Davis, M. B. & Shaw, R. G. Range shifts and adaptive responses to Quaternary climate change. Science 292, 673–679 (2001).
Google Scholar
Parmesan, C. Ecological and evolutionary responses to recent climate change. Annu. Rev. Ecol. Evol. Syst. 37, 637–669 (2006).
Google Scholar
Hewitt, G. The genetic legacy of the Quaternary ice ages. Nature 405, 907–913 (2000).
Google Scholar
Williams, J. E. & Blois, J. L. Range shifts in response to past and future climate change: can climate velocities and species’ dispersal capabilities explain variation in mammalian range shifts? J. Biogeogr. 45, 2175–2189 (2018).
Google Scholar
Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421, 37–42 (2003).
Google Scholar
Thomas, C. D. Climate, climate change and range boundaries. Divers. Distrib. 16, 488–495 (2010).
Google Scholar
Bradshaw, A. D. & McNeilly, T. Evolutionary response to global climatic change. Ann. Bot. 67, 5–14 (1991).
Google Scholar
Harter, D. E. V. et al. Impacts of global climate change on the floras of oceanic islands—projections, implications and current knowledge. Perspect. Plant Ecol. Evol. Syst. 17, 160–183 (2015).
Google Scholar
Veron, S., Haevermans, T., Govaerts, R., Mouchet, M. & Pellens, R. Distribution and relative age of endemism across islands worldwide. Sci. Rep. 9, 1–12 (2019).
Google Scholar
Román-Palacios, C. & Wiens, J. J. Recent responses to climate change reveal the drivers of species extinction and survival. Proc. Natl Acad. Sci. USA 117, 4211–4217 (2020).
Google Scholar
Jump, A. S. & Peñuelas, J. Running to stand still: adaptation and the response of plants to rapid climate change. Ecol. Lett. 8, 1010–1020 (2005).
Google Scholar
Freeman, B. G., Scholer, M. N., Ruiz-Gutierrez, V. & Fitzpatrick, J. W. Climate change causes upslope shifts and mountaintop extirpations in a tropical bird community. Proc. Natl Acad. Sci. USA 115, 11982–11987 (2018).
Google Scholar
Gilbert, K. J. & Whitlock, M. C. The genetics of adaptation to discrete heterogeneous environments: frequent mutation or large-effect alleles can allow range expansion. J. Evol. Biol. 30, 591–602 (2017).
Google Scholar
Christmas, M. J., Breed, M. F. & Lowe, A. J. Constraints to and conservation implications for climate change adaptation in plants. Conserv. Genet. 17, 305–320 (2015).
Google Scholar
Barrett, R. D. H. & Schluter, D. Adaptation from standing genetic variation. Trends Ecol. Evol. 23, 38–44 (2008).
Google Scholar
Lai, Y. T. et al. Standing genetic variation as the predominant source for adaptation of a songbird. Proc. Natl Acad. Sci. USA 116, 2152–2157 (2019).
Google Scholar
Hoban, S. et al. Finding the genomic basis of local adaptation: Pitfalls, practical solutions, and future directions. Am. Nat. 188, 379–397 (2016).
Google Scholar
Hoffmann, A. A. & Sgrò, C. M. Climate change and evolutionary adaptation. Nature 470, 479–485 (2011).
Google Scholar
Catullo, R. A., Llewelyn, J., Phillips, B. L. & Moritz, C. C. The potential for rapid evolution under anthropogenic climate change. Curr. Biol. 29, R996–R1007 (2019).
Google Scholar
Botkin, D. B. et al. Forecasting the effects of global warming on biodiversity. BioScience 57, 227–236 (2007).
Google Scholar
Wiens, J. A., Stralberg, D., Jongsomjit, D., Howell, C. A. & Snyder, M. A. Niches, models, and climate change: assessing the assumptions and uncertainties. Proc. Natl Acad. Sci. USA 106, 19729–19736 (2009).
Google Scholar
Smith, A. B., Godsoe, W., Rodríguez-Sánchez, F., Wang, H. H. & Warren, D. Niche estimation above and below the species level. Trends Ecol. Evol. 34, 260–273 (2019).
Google Scholar
Waldvogel, A.-M. et al. Evolutionary genomics can improve prediction of species’ responses to climate change. Evol. Lett. 4, 4–18 (2020).
Google Scholar
Razgour, O. et al. An integrated framework to identify wildlife populations under threat from climate change. Mol. Ecol. Resour. 18, 18–31 (2018).
Google Scholar
Razgour, O. et al. Considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections. Proc. Natl Acad. Sci. USA 116, 10418–10423 (2019).
Google Scholar
Aguirre-Liguori, J. A., Ramírez-Barahona, S., Tiffin, P. & Eguiarte, L. E. Climate change is predicted to disrupt patterns of local adaptation in wild and cultivated maize. Proc. R. Soc. B 286, 20190486 (2019).
Google Scholar
Evans, T. G., Diamond, S. E. & Kelly, M. W. Mechanistic species distribution modelling as a link between physiology and conservation. Conserv. Physiol. 3, cov056 (2015).
Google Scholar
Hall, S. J. G. Haemoglobin polymorphism in the bank vole, Clethrionomys glareolus, in Britain. J. Zool. 187, 153–160 (1979).
Google Scholar
Kotlík, P. et al. Adaptive phylogeography: functional divergence between haemoglobins derived from different glacial refugia in the bank vole. Proc. R. Soc. B 281, 20140021 (2014).
Google Scholar
Searle, J. B. et al. The Celtic fringe of Britain: Insights from small mammal phylogeography. Proc. R. Soc. B 276, 4287–4294 (2009).
