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Natural hybridization reduces vulnerability to climate change

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  • Ackerly, D. D. Community assembly, niche conservatism, and adaptive evolution in changing environments. Int. J. Plant Sci. 164, S165–S184 (2003).

    Article 

    Google Scholar 

  • Kellermann, V., Van Heerwaarden, B., Sgrò, C. M. & Hoffmann, A. A. Fundamental evolutionary limits in ecological traits drive Drosophila species distributions. Science 325, 1244–1246 (2009).

    Article 
    CAS 

    Google Scholar 

  • Hansen, M. M., Olivieri, I., Waller, D. M. & Nielsen, E. E. Monitoring adaptive genetic responses to environmental change. Mol. Ecol. 21, 1311–1329 (2012).

    Article 

    Google Scholar 

  • Aitken, S. N. & Whitlock, M. C. Assisted gene flow to facilitate local adaptation to climate change. Annu. Rev. Ecol. Evol. Syst. 44, 367–388 (2013).

    Article 

    Google Scholar 

  • Becker, M. et al. Hybridization may facilitate in situ survival of endemic species through periods of climate change. Nat. Clim. Change 3, 1039–1043 (2013).

    Article 

    Google Scholar 

  • Allendorf, F. W., Leary, R. F., Spruell, P. & Wenburg, J. K. The problems with hybrids: setting conservation guidelines. Trends Ecol. Evol. 16, 613–622 (2001).

    Article 

    Google Scholar 

  • Todesco, M. et al. Hybridization and extinction. Evol. Appl. 9, 892–908 (2016).

    Article 
    CAS 

    Google Scholar 

  • Rhymer, J. M. & Simberloff, D. Extinction by hybridization and introgression. Annu. Rev. Ecol. Syst. 27, 83–109 (1996).

    Article 

    Google Scholar 

  • Taylor, S. A. & Larson, E. L. Insights from genomes into the evolutionary importance and prevalence of hybridization in nature. Nat. Ecol. Evol. 3, 170–177 (2019).

    Article 

    Google Scholar 

  • vonHoldt, B. M., Brzeski, K. E., Wilcove, D. S. & Rutledge, L. Y. Redefining the role of admixture and genomics in species conservation. Conserv. Lett. 11, e12371 (2018).

    Article 

    Google Scholar 

  • Hamilton, J. A. & Miller, J. M. Adaptive introgression as a resource for management and genetic conservation in a changing climate. Conserv. Biol. 30, 33–41 (2016).

    Article 

    Google Scholar 

  • Ralls, K., Sunnucks, P., Lacy, R. C. & Frankham, R. Genetic rescue: a critique of the evidence supports maximizing genetic diversity rather than minimizing the introduction of putatively harmful genetic variation. Biol. Conserv. 251, 108784 (2020).

    Article 

    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).

    Article 

    Google Scholar 

  • Rellstab, C., Dauphin, B. & Exposito‐Alonso, M. Prospects and limitations of genomic offset in conservation management. Evol. Appl. 14, 1202–1212 (2021).

    Article 

    Google Scholar 

  • Bay, R. A. et al. Genomic signals of selection predict climate-driven population declines in a migratory bird. Science 359, 83–86 (2018).

    Article 
    CAS 

    Google Scholar 

  • Rellstab, C. et al. Signatures of local adaptation in candidate genes of oaks (Quercus spp.) with respect to present and future climatic conditions. Mol. Ecol. 25, 5907–5924 (2016).

    Article 

    Google Scholar 

  • Fitzpatrick, M. C. & Keller, S. R. Ecological genomics meets community-level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation. Ecol. Lett. 18, 1–16 (2015).

    Article 

    Google Scholar 

  • Exposito-Alonso, M. et al. Genomic basis and evolutionary potential for extreme drought adaptation in Arabidopsis thaliana. Nat. Ecol. Evol. 2, 352–358 (2018).

