Plant traits poorly predict winner and loser shrub species in a warming tundra biome

. 2023 Jun 28 ; 14 (1) : 3837. [epub] 20230628

Jazyk angličtina Země Velká Británie, Anglie Médium electronic

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid37380662
Odkazy

PubMed 37380662
PubMed Central PMC10307830
DOI 10.1038/s41467-023-39573-4
PII: 10.1038/s41467-023-39573-4
Knihovny.cz E-zdroje

Climate change is leading to species redistributions. In the tundra biome, shrubs are generally expanding, but not all tundra shrub species will benefit from warming. Winner and loser species, and the characteristics that may determine success or failure, have not yet been fully identified. Here, we investigate whether past abundance changes, current range sizes and projected range shifts derived from species distribution models are related to plant trait values and intraspecific trait variation. We combined 17,921 trait records with observed past and modelled future distributions from 62 tundra shrub species across three continents. We found that species with greater variation in seed mass and specific leaf area had larger projected range shifts, and projected winner species had greater seed mass values. However, trait values and variation were not consistently related to current and projected ranges, nor to past abundance change. Overall, our findings indicate that abundance change and range shifts will not lead to directional modifications in shrub trait composition, since winner and loser species share relatively similar trait spaces.

Arctic Centre University of Lapland Rovaniemi Finland

Biology Department Grand Valley State University Allendale MI USA

Centre for African Conservation Ecology Nelson Mandela University Port Elizabeth South Africa

Centre for Environmental Sciences Hasselt University Hasselt Belgium

Centre for Integrative Ecology School of Life and Environmental Sciences Deakin University Burwood VIC Australia

Climate Change and Extremes in Alpine Regions Research Centre CERC Davos Switzerland

Copernicus Institute of Sustainable Development Utrecht University Utrecht the Netherlands

CREAF Cerdanyola del Vallès Barcelona Catalonia Spain

Département des Sciences de l'environnement et Centre d'études nordiques Université du Québec à Trois Rivières Trois Rivières Québec Canada

Department of Biological Sciences Florida International University Miami FL USA

Department of Biology Aarhus University Aarhus Denmark

Department of Biology and Environmental Science Marietta College Marietta OH USA

Department of Biology and Environmental Sciences University of Gothenburg Gothenburg Sweden

Department of Biology Memorial University St John's NL Canada

Department of Biology Queen's University Kingston Ontario ON Canada

Department of Biotechnologies and Life Sciences University of Insubria Varese Italy

Department of Chemical and Biological Metrology Federal Institute of Metrology METAS Bern Wabern Switzerland

Department of Ecology and Genetics University of Oulu Oulu Finland

Department of Evolutionary Biology and Environmental Studies University of Zurich Zurich Switzerland

Department of Geography University of British Columbia Vancouver BC Canada

Department of Geosciences and Geography University of Helsinki Helsinki Finland

Department of Physiological Diversity Helmholtz Centre for Environmental Research UFZ Leipzig Germany

Dutch Research Council The Hague The Netherlands

Environmental Science Center Qatar University Doha Qatar

German Centre for Integrative Biodiversity Research Halle Jena Leipzig Leipzig Germany

Gothenburg Global Biodiversity Centre Gothenburg Sweden

Government of British Columbia Vancouver BC Canada

Institute of Biology and Environmental Sciences University of Oldenburg Oldenburg Germany

Institute of Botany and Landscape Ecology University of Greifswald Greifswald Germany

Institute of Hydrobiology Biology Centre of the Czech Academy of Sciences Ceske Budejovice Czech Republic

Komarov Botanical Institute St Petersburg Russia

Land Surface Atmosphere Interactions School of Life Sciences Weihenstephan Freising Germany

Natural Resources Canada Canadian Forest Service Great Lakes Forestry Centre Sault Ste Marie ON Canada

Research Centre for Ecological Change Organismal and Evolutionary Biology Research Programme University of Helsinki Helsinki Finland

Research Group Plants and Ecosystems University of Antwerp Wilrijk Belgium

School of Environment Resources and Sustainability University of Waterloo Waterloo ON Canada

