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Research Article | Open Access

Current climate overrides past climate change in explaining multi-site beta diversity of Lauraceae species in China

Ziyan Liaoa,b,cYouhua ChenaKaiwen PanaMohammed A. DakhildKexin Lina,bXianglin TianeFengying ZhangaXiaogang WuaBikram PandeyaBin WangfNiklaus E. ZimmermanncLin Zhanga( )Michael P. Nobisc
CAS Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization & Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
University of Chinese Academy of Sciences, Beijing, 100039, China
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, CH-8903, Birmensdorf, Switzerland
Botany and Microbiology Department, Faculty of Science, Helwan University, Cairo, 11790, Egypt
Department of Forest Sciences, University of Helsinki, P.O. Box 27, Helsinki, FI-00014, Finland
Academy of Agriculture and Forestry, Qinghai University, Xining, 810016, China
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Abstract

Background

We aimed to characterise the geographical distribution of Sørensen-based multi-site dissimilarity (βsor) and its underlying true turnover (βsim) and nestedness (βsne) components for Chinese Lauraceae and to analyse their relationships to current climate and past climate change.

Methods

We used ensembles of small models (ESMs) to map the current distributions of 353 Lauraceae species in China and calculated βsor and its βsim and βsne components. We tested the relationship between βsor, βsne and βsim with current climate and past climate change related predictors using a series of simultaneous autoregressive (SARerr) models.

Results

Spatial distribution of βsor of Lauraceae is positively correlated with latitude, showing an inverse relationship to the latitudinal α-diversity (species richness) gradient. High βsor occurs at the boundaries of the warm temperate and subtropical zones and at the Qinghai-Tibet Plateau due to high βsne. The optimized SARerr model explains βsor and βsne well, but not βsim. Current mean annual temperature determines βsor and βsne of Lauraceae more than anomalies and velocities of temperature or precipitation since the Last Glacial Maximum.

Conclusions

Current low temperatures and high climatic heterogeneity are the main factors explaining the high multi-site β-diversity of Lauraceae. In contrast to analyses of the β-diversity of entire species assemblages, studies of single plant families can provide complementary insights into the drivers of β-diversity of evolutionarily more narrowly defined entities.

References

 

Alahuhta, J., Antikainen, H., Hjort, J., Helm, A., Heino, J., 2020. Current climate overrides historical effects on species richness and range size of freshwater plants in Europe and North America. J. Ecol. 108(4), 1262-1275. https://doi.org/10.1111/1365-2745.13356.

 

Anderson, M.J., Crist, T.O., Chase, J.M., Vellend, M., Inouye, B.D., Freestone, A.L., Sanders, N.J., Cornell, H.V., Comita, L.S., Davies, K.F., Harrison, S.P., Kraft, N.J.B., Stegen, J.C., Swenson, N.G., 2011. Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist. Ecol. Lett. 14(1), 19-28. https://doi.org/10.1111/j.1461-0248.2010.01552.x.

 

Baselga, A., 2010. Partitioning the turnover and nestedness components of beta diversity. Glob. Ecol. Biogeogr. 19(1), 134-143. https://doi.org/10.1111/j.1466-8238.2009.00490.x.

 

Baselga, A., 2013. Multiple site dissimilarity quantifies compositional heterogeneity among several sites, while average pairwise dissimilarity may be misleading. Ecography 36(2), 124-128. https://doi.org/10.1111/j.1600-0587.2012.00124.x.

 

Baselga, A., 2017. Partitioning abundance-based multiple-site dissimilarity into components: balanced variation in abundance and abundance gradients. Methods Ecol. Evol. 8(7), 799-808. https://doi.org/10.1111/2041-210X.12693.

 

Baselga, A., Orme, C.D.L., 2012. betapart : an R package for the study of beta diversity. Methods Ecol. Evol. 3(5), 808-812. https://doi.org/10.1111/j.2041-210X.2012.00224.x.

 

Bivand, R., Hauke, J., Kossowski, T., 2013. Computing the jacobian in Gaussian spatial autoregressive models: an illustrated comparison of available methods. Geogr. Anal. 45(2), 150-179. https://doi.org/10.1111/gean.12008.

 

Blonder, B., Enquist, B.J., Graae, B.J., Kattge, J., Maitner, B.S., Morueta-Holme, N., Ordonez, A., Šímová, I., Singarayer, J., Svenning, J., Valdes, P.J., Violle, C., 2018. Late Quaternary climate legacies in contemporary plant functional composition. Glob. Chang. Biol. 24(10), 4827-4840. https://doi.org/10.1111/gcb.14375.

