europe. It is written by28 co–authors each responsible for one or moreEuropean countries. Information has been com-piled from museums and private collections, lit-erature and field surveys. The paper is based on aprivate initiative, based on the belief that entomol-ogy and nature conservation would do better withstronger co–operation between conservationistsfrom all European countries.

Taxonomy

Osmoderma species occur in northern America,Europe, Turkey, south–eastern Siberia, north–east-ern China, Korea and Japan (Shaffrath, 2003a).Taxonomists’s opinions differ about the forms ofOsmoderma in Europe. According to Tauzin (1994a,1994b, 1996, 2002), there are two Osmoderma spe-cies in Europe: O. eremita (Scopoli) in WesternEurope and O. lassallei Baraud & Tauzin in EasternEurope. Sparacio (1994) described a third species,O. cristinae, endemic for Sicily. Later, Krell (1996)treated these three European forms of Osmodermaas different subspecies of O. eremita. However, ina recent review of the European Osmoderma,Sparacio (2001) considered again both O. lassalleiand O. cristinae as distinct species, and describeda fourth possible separate species of this complex,O. italica (recently emended O. italicum by Audisioet al., 2003), considered endemic to the southernmainland of Italy. A new, but partly questionable,nomenclatorial and taxonomic scenario of the Eu-ropean Osmaderma was finally recently introducedby Gusakov (2002). An ongoing genetic study by P.Audisio and coll., based on comparison of mtDNAgenes sequences, will probably provide greater in-sight in the taxonomy of the species complex. Forsimplicity, in this paper we do not distinguish be-tween Osmoderma forms, but provisionally applythe name O. eremita to all Osmoderma in Europe.

Life history

Normally, the adults of O. eremita are found fromJuly to September, but in some regions (Germany,Slovenia and Italy) there have been several obser-vations 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.).

4 Ranius et al.

The adults normally die in autumn; nevertheless,a hibernating adult female has once been foundin January in the forest of Fontainebleau, France(Tauzin, 1994b). When rearing the species in thelaboratory, Tauzin (1994b) observed adult malesto have a lifetime of 10–20 days, while femaleslived for more than 90 days. Schaffrath (2003a) fedisolated males which reached lifetimes of 90 days.In a field study in Sweden, males and femalesseemed to have the same life–time, with a maxi-mum of about one month (Ranius, 2001).

During a research project conducted over sev-eral years in Sweden, O. eremita was only foundactive at daytime (T. Ranius, pers. obs.), while inRussia, active adults have also been observed atdusk and night time (N. Nikitsky, pers. obs.) and inGermany and France at dawn (Schaffrath, 2003a;Stegner, 2002). Flying individuals have mainly beenseen in the early afternoon on warm, sunny days.

According to Luce (1996), O. eremita females lay20–80 eggs. When Jönsson (2003) reared the bee-tle in the laboratory, he searched for larvae one–twomonths after the eggs were laid, and found 12–18 larvae produced by each female. Egg incubationlasts 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 alength of 6 mm, but at complete development theycan reach 60 mm and have a weight of more than12 g (Schaffrath, 2003a). Before metamorphosis,the larvae construct an oval cocoon made of theirexcrements and wood mould (Tauzin, 1994b). Fromlaboratory studies, we know that cocoons are madein autumn (September), but metamorphosis takesplace in the following spring (May–June) (Tauzin,1994b). However, in Italy, D. Baratelli (pers. comm.)observed that two larvae found in February devel-oped into adults in April and May of the same year.

In laboratory and field studies in Poland,Pawłowski (1961) found the generation time to bethree or four years. The larval feeding period wasbetween 65 and 93 weeks. Feeding activity tookplace when the average daily temperature exceeded13°C, which means that in Poland the larvae areactive about 30 weeks per year. Developing timeand hibernation depend on the temperature of thewood mould, which varies between years and lo-calities. In Germany, Russia and Latvia, the de-velopment time in the field is also usually eitherthree 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 Swedenthere were, on average, 11 adult beetles per hollowoak and year (Ranius, 2001), and a similar popula-tion size per tree has been reported from HallandsVäderö, southwestern Sweden (Jönsson, 2003). Atboth these sites, there were almost 100 adult bee-tles per year in some trees. Circumstantial recordssuggest that the population size per tree is of thesame magnitude in other parts of Europe. For in-stance, in chestnut and willow trees in LoveroValtellino (Lombardia, Italy) normally 5 to 30, but

sometimes more, individuals per tree were ob-served (P. Audisio, pers. obs.). Also in Latvia, oaksand lime trees have been found harbouringpopulations of the same magnitude (D. Telnov & F.Savich, pers. obs.). Schaffrath (2003b) counted thelarvae and cocoons in three oaks and one beech inGermany and found 30–120 individuals, which im-plied that there was about one larva per litre ofwood mould. In France, Prunier (1999) counted thelarvae in the trunk of an old oak from 1 to 7 m fromthe ground and found more than 150 larvae.

Males of O. eremita emit a characteristic odourthat French entomologists have called "odeur deprune" (= odour of plums) or "odeur de cuir deRussie" (= 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 canbe perceived by humans several metres from thebeetle. Chemical analyses have revealed that themales emit the same compound (a decalactone)that is emitted by apricots and plums, and that thecompound works as a pheromone that attractsfemale O. eremita (Larsson et al., 2003).

Only on a few occasions have O. eremitaadults been seen feeding. In Croatia, B. Gjurašinhas collected O. eremita adults on flowers(Leucanthemum sp. and Viburnum sp.) on twooccasions, and in Spain, there has been a sightingon flowers of Sambucus nigra (L. O. Aguado, pers.obs.). From Germany, M. Bahn (Schnitter in litt.) hasreported two specimens from umbelliferous plants.Schaffrath (2003a) has collected a few reports ofobservations from flowers and sap flows. In Po-land, Russia and Estonia, the beetle has beenobserved feeding on sap flows (Tenenbaum, 1913;Pawłowski, 1961; N. Nikitsky, pers. comm.; I. Süda,pers. obs.). Entomologists frequently search thissource for insects although only a few O. eremitaindividuals have been encountered, suggesting thatO. 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 thatadult beetles feed on bananas and apples.

Habitat requirements

Most findings of O. eremita have been made inhollow but still living, standing trees. The beetlehas also been found in dead, standing trees, butprobably such trees are often unsuitable becausethey are too dry. On some occasions (for instance,we know one tree in Sweden, one in Poland, threein Latvia and one in Estonia), living adults or lar-vae have been found in downed tree trunks. A fewtimes, the species have been found in old stubs(Latvia: D. Telnov, pers. obs.; Russia: N. Nikitsky,pers. obs.; Germany: Stegner, 2002). At many lo-calities, hollows suitable for O. eremita occur onlyin very large trees, but at other sites the species


has also been found at relatively thin, slow–grow-ing trees. For instance, the species has beenfound in Sweden in a hollow oak (Q. robur), grow-ing on a hill, with a diameter of 22 cm (Ranius &Nilsson, 1997), in central Italy in a beech (Fagussylvatica) 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 withthe beetle present are 150–400 years, while treesof rapid–growing species may often harbour O.eremita when they are younger; poplars (Populusspp.) and willow trees (Salix spp.) may harbour O.eremita when they are only a few decades old(Schaffrath, 2003a). The beetle inhabits fruit treesthat are 80–100 years old (Stegner, 2002). Pol-larded oaks in France harbour O. eremita whenthey are only 70–140 years (V. Vignon, pers. obs.).Also in Latvia, the species has been found inmany seemingly younger oaks, especially in ur-ban habitats (D. Telnov, pers. obs.).

The species mainly inhabits trunk hollows con-taining large amounts of wood mould. This hasbeen shown in studies in pasture oaklands inSweden (Ranius, 2000; Hedin & Mellbrand, 2003).Observations from chestnuts, willows and oaksin Italy confirm this (P. Audisio, pers. obs.). AlsoLuce (1995) found that hollows of an intermedi-ate to large size were used by O. eremita to ahigher extent than smaller hollows. Moreover, thebody size of the adult beetles has been found tobe larger in trees with more wood mould (Hedin& Smith, 2003). O. eremita inhabits trees withentrance holes situated a few (2–5) metres fromthe ground more frequently than those with holesnear the ground (Hedin & Mellbrand, 2003). How-ever, the beetle occurs over a wide range ofheights; it has been found in several tree hollowssituated 15–25 m from the ground (V. Vignon, P.Orabi & J.–M. Luce, pers. obs.) but on someoccasions also at or even below the ground level(Prunier, 1999; V. Vignon, pers. obs.).

The larvae usually dig between the wood mouldand the internal wall of the trunk hollow (Palm,1959; Pawłowski, 1961; D. Baratelli, pers. comm.).There, they eat the wall and increase the treehollow and the amount of wood mould. Often thefrass from O. eremita larvae is a dominating partof the tree hollow content. In this way O. eremitamay improve the habitat for other species living intree hollows (Ranius, 2002a). Elater ferrugineusL. and other click beetles, Tenebrio spp. andalleculids such as Prionychus spp. are beetle spe-cies that often occur together with O. eremita [re-ported from France (Brustel , 2001), Denmark (Mar-tin, 1993), Germany (Schaffrath, 2003b), Poland(Pawłowski, 1961) and Sweden (Ranius, 2002a)].The most important predator on O. eremita larvaeis probably the larvae of the click beetle Elaterferrugineus (Schaffrath, 2003b). Other enemies areless known. Vertebrates predating on O. eremitahave only occasionally been reported. However, inKozienice Forest (central Poland), several adults

of O. eremita have been preys of the roller Coraciasgarrulus L. (Rębiś, 1998). Mites and nematodesare other possible enemies, which so far haveonly beeen described anecdotally. Larvae infestedby mites (deutonymphs of Gamasina), collected inwinter (southern Poland) in a hollow stump ofalder, died in the laboratory during the followingsummer killed by these mites (Szwałko, pers.obs.). There is one record of larvae infested by anematod (Martin, 1993). Protaetia lugubris (Herbst)is a Scarabaeid beetle that seems to have similarhabitat requirements as O. eremita (Luce, 1995),and therefore it has been suggested that they maybe competitors (Ranius, 2002c).

Tree species

Oak (Quercus spp.) is the most important tree forO. eremita, followed by lime trees (Tilia spp.), wil-lows (Salix spp.), beech (Fagus sylvatica) and fruittrees (Prunus spp., Pyrus spp, Malus spp.) (fig. 1).In many regions, ash (Fraxinus spp.), elm (Ulmusspp.), chestnut tree (Castanea sativa), aspen andpoplars (Populus spp.), birch (Betula spp.) and ma-ple (Acer platanoides) are also important host trees.Mulberry trees (Morus spp.), common alder (Alnusglutinosa), plane trees (Platanus spp.) walnut trees(Juglans regia) and hornbeam (Carpinus betulus)are other tree species which the beetle has beenfound 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) inSlovakia and Poland. The species has been foundin exotic tree species such as false acacia (Robiniapseudoacacia) (for instance, in France, Germany,Italy and Austria), Japanese honeysuckle (Loniceranipponica) (Janssens, 1960), silver maple (Acersaccharinum) (in Germany: Stegner, 2002) andhorse chestnut (Aesculus hippocastanum) (in Den-mark, Sweden, Poland and Austria).

Most localities today occur on land that has beenused by man for a long time. Only in some regions,such as Spain, southern Italy and the Balkans, moreor less natural forests are reported to be the majorhabitat of O. eremita. Perhaps the beetle is to ahigher extent associated with man–made, moreopen habitats in Northern Europe (even though thebeetle may occur in shaded situations also in Scan-dinavia), but occurs in denser forests further south.This could be a compensation for the climate (cf.Thomas, 1993); in regions with colder climate thespecies tends to avoid the most shaded situa-tions (Ranius & Nilsson, 1997), while in regionswith warm and dry climate, free–standing treesperhaps tend to be too dry. However, it is difficult toachieve hard evidence for this hypothesis.

In Scandinavia, pasture woodlands and deerparks with broadleaved trees are the most impor-tant habitat. Also in Germany, the largest O. eremitalocalities are on land that has been used for graz-ing or hunting (Schaffrath, 2003b).

6 Ranius et al.

The species inhabits urban habitats such asparks and alleys. For instance in Banska Bystrica(Franc, 1997), Strasbourg, Rome, Florence, Dres-den, Leipzig, Salzburg, and Kaunas, O. eremitaoccurs in the city centres. In several regions, suchas Hungary, Slovakia, some parts of Russia andsouth–eastern Germany, the O. eremita localitiesare concentrated to floodplain areas, where thehabitat may be forests or smaller woods in agri-cultural land. Old orchards may be important habi-tats, especially in central Europe (e.g. EasternGermany, Austria and Slovenia).

In some regions, the beetle mainly uses pol-larded trees. Pollarding implies that tree branchesare repeatedly cut in order to increase the produc-tivity of wickers, poles and fuel–wood. In parts ofFrance, there are extensive networks of hedge-rows where O. eremita inhabits pollarded oaks. Inthe intensively cultivated Po river basin of northernItaly, pollarded willows along riversides are themost important habitat for O. eremita. Abandonedpractice 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 thenumber of hollow trees per stand (Ranius, 2000;fig. 2). The positive correlation is consistent withwhat metapopulation ecologists refer to as Lev-in’s rule (Hanski & Gilpin, 1997). Ecological stud-ies of O. eremita support the view that each treepossibly sustains a local population and that thepopulations in stands together form a metapop-ulation (Ranius, 2002b). For instance, the specieshas been found to have a restricted dispersal(Ranius & Hedin, 2001; Hedin et al., 2003), andthe population fluctuations in individual trees takeplace asynchronously (Ranius, 2001).

A survey of an area in southeastern Swedenrevealed that O. eremita still occurs in almost alllarger stands, but the occupancy pattern did notindicate any connectivity between stands (Ranius,2000). This could be because the density of hol-low oaks historically has been much higher thantoday. Over the last two centuries, old oaks haveseverely declined in Sweden (Eliasson & Nilsson,2002; Hedin, 2003). Thus, most hollow tree standswere probably colonized by O. eremita long agoand, lately, the beetle has been confined to smallstands without connectivity.

In the area surveyed in southeastern Sweden,O. eremita was systematically absent from singletrees and very small stands, probably because ofextinctions from these stands (Ranius, 2002c). Thisis consistent with the underlying reasoning of theminimum viable metapopulation size (MVM) con-cept (Hanski et al., 1996). MVM is an estimate ofthe minimum number of interacting local pop-ulations (in this case hollow trees inhabited by O.eremita) that is necessary for long–term survival ofa metapopulation. Computer simulations of O.

eremita show that its metapopulation dynamics areslow, in the sense that it may take centuries fromthe decrease of the number of hollow trees until thesmall O. eremita population finally become extinct(Ranius & Hedin, 2004). Therefore, in many smallerstands which still harbour a population today, weshould not expect O. eremita to be able to survive inthe long run (Ranius & Hedin, 2004).

Survey methods

As O. eremita rarely leave the tree hollows, thespecies must be actively searched for. Where nosurveys targeting O. eremita have been conducted,we should expect that many localities with O.eremita remain unknown.

The most efficient methods to survey O. eremitaare pitfall trapping (Ranius, 2001; fig. 3) andsearching for larvae (Martin, 2002) or remains ofadult beetles and excrements in the wood mould(Ranius & Jansson, 2002). Pitfall trapping is car-ried out during late summer (July–August), whenthe adults are active. If the traps are emptied atleast every second day and the beetles are re-leased, the method is not destructive. By marking,releasing and recapturing the adults, populationsizes may be calculated (Ranius, 2001). Martin(2002) has searched for larvae in the wood mould.This is preferably done in late autumn when thelarvae occur higher up in the wood mould and areeasier to find than at other times of the year.

Ranius & Jansson (2002) have searched for re-mains (pronotum, elytra and heads) of adult beetlesand excrements from larvae in a certain amount ofwood mould from each tree. In Eastern Germany,excrements have been searched for at trunk–basesand many new occurences were found in this way(Stegner, 2002). Several Scarabaeid species havesimilar excrements, however, the shape and sizemake it possible to determine O. eremita excrements(Stegner, 2002). These methods can be usedthroughout the year and are appropriate when largeareas should be systematically surveyed. Asexcrements and remains of adults may persist formany years, their presence does not ascertain thatthere is presently a living population in the tree. Forthis reason it is useful to combine the methods withpitfall trapping: first excrements and remains of bee-tles are searched for, and then pitfall traps are setonly in those trees where excrements or remains ofbeetles have been found. This is a much moreefficient way to search for localities with living adultsin comparison to solely using pitfall traps.

Another method to record the presence of thespecies is to smell for the unmistakable scent ofthe species. This should be done in July or Au-gust, on warm days or afternoons. It is usuallynecessary to be very near the entrance hole, butsometimes it is possible to smell the beetles froma distance of up to tens of metres.

Window trapping is not an appropriate methodto survey O. eremita (Ranius & Jansson, 2002).Hand–collecting of adult beetles is possible, but


Fig. 1. Typical trees harbouring Osmoderma eremita for different parts of Europe: A. Pollarded oaksin 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. eremitabefore 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. Roblesdesmochados en zonas de setos en el oeste de Francia; B. Robles en una región con charcas deAlemania 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 consauces en un parque de Alemania.

Vin

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because the beetles rarely leave the tree hollows,it is not very efficient. O. eremita does not seem tobe attracted by baits such as red wine and molas-ses, normally used for cetonid beetles.

Known localities with O. eremita may be moni-tored, either by studying the beetle population

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

A B

CD

E

8 Ranius et al.

2001). The habitat may be monitored by revisit-ing the localities, checking that the inhabitedtrees are alive and not suffering from competi-tion of neighbouring trees or any other threat.This is much cheaper than monitoring the bee-tle population, and may generate advice aboutwhich management measures are needed. Thepotential to get new hollow trees in the futureshould also be evaluated and planned for. Boththese kinds of monitoring may be conducted, forinstance, every five years.

Occurrence in individual countries

The occurrence of O. eremita in each country whereit occurs (fig. 4) is described below. Lists withlocalities (those mapped in the figures) are givenin the Appendix. Updated information about projectsdealing with O. eremita are available at the website www.eremit.net.

Albania (fig. 5)

Most records are from the northern part of Alba-nia. The only information obtained regarding hosttree concerns an adult found in Tamara on abeech (Fagus sylvatica) (W. Schwienbacher, pers.com.). The species has been found both in low-land (Shkodër) and mountain areas (Maja eRagamit, Maja e Poliçanit).

Austria (fig. 6)

O. eremita is regarded as a highly endangeredspecies (Franz & Zelenka, 1994). However, it hasbeen recorded from more than one hundred lo-calities dispersed over a wide part of Austria. Thedistribution has its centre on the thermically ad-vantaged Eastern Lowland and extends to the in-ner–alpine Low Mountain Range, 800–1,000 ma.s.l. Previously, the species was found in woodand parkland landscapes managed with a lowintensity, but today the species is restricted to oldfruit plantations, trees along paths and streams,and at estates and animal parks with protectedwoodland. Some of the localities are large andonly managed with a low intensity by humans. Theinhabiting O. eremita populations therefore prob-ably have a low extinction risk here. Such localitiesare 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 inthe smallholdings in Upper Austria and in the west-ern parts of Styria (Kreissl, 1974; Mitter, 2001).

Oak (Quercus spp.), willow (Salix spp.) and limetrees (Tilia spp.) are the most important tree spe-cies, whereas beech (Fagus sylvatica), ash (Fraxinusexcelsior), elm (Ulmus glabra) and birch (Betula spp.)are more rarely used. Apple (Malus spp.) and pear

(Pyrus spp.) orchards seem to be important habitatsin some areas. Occasionally O. eremita has beenreported from introduced tree species such as horsechestnut (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 speciesmay have become extinct due to habitat loss.

Belarus (fig. 7)

O. eremita is a rare, local species in Belarus, and isincluded in the Red Data Book (Lapitsin, 1993). Intotal, 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 inlime tree (Tilia spp.), oak (Quercus spp.), elm (Ulmusglabra) and ash (Fraxinus excelsior), but also aspen(Populus tremula) and poplar (Populus spp.).

During the last few years, several new localitieswith O. eremita have been discovered. One locality isthe park of Priluki in the Minsk district. This is anancient park with old lime, ash and oak trees. Thereare many similar parks in Belarus where O. eremitawould possibly be found if the species was surveyed.

Belgium (fig. 8)

The last confirmed record of O. eremita in Belgiumdates back to 1944, and the species has thereforebeen regarded as regionally extinct. However, a re-cent record has been reported from the valley of "laBerwinne" (near Visé). O. eremita has been recordedfrom 15 localities in three different provinces: Brabant(central Belgium), Limburg (eastern Belgium) andLuik (southeastern Belgium). It has been found inold 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 endan-gered and is protected.

Belgium has a long history of forest fragmenta-tion and remaining forests have been intensivelymanaged, with a huge impact on fauna and flora(described by Desender et al., 1999). Especially inthe northern part of Belgium (Flanders), forests havetotally disappeared (e.g. Tack & Hermy, 1998), whilein Wallonia, natural forests have been converted tointensively managed tree plantations. Old trees havebeen removed, and are still being removed, not onlyfrom forests but also from agricultural areas. As aresult, the chance for beetles dependent on treehollows to persist has severely decreased.

No survey specifically targeting O. eremita or anyother saproxylic insects has been conducted duringthe last few decades other than two recent surveys

http://www.eremit.net.


of saproxylic beetles in a few forests (Versteirt et al.,2000; Heirbaut et al., 2002). Old localities where thespecies has been found have not been revisited forthe study of O. eremita.

Bosnia and Herzegovina (fig. 9)

There are old records of O. eremita from a widerange of Bosnia–Herzegovina. The altitudinal rangeis from 50 (Mostar) to 1,350 m a.s.l. (Igman andTreskavica).

Localities with the species present are almostcertainly still widespread throughout the country.However, owing to the civil war, it seems no sur-veys have been conducted over the last few years.

Bulgaria (fig. 5)

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

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)

In Croatia, O. eremita has a broad range, but israre. There are records from 31 localities, madebetween 1892 and 2000. O. eremita is not aprotected species but some localities with O.eremita are protected areas (such as Mt. Velebit,Mt. Učka, Mt. Papuk, Mt. Medvednica, Žumberakand Plitvice). No surveys focusing on O. eremitahave 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 SlovakRepublics it is regarded as endangered (Škapec,1992). Most of the O. eremita localities are situ-ated in southern and eastern Bohemia and most–southern and north–eastern Moravia, but there area few localities also in other parts of Czechia.

Numerous suitable habitats have been lost dur-ing the last fifty years. Nevertheless, some habi-tats, for instance, parks near castles and alleys,have been preserved as isolated fragments withlocal O. eremita populations still present. SomeO. eremita populations inhabit preserved lowland

Fig. 3. Osmoderma eremita and a pitfall trap.The trap consists of a jar placed inside ahollow oak with the opening on the level withthe wood mould surface.

Fig. 3. Osmoderma eremita y una trampa. Latrampa consiste en un recipiente situado den-tro del hueco del roble con la abertura a nivelde la superficie de la madera desmenuzada.

Nik

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Fig. 2. Frequency of occurrence / tree of thebeetle Osmoderma eremita in relation tostand size in localities in the province ofÖstergötland (from Ranius 2002a, n = 155),southeastern Sweden. Stand size is definedas the number of hollow oaks within a clusterwith a distance of < 250 m from one hollowoak to another.

Fig. 2. Frecuencia de presencia / árbol delescarabajo Osmoderma eremita en relacióncon el tamaño de la parcela en localidadesde la provincia de Östergötland (de Ranius2002a, n = 155), sureste de Suecia. El tama-ño de la parcela se define como el númerode huecos en robles dentro de un grupo conuna distancia de < 250 m de un hueco a otro.

1–3 4–6 7–10 11–61 97Stand size

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10 Ranius et al.

forests with large broadleaved trees, especially insouthern Moravia. Many populations seem to besmall and isolated, so the risk of local extinctionsin many cases is probably high. Another endan-gering factor in Czechia is the ongoing removal of"unhealthy" hollow trees, especially in anthropo-genic habitats which host the majority of the O.eremita populations.

Most findings have been made in oak (Quercusspp.), elm (Ulmus spp.), lime (Tilia spp.), willow (Salixspp.) and fruit trees (Balthasar, 1956). According toKollar (2000), the localities in Czechia are mainly inthe lowland (up to 500 m, rarely 600 m a.s.l.).

The distribution of O. eremita is relatively wellknown, with over 500 findings from about 200 lo-calities. This is due to a high number of entomolo-gists in the Czech Republic; the species has neverbeen systematically surveyed.

The first published survey of distribution of O.eremita in Czechia was a grid map by Jelínek(1992). More recently, Kollar (2000) summarizedO. eremita records. During the last two years,mapping has been conducted within the scope ofNATURA 2000. A more detailed survey is in prepa-ration by K. Chobot.

Denmark (fig. 10)

O. eremita is rare in Denmark, and has only beenfound on Eastern Jutland (Jylland) and the islandsZealand (Sjælland), Lolland, and Falster (Martin,2000). It seems to have become rarer in Zealandover the last 100 years, and has probably disap-peared from Jutland, whereas its presence in sev-eral localities on Lolland have been discoveredduring the last few decades. There are recordsfrom 28 localities. However, when these were re-cently revisited, the species were only found in 9 ofthem, even though hollow trees are still present atall localities. O. eremita was searched for in everytree whenever possible. However, some entranceholes were too small or situated too high to reachby ladder. At the largest locality (Bognæs Storskov,Zealand) O. eremita was found in 16 trees, while atthe 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 nearfuture as the populations are small and very iso-lated.

The species has been found breeding in sev-eral different deciduous trees, and once also in aconifer tree: silver fir (Abies alba). The most im-portant habitat is privately–owned deer parks orforests situated near old estates and manors.There, the species occurs mainly in oak (Quercusrobur) beech (Fagus sylvatica), and ash (Fraxinusexcelsior). Outside the forests, it has especiallybeen found in avenue trees: lime (Tilia cordata),elm (Ulmus glabra) and horse chestnut (Aesculushippocastanum).

Specimens from 28 localities were registered,when museums and private collection were re-

viewed in 1990–1991. These 28 localities weresurveyed, and living specimens were found at 10localities (Martin, 1993). When these ten localitieswere inventoried in 1999 (Martin, 2002), O. eremitawas found in 61 hollow trees (46 oaks (Quercusrobur), 10 beeches (F. sylvatica), 3 horse chestnuts(A. hippocastanum) and 2 ashes (F. excelsior)). Ofthese trees, 49 were alive, although several laterfell during a hurricane in December 1999.

Estonia (fig. 11)

Until recent years, O. eremita was known in Esto-nia only from an undated record from Tartu, prob-ably originating from the 19th century. In 1995, thespecies was found in an oak in a wooded meadowin Koiva woodland in southern Estonia. The bee-tles have since been found there repeatedly, oncefeeding on a flow of oak sap. A cocoon includingremains of an adult has also been found in ahollow maple (Acer platanoides) stub in an av-enue at Koikküla, a village situated nearby (Süda,1998, 2003).

Starting in 1999, the Estonian Seminatural Com-munity Conservation Association performed so–called bush clearing in the woodland. The aes-thetic aspect was over–emphasized in the workand a large amount of dead or broken trees wereburnt or removed, including large oak trees (Süda,2003). Despite this, O. eremita is still present atwoodlands along the Koiva river, although thenumber of suitable trees is small.

The existing population and possible new pop-ulations were searched for in 2000–2002 within theEstonian NATURA 2000 program. Despite the exten-sive search, no new records of O. eremita wererecorded, although suitable habitats can be found atother places in Estonia, e.g. on Saaremaa Island.

Finland (fig. 11)

O. eremita is only known from one locality in Fin-land: the island of Ruissalo (Runsala) in Turku.This is however a large locality; in an area ofabout 5 x 2 km, living specimens have been foundin 117 trees, remains from adults occurred in62 trees, and excrements were found in another155 trees (Landvik, 2000).

France (fig. 8)

In France, more than 300 localities with O. eremitaare known. Thus, O. eremita is widely distributed inFrance, but most existing sites are relatively remotefrom each other, leaving wide empty spaces, par-ticularly in forest regions. The species seems tohave decreased severely, especially in the northernpart of the country. In the southern part of France,there are probably still many localities that have notbeen discovered (J.–M. Luce, pers. comm.).


