Journal Home > Volume 9 , Issue 6
Forest Ecosystems 2022, 9(6): 100077 https://doi.org/10.1016/j.fecs.2022.100077
Research Article | Open Access | Issue | Published: 05 December 2022

Mismatch between species distribution and climatic niche optima in relation to functional traits

Show Author's Information Zhenghua Liana,  Juan Wangb( ),  Chunyu Zhanga,  Xiuhai Zhaoa,  Klaus von Gadowc,d
Research Center of Forest Management Engineering of State Forestry and Grassland Administration, Beijing Forestry University, Beijing, 100083, China
Department of Forest Ecology, School of Ecology and Nature Conservation, Beijing Forestry University, Beijing, 100083, China
Faculty of Forestry and Forest Ecology, Georg-August-University Göttingen, Büsgenweg 5, D-37077, Göttingen, Germany
Department of Forest and Wood Science, University of Stellenbosch, Stellenbosch, 7600, South Africa
Keywords:
Demography, Functional traits, Species distribution, Mean annual temperature, Mean annual precipitation, Niche theory
Cite this article:
Lian Z, Wang J, Zhang C, et al. Mismatch between species distribution and climatic niche optima in relation to functional traits. Forest Ecosystems, 2022, 9(6): 100077. https://doi.org/10.1016/j.fecs.2022.100077
Download citation
EndNote(RIS)
BibTeX

437

Views

21

Downloads

Citations

0

Crossref

0

WoS

0

Scopus

0

CSCD

Abstract Full text About this article
Background

Forecasts of climate change impacts on biodiversity often assume that the current geographical distributions of species match their niche optima. However, empirical evidence has challenged this assumption, suggesting a mismatch. We examine whether the mismatch is related to functional traits along temperature or precipitation gradients.

Methods

The observed distributions of 32 tree species in northeast China were evaluated to test this mismatch. Bayesian models were used to estimate the climatic niche optima, i.e. the habitats where the highest species growth and density can be expected. The mismatch is defined as the difference between the actual species occurrence in an assumed niche optimum and the habitat with the highest probability of species occurrence. Species' functional traits were used to explore the mechanisms that may have caused the mismatches.

Results

Contrasting these climatic niche optima with the observed species distributions, we found that the distribution-niche optima mismatch had high variability among species based on temperature and precipitation gradients. However, these mismatches depended on functional traits associated with competition and migration lags only in temperature gradients.

Conclusions

We conclude that more relevant research is needed in the future to quantify the mismatch between species distribution and climatic niche optima, which may be crucial for future designs of forested landscapes, species conservation and dynamic forecasting of biodiversity under expected climate change.


menu
Abstract
Full text
Outline
About this article

Mismatch between species distribution and climatic niche optima in relation to functional traits

Show Author's information Zhenghua Liana, Juan Wangb( ), Chunyu Zhanga, Xiuhai Zhaoa, Klaus von Gadowc,d
Research Center of Forest Management Engineering of State Forestry and Grassland Administration, Beijing Forestry University, Beijing, 100083, China
Department of Forest Ecology, School of Ecology and Nature Conservation, Beijing Forestry University, Beijing, 100083, China
Faculty of Forestry and Forest Ecology, Georg-August-University Göttingen, Büsgenweg 5, D-37077, Göttingen, Germany
Department of Forest and Wood Science, University of Stellenbosch, Stellenbosch, 7600, South Africa

Abstract

Background

Forecasts of climate change impacts on biodiversity often assume that the current geographical distributions of species match their niche optima. However, empirical evidence has challenged this assumption, suggesting a mismatch. We examine whether the mismatch is related to functional traits along temperature or precipitation gradients.

Methods

The observed distributions of 32 tree species in northeast China were evaluated to test this mismatch. Bayesian models were used to estimate the climatic niche optima, i.e. the habitats where the highest species growth and density can be expected. The mismatch is defined as the difference between the actual species occurrence in an assumed niche optimum and the habitat with the highest probability of species occurrence. Species' functional traits were used to explore the mechanisms that may have caused the mismatches.

