Published June 23, 2020 | Version v1
Journal article Restricted

Clearing up the Crystal Ball: Understanding Uncertainty in Future Climate Suitability Projections for Amphibians

Description

Zellmer, Amanda J., Slezak, Pavlina, Katz, Tatum S. (2020): Clearing up the Crystal Ball: Understanding Uncertainty in Future Climate Suitability Projections for Amphibians. Herpetologica 76 (2): 108-120, DOI: 10.1655/0018-0831-76.2.108, URL: https://bioone.org/journals/herpetologica/volume-76/issue-2/0018-0831-76.2.108/Clearing-up-the-Crystal-Ball--Understanding-Uncertainty-in-Future/10.1655/0018-0831-76.2.108.full

Files

Restricted

The record is publicly accessible, but files are restricted to users with access.

Linked records

Additional details

Identifiers

LSID
urn:lsid:plazi.org:pub:FFB9FFB9C84E0F34FFFACC0EFFCDFC16

References

  • Ashrafzadeh, M.R., A.A. Naghipour, M. Haidarian, S. Kusza, and D.S. Pilliod. 2019. Effects of climate change on habitat and connectivity for populations of a vulnerable, endemic salamander in Iran. Global Ecology and Conservation 19:e00637. DOI: https://dx.doi.org/10.1016/j.gecco. 2019.e00637.
  • Ayebare, S., A.J. Plumptre, D. Kujirakwinja, and D. Segan. 2018. Extent of biodiversity surveys and ranges for endemic species in the Albertine Rift. Data in Brief 18:1907-1913. DOI: https://dx.doi.org/10.1016/j.dib.2018. 04.111.
  • Baker, D.J., A.J. Hartley, S.H.M. Butchart, and S.G. Willis. 2016. Choice of baseline climate data impacts projected species̕ responses to climate change. Global change biology 22:2392-2404. DOI: https://dx.doi.org/10. 1111/gcb.13273.
  • Barrett, K., N.P. Nibbelink, and J.C. Maerz. 2014. Identifying priority species and conservation opportunities under future climate scenarios: Amphibians in a biodiversity hotspot. Journal of Fish and Wildlife Management 5:282-297. DOI: https://dx.doi.org/10.3996/022014-JFWM-015.
  • Bates, D., M. Machler, B.M. Bolker, and S.C. Walker. 2015. Fitting linear mixed-effects models using lme4. Journal of Statistical Software 67:1-48. DOI: https://dx.doi.org/10.18637/jss.v067.i01.
  • Beaumont, L.J., E. Graham, D.E. Duursma,. . . J. VanDerWal. 2016. Which species distribution models are more (or less) likely to project broadscale, climate-induced shifts in species ranges? Ecological Modelling 342:135-146. DOI: https://dx.doi.org/10.1016/j.ecolmodel.2016.10.004.
  • Blank, L., and L. Blaustein. 2012. Using ecological niche modeling to predict the distributions of two endangered amphibian species in aquatic breeding sites. Hydrobiologia 693:157-167. DOI: https://dx.doi.org/10. 1007/s10750-012-1101-5.
  • Brun, P., W. Thuiller, Y. Chauvier, L. Pellissier, R.O. Wuest, Z. Wang, and N.E. Zimmermann. 2020. Model complexity affects species distribution projections under climate change. Journal of Biogeography 47:130-142. DOI: https://dx.doi.org/10.1111/jbi.13734.
  • Buisson, L., W. Thuiller, N. Casajus, S. Lek, and G. Grenouillet. 2010. Uncertainty in ensemble forecasting of species distribution. Global Change Biology 16:1145-1157. DOI: https://dx.doi.org/10.1111/j.1365- 2486.2009.02000.x.
  • Carey, C., and M.A. Alexander. 2003. Climate change and amphibian declines: Is there a link? Diversity and Distributions 9:111-121. DOI: https://dx.doi.org/10.1046/j.1472-4642.2003.00011.x.
  • Carvalho, S.B., J.C. Brito, E.J. Crespo, and H.P. Possingham. 2010. From climate change predictions to actions-Conserving vulnerable animal groups in hotspots at a regional scale. Global Change Biology 16:3257- 3270. DOI: https://dx.doi.org/10.1111/j.1365-2486.2010.02212.x.