 

Breiner, F.T., Guisan, A., Bergamini, A., Nobis, M.P., 2015. Overcoming limitations of modelling rare species by using ensembles of small models. Methods Ecol. Evol. 6(10), 1210-1218. https://doi.org/10.1111/2041-210X.12403.

 

Breiner, F.T., Nobis, M.P., Bergamini, A., Guisan, A., 2018. Optimizing ensembles of small models for predicting the distribution of species with few occurrences. Methods Ecol. Evol. 9(4), 802-808. https://doi.org/10.1111/2041-210X.12957.

 

Brown, J.L., 2014. SDMtoolbox: a python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses. Methods Ecol. Evol. 5(7), 694-700. https://doi.org/10.1111/2041-210X.12200.

 
Burnham, K.P., Anderson, D.R., 2002. Model selection and multimodel inference: a practical information-theoretic approach. Springer, New York.
 

Calatayud, J., Hortal, J., Medina, N.G., Turin, H., Bernard, R., Casale, A., Ortuño, V.M., Penev, L., Rodríguez, M.Á., 2016. Glaciations, deciduous forests, water availability and current geographical patterns in the diversity of European Carabus species. J. Biogeogr. 43(12), 2343-2353. https://doi.org/10.1111/jbi.12811.

 
Chamberlain, S., 2020. scrubr: Clean Biological Occurrence Records. R package version 0.1.1. https://cran.r-project.org/package=scrubr (accessed 15 July 2021).
 

Chen, Y., Schmera, D., 2015. Additive partitioning of a beta diversity index is controversial. Proc. Natl. Acad. Sci. 112(52), E7161. https://doi.org/10.1073/pnas.1521798113.

 

Chen, Y., Shen, T.J., Condit, R., Hubbell, S.P., 2018. Community-level species' correlated distribution can be scale-independent and related to the evenness of abundance. Ecology 99(12), 2787-2800. https://doi.org/10.1002/ecy.2544.

 

Condit, R., 2002. Beta-diversity in tropical forest trees. Science 295(5555), 666-669. https://doi.org/10.1126/science.1066854.

 

Dakhil, M.A., Li, J., Pandey, B., Pan, K., Liao, Z., Olatunji, O.A., Zhang, L., Eid, E.M., Abdelaal, M., 2021. Richness patterns of endemic and threatened conifers in south-west China: topographic-soil fertility explanation. Environ. Res. Lett. 16(3), 034017. https://doi.org/10.1088/1748-9326/abda6e.

 

Dauby, G., Stévart, T., Droissart, V., Cosiaux, A., Deblauwe, V., Simo-Droissart, M., Sosef, M.S.M., Lowry, P.P., Schatz, G.E., Gereau, R.E., Couvreur, T.L.P., 2017. ConR : an R package to assist large-scale multispecies preliminary conservation assessments using distribution data. Ecol. Evol. 7(24), 11292-11303. https://doi.org/10.1002/ece3.3704.

 

Di Cola, V., Broennimann, O., Petitpierre, B., Breiner, F.T., D'Amen, M., Randin, C., Engler, R., Pottier, J., Pio, D., Dubuis, A., Pellissier, L., Mateo, R.G., Hordijk, W., Salamin, N., Guisan, A., 2017. ecospat: an R package to support spatial analyses and modeling of species niches and distributions. Ecography 40(6), 774-787. https://doi.org/10.1111/ecog.02671.

 

Dobrovolski, R., Melo, A.S., Cassemiro, F.A.S., Diniz-Filho, J.A.F., 2012. Climatic history and dispersal ability explain the relative importance of turnover and nestedness components of beta diversity. Glob. Ecol. Biogeogr. 21(2), 191-197. https://doi.org/10.1111/j.1466-8238.2011.00671.x.

 

Dormann, C.F., McPherson, M.J., Araújo, M.B., Bivand, R., Bolliger, J., Carl, G., Davies, R.G., Hirzel, A., Jetz, W., Daniel Kissling, W., Kühn, I., Ohlemüller, R., Peres-Neto, P.R., Reineking, B., Schröder, B., Schurr, F.M., Wilson, R., 2007. Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography 30(5), 609-628. https://doi.org/10.1111/j.2007.0906-7590.05171.x.

 

Dormann, C.F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., Marquéz, J.R.G., Gruber, B., Lafourcade, B., Leitão, P.J., Münkemüller, T., McClean, C., Osborne, P.E., Reineking, B., Schröder, B., Skidmore, A.K., Zurell, D., Lautenbach, S., 2013. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36(1), 27-46. https://doi.org/10.1111/j.1600-0587.2012.07348.x.

