Wildlife Biology in Practice, Iberian Lynx Special Issue

Iberian Lynx Special Issue, 2010; 6(3); 34-47;

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Online ISSN: 1646-2742
Copyright © 2010 Barbosa, Real.
Published by: Portuguese Wildlife Society

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    1. Garrote G, Pérez de Ayala R, 2015 Assessing unverified observation data used for estimating Iberian lynx distribution 61(5) 801 http://dx.doi.org/10.1007/s10344-015-0941-5
    2. Garrote G, Pérez de Ayala R, Reino L, Ferreira M, Martínez-Solano , Segurado P, Xu C, Márcia Barbosa A, 2016 Favourable areas for co-occurrence of parapatric species: niche conservatism and niche divergence in Iberian tree frogs and midwife toads () http://dx.doi.org/10.1111/jbi.12850
    3. Garrote G, Pérez de Ayala R, Reino L, Ferreira M, Martínez-Solano , Segurado P, Xu C, Márcia Barbosa A, Painer J, Goeritz F, Dehnhard M, Hildebrandt T, Naidenko S, Sánchez I, Quevedo Muñoz M, Jewgenow K, 2014 Hormone-induced luteolysis on physiologically persisting corpora lutea in Eurasian and Iberian lynx (Lynx lynx and Lynx pardinus) 82(4) 557 http://dx.doi.org/10.1016/j.theriogenology.2014.05.004
    4. Garrote G, Pérez de Ayala R, Reino L, Ferreira M, Martínez-Solano , Segurado P, Xu C, Márcia Barbosa A, Painer J, Goeritz F, Dehnhard M, Hildebrandt T, Naidenko S, Sánchez I, Quevedo Muñoz M, Jewgenow K, Real R, Barbosa A, Bull J, 2016 Species Distributions, Quantum Theory, and the Enhancement of Biodiversity Measures () syw072 http://dx.doi.org/10.1093/sysbio/syw072

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Favourable areas for expansion and reintroduction of Iberian lynx accounting for distribution trends and genetic variation of the wild rabbit


Although on a local scale Iberian lynx distribution is determined by the availability of prey rabbits, recent modelling analyses have uncovered broad-scale disagreements between these two species’ distribution trends. These analyses showed also that the lynx had become restricted to only a fraction of the rabbit’s genetic variability, and that this could be jeopardising its survival in the face of environmental hazards and uncertainty. In the present paper, a follow-up was carried out through the building of lynx and rabbit distribution models based on the most recent Spanish mammal atlas. The predictions of environmental favourability (which is an indicator of abundance) for lynx and rabbit were positively correlated within the lynx's current distribution area, but they were negatively correlated within the total Spanish area where lynx occurred in the 1980’s. Environmental favourability for rabbits was significantly higher where lynx maintains reproductive populations than where it recently disappeared, indicating that rabbit favourability plays an important role and can be a good predictor of lynx persistence. The lynx and rabbit models were extrapolated to predict favourable areas for both species in Spain as well as in Portugal, on the original scale of the distribution data (10x10 km) and on a 100 times finer spatial resolution (1x1 km). The lynx and rabbit models were also combined through fuzzy logic to forecast the potential for lynx occurrence incorporating information on favourable areas for its main prey. Several areas are proposed as favourable for lynx expansion or re-introduction, encompassing both countries and both genetic lineages of the rabbit.

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Lynx pardinus, Oryctolagus cuniculus, specialist predator, predator-prey biogeography, spatial genetic structure, model extrapolation, combined favourability.

