Abstract
Despite widespread biodiversity losses, an understanding of how most taxa will respond to future climate change is lacking. Here we integrate genomics and environmental modelling to assess climate change responses in an ecologically and economically important Arctic species. Environmentally associated genomic diversity and machine learning are used to identify highly vulnerable populations of anadromous (migratory) Arctic charr, and we reconstruct estimates of effective population size spanning the twentieth century to identify past climate-associated declines. We uncover past region-wide declines in effective population size that correspond to decreases in temperature and community biomass in the Northwest Atlantic. We find vulnerable populations near the southern range limit, indicating northward shifts and a possible loss of commercially important life-history variation in response to climate change. The genomic approach used here to investigate climate change response identifies past and future declines that impact species persistence, ecosystem stability and food security in the Arctic.
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Data availability
Environmental, climate, community biomass, weight and abundance data were compiled from publicly available sources or other studies (https://doi.org/10.1098/rsos.170215 (refs. 37,39,40). Genotype data are available at: https://doi.org/10.5061/dryad.8sf7m0ckd.
Code availability
No custom scripts were used in these analyses.
Change history
17 March 2021
A Correction to this paper has been published: https://doi.org/10.1038/s41558-021-01023-8
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Acknowledgements
We thank staff of the Newfoundland DFO Salmonids section, Parks Canada, the Nunatsiavut Government, the NunatuKavut Community Council, the Sivunivut Inuit Community Corporation, the Innu Nation, the Labrador Hunting and Fishing Association and fishers for their support, participation and tissue collections and the staff of the Aquatic Biotechnology Lab at the Bedford Institute of Oceanography for DNA extractions. This study was supported by the Ocean Frontier Institute, a Genomics Research and Development Initiative (GRDI) Grant, a Natural Sciences and Engineering Research Council (NSERC) Discovery Grant and Strategic Project Grant to I.R.B., the Weston Family Award for research at the Torngat Mountains Base Camp and an Atlantic Canada Opportunities Agency and Department of Tourism, Culture, Industry and Innovation grant allocated to the Labrador Institute.
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K.K.S.L., P.V.R.S. and I.R.B. designed the study. K.K.S.L., T.K., S.J.L. and R.R.E.S. contributed to statistical analyses. P.V.R.S., J.B.D., P.B., S.J.D., A.M.M., C.M.N., M.M.F., J.S.L. and B.F.K. provided molecular data and metadata for the study. All authors discussed the findings. K.K.S.L. wrote the manuscript with contributions from all authors.
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Extended data
Extended Data Fig. 1 Absolute loadings for each SNP along the first canonical axis in an RDA.
Absolute loadings for each SNP along the first canonical axis in an RDA with SNPs in the top 95th percentile treated as significant. Environment-associated SNPs are highlighted in red and genes located near top SNPs are labeled (ASIC4 = acid-sensing ion channel 4-like, COL18A1= collagen alpha-1(XVIII) chain, ELOVL1= elongation of very long chain fatty acids protein 1, KCNH2= potassium voltage-gated channel subfamily H member 2-like, PITPNB= phosphatidylinositol transfer protein beta isoform, TGFBR1= TGF-beta receptor type-1, TGM2= protein-glutamine gamma-glutamyltransferase 2, TGOLN2= trans-Golgi network integral membrane protein 2).
Extended Data Fig. 2 Genomic vulnerability is strongly negatively correlated with nucleotide diversity.
Genomic vulnerability is strongly negatively correlated with nucleotide diversity at a all 16,431 SNPs in this study and b 822 environment-associated SNPs under four different emissions scenarios.
Extended Data Fig. 3 Effective population size (Ne) estimates with confidence intervals.
Effective population size (Ne) estimates, representing number of individuals, for 28 populations of Arctic Charr. 95% confidence intervals appear in black and population codes appear in Supplementary Table 1.
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Supplementary Figs. 1–5 and Tables 1–6.
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Layton, K.K.S., Snelgrove, P.V.R., Dempson, J.B. et al. Genomic evidence of past and future climate-linked loss in a migratory Arctic fish. Nat. Clim. Chang. 11, 158–165 (2021). https://doi.org/10.1038/s41558-020-00959-7
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DOI: https://doi.org/10.1038/s41558-020-00959-7
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