Hey, J. On the arbitrary identification of real species. In Speciation and Patterns of Diversity (eds Butlin, R. K. et al.) 15–28 (Cambridge University Press, 2009).
Arbogast, B. S., Edwards, S. V., Wakeley, J., Beerli, P. & Slowinski, J. B. Estimating divergence times from molecular data on phylogenetic and population genetic timescales. Annu. Rev. Ecol. Syst. 33, 707–740 (2002).
Nielsen, R. & Wakeley, J. Distinguishing migration from isolation: A Markov chain Monte Carlo approach. Genetics 158, 885–896 (2001).
Google Scholar
Wakeley, J. The effects of subdivision on the genetic divergence of populations and species. Evolution 54, 1092–1101 (2000).
Google Scholar
Hey, J. & Nielsen, R. Multilocus methods for estimating population sizes, migration rates and divergence time, with applications to the divergence of Drosophila pseudoobscura and D. persimilis. Genetics 167, 747–760 (2004).
Google Scholar
Hey, J. Isolation with migration models for more than two populations. Mol. Biol. Evol. 27, 905–920 (2010).
Google Scholar
Mailund, T. et al. A new isolation with migration model along complete genomes infers very different divergence processes among closely related great ape species. PLoS Genet. 8, e1003125 (2012).
Google Scholar
Igea, J., Aymerich, P., Bannikova, A. A., Gosálbez, J. & Castresana, J. Multilocus species trees and species delimitation in a temporal context: Application to the water shrews of the genus Neomys. BMC Evol. Biol. 15, 209 (2015).
Google Scholar
Sánchez-Gracia, A. & Castresana, J. Impact of deep coalescence on the reliability of species tree inference from different types of DNA markers in mammals. PLoS One 7, e30239 (2012).
Google Scholar
Degnan, J. H. & Rosenberg, N. A. Gene tree discordance, phylogenetic inference and the multispecies coalescent. Trends Ecol. Evol. 24, 332–340 (2009).
Google Scholar
Edwards, S. V. & Beerli, P. Perspective: Gene divergence, population divergence, and the variance in coalescence time in phylogeographic studies. Evolution 54, 1839–1854 (2000).
Google Scholar
Peterson, B. K., Weber, J. N., Kay, E. H., Fisher, H. S. & Hoekstra, H. E. Double digest RADseq: An inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PLoS One 7, e37135 (2012).
Google Scholar
Andrews, K. R., Good, J. M., Miller, M. R., Luikart, G. & Hohenlohe, P. A. Harnessing the power of RADseq for ecological and evolutionary genomics. Nat. Rev. Genet. 17, 81–92 (2016).
Google Scholar
Escoda, L., Fernández-González, A. & Castresana, J. Quantitative analysis of connectivity in populations of a semi-aquatic mammal using kinship categories and network assortativity. Mol. Ecol. Resour. 19, 310–326 (2019).
Google Scholar
Bininda-Emonds, O. R. P. Fast genes and slow clades: Comparative rates of molecular evolution in mammals. Evol. Bioinform. 3, 59 (2007).
Google Scholar
Welch, J. J., Bininda-Emonds, O. R. P. & Bromham, L. Correlates of substitution rate variation in mammalian protein-coding sequences. BMC Evol. Biol. 8, 53 (2008).
Google Scholar
Matassi, G., Sharp, P. M. & Gautier, C. Chromosomal location effects on gene sequence evolution in mammals. Curr. Biol. 9, 786–791 (1999).
Google Scholar
Lercher, M. J., Chamary, J. V. & Hurst, L. D. Genomic regionality in rates of evolution is not explained by clustering of genes of comparable expression profile. Genome Res. 14, 1002–1013 (2004).
Google Scholar
Castresana, J. Genes on human chromosome 19 show extreme divergence from the mouse orthologs and a high GC content. Nucleic Acids Res. 30, 1751–1756 (2002).
Google Scholar
Benton, M. J., Donoghue, P. C. J. & Asher, R. J. Calibrating and constraining molecular clocks. In The Timetree of Life (eds Hedges, S. B. & Kumar, S.) 35–86 (Oxford University Press, 2009).
Bouckaert, R. et al. BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. PLoS Comput. Biol. 15, e1006650 (2019).
Google Scholar
Musser, G. G. & Carleton, M. D. Superfamily Muroidea. In Mammal Species of the World. A Taxonomic and Geographic Reference (eds Wilson, D. E. & Reeder, D. M.) 894–1531 (Johns Hopkins University Press, 2005).
Pardiñas, U. F. J. et al. Family Cricetidae (True Hamsters, Voles, Lemmings and New World Rats and Mice). In Handbook of the Mammals of the World. Volume 7. Rodents II (eds Wilson, D. E. et al.) 204-279 (Lynx Edicions, 2017).