Results

Contrasting these climatic niche optima with the observed species distributions, we found that the distribution-niche optima mismatch had high variability among species based on temperature and precipitation gradients. However, these mismatches depended on functional traits associated with competition and migration lags only in temperature gradients.

Conclusions

We conclude that more relevant research is needed in the future to quantify the mismatch between species distribution and climatic niche optima, which may be crucial for future designs of forested landscapes, species conservation and dynamic forecasting of biodiversity under expected climate change.

Keywords: Demography, Functional traits, Species distribution, Mean annual temperature, Mean annual precipitation, Niche theory

References(78)

AllenC.D.MacaladyA.K.ChenchouniH.BacheletD.McDowellN.VennetierM.KitzbergerT.RiglingA.BreshearsD.D.HoggE.H.T.GonzálezP.FenshamR.ZhangZ.CastroJ.DemidovaN.LimJ.AllardG.RunningS.W.SemerciA.CobbN.A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forestsFor. Ecol. Manag.201025966068410.1016/j.foreco.2009.09.001

Allen, C.D., Macalady, A.K., Chenchouni, H., Bachelet, D., McDowell, N., Vennetier, M., Kitzberger, T., Rigling, A., Breshears, D.D., Hogg, E.H.T., González, P., Fensham, R., Zhang, Z., Castro, J., Demidova, N., Lim, J., Allard, G., Running, S.W., Semerci, A., Cobb, N., 2010. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. Forest Ecol. Manag. 259, 660-684. https://doi.org/10.1016/j.foreco.2009.09.001.
DOI Google Scholar

Amano, T., Székely, T., Sandel, B., Nagy, S., Mundkur, T., Langendoen, T., Blanco, D., Soykan, C.U., Sutherland, W.J., 2018. Successful conservation of global waterbird populations depends on effective governance. Nature 553, 199-202. https://doi.org/10.1038/nature25139.
DOI Google Scholar

Ayres, M.P., Lombardero, M.J., 2000. Assessing the consequences of global change for forest disturbance from herbivores and pathogens. Sci. Total Environ. 262, 263-286. https://doi.org/10.1016/s0048-9697(00)00528-3.
DOI Google Scholar
Batjes, N.H., 2015. World soil property estimates for broad-scale modelling (wise30sec). Report 2015/01, ISRIC - World Soil Information, Wageningen. https://www.isric.org (Accessed 01 August 2022).

Bell, D.M., Pabst, R.J., Shaw, D.C., 2020. Tree growth declines and mortality were associated with a parasitic plant during warm and dry climatic conditions in a temperate coniferous forest ecosystem. Global Change Biol. 26, 1714-1724. https://doi.org/10.1111/gcb.14834.
DOI Google Scholar

Bohner, T., Diez, J., 2020. Extensive mismatches between species distributions and performance and their relationship to functional traits. Ecol. Lett. 23, 33-44. https://doi.org/10.1111/ele.13396.
DOI Google Scholar

Brown, J.H., 1984. On the relationship between abundance and distribution of species. Am. Nat. 124, 255-279. https://doi.org/10.1086/284267.
DOI Google Scholar
BürknerP.brms: an r package for bayesian multilevel models using stanJ. Stat. Software20178012810.18637/jss.v080.i01

Bürkner, P., 2017. brms: An r package for bayesian multilevel models using stan. J. Stat. Softw. 80, 1-28. https://doi.org/10.18637/jss.v080.i01.
DOI Google Scholar

Camarero, J.J., Gazol, A., Sangüesa-Barreda, G., Vergarechea, M., Alfaro-Sánchez, R., Cattaneo, N., Vicente-Serrano, S.M., 2021. Tree growth is more limited by drought in rear-edge forests most of the times. For. Ecosyst. 8, 25. https://doi.org/10.1186/s40663-021-00303-1.
DOI Google Scholar

Canham, C.D., Murphy, L., 2016a. The demography of tree species response to climate: sapling and canopy tree growth. Ecosphere 7. https://doi.org/10.1002/ecs2.1474.
DOI Google Scholar

Canham, C.D., Murphy, L., 2016b. The demography of tree species response to climate: seedling recruitment and survival. Ecosphere 7. https://doi.org/10.1002/ecs2.1424.
DOI Google Scholar

