Hostname: page-component-7c8c6479df-995ml Total loading time: 0 Render date: 2024-03-27T20:05:15.549Z Has data issue: false hasContentIssue false

Potential distributional changes and conservation priorities of endemic amphibians in western Mexico as a result of climate change

Published online by Cambridge University Press:  07 October 2013

ANDRÉS GARCÍA
Affiliation:
Estación de Biología Chamela, Instituto de Biología, Universidad Nacional Autónoma de México, Apdo Postal 21, San Patricio, Jalisco, CP 48980, México
MIGUEL A. ORTEGA-HUERTA*
Affiliation:
Estación de Biología Chamela, Instituto de Biología, Universidad Nacional Autónoma de México, Apdo Postal 21, San Patricio, Jalisco, CP 48980, México
ENRIQUE MARTÍNEZ-MEYER
Affiliation:
Departamento de Zoología, Instituto de Biología, Universidad Nacional Autónoma de México, Circuito exterior s/n, Ciudad Universitaria, Copilco/Coyoacán, Apdo Postal 70-153, CP 04510, México
*
*Correspondence: Miguel A. Ortega-Huerta Tel: + 315 3510202 Fax: + 315 3510200 e-mail: maoh@ibiologia.unam.mx

Summary

There is a growing concern regarding the conservation status of amphibian species worldwide; they are more threatened and declining more rapidly than mammals or birds, and Mexico is considered one of the richest countries on Earth in terms of reptile and amphibian species. Composite models of the current distribution patterns of endemic amphibians in western Mexico were used to predict their potential distributional changes as a consequence of expected climatic changes. The models identified the most significant conservation areas within the region (hotspots), considering existing natural protected areas (NPAs) and previously recognized terrestrial priority regions for conservation (TPRCs). Three niche modelling algorithms (Bioclim, GARP and MaxEnt) used 2412 locality records for 29 species to model their climate envelopes under current and future conditions for the years 2020, 2050 and 2080. The models indicated that overall species persistence was 60% for the years 2020 and 2050, but dropped to < 20% by the year 2080. The current network of NPAs included only 8% of the areas that currently possess the greatest predicted potential richness (16–21 species), and, by 2050, the models indicate they will encompass only 3% of these areas. Six TPRCs included 44% of currently predicted areas with the highest potential species richness, but, by 2050, models predicted only 3% of such areas would persist within one TPRC. Higher uncertainty levels and variability among species surrounded the 2080 projections generated by the three algorithms. Recognition of the potential effects of climate change and consideration of the conservation value of the six TPRCs identified in this study may counteract the potential consequences of climate change on biodiversity in Mexico.