Most of the localities are not in forests but inagricultural landscapes. Forests with O. eremitaare normally only small localities situated far (oftenmore than 100 km) from each other. These forestshave a different history, for instance: (1) old forestsplanted by Colbert in the 17th century in the Forest ofBercé (Sarthe Department) and in the Forest ofTronçais (Allier Department); (2) forests conservedby the Barbizon School of Painters in theFontainebleau forest during the 19th century; (3)ancient castle parks (such as Forest of Compiègnein the Oise Department); (4) very old urban parkswith old trees (for instance, Strasbourg andMulhouse); (5) forests that have been grazed bycattle, for instance the Forest of Massane (PyrénéesOrientales) (Garrigue & Magdalou, 2000) and theForest of Sare (Pyrénées Atlantiques) (Van Meer,1999); and (6) religious sites, such as the beechgrove on the pilgrim site of the Sainte–Baume (VarDepartment) 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, thespecies mainly inhabit old, pollarded oaks. Ex-amples of such networks are, for instance: (1) inthe north of the Aveyron Department in an area ofmore than 500 km²; (2) in Bourbonnais in theAllier and Cher Departments in an area about2,000 km²; and (3) in the west part of France inan area about 30,000 km², in the Ille–and–Vilaine,Indre–and–Loire, Loire–Atlantique, Maine–and–Loire, Morbihan, Mayenne, Orme and Sarthe De-partments (Vignon & Orabi, 2003a, 2003b).

Before land consolidation (in the sixties), O.eremita occurred probably continuously in land-scapes with hedgerow networks. Today, the hedge-row networks have become more fragmented.

Oak is the most important tree species, fol-lowed by chestnut (Castanea sativa), ash(Fraxinus excelsior) and beech (Fagus sylvatica).O. eremita has also been found in common al-der (Alnus glutinosa), birch (Betula spp.) (Prunier1999), wild cherry (Prunus avium), poplar(Populus spp.), apple (Malus spp.) [rather fre-

Fig. 4. Distribution of Osmoderma eremita in Europe: . Last record before 1950, or the timeunknown; . Last record 1950–1989; . Last record in 1990 or later. Larger circles representrecords 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 fechadesconocida; . Último registro entre 1950 y 1989; . Último registro de 1990 o posterior. Los círculosmás grandes representan registros en Alemania Federal de donde no disponemos de datos delocalidades por separado.

12 Ranius et al.

quently in the Orne Department, (J.–F. Asmodé &V. Vignon, pers. obs.)], willow (Salix spp.) andplane tree (Platanus hybrida) (especially intowns). In the Mediterranean beech grove ofSainte–Baume, O. eremita has also been foundin yew trees (Taxus baccata).

A pollarded oak grows relatively fast; a treewith a diameter of 50 cm is normally between 70to 120 years old (Brin, 1999), and such a treemay harbour O. eremita. Pollarded trees over 300years old are very rare, and trees over 140 yearsseem to die relatively fast. Very old, dying treesare normally cut down to be used as firewood,partly for aesthetic reasons.

Only a few sites have been subject to detailedsurveys of hollow trees and O. eremita. When treeswere mapped in the forest of Massanne, there wereon average 60 hollow trees per hectare. The occu-pancy rate of O. eremita was about 6% (Garrigue &Magdalou, 2000). Two hedgerow network regionsin the western part of France, that may form thelargest locality for O. eremita in France, have alsobeen surveyed. In an 8,500 hectares site in theSarthe Department, one hollow tree per hectarewas found. Even in this fragmented site, O. eremitawas present. In the Orne Department, a hedgerownetwork was found to have 5 hollow trees per hec-tare in an area of 5,000 hectares. The highest den-sity observed in hedgerow networks is 10 hollowtrees per hectare in 200 hectares which have neverbeen subjected to land consolidation (J.–F. Asmodé& V. Vignon, pers. obs.). O. eremita occurs in 2 to20 % of the hollow trees in different parts of thehedgerow network in the Sarthe and Orne Depart-ments (J.–F. Asmodé & V. Vignon, pers. obs.). Ahigher occupancy rate, 26%, has been observed ina hedgerow network in the Aveyron Department(Brustel, pers. comm.).

The low occupancy rate in the hedgerow net-works implies that there is a long distance be-tween trees harbouring O. eremita. Therefore, thehabitat fragmentation is at many places probablytoo high for long–term survival of the species. Weassume that in more than 80% of the localitieswhere O. eremita is present today, there is asubstantial risk of extinction within 50 to 100 years.A study of a Carabid beetle in a hedgerow net-work indicated that its current distribution wasbetter correlated with characteristics of the land-scape 50 years ago than the present situation(Petit & Burel, 1998). Perhaps the situation issimilar in O. eremita, and in which case we shouldexpect local extinctions in the future due to thehabitat destruction over the last few decades.

At many sites, there are no younger trees to takeover the role as hollow trees in the future. As it willtake a long time before new hollow trees are gener-ated, survival of insects in hollow trees is possibleonly as long as the present old trees are preserved.

The hedgerow networks, which constitute themost important habitat for O. eremita, have beensubject to severe fragmentation since the 1960's.The decrease in numbers of hollow trees is not

only due to the reduction of hedgerows, but alsoto the lower density of trees in the hedgerows.Today, the hollow trees are very old, and renewalof the habitat is difficult. The traditional practice ofpollarding trees has been abandoned because itno longer serves any economic function. Thisdevelopment is also a consequence of the agri-cultural policy favouring intensive farming of cere-als, for example, rather than cattle rearing andhorse–breeding.

Forests with high densities of hollow trees aresmall and rare. It takes longer for hollows to formin forest trees than in pollarded trees. Therefore,the renewal of hollow trees in forests is in manycases difficult. Planning for the maintenance andthe renewal of hollow trees has to be conducted incooperation with administrators of the countrysideand foresters.

Germany (fig. 6)

More than 1,000 records of O. eremita (both recentand historical) are known from Germany. They aremainly from lower regions (less than 400 m a.s.l.)(Schaffrath, 2003b). O. eremita occurs in all fed-eral states in Germany. According to Schaffrath(2003b), there are at present 111 localities with O.eremita. However, investigations in recent yearshave resulted in a growing additional number (seeStegner, 2002; Ringel et al., 2003). The highestdensity of localities are in parts of Baden–Württemberg and Hessen and Niedersachsen andin Eastern Germany (Mecklenburg–Vorpommern,Brandenburg, Sachsen–Anhalt, Sachsen). InMecklenburg, Brandenburg, Berlin and Baden–Württemberg, the localities are often wide, openforests. In Sachsen and Sachsen–Anhalt, O.eremita is widespread, especially in great floodplain areas around Elbe, Mulde and Saale whichcontain remnants of old forests and pasture lands.O. eremita also occurs in landscape parks, or-chards (especially known in Sachsen) or histori-cal pond regions, where oaks have been plantedaround the ponds (Stegner, 2002). On the out-skirts 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 cem-eteries. The most important trees are oak (Quercusspp.) and lime–trees (Tilia spp.), followed by wil-lows (Salix spp.), beech (Fagus sylvatica) fruit trees(Malus spp., Prunus spp.) and ash (Fraxinusexcelsior).

Changes in land use, both in agriculture landand in forests which affect O. eremita, took placein Western Germany several decades earlier thanin the East (Schaffrath, 2003b). Old–growth for-ests have been cut down, and forests with limetrees, oaks, hornbeams and beeches have beenreplaced by conifer plantations. Where decidu-ous forests remain, trees are usually cut downlong before tree hollows can be generated. In


pasture landscapes and parks, free–standingtrees have become scarcer for several reasons,for instance due to ceased removal of underwood(Vera, 2000). On agricultural fields and in alleystrees have been removed. Besides, a wide relin-quishing of old fruit plantations has led to a mas-sive lost of suitable habitats in Western Germany(Stegner, 2002). A problem, which today is mainly"eastern", is the loss of large trees due to thedevelopment of housing and trade areas and newhighways (Saxony: Lorenz, 2001; Schaffrath,2003b). For instance, many trees with O. eremitawere lost due to the building of an automobilefactory in Dresden.

In Germany, the conservation of O. eremitashould be ensured by the Federal Nature Protec-tion Act, but due to the safety regulations based oncivil law, liability laws and insurance laws, hollowtrees in cities and villages are often cut muchearlier than necessary. Possible safeguards fortrees are rarely considered. Many localities with O.eremita are included in NATURA 2000 sites (ac-cording to EU’s Habitats Directive), but especiallytrees in towns are usually not included in suchsites. This means that some important localitiesfor O. eremita in Germany do not have any siteprotection by NATURA 2000 (Schaffrath, 2003b;Stegner, 2002).

Many findings in Germany occur in isolated treesor very small stands where it is unlikely the spe-cies will be able to survive in the long term. In the19th century, O. eremita was probably common allover Germany (Horion, 1958). In the 1950s, Horion(1958) described the beetle as "...only local andnot common; in the west and southwest a rarity...".Schaffrath (2003b) published the first grid–baseddistribution map for Germany, based on historicaland recent records available from museums andprivate collections. A coordinate–based map ofSachsen (Saxony) was published by Stegner(2002) and is continued under www.eremit.net. Agrid–based map of Mecklenburg–Vorpommern waspublished by Ringel et al. (2003).

Fig. 5. Distribution of Osmoderma eremita inSerbia, Montenegro, Macedonia, Albania,Greece, Rumania, Moldova and Bulgaria: .Last record before 1950, or the time unknown;

. Last record 1950–1989; . Last record in1990 or later.

Fig. 5. Distribución de Osmoderma eremitaen Serbia, Montenegro, Macedonia, Albania,Grecia, Rumania, Moldavia y Bulgaria: . Úl-timo registro anterior a 1950, o fecha desco-nocida; . Último registro entre 1950 y 1989;

. Último registro de 1990 o posterior.

Fig. 6. Distribution of Osmoderma eremita inEastern Germany, Poland, Czechia, Slovakia,Austria and Hungary: . Last record before1950, or the time unknown; . Last record1950–1989; . Last record in 1990 or later.

Fig. 6. Distribución de Osmoderma eremitaen Alemania del este, Polonia, RepúblicaCheca, Eslovaquia, Austria y Hungría: . Úl-timo registro anterior a 1950, o fecha desco-nocida; . Último registro entre 1950 y 1989;

. Último registro de 1990 o posterior.

http://www.eremit.net.

14 Ranius et al.

According to a new focus of nature protectionon O. eremita, numerous investigations have re-cently been accomplished, collecting a lot of newdata. The preparation of management plans forNATURA 2000 sites in the next few years as wellas the demand for monitoring by Habitats Direc-tive will give us even better knowledge about theoccurrence of this species.

Great Britain

O. eremita does not occur in Great Britain (Alexan-der, 2002).

Greece (fig. 5)

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

Hungary (fig. 6)

Endrödi (1956) stated that O. eremita was rare inHungary, but distributed throughout the whole coun-try. This was confirmed when we went through in-sect collections. Most findings are from floodplainareas, mostly in willow trees (Salix spp.). However,the species also occurs at other places, for instanceon Kékes, the highest mountain peak in Hungary.

O. eremita is on the National Biodiversity Moni-toring Program (Merkl & Kovács, 1997) as a rel-evant species when monitoring very old trees orforests. However, so far no detailed studies havebeen 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 ofItaly. Most of the known localities in NorthernItaly are in low altitude areas (up to 700 ma.s.l.), while in Southern Italy and Sicily, thespecies has been found up to 1,500 m a.s.l.The host trees for O. eremita are, in decreas-ing order of importance: deciduous and ever-green oaks (especially Quercus robur, Q. ilex,Q. petraea, Q. frainetto), chestnut (Castanea

sativa), willows (Salix spp.), beech (Fagussylvatica), mulberry (Morus spp.), lime (Tiliacordata), maple (Acer spp.), elm (Ulmus spp.),plane–tree (Platanus orientalis), aspen (Populustremula) and walnut (Juglans regia).

Along the Aterno river valley (Pile and Preturo)and the Peligna river valley (Sulmona), as wellas at the springs of Pescara river (Popoli), O.eremita occurs mainly in woods of white willowSalix alba (Marotta et al., 1997). Also in PianuraPadana (Po Valley), a large and intensively culti-vated lowland, O. eremita is mainly found inplanted willows. Further south, the distributionof O. eremita ranges from the remnants of ever-green Mediterranean forests, which stretch alongthe Tyrrhenian coast up to the belt of montanebeech forest. Several O. eremita localities are inthe submontane and low montane belt of centraland southern Apennines, while others are inbeech forests of Abruzzo, Basilicata and Calab-ria. Along the central Tyrrhenian coast, the spe-cies has only been found in two adjacent naturalreserves: Castelfusano and Castelporziano, bothsituated 20–30 km from Rome. Despite inten-sive search, O. eremita has never been found inthe Circeo National Park, which includes largeareas of forests with old trees.

During the last few decades, several records ofO. eremita have been made in old trees (mainlyoaks) situated in parks or avenues in urban areas(e.g. Florence and Rome). An example of such alocality is "Villa Borghese", a historical park situ-ated in the centre of Rome, where the beetles livein old holm oaks (Quercus ilex). At such placesthe old hollow trees are threatened due to con-flicts with public safety.

We have more information about the species fromnorthern Italy, due to the large number of entomolo-gists there. Surveys focused on O. eremita havebeen 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 ofthe populations are small and isolated. Todaymore than 302 findings are known from 83 locali-ties. 95% of the localities have been discoveredduring the last four years. This species is pro-tected in Latvia and included in the Red Data Bookof 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 recordsare from agricultural and urban areas, mainly cityparks and alleys. In forests, the species has onlybeen observed in very old trees, while in agriculturaland urban landscapes O. eremita often inhabits treesthat seem to be comparatively younger. Lime tree(Tilia cordata), oak (Quercus robur) and maple (Acer


platanoides) are the most important tree species(Telnov, 2001, 2002). In forests, the localities areusually small (often 1–3 trees) and situated severalkilometres from each other. Some old parks andavenues harbour tens of suitable trees.

The species is monitored since 2000 by revisit-ing localities and observing species presence/ab-sence. The only extinctions observed so far havebeen the result of felling old trees regarded asdangerous in the city of Riga and other places.Because many populations are so small and iso-lated, the risk for local extinctions is high duringthe following few decades.

Data from literature and insect collections (muse-ums and private) have been compiled. In the collec-tions there were only about 55 specimens collectedduring the last 155 years. Field surveys have beenconducted mostly during the last four years.

Lithuania (fig. 11)

In Lithuania, O. eremita is rare and regarded asvulnerable (Pileckis & Monsevičius, 1992) with mostfindings being from the central part of the country(Pileckis & Monsevičius, 1995). The species hasbeen found in oak (Quercus spp.), maple (Acer

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

Macedonia (fig. 5)

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

Moldova (fig. 5)

In Moldova, O. eremita is regarded as critically en-dangered (CR) (Neculiseanu & Dănilă, 2000). Weknow only one specimen from Moldova, collectednear Bender, in eastern Moldova, in 1917 (Miller &Zubovski, 1917; Medvedev & Shapiro, 1957).

Fig. 7. Distribution of Osmoderma eremita inBelarus, Russia and Ukraine: . Last recordbefore 1950, or the time unknown; . Lastrecord 1950–1989; . Last record in 1990 orlater.

Fig. 7. Distribución de Osmoderma eremitaen Bielorrusia, Rusia y Ucraína: . Últimoregistro anterior a 1950, o fecha desconoci-da; . Último registro entre 1950 y 1989; .Último registro de 1990 o posterior.

Fig. 8. Distribution of Osmoderma eremita inThe Netherlands, Belgium, France andSpain: . Last record before 1950, or thetime unknown; . Last record 1950–1989;

. Last record in 1990 or later.

Fig. 8. Distribución de Osmoderma eremitaen Países Bajos, Bélgica, Francia y España:

. Último registro anterior a 1950, o fechadesconocida; . Último registro entre 1950 y1989; . Último registro en 1990 o posterior.

16 Ranius et al.

In 2001, surveys revealed the presence of sev-eral saproxylic beetles regarded as indicator byspecies (Speight, 1989). However, O. eremita wasnot found (Neculiseanu et al., 2001). More surveysare to be conducted and these will hopefully alsoprovide records on O. eremita.

The Netherlands (fig. 8)

O. eremita is considered extinct in the Netherlands.The last specimen was collected in 1946 inWijnandsrade, in the extreme south of the country.The very few specimens in Dutch collections sug-gest that O. eremita has been extremely rare overthe last 200 years. Most of the Netherlands hasbeen deforested for centuries and localities with along–term supply of decaying large trees have beenparticularly scarce since a long time ago. As aresult, many saproxylic insects occurred in isolatedpopulations and eventually became extinct.

No specific surveys focused on O. eremita havebeen conducted. Many skilled amateur coleopteristshave been active there during the last century and itseems most unlikely that they have overlooked O.eremita during this time.

Norway (fig. 10)

Live specimens of O. eremita have not beenfound in Norway during the last 100 years. Dur-ing the 19th century, the species was noted fromDrammen (Siebke, 1875) and Asker (Strand,1960; Kvamme & Hågvar, 1985). There are nospecimens from Drammen or Asker in the zoo-logical museums of Norway today, but an adultspecimen in the collection of Zoological Museumin Oslo is labelled "Ex. Coll. Norway. EinarFischer" (Karsten Sund, pers. comm.). Duringthe last few decades only fragments of adultspecimens, probably of very old origin, have beenfound. They have all been collected in hollowoaks at a third locality, on Rauer Island nearFredrikstad (Strand, 1960; Zachariassen, 1981;Hanssen & Hansen, 1998).

Several collectors have searched for the speciesduring the last twenty years, but the negative resulthas led to the assumption that the species hasprobably disappeared from Norway (Zachariassen,1981, 1990; Hanssen et al., 1985). On the Norwe-gian Red List (Anonymous, 1999) the species hasbeen given the category "Extinct?". O. eremita wasone of ten invertebrate species proposed for pro-tection nation–wide according to the Nature Con-servation Act (Anonymous, 1994). However, finallyO. eremita was not protected according to this act,because it was assumed to be regionally extinct(Øystein Størkersen, Directorate for Nature Manage-ment, pers. comm.).

Suitable habitats for O. eremita, such as hollowtrees of oak (Quercus robur), beech (Fagussylvatica) and lime (Tilia cordata), occur mainly in

the agriculture landscape in the county of Østfoldand Vestfold. In addition, there are a few areaswith stands of old oaks in woodland, especially inthe hilly landscape around Lake Farrisvannet inVestfold. The areas around Drammen and Askerare today, like all urban areas around the Oslofjord,heavily exploited and very few localities with hol-low trees are left.

During the last decades, it is mainly huge oakswith great openings near the ground that havebeen investigated (Zachariassen, 1981; Hanssenet al., 1985; Hanssen & Hansen, 1998; Hanssen,1999). Trees with entrance holes that are small orhigher up are less studied in Norway and maypossible contain undiscovered populations of O.eremita.

Poland (fig. 6)

The distribution area covers the whole of Poland,except for mountainous areas. The highest altitudewhere the species has been found is 885 m(Zakopane; Oleksa et al., 2003). In the east, wherethe species’ occurrence is better known, it occursin old trees in small groups along river banks, fieldroads, property borders, and sometimes in old or-chards and parks. It has also been found relativelyoften in urban habitats such as old avenues, cityparks and cementeries. In broadleaved and mixedforest, O. eremita is rare but probably still presentin older stands and wood margins, especially atsites difficult to reach. When saproxylic beetles wereinventoried in thirteen nature reserves of Upper Si-lesia (former Katowice Province), O. eremita wasfound in three reserves (Szafraniec & Szołtys, 1997;J. Michalcewicz, pers. comm.). In 10 x 10 kmsquares in the Niepołomice Forest (southern Po-land), O. eremita was present in at least three outof six squares (P. Szwałko, pers. obs.). In northernPoland, an inventory from 1999–2003 betweenElbląg, Iława, Susz, and the river Pasłęka (northernPoland), revealed that O. eremita occurred in 24 outof 37 investigated 10 x 10 km squares (A. Oleksa &R. Gawroński, unpubl. data).

Oak (Quercus robur) is the most important hosttree 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 frombeech (Fagus sylvatica), ash (Fraxinus excelsior)and horse chestnut (Aesculus hippocastanum)(Pawłowski, 1961). In the Niepołomice forest, co-coons containing remains of larvae and adults ofO. eremita have been found in Scots pine (Pinussylvestris) (Oleksa et al., 2003).

In the second half of 19th century, O. eremitawas probably still abundant and frequent in Po-land. Contemporary authors (e.g. Letzner, 1871)reported it as being found relatively often. For thatreason they did not list localities for O. eremita, incontrast with other beetle species that are morecommon today. O. eremita has lost most of its


habitats today and is extinct in some areas(Szwałko, 1992b). The species is included in localand national red lists (Szwałko, 1992b; Pawłowskiet al., 2002). Old trees have been removed inmanaged forests, along roads and in urban ar-eas, regarded as a source of "pests and patho-genic fungi" or a danger for humans and vehicles.Many monumental trees, which are specially pro-tected by law, have been "cured" by mechanicalcleaning of the hollows and impregnating of thewood surface with pesticides (Szwałko, 1992a).Such methods of "conservation" have been re-stricted due to Polish implementation of the BernConvention and EU’s Habitat Directive. New forestmanagement methods promote preservation ofsome old, especially hollow, trees wherever pos-sible. Localities where the species still exists havealready been or will be protected under the re-cently started NATURA 2000. On the other hand, inmany managed forests (including some forest

nature reserves) the wrongly understood "aestheticmind" gives rise to further elimination of O. eremitahabitats (Gutowski & Buchholz, 2000). As a result,other habitats, such as woods along fields,streams and lakes become more important for thesurvival of the species.

About 170 localities in Poland are known. Muchof the information has originated from entomolo-gists working mainly in the eastern part of Po-land, which at least partly explains the lower den-sity of findings from north–western Poland. Toget a better picture of the whole situation in Po-land, investigations in the western part of thecountry 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 since1911 (Fleck, 1904–1906; Petri, 1912), which canbe explained by the low search effort.

Fig. 9. Distribution of Osmoderma eremita inSwitzerland, Italy, Slovenia, Croatia andBosnia–Herzegovina: . Last record before1950, or the time unknown; . Last record1950–1989; . Last record in 1990 or later.

Fig. 9. Distribución de Osmoderma eremitaen Suiza, Italia, Eslovenia, Croacia, y BosniaHerzegovina, Italy, Slovenia, Croatia andBosnia–Herzegovina: . Último registro an-terior a 1950, o fecha desconocida; . Últi-mo registro entre 1950 y 1989; . Últimoregistro en 1990 o posterior.

Fig. 10. Distribution of Osmoderma eremitain Norway, Denmark and Sweden: . Lastrecord before 1950, or the time unknown; .Last record 1950–1989; . Last record in1990 or later.

Fig. 10. Distribución de Osmoderma eremitaen Noruega, Dinamarca y Suecia: . Últimoregistro anterior a 1950, o fecha desconoci-da; . Último registro entre 1950 y 1989; .Último registro en 1990 o posterior.

18 Ranius et al.

O. eremita occurs, for instance, in oak or mixedforests along the Danube alluvial plain and inbeech or hornbeam mixed forests at the foot of theCarpathians. In many forests, trees with hollowsare often removed because they are considered apotential danger.

Russia (fig. 7)

In western Russia, O. eremita has been found inthe zone of nemoral and boreo–nemoral forest, in18 different regions and in 6 republics. The spe-cies occurs mainly in hollow oak trees (Quercusrobur), and less frequently in willow (Salix spp.),aspen and poplar (Populus spp.), lime (Tiliacordata), ash (Fraxinus excelsior), apple (Malusspp.), pear (Pyrus communis) and elm (Ulmuslaevis) trees. Larvae have occasionally been foundto develop in stubs.

For most parts of Russia we have only limitedknowledge about the species’ occurrence, butmore is known regarding a few regions, such asChuvashiya. At least 70 specimens were observedin Chuvashiya between 1988 and 2002. The spe-cies occurs mainly in oak woods along the Volgabanks, from the western to the eastern border ofthe republic, in floodland oak woods along theSura and in oak woods in the central and east–central parts of Chuvashiya. The height rangesfrom 70–200 m a.s.l. O. eremita has almost neverbeen found in those wide areas in southern andsouth–western Chuvashiya that are covered withmixed forests, and it has not been found in thesteppes in the south–west and south–east. Infloodland oak woods near the Sura River in theprotected zone of the Prisursky State Nature Re-serve, Alatyr district, it is relatively easy to observethe beetle in hollow trees, which occur abun-dantly there.

O. eremita is decreasing in Russia becauseold broad–leaved trees are cut down. Some localpopulations (e.g., in some parts of Cuvashiya andUdmurtiya) are more or less safe because theyare in reserves or other areas where the trees arenot being felled. In all unprotected areas, the spe-cies is vulnerable due to mass cutting of old oaks.The species has been included in the Red DataBook of the Russian Federation (Nikitsky, 1983,2001), USSR (Lopatin, 1984) and in some re-gional 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), andStavropol region (Sigida, 2002). To preserve O.eremita and other species associated with an-cient trees, regional branches of the Ministry ofNatural Resources of Russia should restrict thepermits to cut down old trees, especially oaks.

Data from specimens in museums and pri-vate collections have been collected. In most ofthese localities, we know that O. eremita is stillpresent.

Serbia and Montenegro (fig. 5)

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

Slovakia (fig. 6)

As early as 50–70 years ago, O. eremita was re-ported to be declining in the present territory of theCzech and Slovak Republics (Fleischer, 1927–1930;Pfeffer et al., 1954). However, the beetle occurred atmany sites in southern and central Slovakia andwas locally not rare (Roubal, 1936). Since that time,nature in Slovakia has been modified by humanactivity, and changes in the landscape have mainlyoccurred in easily accessible lowlands and foot-hills. Numerous valuable habitats such as pasturewoodlands, old trees growing in small groups, al-leys and hedges as well as trees bordering riversand streams have been lost. Nevertheless, thiswas not excessive compared to the rest of Europe(Zach, 2003); some habitats have been retained inthe form of isolated fragments and local O. eremitapopulations have survived.

A distribution map of O. eremita was compiled byJelínek (1992) using data from J. Roubal and L.Korbel and archive material from the Faunistic Sec-tion of the Czecho–Slovak Entomological Society.According to this map, there were 20 localities up to1960. Most of them (16) were located in western,southern and central Slovakia. In the period 1960–1990, seven sites in southern and western Slovakiawere recorded on a map, while there were no locali-ties in central and eastern Slovakia. This might indi-cate a strong decrease in the number of O. eremitalocalities in Slovakia. However, when we compiledinformation about the present range of O. eremita,the beetle was recorded from more than 30 locali-ties. Obviously, some of them were not included inthe study by Jelínek (1992). The explanation for thiscan simply be that more information has been ob-tained since that time, although no one is currentystudying the beetle in detail.

O. eremita occurs mainly in the following habitats:(1) oak pasture woodlands with scattered groups oftrees or solitary trees; (2) floodplain forests withlarge trees. It mainly breeds in large willows, pop-lars and oaks —the latter in drier situations; (3)parks and alleys; (4) abandoned orchards, today avery scarce habitat; (5) mixed oak and pine forests;and (6) forest edges with large trees growing onsouth–facing slopes.


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 founddeveloping in Scots pine (Pinus sylvestris) atZahorska nizina lowland, western Slovakia (T.Olsovsky, pers. obs.).

The advantage of polyphagy for Slovakian for-est beetles in general (Whitehead, 2000) is, inthe case of O. eremita, eroded by the ongoingremoval of dying and dead trees. Large deadtrees are not often being replaced by youngerones. This will cause local extinctions of O.eremita populations. In town parks, tree hollowsin "unhealthy" trees are cleaned, and this maydestroy populations. In the Slovakian Red–List,the species is categorized as "endangered"(Holecová & Franc, 2001).

Further data may be available from museumsand private collections. Co–operation with research-ers involved in bat studies carried out in tree hol-lows 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 ofdifferent regions of Slovenia as infrequent (Scopoli,1763; Siegel, 1866; Brancsik, 1871; Martinek, 1875).It seems that the species is distributed all overSlovenia where suitable habitats are present. Oldwillows (Salix spp.) are reported as the most com-mon finding place, but also oak (Quercus spp.) andfruit trees are mentioned as habitat for the species(Scopoli, 1763; Siegel, 1866; Brancsik, 1871;Martinek, 1875). In the collections there are manyvery old specimens, but recent records are few,suggesting that the species has decreased. Thereason is probably the same as in the rest of Eu-rope —old fruit orchards as well as other old treeshave become much rarer. The species is consid-ered endangered by the Slovenian Red List (Anony-mous, 2002). O. eremita has never been surveyedsystematically in Slovenia.

