Abstract
Climate change is a major determinant of shifts in species’ distribution ranges and habitat suitability. The Arctic is one of the planet’s most rapidly warming regions, yet biogeographic responses to contemporary climate change remain unknown for most cold-adapted mammalian species. Using the maximum entropy machine learning algorithm and 40 years (1981–2020) of observation data of muskoxen (Ovibos moschatus) collected across the Northeast Greenland National Park (NGNP), we detect rapid northward shifts (69–108 km per decade) of high to medium suitable habitat coinciding with a southward shift (27 km per decade) of low suitable habitat. Biogeographic response rates accelerated after the start of the twenty-first century, when anomalies in temperature and precipitation became more frequent and intensified. Our study shows that contemporary climate change has led to extreme directional shifts in habitat suitability for the largest herbivore roaming the Arctic tundra when compared to other species from around the globe. The consequences of these extreme directional shifts in habitat suitability on local population persistence remain to be determined but gene flow and dispersal capacity across the rugged Arctic landscape are likely important drivers.
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Data and R code used in this study are available at : https://doi.org/10.5281/zenodo.7050670.
References
Bacon L, Hingrat Y, Jiguet F et al (2017) Habitat suitability and demography, a time-dependent relationship. Ecol Evol 7:2214. https://doi.org/10.1002/ECE3.2821
Bay C (1992) A phytogeographical study of the vascular plants of northern Greenland. Bioscience 36, The Commission for Scientific Research in Greenland, Copenhagen, Denmark
Berger J, Hartway C, Gruzdev A, Johnson M (2018) Climate degradation and extreme icing events constrain life in cold-adapted mammals. Sci Rep 8:1156. https://doi.org/10.1038/s41598-018-19416-9
Beumer LT, van Beest FM, Stelvig M, Schmidt NM (2019) Spatiotemporal dynamics in habitat suitability of a large Arctic herbivore: environmental heterogeneity is key to a sedentary lifestyle. Global Ecol Conserv 18:e00647. https://doi.org/10.1016/J.GECCO.2019.E00647
Bintanja R (2018) The impact of Arctic warming on increased rainfall. Sci Rep 8:1–6. https://doi.org/10.1038/s41598-018-34450-3
Bohl CL, Kass JM, Anderson RP (2019) A new null model approach to quantify performance and significance for ecological niche models of species distributions. J Biogeogr 46:1101–1111. https://doi.org/10.1111/JBI.13573
Booth TH (2017) Assessing species climatic requirements beyond the realized niche: some lessons mainly from tree species distribution modelling. Clim Change 145:259–271. https://doi.org/10.1007/s10584-017-2107-9
Brown JL (2014) SDMtoolbox: a python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses. Methods Ecol Evol 5:694–700. https://doi.org/10.1111/2041-210X.12200
Campos PF, Willerslev E, Sher A et al (2010) Ancient DNA analyses exclude humans as the driving force behind late pleistocene musk ox (Ovibos moschatus) population dynamics. Proc Natl Acad Sci USA 107:5675–5680. https://doi.org/10.1073/pnas.0907189107
Canteri E, Brown SC, Schmidt NM et al (2022) Spatiotemporal influences of climate and humans on muskox range dynamics over multiple millennia. Glob Change Biol 28:6602–6617. https://doi.org/10.1111/gcb.16375
Chen IC, Hill JK, Ohlemüller R et al (2011) Rapid range shifts of species associated with high levels of climate warming. Science 333:1024–1026. https://doi.org/10.1126/science.1206432
Cheptou PO, Hargreaves AL, Bonte D, Jacquemyn H (2017) Adaptation to fragmentation: evolutionary dynamics driven by human influences. Philos Trans R Soc B: Biol Sci 372. https://doi.org/10.1098/RSTB.2016.0037
Clark PJ, Evans FC (1954) Distance to nearest neighbor as a measure of spatial relationships in populations. Ecology 35:445–453. https://doi.org/10.2307/1931034
Cuyler C, Rowell J, Adamczewski J et al (2020) Muskox status, recent variation, and uncertain future. Ambio 49:805–819. https://doi.org/10.1007/s13280-019-01205-x
Desforges J-P, Gonçalo |, Marques M et al (2021) Environment and physiology shape Arctic ungulate population dynamics. Glob Change Biol 27:1755–1771. https://doi.org/10.1111/gcb.15484
Ehrlén J, Morris WF (2015) Predicting changes in the distribution and abundance of species under environmental change. Ecol Lett 18:303–314. https://doi.org/10.1111/ele.12410
Elith J, Graham H, Anderson CP et al (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29:129–151. https://doi.org/10.1111/j.2006.0906-7590.04596.x
Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annu Rev Ecol Evol Syst 40:677–697. https://doi.org/10.1146/annurev.ecolsys.110308.120159
