Conservation Genetics

, Volume 12, Issue 2, pp 503–515 | Cite as

Modelling range shifts and assessing genetic diversity distribution of the montane aquatic mayfly Ameletus inopinatus in Europe under climate change scenarios

  • Julia Taubmann
  • Kathrin Theissinger
  • Kevin A. Feldheim
  • Irina Laube
  • Wolfram Graf
  • Peter Haase
  • Jes Johannesen
  • Steffen U. Pauls
Research Article

Abstract

Genetic diversity is one of the most important criteria to identify unique populations for conservation purposes. In this study we analyze the genetic population structure of the endangered montane mayfly Ameletus inopinatus in its European range. The species is restricted to unpolluted cold-water streams, and exhibits an insular distribution across highlands of Central Europe and a more continuous distribution across Fennoscandia and Northern Euro-Siberia. We genotyped 389 individuals from 31 populations for eight highly polymorphic microsatellite loci to investigate genetic diversity and population structure within and among European mountain ranges. Genetic diversity of A. inopinatus decreases along an east–west gradient in Central Europe and along a north–south gradient in Fennoscandia, respectively. Centres of exceptionally high genetic diversity are located in the Eastern Alps (Andertal Moor, Austria), the High Tatra, the Beskides, the Sudety Mountains and the Eastern German Highlands. Species distribution modelling for 2080 projects major regional habitat loss, particularly in Central Europe mountain ranges. By relating these range shifts to our population genetic results, we identify conservation units primarily in Eastern Europe, that if preserved would maintain high levels of the present-day genetic diversity and continue to provide long-term suitable habitat under future climate warming scenarios.

Keywords

Microsatellites Population genetics Species distribution modelling Conservation Aquatic insects Wahlund effect 

Supplementary material

10592_2010_157_MOESM1_ESM.jpg (2.3 mb)
Supplementary material 1 (JPEG 2375 kb)