Chave, J., Coomes, D., Jansen, S., Lewis, S.L., Swenson, N.G., Zanne, A.E., 2009. Towards a worldwide wood economics spectrum. Ecol. Lett. 12, 351-366. https://doi.org/10.1111/j.1461-0248.2009.01285.x.
DOI Google Scholar

Csergő, A.M., Salguero Gómez, R., Broennimann, O., Coutts, S.R., Guisan, A., Angert, A.L., Welk, E., Stott, I., Enquist, B.J., McGill, B., Svenning, J.C., Violle, C., Buckley, Y.M., 2017. Less favourable climates constrain demographic strategies in plants. Ecol. Lett. 20, 969-980. https://doi.org/10.1111/ele.12794.
DOI Google Scholar

Dallas, T., Decker, R.R., Hastings, A., 2017. Species are not most abundant in the centre of their geographic range or climatic niche. Ecol. Lett. 20, 1526-1533. https://doi.org/10.1111/ele.12860.
DOI Google Scholar

Davis, S.D., Ewers, F.W., Sperry, J.S., Portwood, K.A., Crocker, M.C., Adams, G.C., 2002. Shoot dieback during prolonged drought in Ceanothus (Rhamnaceae) chaparral of California: a possible case of hydraulic failure. Am. J. Bot. 89, 820-828. https://doi.org/10.3732/ajb.89.5.820.
DOI Google Scholar
DavisonR.JacquemynH.AdriaensD.HonnayO.De KroonH.TuljapurkarS.Demographic effects of extreme weather events on a short-lived calcareous grassland species: stochastic life table response experimentsJ. Ecol.20109825526710.1111/j.1365-2745.2009.01611.x

Davison, R., Jacquemyn, H., Adriaens, D., Honnay, O., De Kroon, H., Tuljapurkar, S., 2010. Demographic effects of extreme weather events on a short-lived calcareous grassland species: stochastic life table response experiments. J. Ecol. 98, 255-267. https://doi.org/10.1111/j.1365-2745.2009.01611.x.
DOI Google Scholar
DiezJ.M.GiladiI.WarrenR.PulliamH.R.Probabilistic and spatially variable niches inferred from demographyJ. Ecol.201410254455410.1111/1365-2745.12215

Diez, J.M., Giladi, I., Warren, R., Pulliam, H.R., 2014. Probabilistic and spatially variable niches inferred from demography. J. Ecol. 102, 544-554. https://doi.org/10.1111/1365-2745.12215.
DOI Google Scholar

Ding, Y., Dai, X., 1994. Temperature variation in China during the last 100 years. Meteorol. Month. 19-26.
DOI Google Scholar

Doak, D.F., Morris, W.F., 2010. Demographic compensation and tipping points in climate-induced range shifts. Nature 467, 959-962. https://doi.org/10.1038/nature09439.
DOI Google Scholar

Ehrlén, J., Morris, W.F., 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.
DOI Google Scholar

Evans, M., Merow, C., Record, S., McMahon, S.M., Enquist, B.J., 2016. Towards process-based range modeling of many species. Trends Ecol. Evol., 860-871. https://doi.org/10.1016/j.tree.2016.08.005.
DOI Google Scholar

Faurby, S., Araújo, M.B., 2018. Anthropogenic range contractions bias species climate change forecasts. Nat. Clim. Change 8, 252-256. https://doi.org/10.1038/s41558-018-0089-x.
DOI Google Scholar

Fick, S.E., Hijmans, R.J., 2017. WorldClim 2: new 1-m spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37. https://doi.org/10.1002/joc.5086.
DOI Google Scholar
Gadow, K.V., González, J., Zhang, C., Pukkala, T., Zhao, X., 2021. Sustaining Forest Ecosystems. Vol. 37. in: Tóme, M., Seifert, T., Kurttila, M. (eds.) Managing Forest Ecosystems. Springer. p. 429. https://doi.org/10.1007/978-3-030-58714-7.
DOI