School of GeoSciences University of Edinburgh Edinburgh Scotland UK

Section Systems Ecology Amsterdam Institute for Life and Environment Vrije Universiteit Amsterdam The Netherlands

Swiss Federal Research Institute WSL Birmensdorf Switzerland

Terra Nova National Park Parks Canada Agency Glovertown NL Canada

Threatened Endangered and Diversity Program Alaska Department of Fish and Game Anchorage USA

U S Geological Survey Fort Collins CO USA

Woodwell Climate Research Center Falmouth MA USA

WSL Institute for Snow and Avalanche Research SLF Davos Switzerland

Zobrazit více v PubMed

Rantanen M, et al. The Arctic has warmed nearly four times faster than the globe since 1979. Commun. Earth Environ. 2022;3:1–10. doi: 10.1038/s43247-022-00498-3. DOI

Chylek P, et al. Annual mean Arctic amplification 1970–2020: observed and simulated by CMIP6 climate models. Geophys. Res. Lett. 2022;49:e2022GL099371. doi: 10.1029/2022GL099371. DOI

García Criado M, Myers‐Smith IH, Bjorkman AD, Lehmann CER, Stevens N. Woody plant encroachment intensifies under climate change across tundra and savanna biomes. Glob. Ecol. Biogeogr. 2020;29:925–943. doi: 10.1111/geb.13072. DOI

Martin AC, Jeffers ES, Petrokofsky G, Myers-Smith IH, Macias-Fauria M. Shrub growth and expansion in the Arctic tundra: an assessment of controlling factors using an evidence-based approach. Environ. Res. Lett. 2017;12:13. doi: 10.1088/1748-9326/aa7989. DOI

Myers-Smith IH, et al. Shrub expansion in tundra ecosystems: dynamics, impacts and research priorities. Environ. Res. Lett. 2011;6:045509. doi: 10.1088/1748-9326/6/4/045509. DOI

Naito AT, Cairns D. Patterns and processes of global shrub expansion. Prog. Phys. Geogr. 2011;35:423–442. doi: 10.1177/0309133311403538. DOI

Sturm M, Racine C, Tape KD. Climate change: Increasing shrub abundance in the Arctic. Nature. 2001;411:546. doi: 10.1038/35079180. PubMed DOI

Tape KD, Sturm M, Racine C. The evidence for shrub expansion in Northern Alaska and the Pan-Arctic. Glob. Change Biol. 2006;12:686–702. doi: 10.1111/j.1365-2486.2006.01128.x. DOI

Forbes BC, Fauria MM, Zetterberg P. Russian Arctic warming and ‘greening’ are closely tracked by tundra shrub willows. Glob. Change Biol. 2010;16:1542–1554. doi: 10.1111/j.1365-2486.2009.02047.x. DOI

Macias-Fauria, M., Forbes, B. C., Zetterberg, P. & Kumpula, T. Eurasian Arctic greening reveals teleconnections and the potential for novel ecosystems, 10.1038/nclimate1558 (2012).

Pellissier L, et al. Species distribution models reveal apparent competitive and facilitative effects of a dominant species on the distribution of tundra plants. Ecography. 2010;33:1004–1014. doi: 10.1111/j.1600-0587.2010.06386.x. DOI

Bjorkman AD, et al. Plant functional trait change across a warming tundra biome. Nature. 2018;562:57. doi: 10.1038/s41586-018-0563-7. PubMed DOI

Alexander JM, Diez JM, Levine JM. Novel competitors shape species’ responses to climate change. Nature. 2015;525:515–518. doi: 10.1038/nature14952. PubMed DOI

Mod HK, Scherrer D, Luoto M, Guisan A. What we use is not what we know: environmental predictors in plant distribution models. J. Vegetation Sci. 2016;27:1308–1322. doi: 10.1111/jvs.12444. DOI

Niittynen P, Heikkinen RK, Luoto M. Decreasing snow cover alters functional composition and diversity of Arctic tundra. Proc. Natl Acad. Sci. USA. 2020;117:21480–21487. doi: 10.1073/pnas.2001254117. PubMed DOI PMC

