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Quantitative Habitat Models for the Conservation of the Endangered European Crayfish Austropotamobius pallipes Complex (Astacoidea: Astacidae)

  • Paolo VezzaEmail author
  • Daniela Ghia
  • Gianluca Fea
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Abstract

Crayfish are the largest mobile freshwater invertebrates and are keystone species in European aquatic ecosystems particularly in small streams and rivers. The white-clawed crayfish Austropotamobius pallipes (a species complex) is currently classified by the IUCN Red List as an endangered species (EN), because its populations have decreased significantly over the last decades in a number of European countries including Italy, due mainly to habitat modifications and the introduction and spread of alien species. Data on the ecological requirements of A. pallipes are needed to quantify the effects of habitat alteration, to simulate restoration scenarios, and to implement effective conservation measures for this species. We describe here a new methodology for modelling the habitat requirements for this endangered crayfish using the mesohabitat scale approach based on data from crayfish living in small streams draining the Italian foothills of the Alps (Lombardy region) and in streams in the mountainous areas of the Gran Sasso and Monti della Laga National Park (Abruzzo region). Data from seven morphologically different streams were used to train and validate the habitat models. The Random Forests algorithm was used to identify the best and most parsimonious habitat model, and to define the lowest number of variables to be surveyed in the future. The best habitat models were applied to each stream and used to classify each mesohabitat into suitability categories. Habitat flow-rating curves were developed to analyze spatio-temporal variation of habitat availability, and habitat time series analysis were used to define detailed management schemes for environmental river management. Flow releases and water temperature regimes were assessed for individual water diversions in order (1) to represent how physical habitat changes through time, and (2) to identify stress conditions for A. pallipes created by the persistent limitation of habitat availability. Results indicated that the kind of substrate in the stream bed (such as the proportion of fine-grained substrates), the water depth (whether shallow or deep), and the available cover (such as the presence of boulders, woody debris, and undercut banks) were all significant factors governing the occurrence of crayfish. The habitat models performed well in both calibration and validation phases (with accuracy ranging from 71 to 79 % in training and from 69 to 73 % in validation) and can be considered to be a valuable tool to predict the distribution of A. pallipes over a wide range of stream types. An example of how to establish environmental standards for small streams is presented. The proposed habitat model provides a useful tool that can be applied even when other commonly used methodologies are unsuitable. As such, this habitat model can be used to develop regional rules for the conservation of the endangered crayfish A. pallipes complex and for defining more site-specific management criteria.

Keywords

Endangered crayfish Mesohabitat MesoHABSIM Austropotamobius pallipes Crayfish conservation 

