Charlesworth, B., Charlesworth, D. & Barton, N. H. The effects of genetic and geographic structure on neutral variation. Annu. Rev. Ecol. Evol. Syst. 34(1), 99–125 (2003).
Google Scholar
Bradburd, G. S., Ralph, P. L. & Coop, G. M. Disentangling the effects of geographic and ecological isolation on genetic differentiation. Evolution 67(11), 3258–3273 (2013).
Google Scholar
Orsini, L., Vanoverbeke, J., Swillen, I., Mergeay, J. & De Meester, L. Drivers of population genetic differentiation in the wild: Isolation by dispersal limitation, isolation by adaptation and isolation by colonization. Mol. Ecol. 22(24), 5983–5999 (2013).
Google Scholar
Ronce, O. How does it feel to be like a rolling stone? Ten questions about dispersal evolution. Annu. Rev. Ecol. Evol. Syst. 38, 231–253 (2007).
Google Scholar
Broquet, T. & Petit, E. J. Molecular estimation of dispersal for ecology and population genetics. Annu. Rev. Ecol. Evol. Syst. 40, 193–216 (2009).
Google Scholar
Sexton, J. P., McIntyre, P. J., Angert, A. L. & Rice, K. J. Evolution and ecology of species range limits. Annu. Rev. Ecol. Evol. Syst. 40, 415–436 (2009).
Google Scholar
Qiao, H., Saupe, E. E., Soberón, J., Peterson, A. T. & Myers, C. E. Impacts of niche breadth and dispersal ability on macroevolutionary patterns. Am. Nat. 188(2), 149–162 (2016).
Google Scholar
Mayr, E. Ecological factors in speciation. Evolution 1(4), 263–288 (1947).
Hua, X. & Wiens, J. J. How does climate influence speciation?. Am. Nat. 182(1), 1–12 (2013).
Google Scholar
Rundle, H. D. & Nosil, P. Ecological speciation. Ecol. Lett. 8(3), 336–352 (2005).
Google Scholar
Schluter, D. Evidence for ecological speciation and its alternative. Science 323(5915), 737–741 (2009).
Google Scholar
Wielstra, B. et al. Corresponding mitochondrial DNA and niche divergence for crested newt candidate species. PLoS ONE 7(9), e46671 (2012).
Google Scholar
Wiens, J. J. Speciation and ecology revisited: Phylogenetic niche conservatism and the origin of species. Evolution 58(1), 193–197 (2004).
Manel, S., Schwartz, M. K., Luikart, G. & Taberlet, P. Landscape genetics: combining landscape ecology and population genetics. Trends Ecol. Evol. 18(4), 189–197 (2003).
Google Scholar
Alvarado-Serrano, D. F. & Hickerson, M. J. Spatially explicit summary statistics for historical population genetic inference. Methods Ecol. Evol. 7(4), 418–427 (2016).
Google Scholar
Rissler, L. J. Union of phylogeography and landscape genetics. PNAS 113(29), 8079–8086 (2016).
Google Scholar
Pinho, C. & Hey, J. Divergence with gene flow: Models and data. Annu. Rev. Ecol. Evol. Syst. 41, 215–230 (2010).
Google Scholar
Sobel, J. M., Chen, G. F., Watt, L. R. & Schemske, D. W. The biology of speciation. Evolution 64(2), 295–315 (2010).
Google Scholar
Richards, C. L., Carstens, B. C. & Knowles, L. L. Distribution modelling and statistical phylogeography: An integrative framework for generating and testing alternative biogeographical hypotheses. J. Biogeogr. 34(11), 1833–1845 (2007).
Google Scholar
Alvarado-Serrano, D. F. & Knowles, L. L. Ecological niche models in phylogeographic studies: applications, advances and precautions. Mol. Ecol. 14(2), 233–248 (2014).
Google Scholar
Wang, I. J. Examining the full effects of landscape heterogeneity on spatial genetic variation: A multiple matrix regression approach for quantifying geographic and ecological isolation. Evolution 67(12), 3403–3411 (2013).
Google Scholar
Wright, S. Isolation by distance. Genetics 28(2), 114–138 (1943).
Google Scholar
Sexton, J. P., Hangartner, S. B. & Hoffmann, A. A. Genetic isolation by environment or distance: which pattern of gene flow is most common?. Evolution 68(1), 1–15 (2014).