Hollister RD, et al. Warming experiments elucidate the drivers of observed directional changes in tundra vegetation. Ecol. Evol. 2015;5:1881–1895. doi: 10.1002/ece3.1499. PubMed DOI PMC

Maliniemi T, Kapfer J, Saccone P, Skog A, Virtanen R. Long-term vegetation changes of treeless heath communities in northern Fennoscandia: links to climate change trends and reindeer grazing. J. Vegetation Sci. 2018;29:469–479. doi: 10.1111/jvs.12630. DOI

Chen IC, Hill JK, Ohlemuller R, Roy DB, Thomas CD. Rapid range shifts of species associated with high levels of climate warming. Science. 2011;333:1024–1026. doi: 10.1126/science.1206432. PubMed DOI

Hastings RA, et al. Climate change drives poleward increases and equatorward declines in marine species. Curr. Biol. 2020;30:1572–1577.e2. doi: 10.1016/j.cub.2020.02.043. PubMed DOI

Hickling R, Roy DB, Hill JK, Fox R, Thomas CD. The distributions of a wide range of taxonomic groups are expanding polewards. Glob. Change Biol. 2006;12:450–455. doi: 10.1111/j.1365-2486.2006.01116.x. DOI

Parmesan C, et al. Poleward shifts in geographical ranges of butterfly species associated with regional warming. Nature. 1999;399:579–583. doi: 10.1038/21181. DOI

Birks HH. The Late-Quaternary history of arctic and alpine plants. Plant Ecol. Diversity. 2008;1:135–146. doi: 10.1080/17550870802328652. DOI

Crump, S. E. et al. Ancient plant DNA reveals high Arctic greening during the last interglacial. Proc. Natl Acad. Sci. USA118, e2019069118 (2021). PubMed PMC

Higuera PE, et al. Frequent fires in ancient shrub Tundra: implications of paleorecords for Arctic environmental change. PLoS ONE. 2008;3:e0001744. doi: 10.1371/journal.pone.0001744. PubMed DOI PMC

Gałka M, Swindles GT, Szal M, Fulweber R, Feurdean A. Response of plant communities to climate change during the late Holocene: palaeoecological insights from peatlands in the Alaskan Arctic. Ecol. Indic. 2018;85:525–536. doi: 10.1016/j.ecolind.2017.10.062. DOI

Sturm M, et al. Snow–shrub interactions in arctic tundra: a hypothesis with climatic implications. J. Clim. 2001;14:336–344. doi: 10.1175/1520-0442(2001)014<0336:SSIIAT>2.0.CO;2. DOI

Alsos IG, et al. Frequent long-distance plant colonization in the changing arctic. Science. 2007;316:1606–1609. doi: 10.1126/science.1139178. PubMed DOI

Angert AL, et al. Do species’ traits predict recent shifts at expanding range edges? Ecol. Lett. 2011;14:677–689. doi: 10.1111/j.1461-0248.2011.01620.x. PubMed DOI

Venn SE, Gallagher RV, Nicotra AB. Germination at extreme temperatures: implications for alpine shrub encroachment. Plants. 2021;10:327. doi: 10.3390/plants10020327. PubMed DOI PMC

Andruko R, Danby R, Grogan P. Recent growth and expansion of Birch shrubs across a low Arctic landscape in continental Canada: are these responses more a consequence of the severely declining caribou herd than of climate warming? Ecosystems. 2020;23:1362–1379. doi: 10.1007/s10021-019-00474-7. PubMed DOI PMC

Formica A, Farrer EC, Ashton IW, Suding KN. Shrub expansion over the past 62 years in rocky mountain alpine tundra: possible causes and consequences. Arct. Antarct. Alp. Res. 2014;46:616–631. doi: 10.1657/1938-4246-46.3.616. DOI

Myers-Smith IH, et al. Expansion of canopy-forming willows over the twentieth century on Herschel Island, Yukon Territory, Canada. Ambio. 2011;40:610. doi: 10.1007/s13280-011-0168-y. PubMed DOI PMC

Ropars P, Boudreau S. Shrub expansion at the forest–tundra ecotone: spatial heterogeneity linked to local topography. Environ. Res. Lett. 2012;7:015501. doi: 10.1088/1748-9326/7/1/015501. DOI