 

Dynesius, M., Jansson, R., 2000. Evolutionary consequences of changes in species' geographical distributions driven by Milankovitch climate oscillations. Proc. Natl. Acad. Sci. 97(16), 9115-9120. https://doi.org/10.1073/pnas.97.16.9115.

 
Editorial Committee of Flora of China CAS, 1999. Flora of China, Vol. 4. Science Press, Beijing.
 
ESRI (Environmental Systems Research Institute), 2014. ArcGIS® Desktop Help 10.3 Geostatistical Analyst. https://desktop.arcgis.com/en/arcmap/10.3 (accessed 15 July 2021).
 

Feurdean, A., Bhagwat, S.A., Willis, K.J., Birks, H.J.B., Lischke, H., Hickler, T., 2013. Tree migration-rates: narrowing the gap between inferred Post-Glacial rates and projected rates. PLoS One 8(8), e71797. https://doi.org/10.1371/journal.pone.0071797.

 

Fick, S.E., Hijmans, R.J., 2017. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37(12), 4302-4315. https://doi.org/10.1002/joc.5086.

 

Francis, A.P., Currie, D.J., 2003. A globally consistent richness-climate relationship for angiosperms. Am. Nat. 161(4), 523-536. https://doi.org/10.1086/368223.

 

Fuller, R.A., McDonald-Madden, E., Wilson, K.A., Carwardine, J., Grantham, H.S., Watson, J.E.M., Klein, C.J., Green, D.C., Possingham, H.P., 2010. Replacing underperforming protected areas achieves better conservation outcomes. Nature 466(7304), 365-367. https://doi.org/10.1038/nature09180.

 

Gaston, K.J., 2000. Global patterns in biodiversity. Nature 405(6783), 220-227. https://doi.org/10.1038/35012228.

 

Gaston, K.J., Davies, R.G., Orme, C.D.L., Olson, V.A., Thomas, G.H., Ding, T.S., Rasmussen, P.C., Lennon, J.J., Bennett, P.M., Owens, I.P.F., Blackburn, T.M., 2007. Spatial turnover in the global avifauna. Proc. R. Soc. B Biol. Sci. 274(1618), 1567-1574. https://doi.org/10.1098/rspb.2007.0236.

 

Ge, J., Berg, B., Xie, Z., 2019. Climatic seasonality is linked to the occurrence of the mixed evergreen and deciduous broad-leaved forests in China. Ecosphere 10(9), e02862. https://doi.org/10.1002/ecs2.2862.

 

Gray, C.L., Hill, S.L.L., Newbold, T., Hudson, L.N., Borger, L., Contu, S., Hoskins, A.J., Ferrier, S., Purvis, A., Scharlemann, J.P.W., 2016. Local biodiversity is higher inside than outside terrestrial protected areas worldwide. Nat. Commun. 7(1), 12306. https://doi.org/10.1038/ncomms12306.

 
Guisan, A., Thuiller, W., Zimmermann, N.E., 2017. Habitat suitability and distribution models: with applications in R. Cambridge University Press, Cambridge, UK.
 

Hamann, A., Roberts, D.R., Barber, Q.E., Carroll, C., Nielsen, S.E., 2015. Velocity of climate change algorithms for guiding conservation and management. Glob. Chang. Biol. 21(2), 997-1004. https://doi.org/10.1111/gcb.12736.

 

Hanski, I., 2015. Habitat fragmentation and species richness. J. Biogeogr. 42(5), 989-993. https://doi.org/10.1111/jbi.12478.

 

Harrison, S.P., Yu, G., Takahara, H., Prentice, I.C., 2001. Diversity of temperate plants in east Asia. Nature 413(6852), 129-130. https://doi.org/10.1038/35093166.

 

He, J., Lin, S., Kong, F., Yu, J., Zhu, H., Jiang, H., 2020. Determinants of the beta diversity of tree species in tropical forests: implications for biodiversity conservation. Sci. Total Environ. 704, 135301. https://doi.org/10.1016/j.scitotenv.2019.135301.

 

Hengl, T., de Jesus, J.M., MacMillan, R.A., Batjes, N.H., Heuvelink, G.B.M., Ribeiro, E., Samuel-Rosa, A., Kempen, B., Leenaars, J.G.B., Walsh, M.G., Gonzalez, M.R., 2014. SoilGrids1km - Global soil information based on automated mapping. PLoS One 9(8), e105992. https://doi.org/10.1371/journal.pone.0105992.

 

Herzschuh, U., 2020. Legacy of the Last Glacial on the present-day distribution of deciduous versus evergreen boreal forests. Glob. Ecol. Biogeogr. 29(2), 198-206. https://doi.org/10.1111/geb.13018.