Type
Papers
Copyright
Copyright © Foundation for Environmental Conservation 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anderson, R.P. & Martínez-Meyer, E. (2004) Modeling species’ geographic distributions for conservation assessments: an implementation with the spiny pocket mice (Heteromys) of Ecuador. Biological Conservation 116: 167179.Google Scholar
Anderson, B.J., Akcakaya, H.R., Araújo, M.B., Fordham, D.A., Martinez-Meyer, E., Thuiller, W. & Brook, B.W. (2009) Dynamics of range margins for metapopulations under climate change. Proceedings of the Royal Society of London B 276: 1415.Google ScholarPubMed
Araújo, M.B., Whittaker, R.J., Ladle, R.J. & Erhard, M. (2005) Reducing uncertainty in projections of extinction risk from climate change. Global Ecology and Biogeography 14: 529538.Google Scholar
Araújo, M.B. & New, M. (2006) Ensemble forecasting of species distributions. Trends in Ecology and Evolution 22: 4247.CrossRefGoogle ScholarPubMed
Arriaga, L., Espinoza, J.M., Aguilar, C., Martinez, E., Gomez, L. & Loa, E. (2000) Regiones terrestres prioritarias de México. Report. Comisión Nacional para el Conocimiento y uso de la Biodiversidad (CONABIO), Mexico.Google Scholar
Beale, C.M. & Lennon, J.J. (2013) Incorporating uncertainty in predictive species distribution modelling. Philosophical Transactions of the Royal Society B 367: 247258.Google Scholar
Beebee, T.J.C. & Griffiths, R.A. (2005) The amphibian decline crisis: a watershed for conservation biologys? Biological Conservation 125: 271285.Google Scholar
Biggs, R., Simons, H., Bakkenes, M., Scholesa, R.J., Eickhout, B., Van Vuuren, D. & Alkemade, R. (2008) Scenarios of biodiversity loss in southern Africa in the 21st century. Global Environmental Change 18: 296309.CrossRefGoogle Scholar
Blaustein, A.R. & Wake, D.B. (1990) Declining amphibian populations: a global phenomenon? Trends in Ecology and Evolution 5: 203204.Google Scholar
Blaustein, A.R., Wake, D.B. & Sousa, W.P. (1994) Amphibian declines: judging stability, persistence, and susceptibility of populations to local and global extinctions. Conservation Biology 8, 6071.Google Scholar
Blaustein, A.R. & Kiesecker, J.M. (2001) Complexity in conservation: lessons from the global decline of amphibian populations. Ecology Letters 5: 597608 CrossRefGoogle Scholar
Buckley, L.B. & Jetz, W. (2007) Environmental and historical constraints on global patterns of amphibians richness. Proceedings of the Royal Society B: Biological Sciences 274: 1167–73.CrossRefGoogle ScholarPubMed
Buisson, L., Thuiller, W., Casajus Lek, S. & Grenouillet, G. (2010) Uncertainty in ensemble forecasting of species distribution. Global Change Biology 16: 11451157 Google Scholar
Busby, J.R. (1991) BIOCLIM: a bioclimate analysis and prediction system. In: Nature Conservation: Cost Effective Biological Surveys and Data Analysis, ed. Margules, C.R. & Austin, M.P., pp. 6468. Melbourne, Australia and Cambridge, UK: CSIRO and Cambridge University Press.Google Scholar
Caldwell, J.P. (1987) Demography and life history of two species of chorus frogs (Anura: Hylidae) in South Carolina. Copeia 1987: 114127.CrossRefGoogle Scholar
Carey, C. & Alexander, M.A. (2003) Climate change and amphibian declines: is there a link? Diversity and Distributions 9: 111121.CrossRefGoogle Scholar
Carroll, C., Dunk, J.R., & Moilanen, A. (2010) Optimizing resiliency of reserve networks to climate change: multispecies conservation planning in the Pacific Northwest, USA. Global Change Biology 16: 891904.CrossRefGoogle Scholar
Ceballos, G. & García, A. (1995) Conserving neotropical biodiversity: the role of dry forest in western Mexico. Conservation Biology 9: 13491356.CrossRefGoogle Scholar
CONABIO (2004) Comisión Nacional para el Conocimiento y Uso de la Biodiversidad. Regiones Terrestres Prioritarias, Mapa escala 1:1000000, CONABIO, México.Google Scholar
CONANP (2010) Áreas Naturales Protegidas Federales de México. Mapa Interactivo. Comisión Nacional de áreas Protegidas, Morelia, Michoacán de Ocampo, México [www document]. URL http://conanp.gob.mx/sig/ Google Scholar
Corey, S.J. & Waite, T.A. (2008) Phylogenetic autocorrelation of extinction threat in globally imperilled amphibians. Diversity and Distributions 14: 614629.CrossRefGoogle Scholar
D'Amen, M. & Bombi, P. (2009) Global warming and biodiversity: evidence of climate-linked amphibian declines in Italy. Biological Conservation 104: 30603067.CrossRefGoogle Scholar