Violle C, et al. Let the concept of trait be functional! Oikos. 2007;116:882–892. doi: 10.1111/j.0030-1299.2007.15559.x. DOI

Díaz S, et al. The global spectrum of plant form and function. Nature. 2016;529:167–171. doi: 10.1038/nature16489. PubMed DOI

Shipley B, et al. Reinforcing loose foundation stones in trait-based plant ecology. Oecologia. 2016;180:923–931. doi: 10.1007/s00442-016-3549-x. PubMed DOI

Soudzilovskaia NA, et al. Functional traits predict relationship between plant abundance dynamic and long-term climate warming. Proc. Natl Acad. Sci. USA. 2013;110:18180–18184. doi: 10.1073/pnas.1310700110. PubMed DOI PMC

Pollock LJ, Morris WK, Vesk PA. The role of functional traits in species distributions revealed through a hierarchical model. Ecography. 2012;35:716–725. doi: 10.1111/j.1600-0587.2011.07085.x. DOI

Bruelheide H, et al. Global trait–environment relationships of plant communities. Nat. Ecol. Evolution. 2018;2:1906–1917. doi: 10.1038/s41559-018-0699-8. PubMed DOI

Betway KR, Hollister RD, May JL, Oberbauer SF. Species-specific trends and variability in plant functional traits across a latitudinal gradient in northern Alaska. J. Vegetation Sci. 2021;32:e13040. doi: 10.1111/jvs.13040. DOI

Bolnick DI, et al. Why intraspecific trait variation matters in community ecology. Trends Ecol. Evol. 2011;26:183–192. doi: 10.1016/j.tree.2011.01.009. PubMed DOI PMC

Thomas HJD, et al. Global plant trait relationships extend to the climatic extremes of the tundra biome. Nat. Commun. 2020;11:1–12. doi: 10.1038/s41467-020-15014-4. PubMed DOI PMC

Thomas HJD, et al. Traditional plant functional groups explain variation in economic but not size-related traits across the tundra biome. Glob. Ecol. Biogeogr. 2019;28:78–95. doi: 10.1111/geb.12783. PubMed DOI PMC

Myers‐Smith IH, Thomas HJD, Bjorkman AD. Plant traits inform predictions of tundra responses to global change. N. Phytologist. 2019;221:1742–1748. doi: 10.1111/nph.15592. PubMed DOI

Siefert A, et al. A global meta-analysis of the relative extent of intraspecific trait variation in plant communities. Ecol. Lett. 2015;18:1406–1419. doi: 10.1111/ele.12508. PubMed DOI

Lamy J-BJ-B, et al. Uniform selection as a primary force reducing population genetic differentiation of cavitation resistance across a species range. PLoS ONE. 2011;6:12. doi: 10.1371/journal.pone.0023476. PubMed DOI PMC

Jessen M-T, Kaarlejärvi E, Olofsson J, Eskelinen A. Mammalian herbivory shapes intraspecific trait responses to warmer climate and nutrient enrichment. Glob. Change Biol. 2020;26:6742–6752. doi: 10.1111/gcb.15378. PubMed DOI

Kumordzi BB, et al. Geographic scale and disturbance influence intraspecific trait variability in leaves and roots of North American understorey plants. Funct. Ecol. 2019;33:1771–1784. doi: 10.1111/1365-2435.13402. DOI

Cardou F, et al. Above- and belowground drivers of intraspecific trait variability across subcontinental gradients for five ubiquitous forest plants in North America. J. Ecol. 2022;110:1590–1605. doi: 10.1111/1365-2745.13894. DOI

Henn, J. J. et al. Intraspecific trait variation and phenotypic plasticity mediate alpine plant species response to climate change. Front. Plant Sci.9, 1548 (2018). PubMed PMC

Westoby M. A leaf-height-seed (LHS) plant ecology strategy scheme. Plant Soil. 1998;199:213–227. doi: 10.1023/A:1004327224729. DOI

Hamilton MA, et al. Life-history correlates of plant invasiveness at regional and continental scales. Ecol. Lett. 2005;8:1066–1074. doi: 10.1111/j.1461-0248.2005.00809.x. DOI