Elmendorf SC, Henry GHR, Hollister RD et al (2012) Global assessment of experimental climate warming on tundra vegetation: heterogeneity over space and time. Ecol Lett 15:164–175. https://doi.org/10.1111/j.1461-0248.2011.01716.x
Faurby S, Araújo MB (2018) Anthropogenic range contractions bias species climate change forecasts. Nat Clim Change 8:252–256. https://doi.org/10.1038/s41558-018-0089-x
Feng X, Park DS, Liang Y et al (2019) Collinearity in ecological niche modeling: confusions and challenges. Ecol Evol 9:10365–10376. https://doi.org/10.1002/ece3.5555
Forchhammer M, Boertmann D (1993) The muskoxen Ovibos moschatus in north and northeast Greenland: population trends and the influence of abiotic parameters on population dynamics. Ecography 16:299–308. https://doi.org/10.1111/j.1600-0587.1993.tb00219.x
Hansen BB, Isaksen K, Benestad RE et al (2014) Warmer and wetter winters: characteristics and implications of an extreme weather event in the high Arctic. Environ Res Lett 9:114021–114031. https://doi.org/10.1088/1748-9326/9/11/114021
Hansen CCR, Hvilsom C, Schmidt NM et al (2018) The muskox lost a substantial part of its genetic diversity on its long road to Greenland. Curr Biol 28:4022-4028e5. https://doi.org/10.1016/J.CUB.2018.10.054
Hassel K, Zechmeister H, Prestø T (2014) Mosses (Bryophyta) and liverworts (Marchantiophyta) of the Zackenberg valley, northeast Greenland. lnbg 37:66–84. https://doi.org/10.25227/linbg.01051
Hewitt G (2003) Ice ages: species distributions, and evolution. Evolution on Planet Earth: The Impact of the Physical Environment, 339–361. https://doi.org/10.1016/B978-012598655-7/50045-8
Hickling R, Roy DB, Hill JK et al (2006) The distributions of a wide range of taxonomic groups are expanding polewards. Glob Change Biol 12:450–455. https://doi.org/10.1111/J.1365-2486.2006.01116.X
Inman R, Franklin J, Esque T, Nussear K (2021) Comparing sample bias correction methods for species distribution modeling using virtual species. Ecosphere 12:e03422. https://doi.org/10.1002/ecs2.3422
IPCC (2021) Climate Change 2021: the physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK
Jia GJ, Epstein HE, Walker DA (2003) Greening of arctic Alaska, 1981–2001. Geophys Res Lett 30:2067. https://doi.org/10.1029/2003GL018268
Kass JM, Muscarella R, Galante PJ et al (2021) ENMeval 2.0: redesigned for customizable and reproducible modeling of species’ niches and distributions. Methods Ecol Evol 12:1602–1608. https://doi.org/10.1111/2041-210X.13628
Kelly AE, Goulden ML (2008) Rapid shifts in plant distribution with recent climate change. Proc Natl Acad Sci USA 105:11823–11826. https://doi.org/10.1073/pnas.0802891105
Lima ARA, Baltazar-Soares M, Garrido S et al (2022) Forecasting shifts in habitat suitability across the distribution range of a temperate small pelagic fish under different scenarios of climate change. Sci Total Environ 804:150167. https://doi.org/10.1016/J.SCITOTENV.2021.150167
Liu C, White M, Newell G (2013) Selecting thresholds for the prediction of species occurrence with presence-only data. J Biogeogr 40:778–789. https://doi.org/10.1111/jbi.12058
Loe LE, Hansen BB, Stien A et al (2016) Behavioral buffering of extreme weather events in a high-Arctic herbivore. Ecosphere 7:e01374. https://doi.org/10.1002/ecs2.1374
López-Blanco E, Langen PL, Williams M et al (2022) The future of tundra carbon storage in Greenland – Sensitivity to climate and plant trait changes. Sci Total Environ 846:157385. https://doi.org/10.1016/j.scitotenv.2022.157385
Malhi Y, Franklin J, Seddon N et al (2020) Climate change and ecosystems: threats, opportunities and solutions. Philosophical Trans Royal Soc B: Biol Sci 375:20190104. https://doi.org/10.1098/rstb.2019.0104
May JL, Parker T, Unger S, Oberbauer SF (2018) Short term changes in moisture content drive strong changes in normalized difference Vegetation Index and gross primary productivity in four Arctic moss communities. Remote Sens Environ 212:114–120. https://doi.org/10.1016/j.rse.2018.04.041
Mazziotta A, Triviño M, Tikkanen O-P et al (2016) Habitat associations drive species vulnerability to climate change in boreal forests. Clim Change 135:585–595. https://doi.org/10.1007/s10584-015-1591-z
Merow C, Smith MJ, Silander JA (2013) A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography 36:1058–1069. https://doi.org/10.1111/J.1600-0587.2013.07872.X
Mosbacher JB, Michelsen A, Stelvig M et al (2019) Muskoxen modify plant abundance, phenology, and nitrogen dynamics in a high Arctic fen. Ecosystems 22:1095–1107. https://doi.org/10.1007/s10021-018-0323-4
Muñoz-Sabater J, Dutra E, Agusti-Panareda A et al (2021) ERA5-Land: a state-of-the-art global reanalysis dataset for land applications. Earth Syst Sci Data 13:4349–4383. https://doi.org/10.5194/essd-13-4349-2021