 
Hijmans, R.J., 2020. raster: Geographic data analysis and modelling. R Package Version 3.4-5. http://CRAN.R-project.org/package=raster (accessed 15 July 2021).
 

Jansson, R., 2003. Global patterns in endemism explained by past climatic change. Proc. R. Soc. London Ser. B Biol. Sci. 270(1515), 583-590. https://doi.org/10.1098/rspb.2002.2283.

 

Keil, P., Chase, J.M., 2019. Global patterns and drivers of tree diversity integrated across a continuum of spatial grains. Nat. Ecol. Evol. 3(3), 390-399. https://doi.org/10.1038/s41559-019-0799-0.

 

Kissling, W.D., Carl, G., 2008. Spatial autocorrelation and the selection of simultaneous autoregressive models. Glob. Ecol. Biogeogr. 17(1), 59-71. https://doi.org/10.1111/j.1466-8238.2007.00334.x.

 

Kraft, N.J.B., Comita, L.S., Chase, J.M., Sanders, N.J., Swenson, N.G., Crist, T.O., Stegen, J.C., Vellend, M., Boyle, B., Anderson, M.J., Cornell, H.V., Davies, K.F., Freestone, A.L., Inouye, B.D., Harrison, S.P., Myers, J.A., 2011. Disentangling the drivers of β diversity along latitudinal and elevational gradients. Science 333(6050), 1755-1758. https://doi.org/10.1126/science.1208584.

 

Kremen, C., Cameron, A., Moilanen, A., Phillips, S.J., Thomas, C.D., Beentje, H., Dransfield, J., Fisher, B.L., Glaw, F., Good, T.C., Harper, G.J., Hijmans, R.J., Lees, D.C., Louis, E., Nussbaum, R.A., Raxworthy, C.J., Razafimpahanana, A., Schatz, G.E., Vences, M., Vieites, D.R., Wright, P.C., Zjhra, M.L., 2008. Aligning conservation priorities across taxa in Madagascar with high-resolution planning tools. Science 320(5873), 222-226. https://doi.org/10.1126/science.1155193.

 

Kuhn, I., Nobis, M.P., Durka, W., 2009. Combining spatial and phylogenetic eigenvector filtering in trait analysis. Glob. Ecol. Biogeogr. 18(6), 745-758. https://doi.org/10.1111/j.1466-8238.2009.00481.x.

 

Legendre, P., Mi, X., Ren, H., Ma, K., Yu, M., Sun, I.F., He, F., 2009. Partitioning beta diversity in a subtropical broad-leaved forest of China. Ecology 90(3), 663-674. https://doi.org/10.1890/07-1880.1.

 

Leprieur, F., Tedesco, P.A., Hugueny, B., Beauchard, O., Dürr, H.H., Brosse, S., Oberdorff, T., 2011. Partitioning global patterns of freshwater fish beta diversity reveals contrasting signatures of past climate changes. Ecol. Lett. 14(4), 325-334. https://doi.org/10.1111/j.1461-0248.2011.01589.x.

 

Li, R., Kraft, N.J.B., Yang, J., Wang, Y., 2015. A phylogenetically informed delineation of floristic regions within a biodiversity hotspot in Yunnan, China. Sci. Rep. 5(1), 9396. https://doi.org/10.1038/srep09396.

 

Liao, Z., Zhang, L., Nobis, M.P., Wu, X., Pan, K., Wang, K., Dakhil, M.A., Du, M., Xiong, Q., Pandey, B., Tian, X., 2020. Climate change jointly with migration ability affect future range shifts of dominant fir species in Southwest China. Divers. Distrib. 26(3), 352-367. https://doi.org/10.1111/ddi.13018.

 

Liao, Z., Nobis, M.P., Xiong, Q., Tian, X., Wu, X., Pan, K., Zhang, A., Wang, Y., Zhang, L., 2021. Potential distributions of seven sympatric sclerophyllous oak species in Southwest China depend on climatic, non-climatic, and independent spatial drivers. Ann. For. Sci. 78(1), 5. https://doi.org/10.1007/s13595-020-01012-5.

 

Liu, C., White, M., Newell, G., 2013. Selecting thresholds for the prediction of species occurrence with presence-only data. J. Biogeogr. 40(4), 778-789. https://doi.org/10.1111/jbi.12058.

 

Liu, Y., Su, X., Shrestha, N., Xu, X., Wang, S., Li, Y., Wang, Q., Sandanov, D., Wang, Z., 2019. Effects of contemporary environment and Quaternary climate change on drylands plant diversity differ between growth forms. Ecography 42(2), 334-345. https://doi.org/10.1111/ecog.03698.