Dockerty, T., Lovett, A. & Watkinson, A. (2003) Climate change and nature reserves: examining the potential impacts, with examples from Great Britian. Global Environmental Change 13: 125135.CrossRefGoogle Scholar
Donnelly, M.A. & Crump, M.L. (1998) Potential effects of climate change on two neotropical amphibian assemblages. Climatic Change 39: 541561.CrossRefGoogle Scholar
Duellman, W.E.E. (1999) Patterns of Distribution of Amphibians. Baltimore, MD, USA: Johns Hopkins University Press.Google Scholar
Elith, J. & Graham, C.H. (2009) Do they? How do they? WHY do they differ? On finding reasons for differing performances of species distribution models. Ecography 32: 6677.CrossRefGoogle Scholar
Elith, J., Phillips, S.J., Hastie, T., Dudík, M., Chee, W.Y. & Yates, C.J. (2011) A statistical explanation of MaxEnt for ecologists. Diversity and Distributions 17: 4357.Google Scholar
Fielding, A.H & Bell, J.F. (1997) A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation 24: 3849.Google Scholar
Fitzpatrick, M.C. & Hargrove, W.W. (2009) The projection of species distribution models and the problem of non-analog climate. Biodiversity Conservation 18: 22552261.Google Scholar
Flores-Villela, O. & Goyenechea, I. (2003) Patrones de distribución de anfibios y reptiles de Mexico. In: Una perspectiva latinoamericana de la biogeografía, ed. Morrone, J.J. & Llorente-Bousquets, J., pp. 289296. Mexico: CONABIO/UNAM.Google Scholar
Fordham, D.A., Akcakaya, H.R, Aráujo, M.B., Elith, J., Keith, D.A., Pearson, R., Auld, T.D., Mellin, C., Morgan, J.W., Reagan, T.J., Tozer, M., Watts, M.J., White, M., Wintle, B.A., Yates, C. & Brook, B.W. (2012) Plant extinction risk under climate change: are forecast range shifts an indicator of species vulnerability to global warming? Global Change Biology 18: 13571371.CrossRefGoogle Scholar
Fouquet, A., Ficetola, G.F., Haigh, A. & Gemmell, N. (2010) Using ecological niche modelling to infer past, present and future environmental suitability for Leiopelma hochstetteri, an endangered New Zealand native frog. Biological Conservation 143: 13751384.Google Scholar
García, A. (2006) Using ecological niche modelling to identify diversity hotspots for the herpetofauna of Pacific lowlands and adjacent interior valleys of Mexico. Biological Conservation 130: 2546.Google Scholar
Guisan, A. & Thuiller, W. (2005) Predicting species distribution: offering more than simple habitat models. Ecology Letters 8: 9931009.Google Scholar
Guisan, A. & Zimmermann, N.E. (2000) Predictive habitat distribution models in ecology. Ecological Modelling 135: 147186.Google Scholar
H-Acevedo, D. & Currie, D.J. (2003) Does climate determine broad-scale patterns of species richness? A test of the causal link by natural experiment. Global Ecology and Biogeography 12: 461473.Google Scholar
Hagerman, S., Dowlatabadi, H., Satterfield, T. & McDaniels, T. (2010) Expert views on biodiversity conservation in an era of climate change. Global Environmental Change 20: 192207.CrossRefGoogle Scholar
Hannah, L., Midgley, G.F. & Millar, D. (2002) Climate change-integrated conservation strategies. Global Ecology and Biogeography 11: 485495.Google Scholar
Hannah, L., Midgley, G., Andelman, S., Araújo, M., Hughes, G., Martinez-Meyer, E., Pearson, R. & Williams, P. (2007) Protected area needs in a changing climate. Frontiers in Ecology and the Environment 5: 131138.CrossRefGoogle Scholar
Hickling, R., Roy, D.B., Hill, J.K., Fox, R. & Thomas, C.D. (2006) The distributions of a wide range of taxonomic groups are expanding polewards. Global Change Biology 12: 450455.Google Scholar
Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 19651978.Google Scholar
Houlahan, J.E., Findlay, C.S., Schmidt, B.R., Meyer, A.H. & Kuzmin, S.L. (2000) Quantitative evidence for global amphibian population declines. Nature 404: 752755.Google Scholar
Hubberty, C.J. (1994) Applied Discriminant Analysis. New York, NY, USA: Wiley Interscience: 466 pp.Google Scholar
Hutchison, V.H. & Dupré, K. (1992) Thermoregulation. In: Environmental Physiology of the Amphibia, ed. Feder, M.E. & Burggren, W.W., pp. 206–49. Chicago, Illinois, USA: University of Chicago Press.Google Scholar