Gea-Izquierdo, G., Natalini, F., Cardillo, E., 2021. Holm oak death is accelerated but not sudden and expresses drought legacies. Sci. Total Environ. 754, 141793. https://doi.org/10.1016/j.scitotenv.2020.141793.
DOI Google Scholar

Habibullah, M.S., Din, B.H., Tan, S., Zahid, H., 2022. Impact of climate change on biodiversity loss: global evidence. Environ. Sci. Pollut. R. 29, 1073-1086. https://doi.org/10.1007/s11356-021-15702-8.
DOI Google Scholar

Hacke, U.G., Sperry, J.S., Pockman, W.T., Davis, S.D., McCulloh, K.A., 2001. Trends in wood density and structure are linked to prevention of xylem implosion by negative pressure. Oecologia 126, 457-461. https://doi.org/10.1007/s004420100628.
DOI Google Scholar

Hanba, Y.T., Naohiko, N., Kiyoshi, U., 2000. Relationship between leaf characteristics, tree sizes and species distribution along a slope in a warm temperate forest. Ecol. Res. 15, 393-403. https://doi.org/10.1046/j.1440-1703.2000.00360.x.
DOI Google Scholar

Hoffmann, W.A., Marchin, R.M., Abit, P., Lau, O.L., 2011. Hydraulic failure and tree dieback are associated with high wood density in a temperate forest under extreme drought. Global Change Biol. 17, 2731-2742. https://doi.org/10.1111/j.1365-2486.2011.02401.x.
DOI Google Scholar

Holt, R.D., 2009. Bringing the Hutchinsonian niche into the 21st century: Ecological and evolutionary perspectives. PNAS 106, 19659-19665. https://doi.org/10.1073/pnas.0905137106.
DOI Google Scholar

Hutchinson, G.E., 1957. Concluding remarks. Cold Spring Harb. Symp. Quant. Biol 22, 415-427. https://doi.org/10.1101/SQB.1957.022.01.039.
DOI Google Scholar

Jacobsen, A.L., Pratt, R.B., Ewers, F.W., Davis, S.D., 2007. Cavitation resistance among 26 chaparral species of southern california. Ecol. Monogr. 77, 99-115. https://doi.org/10.1890/05-1879.
DOI Google Scholar

Jörn, P., Jörn, P., Frank, M.S., 2012. Forecasting species ranges by statistical estimation of ecological niches and spatial population dynamics. Global Ecol. Biogeogr. 21, 293-304. https://doi.org/10.1111/j.1466-8238.2011.00663.x.
DOI Google Scholar

Kattge, J., Bonisch, G., Díaz, S., Lavorel, S., Prentice, I.C., Leadley, P., Tautenhahn, S., Werner, G.D.A., Aakala, T., Abedi, M., Acosta, A.T.R., Adamidis, G.C., Adamson, K., Aiba, M., Albert, C.H., Alcántara, J.M., Alcázar C, C., Aleixo, I., Ali, H., Amiaud, B., Wirth, C., 2020. TRY plant trait database - enhanced coverage and open access. Global Change Biol. 26, 119-188. https://doi.org/10.1111/gcb.14904.
DOI Google Scholar

Klos, R.J., Wang, G.G., Bauerle, W.L., Rieck, J.R., 2009. Drought impact on forest growth and mortality in the southeast USA: an analysis using Forest Health and Monitoring data. Ecol. Appl. 19, 699-708. https://doi.org/10.1890/08-0330.1.
DOI Google Scholar
KunstlerG.GuyennonA.RatcliffeS.RügerN.Ruíz BenitoP.ChildsD.Z.DahlgrenJ.LehtonenA.ThuillerW.WirthC.ZavalaM.A.Salguero GomezR.Demographic performance of European tree species at their hot and cold climatic edgesJ. Ecol.20211091041105410.1111/1365-2745.13533

Kunstler, G., Guyennon, A., Ratcliffe, S., Rüger, N., Ruíz Benito, P., Childs, D.Z., Dahlgren, J., Lehtonen, A., Thuiller, W., Wirth, C., Zavala, M.A., Salguero Gomez, R., 2021. Demographic performance of European tree species at their hot and cold climatic edges. J. Ecol. 109, 1041-1054. https://doi.org/10.1111/1365-2745.13533.
DOI Google Scholar

