Mammalian Biology

, Volume 98, Issue 1, pp 128–136 | Cite as

Potential distribution and areas for conservation of four wild felid species in Mexico: Conservation planning

  • O. Monroy-Vilchis
  • Z. Zarco-González
  • M. M. Zarco-GonzálezEmail author
Original investigation


Knowing the potential distribution of species helps to focus conservation efforts more effectively, mainly when dealing with endangered species. The aim of this study was to generate potential distribution models for four species of small wild felids in Mexico (Leopardus pardalis, Leoparduswiedii, Lynx rufus and Puma yagouaroundi). The models were generated based on felids presence records, and topographic, anthropic and vegetation drivers. We used 473 records (171 for L. pardalis, 140 for L. wiedii, 86 for L. rufus and 76 for P. yagouaroundi) to build eleven models per species to then select the three with the best performance and included them in ensemble models. These were based on the formula of the weighted average, which considers the performance of the algorithms evaluated with a subsample of testing records, from which the area under the curve is calculated. In this way, in the ensemble model the consistent zones between algorithms are included, but the one with the best performance predominates. The species with the largest potential distribution area was L. pardalis with 34.3% of the national territory, while L. rufus had the smallest area (14.3%). In the four species a unique set of variables was identified that influence the probability of presence, however the altitude, the arid vegetation and the population density were important variables for three of the four species. We verified our models with recently published presence records. The results of this study reflect a robust analysis of the current and potential distribution of four species of wild felids in Mexico. In addition to being the first step to develop effective conservation strategies at national and local levels.