Spain (fig. 8)

O. eremita seems to be very rare in Spain. It hasbeen found along a narrow band in the northernpart of the country running from the Picos deEuropa in the west to Montseny (Barcelona) in theeast. Apparently suitable habitats are found furtherwest from its known Spanish distribution area butthe species has not been reported there.

The main habitat for O. eremita in Spain ishumid deciduous forest. Most records come frombeech (Fagus sylvatica) forest in the mountains ofthe Pyrenees or Picos de Europa. In Navarra it

has been found in old forests of oak (Quercusrobur and Q. humilis).

In most cases, adults have been found walk-ing on old beech or oak trunks, in shaded andhumid 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 singlecase, an adult was found on an inflorescence ofSambucus nigra (Bahillo de la Puebla et al.,2002). The species seems to be absent frommore anthropogenic environments such asbocages and urban parks. Adults have been ob-served mainly in the daytime but some captureshave been obtained at night, using artificial light(San Martín et al., 2001).

In 1995–96, the information about all Spanisharthropods listed in the Habitat Directive of EUwas gathered and distribution maps and available

Fig. 11. Distribution of Osmoderma eremitain Finland, Estonia, Latvia, Lithuania andKaliningrad (Russia): . Last record before1950, or the time unknown; . Last record1950–1989; . Last record in 1990 or later.

Fig. 11. Distribución de Osmoderma eremitaen Finlandia, Estonia, Latvia, Lituania yKaliningrado (Rusia): . Último registro an-terior a 1950, o fecha desconocida; . Últi-mo registro entre 1950 y 1989; . Últimoregistro en 1990 o posterior.

20 Ranius et al.

biological information on O. eremita were pub-lished (Galante & Verdú, 2000). However, no com-prehensive revision of entomological collectionsseems to have been carried out. Since then, newrecords have been published that extend the Span-ish distribution area to the West (Bahillo de laPuebla et al., 2002; Ugarte San Vicente & UgarteArrue, 2002) and South (San Martín et al., 2001).These new records suggest that the species hasbeen overlooked in the past, due to inefficient sam-pling methods or low sampling effort.

Sweden (fig. 10)

The highest concentration of known O. eremitalocalities in the world occurs in south–easternSweden. O. eremita occurs only in the southernpart of Sweden, up to the northern limit for oakpastures. The main habitat is pasture woodlandswith old oaks, especially near castles, estates andchurches (Ranius, 2000). There are also somerecords from parks, avenues and deciduous for-ests (Antonsson et al., 2003). Oak (Quercus robur)is by far the most important tree species. Espe-cially in the very south of Sweden, O. eremita hasalso been found in several other tree species,such as beech (Fagus sylvatica), ash (Fraxinusexcelsior), lime (Tilia chordata), common alder(Alnus glutinosa) and horse chestnut (Aesculushippocastanum) (Antonsson et al., 2003).

Old oaks were very common in the Swedishagricultural landscape until 200 years ago, butfor a few decades in the early 19th century, farm-ers removed hundreds of thousands of old oaksfrom their land (Eliasson & Nilsson, 2002). It wasmainly on land owned by the nobility where oakswere left. Today, ceased grazing is a severe threatto the oaks on pasture woodlands, mainly be-cause the old trees suffer from competition andshading from the younger ones. Forest regrowthalso changes the microclimate in the trees andmany saproxylic beetles suffer from this (Ranius& Jansson, 2000).

About 30% of the localities are protected asnature reserves, and it is mainly the largestlocalities that are protected (Antonsson et al.,2003). The majority of localities are small, withonly a few suitable trees situated more thanone kilometre from other localities. At thesesites the risk for local extinctions during thefollowing decades is substantial. There are,however, a few localities with more than 100suitable trees (e.g. Bjärka–Säby, Sturefors andHallands Väderö). At these sites, measures aretaken to preserve the hollow tree habitat. There-fore the extinction risk for O. eremita at a na-tional level is probably low. However, there isstill no long–term planning to maintain or in-crease the amount of habitat when the hollowtrees present today become too old.

Ten years ago, 25 localities with O. eremitawere known, while currently this figure is 270, if a

locality is defined as a site with records of livingadults, larvae, fragments of adult body parts, orexcrements situated at least 1 km from otherlocalities. In a recent paper, data were compiledfrom field inventories conducted in 1993–2003(Antonsson et al., 2003). Totally, pitfall traps hadbeen used at 401 localities and wood mouldsampling at 104 localities. O. eremita was foundat about 30% of these localities. All larger Swed-ish museum collections have been gone through(Antonsson et al., 2003). Research on the ecol-ogy of the beetle has been conducted (e.g.Ranius, 2002b).

Switzerland (fig. 9)

During the last few decades, all but one record ofO. eremita in Switzerland are from the town ofSolothurn. There, the species has been found inlime trees (Tilia spp.) in alleys and in a park neara castle (Vögeli, 2002). There are still many oldtrees in alleys and parks in the locality, but someare threatened due to conflicts with public safety.One recent record is from the region of Brusio,near the Italian border, where there are hollowwillows (Salix spp.) and chestnut trees (Castaneasativa) (P. Audisio, pers. obs.).

There are several old records from other locali-ties in Switzerland (Allenspach, 1970). In the early20th century the species was described as "rare,although present throughout the lowlands of Swit-zerland" (Stierlin, 1900). Data on the specimens inSwitzerland’s museums and many private collec-tions have been collected. There were no morethan 80 specimens collected in Switzerland dur-ing the last 150 years. No inventories focused onO. eremita have ever been conducted.

Turkey (fig. 5)

We only know one record of O. eremita from Tur-key: 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 in-cluded 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). Themajority 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. eremitais still present: (1) an oak–dominated (Quercusrobur) forest with lime (Tilia cordata), maple (Acerplatanoides), ash (Fraxinus excelsior) and elm


(Ulmus glabra) trees near the town of Sambir, (2)Kamianec’–Podil’s’kyi, which is a broad–leavedforest dominated by oak (Quercus robur) andhornbeam (Carpinus betulus) with cis–medit-erranean species such as Sorbus torminalis, Vi-burnum lanatana and Scutellaria altissima, (3)Slovianohors’k, in an oak (Quercus robur) forestwith 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 (Acerpseudoplatanus), hornbeam (Carpinus betulus)and durmast oak (Quercus petraea), (5) four lo-calities near the town Chernihiv in the northernpart of Ukraine, (6) near the town Kiliia in theOdesa region, where a few beetles have beenobserved 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 becomeextinct from many of these; the beetle has beenfound since 1990 only at 919 of the localities. Outof these 919, at 79 only excrements have beenfound and at 96 only remains from dead beetleshave been found. For these 175 localities we cannot rule out the possibility that the species hasalready become extinct. On the other hand, thereare many unknown localities that have yet to bediscovered. Everywhere in Europe it seems thatthe majority of localities with O. eremita are smalland isolated. For that reason we should expectmany local extinctions in the future, even thoughthe hollow trees that are left will be protected. Thisis especially the case in regions where habitatloss and fragmentation have occurred recently (forinstance in France, Eastern Germany, Slovakia andCzechia); in Sweden, where the main loss of suit-able trees occurred in the 19th century, O. eremitahas already disappeared from some, but not all,of the smaller sites (fig. 2). In some countries(such as Denmark), all localities are small andthe risk for regional extinction is considerable. Inother countries (e.g. France, Sweden, Latvia andAustria) there are also a few larger localities whereO. eremita may also survive in the long term if thesites are properly managed.

O. eremita still occurs in almost all Europeancountries but is absent from the boreal region, theBritish Isles and most of the Iberian peninsula. O.eremita seem to have decreased in all Europeancountries. Relatively high densities of localitiesoccur in Central Europe (northern Italy, Austria,eastern Germany, Czechia and southern Poland),some parts of Northern Europe (south–easternSweden, Latvia) and France. Perhaps there arealso many localities in the Balkans, but searchingefforts have been very low there during the last few

decades. In some regions in north–western Eu-rope, the species has become extinct or may oc-cur at a single locality (Norway, Danish mainland,the Netherlands, Belgium, north–eastern France).Bearing in mind the severe loss of old trees inEurope, it is perhaps surprising that O. eremitahas not become extinct from larger regions. How-ever, the species can survive in small relictpopulations over decades, and even if it is doomedto extinction it will take time before the speciestotally disappears from a region (Ranius, 2000).

O. eremita mainly occurs in habitats that havebeen used by man for a long time. However, thereare also O. eremita localities in forests, such as inSpain, France, southern Italy, the Balkans, Slovakiaand Germany. Many of the man–made habitats aredestroyed due to changes in agriculture. In Swe-den as an example, pasture woodland suffersfrom forest regrowth due to ceased management,while the abandoned pollarding of oaks in Francemakes it difficult to produce suitable new trees forO. eremita. The beetle can also obviously survivein urban areas, but in many cases there are con-flicts with public safety.

Our compilation of data supports the view that O.eremita is useful as an indicator and umbrella spe-cies as everywhere it is confined to hollow trees —a threatened habitat. There are a few observationsof the beetle in stubs, but there is no indication thatO. eremita populations could survive at localitieswith no tree hollows present. Moreover, the pres-ence of O. eremita indicates a high species rich-ness with many threatened species associated withold trees (Ranius, 2002a). The preservation of O.eremita involves three tasks that are of generalimportance for nature conservation in Europe to-day: (1) to preserve those small remnants of natu-ral forest that still exist, (2) to preserve and restorehabitats connected with historic agricultural land-scapes and (3) to preserve any remaining smallpieces of nature in urban areas. Thus, taking themeasures needed to protect O. eremita will alsocontribute to solving many other current problemsin nature conservation in Europe.

Acknowledgements

The following persons kindly provided valuable in-formation on O. eremita: Ainars Auninš (Latvian Fundfor Nature, Riga, Latvia), Pablo Bahillo de la Puebla(Spain), Danilo Baratelli (Varese), Enrico Barbero(Torino), Massimo Bariselli (Bologna), ArvidsBarševskis (Baltic Institute of Coleopterology,Daugavpils, Latvia), Luca Bartolozzi (Firenze), LuigiBeretta (Vicenza), Detlef Bernhard (Leipzig Univ.),Alexandro Biscaccianti (Roma), Luca Bodei(Bedizzole), Marco Bognolo (Trieste), PierluigiBoschin (Rome), Tristão Branco (Porto, Portugal),Pietro Brandmayr (Arcavacata di Rende, Cosenza),Marek Bunalski (Poznań), Franco Callegari (Ra-venna), Achille Casale (Sassari), Oreste Cavallo(Alba), Cornelia Chimisliu, Zbigniew Chrul (Poland),

22 Ranius et al.

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), DusanFarbiak (Protected Landscape Area Stiavnicke vrchy,Banska Stiavnica), Massimo Forti (Milano), FrankFritzlar (Thüringer Landesanstalt für Umwelt undGeologie, Jena), Janis Gailis (Entomological Soci-ety of Latvia, Riga), Robert Gawroński (Bydgoszcz),Roberto Giannatelli (Grugliasco), Giovanni Gobbi(Roma), César González (Spain), Brigitte Grimm(Austria), Jerzy M. Gutowski (Białowieża), JonasHedin (Lund Univ., Sweden), Klaus Hellrigl (Brixen),Nicklas Jansson (The County Administration Boardof Östergötland, Sweden), Tomas Jaszay (Sarisskemuseum, Bardejov), Manfred Kahlen (Innsbruck),Martinš Kalninš (State Nature Inspection, Riga,Latvia), Krzysztof Karwowski (Pieniny National Park),Stanislav Kaluz (Inst. of Zoology, Slovak Academy ofSciences), Bernhard Klausnitzer (Dresden), AloisKofler (Austria), Mieczysław Kosibowicz (Kraków),Anton Kristin (Inst. of Forest Ecology, SAS, Zvolen),Daniel Kubisz (Kraków), Andrea Liberto (Roma),Jörg Lorenz (Naturschutzinstitut AG Dresden), PaoloMaltzeff (Rome), Franco Marozzini (Rome), ArrigoMartinelli (Rovereto), Vladimir Martynov (Donec'k),Bruno Massa (Palermo), Mieczysław Mazur (Kraków),Luigi Melloni (Bagnara di Romagna), Otto Merkl(curator for Coleoptera, Natural History Museum ofHungary), Jakub Michalcewicz (Kraków), VittorinoMonzini (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), LuigiPetruzziello (Remedello), Emanuele Piattella(Rome), Riccardo Pittino (Milano), Roberto Poggi(Genova), Ljiljana Protić (Beograd), Giulia Rasola(Bolzano), Enrico Ratti (Venezia), Franz Ressl (Aus-tria), Antonio Rey (Genova), Joachim Roppel (Aus-tria), Robert Rossa (Kraków), Ivo Rychlik (SlovakEntomological Society, Bratislava), S. K. Ryndevich(Baranovichi, Belarus), Lucio Saltini (Carpi), FabrizioSanti (Bologna), Ulrich Schaffrath (Kassel), PeerSchnitter (Landesamt für Umwelt Sachsen–Anhalt,Halle), Werner Schwienbacher (Auer), LeonardoSenni (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), PierreTauzin (Vanves), Andrzej Trzeciak (Poland), MarcoUliana (Rosara di Codevigo), Dante Vailati (Brescia),Roberto Valdinazzi (Valle San Bartolomeo), MarcoValle (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), CarloZanella (Vicenza), Iuri Zappi (Bologna), MarkoZdešar (Ljubljana), Stefano Ziani (Forlì), WitoldZiebura (Poland), Sławomir Zieliński (Poland),Stefano Zoia (Milano), Ulrich Zöphel (SächsischesLandesamt für Umwelt und Geologie, Dresden).We also thank Daniela Ottaviani (Rome), AlessioDe Biase (Rome), Emiliano Mancini (Rome),Giorgia Coletti (Rome), Emmanuelle Brunet(France) for help with compiling data and mappingand Hervé Brustel for the great exchanges concern-ing saproxylic insects. Ms Silke Heckenroth andMarcos Méndez helped us with translations. Wethank Monika Štambergová (AOPK ČR, leader ofmapping project in Czechia), for help with the dataand all Czecian collectors who sent information toa mapping project.

Individual co–authors were financially supportedby Anne–Frid Lyngstads miljöfond (to ThomasRanius), VEGA, Slovak Grant Agency for Science,grant No 2/3006/23 and 2/2001/22 (to Peter Zach),the Austrian Federal Environmental Agency (toWolfgang Paill).

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Appendix. Localities with O. eremita recorded. In parenthesis, year for the latest record, type offinding (a. Alive, as larva or adult; r. Remains from adult body parts; e. Excrements). If the specimenwas found alive, only "a" is written, and if remains from a dead adult but no living specimens werefound, only "r", independent of whether there were other kinds of findings. Data from central andsouthern 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 últimoregistro 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 unindividuo 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 endos 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 naturalhistory 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 ofHainburg (2001), Herzogenburg (old, undated), Katzelsdorf near Neudörfl (1998), Laxenburg (2000),Mank near Melk (1961), Mistelbach (2002), Neunkirchen (old, undated), Obernberg/Inn (old, un-dated), 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), Alkovennear 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 vicinityof 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 (before1886), 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), Salz-burg–Leopoldskron (old, undated), Salzburg–Maxglan (1931), Salzburg–Mönchsberg (1960), Salz-burg–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 areincorporated, 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 thatgive specific information on O. eremita in Austria. Additional data have been obtained from numer-ous public and private collections.

32 Ranius et al.

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 anda record published by Janssens (1960). Other specimens collected during the last decades are inprivate collections.

Bosnia and Herzegovina

Babin Potok (before 1956), Drvar (1955), Foča (1913), Igman (before 1956), Ivan planina (before1956), Knežinski Palež near Sarajevo (1957), Knježina (1949/a), Laništa, Mostar (1929), PrenjPlanina (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 in1906), Vraca (published in 1906), Pirin Mts (1961), Nessebar, S. of Burgas (1961–63), RilskiMonastir, Rila (1963), Sofia (1966).

Based on literature (Nedelkov, 1906; Nüssler, 1986) and single specimens in private andmuseum collections.

Croatia

Istra: Štalije (1982), Opatija (before 1914), Učka (1928); Primorje: Rijeka (before 1900), Draga (nearRijeka, 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 communi-cation 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–Kopaniny (1990); Jihočččččeský: Blatná (1999), Písek (1977), Libětice (1954), Vodňany (1951), Veselí nad

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–ČeskéVrbné (1996); Vysočččččina: Chotěboř (1998), Lučice (1976), Náměšt' nad Oslavou (1992), Senorady (1938);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(1946); Plzeňňňňňský: Žihle (1961), Plzeň (1999), Kornatice (1991), Horšovský Týn (1991), Diana (1985),Plzeň–Zábělá (1998), Lopata u Št'áhlav (1992); Praha: Lochkov (1956); Stredočččččeský: Bělá pod Bezdězem(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), Klášterecnad 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 privatecollectors, records published in regional literature and made complete with records mentioned byKollar (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), HalstedklosterDyrehave (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 at28 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.

Appendix. (Cont.)

34 Ranius et al.

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 ofBarville (2000/r); Mayenne department: hedge network of Pré en Pail (2001/r), hedge network ofEvron (2001/r), hedge network of Torcé Vivier en Charnie (2001/r); Sarthe department: hedgenetwork 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: hedgenetwork 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 ofHerrenwald (year?); La Bruche (Strasbourg; 2003/a); Indre department: hedge network of SaintBenoît 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 Cannetde 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 etal., 1999; Landemaine, 2003; Tauzin, 2000; 2002), surveys conducted by H. Brustel in 2002 in theAveyron department, the Entomological Society of Limousin (Corrèze department), and Office de GénieEcologique by J. F. Asmodé, P. Orabi and V. Vignon (Indre–et–Loire, Mayenne, Orne, Sarthe depart-ments) 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), betweenDresden 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 (Dahlen2003/a), Mutzschener Wasser (Mutzschen 2002/a, Gastewitz 2002/r, Wiederoda, 2002/a), Muldefloodplain 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 PlötzkauerAuenwald, 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, HallischerAnger, 1934, around Naumburg, 1944), Marke (1955), Dessau (several years, Luisium 1995/a, Kornhaus

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 nearZeitz (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 (KleinerGerstenbach, 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/BadKösen (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 (NSGHeiligensee, 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 nearTeterow (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 nearTeterow (2001/a), Müritzer See, Waren near Blücherhof (1994/l), Kittendorf (2001/a), NeuenkirchenerWald 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 Holznear Demmin (1985/a), Mueß near Schwerin (Reppin, 1980/a), Brantensee (1998/r), Bennin nearHagenow (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–Seenear 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).

Appendix. (Cont.)

36 Ranius et al.

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 locali-ties 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 an1989 (Schaffrath, 2003b).Saarland: at two localities since 1990 (Schaffrath, 2003b).Hessen (Hesse): many localities before 1980, and also at many localities since 1990 especially inthe 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), MountOlympos (1994), Mount Ossa (1994), Mount Ossa, NE slope, near Kokkinonero (1979), MountTaygetos (before 1886), Pessani, near Alexandhroupolis (1994), Vrondou (1996), Nomos Larisis(Spilia, 2003/a, Omolion, 1991/a, Stomion, 2003/a), Nomos Ioanninon (Vrosina, 2003/a), NomosPierias (Katerini, 1991/a).

Based on published records (Oertzen, 1886; Mikšić, 1959; Tauzin, 1994b; Sparacio, 2001) andunpublished 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 alsowent 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 ofthem were unlabelled or only from the neighbourhood.

Italy

Osmoderma eremitaValle D’Aosta: Aosta (Aosta, year?/a); Piemonte: Torino (1968/a, Baudenasca, loc. Paglieri nearPinerolo, 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,

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, ValSugana, 1930/a, Val d’Adige Inferiore, 1927/a, Vela di Trento, 1960/a, Pinzolo, 1940/a, Vigo Anaunianear 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 Nogherenear Aquilinia, 1921/a, Cattinara, year?/a), Udine (Pontebba, 1895/a, Parco delle Prealpi Giulie nearResia, 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 SanBenedetto, above San Benedetto in Alpe, 1990/a); Toscana: Firenze (1972/a, Firenze, Parco LeCascine, 1954/a, Firenze, Badia Della Valle, 1985/a, Panzano, 1925/a, Marradi, 1971/a), Prato (LaBadia, 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, betweenPereto 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, LaCatusa, 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 gatheredinformation on 500 specimens collected during the last 150 years.

Appendix. (Cont.)

38 Ranius et al.

Latvia

Aizkraukles raj.: Daudzese env., Baibas house 1 km W (2002/e); Erberge, parks (2002/a); Bauskasraj.: 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); Eglainesmeži 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), Pededzeslejtece 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), Slatesvm. (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), PapeNPA, Pape (2001/a), Priekules vm., kv 397, nog. 8 (2001/e); Limbažžžžžu raj.: Augstroze NPA (2001/a);Birinu pils parks (2002/a), Burlaku plavas NPA (2002/e), Salacas ieleja NPA (2002/a), Svetupesozolu 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); Rigacity: 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 Baltezerasalas 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 ielejaNPA (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, kv90, nog. 32, 2001/e), Usma (Usmas tautas skola, 2001/a).

Based on literature, insect collections (museums and private) and field surveys. In the collec-tions there were about 55 specimens collected during the last 155 years. Field surveys have mostlybeen conducted during the last four years.

Lithuania

Ignalina: Didžiagirio forest (2000); Kaišššššiadoriai: Kruonis (1988); Strevininkå forest (2002); Kaunas:Gervenupis (1997); Kaunas (2001); Kleboniškis (1976); Lapes (1963); Kedainiai: (1963); Lazdijai:Meteliai (1980); Marijampole (1963); Panevežžžžžys: Gringaliu forest (1987); Pasvalys: Joniškelis (1983);Plunge; Šilale; Telšššššiai; Trakai: (1978).

Based on specimes in Kaunas T. Ivanauskas Zoological Museum at The Lithuanian Universityof 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:

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 faunisticliterature was checked for additional data (Huijbregts, 2003). In total, 23 O. eremita specimens from14 localities were collected between 1870 and 1946.

Norway

Akershus: Asker (19th century/a); Buskerud: Drammen (before 1875/a); Østfold: Rauer nearFredrikstad (1997/r).

Based on literature, summarized in Hanssen (1999).

Poland

Pobrzeżżżżże Bałłłłłtyku (Baltic Coast): Woliński National Park (before 1951), Puck (1979/a), Wejherowo(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 (PomeraniaLake 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 riverPasłęka (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, Krajkowonear 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 (before1998/r), Zosin near Ułęż (before 1975/a); Podlasie (Podlasie): Sitniki near Siemiatycze (about 1980/a),Liszna near Sławatycze (1995/a); Puszcza Białłłłłowieska (Białłłłłowieżżżżża Primeval Forest): Świnorojenear Narewka (1988/a), Białowieski National Park (1987/a); Dolny ŚŚŚŚŚląąąąąsk (Lower Silesia): Wrocław(before 1929), Brzeg (1982/a) Ziemiełowice near Namysłów (19th century), Pokój (1992/a); WzgórzaTrzebnickie (Trzebnickie Hills): Topolno (19th century), Trzebnica (1975/a); Górny ŚŚŚŚŚląąąąąsk (UpperSilesia): 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 nearChrzanów (1974/a); Wyżżżżżyna Krakowsko–Wieluńńńńńska (Kraków–Wieluńńńńń Upland): Złoty Potok (about1976/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), SkałaKmity near Szczyglice (1970/a), Piekary near Liszki (1997/a), Skawina (1925/a), Michałowice nearKraków (1937/a), Kraków (1928/a), Kraków: Bielany (1968/a), Las Wolski (1952/a), Salwator (1994/a),Zwierzyniec (1917/a), Płaszów (before 1950); Wyżżżżżyna Małłłłłopolska (Małłłłłopolska Upland): LasŁagiewnicki reserve near Łódź–Smolarnia (1996/a), Subina near Koluszki (1984/a), Spała nearInowłódz (1949/a), Zagnańsk (1991/a), Jędrzejów (1990/a), Książ Wielki (1985/a), Mianocice nearMiechów (1872), Miechów forest district (before 1961), Kocmyrzów near Luborzyca 1953/a), NoweBrzesko (1985/a), Zięblice near Kazimierza Wielka (before 1975/a), Czyżowice near KazimierzaWielka (1999/a), Bronowice near Puławy (before 1950/a), Puławy (before 1915); Góry ŚŚŚŚŚwięęęęętokrzyskie(ŚŚŚŚŚwięęęęętokrzyskie Mountains): Świętokrzyski National Park (before 1958); Wyżżżżżyna Lubelska (LublinUpland): Parchatka near Puławy (before 1950/a); Roztocze (Roztocze): Zwierzyniec (1908/a),Kosobudy (1943/a), Ulów (published 1913/a), Hrebenne (1988/r); Nizina Sandomierska (SandomierzLowland): Kraków (Rakowice, 1912/a), Grzegórzki (1937/a), Puszcza Niepołomicka (near Koło re-serve, 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), KotowaWola near Zaleszany (1879), Rozwadów near Stalowa Wola (before 1950), Rzeszów and vicinity(before 1869), Jarosław (1973/a), Przemyśl (1985/a); Sudety Zachodnie (West Sudetes): JeleniaGóra–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),

Appendix. (Cont.)

40 Ranius et al.

Kalwaria Zebrzydow. (1944/a), Kraków (Rżąka, 1998/a), Sieraków near Dobczyce (1909/a), Fałkowicenear 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 nearStary 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 ofZoology PAS, Warszawa; Museum of Natural History, Institute of Systematics and Evolution ofAnimals PAS, Kraków; Upper Silesian Museum, Bytom; Department of Forest Entomology, Agricul-tural University, Poznań) and private collections.

Rumania

Brașșșșșov: 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), CheileSohodol (1999), Tismana (1965); Hunedoara: Haţeg (before 1912), Deva (before 1912), Brad(before 1912); Mehedinţţţţţi: Olănești (1954), Schitu Topolniţei (1992); Mureșșșșș: Sighișoara (before 1912),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 unpub-lished records.

Russia

Kaliningrad region: Kaliningrad (1992/a), Pravdinskyi district (Podlipovo village, 1994/a),Chernjakhovsk (1997), Polessk district (1985–1995/a); Leningrad region: Luga district (PloskoyeManor, 1916/a, Preobrazhenskaya railway station, 8 km down the Luga River, 1915/a, Tolmachyovorailway 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 villagevicinities, 1993/a), Serpukhov district (Prioksko–Terrasny Reserve, 1992–93/a), Ozyory district (nearBelyye 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 theZhizdra 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 fromKoltsovo, 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 (SaralovskoyeForestry, 1995/a); Nizhny Novgorod region: Vetluga district (Kaksha River, 1950–80/a); Ulyanovskregion: 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,); Saratovregion: 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

Appendix. (Cont.)


Appendix. (Cont.)

(1988/a); Voronezh region: Ostrogozhsk district (Shubnoe village vicinities, 1963/a), Borisoglebskand Tellerman forestry, 1970–1997/a); Belgorod region: reserve "Belorechiye", 1985–2002/a, vicinityof 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 vicini-ties, 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 Urgulvicinities,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 SurskyMaydan village, 1980–2000/a, 7 km SE Ivankovo–Lenino village, 1980–2000/a, Mezhdurechye vil-lage, 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 Posadcity (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 (Yuryevkavillage 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, lowerStorozhilsk (2000), Gornomariysky district (Novaya Sloboda village vicinities, 1985–2002/a), Transvolga,2 km south from Kokshamary (1985–2002); Udmurtiya republic: Vavozh district (Gulyayevskoyevillage, 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 Postolkaand 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 nearthe 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: Maykopregion (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 datafrom specimens in museums (especially Zoological Museum of Moscow Lomonosov state Univer-sity, 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) andDedukhin (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), DevinskaKobyla (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

42 Ranius et al.

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: RimavskaSobota (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 nineSlovakian 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 theInstitute 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 severalentomologists.

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 delBidasoa; 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), Lyckebyekbacke (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 kvarnsarea (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


(1997/a), Blekhem (1997/e), Dynestad (1998/a), Garpedansberget, Gamleby (1998), Vinäs, SEfrom 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, SVHäckeberga (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), BiskopsArnö (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 andKärrbogärde (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: Trystorpsekäng (1998/r); Östergötland: Boxholm: Boxholms säteri 2000/e), Lagnebrunna (1997/r), nearSvartån–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), Stormtornaand 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.

Appendix. (Cont.)

44 Ranius et al.

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’kregion: 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 commu-nications.

Appendix. (Cont.)



Fleishman, E., 2005. Identification and conservation application of signal, noise, and taxonomic effects indiversity patterns. Animal Biodiversity and Conservation, 28.1: 45–58.