 

Loarie, S.R., Duffy, P.B., Hamilton, H., Asner, G.P., Field, C.B., Ackerly, D.D., 2009. The velocity of climate change. Nature 462(7276), 1052-1055. https://doi.org/10.1038/nature08649.

 

MacDougall, A.S., McCann, K.S., Gellner, G., Turkington, R., 2013. Diversity loss with persistent human disturbance increases vulnerability to ecosystem collapse. Nature 494(7435), 86-89. https://doi.org/10.1038/nature11869.

 

McFadden, I.R., Sandel, B., Tsirogiannis, C., Morueta-Holme, N., Svenning, J.C., Enquist, B.J., Kraft, N.J.B., 2019. Temperature shapes opposing latitudinal gradients of plant taxonomic and phylogenetic β diversity. Ecol. Lett. 22(7), 1126-1135. https://doi.org/10.1111/ele.13269.

 

McKnight, M.W., White, P.S., McDonald, R.I., Lamoreux, J.F., Sechrest, W., Ridgely, R.S., Stuart, S.N., 2007. Putting beta-diversity on the map: broad-scale congruence and coincidence in the extremes. PLoS Biol. 5(10), 2424-2432. https://doi.org/10.1371/journal.pbio.0050272.

 

Melo, A.S., Rangel, T.F.L.V.B., Diniz-Filho, J.A.F., 2009. Environmental drivers of beta-diversity patterns in New-World birds and mammals. Ecography 32(2), 226-236. https://doi.org/10.1111/j.1600-0587.2008.05502.x.

 

Menéndez-Guerrero, P.A., Green, D.M., Davies, T.J., 2020. Climate change and the future restructuring of Neotropical anuran biodiversity. Ecography 43(2), 222-235. https://doi.org/10.1111/ecog.04510.

 

Mittelbach, G.G, Schemske, D.W., Cornell, H.V., Allen, A.P., Brown, J.M., Bush, M.B., Harrison, S.P., Hurlbert, A.H., Knowlton, N., Lessios, H.A., McCain, C.M., McCune, A.R., McDade, L.A., McPeek, M.A., Near, T.J., Price, T.D., Ricklefs, R.E., Roy, K., Sax, D.F., Schluter, D., Sobel, J.M., Turelli, M., 2007. Evolution and the latitudinal diversity gradient: speciation, extinction and biogeography. Ecol. Lett. 10(4), 315-331. https://doi.org/10.1111/j.1461-0248.2007.01020.x.

 

Moreno-Amat, E., Mateo, R.G., Nieto-Lugilde, D., Morueta-Holme, N., Svenning, J.C., Garcia-Amorena, I., 2015. Impact of model complexity on cross-temporal transferability in Maxent species distribution models: an assessment using paleobotanical data. Ecol. Model. 312, 308-317. https://doi.org/10.1016/j.ecolmodel.2015.05.035.

 
Naimi, B., 2017. usdm: Uncertainty analysis for species distribution models. R package version 1.1-18. https://CRAN.R-project.org/package=usdm (accessed 15 July 2021).
 

Ni, J., Yu, G., Harrison, S.P., Prentice, I.C., 2010. Palaeovegetation in China during the late Quaternary: biome reconstructions based on a global scheme of plant functional types. Palaeogeogr. Palaeocl. 289(1-4), 44-61. https://doi.org/10.1016/j.palaeo.2010.02.008.

 

Nobis, M.P., Jaeger, J.A.G., Zimmermann, N.E., 2009. Neophyte species richness at the landscape scale under urban sprawl and climate warming. Divers. Distrib. 15(6), 928-939. https://doi.org/10.1111/j.1472-4642.2009.00610.x.

 

Ordonez, A., Svenning, J-C., 2017. Consistent role of Quaternary climate change in shaping current plant functional diversity patterns across European plant orders. Sci. Rep. 7(1), 42988. https://doi.org/10.1038/srep42988.

 

Peterson, A.T., Navarro-Sigüenza, A.G., Gordillo, A., 2018. Assumption-versus data-based approaches to summarizing species' ranges. Conserv. Biol. 32(3), 568-575. https://doi.org/10.1111/cobi.12801.

 

Phillips, S.J., Dudík, M., Elith, J., Graham, C.H., Lehmann, A., Leathwick, J., Ferrier, S., 2009. Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecol. Appl. 19(1), 181-197. https://doi.org/10.1890/07-2153.1.

 

Pinto-Ledezma, J.N., Larkin, D.J., Cavender-Bares, J., 2018. Patterns of beta diversity of vascular plants and their correspondence with biome boundaries across North America. Front. Ecol. Evol. 6(11), 194. https://doi.org/10.3389/fevo.2018.00194.