Wright IJ, et al. The worldwide leaf economics spectrum. Nature. 2004;428:821–827. doi: 10.1038/nature02403. PubMed DOI

Aubin I, et al. Traits to stay, traits to move: a review of functional traits to assess sensitivity and adaptive capacity of temperate and boreal trees to climate change. Environ. Rev. 2016;24:164+. doi: 10.1139/er-2015-0072. DOI

Lavorel S, Garnier E. Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail. Funct. Ecol. 2002;16:545–556. doi: 10.1046/j.1365-2435.2002.00664.x. DOI

Guisan A, Thuiller W. Predicting species distribution: offering more than simple habitat models. Ecol. Lett. 2005;8:993–1009. doi: 10.1111/j.1461-0248.2005.00792.x. PubMed DOI

Thuiller W, Guéguen M, Renaud J, Karger DN, Zimmermann NE. Uncertainty in ensembles of global biodiversity scenarios. Nat. Commun. 2019;10:1446. doi: 10.1038/s41467-019-09519-w. PubMed DOI PMC

Dormann CF. Promising the future? Global change projections of species distributions. Basic Appl. Ecol. 2007;8:387–397. doi: 10.1016/j.baae.2006.11.001. DOI

Pearson RG, Dawson TP. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Glob. Ecol. Biogeogr. 2003;12:361–371. doi: 10.1046/j.1466-822X.2003.00042.x. DOI

Elith J, Leathwick JR. Species distribution models: ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst. 2009;40:677–697. doi: 10.1146/annurev.ecolsys.110308.120159. DOI

Chardon NI, Pironon S, Peterson ML, Doak DF. Incorporating intraspecific variation into species distribution models improves distribution predictions, but cannot predict species traits for a wide-spread plant species. Ecography. 2020;43:60–74. doi: 10.1111/ecog.04630. DOI

Cunze S, Heydel F, Tackenberg O. Are plant species able to keep pace with the rapidly changing climate? PLoS ONE. 2013;8:e67909. doi: 10.1371/journal.pone.0067909. PubMed DOI PMC

Fordham DA, et al. Plant extinction risk under climate change: are forecast range shifts alone a good indicator of species vulnerability to global warming? Glob. Change Biol. 2012;18:1357–1371. doi: 10.1111/j.1365-2486.2011.02614.x. DOI

Garzón MB, Robson TM, Hampe A. ΔTraitSDMs: species distribution models that account for local adaptation and phenotypic plasticity. N. Phytologist. 2019;222:1757–1765. doi: 10.1111/nph.15716. PubMed DOI

Normand S, et al. A greener Greenland? Climatic potential and long-term constraints on future expansions of trees and shrubs. Philos. Trans. R. Soc. B: Biol. Sci. 2013;368:20120479. doi: 10.1098/rstb.2012.0479. PubMed DOI PMC

Elmendorf SC, et al. Plot-scale evidence of tundra vegetation change and links to recent summer warming. Nat. Clim. Change. 2012;2:453–457. doi: 10.1038/nclimate1465. DOI

Walker MD, et al. Plant community responses to experimental warming across the tundra biome. Proc. Natl Acad. Sci. USA. 2006;103:1342–1346. doi: 10.1073/pnas.0503198103. PubMed DOI PMC

Gaston, K. J. & Blackburn, T. M. Pattern and Process in Macroecology. (Blackwell Publishing, 2008).

Walker DA, et al. The Circumpolar Arctic vegetation map. J. Vegetation Sci. 2005;16:267–282. doi: 10.1111/j.1654-1103.2005.tb02365.x. DOI

Baruah G, Molau U, Bai Y, Alatalo JM. Community and species-specific responses of plant traits to 23 years of experimental warming across subarctic tundra plant communities. Sci. Rep. 2017;7:2571. doi: 10.1038/s41598-017-02595-2. PubMed DOI PMC

MacLean SA, Beissinger SR. Species’ traits as predictors of range shifts under contemporary climate change: A review and meta-analysis. Glob. Change Biol. 2017;23:4094–4105. doi: 10.1111/gcb.13736. PubMed DOI