Myers-Smith IH, Kerby JT, Phoenix GK et al (2020) Complexity revealed in the greening of the Arctic. Nat Clim Chang 10:106–117. https://doi.org/10.1038/s41558-019-0688-1
Nakagawa S, Schielzeth H (2013) A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol Evol 4:133–142. https://doi.org/10.1111/J.2041-210X.2012.00261.X
Overland JE (2021) Rare events in the Arctic. Clim Change 168:1–13. https://doi.org/10.1007/S10584-021-03238-2/FIGURES/7
Parmesan C, Ryrholm N, Stefanescu C et al (1999) Poleward shifts in geographical ranges of butterfly species associated with regional warming. Nature 399:579–583. https://doi.org/10.1038/21181
Pettorelli N, Ryan S, Mueller T et al (2011) The normalized difference vegetation index (NDVI): unforeseen successes in animal ecology. Climate Res 46:15–27. https://doi.org/10.3354/CR00936
Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259. https://doi.org/10.1016/j.ecolmodel.2005.03.026
Phillips SJ, Dudík M, Elith J et al (2009) Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecol Appl 19:181–197. https://doi.org/10.1890/07-2153.1
Poloczanska ES, Burrows MT, Brown CJ et al (2016) Responses of marine organisms to climate change across oceans. Front Mar Sci 3:62. https://doi.org/10.3389/FMARS.2016.00062/BIBTEX
Pouliot D, Latifovic R, Olthof I (2008) Trends in vegetation NDVI from 1 km AVHRR data over Canada for the period 1985–2006. Int J Remote Sens 30:149–168. https://doi.org/10.1080/01431160802302090
Raiho AM, Henry |, Scharf R et al (2022) Searching for refuge: a framework for identifying site factors conferring resistance to climate-driven vegetation change. Divers Distrib 28:793–809. https://doi.org/10.1111/DDI.13492
Rantanen M, Karpechko AY, Lipponen A et al (2022) The Arctic has warmed nearly four times faster than the globe since 1979. Commun Earth Environ 3:1–10. https://doi.org/10.1038/s43247-022-00498-3
Schmidt NM, van Beest FM, Mosbacher JB et al (2016) Ungulate movement in an extreme seasonal environment: year-round movement patterns of high-arctic muskoxen. Wildl Biology 22:253–267. https://doi.org/10.2981/wlb.00219
Tamstorf MP, Illeris L, Hansen BU, Wisz M (2007) Spectral measures and mixed models as valuable tools for investigating controls on land surface phenology in high arctic Greenland. BMC Ecol 7:9. https://doi.org/10.1186/1472-6785-7-9
Tucker MA, Böhning-Gaese K, Fagan WF et al (2018) Moving in the Anthropocene: global reductions in terrestrial mammalian movements. Science 359:466–469. https://doi.org/10.1126/science.aam9712
van Beest FM, Barry T, Christensen T et al (2022) Extreme event impacts on terrestrial and freshwater biota in the Arctic: a synthesis of knowledge and opportunities. Front Environ Sci 10:983637. https://doi.org/10.3389/fenvs.2022.983637
van Beest FM, Beumer LT, Andersen AS et al (2021) Rapid shifts in Arctic tundra species’ distributions and inter-specific range overlap under future climate change. Divers Distrib 27:1706–1718. https://doi.org/10.1111/ddi.13362
van Beest FM, Beumer LT, Chimienti M et al (2020) Environmental conditions alter behavioural organization and rhythmicity of a large Arctic ruminant across the annual cycle. Royal Soc Open Sci 7:201614. https://doi.org/10.5061/dryad.w3r2280n5
Williams CM, Henry HAL, Sinclair BJ (2015) Cold truths: how winter drives responses of terrestrial organisms to climate change. Biol Rev 90:214–235. https://doi.org/10.1111/brv.12105
Zurell D, Franklin J, König C et al (2020) A standard protocol for reporting species distribution models. Ecography 43:1261–1277. https://doi.org/10.1111/ecog.04960
Acknowledgements
We are grateful to the Joint Arctic Command for making the location data available to us and we thank all sled patrol teams whose dedicated efforts over the years have made this study possible. We also like to thank three reviewers for their constructive feedback on a previous manuscript draft.
Funding
ELB was supported by Greenland Research Council grant number 80.35, financed by the “Danish Program for Arctic Research.”
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FMvB, LHH, and NMS conceived the study. ELB downloaded, formatted, and aggregated the reanalysis of ERA5 data and produced the maps. FMvB performed the statistical analyses and wrote the first manuscript draft. All authors critically revised the manuscript, gave approval for publication, and agree to be accountable for all aspects of the work.
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van Beest, F.M., López-Blanco, E., Hansen, L.H. et al. Extreme shifts in habitat suitability under contemporary climate change for a high-Arctic herbivore. Climatic Change 176, 31 (2023). https://doi.org/10.1007/s10584-023-03510-7
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DOI: https://doi.org/10.1007/s10584-023-03510-7