AbstractIdentification 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 whileelucidating how dynamic measures of diversity (species richness and turnover) affect inferences forconservation planning and adaptive management. Nested subsets analyses suggested that processesinfluencing predictability of assemblage composition differ among taxonomic groups, and the relativeimportance of those processes may vary spatially within a taxonomic group. There may be a time lagbetween deterministic environmental changes and a detectable faunal response, even for taxonomic groupsthat are known to be sensitive to changes in climate and land cover. Measures of beta diversity weresensitive to correlations between sampling resolution and local environmental heterogeneity. Temporal andspatial variation in species composition indicated that spatially extensive sampling is more effective fordrawing inferences about biodiversity responses to environmental change than intensive sampling atrelatively few, smaller sites.

Key words: Adaptive management, Beta diversity, Great Basin, Monitoring, Nestedness, Species richness.

ResumenIdentificación y aplicación en la conservación de los efectos señal, ruido y taxonómicos en patrones dediversidad.— Los estudios de mariposas y aves en el Great Basin han identificado patrones biogeográficosque permiten evaluar cómo las medidas dinámicas de biodiversidad (riqueza específica y renovación deespecies) pueden afectar la planificación y la gestión adaptativa de la conservación. El análisis desubgrupos anidados sugiere que los procesos que influyen en la predicibilidad de la composición de losgrupos difieren entre los distintos grupos taxonómicos. Asimismo la importancia relativa de estos procesospuede variar espacialmente dentro de un grupo taxonómico. Puede haber un retraso en el tiempo entre loscambios ambientales deterministas y una respuesta faunística detectable, incluso para los grupos taxonómicosque se sabe que son sensibles a los cambios del clima y de la cubierta del suelo. Las medidas de diversidadbeta eran sensibles a las correlaciones entre la resolución del muestreo y la heterogeneidad ambientallocal. La variación espacial y temporal en la composición de especies indicó que el muestreo extensivo enel espacio es más efectivo, para obtener inferencias sobre cómo responde la biodiversidad a cambiosambientales, 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: [email protected]

Identification and conservationapplication of signal, noise, andtaxonomic effects in diversity patternsE. Fleishman


46 Fleishman

Introduction

Conservation planning is motivated and directed byevidence that native species, assemblages, andecological functions are responding to deterministicenvironmental change (Scott et al., 1987, 1993;Stein et al., 2000). Human land uses such asurbanization and agriculture frequently drive theenvironmental changes of greatest concern to con-servation biologists (Czech et al., 2000; Lockwood& McKinney, 2001). In order to implement adaptivemanagement, we also must evaluate the biologicaleffects of landscape reconstruction, restoration, anddirected efforts to conserve species and ecosys-tems (Meretsky et al., 2000; Lake, 2001). Mean-while, in the decision–making arena, credible dataon ecological responses to climate change haveproven essential for influencing environmental policy(Easterling et al., 2000; Schär et al., 2004).

Survey and monitoring data sometimes revealsubstantial changes in measures of biodiversityand ecosystem function across space or time, butthose changes may reflect dynamic processes ratherthan observational or experimental treatments perse. Diversity metrics (including species richness,abundance, evenness, and so forth) are infamouslydependent on the spatial and temporal scale ofmeasurement and on life history. For example, thesize of each sampling unit (sampling resolution),the configuration of sampling units across the land-scape, and the spatial extent of the area from whichsamples are drawn affect inferences regardingnumber of species (henceforth, species richness)and identity of species (henceforth, species compo-sition) (Noss, 1983; Wilson & Shmida, 1984; Conroy& Noon, 1996). Geographic coordinates and con-text also matter. For instance, species richnessoften increases along ecotones (Risser, 1995), atintermediate levels of disturbance (Petraitis et al.,1989), and at intermediate points along abioticenvironmental gradients (Fleishman et al., 1998;Colwell & Lees, 2000). Scale dependencies in di-versity patterns bear on a wide range of conserva-tion applications, from identification of mechanismsthat generate and maintain species richness toexploration of relationships between species diver-sity and ecological function (Waide et al., 1999;Willis & Whittaker, 2002).

Scaling issues related to species richness andcomposition also have a taxonomic component.Species perceive and react to their environment asa function of life–history characteristics includingresource requirements, mobility, and body size(Addicott et al., 1987; Kotliar & Wiens, 1990; MacNally, 2005). In theory, therefore, the spatial andtemporal resolution and extent of sampling shouldbe dictated by the ecology of the taxa under inves-tigation. In reality, however, sampling designs fre-quently reflect logistic constraints. The resolutionand extent of sampling for multi–taxonomic studiescommonly is established using a single surveydesign bounded by human conventions, such asadministrative boundaries or land–use types. But a

uniform sampling framework is unlikely to be mean-ingful for understanding diversity patterns in alltaxonomic groups of interest because it confoundsthe components of diversity. For some species agiven sampling resolution will estimate only thealpha component of richness (the mean number ofspecies within a local community) while for otherspecies it will estimate both the alpha and beta(between–habitat diversity) components.

Nonetheless, empirical ecological and biogeo-graphical research can be designed to quantifyeffects of scale and life history in addition to effectsof environmental change. For the past decade, mycolleagues and I have quantified diversity patternsin assemblages of butterflies and birds in the GreatBasin and Mojave Desert in order to elucidatedeterministic and stochastic influences on patternsof species richness and composition, dependenceof those patterns on temporal and spatial scale andlife history, and practical sampling approaches mostlikely to provide valid inferences about ecologicalresponses to an array of environmental changes.Butterflies and birds also are well–known ecologi-cally, relatively easy to study and monitor, andpopular with the general public. In addition, variousmeasures of the species diversity or occurrence ofbutterflies and birds frequently have been proposedas a surrogate measure of the status of each other,of other taxonomic groups, and of environmentalvariables (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 forexamining issues of scale and sampling associ-ated with many types of diversity patterns. Desertecosystems are thought to be highly responsiveto major environmental changes including shiftsin 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 Mojaveis managed by federal and state resource agen-cies for sustained multiple uses ranging fromconservation to recreation to production of re-newable and non–renewable commodities. In thispaper, I present a synopsis of several approacheswe have taken to identify biogeographic patternsand trends in the fauna of the Great Basin whileelucidating how dynamic measures of diversityaffect interpretation of ecological data in the con-text of conservation and management. First, Idescribe our use of nested subsets analyses todetermine whether the composition of local as-semblages is predictable and to identify abioticand biotic factors that may be associated with theorder in which species are likely to appear anddisappear. Second, I summarize how we haveaddressed the probability of detecting faunal re-sponses to deterministic environmental changesover time. Third, I review our work on the effectsof sampling resolution and proximity of samplinglocations on inferences about species richnessand turnover.


Methods

Our data collection incorporates well–established tech-niques that reliably detect species presence and per-mit assessment of distributional trends across spaceand time. Because these methods have been de-scribed in considerable detail in previous publications,along with discussion of sampling adequacy (e.g.,Fleishman et al., 1998; Mac Nally et al., 2004), Iprovide just a brief overview here.

Data for our analyses in the Great Basin werecollected from 1996–2003 in three adjacent moun-tain ranges in central Nevada, the Shoshone Moun-tains, Toiyabe Range, and Toquima Range (Landerand Nye counties) (fig. 1). These mountain rangeshave similar regional climate, biogeographic pastand ancestral biota, and human land–use histo-

ries (Grayson, 1993). Inventories for breeding birdswere conducted in five canyons in the ShoshoneMountains, five canyons in the Toiyabe Range,and six canyons in the Toquima Range. Invento-ries for resident butterflies were conducted in eightcanyons in the Shoshone Mountains, 15 canyonsin the Toiyabe Range, and 11 canyons in theToquima Range. Distances between canyons inthese three mountain ranges, and particularly be-tween the canyons we sampled, usually were muchgreater than the territory or home range sizes ofresident butterflies (Fleishman et al., 1997) andbirds during the breeding season (Ryser, 1985;Dobkin & Wilcox, 1986). We have collected dataon both species occurrence (presence / absence)and abundance; only the occurrence data are pre-sented in this paper.

Fig. 1. Location of (west to east) the Shoshone Mountains, Toiyabe Range, and Toquima Range in theGreat Basin (black rectangle, see inset) and inventory canyons in the three mountain ranges (thickblack lines). Two pairs of canyons in the Toiyabe Range and three pairs of canyons in the ToquimaRange connect at the crest of the range.

Fig. 1. Localización (de oeste a este) de los montes Shoshone, de la cordillera Toiyabe, y de lacordillera Toquima en el Great Basin (rectángulo negro, ver el recuadro) y la relación de cañones delas tres cordilleras montañosas (lineas negras finas). Dos pares de cañones de la cordillera Toiyabe ytres pares de cañones de la cordillera Toquima conectan en la cima de la cordillera.

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48 Fleishman

We divided canyons into multiple contiguoussites (segments) from base to crest. Each site was100–150 m wide and long enough to span a 100–mchange in elevation (Fleishman et al., 1998, 2001b).Mean site length was 1.5 km; more than two–thirdsof the sites were longer than 1 km. Inventories forbutterflies were conducted from 1995–2003 in39 sites in the Shoshone Mountains, 102 in theToiyabe Range, and 54 in the Toquima Range.Inventories for birds were conducted from 2001–2003 in 24 sites in the Shoshone Mountains, 31 inthe Toiyabe Range, and 28 in the Toquima Range.

Our sampling locations covered an elevationalrange of 1872–3272 m and areas from 1.5 ha to44.4 ha. Using walking transects, a standard, de-pendable method for temperate regions (PollardYates, 1993; Harding et al., 1995), we recorded 65resident species of butterflies from our study sites.Birds were sampled using point counts (three perseason) that spanned the range of dominant veg-etation types (Bibby et al., 2000; Siegel et al., 2001;Poulson, 2002). Point counts have been shown tobe an effective method of sampling birds in riparianareas in the Great Basin (Dobkin & Rich, 1998;Betrus, 2002). We recorded 79 species of breedingbirds from our study sites. Lists of species areavailable on request.

We partitioned the landscape into three hierar-chical spatial levels: sites within canyons, can-yons, and mountain ranges. Our finest samplingresolution (smallest sampling grain) was the site.A given site was located within a particular canyonwithin one of the three mountain ranges. To pro-duce species lists at the whole canyon level, ourintermediate sampling resolution or grain, we com-piled species lists for all contiguous sites within agiven canyon. On average, the area of a canyonwas six times larger than the area of a site. Toproduce species lists at the mountain range level,our coarsest sampling resolution or largest grain,we compiled species lists for all canyons that werevisited in a given mountain range.

Predictability of assemblage composition

Nestedness analyses have greatly expanded ourcapacity to understand biotic patterns across net-works of terrestrial or aquatic "islands" of resourcesor habitat (Wright et al., 1998). A nested biota isone in which the species present in relativelydepauperate locations are subsets of the speciespresent in locations that are richer in species(Patterson & Atmar, 1986). Nestedness is a prop-erty of assemblages or communities, not of indi-vidual species (Wright et al., 1998), and has beeninterpreted as a measure of biogeographic order inthe distribution of species (Atmar & Patterson, 1993).Numerous studies have demonstrated that nesteddistributional patterns are common across taxo-nomic groups and ecosystems.

Biotas rarely are perfectly nested. Nestednessanalyses often cannot identify critical thresholds

of environmental variables with respect to systemstate or reliably predict the order of species extir-pation or colonization. Nonetheless, nestednessanalyses are useful as conservation tools becausethey quantify a widespread ecological pattern and—more importantly— highlight processes, includ-ing nonrandom extinction, differential colonization,and nestedness of critical resources, that affectnot only species richness but also species compo-sition (Patterson & Atmar, 1986; Simberloff & Mar-tin, 1991; Cook & Quinn, 1995; Lomolino, 1996;Baber et al., 2004). Although even strong correla-tions between mechanisms or variables and distri-butional patterns cannot be interpreted as cause–and–effect relationships, those correlations can,at minimum, help refine hypotheses that can betested with further observations or manipulativeexperiments (Cook & Quinn, 1995; Kadmon, 1995;Fleishman & Mac Nally, 2002). This aspect ofnestedness analysis is especially pertinent to con-servation planning because it may help to eluci-date whether certain land uses may be responsi-ble for local extinction or colonization events(Hecnar & M’Closkey, 1997; Fleishman & Murphy,1999; Jonsson & Jonsell, 1999).

Presence/absence matrices for nestednessanalysis typically are assembled by listing locationsas rows in order of decreasing species richness andspecies as columns in order of decreasing ubiquity.This ordering provides a description of assemblagecomposition but contributes little toward understand-ing agents that drive assemblage structure and helpus predict species composition across space andtime. If one wishes to test whether a particular envi-ronmental variable may be related to a nested distri-butional pattern, then rows instead may be orderedwith respect to that variable (Fleishman & Mac Nally,2002). For example, listing rows in order of decreas-ing area quantifies the degree to which faunas arenested by area. If an assemblage is nested withrespect to a selected environmental variable —or if anassemblage is more nested with respect to one envi-ronmental variable than another— it suggests that thevariable in question has a non–trivial influence onspecies occurrence in the assemblage.

To test whether assemblages were nested withrespect to alternative ordering variables, we com-puted the relative nestedness index C (Wright &Reeves, 1992) with the program NESTCALC(Wright et al., 1990). We estimated statisticalsignificance using Cochran’s Q statistic (Wright &Reeves, 1992). Values of C vary between 0 and1.0, approaching 1.0 for perfectly nested matrices.A key advantage of this metric is that it allows forstatistical comparison of degree of nestednessamong matrices or data sets. Moreover, C is nothighly sensitive to matrix size (Wright & Reeves,1992; Bird & Boecklen, 1998), although nestednessmay be more variable when matrices are relativelysmall (Wright et al., 1998). We used Z scores(standard–Normal variates) to test whether signifi-cant differences existed in relative nestednessamong matrices (Wright & Reeves, 1992).


Initially, we tested whether nestedness of butter-flies and birds in the Shoshone Mountains, ToiyabeRange, and Toquima Range appeared to be influ-enced by the same environmental variables andwhether those patterns were consistent in space.Although the distributional pattern of both taxo-nomic groups was strongly nested, the environ-mental variables most closely associated with thenested pattern differed between butterflies andbirds (Fleishman et al., 2002a). For example, to-pography (elevation and local topographic hetero-geneity) may help generate nested distributions ofbutterflies (Fleishman & Mac Nally, 2002). Variedtopography tends to create a full gradient ofmicroclimatic conditions, which in turn promoteshigh species richness of plants that serve as re-sources for larval and adult butterflies. Variedtopography also provide numerous locations forseeking mates (Scott, 1975, 1986) and shelterfrom extreme weather events. However, topogra-phy did not appear to be a reliable correlate ofassemblage structure of birds. This result mayreflect differences in the specific resource require-ments of birds and butterflies in the montaneGreat Basin. For instance, species richness ofbirds frequently corresponds to vegetation struc-ture, whereas species richness of butterflies maybe more closely associated with vegetation com-position (but see Rotenberry, 1985; Mac Nally,1990). Comparative resource requirements of but-terflies and birds in this landscape are addressedin greater detail in the section on beta diversity.

Contrary to widespread biogeographic assump-tions (Doak & Mills, 1994; Boecklen, 1997), theassociation between area and nestedness of bothbutterflies and birds was relatively slight. If area ispositively correlated with species richness and abiota is perfectly nested, then species richnessshould be greater in an extensive, contiguous sitethan in a collection of smaller sites. Virtually allreal biotas have presences and absences thatdeviate from perfect nestedness, however, andarea may or may not be an important correlate ofspecies richness of a nested system (Brown, 1978;Doak & Mills, 1994; Kadmon, 1995; Rosenzweig,1995; Ricklefs & Lovette, 1999). In an region asclimatically erratic and topographically heteroge-neous as the Great Basin, critical resources forboth butterflies and birds may not be stronglycorrelated with area.

Also contrary to fundamental biogeographic as-sumptions, we found limited evidence thatnestedness of either group was affected by selec-tive dispersal (Fleishman et al., 2002a; see alsoBird & Boecklen, 1998). If colonization tends todecrease nestedness (i.e., counter the effects ofselective extinction), then less vagile taxonomicgroups should be more nested than comparativelyvagile groups. But if colonization tends to generatenestedness (Loo et al., 2002), then the more vagiletaxonomic groups should be more nested. Resultsof the relatively few previous comparisons havebeen mixed (Cook & Quinn, 1995; Wright et al.,1998). There are several potential explanations why

Table 1. Relative nestedness of butterflies. Values are one–tailed Z–scores for matrices ordered bydifferent criteria: area and topographic heterogeneity (topo). Values represent the relative nestednessof the row versus the column; positive values indicate higher nestedness and negative valuesindicate lower nestedness. For example, the Shoshone Mountains matrix ordered by area wassignificantly 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 colapara matrices ordenadas con distintos criterios: área y heterogeneidad topográfica (topo). Los valoresrepresentan el anidamiento relativo de filas respecto a columnas; valores positivos indican un mayoranidamiento y los negativos, menor anidamiento. Por ejemplo la matriz de los montes Shoshoneordenada por áreas fue significativamente menos anidada que la matriz de la Cordillera Toiyabeordenada por áreas: SH. Montañas Shoshone; TY. Cordillera Toiyabe; TQ. Cordillera Toquima;* P [ 0,05; ** P [ 0,01; *** P [ 0,001.

SH area TY area TQ area SH topo TY topo TQ topo

SH area –4.68*** 3.27*** 1.31

TY area 4.68*** 9.12*** 9.03***

TQ area –3.27*** –9.12*** –6.67***

SH topo 1.31 3.89*** –1.51

TY topo –9.03*** –3.89*** –6.12***

TQ topo 6.67*** 1.51 6.12***

50 Fleishman

correlations between nestedness and dispersal abilitywere weak. One possibility is that the spatial resolu-tion of our bird analyses was too small. Limiteddispersal of birds between study sites would dilute theeffect of differential colonization in generatingnestedness in our analyses. Analyses at a largerspatial resolution (full canyons rather than sites),however, produced virtually identical results (Fleishmanet al., 2002a). Another possibility is that most re-sources used by butterflies and birds are present inthe majority of the locations that we inventoried, atleast during their peak periods of activity.

For butterflies (but not for birds), the rank orderof mountain ranges with respect to nestednesswas sensitive to which environmental variable wasused to order the matrices (Fleishman et al., 2002a)(table 1). Order of species occurrence in theShoshone Mountains and Toquima Range wasmore closely associated with topography than witharea per se, whereas nestedness of butterflies inthe Toiyabe Range was better explained by areathan as a function of topography. Ecologically, thissuggests that the influence of area and topogra-phy on species composition of butterflies variesamong mountain ranges. The importance of localmicroclimatic conditions may increase as the avail-ability of water decreases and vegetational re-sources become less widespread and abundant.

We also tested whether distribution patterns ofbutterfly and bird assemblages appeared to besensitive to human use of riparian areas, a domi-nant anthropogenic stressor in the Great Basin(Kauffman & Krueger, 1984; Armour et al., 1991;Dobkin & Rich, 1998). Livestock grazing, recrea-tion, and other activities that reduce water avail-ability and degrade riparian vegetation had littledetectable effect on nestedness of butterflies andbirds (Fleishman et al., 2002a). At least threeexplanations seem plausible (Fleishman & Murphy,1999). First, human modification of riparian areasmay not be sufficiently severe to cause localextirpations. Second, species with high vulnerabil-ity to changes in the structure and composition ofriparian vegetation may already have disappeared.Third, the magnitude of riparian disturbance maynot be arranged in a predictable (nested) manneracross the region (Hecnar & M’Closkey, 1997).

Few studies of nestedness explicitly have com-pared data on multiple taxonomic groups at thesame locations. Our results suggest that the proc-esses influencing even such prevalent assemblage–level distribution patterns as nestedness vary amongtaxonomic groups. We also found that the relativeimportance of selected processes can vary spatially,both within and among taxonomic groups. Theseconclusions serve as a reminder that taxonomicgroups are not interchangeable for conservation plan-ning, for monitoring the biological effects of knownenvironmental changes, or for assessing the relativeinfluence of natural and anthropogenic disturbanceson native species (Niemi et al., 1997; Simberloff,1998; Andelman & Fagan, 2000; Fleishman et al.,2001a; Rubinoff, 2001).

Signal and noise in logitudinal measuresof biodiversity

Contemporary climate change, invasion of non–native species, and biotic homogenization are mo-tivating efforts to understand the resilience of eco-logical systems (Easterling et al., 2000; Olden &Poff, 2003). Detection of faunal responses to knownenvironmental changes on the order of years todecades typically is based on longitudinal fieldsurveys in which selected taxonomic groups aremonitored across large areas; data on temporaltrends are used to guide and adjust land manage-ment. Because time and money for biological sur-veys and monitoring inevitably are limited, it isimportant to examine whether short–term meas-ures or “snapshots” of species richness and occur-rence accurately reflect longer–term patterns(Hanski, 1999; Moilanen, 2000).

We used up to six years of survey data from twomountain ranges, the Toquima Range and ShoshoneMountains, to examine whether annual variation inbutterfly assemblages over consecutive years reflectedan ecologically meaningful trend as opposed tostochastic system dynamics (Fleishman & Mac Nally,2003). In essence, we aimed to document the appar-ent signal–to–noise ratio in these assemblages overtime. Because our study area did not encompassspecies’ full geographic ranges, we did not attempt todetermine whether the ranges of individual specieshad expanded or contracted (e.g., Parmesan et al.,1999; Thomas et al., 2001). Instead, we focused onamong–site and among–year variation in speciesrichness and species composition, two measures thatlikely will remain the focus of much biological moni-toring on public and private land.

We calculated similarity of species compositionusing the Jaccard index, CJ = j / (a + b – j), where jis the number of species found in all sites and a andb are the number of species in sites A and B,respectively. CJ approaches 1.0 when species com-position is identical between sites and 0.0 when twosites have no species in common (Magurran, 1988).A "time lag" refers to the number of years thatelapsed between inventories. We calculated similar-ity of species composition for time lags of one to sixyears in the Toquima Range and of one or two yearsin the Shoshone Mountains. For a more detaileddescription of methods and analyses, see Fleishman& Mac Nally (2003).

Mean similarity of species composition of butter-flies (i.e., the mean of the site–level values for eachmountain range) varied little as a function of timelag (fig. 2). In the Toquima Range, for example,mean similarity of species composition varied byonly 0.06 (range 0.43 to 0.49) among time lags ofone to six years. Much less of the difference inspecies composition of butterflies was attributableto turnover of species composition within sites overtime than to spatial differences among sites. Thispattern was illustrated most clearly in the ShoshoneMountains, where 3% of the difference in speciescomposition was attributable to turnover of species


composition within sites whereas 74% was attribut-able to spatial differences among sites.

Our results demonstrate that extraction of biotic"signals" from the "noise" of background variation inarid ecosystems is complicated by the severity andunpredictability of weather patterns and various en-vironmental disturbances (Houghton et al., 1975;Rood et al., 2003). Whether measurements ofbiodiversity at two or more points in time are likely toreflect a bona fide temporal trend as opposed tostochasticity largely depends on two related factors:the extent of deterministic environmental changeand the degree of variability characteristic of thebiotic assemblage. One potential explanation for thelack of a detectable temporal trend in our data onspecies composition and species richness of butter-flies (despite considerable variability, especially inspecies composition, between any two given years,Fleishman et al., 2003a) is that during the relativelyshort duration of our study, there were few if anyecologically significant changes in climate or landcover. For example, in five of the six years of ourstudy, annual precipitation was 20% to 60% belowthe mean for the past century. However, precipitationfrom year to year was erratic. For instance, precipi-tation in 2000 was nearly double that in 1999,despite the fact that both years were relatively dry.

Further, although information on species rich-ness and species composition are among the mostpractical data to collect in managed landscapes,these measures may not be highly sensitive toenvironmental changes over years to decades ascompared with demographic parameters like abun-dance and reproduction (Parmesan et al., 1999;Thomas et al., 2001). Population–level measures,however, may be even more prone to randomfluctuations than assemblage–level variables.

By 2100, substantial environmental changes inthe Great Basin are anticipated, ranging fromanthropogenic climate change to modified distur-bance regimes to expansion of non–native inva-sive species (Chambers & Miller, 2004). But de-tection of faunal responses to such changes islikely to be complicated by high background lev-els of local turnover in species composition.Moreover, biological responses to environmentalchange may depend in part on the speed at whichthose changes occur (Grayson, 2000) and whethervariance in environmental conditions also in-creases (McLaughlin et al., 2002). Our work em-phasizes that at minimum, there may be a timelag between deterministic changes in climate orland cover and a detectable faunal response thatcan be used to guide management.

Fig. 2. Mean similarity of species composition of butterflies in the Toquima Range (a) and ShoshoneMountains (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 losmontes Shoshone (b) entre periodos de tiempo de uno a seis años. Las barras de error indican loserrores estándard.

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Response of beta diversity to spatial scale

Most work on scaling issues associated with di-versity patterns has concentrated on species rich-ness. In part because counting species is logisti-cally more feasible than collecting detailed demo-graphic data, species richness has been used asa variable to help prioritize conservation efforts(Scott et al., 1987; Myers et al., 2000) and tomeasure biological responses to natural distur-bance processes, human land use, and alterna-tive management actions at numerous spatialextents (Chapin et al., 2000). Beta diversity (be-tween–habitat diversity), which increases as afunction of turnover in species composition amongcommunities, most often has been considered interms of its contribution to species richness of aheterogeneous landscape (MacArthur, 1966;Whittaker, 1977; Lande, 1996). For example, thetechnique of additive partitioning uses a hierar-chical model of landscape organization (Allen &Starr, 1982) to represent species richness at eachnested level of a landscape as the sum of alphadiversity (the mean number of species within alocal community) and beta diversity at the nextlower level (Lande, 1996; Wagner et al., 2000;Gering et al., 2003).

After discovering that turnover of species com-position within sites over time accounted for muchless of the difference in species composition ofbutterflies in the Great Basin than did spatialdifferences among sites (Fleishman & Mac Nally,2003), we decided it would be useful to explorerelationships between beta diversity and spatialscale more thoroughly. Accordingly, we focuseddirectly on whether beta diversity of butterfliesand birds in the Great Basin depended on sam-pling resolution and the proximity of samplingunits across the landscape (Mac Nally et al.,2004). We also examined the taxonomic compo-nent of scaling issues by comparing how speciescomposition of butterflies and birds responded tosampling resolution and proximity. We calculatedmean similarity of species composition, using theJaccard index, for each sampling grain in turn–sites, canyons, and mountain ranges.

We found that variation in species compositionof butterflies and of birds could be explained asfunctions of both spatial resolution of sampling andrelative distances among sampling units across thelandscape (Mac Nally et al., 2004). Similarity ofspecies composition increased as the samplingresolution decreased (i.e., as grain increased), withmore than 85% of the variation in similarity valuesfor both taxonomic groups attributable to samplingresolution. This result almost certainly reflects theeffect of local environmental heterogeneity on spe-cies composition. High–resolution sampling in arelatively heterogeneous landscape tends to em-phasize differences in species composition alonggradients of resource availability, topography, ormicroclimate. As sampling resolution increases,species composition may reflect emerging similari-

ties in terms of regional climate, land cover, andland use, and biotic assemblages will appear morehomogeneous.

Irrespective of sampling resolution or taxonomicgroup, similarity of species composition decreasedas the biogeographic separation between sam-pling units increased. Although the effect of rela-tive proximity was statistically substantial, how-ever, the absolute difference in species composi-tion in response to relative proximity was modest.For example, assemblages of birds were 14%more similar, and assemblages of butterflies were8% more similar, when canyons were located inthe same mountain range than when canyonswere located in different mountain ranges. Theseresults probably reflect the extraordinarily highvariability in topography in our study system. Al-though there are relatively few major land covertypes in the Great Basin, they are distributed in aremarkable array of local vegetational mosaics.Almost every canyon remains an "island" with adistinct character. Thus, a randomly selected pairof canyons within the same mountain range maynot be much more similar than a randomly se-lected pair of canyons from two nearby mountainranges.

The effects of relative proximity of samplingunits across the landscape were not uniformlygreater for either butterflies or birds (Mac Nally etal., 2004). As we compared the effects of spatialgrain on beta diversity of butterflies and birds,however, two differences immediately were appar-ent (fig. 3). First, at all sampling resolutions, spe-cies composition of butterflies was more similarthan species composition of birds. Second, theeffect of sampling resolution was greater for birdsthan for butterflies, especially when the intermedi-ate sampling resolution was compared to the small-est sampling resolution. In other words, the differ-ence in mean similarity values at the resolution ofmountain ranges versus sites, and at the resolutionof canyons versus sites, was greater for birds thanfor butterflies.