References

  1. Alcamo J, Bouwman A, Edmonds J, Grübler A, Morita T, Sugandhy A (1995) An evaluation of the IPCC IS92 emission scenarios. In: Climate change 1994, radiative forcing of climate change and an evaluation of the IPCC IS92 emission scenarios. Cambridge University Press, Cambridge, pp 233–304Google Scholar
  2. Alsos IG, Alm T, Normand S et al (2009) Past and future range shifts and loss of diversity in dwarf willow (Salix herbacea L.) inferred from genetics, fossils and modelling. Glob Ecol Biogeogr 18:223–239CrossRefGoogle Scholar
  3. Araújo MB, New M (2006) Ensemble forecasting of species distributions. Trends Ecol Evol 22:42–47PubMedCrossRefGoogle Scholar
  4. Beebee TJC (2007) Population structure and its implications for conservation of the great silver beetle Hydrophilus piceus in Britain. Freshw Biol 52:2101–2111CrossRefGoogle Scholar
  5. Böhmer J, Rawer-Jost C, Zenker A (2004) Multimetric assessment of data provided by water managers from Germany: assessment of several different types of stressors with macrozoobenthos communities. Hydrobiologia 516:215–228CrossRefGoogle Scholar
  6. Bonin A, Bellemain E, Bronken Eidesen P, Pompanon F, Brochmann C, Taberlet P (2004) How to track and assess genotyping errors in population genetic studies. Mol Ecol 13:3261–3273PubMedCrossRefGoogle Scholar
  7. Buffagni A, Cazzola M, López-Rodríguez MJ, Alba-Tercedor J, Armanini DG (2009) In: Schmidt-Kloiber A, Hering D (eds) Distribution and ecological preferences of European freshwater organisms. Volume 3—Ephemeroptera. Pensoft Publishers, Sofia, pp 1–254Google Scholar
  8. Bunn SE, Hughes JM (1997) Dispersal and recruitment in streams: evidence from genetic studies. J N Am Benthol Soc 16:338–346CrossRefGoogle Scholar
  9. Chakraborty R, De Andrade M, Daiger SP, Budowle B (1992) Apparent heterozygote deficiencies observed in DNA typing data and their implications in forensic applications. Ann Hum Genet 56:45–57PubMedCrossRefGoogle Scholar
  10. Cordellier M, Pfenninger M (2008) Climate driven range dynamics of the freshwater limpet, Ancylus fluviatilis (Pulmonata, Basommatophora). J Biogeogr 35:1580–1592CrossRefGoogle Scholar
  11. Crandall KA, Bininda-Emonds ORP, Mace GM, Wayne RK (2000) Considering evolutionary processes in conservation biology. Trends Ecol Evol 15:290–295PubMedCrossRefGoogle Scholar
  12. Daking EE, Avise JC (2004) Microsatellite null alleles in parentage analysis. Heredity 93:504–509CrossRefGoogle Scholar
  13. Duelli P (1997) Biodiversity evaluation in agricultural landscapes: an approach at two different scales. Agric Ecosyst Environ 62:81–91CrossRefGoogle Scholar
  14. EU Commission (2010). http://ec.europa.eu/environment/nature/index_en.htm. Accessed 18 March 2010
  15. European Environment Agency (2010) http://www.eea.europa.eu/de. Accessed 18 March 2010
  16. Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial-DNA restriction data. Genetics 131:479–491PubMedGoogle Scholar
  17. Excoffier L, Laval G, Schneider S (2005) Arlequin version 3.11: an integrated software package for population genetics data analysis. Evol Bioinform Online 1:47–50PubMedGoogle Scholar
  18. Felsenstein J (2008) PHYLIP (Phylogeny inference package) version 3.68. Available at http://evolution.genetics.washington.edu/phylip/software.html. Distributed by the author. Department of Genome Sciences, University of Washington, Seattle
  19. Fiedler PL, Jain SK (1992) Conservation biology: the theory and practice of nature conservation, preservation and management. Chapman and Hall, New YorkGoogle Scholar
  20. Frankham R, Ballou JD, Briscoe DA (2002) Introduction to conservation genetics. Cambridge University Press, CambridgeGoogle Scholar
  21. Freeland JR (2005) Molecular ecology. Wiley, HobokenGoogle Scholar
  22. GBIF-Sweden (2010) GBIF data portal. http://data.gbif.org. Accessed 18 March 2010
  23. Gienapp P, Teplitsky C, Alho JS, Mills JA, Merilä J (2008) Climate change and evolution: disentangling environmental and genetic responses. Mol Ecol 17:167–178PubMedCrossRefGoogle Scholar