INEGI (2005) Conjunto de Datos Vectoriales de la Carta de Uso del Suelo y Vegetación, Escala 1: 250,000, Serie III (Continuo Nacional). Edition Primera. Instituto Nacional de Estadística, Geografía e Informática, Aguascalientes, Ags. México.Google Scholar
Keith, D.A., Akcakaya, H.R., Thuiller, W., Midgley, G.F., Pearson, R.G., Phillips, S.J., Regan, H.M., Araújo, M.B. & Rebelo, T.G. (2008) Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models. Biology Letters 4: 560563.Google Scholar
Lawler, J.J., White, D., Neilson, R.P. & Blaustein, A.R. (2006) Predicting climate- induced range shifts: model differences and model reliability. Global Change Biology 12: 15681584.Google Scholar
Lawler, J.J., Shafer, S.I., White, D., Kareiva, P., Maurer, E.P., Blaustein, A.R. & Bartlein, P.J. (2009) Projected climate-induced faunal change in the Western Hemisphere. Ecology 90: 588597.Google Scholar
Leemans, R. & Eickout, B. (2004) Another reason for concern and global impacts on ecosystems for different levels of climate change. Global Environmental Change 14: 219228.Google Scholar
Lemieux, C.J. & Scott, D.J. (2005) Climate change, biodiversity conservation and protected area planning in Canada. Canadian Geography 49: 384399.Google Scholar
Lozano, P., Delgado, T. & Aguirre, Z. (2004) Endemism as a tool for conservation. Podocarpus Nacional Park a case study. Lyonia 2: 4353.Google Scholar
Mansourian, S., Belokurov, A. & Stephenson, P.J. (2009) The role of forest protected areas in adaptation to climate change. Unasylva 231/232: 6369.Google Scholar
Markham, A. (1996) Potential impacts of climate change on ecosystems: a review of implications for policymakers and conservation biologists. Climate Research 6: 179191.Google Scholar
Marmion, M., Parviainen, M., Luoto, M., Heikkinen, R.K. & Thuiller, W. (2009) Evaluation of consensus methods in predictive species distribution modelling. Diversity and Distributions 15: 5969.Google Scholar
Marsh, D.M. & Trenham, P.C. (2001) Metapopulation dynamics and amphibian conservation. Conservation Biology 15: 4049.Google Scholar
Miles, L., Newton, A.C., DeFries, R.S., Ravilious, C., May, I., Blyth, S., Kapos, V. & Gordon, J.E. (2006) A global overview of the conservation status of tropical dry forests. Journal of Biogeography 33: 491505.Google Scholar
Munguía, M., Peterson, A.T. & Sánchez-Cordero, V.M. (2008) Dispersal limitation and geographical distributions of mammal species. Journal of Biogeography 35: 18791887.Google Scholar
Murray, K.A., Retallick, R.W.R., Puschendorf, R., Skerratt, L.F., Rosauer, D., McCallum, H.I., Berger, L., Speare, R. & VanderWal, J. (2011) Issues with modelling the current and future distribution of invasive pathogens. Journal of Applied Ecology 48: 177180.Google Scholar
Noss, R. (2001) Beyond Kyoto: forest management in a time of rapid climate change. Conservation Biology 15: 578590.Google Scholar
Ochoa-Ochoa, L.M. & Flores-Villela, O. (2006) Áreas de diversidad y endemismo de la herpetofauna mexicana. Report. UNAM-CONABIO, México.Google Scholar
Olson, D.M., Dinerstein, E., Wikramanayake, E.D., Burgess, N.D., Powell, G.V.N., Underwood, E.C., D'Amico, J.A., Itoua, I., Strand, H.E.M.J., Loucks, C.J., Allnutt, T.F., Ricketts, T.H., Kura, Y., Lamoreux, J.F., Wettengel, W.W., Hedao, P. & Kassem, K.R. (2001) Terrestrial ecoregions of the world: a new map of life on earth. Biosience 51: 933938.Google Scholar
Parmesan, C. (2006) Ecological and evolutionary responses to recent climate change. Annual Review Ecology and Systematics 37: 637669.Google Scholar
Pearson, R.G., Thuiller, W., Araújo, M.B., Martinez-Meyer, E., Brotons, L., McClean, C., Miles, L., Segurado, P., Dawson, T.P. & Lees, D.C. (2006) Model-based uncertainty in species range prediction. Journal of Biogeography 33: 17041711.CrossRefGoogle Scholar
Peterson, A.T. & Holt, R.D. (2003) Niche differentiation in Mexican birds: using point occurrences to detect ecological innovation. Ecology Letters 6: 774782.Google Scholar
Peterson, A.T., Martínez-Meyer, E., González-Salazar, C. & Hall, P.W. (2004) Modeled climate change effects on distributions of Canadian butterfly species. Canadian Journal of Zoology 82: 851858.Google Scholar
Peterson, A.T. & Navarro-Singüenza, A.G. (2000) Western Mexico: a significant center of avian endemism and challenge for conservation action. Cotinga 14: 4246.Google Scholar