    Article 

    Google Scholar 

  • Kindt, R. AlleleShift: an R package to predict and visualize population-level changes in allele frequencies in response to climate change. PeerJ 9, e11534 (2021).

    Article 

    Google Scholar 

  • Gain, C. & François, O. LEA 3: factor models in population genetics and ecological genomics with R. Mol. Ecol. Resour. 21, 2738–2748 (2020).

    Article 

    Google Scholar 

  • Aguirre-Liguori, J. A., Ramírez-Barahona, S. & Gaut, B. S. The evolutionary genomics of species’ responses to climate change. Nat. Ecol. Evol. 5, 1350–1360 (2021).

    Article 

    Google Scholar 

  • Taylor, S. A., Larson, E. L. & Harrison, R. G. Hybrid zones: windows on climate change. Trends Ecol. Evol. 30, 398–406 (2015).

    Article 

    Google Scholar 

  • Hoffmann, A. A. & Sgro, C. M. Climate change and evolutionary adaptation. Nature 470, 479–485 (2011).

    Article 
    CAS 

    Google Scholar 

  • McGuigan, K., Franklin, C. E., Moritz, C. & Blows, M. W. Adaptation of rainbow fish to lake and stream habitats. Evolution 57, 104–118 (2003).

    Google Scholar 

  • Smith, S., Bernatchez, L. & Beheregaray, L. RNA-seq analysis reveals extensive transcriptional plasticity to temperature stress in a freshwater fish species. BMC Genomics 14, 375 (2013).

    Article 
    CAS 

    Google Scholar 

  • Smith, S. et al. Latitudinal variation in climate‐associated genes imperils range edge populations. Mol. Ecol. 29, 4337–4349 (2020).

    Article 
    CAS 

    Google Scholar 

  • Sandoval-Castillo, J. et al. Adaptation of plasticity to projected maximum temperatures and across climatically defined bioregions. Proc. Natl Acad. Sci. USA 117, 17112–17121 (2020).

    Article 
    CAS 

    Google Scholar 

  • Brauer, C., Unmack, P. J., Smith, S., Bernatchez, L. & Beheregaray, L. B. On the roles of landscape heterogeneity and environmental variation in determining population genomic structure in a dendritic system. Mol. Ecol. 27, 3484–3497 (2018).

    Article 
    CAS 

    Google Scholar 

  • Attard, C. R. et al. Fish out of water: genomic insights into persistence of rainbowfish populations in the desert. Evolution 76, 171–183 (2022).

    Article 

    Google Scholar 

  • Gates, K. et al. Environmental selection, rather than neutral processes, best explain patterns of diversity in a tropical rainforest fish. Preprint at bioRxiv https://doi.org/10.1101/2022.1105.1113.491913 (2022).

    Article 

    Google Scholar 

  • McCairns, R. J. S., Smith, S., Sasaki, M., Bernatchez, L. & Beheregaray, L. B. The adaptive potential of subtropical rainbowfish in the face of climate change: heritability and heritable plasticity for the expression of candidate genes. Evol. Appl. 9, 531–545 (2016).

    Article 
    CAS 

    Google Scholar 

  • McGuigan, K., Zhu, D., Allen, G. & Moritz, C. Phylogenetic relationships and historical biogeography of melanotaeniid fishes in Australia and New Guinea. Mar. Freshwat. Res. 51, 713–723 (2000).

    Article 

    Google Scholar 

  • Unmack, P. J. et al. Malanda Gold: the tale of a unique rainbowfish from the Atherton Tablelands, now on the verge of extinction. Fish. Sahul. 30, 1039–1054 (2016).

    Google Scholar 

  • Moritz, C. Strategies to protect biological diversity and the evolutionary processes that sustain it. Syst. Biol. 51, 238–254 (2002).