Google Scholar
Wang, I. J. & Bradburd, G. S. Isolation by environment. Mol. Ecol. 23(23), 5649–5662 (2014).
Google Scholar
Lee, C. R. & Mitchell-Olds, T. Quantifying effects of environmental and geographical factors on patterns of genetic differentiation. Mol. Ecol. 20(22), 4631–4642 (2011).
Google Scholar
Moreira-Muñoz, A. Plant Geography of Chile Vol. 10, 978–990 (Springer, 2011).
Google Scholar
Orme, A. R. Tectonism, climate, and landscape change. Phys. Geogr. South Am. 1, 23–44 (2007).
Morando, M. et al. Diversification and evolutionary histories of Patagonian steppe lizards. in Lizards of Patagonia (pp. 217–254). (Springer, 2020).
Rull, V. Neotropical diversification: historical overview and conceptual insights. In Neotropical Diversification: Patterns and Processes (eds Rull, V. & Carnaval, A. C.) (Springer, 2020).
Google Scholar
Lessa, E. P., D’Elía, G. & Pardiñas, U. F. J. Mammalian biogeography of Patagonia and Tierra del Fuego. In Bones, Clones and Biomes: The History and Recent Geography of Neotropical Animals (eds Patterson, B. D. & Costa, L. P.) 379–398 (University of Chicago Press, 2012).
Google Scholar
Pardiñas, U. F., D’Elía, G. & Lessa, E. P. The evolutionary history of sigmodontine rodents in Patagonia and Tierra del Fuego. Biol. J. Linn. Soc. 2(103), 495–513 (2011).
Google Scholar
Alarcón, O., D’Elía, G., Lessa, E. P. & Pardiñas, U. Phylogeographic structure of the Fossorial Long-Clawed Mouse Chelemys macronyx (Cricetidae: Sigmodontinae). Zool. Stud. 50(5), 682–688 (2011).
Lessa, E. P., D’Elía, G. & Pardiñas, U. F. J. Genetic footprints of late Quaternary climate change in the diversity of Patagonian-Fueguian rodents. Mol. Ecol. 19(15), 3031–3037 (2010).
Google Scholar
Valdez, L. & D’Elía, G. Genetic diversity and demographic history of the Shaggy Soft-Haired Mouse Abrothrix hirta (Cricetidae; Abrotrichini). Front. Genet. 12, 184 (2021).
Google Scholar
Valdez, L., Quiroga-Carmona, M. & D’Elía, G. Genetic variation of the Chilean endemic long-haired mouse Abrothrix longipilis (Rodentia, Supramyomorpha, Cricetidae) in a geographical and environmental context. PeerJ 8, e9517 (2020).
Google Scholar
Valdez, L. & D’Elía, G. Local persistence of Mann’s soft-haired mouse Abrothrix manni (Rodentia, Sigmodontinae) during Quaternary glaciations in southern Chile. PeerJ 6, e6130 (2018).
Google Scholar
Quiroga-Carmona, M., Abud, C., Lessa, E. P. & D’Elía, G. The mitochondrial genetic diversity of the olive field mouse Abrothrix olivacea (Cricetidae; Abrotrichini) is latitudinally structured across its geographic distribution. J. Mamm. Evol. 29, 431–433 (2022).
Google Scholar
Cañón, C., D’Elía, G., Pardiñas, U. F. & Lessa, E. P. Phylogeography of Loxodontomys micropus with comments on the alpha taxonomy of Loxodontomys (Cricetidae: Sigmodontinae). J. Mamm. 91(6), 1449–1458 (2010).
Google Scholar
Palma, R. E., Boric-Bargetto, D., Torres-Perez, F., Hernández, C. E. & Yates, T. L. Glaciation effects on the phylogeographic structure of Oligoryzomys longicaudatus (Rodentia: Sigmodontinae) in the Southern Andes. PLoS ONE 7(3), e32206 (2012).
Google Scholar
Rodríguez-Serrano, E., Cancino, R. & Palma, R. E. Molecular phylogeography of Abrothrix olivaceus (Rodentia: Sigmodontinae) in Chile. J. Mamm. 87(5), 971–980 (2006).
Google Scholar
Rodríguez-Serrano, E., Hernandez, C. & Palma, R. E. A new record and an evaluation of the phylogenetic relationships of Abrothrix olivaceus markhami (Rodentia: Sigmodontinae). Mamm. Biol. 73(4), 309–317 (2008).