Chevret, P. et al. Genetic structure, ecological versatility, and skull shape differentiation in Arvicola water voles (Rodentia, Cricetidae). J. Zoolog. Syst. Evol. Res. 58, 1323–1334 (2020).
Kryštufek, B. et al. Fossorial morphotype does not make a species in water voles. Mammalia 79, 293–303 (2015).
Centeno-Cuadros, A., Delibes, M. & Godoy, J. A. Dating the divergence between Southern and European water voles using molecular coalescent-based methods. J. Zool. 279, 404–409 (2009).
Castiglia, R. et al. The Italian peninsula hosts a divergent mtDNA lineage of the water vole, Arvicola amphibius s.l., including fossorial and aquatic ecotypes. Hystrix 27, 99–103 (2016).
Mahmoudi, A. et al. Evolutionary history of water voles revisited: Confronting a new phylogenetic model from molecular data with the fossil record. Mammalia 84, 171–184 (2020).
Cassola, F. Arvicola scherman, Montane Water Vole. The IUCN Red List of Threatened Species e.T136766A115519839 (2016).
Somoano, A., Miñarro, M. & Ventura, J. Reproductive potential of a vole pest (Arvicola scherman) in Spanish apple orchards. Spanish J. Agric. Res. 14, e1008 (2016).
Somoano, A., Ventura, J. & Miñarro, M. Continuous breeding of fossorial water voles in northwestern Spain: Potential impact on apple orchards. Folia Zool. 66, 37–49 (2017).
Ventura, J. & Gosálbez, J. Taxonomic review of Arvicola terrestris (Linnaeus, 1758) (Rodentia, Arvicolidae) in the Iberian Peninsula. Bonn Zool. Beitr. 40, 227–242 (1989).
Ventura, J. & Sans-Fuentes, M. A. Geographic variation and divergence in nonmetric cranial traits of Arvicola (Mammalia, Rodentia) in southwestern Europe. Z. Säugetierkunde 62, 99–107 (1997).
Gómez, A. & Lunt, D. H. Refugia within refugia: Patterns of phylogeographic concordance in the Iberian Peninsula. In Phylogeography of Southern European Refugia (eds S. Weiss & N. Ferrand) 155–188 (Springer, 2007).
Batsaikhan, N. et al. Arvicola amphibius, European Water Vole. The IUCN Red List of Threatened Species e.T2149A197271401 (2016).
Cuenca-Bescós, G., Agustí, J., Lira, J., Rubio, M. M. & Rofes, J. A new species of water vole from the early Pleistocene of Southern Europe. Acta Palaeontol. Pol. 55, 565–580 (2010).
Cubo, J., Ventura, J. & Casinos, A. A heterochronic interpretation of the origin of digging adaptations in the northern water vole, Arvicola terrestris (Rodentia: Arvicolidae). Biol. J. Linn. Soc. 87, 381–391 (2006).
Catchen, J. M., Hohenlohe, P. A., Bassham, S., Amores, A. & Cresko, W. A. Stacks: An analysis tool set for population genomics. Mol. Ecol. 22, 3124–3140 (2013).
Google Scholar
Pritchard, J. K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).
Google Scholar
Altschul, S. F. et al. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Res. 25, 3389–3402 (1997).
Google Scholar
Yates, A. D. et al. Ensembl 2020. Nucleic Acids Res. 48, D682–D688 (2020).
Google Scholar
Aghová, T. et al. Fossils know it best: Using a new set of fossil calibrations to improve the temporal phylogenetic framework of murid rodents (Rodentia: Muridae). Mol. Phylogenet. Evol. 128, 98–111 (2018).
Google Scholar
Hey, J. et al. Phylogeny estimation by integration over isolation with migration models. Mol. Biol. Evol. 35, 2805–2818 (2018).
Google Scholar
Phifer-Rixey, M., Harr, B. & Hey, J. Further resolution of the house mouse (Mus musculus) phylogeny by integration over isolation-with-migration histories. BMC Evol. Biol. 20, 120 (2020).
Google Scholar
Hey, J. The divergence of chimpanzee species and subspecies as revealed in multipopulation isolation-with-migration analyses. Mol. Biol. Evol. 27, 921–933 (2010).
Google Scholar
Kumar, S. & Subramanian, S. Mutation rates in mammalian genomes. Proc. Natl. Acad. Sci. U.S.A. 99, 803–808 (2002).
Google Scholar
Uchimura, A. et al. Germline mutation rates and the long-term phenotypic effects of mutation accumulation in wild-type laboratory mice and mutator mice. Genome Res. 25, 1125–1134 (2015).