    Article 

    Google Scholar 

  • Pope, L., Estoup, A. & Moritz, C. Phylogeography and population structure of an ecotonal marsupial, Bettongia tropica, determined using mtDNA and microsatellites. Mol. Ecol. 9, 2041–2053 (2000).

    Article 
    CAS 

    Google Scholar 

  • Hugall, A., Moritz, C., Moussalli, A. & Stanisic, J. Reconciling paleodistribution models and comparative phylogeography in the Wet Tropics rainforest land snail Gnarosophia bellendenkerensis (Brazier 1875). Proc. Natl Acad. Sci. USA 99, 6112–6117 (2002).

    Article 
    CAS 

    Google Scholar 

  • Moritz, C. et al. Identification and dynamics of a cryptic suture zone in tropical rainforest. Proc. R. Soc. B. 276, 1235–1244 (2009).

    Article 
    CAS 

    Google Scholar 

  • Phillips, B. L., Baird, S. J. & Moritz, C. When vicars meet: a narrow contact zone between morphologically cryptic phylogeographic lineages of the rainforest skink, Carlia rubrigularis. Evolution 58, 1536–1548 (2004).

    Google Scholar 

  • Krosch, M. N., Baker, A. M., Mckie, B. G., Mather, P. B. & Cranston, P. S. Deeply divergent mitochondrial lineages reveal patterns of local endemism in chironomids of the Australian Wet Tropics. Austral Ecol. 34, 317–328 (2009).

    Article 

    Google Scholar 

  • Williams, S. E., Bolitho, E. E. & Fox, S. Climate change in Australian tropical rainforests: an impending environmental catastrophe. Proc. R. Soc. B. 270, 1887–1892 (2003).

    Article 

    Google Scholar 

  • Whitehead, P. et al. Temporal development of the Atherton Basalt Province, north Queensland. Aust. J. Earth Sci. 54, 691–709 (2007).

    Article 
    CAS 

    Google Scholar 

  • Moy, K. G., Unmack, P. J., Lintermans, M., Duncan, R. P. & Brown, C. Barriers to hybridisation and their conservation implications for a highly threatened Australian fish species. Ethology 125, 142–152 (2019).

    Article 

    Google Scholar 

  • Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009).

    Article 
    CAS 

    Google Scholar 

  • Buerkle, C. A. Maximum‐likelihood estimation of a hybrid index based on molecular markers. Mol. Ecol. Notes 5, 684–687 (2005).

    Article 
    CAS 

    Google Scholar 

  • Anderson, E. & Thompson, E. A model-based method for identifying species hybrids using multilocus genetic data. Genetics 160, 1217–1229 (2002).

    Article 
    CAS 

    Google Scholar 

  • Dorion, S. & Landry, J. Activation of the mitogen-activated protein kinase pathways by heat shock. Cell Stress Chaperones 7, 200 (2002).

    <a data-track="click" rel="nofollow noopener" data-track-label="10.1379/1466-1268(2002)0072.0.CO;2″ data-track-action=”article reference” href=”https://doi.org/10.1379%2F1466-1268%282002%29007%3C0200%3AAOTMAP%3E2.0.CO%3B2″ aria-label=”Article reference 46″ data-doi=”10.1379/1466-1268(2002)0072.0.CO;2″>Article 
    CAS 

    Google Scholar 

  • Blumstein, M. et al. Protocol for projecting allele frequency change under future climate change at adaptive-associated loci. STAR Protoc. 1, 100061 (2020).

    Article 

    Google Scholar 

  • Gougherty, A. V., Keller, S. R. & Fitzpatrick, M. C. Maladaptation, migration and extirpation fuel climate change risk in a forest tree species. Nat. Clim. Change 11, 166–171 (2021).

    Article 

    Google Scholar 

  • Blumstein, M. et al. A new perspective on ecological prediction reveals limits to climate adaptation in a temperate tree species. Curr. Biol. 30, 1447–1453. e1444 (2020).

    Article 
    CAS 

    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).