Larcher, W., Bauer, H., 1981. Ecological significance of resistance to low temperature. Physiol. Plant Ecol. I, 403-437. https://doi.org/10.1007/978-3-642-68090-8_14.
DOI Google Scholar

Lian, Z., Wang, J., Fan, C., von Gadow, K., 2022. Structure complexity is the primary driver of functional diversity in the temperate forests of northeastern China. For Ecosyst 9, 100048. https://doi.org/10.1016/j.fecs.2022.100048.
DOI Google Scholar

Liu, X., Ma, K., 2015. Plant functional traits-concepts, applications and future directions. Sci. Sin. Vitae 45, 325-339. https://doi.org/10.1360/N052014-00244.
DOI Google Scholar
LoehleC.Height growth rate tradeoffs determine northern and southern range limits for treesJ. Biogeogr.19982573574210.1046/j.1365-2699.1998.2540735.x

Loehle, C., 1998. Height growth rate tradeoffs determine northern and southern range limits for trees. J. Biogeogr. 25, 735-742. https://doi.org/10.1046/j.1365-2699.1998.2540735.x.
DOI Google Scholar

Maguire, B., 1973. Niche response structure and the analytical potentials of its relationship to the habitat. Am. Nat. 107, 213-246. https://doi.org/10.1086/282827.
DOI Google Scholar
ManterD.K.ReeserP.W.StoneJ.K.A climate-based model for predicting geographic variation in swiss needle cast severity in the Oregon coast rangePhytopathology2005951256126510.1094/PHYTO-95-1256

Manter, D.K., Reeser, P.W., Stone, J.K., 2005. A climate-based model for predicting geographic variation in swiss needle cast severity in the Oregon coast range. Phytopathology 95, 1256-1265. https://doi.org/10.1094/PHYTO-95-1256.
DOI Google Scholar

Marshall, K.E., Baltzer, J.L., 2015. Decreased competitive interactions drive a reverse species richness latitudinal gradient in subarctic forests. Ecology 96, 461-470. https://doi.org/10.1890/14-0717.1.
DOI Google Scholar
McGillB.J.Trees are rarely most abundant where they grow bestJ. Plant Ecol.20125465110.1093/jpe/rtr036

McGill, B.J., 2012. Trees are rarely most abundant where they grow best. J. Plant Ecol 5, 46-51. https://doi.org/10.1093/jpe/rtr036.
DOI Google Scholar
MolesA.T.WartonD.I.WarmanL.SwensonN.G.LaffanS.W.ZanneA.E.PitmanA.HemmingsF.A.LeishmanM.R.Global patterns in plant heightJ. Ecol.20099792393210.1111/j.1365-2745.2009.01526.x

Moles, A.T., Warton, D.I., Warman, L., Swenson, N.G., Laffan, S.W., Zanne, A.E., Pitman, A., Hemmings, F.A., Leishman, M.R., 2009. Global patterns in plant height. J. Ecol. 97, 923-932. https://doi.org/10.1111/j.1365-2745.2009.01526.x.
DOI Google Scholar

Munné-Bosch, S., 2018. Limits to Tree Growth and Longevity. Trends Plant Sci. 23, 985-993. https://doi.org/10.1016/j.tplants.2018.08.001.
DOI Google Scholar

Nenzén, H.K., Swab, R.M., Keith, D.A., Araújo, M.B., 2012. demoniche - an R-package for simulating spatially-explicit population dynamics. Ecography 35, 577-580. https://doi.org/10.1111/j.1600-0587.2012.07378.x.
DOI Google Scholar
NicolèF.DahlgrenJ.P.VivatA.Till-BottraudI.EhrlénJ.Interdependent effects of habitat quality and climate on population growth of an endangered plantJ. Ecol.2011991211121810.1111/j.1365-2745.2011.01852.x

Nicolè, F., Dahlgren, J.P., Vivat, A., Till-Bottraud, I., Ehrlén, J., 2011. Interdependent effects of habitat quality and climate on population growth of an endangered plant. J. Ecol. 99, 1211-1218. https://doi.org/10.1111/j.1365-2745.2011.01852.x.
DOI Google Scholar