  • Cayuela, H., A. Valenzuela-Sanchez, L. Teulier. . . B.R. Schmidt. In press. Determinants and consequences of dispersal in vertebrates with complex life cycles: A review of pond-breeding amphibians. The Quarterly Review of Biology. DOI: https://dx.doi.org/10.7287/peerj.preprints.27394v1.
  • Chamberlain, S., V. Barve, D. McGlinn, D. Oldoni, P. Desmet, L. Geffer, and K. Ram. 2019. rgbif: Interface to the Global ''Biodiversity'' Information Facility API. Available at https://CRAN.R-project.org/ package=rgbif. R Foundation for Statistical Computing, Austria.
  • Cobos, M.E., and R.A. Bosch. 2018. Recent and future threats to the Endangered Cuban toad Peltophrnne longinasus: Potential additive impacts of climate change and habitat loss. Oryx 52:116-125. DOI: https://dx.doi.org/10.1017/S0030605316000612.
  • Collins, J.P., and A. Storfer. 2003. Global amphibian declines: Sorting the hypotheses. Diversity and Distributions 9:89-98.
  • Courtois, E.A., E. Michel, Q. Martinez, K. Pineau, M. Dewynter, G.F. Ficetola, and A. Fouquet. 2016. Taking the lead on climate change: Modelling and monitoring the fate of an Amazonian frog. Oryx 50:450- 459. DOI: https://dx.doi.org/10.1017/S0030605315000083.
  • D̕Amen, M., P. Bombi, P.B. Pearman, D.R. Schmatz, N.E. Zimmermann, and M.A. Bologna. 2011. Will climate change reduce the efficacy of protected areas for amphibian conservation in Italy? Biological Conservation 144:989-997. DOI: https://dx.doi.org/10.1016/j.biocon.2010.11. 004.
  • da Fonte, L.F.M., M. Mayer, and S. Lotters. 2019. Long-distance dispersal in amphibians. Frontiers of Biogeography 11:e44577. DOI: https://dx.doi. org/10.21425/f5fbg44577.
  • de Pous, P., A. Montori, F. Amat, and D. Sanuy. 2016. Range contraction and loss of genetic variation of the Pyrenean endemic newt Calotriton asper due to climate change. Regional Environmental Change 16:995- 1009. DOI: https://dx.doi.org/10.1007/s10113-015-0804-3.
  • Diniz-Filho, J.A.F., K.S. Souza, L.M. Bini,. . . S. Gouveia. 2019. A macroecological approach to evolutionary rescue and adaptation to climate change. Ecography 42:1124-1141. DOI: https://dx.doi.org/10. 1111/ecog.04264.
  • Dobson, A., A. Jolly, and D. Rubenstein. 1989. The greenhouse effect and biological diversity. Trends in Ecology and Evolution 4:64-68. DOI: https://dx.doi.org/10.1016/0169-5347(89)90150-X.
  • Donnelly, M.A., and M.L. Crump. 1998. Potential effects of climate change on two Neotropical amphibian assemblages. Pp. 401-421 in Potential Impacts of Climate Change on Tropical Forest Ecosystems (A. Markham, ed.). Springer, Netherlands.
  • Dormann, C.F. 2007. Promising the future? Global change projections of species distributions. Basic and Applied Ecology 8:387-397. DOI: https:// dx.doi.org/10.1016/j.baae.2006.11.001.
  • Dormann, C.F., S.J. Schymanski, J. Cabral. . . A. Singer. 2012. Correlation and process in species distribution models: Bridging a dichotomy. Journal of Biogeography 39:2119-2131. DOI: https://dx.doi.org/10.1111/j.1365- 2699.2011.02659.x.
  • Dormann, C.F., J. Elith, S. Bacher,. . . S. Lautenbach. 2013. Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography 36:27-46. DOI: https://dx.doi.org/10.1111/j. 1600-0587.2012.07348.x.
  • Duan, R.Y., X.Q. Kong, M.Y. Huang, S. Varela, and X. Ji. 2016. The potential effects of climate change on amphibian distribution, range fragmentation and turnover in China. PeerJ 2016:1-17. DOI: https://dx.doi.org/10.7717/ peerj.2185.
  • Elith, J., and J.R. Leathwick. 2009. Species distribution models: Ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution, and Systematics 40:415-436. DOI: https://dx.doi.org/ 10.1146/annurev.ecolsys.l.