References

  1. Ackerfors, H. (1996). The development of crayfish culture in Sweden during the last decade. Freshwater Crayfish, 11, 627–654.Google Scholar
  2. Allouche, O., Tsoar, A., & Kadmon, R. (2006). Assessing the accuracy of species distribution models: Prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology, 43, 1223–1232.CrossRefGoogle Scholar
  3. Aquiloni, L., Martín, M. P., Gherardi, F., & Diéguez-Uribeondo, J. (2011). The North American crayfish Procambarus clarkii is the carrier of the oomycete Aphanomyces astaci in Italy. Biological Invasions, 13, 359–367.CrossRefGoogle Scholar
  4. Barbaresi, S., & Gherardi, F. (2001). Daily activity of the white-clawed crayfish, Austropotamobius pallipes (Lereboullet): A comparison between field and laboratory studies. Journal of Natural History, 35, 1861–1871.CrossRefGoogle Scholar
  5. Bennett, N. D., Croke, B. F. W., Guariso, G., Guillaume, J. H. A., Hamilton, S. H., Jakeman, A. J., et al. (2013). Characterising performance of environmental models. Environmental Modelling and Software, 40, 1–20.CrossRefGoogle Scholar
  6. Benvenuto, C., Gherardi, F., & Ilhéu, M. (2008). Microhabitat use by the white-clawed crayfish in a Tuscan stream. Journal of Natural History, 42, 21–33.CrossRefGoogle Scholar
  7. Berger, C., & Füreder, L. (2013). Linking species conservation management and legal species protection: A case study on stone crayfish. Freshwater Crayfish, 19, 161–175.Google Scholar
  8. Bernardo, J. M., Ilhéu, M., & Costa, A. M. (1997). Distribution, population structure and conservation of Austropotamobius pallipes in Portugal. Bulletin Français de la Pêche et de la Pisciculture, 347, 617–624.CrossRefGoogle Scholar
  9. Bovee, K. D. (1982). A guide to stream habitat analysis using the instream flow incremental methodology. Fort Collins: U.S. Fish and Wildlife Service.Google Scholar
  10. Breiman, L. (2001). Random forest. Machine Learning, 45, 5–32.CrossRefGoogle Scholar
  11. Breiman, L., Friedman, J. H., Olshen, R., & Stone, C. J. (1984). Classification and regression trees. Monterey: Wadsworth and Brooks.Google Scholar
  12. CIPRA [International Commission for the Protection of the Alps]. (2010). Situation Report on Hydropower Generation in the Alpine Region focusing on Small Hydropower.Google Scholar
  13. CIRF [Italian Center for River Restoration]. (2014). L’energia “verde” che fa male ai fiumi. CIRF, Mestre.Google Scholar
  14. Clavero, M., Benejam, L., & Seglar, A. (2009). Microhabitat use by foraging white-clawed crayfish (Austropotamobius pallipes) in stream pools in the NE Iberian Peninsula. Ecological Research, 24, 771–779.CrossRefGoogle Scholar
  15. Cutler, D. R., Edwards, T. C., Beard, K. H., Cutler, A., Hess, K. T., Gibson, J., et al. (2007). Random forests for classification in ecology. Ecology, 88, 2783–2792.CrossRefPubMedGoogle Scholar
  16. Diéguez-Uribeondo, J., Rueda, A., Castien, E., & Bascones, J. C. (1997). A plan of restoration in Navarra for the native freshwater crayfish species of Spain, Austropotamobius pallipes. Bulletin Francais de la Peche et de la Pisciculture, 347, 625–637.CrossRefGoogle Scholar
  17. Elith, J., & Leathwick, J. R. (2009). Species distribution models: Ecological explanation and prediction across space and time. Annual Review of Ecology Evolution and Systematics, 40, 677–697.CrossRefGoogle Scholar
  18. Englund, G., & Krupa, J. J. (2000). Habitat use by crayfish in stream pools: Influence of predators, depth and body size. Freshwater Biology, 43, 75–83.CrossRefGoogle Scholar
  19. Favaro, L., Tirelli, T., & Pessani, D. (2011). Modelling habitat requirements of white-clawed crayfish (Austropotamobius pallipes) using support vector machines. Knowledge and Management of Aquatic Ecosystems, 401, 21.CrossRefGoogle Scholar
  20. Fea, G., Nardi, P. A., Ghia, D., Spairani, M., Manenti, R., Rossi, S., et al. (2006). Dati preliminari sulla distribuzione in Lombardia dei gamberi d’acqua dolce autoctoni e alloctoni. Atti Soc. it. Sci. nat. Museo civ. Stor. nat. Milano, 147, 201–210.Google Scholar