Supplementary files


  1. Branco, M., Ferrand, N. & Monnerot, M. 2000. Phylogeography of the European rabbit (Oryctolagus cuniculus) in the Iberian Peninsula inferred from RFLP analysis of the cytochrome b gene. Heredity 85: 307-317.
    doi: 10.1046/j.1365-2540.2000.00756.x
  2. Johnson, W.E., Godoy, J.A., Palomares, F., Delibes, M., Fernandes, M., Revilla, E. & O'Brien, S.J. 2004. Phylogenetic and phylogeographic analysis of Iberian lynx populations. J. Hered. 95: 19-28.
    doi: 10.1046/j.1365-2540.2000.00756.x
  3. Palomares, F., Delibes, M., Revilla, E., Calzada, J. & Fedriani, J.M. 2001. Spatial ecology of Iberian lynx and abundance of European rabbits in southwestern Spain. Wildl. Monogr. 148: 1-36.
  4. Real, R., Barbosa A.M., Rodríguez A., García F.J., Vargas J.M., Palomo L.J. & Delibes M. 2009. Conservation biogeography of ecologically-interacting species: the case of the Iberian lynx and the European rabbit. Divers. Distrib. 15: 390-400.
    doi: 10.1111/j.1472-4642.2008.00546.x
  5. Rodríguez, A. & Delibes, M. 1992. Current range and status of the Iberian lynx Felis pardina Temminck, 1824 in Spain. Biol. Conserv. 61: 189-196
    doi: 10.1016/0006-3207(92)91115-9
  6. Palomo, L.J., Gisbert, J. & Blanco, J.C. 2007. Atlas y libro rojo de los mamíferos terrestres de España. [Atlas and red book of the terrestrial mammals of Spain]. Dirección General para la Biodiversidad ­ SECEM ­ SECEMU, Madrid.
  7. Palomo, L.J., & Gisbert, J. 2002. Atlas de los mamíferos terrestres de España. [Atlas of the terrestrial mammals of Spain]. Dirección General de Conservación de la Naturaleza-SECEM-SECEMU, Madrid.
  8. Delibes-Mateos, M., Ferreras, P. & Villafuerte R. 2009. European rabbit population trends and associated factors: a review of the situation in the Iberian Peninsula. Mamm. Rev. 39: 124-140.
    doi: 10.1111/j.1365-2907.2009.00140.x
  9. Barbosa, A.M., Real, R. & Vargas, J.M. 2009. Transferability of environmental favourability models in geographic space: the case of the Iberian desman (Galemys pyrenaicus) in Portugal and Spain. Ecol. Model. 220: 747-754.
    doi: 10.1016/j.ecolmodel.2008.12.004
  10. Barbosa, A.M., Real, R., Olivero, J. & Vargas, J.M. 2003. Otter (Lutra lutra) distribution modeling at two resolution scales suited to conservation planning in the Iberian Peninsula. Biol. Conserv. 114: 377-387.
    doi: 10.1016/S0006-3207(03)00066-1
  11. Barbosa, A.M., Real, R. & Vargas, J.M. 2010. Use of coarse-resolution models of species'distributions to guide local conservation inferences. Conserv. Biol., in press.
    doi: 10.1111/j.1523-1739.2010.01517.x
  12. Austin, M.P. 1980. Searching for a model for use in vegetation analysis. Vegetatio 42: 11-21.
    doi: 10.1007/BF00048865
  13. Guisan, A., Weiss, S.B. & Weiss, A.D. 1999. GLM versus CCA spatial modeling of plant specie distribution. Plant Ecol. 143: 107-122.
    doi: 10.1023/A:1009841519580
  14. Post, E. & Forchhammer, M.C. 2002. Synchronization of animal population dynamics by large-scale climate. Nature 420: 168-171.
    doi: 10.1038/nature01064
  15. Borcard, D., Legendre, P. & Drapeau, P. 1992. Partialling out the spatial component of ecological variation. Ecology 73: 1045-1055.
    doi: 10.2307/1940179
  16. Diniz-Filho, J.A.F., Bini, L.M. & Hawkins, B.A. 2003. Spatial autocorrelation and red herrings in geographical ecology. Global Ecol. Biogeogr. 12: 53-64.
    doi: 10.1046/j.1466-822X.2003.00322.x
  17. Kühn, I., 2007. Incorporating spatial autocorrelation may invert observed patterns. Divers. Distrib. 13: 66-69.
  18. Legendre, P. 1993. Spatial autocorrelation: trouble or new paradigm? Ecology 74: 1659-1673.
    doi: 10.2307/1939924
  19. Barbosa, A.M., Real, R., Márquez, A.L. & Rendón, M.A. 2001. Spatial, environmental and human influences on the distribution of otter (Lutra lutra) in the Spanish provinces. Divers. Distrib. 7: 137-144.
    doi: 10.1046/j.1472-4642.2001.00104.x
  20. Real, R., Barbosa, A.M., Porras, D., Kin, M.S., Márquez, A.L., Guerrero, J.C., Palomo, L.J., Justo, E.R. & Vargas, J.M. 2003. Relative importance of environment, human activity and spatial situation in determining the distribution of terrestrial mammal diversity in Argentina. J. Biogeogr. 30: 939-947.
    doi: 10.1046/j.1365-2699.2003.00871.x
  21. U.S. Geological Survey. 1996. GTOPO30. In: Land Processes Distributed Archive Center. United
    States Geological Survey, Denver. Available from http://www.etsimo.uniovi.es/~feli/Data/Datos.html. Cited 19 October 1999.
  22. Font, I. 1983. Atlas climático de España. [Climatic atlas of Spain]. Instituto Nacional de Meteorología, Madrid.
  23. Font, I. 2000. Climatología de España y Portugal. [Climatology of Spain and Portugal]. Ediciones Universidad de Salamanca, Salamanca.