Peterson, A.T., Ortega-Huerta, M.A., Bartley, J., Sánchez-Cordero, V., Soberón, J., Buddemeier, R.H. & Stockwell, D.R.V. (2002) Future projections for Mexican faunas under global climate change scenarios. Nature 416: 626629.Google Scholar
Phillips, S.J., Anderson, R.P. & Schapire, R.E. (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling 190: 231259.Google Scholar
Pounds, J.A. (2001) Climate and amphibian declines. Nature 410: 639640.Google Scholar
Pounds, J.A., Fogden, M.P.L. & Campbell, J.H. (1999) Biological response to climate change on a tropical mountain. Nature 398: 611615.Google Scholar
Pulliam, H.R. (2000) On the relationship between niche and distribution. Ecology Letters 3: 349361.Google Scholar
Rehfeldt, G.E., Crookston, N.L., Sáenz-Romero, C. & Campbell, E. M. (2012) North American vegetation model for land-use planning in a changing climate: a solution to large classification problems. Ecological Applications 22: 119141.Google Scholar
Rödder, D., Kielgast, K., Bielby, J., Schmidtlein, S., Bosch, J., Garner, T.W.J., Veith, M., Walker, S., Fisher, M.C. & Lötters, S. (2009) Global amphibian extinction risk assessment for the panzootic Chytrid Fungus. Diversity 1: 5266.Google Scholar
Root, T.L., Price, J.T., Hall, K.R., Schneider, S.H., Rosenzweig, C. & Pounds, J.A. (2003) Fingerprints of global warming on wild animals and plants. Nature 421: 5760.Google Scholar
Sinclair, S.J., White, M.D., Newell, G.R. 2010. How useful are species distribution models for managing biodiversity under future climates? Ecology and Society 15: 8 [www document]. URL: http://www.ecologyandsociety.org/vol15/iss1/art8/ Google Scholar
Skerratt, L.F., Berger, L., Speare, R., Cashins, R., McDonald, K.R., Phillott, A.D., Hines, H.B. & Kenyon, N. (2007) Spread of Chytridiomycosis has caused the rapid global decline and extinction of frogs. EcoHealth 4: 125134.Google Scholar
Stockwell, D.R.B. & Peters, D. (1999) The GARP modelling system: problems and solutions to automated spatial prediction. International Journal of Geographical Information Science 13: 143158.Google Scholar
Stuart, N., Chanson, J.S., Cox, N.A., Young, B.E., Rodrigues, A.S.L., Fischman, D.L. & Waller, R.W. (2004) Status and trends of amphibian declines and extinctions worldwide. Science 306: 17831786.Google Scholar
Thuiller, W. (2004) Patterns and uncertainties of species’ range shifts under climate change. Global Change Biology: 10, 18.Google Scholar
Thuiller, W., Lavorel, S. & Araújo, M.B. (2005) Niche properties and geographical extent as predictors of species sensitivity to climate change. Global Ecology and Biogeography 14: 347357.Google Scholar
Trejo-Vazquez, I. & Dirzo, R. (2000) Deforestation of seasonally dry forest: a national and local analysis in Mexico. Biological Conservation 94: 133142.Google Scholar
Villers, L. & Trejo-Vazquez, I. (1998) Climate change on Mexican forests and Natural Protected Areas. Global Environmental Change 8: 141157.Google Scholar
Walther, G.R., Post, E., Convey, P., Menzel, A., Parmesan, C., Beebee, T.J.C., Fromentin, J.M., Hoegh-Guldberg, O. & Bairlein, F. (2002) Ecological responses to recent climate change. Nature 416: 389395.Google Scholar
Wiens, J.A., Stralberg, D., Jongsomjit, D., Howell, C.A. & Snyder, M.A. (2009) Niches, models, and climate change: assessing the assumptions and uncertainties. Proceedings of the National Academy of Sciences USA 106: 1972919736.Google Scholar
Whitfield, S.M., Bell, K.E., Philippi, T., Sasa, M., Bolaños, F., Cháves, G., Savage, J.M. & Donnelly, M.A. (2007) Amphibian and reptile declines over 35 years at La Selva, Costa Rica. Proceedings of the National Academy of Sciences USA 104: 83528356.Google Scholar
Williams, J. (1993) Multiobjective methods for selecting protected areas. PhD dissertation, Johns Hopkins University, USA.Google Scholar
Williams, P., Hannah, L., Andelman, S., Midgley, G., Araújo, M., Hughes, G., Manne, L., Martínez-Meyer, E. & Pearson, R. (2005) Planning for climate change: identifying minimum-dispersal corridors for Cape Proteaceae. Conservation Biology 19: 10631074.Google Scholar
Supplementary material: File

García Supplementary Material

Appendix

Download García Supplementary Material(File)
File 695.4 KB
Supplementary material: Image

García Supplementary Material

Image

Download García Supplementary Material(Image)
Image 7.9 MB
Supplementary material: Image

García Supplementary Material

Image

Download García Supplementary Material(Image)
Image 8.6 MB