Nathan R, et al. Mechanisms of long-distance seed dispersal. Trends Ecol. Evolution. 2008;23:638–647. doi: 10.1016/j.tree.2008.08.003. PubMed DOI

Moles AT, Westoby M. Seedling survival and seed size: a synthesis of the literature. J. Ecol. 2004;92:372–383. doi: 10.1111/j.0022-0477.2004.00884.x. DOI

Gaudet CL, Keddy PA. A comparative approach to predicting competitive ability from plant traits. Nature. 1988;334:242–243. doi: 10.1038/334242a0. DOI

Moles AT, et al. Global patterns in plant height. J. Ecol. 2009;97:923–932. doi: 10.1111/j.1365-2745.2009.01526.x. DOI

Lembrechts JJ, et al. Microclimate variability in alpine ecosystems as stepping stones for non-native plant establishment above their current elevational limit. Ecography. 2018;41:900–909. doi: 10.1111/ecog.03263. DOI

Opedal ØH, Armbruster WS, Graae BJ. Linking small-scale topography with microclimate, plant species diversity and intra-specific trait variation in an alpine landscape. Plant Ecol. Diversity. 2015;8:305–315. doi: 10.1080/17550874.2014.987330. DOI

Sporbert M, et al. Testing macroecological abundance patterns: The relationship between local abundance and range size, range position and climatic suitability among European vascular plants. J. Biogeogr. 2020;47:2210–2222. doi: 10.1111/jbi.13926. DOI

Kaarlejärvi E, Eskelinen A, Olofsson J. Herbivores rescue diversity in warming tundra by modulating trait-dependent species losses and gains. Nat. Commun. 2017;8:419. doi: 10.1038/s41467-017-00554-z. PubMed DOI PMC

Sporbert M, et al. Different sets of traits explain abundance and distribution patterns of European plants at different spatial scales. J. Vegetation Sci. 2021;32:e13016. doi: 10.1111/jvs.13016. DOI

Hagan, J. G., Henn, J. J. & Osterman, W. H. A. Plant traits alone are good predictors of ecosystem properties when used carefully. Nature Ecology and Evolution 1–3, 10.1038/s41559-022-01920-x (2023). PubMed

Dupré C, Ehrlén J. Habitat configuration, species traits and plant distributions. J. Ecol. 2002;90:796–805. doi: 10.1046/j.1365-2745.2002.00717.x. DOI

Estrada A, et al. Species’ intrinsic traits inform their range limitations and vulnerability under environmental change. Glob. Ecol. Biogeogr. 2015;24:849–858. doi: 10.1111/geb.12306. DOI

Beissinger SR, Riddell EA. Why are species’ traits weak predictors of range shifts? Annu. Rev. Ecol., Evolution, Syst. 2021;52:47–66. doi: 10.1146/annurev-ecolsys-012021-092849. DOI

Kremer A, Potts BM, Delzon S. Genetic divergence in forest trees: understanding the consequences of climate change. Funct. Ecol. 2014;28:22–36. doi: 10.1111/1365-2435.12169. DOI

Salguero‐Gómez R, Violle C, Gimenez O, Childs D. Delivering the promises of trait-based approaches to the needs of demographic approaches, and vice versa. Funct. Ecol. 2018;32:1424–1435. doi: 10.1111/1365-2435.13148. PubMed DOI PMC

Cornwell WK, Ackerly DD. A link between plant traits and abundance: evidence from coastal California woody plants. J. Ecol. 2010;98:814–821. doi: 10.1111/j.1365-2745.2010.01662.x. DOI

Van der Veken S, Bellemare J, Verheyen K, Hermy M. Life-history traits are correlated with geographical distribution patterns of western European forest herb species. J. Biogeogr. 2007;34:1723–1735. doi: 10.1111/j.1365-2699.2007.01738.x. DOI

Holzinger B, Hülber K, Camenisch M, Grabherr G. Changes in plant species richness over the last century in the eastern Swiss Alps: elevational gradient, bedrock effects and migration rates. Plant Ecol. 2008;195:179–196. doi: 10.1007/s11258-007-9314-9. DOI