Birds in our study system typically have territorysizes or home ranges about an order of magnitudelarger than those of butterflies. If home range sizeis the primary influence on species composition,then we would expect beta diversity of birds in ourstudy system to be lower than beta diversity ofbutterflies. But previous work suggested, to thecontrary, that resource specialization was morestrongly associated with structure of bird assem-blages than territory size (Fleishman et al., 2002a).If ecological specialization and geographic distri-bution are negatively correlated (Rabinowitz, 1981;Kunin & Gaston, 1997), then beta diversity oftaxonomic groups with relatively general resourceneeds should be lower than beta diversity of groupswith more specialized needs. Although in manyinstances one might assume that birds have moregeneral requirements than butterflies, this may notbe the case in the Great Basin. Butterflies oftenare considered "specialists" because as larvae


they are restricted to one or a few closely relatedhost plants (Ehrlich & Raven, 1964; Scott, 1986).In many ecosystems, however, the resource re-quirements of adult butterflies are fairly general(Holl, 1995; Pullin, 1995), and species composi-tion of butterflies may be more closely associatedwith distribution of an array of potential nectarsources than with distribution of specific larvalhost plants. Availability of nectar is positively cor-related with spatial distribution of adults and lar-vae (Gilbert & Singer, 1973; Murphy, 1983; Murphyet al., 1984) and may reduce the probability oflocal emigration (Kuussaari et al., 1996, Moilanen& Hanski, 1998). Many adult butterflies in theGreat Basin can exploit virtually any source ofnectar, from flowering shrubs to native forbs tonon–native invasive species. Thus, it may be ap-propriate to classify butterflies in our study systemas relative generalists.

Species composition of birds traditionally wasthought to be more closely associated with veg-etation structure (physiognomy) than with vegeta-tion composition (floristics) (MacArthur et al., 1966,Rotenberry & Wiens, 1980). However, some evi-dence suggests that vegetation composition ismore influential than vegetation structure (Tomoff,1974; Wiens & Rotenberry, 1981), especially atrelatively fine spatial resolution (Rotenberry, 1985;Wiens et al., 1987). In the Great Basin, speciescomposition of breeding birds may be affected bythe patchy distribution of various species of trees,which provide nesting sites that differ in theirsuitability for particular species or guilds (Fleishmanet al., 2003a). In particular, Neotropical migrantbirds, which account for about one–third the as-semblage in our study system (Gough et al., 1998),are thought to be relatively selective in choosingnesting sites because of the physical stress theyundergo during migration and the limited temporalwindow available for establishing a breeding terri-tory and reproducing (Robbins et al., 1989; Martin,1992, 1995). Two of the most common trees in ourstudy system, piñon (Pinus monophylla) and juni-per (Juniperus osteosperma), are relatively wide-spread and sometimes form large stands, espe-cially in drier areas. However, dominant ripariantrees and shrubs such as cottonwood and aspen(Populus spp.), willow (Salix spp.), birch (Betulaoccidentalis), and rose (Rosa woodsii) have com-paratively patchy distributions.

Ecologists are well aware that measures ofbiodiversity, and inferences about diversity pat-terns, depend on spatial and temporal scale. Ourresults, which did not support the assumption thatspecies turnover largely is a function of relativehome range size, emphasize the relevance of em-pirical tests of diversity theories to conservationand management. Further, as our understanding ofrelationships between species diversity and variouscomponents of “scale” increases, so should ourability to recognize underlying mechanisms and tomaintain native biodiversity and ecological proc-esses.

Discussion

Around the world, climate change, urbanizationand other land uses, and invasive species aremodifying ecosystem processes, species distribu-tions, and population dynamics of native species.Understanding how assemblages of native plantsand animals respond and evolve to these environ-mental changes is critical to development of effec-tive, practical strategies for ecological restorationand maintenance. Yet the trinity of time, money,and information is elusive for conservation biolo-gists and practitioners. Knowledge of the extent towhich measures of biological diversity vary inspace and time in the absence of deterministic“treatments” is essential for making accurate infer-ences and taking appropriate conservation action,especially when the consequences of those ac-tions may be irreversible.

In virtually all of our work in the Great Basin,irrespective of geographic location or taxonomicgroup, we have been struck by the considerablevariation in species composition across space andtime. At our finest sampling resolution (site level),for example, mean similarities of species composi-

Fig. 3. Beta diversity (mean communitysimilarity) of butterflies and birds at differentspatial resolutions of sampling. Spatial extentof sampling was constant. Error bars are onestandard deviation. Values are parametermeans.

Fig. 3. Diversidad beta (similaridad media en lacomunidad) de mariposas y aves de muestreosrealizados a distintas resoluciones espaciales.La extensión espacial de la muestra fue cons-tante. Las barras de errores son una desvia-ción estándard. Los valores son mediasparamétricas.

birdsbutterflies

1.00

0.75

0.50

0.25

0.00

Mea

n s

imila

rity

site canyon rangeSpatial resolution

54 Fleishman

tion of butterflies and birds were 0.397 and 0.295; atthe mountain range level, mean similarities were 0.875for butterflies and 0.662 for birds (Mac Nally et al.,2004). As a consequence, our work suggests stronglythat spatially extensive sampling may be a more effec-tive strategy for drawing inferences about regionalspecies composition than sampling small areas scat-tered across the landscape. Similarly, recent work hasshown that even after accounting for differences indetection probability, annual site–level turnover rates ofmany species of butterflies and birds in the GreatBasin are as high as 50%. Despite considerable turno-ver in species composition, however, species richnessof butterflies and birds in our study system has tendedto be relatively consistent between years, especially atthe landscape level (Fleishman & Mac Nally, 2003;Fleishman et al., 2003b). Brown et al. (2001) likewisefound that species richness of birds in northern Michi-gan and rodents in the Chihuahuan Desert remainedfairly constant over the long term (22 years and 50years, respectively) notwithstanding substantial changesin species composition, climate, and other environ-mental conditions.

In related work, we examined whether relativelylimited spatial and temporal sampling can provide validinferences about biological responses to variables thatare affected by conservation and restoration actions,including dominance of non–native invasive plants(Mac Nally et al., 2004; Fleishman et al., 2005). In theMojave Desert, both invasion of salt–cedar (Tamarixramosissima) and human efforts to eradicate salt–cedar have altered vegetational communities and somemeasures of faunal diversity. We examined whethersimilar inferences about relationships between plantsand butterflies in the Muddy River drainage could havebeen obtained by using data from a subset of the 85locations included in the study, by sampling less inten-sively in time (fewer visits per site), or by sampling overa shorter period of time. We found that similar infer-ences about the importance of six vegetation–basedpredictor variables on species richness of butterflies,and about occurrence rates of individual species ofbutterflies, could be obtained by sampling as few as10% of sites and by sampling less intensively orextensively in time.

Collectively, our ongoing research in arid environ-ments in the western United States suggests thatrelatively limited data sets may allow us to drawreliable inferences for adaptive management in thecontext of ecological restoration and rehabilitation.Integrating studies of biogeographic patterns withexamination of how study design itself affects eco-logical inferences may be one of the most productiveavenues for developing adaptive management strat-egies that will conserve both biodiversity and theprocesses that sustain it.

Acknowledgements

R. Blair, J. Fay, R. Mac Nally, and D. Murphy havebeen integral participants in the research describedhere. Thanks to G. Austin, C. Betrus, L. Bulluck, J.

Bulluck, D. Dobkin, and the Great Basin Ecosys-tem Management Project for collaboration andassistance. J. Seoane and an anonymous reviewerprovided helpful comments on the manuscript.Support for this work was provided by the NevadaBiodiversity Research and Conservation Initiativeand by the Joint Fire Sciences Program via theRocky Mountain Research Station, Forest Service,U.S. Department of Agriculture.

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Corn, P. S., 2005. Climate change and amphibians. Animal Biodiversity and Conservation, 28.1: 59–67.

AbstractClimate change and amphibians.— Amphibian life histories are exceedingly sensitive to temperature andprecipitation, and there is good evidence that recent climate change has already resulted in a shift tobreeding earlier in the year for some species. There are also suggestions that the recent increase in theoccurrence of El Niño events has caused declines of anurans in Central America and is linked to elevatedmortality of amphibian embryos in the northwestern United States. However, evidence linking amphibiandeclines in Central America to climate relies solely on correlations, and the mechanisms underlying thedeclines are not understood. Connections between embryo mortality and declines in abundance have notbeen demonstrated. Analyses of existing data have generally failed to find a link between climate andamphibian declines. It is likely, however, that future climate change will cause further declines of someamphibian species. Reduced soil moisture could reduce prey species and eliminate habitat. Reducedsnowfall and increased summer evaporation could have dramatic effects on the duration or occurrence ofseasonal wetlands, which are primary habitat for many species of amphibians. Climate change may be arelatively minor cause of current amphibian declines, but it may be the biggest future challenge to thepersistence of many species.

Key words: Amphibians, Amphibian decline, Breeding phenology, Global climate change.

ResumenCambio climático y anfibios.— Las historias vitales de los anfibios son sumamente sensibles a latemperatura y a la precipitación, y hay una clara evidencia que el reciente cambio climático ha tenido comoresultado para algunas especies una anticipación del periodo de cría a lo largo del año. También se cree queel aumento reciente en la ocurrencia de fenómenos de El Niño ha causado el descenso de anuros enAmérica Central y está relacionado con la mortalidad elevada de embriones de anfibios en el noroeste delos Estados Unidos. Sin embargo, la evidencia que relaciona el descenso de anfibios en América Centralcon el clima está basado únicamente en correlaciones, y no se entienden los mecanismos fundamentalesque provocan este descenso. No se han podido demostrar las conexiones entre la mortalidad de embrionesy el descenso de abundancia. El análisis de los datos generalmente falla a la hora de encontrar unaconexión entre descensos de anfibios y el clima. Es probable, sin embargo, que posteriores cambiosclimáticos puedan causar descensos adicionales de algunas especies de anfibios. La humedad reducida dela tierra podría reducir las especies presa y eliminar el habitat. La reducción de nevadas invernales y elincremento de la evaporación en verano podrían tener efectos dramáticos en la duración u ocurrencia depantanos estacionales, que es el habitat principal para muchas especies de anfibios. El cambio del climapuede ser una causa relativamente secundaria de los descensos actuales de anfibios, pero en el futuropuede 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.

Climate change and amphibians

P. S. Corn

60 Corn

der, 2003), and not changes in distribution. Forexample, Livo & Yeakley (1997) failed to detectany directional change in elevation associatedwith declines of Boreal Toads (Bufo boreas) in theRocky Mountains in Colorado, USA. However,Martínez–Solano et al. (2003) attributed the in-crease in occurrence of Iberian Green Frogs (Ranaperezi) in Peñalara National Park in Spain torecent climate warming. Thomas et al. (2004)estimated changes in distribution for a number ofspecies based on predicted changes in their cli-mate envelopes, and by applying the relationshipbetween area and diversity, predicted that 18–35%of the species they examined (which included 23frogs from Queensland, Australia) will have a highrisk of extinction by 2050. Because amphibiandecline is already a significant problem, the poten-tial for greatly increased risk of extinction makes itimportant to understand how climate change af-fects amphibians.

Amphibians are ectotherms, and all aspects ofamphibian life history are strongly influenced by theexternal environment, including weather and cli-mate. Temperature is a particularly important factoraffecting aquatic amphibian larvae. Ultsch et al.(1999) provided a concise statement:

"…environmental temperature dramatically af-fects the time taken to reach metamorphosis, whichcan be critical to the survival of an individual facedwith a drying habitat or the onset of winter. Tem-perature also affects differentiation and growth rates,body size at metamorphosis, mechanisms of gasexchange, rates of energy metabolism, and un-doubtedly many other physiological parametersdocumented in ectothermic vertebrates. Moreover,the limits of temperature tolerance and tempera-ture–dependent life history traits of anuran larvaeare generally related to the geographic distributionof a species."

Ovaska (1997) and Donnelly & Crump (1998)described how changes in temperature and pre-cipitation regimes could result in changes in thedistr ibut ion and abundance of amphibianpopulations. Direct effects include changes inmovements, phenology, and physiological stress.Indirect effects include changes in predators, com-petitors, food supply, and habitat. Most researchto date has emphasized direct effects of climatechange. Indirect effects, particularly the links topopulation dynamics, are notoriously difficult todocument.

The consequences of climate change are di-verse, and effects can be beneficial as well asdetrimental (Ovaska, 1997; McCarty, 2001). A shiftin breeding activity to earlier in the season mayprovide additional time for growth and develop-ment. Larger individuals may survive over winterbetter and may have increased reproductive fitnessthan small ones (Reading & Clarke, 1999). Breed-ing earlier reduces exposure to UV–B (Merilä et al.,2000; Corn & Muths, 2002; Cummins, 2003). Onthe other hand, earlier breeding could bring in-creased risk of exposure to extreme temperatures

Introduction

Considerable progress has been made in the pastdecade in documenting the nature and extent ofamphibian declines (Waldman & Tocher, 1998;Alford & Richards, 1999; Corn, 2000; Houlahan etal., 2000; Hero & Shoo, 2003). Declines of am-phibian species have been documented in most ofthe world, including Spain (Márquez et al., 1995;Bosch et al., 2001; Martínez–Solano et al., 2003).Knowledge of the status of amphibians is incom-plete, but it appears that declines are most severein Australia (Laurence et al., 1996), Central America(Pounds et al., 1997; Lips, 1998, 1999), and thewestern United States (Drost & Fellers, 1996; Fisher& Shaffer, 1996; Sredl et al., 1997). There is alsoa better understanding of at least some of thecauses of amphibian declines, compared to 1990,when the issue of declining amphibians first gainedwidespread attention (Collins & Storfer, 2003).Habitat destruction or alteration, contaminants,introduced predators, and disease have all beenidentified as potential or likely causes of declines(Stebbins & Cohen, 1995; Sparling et al., 2000;Linder et al., 2003; Semlitsch, 2003). Global changeas a cause of amphibian declines has also beenstudied from two main perspectives: increasingtemperatures and increasing ultraviolet–b radia-tion (UV–B) due to thinning of stratospheric ozone.Although field and laboratory experiments haveshown that ambient UV–B may cause mortality ordeformities in some amphibian species (Blausteinet al., 1998; 2003b), the UV–B hypothesis is con-troversial and has been the subject of a series ofcontentious 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 hypoth-esis that increasing UV–B has contributed to am-phibian declines is undermined by a lack of evi-dence linking results from experimental studies tochanges in abundance or distribution (Corn &Muths, 2002) and by the general lack of evidencethat amphibians have been exposed to increaseddoses of UV–B (Corn & Muths, 2004).

There is increasingly strong evidence, however,that recent climate change has affected the biol-ogy of numerous species worldwide. Global aver-age temperature has increased by about 0.6°Cduring the past century, which is the warmestperiod of the preceding millennium (Jones et al.,2001). This increase in temperature is largelyattributable to increasing greenhouse gasses(Crowley, 2000). Warming spring temperatureshave resulted in measurable shifts in phenology(e.g., timing of budding, flowering, emergence,breeding) to earlier dates, and distributions ofsome plants and animals have shifted pole–wardand higher in elevation (Walther et al., 2002;Parmesan & Yohe, 2003; Root et al., 2003). Theeffects on amphibians observed so far mainlyinvolve changes in the timing of breeding of somespecies (Blaustein et al., 2003a; Carey & Alexan-


from more variable early spring weather (Corn &Muths, 2002). The effects of changes in tempera-ture and precipitation on hydrology and hydroperiod(the length of time a temporary pond retains water)may have large effects on amphibians. Early dryingof temporary ponds may result in less time avail-able to complete metamorphosis (Semlitsch, 1987;Pechmann et al., 1989, Rowe & Dunson, 1995).Changes in breeding phenology and pond hydrol-ogy may affect growth rates of larvae (Rowe &Dunson, 1995; Reading & Clarke, 1999; Boone etal., 2002), and because much predation on am-phibian larvae is related to size, this may alter therelationships between amphibians and their preda-tors.

Several recent papers have reviewed the effectsof climate change on amphibians (Blaustein et al.,2003a; Boone et al., 2003; Carey & Alexander,2003). However, few studies have addressed theeffects of climate change on amphibians in montaneor boreal habitats with persistent winter snow cover,where the timing of snowmelt is the primary influ-ence on breeding phenology. Thomas et al. (2004)predicted the smallest increase in extinction risk inalpine and boreal forest habitats, but warming tem-peratures in the next 50–100 years are predicted todrastically alter the characteristics of mountain snowpacks. Numerous questions still need answers if weare to predict how climate change will affect thedistribution and abundance of amphibians.

Effects of climate change on amphibians

Changes in breeding phenology

Several studies have demonstrated trends towardsbreeding earlier by some species of amphibians.Terhivuo (1988) used the longest time series foramphibians, 140 years of observations collected byvolunteers in Finland, and found that CommonFrogs (Rana temporaria) bred 2 to 13 days earlierin the 1980s than in the 1840s, depending onlatitude. Gibbs & Breisch (2001) compared data onthe dates of first calling by anurans near Ithaca, NYcollected 1900–1912 (Wright, 1914) to data gath-ered by the during 1990–1999 by the New YorkState Amphibian and Reptile Atlas Project. Fourspecies began breeding activity significantly earlier(by 10–14 days) during the last decade, comparedto the first 12 years of the 20th Century. Over thesame period, significant increases in mean dailytemperatures (1.2–2.3°C) also occurred in 5 of the8 months important to gametogenesis in thesespecies. In Poland, the dates of first spawning byR. temporaria and Common Toads (B. bufo) shifted8–9 days earlier between 1978 and 2002 and werecorrelated with warmer spring temperatures(Tryjanowski et al., 2003). The most dramatic shiftsin the shortest time were found in England, wheretwo anuran species deposited eggs 2–3 weeksearlier and the three species of salamander arrivedat breeding ponds 5–7 weeks earlier in 1990–1994

compared to 1978–1982 (Beebee, 1995). Thesechanges result from warmer spring temperaturesassociated with the North Atlantic Oscillation(Forchhammer et al., 1998).

The trend toward earlier breeding by amphibiansin recent years is not universal. There are about anequal number of cases in England and NorthAmerica where there is no significant trend towardearlier breeding as there are cases of significanttrends (Beebee, 1995; Reading, 1998; Blaustein etal., 2001; Gibbs & Breisch, 2001; Corn & Muths,2002). Most of these cases use time series of < 20years, which may be too short to demonstratesignificant trends in the face of large interannualvariation in the timing of breeding. For example,Blaustein et al. (2001) found a non–significant trendtoward earlier breeding in one of three populationsof B. boreas in the Cascade Mountains in Oregon,USA for 1982–1999. Corn (2003) analyzed thesedata using the relationship between the timing ofbreeding and the size of the winter snow pack tomodel the timing of breeding. Predicted breeding inthe one population showed a much more pro-nounced trend toward breeding earlier by about 20days between 1950 and 2000.

Long time series (>50 years) are probably nec-essary to separate the effects of anthropogenicwarming from multi–decadal cycles on changes inbreeding phenology. That Beebee (1995) andTryjanowski et al. (2003) found greater shifts inphenology after about 30 years than did Terhivuo(1988) after 140 years may reflect this phenom-enon. For example, snow accumulation in the north-west United States is strongly influenced by thePacific Decadal Oscillation (PDO), Selkowitz et al.,2002). Because the 1950s were a period of higherthan average snowfall, the trend toward earlierbreeding by the population of B. boreas in Oregon(Corn, 2003) is likely to have been strongly influ-enced by the PDO.

Changes in populations

Climate change has been considered a potentialcause of population declines since the beginning ofthe current spate of concern about the status ofamphibians (Wyman, 1990), but the role of climatechange in the decline of anurans in the cloud forestof Costa Rica has received the most attention.About half of the 50 species expected to occur inthe Monteverde region had disappeared by 1990(Pounds et al., 1997). These included the distinc-tive Golden Toad (B. periglenes). The decline of thisspecies was first observed in 1987, and is not beenobserved since 1989 and is likely extinct (Crump etal., 1992). Pounds & Crump (1994) described the1987 crash of B. periglenes as resulting from aboveaverage temperatures and below average precipita-tion that were associated with a strong El Niño/Southern Oscillation (ENSO). This event killed eggsand tadpoles by premature drying of breeding ponds,but the explanation for the subsequent disappear-ance of adult toads was not apparent. Pounds and

62 Corn

Crump discussed hypotheses for how adults mayhave been affected, including physiologic stress,impaired immune system function leading to dis-ease, and contaminants. They also described thedecline of the Harlequin Frog (Atelopus varius) inthe same region. This species congregates in moistrefugia, such as the splash zones of waterfalls,during dry periods, and becomes more susceptibleto predation and parasitism (Pounds & Crump,1987; Donnelly & Crump, 1998).

Pounds et al. (1999) described continuing popu-lation fluctuations of anurans at Monteverde in the1990s, with significant declines involving about 20species in 1994 and 1998. These more recentdeclines were also correlated with warm and dryconditions associated with decreasing dry seasonmist frequency. The retreat of the cloud bank tohigher elevations is a product of global warmingand is accentuated during strong ENSO events(Still et al., 1999). Pounds et al. (1999) also ob-served changes in other animals, in addition todeclines of anurans. In a cloud–forest study plot,there has been an increase in the frequency of birdspecies that normally breed at lower elevationsbelow the cloud forest, and two species of anolinelizards, endemic to the highlands of western CostaRica and Panama, declined and disappeared by1996. Although the changes in the cloud forestfauna were strongly correlated with climatic events,our understanding of the mechanisms underlyingthe declines of anurans and lizards has not pro-gressed beyond the hypotheses presented byPounds et al. (1997). Middleton et al. (2001) usedsatellite–based observations to estimate surfaceUV–B exposure at Central and South Americansites, including Monteverde, where amphibian de-clines have been observed. They found increasingtrends from 1979 to 1998, in annual averaged UV–B exposure and the number of days per year withhigh UV–B, that were strongest in Central America.However, most of the declining amphibian speciesat Monteverde are forest–floor dwellers that havelimited exposure to sunlight. According to Pounds &Crump (1994: p 73), B. periglenes, "…normallyhide in retreats about 95% of the time, emerging tobreed beneath the forest canopy, typically underheavy cloud cover." Middleton et al. (2001) wereunable to describe a plausible mechanism for howincreasing UV–B could affect such species. Thetrends of increasing UV–B may be a by–product ofdecreased cloudiness (Still et al., 1999) and notrelated to the amphibian declines that have beenobserved to date.

Kiesecker et al. (2001) described a mechanismby which climate change and UV–B radiation coulddirectly affect the abundance of B. boreas in thePacific Northwest. ENSO events result in low winterprecipitation in the Cascade Mountains, and in thefollowing spring, toad embryos develop in shal-lower water than in years with high winter precipita-tion. Kiesecker et al. found a significant regressionbetween depth at which embryos develop and mor-tality. At depths less than 20 cm, infection by the

pathogenic water mold Saprolegnia ferax was greaterthan 50%. Kiesecker & Blaustein (1995) demon-strated experimentally that B. boreas embryos weresusceptible to S. ferax only in the presence of UV–B radiation. Kiesecker et al. (2001) exposed B.boreas embryos to ambient sunlight and sunlightwith UV–B removed by mylar filters at 3 depths (10,50, and 100 cm). Mortality of embryos exposed toambient sunlight exceeded mortality of embryosprotected from UV–B only in the shallowest treat-ment. Kiesecker et al. (2001) concluded that inENSO years, embryos develop in shallower water,are exposed to higher doses of UV–B radiation, andconsequently suffer catastrophic mortality from in-fection by S. ferax.

Analyzing global change as an explanationfor amphibian declines

Although Pounds et al. (1999) provide correlationsbetween decline of anurans in Costa Rica andENSO events, the mechanisms causing the de-clines are still a matter of speculation. The liftingcloud bank hypothesis (Still et al., 1999) is a com-puter simulation, and temperature data collected byPounds et al. (1999) are not consistent with itspredictions. Pounds et al. recorded a decrease inthe difference between daytime and nighttime tem-peratures, but clear skies should result in lowernighttime temperatures and an increase in the dif-ference. Pounds et al. did record greater frequencyof dry season days without precipitation from mistduring ENSO years, so it may be that precipitationis much more important that temperature as afactor in the declines of amphibians in theMonteverde region. However, Alexander & Eischeid(2001) point out that the ENSO event in 1982–1983was stronger than the 1986–1987 event, but it wasnot coincident with amphibian declines atMonteverde.

The study of B. boreas by Kiesecker et al. (2001)shifted one of the emphases in the study of causesof amphibian declines from direct effects of increas-ing UV–B radiation (Blaustein et al., 1998) to morecomplex interactions (Blaustein & Kiesecker, 2002).Pounds (2001) stated that Kiesecker et al. (2001),"…identify a complete chain of events whereby cli-mate change causes wholesale mortality in an am-phibian population." However, this is a significantoverstatement. Kiesecker et al. (2001) linked climatechange, UV–B radiation, and disease with excessivemortality of embryos. It has not been demonstratedthat this has affected the abundance of adult toads.Kiesecker et al. (2001) stated, "If bouts of highembryo mortality occur with greater regularity andintensity, they may result in population declines."However, the populations of toads studied byKiesecker et al. have not declined (Olson, 2001),and sensitivity analysis suggests that abundance isnot strongly related to changes in embryo mortality(Biek et al., 2002; Vonesh & De la Cruz, 2002).Furthermore, the mechanism of embryo mortality


proposed by Kiesecker et al. (2001) is open toquestion. In the mountains of the western U.S.,amphibian breeding phenology is controlled bysnowmelt, and low winter precipitation results inearlier breeding (Corn & Muths, 2002; Corn, 2003).Earlier breeding reduces exposure of embryos toUV–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 ofany amphibian breeding site in the Cascades (Palenet al., 2002). Therefore, it may not be appropriate togeneralize based on results of studies at this site.

Population declines associated with infectionby the pathogenic fungus Batrachochytriumdendrobatidis have been documented in amphib-ians in many regions, including Spain (Bosch et al.,2001), and Daszak et al. (2003) considerchytridiomycosis to be an emerging infectious dis-ease (EID). An EID may be caused by a commonpathogen that increases in range and virulencefollowing an environmental change (Daszak et al.,2001), and because B. dendrobatidis suvives bestat moderate temperatures (23° C) and dies at 30° C(Longcore et al., 1999), it is tempting to hypoth-esize that climate change may be playing a role inchytridiomycosis as an EID. There have been sev-eral attempts to relate amphibian declines, some ofwhich may be caused by chytridiomycosis, to re-cent weather patterns and climate data, none ofwhich have been very successful. Numerous spe-cies of rainforest frogs have disappeared or de-clined in eastern Australia, primarily in the moun-tains of eastern Queensland and northeastern NewSouth Wales (Laurance et al., 1996; Mahony, 1996).Laurance (1996) analyzed weather data, and al-though wet season rainfall was reduced in the 5years preceding declines, he concluded this wasnot out of the range of normal variation and wasinsufficient to have caused the declines.

Alexander & Eischeid (2001) examined climatedata for regions with documented amphibian de-clines (Colorado, Puerto Rico, Central America,and Queensland), and found results similar toLaurance (1996). There were few similarities inweather among areas before the declines occurred,and although warmer temperatures occurred duringthe onset of declines in Puerto Rico and Queens-land, these were not extreme. Alexander andEischeid concluded that abnormal temperature andprecipitation were unlikely to have caused the de-clines directly. Because the chytrid fungus maysurvive better at cooler temperatures, and is likelyto be transmitted among amphibians by a motileaquatic stage, warmer and drier climate trendsseem unlikely to promote outbreaks of chytridio-mycosis. However, we need considerably more in-formation before rejecting a link between climatechange and disease.

Davidson et al. (2001, 2002) examined the geo-graphic patterns of the declines of several amphib-ian species in California, related to climate, UV–Bradiation, urbanization, and agriculture. They hy-pothesized that climate change would be mani-

fested in declines related to related to latitude,elevation, and precipitation. Specific predictions weremore declines at lower latitudes and elevations andat drier sites. However, they found no evidence tosupport this hypothesis. Declines of several spe-cies occurred downwind of agricultural areas, sug-gesting that airborne contaminants might be thegreatest threat.