Google Scholar
Sánchez, J., Poljak, S., Teta, P., Lanusse, L. & Lizarralde, M. S. A contribution to the knowledge of the taxonomy of the subgenus Abrothrix (Angelomys) (Rodentia, Cricetidae) in southernmost South America. Polar Biol. 45(4), 601–614 (2022).
Google Scholar
Patton, J., Pardiñas, U. F. & D’Elía, G. Mammals of South America Vol. 2 (The University of Chicago Press, 2015).
Google Scholar
Patterson, B. D., Smith, M. F. & Teta, P. Genus Abrothrix Waterhouse, 1837. In Mammals of South America Vol. 2 (eds Patton, J. L. et al.) 109–127 (The University of Chicago Press, 2015).
Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: A new method for the analysis of genetically structured populations. BMC Genet. 11, 94 (2010).
Google Scholar
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high-resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25(15), 1965–1978 (2005).
Google Scholar
Quantum GIS Development Team (2021) Quantum GIS Geographic Information System. Version 3.18.2-Zürich
Hijmans, R. J. et al. Package ‘raster’. R package. (2015).
Kuhn, M. caret: Classification and Regression Training. (2019) https://CRAN.R-project.org/package=caret.
Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5–7. (2020). https://CRAN.R-project.org/package=vegan.
Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35(6), 1547–1549 (2018).
Google Scholar
Wang, C. et al. Comparing spatial maps of human population-genetic variation using Procrustes analysis. Stat. Appl. Genet. Mol. Biol. 9(1), 13 (2010).
Google Scholar
Wang, C., Zöllner, S. & Rosenberg, N. A. A quantitative comparison of the similarity between genes and geography in worldwide human populations. PLoS Genet. 8(8), e1002886 (2012).
Google Scholar
Bivand, R., Keitt, T. & Rowlingson, B. rgdal: Bindings for the ‘Geospatial’ Data Abstraction Library. R package version 1.5–28. (2021). https://CRAN.R-project.org/package=rgdal.
Kierepka, M. E. & Latch, K. E. Performance of partial statistics in individual-based landscape genetics. Mol. Ecol. 15(3), 512–525 (2015).
Google Scholar
Legendre, P. & Legendre, L. Numerical Ecology (Elsevier, 2012).
Google Scholar
Lê, S., Josse, J. & Husson, F. FactoMineR: An R package for multivariate analysis. J. Stat. Soft. 25(1), 1–8 (2008).
Google Scholar
Barria, A. M. et al. The importance of intraspecific variation for niche differentiation and species distribution models: the ecologically diverse frog Pleurodema thaul as study case. Evol. Biol. 47(3), 206–219 (2020).
Google Scholar
Blonder, B., Lamanna, C., Violle, C. & Enquist, B. J. The n-dimensional hypervolume. Glob. Ecol. Biol. 23(5), 595–609 (2014).
Google Scholar
Aiello-Lammens, M. E., Boria, R. A., Radosavljevic, A., Vilela, B. & Anderson, R. P. spThin: An R package for spatial thinning of species occurrence records for use in ecological niche models. Ecography 38(5), 541–545 (2015).
Google Scholar
Peterson, A. T. et al. Ecological Niches and Geographic Distributions (Princeton University Press, 2011).
Google Scholar
Viale, M. et al. Contrasting climates at both sides of the Andes in Argentina and Chile. Front. Environ. Sci. 7, 69 (2019).
Google Scholar
Pacifici, M. et al. Global correlates of range contractions and expansions in terrestrial mammals. Nat. Commun. 11(1), 1–9 (2020).
Google Scholar
Di Marco, M., Pacifici, M., Maiorano, L. & Rondinini, C. Drivers of change in the realised climatic niche of terrestrial mammals. Ecography 44(8), 1180–1190 (2021).
Google Scholar
Phillips, S. J., Anderson, R. P., Dudík, M., Schapire, R. E. & Blair, M. E. Opening the black box: An open-source release of Maxent. Ecography 40(7), 887–893 (2017).
Google Scholar
Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Model 190(3–4), 231–259 (2006).
Google Scholar
Phillips, S. J., Dudík, M. & Schapire, R. E. Maxent Software for Modeling Species Niches and Distributions. (American Museum of Natural History, 2018) http://biodiversityinformatics.amnh.org/opensource/maxent/.