Prager CM, et al. A mechanism of expansion: Arctic deciduous shrubs capitalize on warming-induced nutrient availability. Oecologia. 2020;192:671–685. doi: 10.1007/s00442-019-04586-8. PubMed DOI

Hudson JMG, Henry GHR, Cornwell WK. Taller and larger: shifts in Arctic tundra leaf traits after 16 years of experimental warming. Glob. Change Biol. 2011;17:1013–1021. doi: 10.1111/j.1365-2486.2010.02294.x. DOI

Vowles T, Björk RG. Implications of evergreen shrub expansion in the Arctic. J. Ecol. 2019;107:650–655. doi: 10.1111/1365-2745.13081. DOI

Vuorinen KEM, et al. Open tundra persist, but arctic features decline-Vegetation changes in the warming Fennoscandian tundra. Glob. Change Biol. 2017;23:3794–3807. doi: 10.1111/gcb.13710. PubMed DOI

Chapin FS, Bret‐Harte MS, Hobbie SE, Zhong H. Plant functional types as predictors of transient responses of arctic vegetation to global change. J. Vegetation Sci. 1996;7:347–358. doi: 10.2307/3236278. DOI

Bjorkman, A. D. et al. Status and trends in Arctic vegetation: Evidence from experimental warming and long-term monitoring. Ambio, 10.1007/s13280-019-01161-6 (2019). PubMed PMC

Hollister RD, Webber PJ, Bay C. Plant response to temperature in Northern Alaska: implications for predicting vegetation change. Ecology. 2005;86:1562–1570. doi: 10.1890/04-0520. DOI

Myers-Smith IH, et al. Complexity revealed in the greening of the Arctic. Nat. Clim. Change. 2020;10:106–117. doi: 10.1038/s41558-019-0688-1. DOI

Harrison SP, et al. Ecophysiological and bioclimatic foundations for a global plant functional classification. J. Vegetation Sci. 2010;21:300–317. doi: 10.1111/j.1654-1103.2009.01144.x. DOI

Kühn, N. et al. Globally important plant functional traits for coping with climate change. Front. Biogeogr.13, e53774 (2021).

Svenning J-C, Fløjgaard C, Marske KA, Nógues-Bravo D, Normand S. Applications of species distribution modeling to paleobiology. Quat. Sci. Rev. 2011;30:2930–2947. doi: 10.1016/j.quascirev.2011.06.012. DOI

Gough L. Neighbor effects on germination, survival, and growth in two arctic tundra plant communities. Ecography. 2006;29:44–56. doi: 10.1111/j.2005.0906-7590.04096.x. DOI

Post, E., Cahoon, S. M. P., Kerby, J. T., Pedersen, C. & Sullivan, P. F. Herbivory and warming interact in opposing patterns of covariation between arctic shrub species at large and local scales. Proc. Natl Acad. Sci. USA118, e2015158118 (2021). PubMed PMC

Wisz MS, et al. The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling. Biol. Rev. 2013;88:15–30. doi: 10.1111/j.1469-185X.2012.00235.x. PubMed DOI PMC

Hemrová L, Bullock JM, Hooftman DAP, White SM, Münzbergová Z. Drivers of plant species’ potential to spread: the importance of demography versus seed dispersal. Oikos. 2017;126:1493–1500. doi: 10.1111/oik.03975. DOI

Normand S, Zimmermann NE, Schurr FM, Lischke H. Demography as the basis for understanding and predicting range dynamics. Ecography. 2014;37:1149–1154. doi: 10.1111/ecog.01490. DOI

Graae BJ, et al. Stay or go – how topographic complexity influences alpine plant population and community responses to climate change. Perspect. Plant Ecol. Evol. Syst. 2018;30:41–50. doi: 10.1016/j.ppees.2017.09.008. DOI

Lenoir J, et al. Dispersal ability links to cross-scale species diversity patterns across the Eurasian Arctic tundra. Glob. Ecol. Biogeogr. 2012;21:851–860. doi: 10.1111/j.1466-8238.2011.00733.x. DOI

Ehrlén J, Morris WF, Euler Tvon, Dahlgren JP. Advancing environmentally explicit structured population models of plants. J. Ecol. 2016;104:292–305. doi: 10.1111/1365-2745.12523. DOI

Myers‐Smith, I. H. et al. Eighteen years of ecological monitoring reveals multiple lines of evidence for tundra vegetation change. Ecol. Monographs89, e01351 (2019).

