当前气候、古气候和生境异质性对中国常绿阔叶木本植物生物地理格局的影响（英文）
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摘要
Understanding biogeographic patterns and the mechanisms underlying them has been a main issue in macroecology and biogeography, and has implications for biodiversity conservation and ecosystem sustainability. Evergreen broad-leaved woody plants(EBWPs) are important components of numerous biomes and are the main contributors to the flora south of 35°N in China. We calculated the grid cell values of species richness(SR) for a total of 6265 EBWP species in China, including its four growth-forms(i.e., tree, shrub, vine, and bamboo), and estimated their phylogenetic structure using the standardized phylogenetic diversity(SPD) and net relatedness index(NRI). Then we linked the three biogeographical patterns that were observed with each single environmental variable representing the current climate, the last glacial maximum(LGM)–present climate variability, and habitat heterogeneity, using ordinary least squares regression with a modified t-test to account for spatial autocorrelation. The partial regression method based on a general linear model was used to decompose the contributions of current and historical environmental factors to the biogeographical patterns observed. The results showed that most regions with high numbers of EBWP species and phylogenetic diversity were distributed in tropical and subtropical mountains with evergreen shrubs extending to Northeast China. Current mean annual precipitation was the best single predictor. Topographic variation and its effect on temperature variation was the best single predictor for SPD and NRI. Partial regression indicated that the current climate dominated the SR patterns of Chinese EBWPs. The effect of paleo-climate variation on SR patterns mostly overlapped with that of the current climate. In contrast, the phylogenetic structure represented by SPD and NRI was constrained by paleo-climate to much larger extents than diversity, which was reflected by the LGM–present climate variation and topog-raphy-derived habitat heterogeneity in China. Our study highlights the importance of embedding multiple dimensions of biodiversity into a temporally hierarchical framework for understanding the biogeographical patterns, and provides important baseline information for predicting shifts in plant diversity under climate change.
Understanding biogeographic patterns and the mechanisms underlying them has been a main issue in macroecology and biogeography, and has implications for biodiversity conservation and ecosystem sustainability. Evergreen broad-leaved woody plants(EBWPs) are important components of numerous biomes and are the main contributors to the flora south of 35°N in China. We calculated the grid cell values of species richness(SR) for a total of 6265 EBWP species in China, including its four growth-forms(i.e., tree, shrub, vine, and bamboo), and estimated their phylogenetic structure using the standardized phylogenetic diversity(SPD) and net relatedness index(NRI). Then we linked the three biogeographical patterns that were observed with each single environmental variable representing the current climate, the last glacial maximum(LGM)–present climate variability, and habitat heterogeneity, using ordinary least squares regression with a modified t-test to account for spatial autocorrelation. The partial regression method based on a general linear model was used to decompose the contributions of current and historical environmental factors to the biogeographical patterns observed. The results showed that most regions with high numbers of EBWP species and phylogenetic diversity were distributed in tropical and subtropical mountains with evergreen shrubs extending to Northeast China. Current mean annual precipitation was the best single predictor. Topographic variation and its effect on temperature variation was the best single predictor for SPD and NRI. Partial regression indicated that the current climate dominated the SR patterns of Chinese EBWPs. The effect of paleo-climate variation on SR patterns mostly overlapped with that of the current climate. In contrast, the phylogenetic structure represented by SPD and NRI was constrained by paleo-climate to much larger extents than diversity, which was reflected by the LGM–present climate variation and topog-raphy-derived habitat heterogeneity in China. Our study highlights the importance of embedding multiple dimensions of biodiversity into a temporally hierarchical framework for understanding the biogeographical patterns, and provides important baseline information for predicting shifts in plant diversity under climate change.
Understanding biogeographic patterns and the mechanisms underlying them has been a main issue in macroecology and biogeography, and has implications for biodiversity conservation and ecosystem sustainability. Evergreen broad-leaved woody plants(EBWPs) are important components of numerous biomes and are the main contributors to the flora south of 35°N in China. We calculated the grid cell values of species richness(SR) for a total of 6265 EBWP species in China, including its four growth-forms(i.e., tree, shrub, vine, and bamboo), and estimated their phylogenetic structure using the standardized phylogenetic diversity(SPD) and net relatedness index(NRI). Then we linked the three biogeographical patterns that were observed with each single environmental variable representing the current climate, the last glacial maximum(LGM)–present climate variability, and habitat heterogeneity, using ordinary least squares regression with a modified t-test to account for spatial autocorrelation. The partial regression method based on a general linear model was used to decompose the contributions of current and historical environmental factors to the biogeographical patterns observed. The results showed that most regions with high numbers of EBWP species and phylogenetic diversity were distributed in tropical and subtropical mountains with evergreen shrubs extending to Northeast China. Current mean annual precipitation was the best single predictor. Topographic variation and its effect on temperature variation was the best single predictor for SPD and NRI. Partial regression indicated that the current climate dominated the SR patterns of Chinese EBWPs. The effect of paleo-climate variation on SR patterns mostly overlapped with that of the current climate. In contrast, the phylogenetic structure represented by SPD and NRI was constrained by paleo-climate to much larger extents than diversity, which was reflected by the LGM–present climate variation and topog-raphy-derived habitat heterogeneity in China. Our study highlights the importance of embedding multiple dimensions of biodiversity into a temporally hierarchical framework for understanding the biogeographical patterns, and provides important baseline information for predicting shifts in plant diversity under climate change.
引文
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Dreiss L M,Burgio K R,Cisneros L M et al.,2015.Taxonomic,functional,and phylogenetic dimensions of rodent biodiversity along an extensive tropical elevational gradient.Ecography,38(9):876-888.