Muscarella, R. et al. ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods Ecol. Evol. 5(11), 1198–1205 (2014).
Google Scholar
Radosavljevic, A. & Anderson, R. P. Making better Maxent models of species distributions: complexity, overfitting and evaluation. J. Biogeogr. 41(4), 629–643 (2014).
Google Scholar
Warren, D. L. & Seifert, S. N. Ecological niche modeling in Maxent: The importance of model complexity and the performance of model selection criteria. Ecol. Appl. 21(2), 335–342 (2011).
Google Scholar
Warren, D. L., Wright, A. N., Seifert, S. N. & Shaffer, H. B. Incorporating model complexity and spatial sampling bias into ecological niche models of climate change risks faced by 90 California vertebrate species of concern. Diver. Dist. 20(3), 334–343 (2014).
Google Scholar
Franklin, J. Mapping Species Distributions: Spatial Inference and Prediction (Cambridge University Press, 2010).
Google Scholar
Merow, C., Smith, M. J. & Silander, J. A. A practical guide to MaxEnt for modeling species’ distributions: What it does, and why inputs and settings matter. Ecography 36(10), 1058–1069 (2013).
Google Scholar
Elith, J., Kearney, M. & Phillips, S. The art of modelling range-shifting species. Methods Ecol. Evol. 1(4), 330–342 (2010).
Google Scholar
Osorio-Olvera, L. et al. ntbox: An r package with graphical user interface for modelling and evaluating multidimensional ecological niches. Methods Ecol. Evol. 11(10), 1199–1206 (2020).
Google Scholar
Guevara, L., Gerstner, B. E., Kass, J. M. & Anderson, R. P. Toward ecologically realistic predictions of species distributions: A cross-time example from tropical montane cloud forests. Glob. Change Biol. 24, 1511–1522 (2018).
Google Scholar
Otto-Bliesner, B. L., Marshall, S. J., Overpeck, J. T., Miller, G. H. & Hu, A. Simulating arctic climate warmth and icefield retreat in the last interglaciation. Science 311(5768), 1751–1753 (2008).
Google Scholar
Watanabe, S. et al. MIROC-ESM 2010: Model description and basic results of CMIP5-20c3m experiments. Geosci. Model Dev. 4(4), 845 (2011).
Google Scholar
Knowles, L. L., Massatti, R., He, Q., Olson, L. E. & Lanier, H. C. Quantifying the similarity between genes and geography across Alaska’s alpine small mammals. J. Biogeogr. 43(7), 1464–1476 (2016).
Google Scholar
McGaughran, A., Morgan, K. & Sommer, R. J. Environmental variables explain genetic structure in a beetle-associated nematode. PLoS ONE 9(1), e87317 (2014).
Google Scholar
Wang, I. J. Choosing appropriate genetic markers and analytical methods for testing landscape genetic hypotheses. Mol. Ecol. 20(12), 2480–2482 (2011).
Google Scholar
Bohonak, A. J. & Vandergast, A. G. The value of DNA sequence data for studying landscape genetics. Mol. Ecol. 20(12), 2477–2479 (2011).
Google Scholar
Vandergast, A. G., Bohonak, A. J., Weissman, D. B. & Fisher, R. N. Understanding the genetic effects of recent habitat fragmentation in the context of evolutionary history: Phylogeography and landscape genetics of a southern California endemic Jerusalem cricket (Orthoptera: Stenopelmatidae: Stenopelmatus). Mol. Ecol. 16(5), 977–992 (2007).
Google Scholar
Pearson, O. P. & Smith, M. F. Genetic similarity between Akodon olivaceus and Akodon xanthorhinus (Rodentia: Muridae) in Argentina. J. Zool. 247(1), 43–52 (1999).
Google Scholar
Smith, M. F., Kelt, D. A. & Patton, J. L. Testing models of diversification in mice in the Abrothrix olivaceus/xanthorhinus complex in Chile and Argentina. Mol. Ecol. 10(2), 397–405 (2001).
Google Scholar
Palma, R. E., Marquet, P. A. & Boric-Bargetto, D. Inter- and intraspecific phylogeography of small mammals in the Atacama Desert and adjacent areas of northern Chile. J. Biogeogr. 32(11), 1931–1941 (2005).
Google Scholar
Arroyo, M. T. K., Squeo, F. A., Armesto, J. J. & Villagran, C. Effects of aridity on plant diversity in the northern Chilean Andes: Results of a natural experiment. Ann. Mol. Bot. Gard. 1, 55–78 (1988).