Conservation Potential distribution Mexico Small felids Conservation planning 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Anderson, R.P., Lew, D., Peterson, A.T., 2003. Evaluating predictive models of species distributions: criteria for selecting optimal models. Ecol. Modell. 162, 211-232, Scholar
  2. Aranda, M., 2005. Puma yagouaroundi. In: Ceballos, G., Oliva, G. (Eds.), Los mamíferos silvestres de México. CONABIO - UNAM - Fondo de Cultura Económica, México D.F, pp. 358-369.Google Scholar
  3. Aranda, M., Valenzuela-Galván, D., 2015. Registro notable de margay (Leopardus wiedii) en el bosque mesófilo de montana de Morelos, México. Rev. Mex. Biodivers. 86, 1110-1112, Scholar
  4. Araújo, M., Pearson, R., Thuiller, W., Erhard, M., 2005. Validation of species climate impact models under climate change. Glob. Chang. Biol. 11, 1504-1513, Scholar
  5. Aubry, K.B., Raley, C.M., McKelvey, K.S., 2017. The importance of data quality for generating reliable distribution models for rare, elusive, and cryptic species. PLoS One 12 (6), e0179152, Scholar
  6. Ávila-Villegas, S., Lamberton-Moreno, J., 2013. Wildlife survey and monitoring in the sky Island region with an emphasis on neotropical felids. In: Gottfried, Gerald J., Ffolliott, Peter F., Gebow, Brooke S., Eskew, Lane G., Collins, Loa C. (Eds.), Merging Science and Management in a Rapidly Changing World: Biodiversity and Management of the Madrean Archipelago III and 7th Conference on Research and Resource Management in the Southwestern Deserts; 2012 May 1-5; Tucson, AZ. Proceedings. RMRS-P-67. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, pp. 441-447.Google Scholar
  7. Campbell, L., 2003. Jaguarundi. In: Endangered and Threatened Animals of Texas Their Life History and Management. Wildlife Division. 4200 Smith School Road Austin, Texas 78744.Google Scholar
  8. Ceballos, G., Blanco, S., González, C., Martínez, E., 2006. ‘Lynx rufus. Distribución potencial’. Extraído del proyecto DS006’ Modelado de la distribución de las especies de mamíferos de México para un análisis GAP.Google Scholar
  9. Center for International Earth Science Information Network-CESIN-Columbia University and Centro Internacional de Agricultura Tropical -CIAT-, 2010. Gridded Population of the World, Versión 3 (GPWv3): Population Density Grid, Future Estimates. NASA Socioeconomic Data and Aplications Center SEDAC, Palisades, NY (Accessed 15.05.2016).Google Scholar
  10. Céspedes-Flores, S., Moreno-Sánchez, E., 2010. Estimación del valor de la pérdida de recurso forestal y su relación con la reforestación en las entidades federativas de México. Investigación ambiental 2, 5-13.Google Scholar
  11. Clark Labs, 2006. Idrisi 15: the Andes edition. Clark Photo Labs, Worcester, Massachusetts, MA, USA.Google Scholar
  12. CONABIO, 2015. NATURALISTA Plataforma de Ciencia (Accessed: 20-05-2015) Scholar
  13. Coronado-Quibrera, W., 2011. Distribución geográfica y ecológica del jaguarundi (Pumayaguaroundi) en el estado de San Luis Potosí, México. Master thesis. Colegio de Postgraduados. Montecillo, Texcoco, Edo. de México.Google Scholar
  14. Crooks, K., Burdett, C., Theobald, D., Rondinini, C., Boitani, L., 2011. Global patterns of fragmentation and connectivity of mammalian carnivore habitat. Philos. Trans. R. Soc. Lond. B Biol. Sci. 366, 2642-2651, doi: [10.1098/rstb.2011.0120].PubMedPubMedCentralCrossRefGoogle Scholar
  15. Domíguez-Vega, H., Monroy-Vilchis, O., Balderas-Valdivia, C., Gienger, C.M., Ariano-Sánchez, D., 2012. Predicting the potential distribution of the beaded lizard and identification of priority areas for conservation. J. Nat. Conserv. 20 (4), 247-4253, Scholar
  16. Drake, J.M., Bossenbroek, J.M., 2009. Profiling ecosystem vulnerability to invasion by zebra mussels with support vector machines. Theor. Ecol. 4, 189-198, Scholar
  17. Engler, R., Guisan, A., Rechsteiner, L., 2004. An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data. J. Appl. Ecol. 41, 263-274, Scholar
  18. Espinosa, C., Trigo, T., Tirelli, F., Gonc¸alves da Silva, L., Eizirik, E., Queirolo, D., Mazim, D., Peters, F., Favarini, M., de Freitas, T., 2017. Geographic distribution modeling of the margay (Leopardus wiedii) and jaguarundi (Puma yagouaroundi): a comparative assessment. J. Mammal. 1, 252-262, Scholar