    Article 
    CAS 

    Google Scholar 

  • Goicoechea, P. G. et al. Adaptive introgression promotes fast adaptation in oaks marginal populations. Preprint available at bioRxiv https://doi.org/10.1101/731919 (2019).

  • Lavergne, S. & Molofsky, J. Increased genetic variation and evolutionary potential drive the success of an invasive grass. Proc. Natl Acad. Sci. USA 104, 3883–3888 (2007).

    Article 
    CAS 

    Google Scholar 

  • De Carvalho, D. et al. Admixture facilitates adaptation from standing variation in the European aspen (Populus tremula L.), a widespread forest tree. Mol. Ecol. 19, 1638–1650 (2010).

    Article 

    Google Scholar 

  • De-Kayne, R. et al. Genomic architecture of adaptive radiation and hybridization in Alpine whitefish. Nat. Commun. 13, 4479 (2022).

    Article 
    CAS 

    Google Scholar 

  • Baskett, M. L. & Gomulkiewicz, R. Introgressive hybridization as a mechanism for species rescue. Theor. Ecol. 4, 223–239 (2011).

    Article 

    Google Scholar 

  • Meier, J. I. et al. The coincidence of ecological opportunity with hybridization explains rapid adaptive radiation in Lake Mweru cichlid fishes. Nat. Commun. 10, 1–11 (2019).

    Article 
    CAS 

    Google Scholar 

  • Svardal, H. et al. Ancestral hybridization facilitated species diversification in the Lake Malawi cichlid fish adaptive radiation. Mol. Biol. Evol. 37, 1100–1113 (2020).

    Article 
    CAS 

    Google Scholar 

  • Racimo, F., Sankararaman, S., Nielsen, R. & Huerta-Sánchez, E. Evidence for archaic adaptive introgression in humans. Nat. Rev. Genet. 16, 359–371 (2015).

    Article 
    CAS 

    Google Scholar 

  • Jeong, C. et al. Admixture facilitates genetic adaptations to high altitude in Tibet. Nat. Commun. 5, 1–7 (2014).

    Article 

    Google Scholar 

  • Nolte, A. W., Freyhof, J., Stemshorn, K. C. & Tautz, D. An invasive lineage of sculpins, Cottus sp. (Pisces, Teleostei) in the Rhine with new habitat adaptations has originated from hybridization between old phylogeographic groups. Proc. R. Soc. B. 272, 2379–2387 (2005).

    Article 

    Google Scholar 

  • Fitzpatrick, M. C., Chhatre, V. E., Soolanayakanahally, R. Y. & Keller, S. R. Experimental support for genomic prediction of climate maladaptation using the machine learning approach Gradient Forests. Mol. Ecol. Resour. 21, 2749–2765 (2021).

    Article 
    CAS 

    Google Scholar 

  • Schneider, C., Cunningham, M. & Moritz, C. Comparative phylogeography and the history of endemic vertebrates in the Wet Tropics rainforests of Australia. Mol. Ecol. 7, 487–498 (1998).

    Article 

    Google Scholar 

  • Hewitt, G. M. Quaternary phylogeography: the roots of hybrid zones. Genetica 139, 617–638 (2011).

    Article 

    Google Scholar 

  • Pfennig, K. S., Kelly, A. L. & Pierce, A. A. Hybridization as a facilitator of species range expansion. Proc. R. Soc. B. 283, 20161329 (2016).

    Article 

    Google Scholar 

  • Soulé, M. E. What is conservation biology? A new synthetic discipline addresses the dynamics and problems of perturbed species, communities, and ecosystems. Bioscience 35, 727–734 (1985).

    Google Scholar 

  • Biermann, C. & Havlick, D. Genetics and the question of purity in cutthroat trout restoration. Restor. Ecol. 29, e13516 (2021).

    Article 

    Google Scholar 

  • Fredrickson, R. J. & Hedrick, P. W. Dynamics of hybridization and introgression in red wolves and coyotes. Conserv. Biol. 20, 1272–1283 (2006).