  21. Foster, J. (1993). The relationship between refuge size and body size in the crayfish Austropotamobius pallipes (Lereboullet). Freshwater Crayfish, 9, 345–349.Google Scholar
  22. Foster, J. (1995). Factors influencing the distribution and abundance of the crayfish Austropotamobius pallipes (Lereboullet) in Wales and the Marches, UK. Freshwater Crayfish, 8, 78–98.Google Scholar
  23. Freeman, E. A., Moisen, G. G., & Frescino, T. S. (2012). Evaluating effectiveness of down-sampling for stratified designs and unbalanced prevalence in Random Forest models of tree species distributions in Nevada. Ecology Models, 233, 1–10.CrossRefGoogle Scholar
  24. Füreder, L., Gherardi, F., Holdich, D., Reynolds, J., Sibley, P., & Souty-Grosset, C. (2010). Austropotamobius pallipes. The IUCN Red List of Threatened Species 2010: Public Internet. e.T2430A9438817. Accessed Feb 27, 2014.Google Scholar
  25. Gherardi, F., Acquistapace, P., & Santini, G. (2001). Foraging by a threatened species: The white-clawed crayfish, Austropotamobius pallipes. Archiv für Hydrobiologie, 152, 339–351.Google Scholar
  26. Gherardi, F., Acquistapace, P., & Santini, G. (2004). Food selection in omnivores: A case study of the Austropotamobius pallipes. Archiv für Hydrobiologie, 159, 357–376.CrossRefGoogle Scholar
  27. Ghia, D., Vezza, P., Fea, G., Spairani, M., & Sacchi, R. (2013) The meso-habitat scale as a new approach for the conservation of the endangered crayfish Austropotamobius pallipes complex in Northern Italy. In: Regional European crayfish meeting, Croatia. Contribution awarded with the novelty award.Google Scholar
  28. Ghia, D., Fea, G., Conti, A., Sacchi, R., & Nardi, P. A. (2015). Estimating age composition in Alpine native populations of Austropotamobius pallipes complex. Journal of Limnology, 74, 501–511.Google Scholar
  29. Holdich, D. M., & Rogers, W. D. (1997). The white-clawed crayfish, Austropotamobius pallipes, in Great Britain and Ireland with particular reference to its conservation in Great Britain. Bulletin Français de la Pêche et de la Pisciculture, 347, 597–616.CrossRefGoogle Scholar
  30. Holdich, D. M., Reynolds, J. D., Souty-Grosset, C., & Sibley, P. J. (2009). A review of the ever increasing threat to European crayfish from non-indigenous crayfish species. Knowledge and Management of Aquatic Ecosystems, 394–395, 11.CrossRefGoogle Scholar
  31. Jorde, K., Schneider, M., Peter, A., & Zöllner, F. (2001). Models for the evaluation of fish habitat quality and instream flow assessment. In: CD-ROM Proceedings of third international symposium on environmental hydraulics. Tempe, Arizona.Google Scholar
  32. Liaw, A., & Wiener, M. (2002). Classification and regression by Random Forest. R News, 2, 18–22.Google Scholar
  33. Maddock, I., Harby, A., Kemp, P., & Wood, P. J. (Eds.). (2013). Ecohydraulics: an integrated approach. West Sussex: Wiley-Blackwell.Google Scholar
  34. Milhous, R., Bartholow, J., Updike, M., & Moos, A. (1990). Reference manual for generation and analysis of habitat time series. U.S. Fish and Wildlife Services: Fort Collins.Google Scholar
  35. Montgomery, D., & Buffington, J. (1997). Channel-reach morphology in mountain drainage basins. Geological Society of America Bulletin, 109, 591–611.CrossRefGoogle Scholar
  36. Murphy, M. A., Evans, J. S., & Storfer, A. (2010). Quantifying Bufo boreas connectivity in Yellowstone National Park with landscape genetics. Ecology, 91, 252–261.CrossRefPubMedGoogle Scholar
  37. Naura, M., & Robinson, M. (1998). Principles of using River Habitat Survey to predict the distribution of aquatic species: An example applied to the native white-clawed crayfish Austropotamobius pallipes. Aquatic Conservation: Marine and Freshwater Ecosystems, 8, 515–527.CrossRefGoogle Scholar