Future effects of climate change onamphibians

The relationship between current amphibian de-clines and climate change may be ambiguous, butit is fairly easy to predict serious consequences toamphibian abundance and distribution if predic-tions of climate change during the next centurycome to pass. MacCracken et al. (2001) and Hulme& Viner (1998) describe potential outcomes for theUnited States and the tropics, respectively.MacCracken et al. (2001) describe outcomes ofclimate models based on increasing atmosphericCO2 concentrations. Global mean temperatureswould rise 1.2–3.5°C, but increases would be higherat mid to high latitudes and greater over continentsthan over oceans. Warming over the U.S. would bebetween 2.8 and 5°C and result from higher winterand nighttime temperatures. Global precipitationwill increase, but predicting local patterns is diffi-cult. Less snow is expected, reducing the area ofsnow cover during winter. Higher summer tempera-tures will increase evaporation, reducing soil mois-ture. Extreme precipitation events will become morefrequent. In the tropics, the predictions describedby Hulme & Viner (1998) are qualitatively similar:increased temperature, increased length of the dryseason, decreased soil moisture, and greaterinterannual variation in rainfall.

Donnelly & Crump (1998) predict that tropicalamphibians will suffer reduced reproductive suc-cess, reduced food supply, and a disruption inbreeding behavior and periodicity. They predict thatthe effects will be greatest on endemic species,those species restricted to a specific location andwhich usually have specialized ecological require-ments. Donnelly and Crump note that if all theendemic amphibians were lost in three CentralAmerican countries, Costa Rica, Panama, and Hon-duras, amphibian diversity in those countries woulddecrease by 17 to 26%. Thomas et al. (2004)forecast similar changes in a suite of tropicalanurans in Australia by the year 2050, based onshrinkage of available habitat resulting from pre-dicted changes in temperature and precipitation.Teixeira & Arntzen (2002) used a similar approachto predict reduced distribution of the Golden–stripedSalamander, Chioglossa lusitanica, in Spain andPortugal between 2050 and 2080.

Thomas et al. (2004) predicted the smallest riskof extinction for species inhabiting boreal and al-pine habitats. However, several species of amphib-ians in the mountains of the western U.S. have

64 Corn

declined in the past 20–30 years (Corn, 2000),and climate models predict that rising winter tem-peratures will dramatically reduce the extent andduration of mountain snow packs in most of thisregion in the next 50–100 years (McCabe & Wolock,1999; Leung et al., 2004; Stewart et al., 2004). Iftrue, this will result in earlier breeding by mostmontane amphibians (Corn & Muths, 2002; Corn,2003), increasing the strain on populations thatmay already be in decline. The consequences ofearlier breeding may include more frequent expo-sure to killing frosts (Inouye et al., 2001). Theduration of the larval period may increase, be-cause water temperatures warm more slowly inearly spring. Amphibians breeding in lentic watertypically have high larval mortality, and there isstrong selection for reducing the time spent aslarvae (Berven, 1982). Reduced water storage assnow, earlier runoff, and an increase in evapora-tion due to warmer summer temperatures willlikely reduce the hydroperiod of temporary ponds,but specific predictions are complex and requirelinking hydrologic models to climate change pre-dictions. Any significant change in occurrence orhydroperiod of temporary ponds could have seri-ous effects on amphibian diversity. Several am-phibian species use temporary ponds as theirprimary breeding habitat. Predators and competi-tion from other amphibians restricts the ability ofthese species to switch to more permanent water(Wellborn et al., 1996; Snodgrass et al., 2000).Threats to montane amphibians may be moresevere than predicted generally for boreal andalpine species by Thomas et al. (2004).

Finally, an increase in the frequency of severeweather events is likely to cause problems foramphibians. Drought has been documented sev-eral times as a serious challenge to populationpersistence (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 ascauses of declines at regional scales (Heyer etal., 1988; Woolbright, 1997; Corn, 2000). In-creases in catastrophic mortality are difficult forstable populations to cope with, but for thoseamphibian species already in decline, increasesin severe weather events could make survivalextremely difficult.

Acknowledgements

The initial draft of this paper was written in 2001 fora book resulting from the University of GeorgiaState–of–the–Art Conference: The Big Unknowns inGlobal Change: Climatic, Biotic, Human Systems.Although the book was never published, I thankElgene Box and Lynn Usery for inviting me to partici-pate. I thank Mo Donnelly, Rafael Márquez, JulietPulliam, and an anonymous reviewer for commentson earlier drafts.

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Geist, C., Liao, J., Libby, S. & Blumstein, D. T., 2005. Does intruder group size and orientation affect flightinitiation distance in birds? Animal Biodiversity and Conservation, 28.1: 69–73.

AbstractDoes intruder group size and orientation affect flight initiation distance in birds?— Wildlife managers useflight initiation distance (FID), the distance animals flee an approaching predator, to determine set backdistances to minimize human impacts on wildlife. FID is typically estimated by a single person; this studyexamined 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 PiedCurrawongs (Strepera graculina) and to Crimson Rosellas (Platycerus elegans). Rosellas flushed atsignificantly greater distances when approached by two people compared to a single person. This effect wasnot seen in currawongs. Intruder orientation did not influence the FID of either species. Results suggest thatintruder number should be better integrated into estimates of set back distance to manage human visitationaround sensitive species.

Key words: Flight initiation distance, Intruder group size, Intruder orientation, Human disturbance, Set–backdistances.

Resumen¿El tamaño y la orientación del grupo intruso afecta a la distancia de iniciación al vuelo en aves?— Losgestores de la fauna utilizan la distancia de iniciación al vuelo (FID), la distancia a la que los animaleshuyen cuando se les acerca un depredador, para determinar las distancias de respuesta a fin de minimizarel impacto humano en la fauna. La FID es estimada típicamente por una sola persona; este estudioexaminó los efectos del número y de la orientación del intruso en la FID. Se aplicaron tres tratamientosdistintos de tamaño del grupo (persona solitaria, dos personas una al lado de la otra, dos personas unadetras de la otra) a currawongs cálidos (Strepera graculina) y a pericos elegantes (Platycerus elegans). Lospericos elegantes huían a distancias perceptiblemente mayores cuando se le acercaban dos personas quecuando se le acercaba una sola. Este efecto no fue observado en los currawongs pálidos. La orientacióndel intruso no influenció en la FID de ninguna especie. Los resultados sugieren que el número de intrusosdebería ser considerado en las estimaciones de las distancias de respuesta, para poder gestionar lasvisitas de personas cerca de especies sensibles.

Palabras clave: Distancia de iniciación al vuelo, Tamaño del grupo intruso, Orientación del intruso, Molestiahumana, 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 DriveSouth, Univ. of California, Los Angeles, CA 90095–1606, U.S.A.

Corresponding author: D. T. Blumstein. E–mail: [email protected]

Does intruder group size andorientation affect flight initiationdistance in birds?

C. Geist, J. Liao, S. Libby & D. T. Blumstein


70 Geist et al.

Gochfeld, 1990; broad–headed skinks (Eumeceslaticeps) –Cooper, 1997). This evidence suggeststhat some animals can perceive subtle differencesin intruder behavior and adjust their responsesaccordingly (Burger & Gochfeld, 1990). In order forthe prey to react, the intruder must be within theprey’s field of view (Cooper, 1997). If the prey andpredator look at each other, then there is a greaterprobability that the predator has detected the preyand poses a greater risk to the prey. If birds candetect and make eye contact with two intrudersside–by–side better than two intruders directly be-hind one another, then the side–by–side orientationapproach 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 BoodereeNational Park (150º 43’ N, 35º 8’ W), 200 km S ofSydney.

From 23 X–6 XI 03, the effects of intruder numberand orientation on FID were studied by walkingtowards these two species at ten locations aroundthe park. The locations included a commonly visitedbeach (Murray Beach), camping areas (Bristol Point,Cave Beach, Green Patch, Iluka Beach), native bushland (Hole in the Wall, Steamers Beach, TelegraphCreek), a managed natural garden (The BoodereeBotanic Gardens), and an Australian naval college(HMAS Creswell). The sites were chosen becausethey contained hiking trails surrounded by moistforests and woodlands. At each of these locations,data were collected while walking along the trail.Locations were geographically grouped into six re-gions to study for location effects.

Data collection

To measure FID, perched or foraging subjects thatwere not initially disturbed by the observer’s pres-ence were identified. Highly vigilant or nestingbirds were not approached. The subject was thenflushed by walking towards it at a constant pace ofapproximately 1.0 m/s, while maintaining eye con-tact. Before data were collected, observers trainedthemselves to maintain a consistent stride lengthand a constant pace. Paces were converted tometers for analysis. Observers recorded the dis-tance from the focal bird at the start of the experi-mental approach, the height off the ground at thestart of the approach, and the distance the birdinitiated flight. Each flush was conducted usingone of three different treatments listed below: (1)one person directly approached a bird, (2) twopeople, 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 behindone another approached a bird.

Introduction

The distance at which an animal begins to flee anadvancing predator is commonly referred to as"flight–initiation distance" (Ydenberg & Dill, 1986)or "flush distance" (Holmes et al., 1993). Thereshould be strong selection for successful animalsto flee at an optimal FID. Early flight might reduceforaging efficiency, while late flight could end withaccidental predation. Successful individuals shouldbalance the costs of flight with the benefits ofremaining. Ydenberg & Dill (1986) developed aneconomic model to qualitatively predict optimalflight distances from approaching predators. Sub-sequent studies have demonstrated that optimalFID 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; dan-gerousness of the predator –McLean & Godin,1989; availability of cover –LaGory, 1987).

Ecotourism and outdoor activities have grownincreasingly popular, but the effects of humans arenot entirely benign to wildlife (Wearing & Neil, 1999;Christ et al., 2003). Wildlife managers try to reducehuman disturbance by assuming that approachinghumans are perceived as predators (e.g., Frid & Dill,2002), and then using FID to develop set backdistances –the minimum distance that a human mayapproach before the bird is disturbed (e.g., Holmeset al., 1993; Rodgers & Smith, 1995). Such dis-tances are often used to establish seasonal touristlimits and to restrict recreational access (Fernández–Juricic et al., 2001).

Tourist numbers vary considerably, yet we areaware of no experimental studies studying whetherthere is an effect of intruder number on FID. Thisstudy examined whether birds modified their FIDwhen faced with one or two approaching humans.By increasing the number of advancing intruders,we generated an effect similar to increasing preda-tor density. Theory is not clear on how increasedpredator densities affect antipredator behavior inprey because the effects of predator density mayvary with ecological circumstances (Abrams,1994). FID was used as a quantitative measure-ment of a bird’s assessment of risk (Ydenberg &Dill, 1986; Frid & Dill, 2002). If intruder numberincreased the perception of risk, then it wasexpected that more intruders would result in largerFIDs.

This study also examined how birds assessedrisk when two humans approached side–by–side, ordirectly behind one another. The side–by–side orien-tation treatment was executed with one intruderapproaching tangentially while another intruder ap-proached directly. Previous studies have found thatprey perceive tangential approaches as less evoca-tive than direct approaches (e.g., great black–backedgulls (Larus argentus) –Burger & Gochfeld, 1981;black iguanas (Ctenosaura similis) –Burger &


The location and distance to vegetation coverwas also noted because these additional factorscould influence FID (Burger & Gochfeld, 1991).Subjects at the same site were selected if it was notpossible for them to have seen previous experimen-tal approaches, because previous exposure couldhave influenced their response (e.g., Runyan &Blumstein, in press).

Data analysis

For each species, general linear models werefitted to study the effect of treatment on FID. Weused the "direct" FID, calculated with the Pythago-rean Theorem, as our measure of FID because,for some birds, FID is influenced by the height abird is in a tree (Blumstein et al., in press). Theeffect of FID was determined based on the directdistance between the prey and the predator. Moreo-ver, because FID typically is influenced by intruderstarting distance (Blumstein, 2003), starting dis-tance must be included in models. Such modelsmust be forced through the origin because, logi-cally, a starting distance of 0 m must have a FIDof 0 m. Doing so, however, makes the main effectof treatment uninterpretable. Hence, to understandthe effect of treatment on the expected relation-ship between starting distance and FID, the inter-action between starting distance and treatmentwas examined.

Analyses focused on flushes with starting dis-tances that ranged between 10 m and 50 m. Thecurrawong data set contained 23 single, direct ap-proaches, 19 paired, side–by–side approaches, and20 paired, one–behind–another approaches. Therosella data set contained 20 single, direct ap-proaches, 20 paired, side–by–side approaches, and27 paired, one–behind–another approaches.

Other factors could influence FID. The effect ofthe regions where the birds were flushed, and thedistance a subject was from vegetation on FID wereexamined by fitting general linear models and ex-amining the interaction of these factors with start-ing distance. No significant interactions were found(location effect: PCurrawong = 0.605, adjustedR2

Currawong = 0.830, model PCurrawong = 0.0001PRosella = 0.979, adjusted R2

Rosella = 0.759, modelPRosella = 0.0001; distance to vegetative cover:PCurrawong = 0.239, adjusted R2

Currawong = 0.839, modelPCurrawong = 0.0001; PRosella = 0.810, adjustedR2

Rosella = 0.766, model PRosella = 0.0001), and wetherefore do not believe that our main results (dis-cussed below) are confounded by their effect.

Results

Currawongs

Variation in FID was not significantly explained bythe interaction of treatment type and starting dis-tance (Pinteraction = 0.337, adjusted R2 = 0.837,Pmodel = 0.0001), intruder number and starting dis-

tance (Pinteraction= 0.121, adjusted R2 = 0.841,Pmodel = 0.0001), or between the two, two–personapproaches ( Pinteraction = 0.279, adjusted R2 = 0.846,Pmodel = 0.0001; fig. 1A).

Rosellas

Variation in the FID was significantly explainedby the interaction of treatment and starting dis-tance (Pinteraction= 0.0009, adjusted R2 = 0.843,Pmodel = 0.0001), intruder number and starting dis-tance (Pinteraction = 0.0004, adjusted R2 = 0.843,Pmodel = 0.0001), but there was no difference betweenthe 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 whetherintruder number and orientation had an affect onbirds’ decision to flee approaching humans. Whileneither studied species responded to variation inthe orientation of the paired intruders, rosellasflushed at significantly greater distances when ap-proached by two intruders, than by a single in-truder. This finding suggests that rosellas assesseda higher risk of predation when approached by twointruders than by one. More importantly, the findingthat intruder number effects flight decisions hasimportant implications for the estimation of setback distances as well as for strategies to reducehuman disturbance on vulnerable wildlife.

Our results were likely not influenced by habitu-ation; at our sites, both species appeared reason-ably habituated to humans. Rather, variation inresponse may result from variation in the species’natural history. Crimson Rosellas are seedeatersand Pied Currawongs are omnivores (Higgins,1999; Fagg, 2002). Foraging for non–plant itemsis relatively time consuming (Naoki, 2003) and, fora given level of risk, currawongs may experience agreater cost of flight. In contrast, animals foragingon seeds could always return. Hence, currawongsmight be more tolerant of intruders and less sen-sitive to variation in risk. To properly evaluate thisnatural history hypothesis, more species with vari-able diets must be studied in a formal comparativeanalysis (e.g., Blumstein et al., in press).

While an effect of intruder orientation was ex-pected, none was found. Further experiments mustbe conducted to determine why, but it is likely thatthe intruders were too close together to reflectdistinctly different risks. More generally, develop-ing a fundamental understanding of how birdsperceive groups of humans will be important tobetter manage human disturbance.

This study demonstrated that birds may re-spond differently to multiple intruders. Somewhatremarkably, the effect was present with the addi-tion of a single person. Future studies conductedwith larger group sizes would be needed to deter-mine the precise shape of the function of this

72 Geist et al.

effect. Coordinating larger groups in an experimentwill be difficult, but it is essential to document thesize beyond which effects of additional people areno longer experienced. Such findings could assistin establishing acceptable visitor densities in bufferareas. A first step towards determining whethervisitor number might be important could be ob-tained by replicating our experimental design onvulnerable species.

Acknowledgements

Research was conducted with permission from theWreck Bay Aboriginal Community, EnvironmentAustralia (BDR03/00012), and the HMAS Cresswell.We thank Matt Hudson, Arthur Georges, and theCommander of the HMAS Cresswell for assist-ance obtaining relevant permits. Research waspartially supported by the UCLA Office of Instruc-tional Development, the Department of Ecologyand Evolutionary Biology, and the Lida Scott BrownOrnithology Trust. We thank Brenda Larison andMichael Mitchell for statistical advice, and Kenand Patti Nagy for logistical support.

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Fig. 1. The relationship between starting distance and treatment on FID for Pied Currawongs (A) andCrimson Rosellas (B): single flushes, diamonds and small dashed line; side–by–side flushes, squaresand 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, cuadradosy líneas continuas; aproximaciones uno detras de otro, triángulos y lineas de puntos grandes.

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Long–term trendsof native and non–native fish faunasin the American SouthwestJ. D. Olden & N. L. Poff

Olden, J. D. & Poff, N. L., 2005. Long–term trends of native and non–native fish faunas in the AmericanSouthwest. Animal Biodiversity and Conservation, 28.1: 75–89.

AbstractLong–term trends of native and non–native fish faunas in the American Southwest.— Environmentaldegradation and the proliferation of non–native fish species threaten the endemic, and highly unique fishfaunas of the American Southwest. The present study examines long–term trends (> 160 years) of fishspecies 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 ratesof spread. Among the fastest expanding invaders in the basin are red shiner (Cyprinella lutrensis), fatheadminnow (Pimephales promelas), green sunfish (Lepomis cyanellus), largemouth bass (Micropterus salmoides),western mosquitofish (Gambussia affinis) and channel catfish (Ictalurus punctatus); species considered tobe the most invasive in terms of their negative impacts on native fish communities. Interestingly, non–nativespecies that have been recently introduced (1950+) have generally spread at substantially lower rates ascompared to species introduced prior to this time (especially from 1920 to 1950), likely reflecting reductionsin human–aided spread of species. We found general agreement between patterns of species decline andextant 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 comparedto "threatened" species, which in turn have shown greater declines and smaller distributions than thosespecies not currently listed. A number of notable exceptions did exist, however, and these may providecritical information to help guide the future listing of species (i.e., identification of candidates) and theupgrading or downgrading of current listed species that are endemic to the Lower Colorado River Basin. Thestrong correlation between probability estimates of local extirpation and patterns of native species declineand present–day distributions suggest a possible proactive conservation strategy of implementing manage-ment actions for declining species prior to extreme rarity and imperilment.

Key words: Lower Colorado River, Desert fishes, Extinction, Extirpation, Invasions, Biotic homogenization.

ResumenTendencias a largo plazo de la fauna piscícola autóctona y alóctona en el sudoeste americano.— Ladegradación 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 identificalas especies autóctonas (n = 28) que exhiben los índices más altos de disminución y las especiesalóctonas (n = 48) que muestran los índices más altos de dispersión. Entre los invasores de la cuencaque 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), lagambusia (Gambussia affinis) y el pez gato (Ictalurus punctatus), especies consideradas las másinvasivas por su impacto negativo en las comunidades autóctonas de peces. Las especies alóctonasintroducidas recientemente (1950+), en general se han dispersado en tasas substancialmente más bajasque las introducidas con anterioridad (especialmente desde 1920 a 1950), probablemente reflejando unareducción en la dispersión de especies relacionada con el hombre. Encontramos concordancias entre lospatrones de disminución de las especies y el tamaño de la zona de distribución existente, y el estatus en

76 Olden & Poff

las listas oficiales del Acta de Especies Amenazadas de EE.UU. Las especies "en peligro de extinción", engeneral, 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 enla lista. Hay, sin embargo, un número de excepciones notable, que pueden proporcionar información críticapara la confección de futuras listas de especies (es decir, identificando candidatos), y para el cambio deestatus de las especies endémicas en la cuenca inferior del río Colorado. La gran correlación entre laprobabilidad estimada de extirpación local, y los patrones de disminución de las especies autóctonas y lasdistribuciones existentes sugieren una estrategia activa de conservación para implementar acciones decontrol 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: [email protected]



over half of which are considered established (Rinne& Janisch, 1995). Long–term conservation and man-agement strategies for the Lower Colorado RiverBasin require knowledge about rates of change inthe distribution of native and non–native speciesover time. Such strategies should be based on theanalysis of large–scale, long–term datasets, whichwhen combined with small–scale experimental stud-ies, will provide complementary approaches to bet-ter understanding distributional shifts of native andnon–native species and their association with al-tered environmental regimes. Broad–scale studiesprovide the foundation for proactive conservationby identifying native species declines prior to ex-treme rarity so that management efforts can beimplemented before imperilment (Anderson et al.,1995; Patton et al., 1998).

To date, evidence for the widespread replace-ment of native fish communities by non–nativespecies in the Lower Colorado River Basin hasbeen largely anecdotal and has lacked rigourousquantification. This is not to say that species’ distri-butions have not, and are not continuing to change.Rather the extent to which species’ distributionshave decreased or increased over time has onlybeen investigated for a limited number of species(mainly mainstem "big–river" species) and there-fore remains largely unknown (and not quantified)for the majority of the species pool. We addressthis research need by presenting a historical per-spective on long–term trends of native and non–native freshwater fish species distributions in theLower Colorado River Basin using an unparalleleddataset containing tens of thousands of recordscollected over a century and a half. By conductinga broad, spatio–temporal assessment of changesin patterns of species’ occurrences, we shed impor-tant insight into rates of native species decline andnon–native species expansion for the entire, present–day species pool of Lower Colorado River Basin.We address the question of whether long–termdistribution trends can act as a surrogate for localextirpation risk of native species and "test" thebiological component of the United States Endan-gered Species Act by comparing these trends tospecies’ official status. This comparison may helpaddress the question of whether governmental leg-islation is, in fact, helping identity (and conserve)those rare, endemic species that have experiencedsubstantial declines in their distributions and arecurrently rare in the Lower Colorado River.

Material and methods

The Colorado River is the primary waterway andlifeline of the American Southwest. Our study fo-cused on the lower basin of the Colorado River(hereafter called Lower CR Basin), which includesca. 26,000 km of streams and rivers between GlenCanyon Dam (located at the border between Ari-zona and Utah, U.S.A.) and the Gulf of California,and drains ca. 362,750 km2 from five states of the

Introduction

"The Colorado [River], along the greater part of itslonely and majestic way, shall be forever unvisitedand undisturbed."

Lieutenant Joseph C. Ives (1857)

Undeterred by legends of earlier expeditions thathad failed, in 1868 John Wesley Powell was suc-cessful in his first historic journey down the treach-erous Colorado River. Shortly thereafter, he statedhis strong belief that, although considerably re-mote, the western resources were meant to be"redeemed" from a state of idleness for societal use(deBuys, 2001). During the next 130 years Powell’svision was realized, and the waters of the ColoradoRiver played a pivotal role in the settlement, growthand economic development of the American South-west (Carlson & Muth, 1989). Efforts to tame theColorado River began soon after the arrival ofwestern Europeans, and today hundreds of damsand diversion structures have created one of themost controlled rivers on Earth (Fradkin, 1981).The Colorado River now provides irrigation waterfor more than 3.7 million acres (1.5 hectares) offarmland and delivers water and electrical power to30 million people in the United States and Mexico(Mueller & Marsh, 2002).

The Colorado River ecosystem has been greatlychanged during the last century both by environmen-tal alterations and by the introduction and spread ofnon–native fish species. The construction of waterdevelopment projects began in the early 1900s(Fradkin, 1981; Carlson & Muth, 1989), and by the1960s much of the mainstem river had been con-verted into a system of dams and diversions. Suchchanges continue to compromise the efficiency oflife–history adaptations that have evolved to allownative fishes to thrive in the historically harsh, fluctu-ating environment of the Colorado River Basin (Miller,1961; Minckley & Deacon, 1968, 1991). These dra-matic environmental alterations have also facilitatedthe widespread and human–assisted invasion of non–native fish species that prey on and compete withnative fishes (Minckley, 1991; Douglas et al., 1994;Marsh & Douglas, 1997; Marsh & Pacey, 2003).

The case for conservation for the Lower Colo-rado River Basin is most urgent as the distributionsof native fish species continue to decline at unprec-edented rates and the spread of non–native fishesaccelerate at an unparalleled speed (Minckley etal., 2003). Of the 31 native fish species in theLower Colorado Basin, 25 are extinct, extirpated,listed under the US Endangered Species Act(USFWS, 1999), or believed to have suffered sig-nificant declines in distribution (Minckley, 1991).Remnant native populations are highly fragmented,compounding the problem of recovery and furtherelevating the probability of extinction (Fagan et al.,2002). In contrast, the deliberate introduction ofnon–indigenous fishes in the Lower Colorado RiverBasin began in the late 1800s (Minckley, 1999) andtoday more than 90 species have been introduced,

78 Olden & Poff

United States and northwestern Mexico (fig. 1). Toexamine long–term temporal trends in native andnon–native freshwater fish faunas we used theSONFISHES database (Desert Fishes Council, http://www.desertfishes.org/na/gis/index.html). This da-tabase was developed by the tireless efforts of thelate ichthyologist W. L. Minckley and contains> 38,000 occurrence records for 132 freshwaterfish species from over 150 years of research through-out the Lower CR Basin. SONFISHES containsincidence, identity, and collection data for the com-plete holdings of major regional museum collec-tions, numerous smaller holdings, and records frompeer–reviewed and gray literature sources. Recordsare geo–referenced to within 1 km of their collectingsite in a Geographic Information System (seeUnmack, 2002 for details).

Using ArcGIS (Environmental Services ResearchInc., v. 8.3) we plotted 28,755 locality recordsfrom 1840 to 2000 (excluding occurrence recordsresult ing from art i f icial translocations andreintroductions) for 28 native species and 48 non–native species from the SONFISHES databaseonto a digital coverage of streams and rivers inthe Lower CR Basin (U.S. Geological Survey En-hanced River Reach File 2.0: http://www.usgs.gov/).We summarized the dataset in several ways toaddress the objectives of the study. Based on thelarge size and high temporal frequency of localityrecords in the dataset (see table 1) we were ableto examine species patterns for 5 time periods:pre–1960; 1960–69; 1970–79; 1980–89; and 1990–1999. Following Fagan et al. (2002), historicallocality records for native species were consideredto be those collected prior to 1980, whereas mod-ern (or extant) native records were collected be-tween 1980 and 1999. For native species, histori-cal presences and extant absences constitute trueextirpation events because modern records in thedataset are almost exclusively the result of inten-sive efforts by federal or state agencies to deter-mine species’ complete distributions prior to list-ing decisions under the U.S. or Mexican Endan-gered Species Acts (Fagan et al., 2002).

For each time period, we calculated the total riverkilometres that each species was present by sum-ming the length of the river segments (defined as asection of river delineated by two confluences) inwhich the species was recorded. Importantly, if aspecies was collected multiple times in the sameriver segment in the same time period, the length ofthe river segment was counted only once whencalculating total river kilometres. Species’ distribu-tions were estimated by dividing the total river kilo-metres that a species was present by the total riverkilometres where all species were present during thespecified time period (see table 1). This approachattempts to account for the influence of differentialsampling effort (assumed to be proportional to thenumber of records) through time. Distributions wererepresented as a percentage and are assumed toprovide an approximation for the total size of thespecies distribution in the entire Lower CR Basin.

For native species, distributional changes werecalculated by subtracting extant range size (1980–1999) from historical range size (pre–1980) anddividing by historical range size. Regression analy-ses with curve estimation (SPSS, v.11) were con-ducted to assess relationships between extant dis-tribution size (%), percent distributional change andthe estimated probability of local extirpation (asgiven for 25 species in table 1 of Fagan et al.,2002). Pairwise t–tests were used to compare dis-tributional change and extant distributions betweenspecies with different official statuses under theU.S. Endangered Species Act (data obtained fromthe United States Fish and Wildlife Service: Threat-ened and Endangered Species System, http://endangered.fws.gov, as of July 2004). For non–native species, dates of introduction were estimatedusing both table 6 of Mueller & Marsh (2002) andyear of first occurrence in the SONFISHES data-base. Extant distributions were divided by the numberof years since introduction (calculated from 2000)to estimate the rate of non–native species spread inthe basin (km·year–1). Regression analyses wereconducted to assess relationships between date ofintroduction, extant distribution size, and rate ofspread for each species.