  • Ficetola, G.F., L. Maiorano, A. Falcucci, N. Dendoncker, L. Boitani, E. Padoa-Schioppa, C. Miaud, and W. Thuiller. 2010. Knowing the past to predict the future: Land-use change and the distribution of invasive bullfrogs. Global Change Biology 16:528-537. DOI: https://dx.doi.org/10. 1111/j.1365-2486.2009.01957.x.
  • Fitzpatrick, M.C., and W.W. Hargrove. 2009. The projection of species distribution models and the problem of non-analog climate. Biodiversity and Conservation 18:2255-2261. DOI: https://dx.doi.org/10.1007/s10531- 009-9584-8.
  • Giovannini, A., D. Seglie, and C. Giacoma. 2014. Identifying priority areas for conservation of spadefoot toad, Pelobates fuscus insubricus using a maximum entropy approach. Biodiversity and Conservation 23:1427- 1439. DOI: https://dx.doi.org/10.1007/s10531-014-0674-x.
  • Goncalves, J., J.P. Honrado, J.R. Vicente, and E. Civantos. 2016. A modelbased framework for assessing the vulnerability of low dispersal vertebrates to landscape fragmentation under environmental change. Ecological Complexity 28:174-186. DOI: https://dx.doi.org/10.1016/j. ecocom.2016.05.003.
  • Hansen, R.W. 2017. California amphibian and reptile species of special concern. Copeia 105:791-795.
  • Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones, and A. Jarvis. 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25:1965-1978. DOI: https://dx.doi. org/10.1002/joc.1276.
  • Hijmans, R.J., S. Phillips, J. Leathwick, and J. Elith. 2017. Package ''dismo'': Species distribution modeling. Available at https://cran.r-project.org/web/ packages/dismo/dismo.pdf. R Foundation for Statistical Computing, Austria.
  • Hof, C., M.B. Araujo, W. Jetz, and C. Rahbek. 2011. Additive threats from pathogens, climate and land-use change for global amphibian diversity. Nature 480:516-519. DOI: https://dx.doi.org/10.1038/nature10650.
  • Houlahan, J., C. Findlay, and B. Schmidt. 2000. Quantitative evidence for global amphibian population declines. Nature 404:752-755. DOI: https:// dx.doi.org/10.1038/35008052.
  • Iosif, R., M. Papes, C. Samoila, and D. Cogalniceanu. 2014. Climateinduced shifts in the niche similarity of two related spadefoot toads (genus Pelobates). Organisms Diversity and Evolution 14:397-408. DOI: https://dx.doi.org/10.1007/s13127-014-0181-7.
  • Jarnevich, C.S., and N.E. Young. 2019. Not so normal normals: Species distribution model results are sensitive to choice of climate normals and model type. Climate 7:37. DOI: https://dx.doi.org/10.3390/cli7030037.
  • Jockusch, E.L., I. Martinez-Solano, and E.K. Timpe. 2015. The effects of inference method, population sampling, and gene sampling on species tree inferences: An empirical study in slender salamanders (plethodontidae: Batrachoseps). Systematic Biology 64:66-83. DOI: https://dx.doi.org/ 10.1093/sysbio/syu078.
  • Jockusch, E.L., and D.B. Wake. 2002. Falling apart and merging: Diversification of slender salamanders (Plethodontidae: Batrachoseps) in the American West. Biological Journal of the Linnean Society 76:361- 391.
  • Johnson, J.B., and K.S. Omland. 2004. Model selection in ecology and evolution. Trends in Ecology and Evolution 19:101-108. DOI: https://dx. doi.org/10.1016/j.tree.2003.10.013.
  • Johnston, K.M., and O.J. Schmitz. 1997. Wildlife and climate change: Assessing the sensitivity of selected species to simulated doubling of atmospheric CO2. Global Change Biology 3:531-544. DOI: https://dx.doi. org/10.1046/j.1365-2486.1997.00093.x.
  • Kafash, A., S. Ashrafi, A. Ohler, M. Yousefi, S. Malakoutikhah, G. Koehler, and B.R. Schmidt. 2018. Climate change produces winners and losers: Differential responses of amphibians in mountain forests of the Near East. Global Ecology and Conservation 16:e00471. DOI: https://dx.doi. org/10.1016/j.gecco.2018.e00471.
  • Katz, T.S., and A.J. Zellmer. 2018. Comparison of model selection technique performance in predicting the spread of newly invasive species: A case study with Batrachochntrium salamandriVorans. Biological Invasions DOI: https://dx.doi.org/10.1007/s10530-018-1690-7.