  24. Glaubitz JC (2004) CONVERT: a user friendly program to reformat diploid genotypic data for commonly used population genetic software packages. Mol Ecol Notes 4:309–310CrossRefGoogle Scholar
  25. Graf W, Schultz H, Janececk B (2004) Ökofaunistische Erhebungen und Bewertung im Natura 2000-Gebiet St. Lorenzener Hochmoor, Makrozoobenthos EndberichtGoogle Scholar
  26. Graham CH, Ferrier S, Huettman F, Moritz C, Townsend Peterson A (2004) New developments in museum-based informatics and applications in biodiversity analysis. Trends Ecol Evol 19:497–503PubMedCrossRefGoogle Scholar
  27. Guillot G, Mortier F, Estoup A (2005) GENELAND: a computer package for landscape genetics. Mol Ecol Notes 5:712–715CrossRefGoogle Scholar
  28. Harte J, Ostling A, Green JL, Kinzig A (2004) Climate change and extinction risk. Nature. doi:10.1038/nature02718
  29. Haybach A (2003) Zoogeographische Aspekte der Eintagsfliegenbesiedlung Deutschlands (Insecta, Ephemeroptera). Verhandlungen der westdeutschen Entomologentagung Düsseldorf 2002:187–209Google Scholar
  30. Hendrey GR, Wright RF (1976) Acid precipitation in Norway: effects on aquatic fauna. J Gt Lakes Res 2:192–207CrossRefGoogle Scholar
  31. Hering D, Schmidt-Kloiber A, Murphy J, Lücke S, Zamora-Muñoz C, López Rodríguez MJ, Huber T, Graf W (2009) Potential impact of climate change on aquatic insects: a sensitivity analysis for European caddisflies (Trichoptera) based on distribution patterns and ecological preferences. Aquat Sci 71:3–14CrossRefGoogle Scholar
  32. Hewitt GM (1996) Some genetic consequences of ice ages, and their role in divergence and speciation. Biol J Linn Soc 58:247–276Google Scholar
  33. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978CrossRefGoogle Scholar
  34. Hoelzel E (1967) Die Fauna des Hochmoores von St. Lorenzen in den Gurker Alpen. Carinthia 195–211Google Scholar
  35. Hoffmann AA, Willi Y (2008) Detecting genetic responses to environmental change. Nat Rev Genet 9:421–432PubMedCrossRefGoogle Scholar
  36. Houghton J (2001) The science of global warming. Interdiscip Sci Rev 26:247–257CrossRefGoogle Scholar
  37. Hughes AR, Inouye BD, Johnson MTJ, Underwood N, Vellend M (2008) Ecological consequences of genetic diversity. Ecol Lett 11:609–623PubMedCrossRefGoogle Scholar
  38. Ihaka R, Gentleman R (1996) R: a language for data analysis and graphics. J Comp Graph Stat 5:299–314CrossRefGoogle Scholar
  39. Jackson JK, Resh VH (1992) Variation in genetic structure among populations of the caddisfly Helicopsyche borealis from three streams in northern California, U.S.A. Freshw Biol 27:29–42CrossRefGoogle Scholar
  40. Kalinowski ST (2004) Counting alleles with rarefaction: private alleles and hierarchical sampling designs. Conserv Genet 5:539–543CrossRefGoogle Scholar
  41. Leberg PL (2002) Estimating allelic richness: effects of sample size and bottlenecks. Mol Ecol 11:2445–2449PubMedCrossRefGoogle Scholar
  42. Malzacher P, Jacob U, Haybach A, Reusch H (1998) Rote Liste der Eintagsfliegen (Ephemeroptera). In: Binot M, Bless R, Boye P, Gruttke H, Pretscher P (eds) Rote Liste gefährdeter Tiere Deutschlands, Bundesamt für Naturschutz (BfN). Bonn-Bad Godesberg, Germany, pp 264–267Google Scholar
  43. McNeely JA, Miller KR, Reid WV, Mittermeier RA, Werner TB (1990) Conserving the world’s biological diversity. World Conservation Union, World Resources Institute, Conservation International, World Wildlife Fund—US, and the World Bank, Washington, DCGoogle Scholar
  44. Moussalli A, Moritz C, Williams SE, Carnaval AC (2009) Variable responses of skinks to a common history of rainforest fluctuation: concordance between phylogeography and palaeo-distribution models. Mol Ecol 18:483–499PubMedCrossRefGoogle Scholar
  45. Nei M, Tajima F, Tateno Y (1983) Accuracy of estimated phylogenetic trees from molecular data. J Mol Evol 19:153–170PubMedCrossRefGoogle Scholar
  46. OTA (US Congress Office of Technology Assessment) (1987) Technologies to maintain biological diversity. US Government Printing Office, Washington, DCGoogle Scholar