Google Scholar
Milholland, B. et al. Differences between germline and somatic mutation rates in humans and mice. Nat. Commun. 8, 15183 (2017).
Google Scholar
Wright, B. R. et al. A demonstration of conservation genomics for threatened species management. Mol. Ecol. Resour. 20, 1526–1541 (2020).
Google Scholar
Escoda, L. & Castresana, J. The genome of the Pyrenean desman and the effects of bottlenecks and inbreeding on the genomic landscape of an endangered species. Evol. Appl. 14, 1898–1913 (2021).
Google Scholar
Arnold, B., Corbett-Detig, R. B., Hartl, D. & Bomblies, K. RADseq underestimates diversity and introduces genealogical biases due to nonrandom haplotype sampling. Mol. Ecol. 22, 3179–3190 (2013).
Google Scholar
Cariou, M., Duret, L. & Charlat, S. How and how much does RAD-seq bias genetic diversity estimates?. BMC Evol. Biol. 16, 240 (2016).
Google Scholar
Campbell, C. R. et al. Pedigree-based and phylogenetic methods support surprising patterns of mutation rate and spectrum in the gray mouse lemur. Heredity 127, 233–244 (2021).
Google Scholar
Scornavacca, C. et al. Orthomam v10: Scaling-up orthologous coding sequence and exon alignments with more than one hundred mammalian genomes. Mol. Biol. Evol. 36, 861–862 (2019).
Google Scholar
Willis, S. C., Hollenbeck, C. M., Puritz, J. B., Gold, J. R. & Portnoy, D. S. Haplotyping RAD loci: An efficient method to filter paralogs and account for physical linkage. Mol. Ecol. Resour. 17, 955–965 (2017).
Google Scholar
O’Leary, S. J., Puritz, J. B., Willis, S. C., Hollenbeck, C. M. & Portnoy, D. S. These aren’t the loci you’e looking for: Principles of effective SNP filtering for molecular ecologists. Mol. Ecol. 27, 3193–3206 (2018).
Dahl-Jensen, D. et al. Eemian interglacial reconstructed from a Greenland folded ice core. Nature 493, 489–494 (2013).
Google Scholar
Clark, P. U. et al. The last glacial maximum. Science 325, 710–714 (2009).
Google Scholar
Pinho, C. & Hey, J. Divergence with gene flow: Models and data. Annu. Rev. Ecol. Evol. Syst. 41, 215–230 (2010).
Balmori-de la Puente, A. et al. Size increase without genetic divergence in the Eurasian water shrew Neomys fodiens. Sci. Rep. 9, 17375 (2019).
Google Scholar
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Google Scholar
Foll, M. & Gaggiotti, O. A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: A Bayesian perspective. Genetics 180, 977–993 (2008).
Google Scholar
Freedman, A. H. et al. Genome sequencing highlights the dynamic early history of dogs. PLoS Genet. 10, e1004016 (2014).
Google Scholar
Felsenstein, J. PHYLIP-phylogeny inference package (version 3.4). Cladistics 5, 164–166 (1989).
Zheng, X. et al. A high-performance computing toolset for relatedness and principal component analysis of SNP data. Bioinformatics 28, 3326–3328 (2012).
Google Scholar
Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 14, 2611–2620 (2005).
Google Scholar
Jakobsson, M. & Rosenberg, N. A. CLUMPP: A cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23, 1801–1806 (2007).
Google Scholar
Goudet, J. HIERFSTAT, a package for R to compute and test hierarchical F-statistics. Mol. Ecol. Notes 5, 184–186 (2005).
Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: Improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).
Google Scholar
Castresana, J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol. Biol. Evol. 17, 540–552 (2000).
Google Scholar
Stamatakis, A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).
Google Scholar
Brown, R. P. & Yang, Z. Rate variation and estimation of divergence times using strict and relaxed clocks. BMC Evol. Biol. 11, 271 (2011).
Google Scholar
Rambaut, A., Drummond, A. J., Xie, D., Baele, G. & Suchard, M. A. Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7. Syst. Biol. 67, 901–904 (2018).
Google Scholar
Hey, J. & Wang, K. The effect of undetected recombination on genealogy sampling and inference under an isolation-with-migration model. Mol. Ecol. Resour. 18, 489 (2019).
QGIS_Development_Team. QGIS Geographic Information System. Open Source Geospatial Foundation Project. http://qgis.osgeo.org (2021).
IUCN. Arvicola scherman. The IUCN Red List of Threatened Species. Version 6.2. https://www.iucnredlist.org. Downloaded on 04 September 2019. (2019).
IUCN. Arvicola amphibius. The IUCN Red List of Threatened Species. Version 6.2. https://www.iucnredlist.org. Downloaded on 10 July 2019. (2019).
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