Orlandi, F., García-Mozo, H., Dhiab, A.B., Galán, C., Msallem, M., Romano, B., Abichou, M., Dominguez-Vilches, E., Fornaciari, M., 2013. Climatic indices in the interpretation of the phenological phases of the olive in mediterranean areas during its biological cycle. Clim. Change 116, 263-284. https://doi.org/10.1007/s10584-012-0474-9.
DOI Google Scholar

Pagel, J., Treurnicht, M., Bond, W.J., Kraaij, T., Schurr, F.M., 2020. Mismatches between demographic niches and geographic distributions are strongest in poorly dispersed and highly persistent plant species. PNAS 117, 201908684. https://doi.org/10.1073/pnas.1908684117/-/DCSupplemental.
DOI Google Scholar

Pearce-Higgins, J.W., Ockendon, N., Baker, D.J., Carr, J., White, E.C., Almond, R.E.A., Amano, T., Bertram, E., Bradbury, R.B., Bradley, C., Butchart, S.H.M., Doswald, N., Foden, W., Gill, D.J.C., Green, R.E., Sutherland, W.J., Tanner, E.V.J., 2015. Geographical variation in species' population responses to changes in temperature and precipitation. Proceed. Royal Soc. B Biol. Sci. 282, 20151561. https://doi.org/10.1098/rspb.2015.1561.
DOI Google Scholar

Peréz, S.V., Heikkinen, J., Salemaa, M., Makipaa, R., 2020. Global warming will affect the maximum potential abundance of boreal plant species. Ecography 43. https://doi.org/10.1111/ecog.04720.
DOI Google Scholar
PhilipS.LoehleC.Height growth rate tradeoffs determine northern and southern range limits for treesJ. Biogeogr.19982573574210.1046/j.1365-2699.1998.2540735.x

Philip, S., Loehle, C., 1998. Height growth rate tradeoffs determine northern and southern range limits for trees. J. Biogeogr. 25, 735-742. https://doi.org/10.1046/j.1365-2699.1998.2540735.x.
DOI Google Scholar

Pironon, S., Villellas, J., Thuiller, W., Eckhart, V.M., Geber, M.A., Moeller, D.A., García, M.B., 2018. The ‘Hutchinsonian niche’ as an assemblage of demographic niches: implications for species geographic ranges. Ecography 41, 1103-1113. https://doi.org/10.1111/ecog.03414.
DOI Google Scholar

Poorter, L., Wright, S.J., Paz, H., Ackerly, D.D., Condit, R., Ibarra-Manriquez, G., Harms, K.E., Licona, J.C., Martínez-Ramos, M., Mazer, S.J., Müller-Landau, H.C., Peña-Claros, M., Webb, C.O., Wright, I.J., 2008. Are functional traits good predictors of demographic rates? Evidence from five neotropical forests. Ecology 89, 1908-1920. https://doi.org/10.1890/07-0207.1.
DOI Google Scholar

Pulliam, H.R., 2000. On the relationship between niche and distribution. Ecol. Lett. 3, 349-361. https://doi.org/10.1046/j.1461-0248.2000.00143.x.
DOI Google Scholar
R Core Team, 2021. R: a Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.r-project.org/ (Accessed 01 August 2022).
Reed, D.H., 2012. Impact of Climate Change on Biodiversity. in: Chen, W., Seiner, J., Suzuki, T., Lackner, M. (Eds.), Handbook of Climate Change Mitigation. Springer-Verlag, New York, pp. 505-530. https://link.springer.com/referencework/10.1007/978-1-4419-7991-9 (Accessed 01 August 2022).
DOI

Rice, K.J., Matzner, S.L., Byer, W., Brown, J.R., 2004. Patterns of tree dieback in Queensland, Australia: the importance of drought stress and the role of resistance to cavitation. Oecologia 139, 190-198. https://doi.org/10.1111/ecog.04027.
DOI Google Scholar