  38. Parasiewicz, P. (2007a). The MesoHABSIM model revisited. River Research and Applications, 23, 893–903.CrossRefGoogle Scholar
  39. Parasiewicz, P. (2007b). Using MesoHABSIM to develop reference habitat template and ecological management scenarios. River Research and Applications, 23, 924–932.CrossRefGoogle Scholar
  40. Parasiewicz, P., Ryan, K., Vezza, P., Comoglio, C., Ballestero, T., & Rogers, J. N. (2012). Use of quantitative habitat models for establishing performance metrics in river restoration planning. Ecohydrology, 6, 668–678.CrossRefGoogle Scholar
  41. Parasiewicz, P., Rogers, J. N., Vezza, P., Gortazar, J., Seager, T., Pegg, M., et al. (2013). Applications of the MesoHABSIM simulation model. In H. A. Maddock, P. Kemp, & P. Wood (Eds.), Ecohydraulics: An integrated approach (pp. 109–124). West Sussex: Wiley.CrossRefGoogle Scholar
  42. Petitguyot, T., Bussettini, M., Linsen, M., Schmidt, G., Arqued-Esquía, V. M., Smolar-Žvanut, N., et al. (2015). Ecological flows in the implementation of the Water framework directive. Common Implementation Strategy (CIS) Guidance Document n 31. European Union, Luxembourg.Google Scholar
  43. Rinaldi, M., Belletti, B., Comiti, F., Nardi, L., Mao, L., & Bussettini, M. (2015). Sviluppo di un sistema di rilevamento e classificazione delle Unità Morfologiche dei corsi d’acqua (SUM). Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA), Rome, ItalyGoogle Scholar
  44. Smith, G. R. T., Learner, M. A., Slater, F. M., & Foster, J. (1996). Habitat features important for the conservation of the native crayfish Austropotamobius pallipes in Britain. Biological Conservation, 75, 239–246.CrossRefGoogle Scholar
  45. Souty-Grosset, C., Holdich, D. M., Noel, P. Y., Reynolds, J. D., & Haffner, P. (2006). Atlas of crayfish in Europe. Paris: Museum National d’Histoire Naturelle.Google Scholar
  46. Strobl, C., Boulesteix, A. L., Kneib, T., Augustin, T., & Zeileis, A. (2008). Conditional variable importance for random forests. BMC Bioinformatics, 9, 307.CrossRefPubMedPubMedCentralGoogle Scholar
  47. Vaughan, I. P., & Ormerod, S. J. (2005). The continuing challenges of testing species distribution models. Journal of Applied Ecology, 42, 720–730.CrossRefGoogle Scholar
  48. Vezza, P., Parasiewicz, P., Rosso, M., & Comoglio, C. (2012a). Defining minimum environmental flows at regional scale: Application of mesoscale habitat models and catchments classification. River research and applications, 28, 675–792.CrossRefGoogle Scholar
  49. Vezza, P., Parasiewicz, P., Spairani, M., & Comoglio, C. (2012b). Meso-scale habitat modelling in Alpine high gradient streams. In H. Mader & J. Kraml (Eds.), Proceeding of the 9th eco-hydraulics symposium. Vienna: ISE 2012.Google Scholar
  50. Vezza, P., Parasiewicz, P., Calles, O., Spairani, M., & Comoglio, C. (2014a). Modelling habitat requirements of bullhead (Cottus gobio) in alpine streams. Aquatic Sciences, 76, 1–15.CrossRefGoogle Scholar
  51. Vezza, P., Parasiewicz, P., Spairani, M., & Comoglio, C. (2014b). Habitat modelling in high gradient streams: The meso-scale approach and application. Ecological Applications, 24, 844–861.CrossRefPubMedGoogle Scholar
  52. Vezza, P., Muñoz-Mas, R., Martinez-Capel, F., & Mouton, A. (2015). Random forests to evaluate biotic interactions in fish distribution models. Environmental Modelling and Software, 67, 173–183.CrossRefGoogle Scholar
  53. Whitehouse, A. T., Peay, S., & Kindemba, V. (2009). Ark sites for white-clawed crayfish—guidance for the aggregates industry. In: Buglife—The Invertebrate Conservation Trust, UK.Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.International Centre for Ecohydraulics Research (ICER)University of SouthamptonSouthamptonUK
  2. 2.Dpto. de Ingeniería Rural y Agroalimentaria (DIRA)Universitat Politecnica de ValenciaValenciaSpain
  3. 3.Dipartimento di Scienze della Terra e dell’AmbienteUniversità degli Studi di PaviaPaviaItaly

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