  47. Parmesan C, Yohe G (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature 421:37–42PubMedCrossRefGoogle Scholar
  48. Pauls SU, Lumbsch T, Haase P (2006) Phylogeography of the montane caddisfly Drusus discolor: evidence for multiple refugia and periglacial survival. Mol Ecol 15:2153–2169PubMedCrossRefGoogle Scholar
  49. Petit RJ, El Mousadik A, Pons O (1998) Identifying populations for conservation on the basis of genetic markers. Conserv Biol 12:844–855CrossRefGoogle Scholar
  50. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259CrossRefGoogle Scholar
  51. Raymond M, Rousset F (1995) GENEPOP (version 1.2) population genetics software for exact tests and ecumenicism. J Hered 86:248–249Google Scholar
  52. Reed DH, Frankham R (2003) Correlation between fitness and genetic diversity. Conserv Biol 17:230–237CrossRefGoogle Scholar
  53. Rice WR (1989) Analyzing tables of statistical tests. Evolution 43:223–225CrossRefGoogle Scholar
  54. Rosenberg DM, Resh VH (1993) Freshwater biomonitoring and benthic invertebrates. Chapman & Hall, New YorkGoogle Scholar
  55. Russev B, Vidinova Y (1994) Distribution and ecology of the representatives of some families of order Ephemeroptera (Insecta) in Bulgaria. Lauterbornia 19:107–113Google Scholar
  56. SAS Institute Inc. (2007) JMP user guide. SAS Institute Inc, CaryGoogle Scholar
  57. Schultz H, Janecek B, Hess M, Reusch H, Graf W (2004) Das Makrozoobenthos des Natura 2000 Gebietes St. Lorenzener Hochmoor (Andertal, Kernten) unter besonderer Berücksichtigung der Libellenfauna (Insecta: Odonata). Carinthia II 196:343–358Google Scholar
  58. Slatkin M (1995) A measure of population subdivision based on microsatellite allele frequencies. Genetics 139:457–462PubMedGoogle Scholar
  59. Soldán T, Enktaivan S, Godunko RJ (2009) Commented checklist of mayflies (Ephemeroptera) of Mongolia. Aquat Insects 31:653–670CrossRefGoogle Scholar
  60. Taberlet P (1998) Biodiversity at the intraspecific level: the comparative phylogeographic approach. J Biotechnol 64:91–100CrossRefGoogle Scholar
  61. Takezaki N, Nei M (1996) Genetic distances and reconstruction of phylogenetic trees from microsatellite DNA. Genetics 144:389–399PubMedGoogle Scholar
  62. Theissinger K, Feldheim KA, Taubmann J, Seitz A, Pauls SU (2008) Isolation and characterization of 10 higly polymorphic di- and trinucleotide microsatellite markers in the mayfly Ameletus inopinatus (Ephemeroptera: Siphlonuridae). Mol Ecol Resour 8:1285–1287CrossRefGoogle Scholar
  63. Thomas CD, Cameron A, Green RE, Bakkenes M, Beaumont LJ, Collingham YC et al (2004) Extinction risk from climate change. Nature 427:145–147PubMedCrossRefGoogle Scholar
  64. Van Oosterhout CV, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes 4:535–538CrossRefGoogle Scholar
  65. Wilcock HR, Bruford MW, Nichols RA, Hildrew AG (2007) Landscape, habitat characteristics and the genetic population structure of two caddisflies. Freshw Biol 52:1907–1929CrossRefGoogle Scholar
  66. Wright JF, Sutcliffe DW, Furse MT (eds) (2000) Assessing the biological quality of fresh waters: RIVPACS and other techniques. Freshwater Biological Association, Ambleside, Cumbria, UKGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Julia Taubmann
    • 1
    • 2
  • Kathrin Theissinger
    • 1
    • 2
  • Kevin A. Feldheim
    • 3
  • Irina Laube
    • 1
    • 4
  • Wolfram Graf
    • 5
  • Peter Haase
    • 2
  • Jes Johannesen
    • 1
  • Steffen U. Pauls
    • 4
    • 6
  1. 1.Department of Ecology, Institute of ZoologyJohannes Gutenberg UniversityMainzGermany
  2. 2.Department of Limnology and ConservationSenckenbergGelnhausenGermany
  3. 3.Pritzker Laboratory for Molecular Systematics and EvolutionThe Field MuseumChicagoUSA
  4. 4.Biodiversity and Climate Research Centre (BiK-F)Frankfurt am MainGermany
  5. 5.Institute of Hydrobiology and Aquatic Ecosystem ManagementWienAustria
  6. 6.Department of EntomologyUniversity of MinnesotaSt PaulUSA

Personalised recommendations