Google Scholar
Del Pozo, A. H., Fuentes, E. R., Hajek, E. R. & Molina, J. D. Zonación microclimática por efecto de los manchones de arbustos en el matorral de Chile central. Rev. Chil. Hist. Nat. 62, 85–94 (1989).
Armesto, J. J., Vidiella, P. E. & Gutiérrez, J. R. Plant communities of the fog-free coastal desert of Chile: Plant strategies in a fluctuating environment. Rev. Chil. Hist. Nat. 66, 271–282 (1993).
Veblen, T. T., Young, K. R. & Orme, A. R. The Physical Geography of South America (Oxford University Press, 2015).
Kelt, D. A. et al. Community structure of desert small mammals: Comparisons across four continents. Ecology 77(3), 746–761 (1996).
Google Scholar
Shenbrot, G. B., Krasnov, B. R. & Rogovin, K. A. Spatial Ecology of Desert Rodent Communities (Springer, 1999).
Google Scholar
Van Strien, M. J., Holderegger, R. & Van Heck, H. J. Isolation-by-distance in landscapes: considerations for landscape genetics. Heredity 114(1), 27–37 (2015).
Google Scholar
Diniz-Filho, J. A. F. et al. Mantel test in population genetics. Genet. Mol. Biol. 36(4), 475–485 (2013).
Google Scholar
Blier, P. U., Dufresne, F. & Burton, R. S. Natural selection and the evolution of mtDNA-encoded peptides: Evidence for intergenomic co-adaptation. Trends Genet. 17(7), 400–406 (2001).
Google Scholar
Meiklejohn, C. D., Montooth, K. L. & Rand, D. M. Positive and negative selection on the mitochondrial genome. Trends Genet. 23(6), 259–263 (2007).
Google Scholar
Giorello, F. M. et al. An association between differential expression and genetic divergence in the Patagonian olive mouse (Abrothrix olivacea). Mol. Ecol. 27(16), 3274–3286 (2018).
Google Scholar
Soberón, J. Grinnellian and Eltonian niches and geographic distributions of species. Ecol. Lett. 10(12), 1115–1123 (2007).
Google Scholar
Holt, R. D. Bringing the Hutchinsonian niche into the 21st century: Ecological and evolutionary perspectives. PNAS 106(Supplement 2), 19659–19665 (2009).
Google Scholar
Soberón, J. & Nakamura, M. Niches and distributional areas: Concepts, methods, and assumptions. PNAS 106(Supplement 2), 19644–19650 (2009).
Google Scholar
Kearney, M. & Porter, W. P. Mapping the fundamental niche: Physiology, climate, and the distribution of a nocturnal lizard. Ecology 85(11), 3119–3131 (2004).
Google Scholar
Kearney, M. & Porter, W. P. Mechanistic niche modelling: Combining physiological and spatial data to predict species’ ranges. Ecol. Lett. 12(4), 334–350 (2009).
Google Scholar
Bonetti, M. F. & Wiens, J. J. Evolution of climatic niche specialization: A phylogenetic analysis in amphibians. Proc. R. Soc. B. 281(1795), 20133229 (2014).
Google Scholar
Sexton, J. P., Montiel, J., Shay, J. E., Stephens, M. R. & Slatyer, R. A. Evolution of ecological niche breadth. Annu. Rev. Ecol. Evol. Syst. 48, 183–206 (2017).
Google Scholar
Holt, R. D. On the evolutionary ecology of species’ ranges. Evol. Ecol. Res. 5(2), 159–178 (2003).
Merilä, J. & Hendry, A. P. Climate change, adaptation, and phenotypic plasticity: The problem and the evidence. Evol. Appl. 7(1), 1–14 (2014).
Google Scholar
Schmid, M. & Guillaume, F. The role of phenotypic plasticity on population differentiation. Heredity 119(4), 214–225 (2017).
Google Scholar
Novoa, F., Rivera, A., Rosenmann, M. & Sabat, P. Intraspecific differences in metabolic rate of Chroeomys olivaceus (Rodentia: Muridae): The effect of thermal acclimation in arid and mesic habitats. Rev. Chil. Hist. Nat. 78, 207–214 (2005).