 

Podani, J., Schmera, D., 2011. A new conceptual and methodological framework for exploring and explaining pattern in presence -absence data. Oikos 120(11), 1625-1638. https://doi.org/10.1111/j.1600-0706.2011.19451.x.

 

Qian, H., Ricklefs, R.E., 2007. A latitudinal gradient in large-scale beta diversity for vascular plants in North America. Ecol. Lett. 10(8), 737-744. https://doi.org/10.1111/j.1461-0248.2007.01066.x.

 

Qian, H., Ricklefs, R.E, White, P.S., 2005. Beta diversity of angiosperms in temperate floras of eastern Asia and eastern North America. Ecol. Lett. 8(1), 15-22. https://doi.org/10.1111/j.1461-0248.2004.00682.x.

 

Qian, H., Jin, Y., Leprieur, F., Wang, X., Deng, T., 2020. Geographic patterns and environmental correlates of taxonomic and phylogenetic beta diversity for large-scale angiosperm assemblages in China. Ecography 43(11), 1706-1716. https://doi.org/10.1111/ecog.05190.

 

Qiu, Y.X., Fu, C.X., Comes, H.P., 2011. Plant molecular phylogeography in China and adjacent regions: tracing the genetic imprints of Quaternary climate and environmental change in the world's most diverse temperate flora. Mol. Phylogenet. Evol. 59(1), 225-244. https://doi.org/10.1016/j.ympev.2011.01.012.

 
R-Core-Team., 2020. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
 

Rahbek, C., 2005. The role of spatial scale and the perception of large-scale species-richness patterns. Ecol. Lett. 8(2), 224-239. https://doi.org/10.1111/j.1461-0248.2004.00701.x.

 

Ren, Z., Peng, H., Liu, Z.W., 2016. The rapid climate change-caused dichotomy on subtropical evergreen broad-leaved forest in Yunnan: reduction in habitat diversity and increase in species diversity. Plant Divers. 38(3), 142-148. https://doi.org/10.1016/j.pld.2016.04.003.

 

Righetti, D., Vogt, M., Gruber, N., Psomas, A., Zimmermann, N.E., 2019. Global pattern of phytoplankton diversity driven by temperature and environmental variability. Sci. Adv. 5(5), eaau6253. https://doi.org/10.1126/sciadv.aau6253.

 
Rohwer, J.G., 1993. Lauraceae, in: Kubitzki, K., Rohwer, J.G., Bittrich, V. (Eds. ), Flowering plants dicotyledons. The Families and Genera of Vascular Plants, vol 2. Springer, Berlin, Heidelberg.
 

Saladin, B., Pellissier, L., Graham, C.H., Nobis, M.P., Salamin, N., Zimmermann, N.E., 2020. Rapid climate change results in long-lasting spatial homogenization of phylogenetic diversity. Nat. Commun. 11(1), 4663. https://doi.org/10.1038/s41467-020-18343-6.

 

Sandel, B., Arge, L., Dalsgaard, B., Davies, R.G., Gaston, K.J., Sutherland, W.J., Svenning, J.C., 2011. The influence of late quaternary climate-change velocity on species endemism. Science 334(6056), 660-664. https://doi.org/10.1126/science.1210173.

 

Scherrer, D., Christe, P., Guisan, A., 2019. Modelling bat distributions and diversity in a mountain landscape using focal predictors in ensemble of small models. Divers. Distrib. 25(5), 770-782. https://doi.org/10.1111/ddi.12893.

 

Schluter, D., Pennell, M.W., 2017. Speciation gradients and the distribution of biodiversity. Nature 546(7656), 48-55. https://doi.org/10.1038/nature22897.

 

Schmera, D., Podani, J., Legendre, P., 2020. What do beta diversity components reveal from presence-absence community data? Let us connect every indicator to an indicandum! Ecol. Indic. 117, 106540. https://doi.org/10.1016/j.ecolind.2020.106540.

 

Sheldon, K.S., Yang, S., Tewksbury, J.J., 2011. Climate change and community disassembly: impacts of warming on tropical and temperate montane community structure. Ecol. Lett. 14(12), 1191-1200. https://doi.org/10.1111/j.1461-0248.2011.01689.x.

 

Shrestha, N., Su, X., Xu, X., Wang, Z., 2018. The drivers of high Rhododendron diversity in south-west China: does seasonality matter? J. Biogeogr. 45(2), 438-447. https://doi.org/10.1111/jbi.13136.