  24. I.G.N. 1999. Mapa de carreteras. Península Ibérica, Baleares y Canarias. [Road map. Iberian Peninsula, Balearic and Canary Islands]. Instituto Geográfico Nacional and Ministerio de Fomento, Madrid.
  25. GRASS Development Team. 2009. Geographic resources analysis support system (GRASS). Open Source Geospatial Foundation, Vancouver, British Columbia. Available from: http://grass.osgeo.org. Cited 19 January 2009.
  26. Quantum GIS Development Team. 2009. Quantum GIS. Geospatial Foundation, Vancouver, British Columbia.
    Available from: http://qgis.osgeo.org. Cited 19 January 2009.
  27. R Development Core Team. 2009. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.
    Available from: http://www.r-project.org. Cited 19 January 2009.
  28. Real, R., Barbosa, A.M. & Vargas, J.M. 2006. Obtaining environmental favourability functions from logistic regression. Environ. Ecol. Stat. 13: 237-245.
    doi: 10.1007/s10651-005-0003-3
  29. Meynard, C.N. & Quinn, J.F. 2007. Predicting species distributions: a critical comparison of the most common statistical models using artificial species. J.Biogeogr. 34: 1455-1469.
    doi: 10.1111/j.1365-2699.2007.01720.x
  30. Randin, C.F., Dirnböck, T., Dullinger, S., Zimmermann, N.E., Zappa, M. & Guisan, A. 2006. Are niche-based species distribution models transferable in space? J. Biogeogr. 33: 1689-1703.
    doi: 10.1111/j.1365-2699.2006.01466.x
  31. Jiménez-Valverde, A. & Lobo, J. 2006. Distribution Determinants of Endangered Iberian Spider Macrothele calpeiana (Araneae, Hexathelidae). Environ. Entomol. 35: 1491-1499.
    doi: 10.1603/0046-225X-35.6.1491
  32. Akaike, H. 1973. Information theory and an extension of the maximum likelihood principle. In: Petrov, B. N. & Csaki, F. (eds.), Proceedings of the Second International Symposium on Information Theory. Akadémia Kiadó, Budapest, pp. 267-281.
  33. Crawley, M.J. 2007. The R Book. John Wiley & Sons, Chichester (UK).
    doi: 10.1002/9780470515075
  34. Benjamini, Y. & Hochberg, Y. 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B. 57: 289-300.
  35. García, L.V. 2003. Controlling the false discovery rate in ecological research. Trends Ecol. Evol. 18: 553-554.
    doi: 10.1016/j.tree.2003.08.011
  36. Hosmer, D.W. & Lemeshow, S. 2000. Applied Logistic Regression (2nd ed). John Wiley and Sons, New York.
    doi: 10.1002/0471722146
  37. Legendre, P. & Legendre, L. 1998. Numerical ecology (2nd ed). Elsevier, Amsterdam.
  38. Fielding, A.H. & Bell, J.F. 1997. A review of methos for the assessment of prediction errors in conservation presence/absence models. Environ. Conserv. 24: 38-49.
    doi: 10.1017/S0376892997000088
  39. Lobo, J.M., Jiménez-Valverde, A. & Real, R., 2008. AUC: a misleading measure of the performance of predictive distribution models. Global Ecol. Biogeogr. 17: 145-151.
    doi: 10.1111/j.1466-8238.2007.00358.x
  40. Mason, S.J. & Graham, N.E. 2002.Areas beneath the relative operating characteristics (ROC) and levels (ROL) curves: statistical significance and interpretation. Q. J. R. Meteorol. Soc. 128: 2145-2166.
    doi: 10.1256/003590002320603584
  41. Araújo, M.B. & Williams, P.H. 2000. Selecting areas for species persistence using occurrence data. Biol. Conserv. 96: 331-345.
    doi: 10.1016/S0006-3207(00)00074-4
  42. Barbosa, A.M., Segovia, J.M., Vargas, J.M., Torres, J., Real, R. & Miquel, J. 2005. Predictors of red fox (Vulpes vulpes) helminth parasite diversity in the provinces of Spain. Wildl. Biol. Pract. 1: 3-14.
    doi: 10.2461/wbp.2005.1.2
  43. Estrada, A., Real, R., & Vargas, J.M. 2008. Using crisp and fuzzy modelling to identify favourability hotspots useful to perform gap analysis. Biodivers. Conserv. 17: 857-871.
    doi: 10.1007/s10531-008-9328-1
  44. I.P.C.C. 2007. Climate Change 2007: Synthesis Report. Summary for Policymakers. Intergovernmental Panel on Climate Change, Geneva.
  45. Carter, R.N. & Prince, S.D. 1981. Epidemic models used to explain biogeographical distributional limits. Nature 293: 644-645
    doi: 10.1038/293644a0
  46. Levins, R. 1969. Some demographic and genetic consequences of environmental heterogeneity for biological control. Bull. Entomol. Soc. Am. 15: 237-240.
  47. Hanski, I. & Simberloff, D. 1997. The metapopulation approach, its history, conceptual domain, and application to conservation. In: Hanski, I. & Gilpin, M. (eds.), Metapopulation biology: ecology, genetics and evolution. Academic Press, San Diego, pp. 5-26.
  48. Muñoz, A.R., Real, R., Barbosa, A.M. & Vargas, J.M. 2005. Modelling the distribution of Bonelli's Eagle in Spain: Implications for conservation planning. Divers. Distrib. 11: 477-486.
    doi: 10.1111/j.1366-9516.2005.00188.x