Results

Temporal patterns of native fish distributions

Over the past century and a half, native fishes havepredominantly decreased in their spatial distribu-tions throughout the Lower CR Basin. Native fishspecies typically showed dramatic declines in thesize of their distributions; a trend, however, thatvaried among species from 100% range reduction to14% range expansion (table 2). In total, the distribu-tion of 23 species decreased and 5 species slightlyincreased. Distribution trends over time illustratethat species have exhibited differential patterns ofchange. Gila trout, Virgin River spinedace and Gilatopminnow, for example, have shown gradual reduc-tions in their distribution, whereas Coloradopikeminnow, bonytail, razorback sucker, spikedaceand Gila chub (among others) have shown punctu-ated declines. Other species appear to be occupyingrelatively constant ranges in the basin, includingroundtail chub, bluehead sucker and Sonora sucker.Extant native fishes range from being completelyabsent (i.e., 0%) to occupying an estimated two–fifths of the basin (table 2). According to our resultsusing modern locality records, five species havebeen extirpated (only Santa Cruz pupfish is trulyextinct) and 15 species currently occupy extremelysmall distributions in the basin (< 5%), whereasother species still exhibit relatively broad distribu-tions (> ca. 30%), e.g., specked dace, longfin dace,desert sucker and Sonora sucker.

With respect to identifying those species thatwarrant special concern and targeted conservationefforts, it is necessary to examine associations

http://www.desertfishes.org/na/gis/index.html

http://www.desertfishes.org/na/gis/index.html

http://www.usgs.gov/

http://endangered.fws.gov

http://endangered.fws.gov


between the probability of local extirpation andbroad–scale temporal trends in their distributions.We obtained estimates of local extirpation for 25native species from table 1 of Fagan et al. (2002),who calculated these probabilities using theSONFISHES database as the proportion of historicrecords at a 5–km reach scale having no modernrecords (e.g., if an extinct species was present in50 of 1000 pre–1980 records, its extinction prob-ability would be 0.95). We found a significant posi-tive and linear relationship between percent distri-butional decline and the probability of extirpation(R2 = 0.807, P < 0.001), indicating that nativespecies exhibiting greater declines in their distribu-tions at the whole basin scale also have a greaterrisk of local extirpation (fig. 2A). By examiningdeviations from this relationship we see that hump-back chub (code X) and Virgin River spinedace (L),for example, have a higher estimated local extirpa-tion risk compared to what is expected according totheir basin–level decline over time (large positiveresidual). In contrast, desert pupfish (B), spikedace(N), loach minnow (R) and desert sucker (U) havea much lower extirpation risk as predicted fromtheir level of distributional decline (large negativeresidual). Additionally, we found a significant nega-tive and non–linear relationship between extant dis-tribution size and the probability of local extirpation(R2 = 0.571, P < 0.001, quadratic curve), indicatingthat species with smaller present–day distributionshave a greater estimated risk of local extirpation(fig. 2B). Species such as roundtail chub (V) and

Table 1. Diagnostic properties of theSONFISHES database used in this study.Reported fields include the number of localityrecords (i.e., fish observations) and total riverkilometres during different time periods (T): N.Native; nN. Non–native; TRkm. Total riverkilometres where all species were observed.

Tabla 1. Propiedades de diagnóstico de labase de datos SONFISHES utilizada en esteestudio. Los campos que se presentanincluyen el número de registros de localidad(observaciones de peces) y el total dekilómetros de río a lo largo de distintosperíodos de tiempo (T): N. Autóctonos; nN.Alóctonos; TRkm. Kilómetros totales de ríodonde se observaron todas las especies.

Records

T N nN 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 5,389 5,334 6,491

Total 15,763 12,992 14,380

Fig. 1. Map of the Lower Colorado River Basin showing the 28,755 locality records from theSONFISHES 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 dela base de datos SONFISHES utilizada en este estudio. El recuadro muestra la situación de losprincipales drenajes del río.

W E

N

SColoradoLittle

ColoradoSalt

Gila

Sonora

UnitedStates

80 Olden & Poff

Sonora sucker (Y) have greater probability of extir-pation than that expected from their present distri-butions in the basin, whereas the local extirpationprobabilities of loach minnow (R), headwater chub(AA) and Little Colorado spinedace (BB) are muchlower than is suggested from their current distribu-tions. Visual examination of this figure suggests athreshold relationship where species with extantdistributions greater than 10% are at much lowerrisk to local extirpation (probability < 0.5) comparedto those species will extremely small distributions.

Comparisons of species distributional changeand extant distribution size with categories of offi-cial status under the U.S. Endangered Species Act(provided in table 2) also revealed interesting find-ings (fig. 3). With increasing risk category (i.e., notlisted–threatened–endangered), we found averagedistributional decline to become larger and extantdistribution size to become markedly smaller. En-dangered species exhibit significantly greater distri-butional declines compared to threatened species(t1,15 = 2.93, P = 0.01) and to those species notlisted (t1,20 = 4.33, P < 0.001). Similarly, endan-gered species exhibit significantly smaller extantdistributions compared to threatened species(t1,15 = –4.78, P < 0.001) and to those species notlisted (t1,20 = –4.30, P < 0.001). Extant distributionsof threatened species were marginally smaller thanspecies not listed (t1,11 = –1.90, P = 0.08), althoughthe rate of distributional decline did not differ.

For illustrative purposes figure 4 shows histori-cal and extant distributions of three native speciesthat exhibit markedly different % decline over time

and have different ESA statuses – bonytail (Endan-gered, 87.5% decline), spikedace (Threatened,45.9% decline) and specked dace (Not Listed, 16.5%decline). Historical populations of bonytail in theSalt River, Gila River and mainstem Colorado Riverhave been lost, and present–day distributions arerestricted to Lake Mohave above Davis Dam.Spikedace populations were once present in therivers Salt, Verde, Gila and San Pedro, but are nowconfined to only small stretches of the Gila Riverand Verde River. Specked dace was historicallyabundant and continuous throughout the basin, butits present–day distribution is greatly reduced andhighly 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 thesize of their distributions over time (table 3). At theextreme, fathead minnow, green sunfish and redshiner exhibit the greatest rates of invasion, spread-ing at over 50 km·year–1 since their dates of intro-duction. As expected, we found a strong, positiverelationship between the rate of spread and extantdistribution size (R2 = 0.874, P < 0.001), indicatingthat fast spreading non–native species are gener-ally more broadly distributed in the basin (fig. 5A).A number of non–native species are much morebroadly distributed in the basin as what is expectedbased 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

Fig. 2. Comparisons of percentages of distributional decline (A), extant distribution size (B) andprobability of local extirpation of native fishes in the Lower Colorado River Basin. Least–squaresregression lines are represented. Letter codes refer to native species in table 2.

Fig. 2. Comparaciones entre porcentajes de disminución distribucional (A), tamaño de la distribuciónexistente (B) y probabilidad de extirpación local de peces autóctonos en la cuenca inferior del ríoColorado. Se representan las líneas de regresión de mínimos cuadrados. Los códigos de letras serefieren a las especies autóctonas de la tabla 2.

1.0

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A B


Table 2. Temporal patterns of native fish distributions in the Lower Colorado River Basin expressedas a percentage of the total kilometres of rivers where all species were observed for each timeperiod. Nomenclature follows Nelson et al. (2004): C. Code, labels in figure 2; S. Species' officialfederal 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 inspecies’ distribution. Note that P. lucius, C. macularius, M. coriacea and G. robusta jordani are notextinct from the lower basin, but are estimated as exhibiting a 100% decline because the databasedoes not contain recent records of their occurrence.

Tabla 2. Patrones temporales de distribución de peces autóctonos en la cuenca inferior del ríoColorado, expresadas en porcentajes del total de kilómetros de río donde se observaron todas lasespecies 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 especieen peligro; si no hay estatus la especie no se encuentra en la lista); ER. Rango existente en porcentajede distribución de las especies basada en registros entre 1981–1999; D. Disminución, cambio deporcentaje 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 unadisminución del 100% debido a que la base de datos no contiene registros recientes de su presencia.

Temporal trends

Species C S <1960 1960s 1970s 1980s 1990s ER D

Colorado pikeminnow (Ptychocheilus lucius) A E 4.4 0.0 0.0 0.0 0.0 0.0 100.0

Desert pupfish (Cyprinodon macularius) B E 3.2 0.0 0.0 0.0 0.0 0.0 100.0

Moapa dace (Moapa coriacea) C E 1.0 0.9 0.0 0.0 0.0 0.0 100.0

Pahranagat roundtail chub (Gila robusta jordani) D E 1.2 1.1 1.0 0.0 0.0 0.0 100.0

Santa Cruz pupfish (Cyprinodon arcuatus) E X 0.7 0.7 0.0 0.0 0.0 0.0 100.0

Bonytail (Gila elegans) F E 8.1 2.4 2.0 0.6 0.8 0.5 87.7

Gila trout (Oncorhynchus gilae gilae) G E 1.9 2.0 1.7 0.4 0.0 0.3 84.0

Woundfin (Plagopterus argentissimus) H E 3.5 2.0 0.8 0.5 0.2 0.6 78.9

White River spinedace (Lepidomeda albivallis) I E 4.2 1.9 0.0 0.7 0.0 0.6 74.3

White River springfish (Crenichthys baileyi) J E 5.5 6.1 0.0 1.2 0.0 1.0 71.1

Flannelmouth sucker (Catostomus latipinnis) K 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) M E 11.9 2.4 4.0 3.5 2.9 3.7 49.7

Spikedace (Meda fulgida) N T 12.9 2.8 4.5 3.4 4.9 4.2 45.9

Virgin River roundtail chub (Gila seminuda) O E 2.6 2.8 1.0 0.7 1.6 1.4 42.5

Gila topminnow (Poeciliopsis occidentalis) P E 8.3 2.5 1.7 3.6 3.9 3.7 36.8

Apache trout (Oncorhynchus gilae apache) Q T 4.0 6.1 5.7 2.1 4.6 4.5 26.9

Loach minnow (Rhinichthys cobitis) R T 9.8 3.8 7.0 5.3 6.8 5.8 17.9

Speckled dace (Rhinichthys osculus) S 52.8 50.3 42.6 32.2 40.6 40.6 16.5

Gila chub (Gila intermedia) T PE 14.0 4.0 4.6 6.2 10.4 7.7 15.9

Desert sucker (Catostomus clarkii) U 45.4 43.6 39.8 40.4 37.0 38.3 13.5

Roundtail chub (Gila robusta) V 18.4 16.2 12.9 16.6 15.6 17.7 6.2

Bluehead sucker (Catostomus discobolus) W 5.6 7.9 13.2 6.0 13.0 11.1 3.5

Humpback chub (Gila cypha) X E 0.6 1.5 3.0 3.0 1.4 2.5 –6.1

Sonora sucker (Catostomus insignis) Y 25.9 28.5 25.4 28.5 29.5 29.3 –8.2

Longfin dace (Agosia chrysogaster) Z 34.9 28.1 33.5 45.4 46.2 40.9 –11.4

Headwater chub (Gila nigra) AA 3.1 2.2 1.9 2.3 2.3 2.3 –12.6

Little Colorado spinedace (Lepidomeda vittata) BB T 1.5 3.0 1.4 3.0 3.9 3.6 –14.1

82 Olden & Poff

two latest invaders to the basin, blue tilapia (9) andflathead catfish (6), were found to have very fastrates of spread, although they are still limited intheir distribution due to their short invasion history.

Although we expected the positive relationship infigure 5A because extant distribution size was usedto calculate spread, the unexplained variation inthis relationship can be attributed, in part, to thelack of a significant negative relationship betweenthe year of introduction and rate of spread(R2 = 0.051, P = 0.124) (fig. 5B). Interestingly, wefound a significant negative relationship betweenyear of introduction and extant distribution size(R2 = 0.243, P < 0.001) (fig. 5C). Visual examina-tion of this figure suggests a threshold relationshipwhere non–native species introduced after 1950have limited distributions (< 10%) whereas specieswill longer invasion histories in the basin have abroad range of distribution sizes (10–45%). Fur-ther, a number of species deviate from this relation-ship, indicating that species with long invasionhistories do not necessarily have large extant distri-butions in the basin, e.g., yellow bass (35), whitecrappie (36), brown bullhead (42). Of note is thatthe top 5 fastest spreading non–native species(species 1–5 in table 3) were all introduced be-tween 1920 and 1950 (fig. 5B) and have muchgreater present–day distributions than expectedbased on their length of invasion history (fig. 5C).

Discussion

Distributions of native and non–native fishes havechanged dramatically over the past century(Courtenay et al., 1984; Moyle, 1986; Gido & Brown,1999), resulting in the biotic homogenization of fishfaunas throughout North America (Rahel, 2000;Olden & Poff, 2004; Taylor, 2004). Biogeographicstudies that explore long–term trends in speciesdistributions can provide important insight into pre-dicting the identity of those species declining intheir distribution and under risk of extinction (e.g.,Williams et al., 1989; Reinthal & Stiassny, 1991;Anderson et al., 1995; Patton et al., 1998). Moregenerally, such studies can help understand howtemporal changes in native species distributionsrelate to patterns of non–native species distribu-tions, thus providing correlative insight into broad–scale implications of biological invasions.

Temporal patterns of native fish distributions

The American Southwest contains among the mostthreatened aquatic systems in North America, anddespite early warnings (Dill, 1944; Miller, 1946), theunique, highly endemic, native fish fauna of theLower Colorado River Basin have become increas-ingly imperilled over time. Our study provides quan-titative estimates of distributional trends in nativefishes and show significant declines of many spe-cies over both historical and recent times. Thesefindings provide empirical support for the observa-

tional hypothesis of Mueller & Marsh (2002) whopostulated that native fishes rapidly declined be-tween 1890 and 1935 because of intensive watermanagement practices and the introduction of com-mon carp, bullhead and channel catfish, which wasthen followed by a prolonged period when remnantcommunities gradually disappeared after the con-struction of Roosevelt, Hoover, Imperial, and anumber of other dams that caused remarkablehydraulic and physical change to the basin.

Our results indicate the highest rate of declinesin a number of native fish species that have previ-ously identified as imperilled in the basin, includinga number of "big–river" fishes such as Coloradopikeminnow, razorback sucker, bonytail andflannelmouth sucker; and species inhabiting mar-ginal spring and stream habitats such as the desertpupfish and Gila topminnow (Minckley & Deacon,1991; Mueller & Marsh, 2002). The last wild Colo-rado pikeminnow was caught in 1975 in the LowerColorado River; bonytail likely persist only in LakeMohave; and although annual spawning occurs,razorback sucker populations consist largely of old

Fig. 3. Comparisons of percentages ofdistributional decline and extant distributionsize of native species classified as classifiedunder the U.S. Endangered Species Act: Nl.Not listed; T. Threatened; E. Endangered. (Barsrepresent means and whiskers represent 1standard error.)

Fig. 3. Comparaciones entre los porcentajesde disminución y de tamaño de la distribuciónexistente de peces autóctonos clasificadossegún el Acta de Especies en peligro deExtinción de EE.UU.: Nl. No están en la lista;T. Amenazadas; E. En peligro. (Las barrasrepresentan las medias y las prolongacionesrepresentan un error estándar igual a 1.)

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Table 3. Temporal patterns of non–native fish distributions in the Lower Colorado River Basin expressedas the percentage of the total kilometres of rivers where all species were observed for each timeperiod. Nomenclature follows Nelson et al. (2004): C. Code, labels in figure 5; I. Year of introductionor 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 Coloradoexpresadas como el porcentaje del total de kilómetros de río donde se observaron todas las especiesen 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 dedistribución de las especies basada en los registros de 1980–1999; S. Tasa de dispersión en km/año.

Temporal trends

Species C I <1960 1960s 1970s 1980s 1990s ER S

Fathead minnow (Pimephales promelas) 1 1950 1.9 7.7 21.8 28.7 39.2 39.3 74.1

Green sunfish (Lepomis cyanellus) 2 1937 11.4 16.9 19.8 30.9 44.1 42.0 62.9

Red shiner (Cyprinella lutrensis) 3 1950 0.9 17.4 18.7 27.4 27.9 28.9 54.6

Western mosquitofish (Gambusia affinis) 4 1922 15.4 16.5 19.2 28.1 27.5 31.3 37.9

Largemouth bass (Micropterus salmoides) 5 1935 9.2 15.3 11.6 20.6 19.9 23.6 34.2

Flathead catfish (Pylodictis olivaris) 6 1962 1.0 0.6 3.1 9.3 9.3 9.5 23.7

Bluegill (Lepomis macrochirus) 7 1937 8.0 8.2 7.2 12.8 12.7 15.6 23.4

Channel catfish (Ictalurus punctatus) 8 1892 11.2 15.1 14.6 27.5 15.4 25.2 22.0

Blue tilapia (Oreochromis aureus) 9 1978 0.0 0.0 0.3 5.9 1.0 4.8 20.7

Yellow bullhead (Ameiurus natalis) 10 1899 5.7 7.6 10.9 16.3 21.8 21.9 20.4

Common carp (Cyprinus carpio) 11 1881 14.0 16.5 15.8 21.7 21.2 25.1 19.9

Smallmouth bass (Micropterus dolomieui) 12 1942 2.8 3.5 5.2 10.8 10.1 11.1 18.0

Rainbow trout (Oncorhynchus mykiss) 13 1900 12.4 18.7 23.3 16.7 20.3 19.1 18.0

Threadfin shad (Dorosoma petenense) 14 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) 16 1959 0.4 0.8 1.6 5.6 1.5 5.2 11.9

Brown trout (Salmo trutta) 17 1924 2.4 7.3 8.6 7.1 10.3 8.9 11.0

Goldfish (Carassius auratus) 18 1944 0.1 6.8 1.4 5.5 2.4 6.3 10.6

Plains killifish (Fundulus zebrinus) 19 1950 0.0 1.3 4.6 4.3 2.2 4.8 9.0

Black crappie (Pomoxis nigromaculatus) 20 1936 7.5 2.5 4.4 4.7 2.9 5.6 8.3

Black bullhead (Ameiurus melas) 21 1904 9.3 11.2 6.8 7.7 6.7 8.2 8.1

Sailfin molly (Poecilia latipinna) 22 1950 1.0 2.7 1.4 5.1 0.7 4.2 7.9

Brook trout (Salvelinus fontinalis) 23 1920 2.6 4.2 3.9 4.3 7.6 6.3 7.4

Walleye (Sander vitreus) 24 1971 0.0 0.1 0.3 0.8 1.5 1.8 5.7

Rio Grande cichlid (Herichthys cyanoguttatus) 25 1996 0.0 0.0 0.0 0.0 0.3 0.2 5.5

Arctic grayling (Thymallus arcticus) 26 1965 0.0 0.9 0.8 0.8 2.2 2.0 5.3

Cutthroat trout (Oncorhynchus clarkii) 27 1937 1.3 1.3 0.6 2.2 3.2 3.3 5.0

Northern pike (Esox lucius) 28 1969 0.0 0.0 1.3 1.5 0.1 1.3 4.0

Redside shiner (Richardsonius balteatus) 29 1950 0.0 0.8 1.1 2.4 0.0 2.0 3.8

Redear sunfish (Lepomis microlophus) 30 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) 32 1965 0.0 0.0 0.3 1.4 1.0 1.1 3.1

Rock bass (Ambloplites rupestris) 33 1962 0.0 0.0 0.0 0.4 0.5 0.7 1.8

84 Olden & Poff

Temporal patterns of non–native fish distributions

The establishment of non–native fish species hassubstantially changed native fish community struc-ture in southwestern rivers (Minckley & Deacon,1968, 1991; Meffe, 1985; Rinne & Minckley, 1991).While the total number of non–native fishes contin-ues to increase across the U.S. (Gido & Brown,1999; Rahel, 2000; Meador et al., 2003), quantita-tive estimates of distributional changes are lackingfor most fish, and such analyses are rarely con-ducted at large temporal and spatial scales that arerequired to properly understand these processes.Our study contributes to a better understanding ofthe shear magnitude in which non–native specieshave spread throughout the Lower Colorado RiverBasin over the past century and points to thoseinvaders that have exhibited considerable rates ofexpansion since their introduction. This informationprovides a scientific basis for the management offast spreading species and enhanced educationtargeted specifically to reducing their future intro-duction by humans.

Perhaps our most striking result is that red shiner,fathead minnow, green sunfish, largemouth bass,western mosquitofish and channel catfish are theamong the fastest expanding invaders in the ba-sin, and these species have also been identifiedby expert ichthyologists as having the greatestnegative impacts on native fish communities(Hawkins & Nesler, 1991; J. D. Olden, unpub-lished survey data). Recent studies have furthersupported the significant ecological effects of these

Temporal trends

Species C I <1960 1960s 1970s 1980s 1990s ER S

Guppy (Poecilia reticulata) 34 1950 0.0 1.3 0.5 0.8 0.4 0.9 1.6

Yellow bass (Morone mississippiensis) 35 1931 0.4 0.4 0.3 1.2 0.1 1.1 1.5

White crappie (Pomoxis annularis) 36 1934 1.8 0.4 0.0 0.1 0.7 0.6 0.8

Shortfin molly (Poecilia mexicana) 37 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) 39 1960 0.0 0.1 0.0 0.1 0.0 0.1 0.2

Bigmouth buffalo (Ictiobus cyprinellus) 40 1964 0.0 0.5 0.2 0.1 0.1 0.1 0.2

Smallmouth buffalo (Ictiobus bubalus) 41 1950 0.0 0.5 0.3 0.0 0.1 0.1 0.1

Brown bullhead (Ameiurus nebulosus) 42 1910 6.6 1.5 0.0 0.0 0.0 0.0 0.0

Convict cichlid (Archocentrus nigrofasciatus) 43 1955 0.0 1.5 0.0 0.0 0.0 0.0 0.0

Grass carp (Ctenopharyngodon idellus) 44 1976 0.0 0.0 1.8 0.0 0.0 0.0 0.0

Black buffalo (Ictiobus niger) 45 1966 0.0 0.4 0.2 0.0 0.0 0.0 0.0

Warmouth (Lepomis gulosus) 46 1958 0.2 0.0 0.0 0.0 0.0 0.0 0.0

Spotted bass (Micropterus punctulatus) 47 1956 0.6 0.5 0.1 0.0 0.0 0.0 0.0

Yellow perch (Perca flavescens) 48 1951 0.6 0.2 0.0 0.0 0.0 0.0 0.0

Table 3. (Cont.)

adults with no evidence of recruitment (Minckley,1991). Other, comparatively less studied, speciesalso experienced significant declines over time,including spikedace and woundfin. Similarly, loachminnow has seen dramatic declines when com-pared to historical records, although there is someevidence that its distribution has remained fairlyconstant over the recent decades. This finding issupported by recent work showing the local stabil-ity of remnant loach minnow populations in Ari-zona (Marsh et al., 2003). In contrast to the manyspecies that have exhibited significant declines intheir distributions, longfin dace, desert sucker andSonora sucker are presently abundant throughoutthe basin and appear to have maintained relativelystable distributions over time. Finally, temporaltrends and present–day sizes of species’ distribu-tions were highly correlated to estimates of localextirpation risk for the native fishes. This suggeststhat long–term studies conducted at the drainagescale might provide a coarse–level surrogate foridentifying those species that are most likely toextirpated at the local reach scale.

In summary, a number of explanations are pos-sible to describe the distributional changes ob-served in our study. By explicitly linking patterns ofenvironmental degradation and non–native speciesdistributions to patterns of native species distribu-tions, we could gain greater insight into potentialmechanisms of native imperilment and thus bettertease apart the synergistic manner in which thesestresses are threatening native faunas in the LowerColorado River Basin (Olden et al., in press).


introductions of gamefish or forage species outsidetheir native ranges (Courtenay & Moyle, 1996), apattern that reflects both a saturation of gamefishspecies in many drainages and a heightened aware-ness by fisheries biologists of the problems associ-ated with non–native species (Rahel, 1997). How-ever, inadvertent introductions (e.g., aquarium tradereleases: Padilla & Williams, 2004) and unauthor-ized introductions (Rahel, 2004) by the public con-tinue, which likely explain the notable exceptions tothis general pattern – blue tilapia and flatheadcatfish – both species exhibiting very high fasterrates of spread since its introduction in recentdecades.

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 asvectors of exotic parasites, including the Asian fishtapeworm (Clarkson et al., 1997).

Of particular interest is that non–native speciesintroduced after 1950 have generally spread atsubstantially lower rates as compared to non–native introduced prior to this time (especially1920–1950), and consequently occupy muchsmaller distributions. The most optimistic explana-tion for this threshold pattern is that recent decadeshave seen declines in U.S. government–sanctioned

Fig. 4. Maps of historical and extant distributions of three native fishes exhibiting markedly differentpercentage 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 riversegments where the species was recorded present during the time period. See inset of figure 1 forlocations of major river drainages.

Fig. 4. Mapas de las distribuciones históricas y existentes de tres peces autóctonos mostrandoporcentajes distintos de disminución a lo largo del tiempo y con distintos estatus reconocidos en el Actade Especies Amenazadas de EE.UU.: A. Carpita elegante (Gyla elegans), en peligro, 87,7% dedisminución; 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 seccionesdel río donde se registró la especie a lo largo del periodo de estudio. Ver el recuadro de la figura 1 paralas localizaciones de los principales drenajes del río.

A B C

Historical(pre–1980)

Extant(1980–1999)

86 Olden & Poff

for common carp (range expansion) and whitecrappie, rock bass and yellow perch (range declinesor low rates of spread). In contrast to distributionalchanges, comparisons of extant distribution sizesshowed remarkable similarity for 15 species sharedby the Lower Colorado River basin and plain streamsin Oklahoma and Kansas (Gido et al., 2004). Insummary, these comparisons suggest that a numberof non–native species exhibit similar distribution sizesin these different ecoregions, yet the rate at whichthey have spread to obtain their distributions differs(likely a result of different rates and timing of humanintroductions).

Conservation and management implications fornative fishes

The United States Endangered Species Act (ESA)of 1973, together with other environmental legisla-

Fig. 5. Comparisons of extant distribution size percentages, rate of spread (km/year) and year ofintroduction of non–native fishes in the Lower Colorado River Basin. Least–squares regression linesare 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. Serepresentan las líneas de regresión de mínimos cuadrados. Los números indican las especiesalóctonas de la tabla 3.

Results from our study show both similarities anddifferences to other long–term studies of fish inva-sions conducted in Great Plains streams of Wyo-ming (Patton et al., 1998) and Oklahoma and Kan-sas (Gido et al., 2004). Great Plains stream aresimilar to desert streams in the American Southwestin that they present harsh environmental conditionsand disturbance regimes (Dodds et al., 2004), andthey have been invaded by a relatively large numberof non–native species as compared to other regionsof the United States (Gido & Brown, 1999), thusmaking it suitable to compare rates of spread be-tween these regions. Based on species common toall three regions, our study found that red shiner,fathead minnow, green sunfish, largemouth bass,channel catfish and black bullhead exhibit relativelyhigh rates of spread, whereas Patton et al. (1998)found that these species’ distributions were decliningin Wyoming. However, similar patterns were found

A B

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tion, has played an important role in the effort toconserve native fishes in the Lower Colorado Basin(Minckley et al., 2003). Although in principle ESAdecisions are based on the best biological informa-tion, many factors other than biology, includingsocioeconomic and political issues, influence mostplans and projects. We believe our study providessome new insight into the biological component ofthe listing process for the Lower Colorado River byrelating long–term species’ distributional trends totheir federal status under the ESA. This comparisonmay help address the question of whether the ESAis, in fact, helping identity (and conserve) thoserare species experiencing substantial declines intheir distributions. Our results show good agree-ment between patterns of species decline and ex-tant distribution sizes and expectations based ontheir official status. "Endangered" species have gen-erally experienced greater declines in their distribu-tions compared to "threatened" species, which inturn have shown greater declines than those spe-cies not currently listed. Likewise, non–listed spe-cies have three times larger extant distributionsthan "threatened" species, which in turn have twotime larger distributions than "endangered" species.These patterns are reassuring, in that they supportthe biological underpinnings of the ESA for thenative species of this region.

Interestingly, although general patterns were inagreement we did find a number of notable excep-tions, which we believe can provide critical informa-tion to help guide the future listing of species (i.e.,identification of candidates) and the upgrading ordowngrading of current listed species that are en-demic to this region. For example, based on tempo-ral trends and extant distribution sizes alone, ourresults suggest that 3 non–listed species might meritconsideration for listing under ESA: headwater chubcould be a candidate for threatened status (on thebasis of extant distribution), and flannelmouth suckerand Virgin River spinedace could be candidates forendangered status. Our results also suggest thatApache trout have experienced significant declinesand exhibit extant distributions that correspond moreclosely with “endangered” species and therefore couldbe considered for upgrading from its threatenedstatus. Other factors not evident from distributionaldata support these ideas, e.g., Apache trout are alsoat high risk to the effects of intensive hybridizationwith non–native trout (Dowling & Childs, 1992) aswell as those arising from hatchery practices. It isvery interesting to note that Apache trout was for-merly listed as endangered but was downlisted in1975 to threatened status to facilitate a manage-ment program that included recreational angling(Behnke, 1992). This is an excellent example wheresocioeconomic issues have likely outweighed spe-cies biology in the ESA listing process.