  19. Ferraz, K., Ferraz, S., Cunha de Paula, R., Beisiegel, B., Breitenmoser, C., 2012. Species distribution modeling for conservation purposes. Natureza Conservac¸ao 10(2), 214-220.CrossRefGoogle Scholar
  20. Grigione, M., Menke, K., López-González, C., List, R., Banda, A., Carrera, J., Carrera, J., Giordano, A., Morrison, J., Sterrnberg, M., Thomas, R., Van, B., 2009. Identifying potential conservation areas for felids in the USA and Mexico: integrating reliable knowledge across an international border. Oryx 43, 78-86, Scholar
  21. Guisan, A., Zimmermann, N., 2000. Predictive habitat distribution models in ecology. Ecol. Modell. 135, 147-186, Scholar
  22. Haddad, N., Brudving, L., Clobert, J., et al., 2015. Habitat fragmentation and its lasting impact on Earth’s ecosystems. Sci. Adv. 1 (2), e1500052, Scholar
  23. Haines, A., Tewes, M., Laack, L., 2005. Survival and sources of mortality in ocelots. J. Wildl. Manag. 69, 255-263.CrossRefGoogle Scholar
  24. Hanley, J., McNeil, B., 1982. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143, 29-36, Scholar
  25. Hartley, S., Harris, R., Lester, P., 2006. Quantifying uncertainty in the potential distribution of an invasive species: climate and the Argentine ant. Ecol. Lett. 9, 068-1079, Scholar
  26. Hirzel, A.H., Hausser, J., Chessel, D., Perrin, N., 2002. Ecological-niche factor analysis: how to compute habitat-suitability maps without absence data? Ecology 83 (7), 2027-2036.CrossRefGoogle Scholar
  27. Hirzel, A., Arlettaz, R., 2003. Modelling habitat suitability for complex species distribucions by environmental-distance geometric mean. J. Environ. Manage. 32, 614-623, Scholar
  28. Hirzel, A., Hausser, J., Perrin, N., URL: 2004. Biomapper4.0. Lab. of Conservation Biology, Department of Ecology and Evolution. University of Lausanne Scholar
  29. Hodge, A., 2014. Habitat selection of the margay (Leopardus wiedii) in the eastern Andean foothills of Ecuador. Mammalia 78, 351-358, Scholar
  30. Holbrook, J., Caso, A., De Young, R., Tewes, M., 2013. Population genetics of jaguarundis in Mexico: implications for future research and conservation. Wildl. Soc. Bull. 37, 336-341, Scholar
  31. INE (Instituto Nacional de Ecología), 2007. Transformación de los Sistemas Naturales de México (Accessed: 20.05.2016) Scholar
  32. INEGI (Instituto Nacional de Estadística y Geografía), Escala 1:250 000. Serie VI 2015. Conjunto de datos vectoriales de Uso del suelo y vegetación. Scholar
  33. INEGI (Instituto Nacional de Estadística y Geografía), 2014. INEGI (Instituto Nacional de Estadística y Geografía) (Accessed: 20.05.2016) Scholar
  34. Liu, C., Berry, P., Dawson, T., Pearson, R., 2005. Selecting thresholds of occurrence in the prediction of species distribution. Ecography 28, 385-393, Scholar
  35. Marmion, M., Parviaenen, M., Luoto, M., Heikkinen, R., Thuiller, W., 2009. Evaluation of consensus methods in predictive species distribution modelling. Divers. Distrib. 15, 59-69, Scholar
  36. Martínez-Calderas, J., Rosas-Rosas, O., Martínez-Montoya, J., Tarango-Arámbula, L., Clemente-Sánchez, F., Crosby-Galván, M., Sánchez-Hermosillo, M., 2011. Distribución del ocelote (Leopardus pardalis) en San Luis Potosí, México. Rev. Mex. Biodivers. 82, 997-1004, Scholar
  37. Muñoz, M., Giovanni, R., Siqueira, M., Sutton, T., Brewer, P., Pereira, R., Canhos, D., Canhos, V., 2009. openModeller: a generic approach to species’ potential distribution modelling. GeoInformatica 15, 111-135, Scholar
  38. Newbold, T., 2010. Applications and limitations of museum data for conservation and ecology, with particular attention to species distribution models. Prog. Phys. Geogr.: Earth Environ. 34 (1), 3-22, Scholar
  39. Ortega-Huerta, M., Vega-Rivera, J., 2017. Validating distribution models for twelve endemic bird species of tropical dry forest in western Mexico. Ecol. Evol. 19, 7672-7686, https://doi: 10.1002/ece3.3160.CrossRefGoogle Scholar
  40. Pearson, R., Dawson, T., Liu, C., 2004. Modelling species distributions in Britain: a hierarchical integration of climate and land-cover data. Ecography 27, 285-298, Scholar