 

Socolar, J.B., Gilroy, J.J., Kunin, W.E., Edwards, D.P., 2016. How should beta-diversity inform biodiversity conservation? Trends Ecol. Evol. 31(1), 67-80. https://doi.org/10.1016/j.tree.2015.11.005.

 

Soininen, J., Heino, J., Wang, J., 2018. A meta-analysis of nestedness and turnover components of beta diversity across organisms and ecosystems. Glob. Ecol. Biogeogr. 27(1), 96-109. https://doi.org/10.1111/geb.12660.

 
Song, Y., 2014. Evergreen broad-leaved forests in china: classification-ecology-conservation (Tables). Science Press, Beijing.
 

Song, Y., Yu, W., Tan, Y., Jin, J., Wang, B., Yang, J., Liu, B., Corlett, R.T., 2020. Plastid phylogenomics improve phylogenetic resolution in the Lauraceae. J. Syst. Evol. 58(4), 423-439. https://doi.org/10.1111/jse.12536.

 

Sreekar, R., Katabuchi, M., Nakamura, A., Corlett, R.T., Slik, J.W.F., Fletcher, C., He, F., Weiblen, G.D., Shen, G., Xu, H., Sun, I-F., Cao, K., Ma, K., Chang, L-W., Cao, M., Jiang, M., Gunatilleke, I.A.U.N., Ong, P., Yap, S., Gunatilleke, C.V.S., Novotny, V., Brockelman, W.Y., Xiang, W., Mi, X., Li, X., Wang, X., Qiao, X., Li, Y., Tan, S., Condit, R., Harrison, R.D., Koh, L.P., 2018. Spatial scale changes the relationship between beta diversity, species richness and latitude. Roy. Soc. Open Sci. 5(9), 181168. https://doi.org/10.1098/rsos.181168.

 

Subba, B., Sen, S., Ravikanth, G., Nobis, M.P., 2018. Direct modelling of limited migration improves projected distributions of Himalayan amphibians under climate change. Biol. Conserv. 227(5), 352-360. https://doi.org/10.1016/j.biocon.2018.09.035.

 

Svenning, J-C., Skov, F., 2007. Could the tree diversity pattern in Europe be generated by postglacial dispersal limitation? Ecol. Lett. 10(6), 453-460. https://doi.org/10.1111/j.1461-0248.2007.01038.x.

 

Tanaka, K.R., Torre, M.P., Saba, V.S., Stock, C.A., Chen, Y., 2020. An ensemble high-resolution projection of changes in the future habitat of American lobster and sea scallop in the Northeast US continental shelf. Divers. Distrib. 26(8), 987-1001. https://doi.org/10.1111/ddi.13069.

 

Ter Steege, H., Jansen-Jacobs, M.J., Datadin, V.K., 2000. Can botanical collections assist in a National Protected Area Strategy in Guyana? Biodivers. Conserv. 9(2), 215-240. https://doi.org/10.1023/A:1008990107253.

 
The Biodiversity Committee of Chinese Academy of Sciences, 2020. Catalogue of Life China: 2020 Annual Checklist, Beijing.
 

Tuanmu, M.N., Jetz, W., 2015. A global, remote sensing-based characterization of terrestrial habitat heterogeneity for biodiversity and ecosystem modelling. Glob. Ecol. Biogeogr. 24(11), 1329-1339. https://doi.org/10.1111/geb.12365.

 

Tuomisto, H., 2010a. A diversity of beta diversities: straightening up a concept gone awry. Part 1. Defining beta diversity as a function of alpha and gamma diversity. Ecography 33(1), 2-22. https://doi.org/10.1111/j.1600-0587.2009.05880.x.

 

Tuomisto, H., 2010b. A diversity of beta diversities: straightening up a concept gone awry. Part 2. Quantifying beta diversity and related phenomena. Ecography 33(1), 23-45. https://doi.org/10.1111/j.1600-0587.2009.06148.x.

 

Viana, D.S., Figuerola, J., Schwenk, K., Manca, M., Hobæk, A., Mjelde, M., Preston, C.D., Gornall, R.J., Croft, J.M., King, R.A., Green, A.J., Santamaría, L., 2016. Assembly mechanisms determining high species turnover in aquatic communities over regional and continental scales. Ecography 39(3), 281-288. https://doi.org/10.1111/ecog.01231.

 

Wang, Z., Fang, J., Tang, Z., Shi, L., 2012a. Geographical patterns in the beta diversity of China's woody plants: the influence of space, environment and range size. Ecography 35(12), 1092-1102. https://doi.org/10.1111/j.1600-0587.2012.06988.x.