  • Kearney, M.R., B.A. Wintle, and W.P. Porter. 2010. Correlative and mechanistic models of species distribution provide congruent forecasts under climate change. Conservation Letters 3:203-213. DOI: https://dx. doi.org/10.1111/j.1755-263X.2010.00097.x.
  • Lemes, P., and R.D. Loyola. 2013. Accommodating species climate-forced dispersal and uncertainties in spatial conservation planning. PLoS One 8:e54323. DOI: https://dx.doi.org/10.1371/journal.pone.0054323.
  • Liu, C., G. Newell, and M. White. 2016. On the selection of thresholds for predicting species occurrence with presence-only data. Ecology and Evolution 6:337-348. DOI: https://dx.doi.org/10.1002/ece3.1878.
  • Lourenco-de-Moraes, R., F.S. Campos, R.B. Ferreira, M. Sole, K.H. Beard, and R.P. Bastos. 2019. Back to the future: Conserving functional and phylogenetic diversity in amphibian-climate refuges. Biodiversity and Conservation 28:1049-1073. DOI: https://dx.doi.org/10.1007/s10531-019- 01706-x.
  • Loyola, R.D., P. Lemes, J.C. Nabout, J. Trindade-Filho, M.D. Sagnori, R. Dobrovolski, and J.A.F. Diniz-Filho. 2013. A straightforward conceptual approach for evaluating spatial conservation priorities under climate change. Biodiversity and Conservation 22:483-495. DOI: https://dx.doi. org/10.1007/s10531-012-0424-x.
  • Loyola, R.D., P. Lemes, F.T. Brum, D.B. Provete, and L.D.S. Duarte. 2014. Clade-specific consequences of climate change to amphibians in Atlantic Forest protected areas. Ecography 37:65-72. DOI: https://dx.doi.org/10. 1111/j.1600-0587.2013.00396.x.
  • Markovic, D., S. Carrizo, J. Freyhof, N. Cid, S. Lengyel, M. Scholz, H. Kasperdius, and W. Darwall. 2014. Europe̕s freshwater biodiversity under climate change: Distribution shifts and conservation needs. Diversity and Distributions 20:1097-1107. DOI: https://dx.doi.org/10. 1111/ddi.12232.
  • Mazerolle, M.J. 2019. AICcmodavg: Model selection and multimodel inference based on (Q)AIC(c). R package Version 2.2-2. Available at https://cran.r-project.org/web/packages/AICcmodavg/AICcmodavg.pdf.
  • Merow, C., M.J. Smith, and J.A. Silander. 2013. A practical guide to MaxEnt for modeling species̕ distributions: What it does, and why inputs and settings matter. Ecography 36:1058-1069. DOI: https://dx.doi.org/10. 1111/j.1600-0587.2013.07872.x.
  • Milanovich, J.R., W.E. Peterman, N.P. Nibbelink, and J.C. Maerz. 2010. Projected loss of a salamander diversity hotspot as a consequence of projected global climate change. PLoS One 5:e12189. DOI: https://dx. doi.org/10.1371/journal.pone.0012189.
  • Morales, N.S., I.C. Fernandez, and V. Baca-Gonzalez. 2017. MaxEnt̕s parameter configuration and small samples: Are we paying attention to recommendations? A systematic review. PeerJ 5:e3093. DOI: https://dx. doi.org/10.7717/peerj.3093.
  • Moran-Ordonez, A., J.J. Lahoz-Monfort, J. Elith, and B.A. Wintle. 2017. Evaluating 318 continental-scale species distribution models over a 60- year prediction horizon: What factors influence the reliability of predictions? Global Ecology and Biogeography 26:371-384. DOI: https://dx.doi.org/10.1111/geb.12545.
  • Muscarella, R., P.J. Galante, M. Soley-Guardia, R.A. Boria, J.M. Kass, M. Uriarte, and R.P. Anderson. 2014. ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for MAXENT ecological niche models. Methods in Ecology and Evolution 5:1198-1205. DOI: https://dx.doi.org/10.1111/ 2041-210X.12261.
  • Nabout, J.C., P. Carvalho, M.U. Prado, P.P. Borges, K.B. Machado, K.B. Haddad, T.S. Michelan, H.F. Cunha, and T.N. Soares. 2012. Trends and biases in global climate change literature. Natureza a Conservacao 10:45- 51. DOI: https://dx.doi.org/10.4322/natcon.2012.008.