Google Scholar
Bozinovic, F., Rojas, J. M., Maldonado, K., Sabat, P. & Naya, D. E. Between-population differences in digestive flexibility in the olivaceous field mouse. Zool 113(6), 373–377 (2010).
Google Scholar
Bozinovic, F., Rojas, J. M., Gallardo, P. A., Palma, R. E. & Gianoli, E. Body mass and water economy in the South American olivaceous field mouse along a latitudinal gradient: Implications for climate change. J. Arid. Environ. 75(5), 411–415 (2011).
Google Scholar
Naya, D. E. et al. Digestive morphology of two species of Abrothrix (Rodentia, Cricetidae): Comparison of populations from contrasting environments. J. Mammal. 95(6), 1222–1229 (2014).
Google Scholar
Warren, D. L., Glor, R. E. & Turelli, M. Environmental niche equivalency versus conservatism: Quantitative approaches to niche evolution. Evolution 62(11), 2868–2883 (2008).
Google Scholar
Goudarzi, F. et al. Geographic separation and genetic differentiation of populations are not coupled with niche differentiation in threatened Kaiser’s spotted newt (Neurergus kaiseri). Sci. Rep. 9(1), 1–12 (2019).
Google Scholar
Pyron, R. A., Costa, G. C., Patten, M. A. & Burbrink, F. T. Phylogenetic niche conservatism and the evolutionary basis of ecological speciation. Biol. Rev. 90(4), 1248–1262 (2015).
Google Scholar
Latorre, C. et al. Late Quaternary environments and paleoclimate. In The Geology of Chile (eds Moreno, T. & Gibbons, W.) 309–328 (Geological Society, 2007).
Google Scholar
Kaplan, M. R., Moreno, P. I. & Rojas, M. Glacial dynamics in southernmost South America during Marine Isotope Stage 5e to the Younger Dryas chron: A brief review with a focus on cosmogenic nuclide measurements. J. Quat. Sci. 23(6–7), 649–658 (2008).
Google Scholar
McCulloch, R. D. et al. Climatic inferences from glacial and palaeoecological evidence at the last glacial termination, southern South America. J. Quat. Sci. 15(4), 409–417 (2000).
Google Scholar
Giorello, F. M., D’Elía, G. & Lessa, E. P. Genomic footprints of Quaternary colonization and population expansion in the Patagonian-Fuegian region rules out a separate southern refugium in Tierra del Fuego. J. Biogeogr. 48(10), 2656–2670 (2021).
Google Scholar
Knowles, L. L., Carstens, B. C. & Keat, M. L. Coupling genetic and ecological-niche models to examine how past population distributions contribute to divergence. Curr. Biol. 17(11), 940–946 (2007).
Google Scholar
Diniz-Filho, J. A. F. et al. Correlation between genetic diversity and environmental suitability: Taking uncertainty from ecological niche models into account. Mol. Ecol. 15(5), 1059–1066 (2015).
Google Scholar
Guevara, L., León-Paniagua, L., Rios, J. & Anderson, R. P. Variación entre modelos de circulación global para reconstrucciones de distribuciones geográficas del Último Máximo Glacial: Relevancia en la filogeografía. Ecosistemas 27(1), 62–76 (2018).
Google Scholar
Guevara, L., Morrone, J. J. & León-Paniagua, L. Spatial variability in species’potential distributions during the Last Glacial Maximum under different Global Circulation Models: Relevance in evolutionary biology. J. Zool. Syst. Evol. Res. 57(1), 113–126 (2019).
Google Scholar
Cab-Sulub, L. & Álvarez-Castañeda, S. T. Genetic isolation between conspecific populations and their relationship to climate heterogeneity. Acta Oecol. 116, 103847 (2022).
Google Scholar
Teta, P., de la Sancha, N. U., D’Elía, G. & Patterson, B. D. Andean rain shadow effect drives phenotypic variation in a widely distributed Austral rodent. J. Biogeogr. 00, 1–12 (2022).
León-Tapia, M. A. DNA barcoding and demographic history of Peromyscus yucatanicus (Rodentia: Cricetidae) endemic to the Yucatan Peninsula, Mexico. J. Mammal. Evol. 28(2), 481–495 (2021).
Google Scholar
Lin, X. et al. Climatic-niche evolution with key morphological innovations across clades within Scutiger boulengeri (Anura: Megophryidae). Ecol. Evol. 11, 10353–10368 (2021).
Google Scholar
Source: Ecology - nature.com