Dutilleul P,Clifford P,Richardson S et al.,1993.Modifying the t test for assessing the correlation between two spatial processes.Biometrics,49(1):305-314.
Faith D P,1992.Conservation evaluation and phylogenetic diversity.Biological Conservation,61(1):1-10.
Fang J,Wang Z,Tang Z,2011.Atlas of Woody Plants in China:Distribution and Climate.New York:Springer Science&Business Media.
Favre A,P?ckert M,Pauls S U et al.,2015.The role of the uplift of the Qinghai-Tibetan Plateau for the evolution of Tibetan biotas.Biological Reviews,90(1):236-253.
Feng G,Mao L,Sandel B et al.,2015.High plant endemism in China is partially linked to reduced glacial-interglacial climate change.Journal of Biogeography,43(1):145-154.
Feng G,Mi X,B?cher P K et al.,2014.Relative roles of local disturbance,current climate and paleoclimate in determining phylogenetic and functional diversity in Chinese forests.Biogeosciences,11(5):1361.
Fjelds?J,Bowie R C K,Rahbek C,2012.The role of mountain ranges in the diversification of birds.Annual Review of Ecology Evolution and Systematics,43(1):249-265.
Francis A P,Currie D J,1998.Global patterns of tree richness in moist forests:Another look.Oikos,81(3):598-602.
Fung T,O’Dwyer J P,Rahman K A et al.,2016.Reproducing static and dynamic biodiversity patterns in tropical forests:The critical role of environmental variance.Ecology,97(5):1207-1217.
Gaston K J,Fuller R A,2009.The sizes of species:Geographic ranges.Journal of Applied Ecology,46(1):1-9.
Goldie X,Gillman L,Crisp M et al.,2010.Evolutionary speed limited by water in arid Australia.Proceedings of the Royal Society of London B:Biological Sciences,277(1694):2645-2653.
Graham C H,Fine P V A.2008.Phylogenetic beta diversity:Linking ecological and evolutionary processes across space in time.Ecology Letters,11(12):1265-1277.
Hawkins B A,Field R,Cornell H V et al.,2003.Energy,water,and broad-scale geographic patterns of species richness.Ecology,84(12):3105-3117.
Hawkins B A,Porter E E,2003.Relative influences of current and historical factors on mammal and bird diversity patterns in deglaciated North America.Global Ecology&Biogeography,12(6):475-481.
Hortal J,Diniz-Filho J A F,Bini L M et al.,2011.Ice age climate,evolutionary constraints and diversity patterns of European dung beetles.Ecology Letters,14(8):741-748.
Jarzyna M A,Jetz W,2016.Detecting the multiple facets of biodiversity.Trends in Ecology&Evolution,31(7):527-538.
Jetz W,Rahbek C,2002.Geographic range size and determinants of avian species richness.Science,297(5586):1548-1551.
Kembel S W,Cowan P D,Helmus M R et al.,2010.Picante:R tools for integrating phylogenies and ecology.Bioinformatics,26(11):1463-1464.
Kerr J T,Southwood T,Cihlar J,2001.Remotely sensed habitat diversity predicts butterfly species richness and community similarity in Canada.Proceedings of the National Academy of Sciences,98(20):11365-11370.
Kissling W D,Baker W J,Balslev H et al.,2012a.Quaternary and pre-Quaternary historical legacies in the global distribution of a major tropical plant lineage.Global Ecology&Biogeography,21(9):909-921.
Kissling W D,Eiserhardt W L,Baker W J et al.,2012b.Cenozoic imprints on the phylogenetic structure of palm species assemblages worldwide.Proceedings of the National Academy of Sciences,109(19):7379-7384.
Kreft H,Jetz W,2007.Global patterns and determinants of vascular plant diversity.Proceedings of the National Academy of Sciences,104(14):5925-5930.
Kubota Y,Kusumoto B,Shiono T et al.,2016.Phylogenetic properties of Tertiary relict flora in the East Asian continental islands:Imprint of climatic niche conservatism and in situ diversification.Ecography,40(3):436-447.10.1111/ecog.02033.
Kubota Y,Shiono T,Kusumoto B,2015.Role of climate and geohistorical factors in driving plant richness patterns and endemicity on the east Asian continental islands.Ecography,38(6):639-648.
Legendre P,Legendre L,1998.Numerical Ecology.Elsevier.
Lei F,Qu Y,Song G et al.,2015.The potential drivers in forming avian biodiversity hotspots in the East Himalaya-Mountains of Southwest China.Integrative Zoology,10(2):171-181.
Li Y,Wang Z,Xu X et al.,2016.Leaf margin analysis of Chinese woody plants and the constraints on its application to paleoclimatic reconstruction.Global Ecology&Biogeography,25(12):10.1111/geb.12498.
Liu Y,Hu J,Li S H et al.,2016.Sino-Himalayan Mountains act as cradles of diversity and immigration centers in the diversification of parrotbills(Paradoxornithidae).Journal of Biogeography,43(8):1488-1501.
Liu Y,Su X,Shrestha N et al.,2018.Effects of contemporary environment and Quaternary climate change on drylands plant diversity differ between growth forms.Ecography,42(2):334-345.
Loarie S R,Duffy P B,Hamilton H et al.,2009.The velocity of climate change.Nature,462(7276):1052-1057.
López-Pujol J,Zhang F M,Sun H Q et al.,2011.Mountains of southern China as“plant museums”and“plant cradles”:Evolutionary and conservation insights.Mountain Research and Development,31(3):261-269.
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