  • Ochoa-Ochoa, L.M., P. Rodriguez, F. Mora, O. Flores-Villela, and R.J. Whittaker. 2012. Climate change and amphibian diversity patterns in Mexico. Biological Conservation 150:94-102. DOI: https://dx.doi.org/10. 1016/j.biocon.2012.03.010.
  • Ortega-Andrade, H.M., O. Rojas-Soto, and C. Paucar. 2013. Novel data on the ecology of Cochranella mache (Anura: Centrolenidae) and the importance of protected areas for this critically endangered glassfrog in the Neotropics. PLoS One 8:1-13. DOI: https://dx.doi.org/10.1371/ journal.pone.0081837.
  • Parra-Olea, G., E. Martinez-Meyer, and G. Perez-Ponce de Leon. 2005. Forecasting climate change effects on salamander distribution in the highlands of Central Mexico. Biotropica 37:202-208.
  • Pearman, P.B., M. D̕Amen, C.H. Graham, W. Thuiller, and N.E. Zimmermann. 2010. Within-taxon niche structure: Niche conservatism, divergence and predicted effects of climate change. Ecography 33:990- 1003. DOI: https://dx.doi.org/10.1111/j.1600-0587.2010.06443.x.
  • Pearson, R.G., W. Thuiller, M.B. Araujo,. . . D.C. Lees. 2006. Model-based uncertainty in species range prediction. Journal of Biogeography 33:1704-1711. DOI: https://dx.doi.org/10.1111/j.1365-2699.2006.01460.x.
  • Peterson, A.T., M.A. Ortega-Huerta, J. Bartley, V. Sanchez-Cordero, J. Soberon, R.H. Buddemeier, and D.R.B. Stockwell. 2002. Future projections for Mexican faunas under global climate change scenarios. Nature 416:626-629. DOI: https://dx.doi.org/10.1038/416626a.
  • Petitpierre, B., O. Broennimann, C. Kueffer, C. Daehler, and A. Guisan. 2017. Selecting predictors to maximize the transferability of species distribution models: Lessons from cross-continental plant invasions. Global Ecology and Biogeography 26:275-287. DOI: https://dx.doi.org/ 10.1111/geb.12530.
  • Phillips, S.J., R.P. Anderson, M. Dudik, R.E. Schapire, and M.E. Blair. 2017. Opening the black box: An open-source release of Maxent. Ecography 40:887-893. DOI: https://dx.doi.org/10.1111/ecog.03049.
  • Phillips, S.J., M. Dudik, and R.E. Schapire. 2006. Maxent software for modeling species niches and distributions. Available at: http:// biodiversityinformatics.amnh.org/open_source/maxent/
  • Popescu, V.D., L. Rozylowicz, D. Cogalniceanu, I.M. Niculae, and A.L. Cucu. 2013. Moving into protected areas? Setting conservation priorities for Romanian reptiles and amphibians at risk from climate change. PLoS One 8:e79330. DOI: https://dx.doi.org/10.1371/journal.pone.0079330.
  • Real, R., A.L. Marquez, J. Olivero, and A. Estrada. 2010. Species distribution models in climate change scenarios are still not useful for informing policy planning: An uncertainty assessment using fuzzy logic. Ecography 33:304-314. DOI: https://dx.doi.org/10.1111/j.1600-0587. 2010.06251.x.
  • Richgels, K.L.D., R.E. Russell, J. Adams, C.L. White, and E.H. Campbell. 2016. Spatial variation in risk and consequence of Batrachochntrium introduction in the USA subject areas. Royal Society of Open Science 3:150616. DOI: https://dx.doi.org/10.1098/rsos.150616
  • Rodda, G.H., C.S. Jarnevich, and R.N. Reed. 2011. Challenges in identifying sites climatically matched to the native ranges of animal invaders. PLoS One 6:e14670. DOI: https://doi.org/10.1371/journal.pone.0014670.
  • Rodriguez, J.P., L. Brotons, J. Bustamante, and J. Seoane. 2007. The application of predictive modelling of species distribution to biodiversity conservation. Diversity and Distributions 13:243-251. DOI: https://dx. doi.org/10.1111/j.1472-4642.2007.00356.x.