Santini, L., Pironon, S., Maiorano, L., Thuiller, W., 2018. Addressing common pitfalls does not provide more support to geographical and ecological abundant-centre hypotheses. Ecography 19, 1043. https://doi.org/10.1111/ecog.04027.
DOI Google Scholar
SchurrF.M.PagelJ.CabralJ.S.GroeneveldJ.BykovaO.O HaraR.B.HartigF.KisslingW.D.LinderH.P.MidgleyG.F.SchröderB.SingerA.ZimmermannN.E.How to understand species niches and range dynamics: a demographic research agenda for biogeographyJ. Biogeogr.2012392146216210.1111/j.1365-2699.2012.02737.x

Schurr, F.M., Pagel, J., Cabral, J.S., Groeneveld, J., Bykova, O., O Hara, R.B., Hartig, F., Kissling, W.D., Linder, H.P., Midgley, G.F., Schröder, B., Singer, A., Zimmermann, N.E., 2012. How to understand species niches and range dynamics: a demographic research agenda for biogeography. J. Biogeogr. 39, 2146-2162. https://doi.org/10.1111/j.1365-2699.2012.02737.x.
DOI Google Scholar

Sintayehu, D.W., 2018. Impact of climate change on biodiversity and associated key ecosystem services in Africa: a systematic review. Ecosyst. Health Sust. 4, 225-239. https://doi.org/10.1080/20964129.2018.1530054.
DOI Google Scholar
SporbertM.KeilP.SeidlerG.BruelheideH.JandtU.AćićS.BiurrunI.CamposJ.A.ČarniA.ChytrýM.ĆušterevskaR.DenglerJ.GolubV.JansenF.KuzemkoA.LenoirJ.MarcenòC.MoeslundJ.E.Pérez-HaaseA.RūsiņaS.WelkE.Testing macroecological abundance patterns: the relationship between local abundance and range size, range position and climatic suitability among European vascular plantsJ. Biogeogr.2020472210222210.1111/jbi.13926

Sporbert, M., Keil, P., Seidler, G., Bruelheide, H., Jandt, U., Aćić, S., Biurrun, I., Campos, J.A., Čarni, A., Chytrý, M., Ćušterevska, R., Dengler, J., Golub, V., Jansen, F., Kuzemko, A., Lenoir, J., Marceno, C., Moeslund, J.E., Pérez-Haase, A., Rusina, S. Welk, E., 2020. Testing macroecological abundance patterns: The relationship between local abundance and range size, range position and climatic suitability among European vascular plants. J. Biogeogr. 47, 2210-2222. https://doi.org/10.1111/jbi.13926.
DOI Google Scholar

Sun, M., Tian, K., Zhang, Y., Wang, X., Guan, D., Yue, H., 2017. Research on leaf functional traits and their environmental adaptation. Plant Sci. J. 35, 940-949. https://doi.org/10.11913/PSJ.2095-0837.2017.60940.
DOI Google Scholar

Sun, S., He, C., Qiu, L., Li, C., Zhang, J., Meng, P., 2018. Stable isotope analysis reveals prolonged drought stress in poplar plantation mortality of the Three-North Shelter Forest in Northern China. Agr. Forest Meteorol. 252, 39-48. https://doi.org/10.1016/j.agrformet.2017.12.264.
DOI Google Scholar

Swenson, N.G., Enquist, B.J., 2007. Ecological and evolutionary determinants of a key plant functional trait: Wood density and its community-wide variation across latitude and elevation. Am. J. Bot. 94, 451-459. https://doi.org/10.3732/ajb.94.3.451.
DOI Google Scholar

Thuiller, W., Münkemüller, T., Schiffers, K.H., Georges, D., Dullinger, S., Eckhart, V.M., Edwards, T.C., Gravel, D., Kunstler, G., Merow, C., Moore, K., Piedallu, C., Vissault, S., Zimmermann, N.E., Zurell, D., Schurr, F.M., 2014. Does probability of occurrence relate to population dynamics? Ecography 37, 1155-1166. https://doi.org/10.1111/ecog.00836.
DOI Google Scholar

Toräng, P., Ehrlén, J., Agren, J., 2010. Linking environmental and demographic data to predict future population viability of a perennial herb. Oecologia 163, 99-109. https://doi.org/10.1007/s00442-009-1552-1.
DOI Google Scholar