Concerning potential data limitations

When analyzing compiled data that has not beensystematically collected, as is the case in this study,

it is important to consider the effects of samplingbias, spatial scale and data resolution when inter-preting the results. Sampling intensity (i.e., as indi-cated by the number of records) increased throughtime for both native and non–native species. Conse-quently, our study provides minimum estimates ofnative species decline because sampling intensity inrecent decades always exceeded that of previousdecades, whereas the opposite is true for non–nativespecies where rates of spread may be over–esti-mated. Spatial scale must also be considered whenusing historic data to examine species declines.Patton et al. (1998) found greater changes in spe-cies distributions at the reach scale compared to thedrainage scale for 37 species in Wyoming, whichsuggests that smaller–scale analyses of temporaltrends may provide an over–estimates of speciesdeclines. Lastly, although species presence data arenot as informative as abundance data for assessingtemporal trends, local population fluctuations mayconfound trend interpretations, especially in for highlyvariable desert streams characteristic of the Ameri-can Southwest (Eby et al., 2003). While we acknowl-edge the above data limitations and issues of sam-pling and spatial scale, we believe our analyses areappropriate for this region at a scale of study rel-evant to broad–scale conservation and managementplanning. Indeed, a number of studies have alreadyillustrated the utility of the SONFISHES database foraddressing pressing fish conservation issues in theAmerican Southwest (e.g., Fagan et al., 2002;Unmack & Fagan, 2004) and our study is the first touse this powerful dataset to address broad–scalechanges in fish distributions.

Conclusion

The extensive regulation of the Lower ColoradoRiver Basin threatens native fish faunas by drasti-cally altering natural flow, temperature and sedi-ment regimes, and promoting the establishmentand spread of non–native species. Results fromthis study provide a reach–scale examination ofdistributional trends of the fishes of the LowerColorado River Basin over the past century. Thesetrends indicate high priorities for conservation andmanagement efforts by identifying declining spe-cies before they are lost forever. However, beforemanagement plans can be implemented we mustfirst recognize and quantify the degree to whichnative species are declining and non–native spe-cies are spreading across riverine landscapes.

Acknowledgements

This research would not of been possible without thetireless efforts of the late W. L. Minckley, who dedi-cated his life to the conservation of desert fishes inthe American Southwest. We thank Peter Unmack forgraciously providing the SONFISHES database andKevin Bestgen for his continued insights on Colorado

88 Olden & Poff

River fishes. Comments from the Editor and an anony-mous reviewer greatly improved the final paper. Fund-ing for this research was provided by the AmericanMuseum of Natural History (Theodore Roosevelt Me-morial Scholarship), the American Fisheries Society(William Trachtenberg Scholarship) and Ocean Jour-ney (Conservation Grant) to JDO, and U.S. EPASTAR Grant #R828636 to NLP.

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Molero–Baltanás, R., Gaju–Ricart, M. & Bach de Roca, C., 2005. Ctenolepisma almeriensis n. sp. ofLepismatidae (Insecta, Zygentoma) from south–eastern Spain. Animal Biodiversity and Conservation,28.1: 91–99.

AbstractCtenolepisma 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. Thisspecies was determined previously as Ctenolepisma lineata (Fabricius, 1775), which is widespread over thesouth–western Palaeartic region. The main difference between the two species is the setation of thoracicsternites. In each bristle–comb of the mesosternum and the metasternum, macrosetae are arranged in asingle row in C. lineata and in two parallel rows in C. almeriensis n. sp. In the prosternum, the first speciesshows 1–2 irregular lines of macrosetae per comb, and the new species shows 2–3 lines. Based on otherparameters of setation, a discriminant analysis was carried out to separate a group of Spanish specimensof C. lineata from another group of specimens of the new species. This analysis demonstrated the validityof the occurrence of double or single lines of macrosetae in thoracic sternites to distinguish between thetwo species.

Key words: Ctenolepisma almeriensis n. sp., Ctenolepisma lineata, Spain, Thysanura, New species, Aridregions fauna

ResumenCtenolepisma almeriensis sp. n. de Lepismatidae (Insecta, Zygentoma) de España suroriental.— Sedescribe Ctenolepisma almeriensis sp. n., distribuida por el sureste de la Península Ibérica. Previamenteesta especie se había identificado como Ctenolepisma lineata (Fabricius, 1775), extendida por el Paleárticosuroccidental. La principal diferencia entre ambas especies reside en la quetotaxia de los esternitostorácicos: 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 deC. lineata consta de 1–2 líneas irregulares, por 2–3 filas en la nueva especie. Se ha realizado un análisisdiscriminante para separar, con base en otros parámetros de la quetotaxia, un grupo de especímenesespañoles de C. lineata de otro grupo encuadrable a priori en la nueva especie, demostrándose que lapresencia de filas simples o dobles de macroquetas en los esternitos torácicos representa una característicaválida 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. deCórdoba. 14014–Córdoba, España (Spain); Carmen Bach de Roca, Dept. de Biología Animal, Vegetal yEcología, Fac. de Ciencias, Univ. Autónoma de Barcelona, 08193–Bellaterra (Barcelona), España (Spain).

Corresponding author: R. Molero Baltanás. E–mail: [email protected]

Ctenolepisma almeriensis n. sp. ofLepismatidae (Insecta, Zygentoma)from south–eastern Spain

R. Molero–Baltanás, M. Gaju–Ricart & C. Bachde Roca


92 Molero–Baltanás et al.

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, atotal of 100 specimens were selected, 50 fromeach species (25 males and 25 females), eachfrom a different sample and locality. Statisticalanalysis included six quantitative variables ineach specimen, resulting in a total of 600 data.

A standardized principal component analysiswas performed to obtain combinations of the sixvariables which account for most variability in thedata. The most useful variables were then in-cluded in a discriminant analysis to determinewhether C. lineata and C. almeriensis were signifi-cantly different. Mann–Whitney U–tests were alsoconducted to compare medians of the four groups.

Variables and their abbreviations used in thediscriminant analysis for the differentiation be-tween C. lineata and C. almeriensis: N–notum.Number of macrosetae of a posterolateral comb ofthe metanotum; N–pros. Number of macrosetae ofa posterolateral comb of an antedistal comb of theprosternum; N–meso. Number of macrosetae of aposterolateral comb on the mesosternum; N–meta.Number of macrosaeta of a posterolateral combon the metasternum; N–uro. Number of macrosetaeof a lateral comb of the urosternite IV; D/a[Mt].Ratio distance between lateral combs of urosterniteIV / width of a comb.

Introduction

Ctenolepisma lineata (Fabricius, 1775) is a wide-spread species of Lepismatidae native to thesouth of Europe and introduced in other regionsand continents. Following revision of materialthat had been determined as this taxon fromdifferent countries, notable variability has beendetected, to the point that it is reasonable to statethat C. lineata is not one but a group of species.Several forms have been found within the IberianPeninsula, the most widespread considered hereas the typical C. lineata. A different form whichoccurs in the south–east Spain is described hereas a new species.

Material and methods

As usual in this order, specimens were fixed inalcohol, and many were dissected and mounted inTendeiro medium for microscopic observation toverify identification. The studied material is depos-ited in the following institutions: MNCN. MuseoNacional de Ciencias Naturales (Madrid, Spain);UCO. Dept. de Zoología, Univ. of Córdoba (Córdoba,Spain).

Some specimens have been studied and pub-lished previously: (a) included in Molero–Baltanás

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.

0.2 mm

0.2 mm

0.2 mm

0.2 mm

0.2 mm0.2 mm

1 2 3

4

5

6


Results and discussion

Description of Ctenolepisma almeriensis n. sp.

Studied Material

Holotype: Almería, Dalías, Dos Hermanas Peak, GádorMountains, 1,800 m, 23 III 89, one male (MNCN, ref.9493). Allotype: 1 female collected in the same local-ity and date, with 1 male, 2 females and a youngspecimen, 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 and4 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 and3 females (UCO, ref. Z0433) (a); El Ejido (PuntaSabinal), 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 youngspecimen (UCO, ref. Z0411) (a); Mojácar, near thebeach, 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 malesand 1 female (UCO, ref. Z0317) (a); Níjar, Cabo deGata, 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 malesand 4 females (UCO, ref. Z0424) (a); Níjar, Pozo delos 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 malesand 3 females (UCO, ref. Z0561); Purchena, 21 VI 86,2 males and 1 female (UCO, ref. Z0211) (a); Roquetasde Mar, 06 IV 85, 1 female (UCO, ref. Z0506); Serónto 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); TabernasDesert, 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, Filabresmountains, 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 youngspecimen (UCO, ref. 0413) (a).

Murcia: Blanca, Pila mountains, 30 III 93, 1 maleand 1 female (UCO, ref. Z2038); Mazarrón, 21 VI 86,3 males and 2 females (UCO, ref. Z1417) (b); Mazarrónto 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 thebase of pine–trees or Juniperus shrubs. The habitatis similar to that of C. lineata in Spain, but the newspecies appears to tolerate a higher degree ofaridity. It is found from sea level to 2,000 m atSierra de Gádor and Sierra de los Filabres in theprovince of Almería.

C. almeriensis n. sp. is mainly seen in the aridbio–geographic province named "Murciano—Almeriense" (Rivas–Martínez, 1987) in south–east-ern Spain, being more frequent in the south (prov-ince of Almería) where the rainfall is lower. It spreadsover the Spanish provinces of Almería, Murcia,Alicante and Valencia, always on the Mediterra-nean slope. The species takes its name from theprovince where it is most abundant.

Description

Body length of females up to 13.2 mm, males up to12 mm. Fusiform and relatively robust body, thoraxslightly wider (up to 3.5 mm) than the abdomenbase. Faint to distinct epidermic pigment, usuallyviolet–brown, with a variable pattern of distribution;this pigment can be more intense on the hind partof body, on the basal or distal parts of the articles ofthe appendages, and on the head, or it can benearly uniformly extended (except for a lighter to-nality ventrally). Scales dorsally brown, yellowishbrown, dark greyish, silvery grey or greyish–brown,darkish and often with iridescence; they can drawan almost uniform pattern of distribution or can bearranged in alternately light (yellowish brown) anddark (greyish) longitudinal lines, as in other speciesof the genus.

Setation of head as usual for the genus. Eyesblack, composed of about 12–13 ommatidia. An-tennae longer than body, up to 15 mm (maximumpreserved). Maxillary palp with long articles, thedistal one 0.9–1.2 times longer than the antedistaland 4.7–9 times longer than wide (fig. 1). Distalarticle of the labial palp more or less unilaterallydilated, shorter to slightly wider at the apex thanlong; it always bears five sensory papillae arrangedin a single row (fig. 2).

Pronotum with 8–9 + 8–9, mesonotum with(9)10–11 pairs and metanotum with 9–10 + 9–10lateral bristle–combs of 3–7 macrosetae each.Trichobothrial areas of the nota situated on the lastand penultimate lateral combs in meso– andmetanotum, and on the last and the antepenulti-mate combs in the pronotum. Posterolateral bris-tle–combs usually with 7–12 macrosetae each.


Figs. 7–9. Ctenolepisma almeriensis n. sp., holotype. Tibiae showing distribution of plumose macrosetaeand 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 macroquetasplumosas y de las espinas agudas: 7. Tibia I; 8. Tibia II; 9. Tibia III.

Thoracic sterna as shaped in figs. 3–6, verysimilar to those of C. lineata, except for the featuresobserved 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 asingle row. In the prosternum they are arranged in2–3 irregular almost parallel lines (fig. 3), and on themeso– and metasternum there are usually two moreor less parallel and very close rows (figs. 4–5). Thenumber of setae per "comb" is variable, but on theaverage it ranges from 8 to 20. The highest num-bers of macrosetae are often observed in theantedistal combs. The number of combs on eachsternite is also variable; there are usually 4–5 pairsin the prosternum, 2–3 pairs in the mesosternumand two pairs in the metasternum. However, theextension of these combs can produce a juxtaposi-tion of the contiguous fields of macrosetae andtherefore the number of perceptible combs is re-duced. Consequently, in the metasternum it is pos-sible to count only 1+1 large combs with more than20 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 lengthis shorter or equal to the diameter of the tibia. Thenumber of such macrosetae is usually 2–4 dorsaland 3–6 ventral in all tibiae. On the inner side thereare many lanceolate scales that are absent on theouter side. These scales have also been detected inthe proximal article of the tarsi. Hyaline short spinesare usually present ventrally on the outer side of thearticle (figs. 7–9), as in many specimens of C.lineata from the Iberian Peninsula, although thesespines are more numerous and even shorter andstronger in this new species. Up to 25 spines have

been observed on a hind tibiae (fig. 9), but in otherspecimens the spines are absent.

Apex of the outer side of the femora covered byelongate and lanceolate scales, the inner side withmany scales shortened and with truncate oremarginated apex.

Urotergite I with 1+1 combs, II–VII with 3+3combs and VIII with 2+2 combs. Submedian bris-tle–combs with 7–9 macrosetae each, lateralcombs with 6–10 and sublateral with 7–15macrosetae. Urotergite X subtriangular, short, witha rounded apex that can show an angled or roundedpoint, more or less prolonged (figs. 10–13).Urosternites I and II without setae, III–VIII with1+1 lateral bristle–combs usually with 14–27macrosetae each; young specimens may bearfewer than 14 and the largest specimens maybear more than 27 macrosetae, but this is notusual. In relation with the high number of setaeper comb, the distance between the lateral combsof a urosternite is 2.7–5 times wider than the widthof a comb.

Both sexes with two pairs of stylets. In malesthe inner process of the IXth coxite is slightlylonger than wide (ratio length/width = 1.1–1.2)and about 3–3.5 times longer than the outer proc-ess (fig. 15). These two ratios are 2.5 and 2.5–4 infemales. The stylets IX are about 2.6 times longerthan the inner process of the coxites IX in malesand about 2.3 times in females (fig. 14). Oviposi-tor very long, with 55–57 segments, reaching be-yond the apex of the stylets IX up to 2–2.5 timesthe latter’s length (fig. 16). Apices of gonapophisesunsclerotized. Caudal filaments as long as bodylength or slightly longer (maximum preserved in aparacercus: 13.5 mm; cerci a bit shorter).

7 8

9

0.2 mm

0.2 mm

0.2 mm


Comparing C. almeriensis n. sp. with otherCtenolepisma species

The main feature to distinguish this species from theother Ctenolepisma Escherich, 1905 from Europe, isthe occurrence of double combs, i.e., fields ofmacrosetae on the thoracic sternites that are com-posed of two more or less parallel rows of plumosesetae; in the prosternum these rows are more irregu-lar and three rows can be observed in some fields.Some previously known species from other conti-nents show these "double combs"; this finding ismentioned in the descriptions of South African C.weberi and C. pretoriana by Wygodzinsky (1955),and in that of C. saxeta (Irish, 1987), but notaxonomic significance was given to this feature.This character has been also detected inundescribed taxa from North Africa and the NearEast (probably identified as C. lineata, without afuller involving dissection of the specimens). C.almeriensis sp. n. is the only one of the availablespecimens from the West–Palaeartic region withdouble combs that bears only two pairs of styletsin both sexes. However, the occurrence of a dou-ble or single row in the aforementioned combs isspecially useful for distinguishing between C.

Figs. 10–16. Ctenolepisma almeriensis n. sp. Types: 10–13. Xth urotergites of different specimensshowing 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 especímenesmostrando 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.

almeriensis n. sp. and C. lineata (respectively),two very similar taxa from the Iberian Peninsula(see figs. 17 and 18). The validity of this featurefor distinguishing between both species is con-firmed with a discriminant analysis (see below).More attention should therefore be paid to thisfeature for the future diagnosis of species of thisgenus.

Comparison of Ctenolepisma lineata and the newspecies

In comparison with the other European speciesbelonging to the lineata–group, the new speciesdescribed here is most similar to C. lineata as itstenth urotergite has the same shape, its legs showthe same cover of scales and its abdominal setationis similar. For this reason, a detailed comparison ofthese two taxa is carried out here to elucidate thevalidity of the aforementioned character that isused to separate these two species.

Other differences can be found between speci-mens with double and single sternal combs, suchas the number of macrosetae on the lateral andposterolateral combs of the nota, and on the combsof urotergites, thoracic sterna and urosternites. Even

10

11

12

13

0.2 mm

0.2 mm

0.2 mm

0.2 mm

0.2 mm 0.2 mm 0.2 mm

14 16 15


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 típicade Ctenolepisma lineata como C. almeriensis sp. n.

Figs. 17–18. SEM photos of the apical part of the metasternum in Ctenolepisma lineata (17), showinga single row of macrosetae, and Ctenolepisma almeriensis n. sp. (18), with a double row (mainlyinsertions 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 unadoble fila (se aprecian fundamentalmente las inserciones de las macroquetas).

are significantly different on the basis of thesevariable features, thereby proving the validity ofthe "single/double rows of macrosetae" in thesternal combs.

The variables selected are detailed in Materialand methods and were measured in 50 specimensof C. lineata and the same number of specimensbelonging to the new species.

the ratio distance between combs / width of a combin the metasternum and in the urosternites maydiffer. However, in these features the margins ofvariability overlap, so in some cases it is difficultto ascribe a certain specimen to C. lineata or to C.almeriensis if we do not see the combs of thethoracic sternites. A discriminant analysis maydemonstrate whether C. lineata and C. almeriensis

17 18100 m 10 m

Ctenolepisma lineataCtenolepisma almeriensis


Table 1. Classification table of the discriminantanalysis: A. Actual SPSEX; S. Group size.Predicted SPSEX groups are the same as infig. 21.

Tabla 1. Tabla de clasificación del análisisdiscriminante: A. SPSEX actual; S. Tamañodel grupo. Los grupos predefinidos SPSEXson los mismos que en la fig. 21.

Predicted SPSEX

A S 1 2 3 4

1 25 19 6 0 0

2 25 6 19 0 0

3 25 0 0 14 11

4 25 0 0 8 17

These conclusions justify the differentiation be-tween the two species and the validity of thedouble combs of macrosetae on thoracic sternitesas a clear character to distinguish between them.

The specimens belonging to the new specieshave never been found within the area occupiedby the typical C. lineata. The two species com-pared have never been found together in thesame locality (they are probably vicarious; seefig. 19). The distribution area of C. almeriensis ismainly inside the limits of the biogeographic sec-tor called “murciano–almeriense”, which is knownin faunistic works for its importance as a centre ofendemic 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 (Pvalue < 0.05).

Tabla 2. Valores Z calculados por los tests U de Mann–Whitney para dos muestras: Sp1. Grupospredefinidos 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 Sp1M–Sp1H Sp2M–Sp2H Sp1M–Sp2M Sp1H–Sp2H

N–notum –2,77* 0,08 6,18* 5,91*

N–pros –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*

All the specimens of C. lineata were from Spain(localities nearest to the area where C. almeriensisis found, see map in fig. 19) and only specimenswith two pair of stylets were selected, as it has beenrecently 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 compo-nent analysis (fig. 20), two components, 1 and 2,account for more than the 90% of variability. All thevariables selected show a significant weight toexplain this variability and therefore all of them areincluded in the discriminant analysis.

Taking into account the 600 data obtained fromthe total of 100 specimens (25 per predefined group),the following discriminant analyses were carriedout: (1) comparison between males of the twopredefined species; (2) comparison between fe-males of the two predefined species; (3) and (4)Comparison between males and females withineach one of the two species; and (5) comparisonbetween 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 predefinedspecies, as can be seen in the biplot of the discrimi-nant functions 1 and 2 (fig. 21), and in the classifi-cation variables (see material and methods). Theanalysis finds significant differences between spe-cies, but these differences are not found betweensexes of a given species.

The results of the Mann–Whitney U–tests to com-pare the medians of the four groups are shown intable 2. They are highly significant when differentpredefined species were compared, and not signifi-cant when both sexes within a species were com-pared (except for one variable in C. lineata, whichcould have a significant value for sexual dimorphism).


future but for the time being the findings in thiswork appear to be sufficient to maintain C.almeriensis as a good species, and subsequentlyto demonstrate the validity of the double combsof thoracic sternites as an anatomic characteris-tic with taxonomic importance in the genusCtenolepisma.

acts as a barrier for the wet western winds andoriginates an arid region in this corner of thePeninsula. Therefore, the new form ofCtenolepisma seems to be geographically iso-lated. Such geographic evidence also justifiesthe differentiation between the two species. Thismay be supported by molecular evidence in the

Fig. 20. Biplot of component principal analysis. Names of the variables are given in Material andmethods.

Fig. 20. Gráfico del análisis de componentes principales. Los nombres de las variables se indican enMaterial and methods.

Fig. 21. Biplot of the discriminant analysis: SPSEX groups are established on the basis of sex andpredefined species Ctenolepisma lineata and C. almeriensis.

Fig. 21. Gráfico del análisis discriminante: grupos SPSEX se han establecido en base al sexo y a laespecie predefinida Ctenolepisma lineata y C. almeriensis.

6

4

2

0

–2–4.3 –2.3 –0.3 1.7

Component 1

Co

mp

on

ent

2

2.8

1.8

0.8

–0.2

–1.2

–2.2

–3.2–3.6 –1.6 0.4 2.4 4.4 6.4

Function 1

Fu

nct

ion

2

SPSEX groups

N_uroN_not

N_prosN_meso

N_meta

d_a[Mt]

C. lineata, males

C. lineata, females

C. almeriensis, males

C. almeriensis, females

centroids


Apterygota, Zygentoma). Acta Zool. Fennica, 195:107–110.

Molero–Baltanás, R., 1995. Estudio taxonómico delos Zygentoma de España (Insecta: Apterygota).Ph. D. Thesis, Univ. of Cordoba.

Rivas–Martínez, S., 1987. Nociones sobre Fitosocio-logía, Biogeografía y Bioclimatología. In: Peinado,M., Rivas–Martínez, S., Eds. La vegetación deEspaña. Serv. de Publicaciones Univ. de Alcalá deHenares. Madrid: 19–45.

Wygodzinsky, P., 1955. Thysanura. South. afr. anim.Life, 2: 83–190.

References

Irish, J., 1987. Revision of the genus CtenolepismaEscherich (Thysanura:Lepismatidae) in South-ern 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 deRoca, C. & Mendes, L. F., 1994. New faunisticdata on the Lepismatidae of Spain (Insecta,

Animal Biodiversity and Conservation 28.1 (2005) I

ISSN: 1578–665X © 2005 Museu de Ciències Naturals

Animal Biodiversity and Conservation

Animal Biodiversity and Conservation (abans Miscel·lània Zoològica) és una revista inter disciplinària publicada, des de 1958, pel Museu de Zoologia de Barcelona. Inclou articles d'inves tigació empírica i teòrica en totes les àrees de la zoologia (sistemàtica, taxo nomia, morfo logia, 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 executiu, 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.

Normes de publicació

Els treballs s'enviaran preferentment de forma electrònica ([email protected]). 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 investigacions originals no publicades anterior ment 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 programa 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.

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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 manus crits 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 neologismes 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.

Format dels articles

Títol. El títol serà concís, però suficientment indicador del contingut. Els títols amb desig nacions 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 castellano parlants. Palabras clave en castellà.Adreça postal de l’autor o autors.(Títol, Nom, Abstract, Key words, Resumen, Palabras clave i Adreça postal, conformaran la primera pàgina.)



II

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, mètodes d’estudi i d’anàlisi de les dades i zona d’estudi.Resultados. En aquesta secció es presentaran únicament les dades obtingudes que no hagin estat publicades prèviament.Discusión. Es discutiran els resultats i es compararan amb treballs relacionats. Els sug geriments 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 abun-

dance. C. Griffin & Company, London. * Treballs de contribució en llibres:Macdonald, D. W. & Johnson, D. P., 2001. Dispersal

in theory and practice: consequences for conservation 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 alfabè ticament per autors i cronològicament per a un mateix autor, afegint les lletres a, b, c,... als treballs del mateix any. En el text, s’indi caran 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 ressenyades 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 autors. 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 repro dueixen 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 (Introducción, 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 insti tució 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) III



Animal Biodiversity and Conservation (antes Miscel·lània Zoològica) es una revista interdisciplinar, 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, taxo nomía, morfología, biogeografía, ecología, etología, fisiología y genética) 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 registrada 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 garantizar su calidad. El proceso de revisión es rápido y constructivo, y se realiza vía correo electrónico siempre 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 propiedad de la revista. Ésta se reserva los derechos de autor, y ninguna parte del trabajo podrá ser reproducida sin citar su procedencia.

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Cuando el trabajo sea aceptado los autores deberán enviar a la Redacción una copia impresa de la versión final junto con un disquete del manuscrito preparado con un pro cesador de textos e indicando el programa utilizado (preferiblemente Word). Las pruebas de imprenta enviadas a los autores deberán

remitirse corregidas al Consejo Editor en el plazo máximo de 10 días. Los gastos debidos a modificaciones sustanciales en las pruebas de im pren ta, introducidas 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 ofre ce, sin cargo ninguno, 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, evitán dose 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.

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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 consentimiento 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, resultados 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.



IV

Resumen en castellano, traducción del abstract. Su traducción puede ser solicitada a la revista en el caso de autores que no sean castellano hablan tes. 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 antecedentes del tema tratado, así como de los objetivos del trabajo.Material y métodos. Incluirá la información referente a las especies estudiadas, aparatos utilizados, metodología de estudio y análisis de los datos y zona de estudio.Resultados. En esta sección se presentarán únicamente los datos obtenidos que no hayan sido publicados previamente.Discusión. Se discutirán los resultados y se compararán 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 abun-

dance. C. Griffin & Company, London. * Trabajos de contribución en libros:Macdonald, D. W. & Johnson, D. P., 2001. Dispersal


* 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 alfabética men te por autores, cronológicamen te para un mismo autor y con las letras a, b, c,... para los tra bajos 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 tridimen sionales. 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) V



Animal Biodiversity and Conservation (formerly Miscel·lània Zoològica) is an inter dis ci pli nary journal which has been published by the Zoological Museum of Bar celona since 1958. It includes empirical and theoretical research in all aspects of Zoology (Systematics, Taxo nomy, Morphology, Bio geography, Ecology, Etho logy, Physio logy 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 Editor, 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 property of the journal, which reserves copyright, and no published material may be reproduced without quoting its origin.

Information for authors

Electronic submission of papers is encouraged ([email protected]). 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 consi deration in Animal Biodivers ity 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.

Manuscripts

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 contributions 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 untrans latable 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 written 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.

Formatting of articles

Title. The title must be concise but as infor mative 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 type written lines (840 spaces), covering the con tents 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 trans lated 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 in clude the historical background of the sub ject as well as the aims of the paper.




VI

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. Sug gestions for future research may be given at the end of this section.Acknowledgements (optional).References. All manuscripts must include a bibliography 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 abun-

dance. C. Griffin & Company, London.* Contributions or chapters of books:Macdonald, D. W. & Johnson, D. P., 2001. Dispersal


* 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. Biblio graphic citations in the text must appear in the usual way: "...according to Wemmer (1998)...", "...has been defined by Robinson & Redford (1991)...", "...the pros pec tions 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, numbered consecutively in Arabic numerals (1, 2, 3, etc.) and with re ference 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 tridimen sional. 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, Acknowled ge ments and References) should not be number ed. 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.

VIIAnimal Biodiversity and Conservation 28.1 (2005)

Animal Biodiversity and Conservation Subscription Form

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Send cheque by postal mail to: Lluïsa Arroyo Dept. of Scientific Publications Museu de Ciències Naturals de la Ciutadella Psg. Picasso s/n. 08003 Barcelona, Spain Bank Transfer to Caixa d’Estalvis i Pensions de Barcelona ("La Caixa") IBAN: ES03 2100 3000 1422 0170 1046 Swicht code / bic code: CAIX ES BB

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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 Ornitho-logical 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

1–44Ranius, 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, Scarabaei-dae, Cetoniinae) in Europe

45–58 ReviewFleishman, E. Identification and conservation application of signal, noise, and taxonomic effects in diversity patterns

59–67 ReviewCorn, P. S. Climate change and amphibians

69–73Geist, C., Liao, J., Libby, S. & Blumstein, D. T.Does intruder group size and orientation affect flight initiation distance in birds?

75–89Olden, J. D. & Poff, N. L.Long–term trends of native and non–native fish faunas in the American Southwest

91–99Molero–Baltanás, R., Gaju–Ricart, M. & Bach de Roca, C.Ctenolepisma almeriensis n. sp. of Lepis-matidae (Insecta, Zygentoma) from south–eastern Spain

animal biodiversity and conservation issue 28.1 (2005)

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