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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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.
The authors declare no competing interests.
Peer review information Nature Climate Change thanks the anonymous reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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.
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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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