Google Scholar
Escalante, M. A., Horníková, M., Marková, S. & Kotlík, P. Niche differentiation in a postglacial colonizer, the bank vole Clethrionomys glareolus. Ecol. Evol. 11, 8054–8070 (2021).
Google Scholar
Reischl, E., Dafre, A. L., Franco, J. L. & Wilhelm Filho, D. Distribution, adaptation and physiological meaning of thiols from vertebrate hemoglobins. Comp. Biochem. Physiol. Part C. Toxicol. Pharmacol. 146, 22–53 (2007).
Google Scholar
Storz, J. F. & Wheat, C. W. Integrating evolutionary and functional approaches to infer adaptation at specific loci. Evolution 64, 2489–2509 (2010).
Google Scholar
Rossi, R. et al. Different metabolizing ability of thiol reactants in human and rat blood. Biochemical and pharmacological implications. J. Biol. Chem. 276, 7004–7010 (2001).
Google Scholar
Vitturi, D. A. et al. Antioxidant functions for the hemoglobin β93 cysteine residue in erythrocytes and in the vascular compartment in vivo. Free Radic. Biol. Med. 55, 119–129 (2013).
Google Scholar
Petersen, A. G. et al. Hemoglobin polymerization via disulfide bond formation in the hypoxia-tolerant turtle Trachemys scripta: Implications for antioxidant defense and O2 transport. Am. J. Physiol. Regul. Integr. Comp. Physiol. 314, R84–R93 (2018).
Google Scholar
Paital, B. et al. Longevity of animals under reactive oxygen species stress and disease susceptibility due to global warming. World J. Biol. Chem. 7, 110–127 (2016).
Google Scholar
Jacobs, P. J., Oosthuizen, M. K., Mitchell, C., Blount, J. D. & Bennett, N. C. Heat and dehydration induced oxidative damage and antioxidant defenses following incubator heat stress and a simulated heat wave in wild caught four-striped field mice Rhabdomys dilectus. PLoS One 15, e0242279 (2020).
Google Scholar
Kotlík, P., Marková, S., Horníková, M., Escalante, M. A. & Searle, J. B. The bank vole (Clethrionomys glareolus) as a model system for adaptive phylogeography in the European theater. Front. Ecol. Evol. 10, 866605 (2022).
Google Scholar
Strážnická, M., Marková, S., Searle, J. B. & Kotlík, P. Playing hide-and-seek in beta-globin genes: Gene conversion transferring a beneficial mutation between differentially expressed gene guplicates. Genes 9, 492 (2018).
Google Scholar
Stocker, T. Climate Change 2013: the Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, 2013).
Araújo, M. B., Pearson, R. G., Thuiller, W. & Erhard, M. Validation of species-climate impact models under climate change. Glob. Chang. Biol. 11, 1504–1513 (2005).
Google Scholar
Peterson, A. T., Papeş, M. & Soberón, J. Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecol. Modell. 213, 63–72 (2008).
Google Scholar
Warren, D. L., Glor, R. E. & Turelli, M. Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution 62, 2868–2883 (2008).
Google Scholar
Warren, D. L. et al. ENMTools 1.0: an R package for comparative ecological biogeography. Ecography 44, 504–511 (2021).
Google Scholar
Mayes, J. & Wheeler, D. Regional weather and climates of the British Isles—part 1: introduction. Weather 68, 3–8 (2013).
Google Scholar
Kotlík, P., Marková, S., Konczal, M., Babik, W. & Searle, J. B. Genomics of end-Pleistocene population replacement in a small mammal. Proc. R. Soc. B 285, 20172624 (2018).
Google Scholar
Capblancq, T., Fitzpatrick, M. C., Bay, R. A., Exposito-Alonso, M. & Keller, S. R. Genomic prediction of (mal)adaptation across current and future climatic landscapes. Annu. Rev. Ecol. Evol. Syst. 51, 245–269 (2020).
Google Scholar
Benito Garzón, M., Robson, T. M. & Hampe, A. ΔTraitSDMs: species distribution models that account for local adaptation and phenotypic plasticity. N. Phytol. 222, 1757–1765 (2019).
Google Scholar
Wisz, M. S. et al. Effects of sample size on the performance of species distribution models. Divers. Distrib. 14, 763–773 (2008).
Google Scholar
Phillips, S. J., Dudík, M. & Schapire, R. E. A maximum entropy approach to species distribution modeling. in Twenty-first International Conference on Machine Learning – ICML ’04 9, 83 (ACM Press, 2004).
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, 1965–1978 (2005).
Google Scholar
Zeng, Y., Low, B. W. & Yeo, D. C. J. Novel methods to select environmental variables in MaxEnt: A case study using invasive crayfish. Ecol. Modell. 341, 5–13 (2016).
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, 335–342 (2011).
Google Scholar
Warren, D. L., Glor, R. E. & Turelli, M. ENMTools: a toolbox for comparative studies of environmental niche models. Ecography 33, 607–611 (2010).
Google Scholar
Gent, P. R. et al. The community climate system model version 4. J. Clim. 24, 4973–4991 (2011).
Google Scholar
Dufresne, J. L. et al. Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5. Clim. Dyn. 40, 2123–2165 (2013).
Google Scholar
Watanabe, S. et al. MIROC-ESM 2010: model description and basic results of CMIP5-20c3m experiments. Geosci. Model Dev. 4, 845–872 (2011).
Google Scholar
Giorgetta, M. A. et al. Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5. J. Adv. Model. Earth Syst. 5, 572–597 (2013).
Google Scholar
Schoener, T. W. The anolis lizards of Bimini: resource partitioning in a complex fauna. Ecology 49, 704–726 (1968).
Google Scholar
Source: Ecology - nature.com