    Article 

    Google Scholar 

  • Hirashiki, C., Kareiva, P. & Marvier, M. Concern over hybridization risks should not preclude conservation interventions. Conserv. Sci. Pract. 3, e424 (2021).

    Google Scholar 

  • Unmack, P. J., Allen, G. R. & Johnson, J. B. Phylogeny and biogeography of rainbowfishes (Melanotaeniidae) from Australia and New Guinea. Mol. Phylogenet. Evol. 67, 15–27 (2013).

    Article 

    Google Scholar 

  • Allen, G. Rainbowfishes in Nature and the Aquarium (Tetra Publications, 1995).

  • Seehausen, O. Hybridization and adaptive radiation. Trends Ecol. Evol. 19, 198–207 (2004).

    Article 

    Google Scholar 

  • Pusey, B., Kennard, M. J. & Arthington, A. H. Freshwater Fishes of North-eastern Australia (CSIRO Publishing, 2004).

  • Zhu, D., Degnan, S. & Moritz, C. Evolutionary distinctiveness and status of the endangered Lake Eacham rainbowfish (Melanotaenia eachamensis). Conserv. Biol. 12, 80–93 (1998).

    Article 

    Google Scholar 

  • McGuigan, K., Chenoweth, S. F. & Blows, M. W. Phenotypic divergence along lines of genetic variance. Am. Nat. 165, 32–43 (2005).

    Article 

    Google Scholar 

  • Sunnucks, P. & Hales, D. F. Numerous transposed sequences of mitochondrial cytochrome oxidase I-II in aphids of the genus Sitobion (Hemiptera: Aphididae). Mol. Biol. Evol. 13, 510–524 (1996).

    Article 
    CAS 

    Google Scholar 

  • Peterson, B., Weber, J., Kay, E., Fisher, H. & Hoekstra, H. Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PLoS ONE 7, e37135 (2012).

    Article 
    CAS 

    Google Scholar 

  • Catchen, J. M., Amores, A., Hohenlohe, P., Cresko, W. & Postlethwait, J. H. Stacks: building and genotyping loci de novo from short-read sequences. G3: Genes Genomes Genet. 1, 171–182 (2011).

    Article 
    CAS 

    Google Scholar 

  • Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    Article 
    CAS 

    Google Scholar 

  • Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357 (2012).

    Article 
    CAS 

    Google Scholar 

  • DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).

    Article 
    CAS 

    Google Scholar 

  • Danecek, P. et al. Twelve years of SAMtools and BCFtools. Gigascience 10, giab008 (2021).

    Article 

    Google Scholar 

  • Goudet, J. Hierfstat, a package for R to compute and test hierarchical F‐statistics. Mol. Ecol. Notes 5, 184–186 (2005).

    Article 

    Google Scholar 

  • R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021).

  • Bailey, R. ribailey/gghybrid: gghybrid R package for Bayesian hybrid index and genomic cline estimation. v2.0.0 https://doi.org/10.5281/zenodo.3676498 (2020).

  • Wringe, B. hybriddetective: automates the process of detecting hybrids from genetic data. R package version 0.1.0.9000 https://github.com/bwringe/hybriddetective (2016).

  • Pickrell, J. K. & Pritchard, J. K. Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet. 8, e1002967 (2012).

    Article 
    CAS 

    Google Scholar 

  • Malinsky, M., Matschiner, M. & Svardal, H. Dsuite‐Fast D‐statistics and related admixture evidence from VCF files. Mol. Ecol. Resour. 21, 584–595 (2021).

    Article 

    Google Scholar 

  • Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    Article 
    CAS 

    Google Scholar 

  • Green, R. E. et al. A draft sequence of the Neandertal genome. Science 328, 710–722 (2010).