 

Wang, Z., Fang, J., Tang, Z., Lin, X., 2012b. Relative role of contemporary environment versus history in shaping diversity patterns of China's woody plants. Ecography 35(12), 1124-1133. https://doi.org/10.1111/j.1600-0587.2011.06781.x.

 

Wang, X., Wiegand, T., Anderson-Teixeira, K.J., Bourg, N.A., Hao, Z., Howe, R., Jin, G., Orwig, D.A., Spasojevic, M.J., Wang, S., Wolf, A., Myers, J.A., 2018. Ecological drivers of spatial community dissimilarity, species replacement and species nestedness across temperate forests. Glob. Ecol. Biogeogr. 27(5), 581-592. https://doi.org/10.1111/geb.12719.

 

Watson, J.E.M., Dudley, N., Segan, D.B., Hockings, M., 2014. The performance and potential of protected areas. Nature 515(7525), 67-73. https://doi.org/10.1038/nature13947.

 

Xu, Y., Shen, Z., Ying, L., Wang, Z., Huang, J., Zang, R., Jiang, Y., 2017. Hotspot analyses indicate significant conservation gaps for evergreen broadleaved woody plants in China. Sci. Rep. 7(1), 1-10. https://doi.org/10.1038/s41598-017-02098-0.

 

Xu, Y., Shen, Z., Zhang, J., Zang, R., Jiang, Y., 2021. The effects of multi-scale climate variability on biodiversity patterns of Chinese evergreen broad-leaved woody plants: growth form matters. Front. Ecol. Evol. 8, 148-162. https://doi.org/10.3389/fevo.2020.540948.

 

Yang, Y., Liu, B., 2015. Species catalogue of Lauraceae in China: problems and perspectives. Biodiv. Sci. 23(2), 232-236. https://doi.org/10.17520/biods.2015027 (in Chinese).

 

Ye, J-W., Bai, W-N., Bao, L., Wang, T-M., Wang, H-F., Ge, J-P., 2017. Sharp genetic discontinuity in the aridity-sensitive Lindera obtusiloba (Lauraceae): solid evidence supporting the Tertiary floral subdivision in East Asia. J. Biogeogr. 44(9), 2082-2095. https://doi.org/10.1111/jbi.13020.

 

Ye, J., Lu, L., Liu, B., Yang, T., Zhang, J., Hu, H., Li, R., Lu, A., Liu, H., Mao, L., Chen, Z., 2019a. Phylogenetic delineation of regional biota: a case study of the Chinese flora. Mol. Phylogenet. Evol. 135(3), 222-229. https://doi.org/10.1016/j.ympev.2019.03.011.

 

Ye, J-W., Li, D.Z., Hampe, A., 2019b. Differential Quaternary dynamics of evergreen broadleaved forests in subtropical China revealed by phylogeography of Lindera aggregata (Lauraceae). J. Biogeogr. 46(6), 1112-1123. https://doi.org/10.1111/jbi.13547.

 

Zellweger, F., Roth, T., Bugmann, H., Bollmann, K., 2017. Beta diversity of plants, birds and butterflies is closely associated with climate and habitat structure. Glob. Ecol. Biogeogr. 26(8), 898-906. https://doi.org/10.1111/geb.12598.

 

Zhao, H., Wu, R., Long, Y., Hu, J., Yang, F., Jin, T., Wang, J., Hu, P., Wu, W., Diao, Y., Guo, Y., 2019. Individual-level performance of nature reserves in forest protection and the effects of management level and establishment age. Biol. Conserv. 233(2), 23-30. https://doi.org/10.1016/j.biocon.2019.02.024.

 

Zhu, S.S., Comes, H.P., Tamaki, I., Cao, Y.N., Sakaguchi, S., Yap, Z.Y., Ding, Y.Q., Qiu, Y.X., 2020. Patterns of genotype variation and demographic history in Lindera glauca (Lauraceae), an apomict-containing dioecious forest tree. J. Biogeogr. 47(9), 2002-2016. https://doi.org/10.1111/jbi.13874.

 

Zwiener, V.P., Lira-Noriega, A., Grady, C.J., Padial, A.A., Vitule, J.R.S., 2018. Climate change as a driver of biotic homogenization of woody plants in the Atlantic Forest. Glob. Ecol. Biogeogr. 27(3), 298-309. https://doi.org/10.1111/geb.12695.

Forest Ecosystems
Article number: 100018
Cite this article:
Liao Z, Chen Y, Pan K, et al. Current climate overrides past climate change in explaining multi-site beta diversity of Lauraceae species in China. Forest Ecosystems, 2022, 9(2): 100018. https://doi.org/10.1016/j.fecs.2022.100018

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Published: 03 March 2022
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