  41. Pérez-Irineo, G., Santos-Moreno, A., 2014. Density, distribution, and activity of the ocelot Leopardus pardalis (Carnivora: felidae) in Southeast Mexican rainforests. Rev. Biol. Trop. 62, 1421-1432, Scholar
  42. Peterson, A., Papes, M., Eaton, M., 2007. Transferability and model evaluation in ecological niche modeling: a comparison of GARP and Maxent. Ecography 30, 550-560, Scholar
  43. Phillips, S., Anderson, R., Schapire, R., 2006. Maximum entropy modeling of species geographic distributions. Ecol. Modell. 190, 231-259, Scholar
  44. Pliscoff, P., Fuentes-Carrillo, T., 2011. Modelación de la distribución de especies y ecosistemas en el tiempo y en el espacio: una revisión de las nuevas herramientas y enfoques disponibles. Rev. Geogr. Norte Gd. 48, 61-79, Scholar
  45. Ramírez-Bravo, O., Bravo-Carrete, E., Hernández-Santín, C., Schinkel-Brault, S., Kinnear, C., 2010. Ocelot (Leopardus pardalis) distribution in the state of Puebla, Central Mexico. Therya 1, 111-120, Scholar
  46. Roberts, N., Crimmins, S., 2010. Bobcat population status and management in North America: evidence of large-scale population increase. J. Fish Wildl. Manag. 1, 169-174, Scholar
  47. Rocha-Mendes, F., Bianconi, G., 2009. Opportunistic predatory behavior of margay, Leopardus wiedii (Schinz, 1821) in Brazil. Mammalia 73, 151-152, Scholar
  48. Romero, R., 2005. Lynx rufus. In: Ceballos, G., Oliva, G. (Eds.), Los mamíferos silvestres de México: 362-364. CONABIO - UNAM - Fondo de Cultura Económica, México D.F.Google Scholar
  49. SEMARNAT (Secretaría del Medio Ambiente y Recursos Naturales), 2009. Inventario Nacional Forestal y de Suelos México 2004-2009. Una herramienta que da certeza a la planeación, evaluación y el desarrollo forestal de México. Press, Zapopan, Jalisco, México.Google Scholar
  50. Stockman, A., Beamer, D., Bond, J., 2006. An evaluation of a GARP model as an approach to predicting the spatial distribution of non-vagile invertebrate species. Divers. Distrib. 12, 81-89, Scholar
  51. Stockwell, D., Peters, D., 1999. The GARP modelling system: problems and solutions to automated spatial prediction. Int. J. Geogr. Inf. Sci. 13, 143-158.CrossRefGoogle Scholar
  52. Sunquist, M., Sunquist, F., 2002. Wild Cats of the World. University of Chicago Press, Chicago.CrossRefGoogle Scholar
  53. USGS (United States Geological Survey), 2007. Shuttle Radar Topography Mision (SRTM) 3-arc Second ARTM Format Documentation. USGS/NASA Scholar
  54. Valdez-Jiménez, D., García-Balderas, M., Quintero-Díaz, G., 2013. Presencia del ocelote (Leopardus pardalis) en la “Sierra del laurel”, municipio de Calvillo, Aguascalientes, México. Nota científica. Acta Zoológica Mexicana (n.s.) 29, 688-692.Google Scholar
  55. Valenzuela, D., Vázquez, L, 2007. Consideraciones para priorizar la conservación de carnívoros mexicanos. Pp. 197-214 inTópicos en sistemática, biogeografía, ecología y conservación de mamíferos. Universidad Autónoma del Estado de Hidalgo, Pachuca, México.Google Scholar
  56. Velazco-Macías, C., Peña-Mondragón, J., 2015. Nuevo registro de ocelote (Leopardus pardalis) en el estado de Nuevo León, México. Acta Zoológica Mexicana (n.s.) 31, 470-472.CrossRefGoogle Scholar
  57. Zarco-González, M., Monroy-Vilchis, O., Alaníz, J., 2013. Spatial model of livestock predation by jaguar and puma in Mexico: conservation planning. Biol. Conserv. 159, 80-87, Scholar
  58. SEMARNAT (Secretaría del Medio Ambiente y Recursos Naturales), 2010. PROYECTO de Modificación del Anexo Normativo III, Lista de especies en riesgo de la Norma Oficial Mexicana NOM 059 SEMARNAT 2010, Protección ambiental-Especies nativas de México de flora y fauna silvestres-Categorías de riesgo y especificaciones para su inclusión, exclusión o cambio-Lista de especies en riesgo, publicada el 30 de diciembre de 2010.Google Scholar

Copyright information

© Deutsche Gesellschaft für Säugetierkunde 2019

Authors and Affiliations

  • O. Monroy-Vilchis
    • 1
  • Z. Zarco-González
    • 1
  • M. M. Zarco-González
    • 1
    Email author
  1. 1.Center for Research in Applied Biological Sciences (CICBA), Autonomous University of State of Mexico, Carretera Toluca-IxtlahuacaUnidad San Cayetano de MorelosTolucaMexico

Personalised recommendations