    Article 
    CAS 

    Google Scholar 

  • Durand, E. Y., Patterson, N., Reich, D. & Slatkin, M. Testing for ancient admixture between closely related populations. Mol. Biol. Evol. 28, 2239–2252 (2011).

    Article 
    CAS 

    Google Scholar 

  • Malinsky, M. et al. Genomic islands of speciation separate cichlid ecomorphs in an East African crater lake. Science 350, 1493–1498 (2015).

    Article 
    CAS 

    Google Scholar 

  • Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    Article 
    CAS 

    Google Scholar 

  • Karger, D. N. et al. Climatologies at high resolution for the earth’s land surface areas. Sci. Data 4, 1–20 (2017).

    Article 

    Google Scholar 

  • Karger, D. N. et al. CHELSA climatologies at high resolution for the Earth’s land surface areas (v.1.0). https://doi.org/10.1594/WDCC/CHELSA_v1 (2016).

  • Ackerley, D. & Dommenget, D. Atmosphere-only GCM (ACCESS1.0) simulations with prescribed land surface temperatures. Geosci. Model Dev. 9, 2077–2098 (2016).

    Article 

    Google Scholar 

  • Brown, J. L., Hill, D. J., Dolan, A. M., Carnaval, A. C. & Haywood, A. M. PaleoClim: high spatial resolution paleoclimate surfaces for global land areas. Sci. Data 5, 1–9 (2018).

    Article 

    Google Scholar 

  • Fordham, D. A. et al. PaleoView: a tool for generating continuous climate projections spanning the last 21,000 years at regional and global scales. Ecography 40, 1348–1358 (2017).

    Article 

    Google Scholar 

  • Thuiller, W., Lafourcade, B., Engler, R. & Araújo, M. B. BIOMOD–a platform for ensemble forecasting of species distributions. Ecography 32, 369–373 (2009).

    Article 

    Google Scholar 

  • Lemus-Canovas, M., Lopez-Bustins, J. A., Martin-Vide, J. & Royé, D. synoptReg: an R package for computing a synoptic climate classification and a spatial regionalization of environmental data. Environ. Model. Softw. 118, 114–119 (2019).

    Article 

    Google Scholar 

  • Hao, T., Elith, J., Guillera‐Arroita, G. & Lahoz‐Monfort, J. J. A review of evidence about use and performance of species distribution modelling ensembles like BIOMOD. Divers. Distrib. 25, 839–852 (2019).

    Article 

    Google Scholar 

  • Galpern, P., Peres‐Neto, P. R., Polfus, J. & Manseau, M. MEMGENE: spatial pattern detection in genetic distance data. Methods Ecol. Evol. 5, 1116–1120 (2014).

    Article 

    Google Scholar 

  • Peres‐Neto, P. R. & Galpern, P. memgene: spatial pattern detection in genetic distance data using Moran’s eigenvector maps. R package version 1.0.1 https://cran.r-project.org/web/packages/memgene/ (2019).

  • Oksanen, J. et al. vegan: community ecology package. R package version 2.3–0 https://cran.r-project.org/web/packages/vegan/ (2015).

  • Forester, B. R., Jones, M. R., Joost, S., Landguth, E. L. & Lasky, J. R. Detecting spatial genetic signatures of local adaptation in heterogeneous landscapes. Mol. Ecol. 25, 104–120 (2015).

    Article 

    Google Scholar 

  • Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 6, 80–92 (2012).

    Article 
    CAS 

    Google Scholar 

  • Szklarczyk, D. et al. The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 49, D605–D612 (2021).

    Article 
    CAS 

    Google Scholar 

  • Brauer, C. J. et al. Data for ‘Natural hybridisation reduces vulnerability to climate change’. figshare https://doi.org/10.6084/m9.figshare.21692918 (2022).

  • Brauer, C. J. et al. Code for ‘Natural hybridisation reduces vulnerability to climate change’. GitHub https://github.com/pygmyperch/NER (2022).


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