Urban, M.C., Bocedi, G., Hendry, A.P., Mihoub, J.B., Er, G.P., Singer, A., Bridle, J.R., Crozier, L.G., Meester, L.D., Godsoe, W., 2016. Improving the forecast for biodiversity under climate change. Science 353. https://doi.org/10.1126/science.aad8466.
DOI Google Scholar

Villellas, J., Doak, D.F., García, M.B., Morris, W.F., 2015. Demographic compensation among populations: what is it, how does it arise and what are its implications? Ecol. Lett. 18, 1139-1152. https://doi.org/10.1111/ele.12505.
DOI Google Scholar

Violle, C., Navas, M., Vile, D., Kazakou, E., Fortunel, C., Hummel, I., Garnier, E., 2007. Let the concept of trait be functional! Oikos 116, 882-892. https://doi.org/10.1111/j.2007.0030-1299.15559.x.
DOI Google Scholar
WangZ.LiY.SuX.TaoS.FengX.WangQ.XuX.LiuY.MichaletzS.T.ShresthaN.LarjavaaraM.EnquistB.J.Patterns and ecological determinants of woody plant height in eastern Eurasia and its relation to primary productivityJ. Plant Ecol.20191279180310.1093/jpe/rtz025

Wang, Z., Li, Y., Su, X., Tao, S., Feng, X., Wang, Q., Xu, X., Liu, Y., Michaletz, S.T., Shrestha, N., Larjavaara, M., Enquist, B.J., 2019. Patterns and ecological determinants of woody plant height in eastern Eurasia and its relation to primary productivity. J. Plant Ecol. 12, 791-803. https://doi.org/10.1093/jpe/rtz025.
DOI Google Scholar

Wisheu, I.C., 1998. How organisms partition habitats: different types of community organization can produce identical patterns. Oikos 83, 246-258. https://doi.org/10.2307/3546836.
DOI Google Scholar

Woodward, F.I., 1990. The impact of low temperatures in controlling the geographical distribution of plants. Philos. Trans. R. Soc. Lond. B Biol. Sci. 326, 585-593. https://doi.org/10.1098/rstb.1990.0033.
DOI Google Scholar

Wright, I.J., Reich, P.B., Westoby, M., Ackerly, D.D., Baruch, Z., Bongers, F., Cavender-Bares, J., Chapin, T., Cornelissen, J.H.C., Diemer, M., 2004. The worldwide leaf economics spectrum. Nature 428, 821-827. https://doi.org/10.1038/nature02403.
DOI Google Scholar

Xu, K., Wang, X., Jiang, C., Sun, O.J., 2020. Assessing the vulnerability of ecosystems to climate change based on climate exposure, vegetation stability and productivity. For. Ecosyst. 7, 23. https://doi.org/10.1186/s40663-020-00239-y.
DOI Google Scholar

Yuan, Z., Ali, A., Wang, S., Gazol, A., Freckleton, R., Wang, X., Lin, F., Ye, J., Zhou, L., Hao, Z., Loreau, M., 2018. Abiotic and biotic determinants of coarse woody productivity in temperate mixed forests. Sci. Total Environ. 630, 422-431. https://doi.org/10.1016/j.scitotenv.2018.02.125.
DOI Google Scholar

Zurell, D., Thuiller, W., Pagel, J., Cabral, J.S., Zimmermann, N.E., 2016. Benchmarking novel approaches for modelling species range dynamics. Global Change Biol. 22, 2651-2664. https://doi.org/10.1111/gcb.13251.
DOI Google Scholar
Publication history
Copyright
Acknowledgements
Rights and permissions

Publication history

Received: 01 September 2022
Revised: 22 November 2022
Accepted: 29 November 2022
Published: 05 December 2022
Issue date: December 2022

Copyright

© 2022 The Authors.

Acknowledgements

Acknowledgements

This work was supported by the Key Project of National Key Research and Development Plan (No. 2022YFD2201004) and Beijing Forestry University Outstanding Young Talent Cultivation Project (No. 2019JQ03001). We are grateful to colleagues who surveyed data together.

Rights and permissions

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Return