  • Rosenstock, N., C. Toranza, and A. Brazeiro. 2015. Climate and land-use changes effects on the distribution of a regional endemism: Melanophrnniscus sanmartini (Amphibia, Bufonidae). Iheringia, Serie Zoologia 105 : 209 - 216 . DOI : https : // dx . doi . org / 10.1590 / 1678 - 476620151052209216.
  • Roubicek, A.J., J. VanDerWal, L.J. Beaumont, A.J. Pitman, P. Wilson, and L. Hughes. 2010. Does the choice of climate baseline matter in ecological niche modelling? Ecological Modelling 221:2280-2286. DOI: https://dx. doi.org/10.1016/j.ecolmodel.2010.06.021.
  • Salas, E.A.L., V.A. Seamster, N.M. Harings, K.G. Boykin, G. Alvarez, and K.W. Dixon. 2017. Projected future bioclimate-envelope suitability for reptile and amphibian species of concern in South Central USA. Herpetological Conservation and Biology 12:522-547.
  • Sales, L.P., O.V. Neves, P. De Marco, and R. Loyola. 2017. Model uncertainties do not affect observed patterns of species richness in the Amazon. PLoS One 12:e0183785. DOI: https://dx.doi.org/10.1371/ journal.pone.0183785.
  • Saupe, E.E., V. Barve, C.E. Myers, J. Soberon, N. Barve, C.M. Hensz, A.T. Peterson, H.L. Owens, and A. Lira-Noriega. 2012. Variation in niche and distribution model performance: The need for a priori assessment of key causal factors. Ecological Modelling 237-238:11-22. DOI: https://dx.doi. org/10.1016/j.ecolmodel.2012.04.001.
  • Schivo, F., V. Bauni, P. Krug, and R.D. Quintana. 2019. Distribution and richness of amphibians under different climate change scenarios in a subtropical region of South America. Applied Geography 103:70-89. DOI: https://dx.doi.org/10.1016/j.apgeog.2019.01.003.
  • Smalling, K.L., C.A. Eagles-Smith, R.A. Katz, and E.H. Campbell Grant. 2019. Managing the trifecta of disease, climate, and contaminants: Searching for robust choices under multiple sources of uncertainty. Biological Conservation 236:153-161. DOI: https://dx.doi.org/10.1016/j. biocon.2019.05.026.
  • Smith, M.A., and D.M. Green. 2005. Dispersal and the metapopulation paradigm in amphibian ecology and conservation: Are all amphibian populations metapopulations? Ecography 28:110-128. DOI: https://dx. doi.org/10.1111/j.0906-7590.2005.04042.x.
  • Soares de Oliveira, I., D. Rodder, C. Capinha, F. Ahmadzadeh, A. Karlokoski Cunha de Oliveira, and L.F. Toledo. 2016. Assessing future habitat availability for coastal lowland anurans in the Brazilian Atlantic rainforest. Studies on Neotropical Fauna and Environment 51:45-55. DOI: https://dx.doi.org/10.1080/01650521.2016.1160610.
  • Struecker, B.P., and J. Milanovich. 2017. Predicted suitable habitat declines for midwestern United States amphibians under future climate change and land-use change scenarios. Herpetological Conservation and Biology 12:635-654.
  • Subba, B., S. Sen, G. Ravikanth, and M.P. Nobis. 2018. Direct modelling of limited migration improves projected distributions of Himalayan amphibians under climate change. Biological Conservation 227:352- 360. DOI: https://dx.doi.org/10.1016/j.biocon.2018.09.035.
  • Teixeira, J., and J.W. Arntzen. 2002. Potential impact of climate warming on the distribution of the Golden-striped salamander, Chioglossa lusitanica, on the Iberian Peninsula. Biodiversity and Conservation 11:2167-2176. DOI: https://dx.doi.org/10.1023/A:1021342611769.
  • Thomson, R.C., A.N. Wright, and H.B. Shaffer. 2016. California Amphibian and Reptile Species of Special Concern. California Department of Fish and Wildlife and University of California Press, USA.
  • Thuiller, W. 2004. Patterns and uncertainties of species̕ range shifts under climate change. Global Change Biology 10:2020-2027. DOI: https://dx. doi.org/10.1111/j.1365-2486.2004.00859.x.
  • Thuiller, W., M. Gueguen, J. Renaud, D.N. Karger, and N.E. Zimmermann. 2019. Uncertainty in ensembles of global biodiversity scenarios. Nature Communications 10:1-9. DOI: https://dx.doi.org/10.1038/s41467-019- 09519-w.