Haider S, et al. Think globally, measure locally: the MIREN standardized protocol for monitoring plant species distributions along elevation gradients. Ecol. Evol. 2022;12:e8590. doi: 10.1002/ece3.8590. PubMed DOI PMC

Pauli, H. et al. The GLORIA field manual – standard Multi-Summit approach, supplementary methods and extra approaches. 5th edition. (GLORIA-Coordination, Austrian Academy of Sciences & University of Natural Resources and Life Sciences, Vienna, 2015).

Bonan, G. B. & Doney, S. C. Climate, ecosystems, and planetary futures: the challenge to predict life in Earth system models. Science359, eaam8328 (2018). PubMed

Fisher RA, et al. Vegetation demographics in Earth System Models: a review of progress and priorities. Glob. Change Biol. 2018;24:35–54. doi: 10.1111/gcb.13910. PubMed DOI

Wullschleger SD, et al. Plant functional types in Earth system models: past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems. Ann. Bot. 2014;114:1–16. doi: 10.1093/aob/mcu077. PubMed DOI PMC

Sulman BN, et al. Integrating arctic plant functional types in a land surface model using above- and belowground field observations. J. Adv. Modeling Earth Syst. 2021;13:e2020MS002396.

Berdanier AB. Global treeline position. Nat. Educ. Knowl. 2010;3:11.

Wilson, B. F. Shrub Stems: Form and Function. in Plant Stems. Physiology and Functional Morphology. 91–102 (Academic Press, 1995).

Kattge J, et al. TRY plant trait database – enhanced coverage and open access. Glob. Change Biol. 2020;26:119–188. doi: 10.1111/gcb.14904. PubMed DOI

Garnier E, et al. Towards a thesaurus of plant characteristics: an ecological contribution. J. Ecol. 2017;105:298–309. doi: 10.1111/1365-2745.12698. DOI

Bjorkman AD, et al. Tundra Trait Team: a database of plant traits spanning the tundra biome. Glob. Ecol. Biogeogr. 2018;27:1402–1411. doi: 10.1111/geb.12821. DOI

Myers-Smith IH, et al. Methods for measuring arctic and alpine shrub growth: a review. Earth-Sci. Rev. 2015;140:1–13. doi: 10.1016/j.earscirev.2014.10.004. DOI

Christensen, R. Advanced Linear Modeling: Statistical Learning and Dependent Data, 10.1007/978-3-030-29164-8 (Springer International Publishing, 2019).

Bürkner P-C. brms: An R Package for Bayesian multilevel models using Stan. J. Stat. Softw. 2017;80:1–28. doi: 10.18637/jss.v080.i01. DOI

Tamme R, et al. Predicting species’ maximum dispersal distances from simple plant traits. Ecology. 2014;95:505–513. doi: 10.1890/13-1000.1. PubMed DOI

Harrison XA, et al. A brief introduction to mixed effects modelling and multi-model inference in ecology. PeerJ. 2018;6:e4794. doi: 10.7717/peerj.4794. PubMed DOI PMC

Bolker BM, et al. Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS. Methods Ecol. Evol. 2013;4:501–512. doi: 10.1111/2041-210X.12044. DOI

Henry GHR, Molau U. Tundra plants and climate change: the International Tundra Experiment (ITEX) Glob. Change Biol. 1997;3:1–9. doi: 10.1111/j.1365-2486.1997.gcb132.x. DOI

Berends, M. S. et al. AMR - An R Package for Working with Antimicrobial Resistance Data. bioRxiv 810622, 10.1101/810622 (2021).

Oksanen, J. et al. Vegan: Community Ecology Package. R package version 2.5-7, https://CRAN.R-project.org/package=vegan (2020).

R Core Team. R: A language and environment for statistical computing (2020).

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