  • Toranza, C., and R. Maneyro. 2013. Potential effects of climate change on the distribution of an endangered species: Melanophrnniscus monteVidensis (Anura: Bufonidae). Phyllomedusa 12:97-106. DOI: https://dx.doi. org/10.11606/issn.2316-9079.v12i2p97-106.
  • Ureta, C., A.P. Cuervo-Robayo, E. Calixto-Perez, C. Gonzalez-Salazar, and E. Fuentes-Conde. 2018. A first approach to evaluate the vulnerability of islands̕ vertebrates to climate change in Mexico. Atmosfera 31:221-254. DOI: https://dx.doi.org/10.20937/ATM.2018.31.03.03.
  • Vasconcelos, T.S., and B.T.M. Do Nascimento. 2016. Potential climatedriven impacts on the distribution of generalist treefrogs in South America. Herpetologica 72:23-31. DOI: https://dx.doi.org/10.1655/ herpetologica-d-14-00064.
  • Viechtbauer, W. 2010. Conducting meta-analyses in R with the metafor. Journal of Statistical Software 36:1-48. DOI: http://dx.doi.org/10.18637/ jss.v036.i03.
  • Vieites, D.R., M.S. Min, and D.B. Wake. 2007. Rapid diversification and dispersal during periods of global warming by plethodontid salamanders. Proceedings of the National Academy of Sciences of the United States of America 104:19903-19907. DOI: https://dx.doi.org/10.1073/pnas. 0705056104.
  • Wake, D.B. 1991. Declining amphibian populations. Science 253:860. DOI: https://dx.doi.org/10.1126/science.253.5022.860.
  • Wake, D.B. 1996. A new species of Batrachoseps (Amphibia: Plethodontidae) from the San Gabriel Mountains, southern California. Contributions in Science, Natural History Museum of Los Angeles County 463:1-12.
  • Warren, D.L., and S.N. Seifert. 2011. Ecological niche modeling in Maxent: The importance of model complexity and the performance of model selection criteria. Ecological Applications 21:335-342. DOI: https://dx. doi.org/10.1890/10-1171.1.
  • Warren, D.L., A.N. Wright, S.N. Seifert, and H.B. Shaffer. 2014. Incorporating model complexity and spatial sampling bias into ecological niche models of climate change risks faced by 90 California vertebrate species of concern. Diversity and Distributions 20:334-343. DOI: https:// dx.doi.org/10.1111/ddi.12160.
  • Warren, D.L., N.J. Matzke, and T.L. Iglesias. 2020. Evaluating presenceonly species distribution models with discrimination accuracy is uninformative for many applications. Journal of Biogeography 47:167- 180. DOI: https://dx.doi.org/10.1111/jbi.13705.
  • Wisz, M.S., R.J. Hijmans, J. Li,. . . N.E. Zimmermann. 2008. Effects of sample size on the performance of species distribution models. Diversity and Distributions 14:763-773. DOI: https://dx.doi.org/10.1111/j.1472- 4642.2008.00482.x.
  • Wright, A.N., R.J. Hijmans, M.W. Schwartz, and H.B. Shaffer. 2015. Multiple sources of uncertainty affect metrics for ranking conservation risk under climate change. Diversity and Distributions 21:111-122. DOI: https://dx.doi.org/10.1111/ddi.12257.
  • Wright, A.N., M.W. Schwartz, R.J. Hijmans, and H. Bradley Shaffer. 2016. Advances in climate models from CMIP3 to CMIP5 do not change predictions of future habitat suitability for California reptiles and amphibians. Climatic Change 134:579-591. DOI: https://dx.doi.org/10. 1007/s10584-015-1552-6.
  • Yap, T.A., M.S. Koo, R.F. Ambrose, D.B. Wake, and V.T. Vredenburg. 2015. Averting a North American biodiversity crisis. Science 349:481-482. DOI: https://dx.doi.org/10.1126/science.aab1052.
  • Zank, C., F.G. Becker, M. Abadie, D. Baldo, R. Maneyro, and M. Borges-Martins. 2014. Climate change and the distribution of neotropical redbellied toads (Melanophrnniscus, Anura, Amphibia): How to prioritize species and populations? PLoS One 9:1-11. DOI: https://dx.doi.org/10. 1371/journal.pone.0094625.