globalchange  > 影响、适应和脆弱性
DOI: 10.1111/gcb.13271
论文题名:
A trait-based approach for predicting species responses to environmental change from sparse data: how well might terrestrial mammals track climate change?
作者: Santini L.; Cornulier T.; Bullock J.M.; Palmer S.C.F.; White S.M.; Hodgson J.A.; Bocedi G.; Travis J.M.J.
刊名: Global Change Biology
ISSN: 13541013
出版年: 2016
卷: 22, 期:7
起始页码: 2415
结束页码: 2424
语种: 英语
英文关键词: climate change velocity ; demographic models ; dispersal ; integrodifference equations ; life-history traits ; population spread rate ; range shift ; rangeShifter ; trait space ; virtual species
Scopus关键词: climate change ; demography ; dispersal ; environmental change ; equation ; life history trait ; mammal ; population modeling ; Mammalia
英文摘要: Estimating population spread rates across multiple species is vital for projecting biodiversity responses to climate change. A major challenge is to parameterise spread models for many species. We introduce an approach that addresses this challenge, coupling a trait-based analysis with spatial population modelling to project spread rates for 15 000 virtual mammals with life histories that reflect those seen in the real world. Covariances among life-history traits are estimated from an extensive terrestrial mammal data set using Bayesian inference. We elucidate the relative roles of different life-history traits in driving modelled spread rates, demonstrating that any one alone will be a poor predictor. We also estimate that around 30% of mammal species have potential spread rates slower than the global mean velocity of climate change. This novel trait-space-demographic modelling approach has broad applicability for tackling many key ecological questions for which we have the models but are hindered by data availability. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
资助项目: LS was supported by two STSMs by the COST Action ES1101 ”Harmonising Global Biodiversity Modelling“ (Harmbio), supported by COST (European Cooperation in Science and Technology). JMB and SMW were funded by CEH projects NEC05264 and NEC05100. JMJT and SCFP are grateful for the support of the Natural Environment Research Council UK (NE/J008001/1). LS, JAH and JMJT conceived the original idea. LS, JAH, JMB, TC & JMJT designed the study ; LS collected the data ; LS and TC performed the statistical analyses ; LS conducted the integrodifference modelling assisted by JMB and SMW. LS conducted the individual-based modelling assisted by SCFP. LS led the writing supported by JMJT, JMB, SCFP, SMW, TC, JAH and GB.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/61365
Appears in Collections:影响、适应和脆弱性

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作者单位: Department of Biology and Biotechnologies, Sapienza Università di Roma, Viale dell'Università 32, Rome, Italy; Institute of Biological and Environmental Sciences, University of Aberdeen, Zoology Building, Tillydrone Avenue, Aberdeen, United Kingdom; NERC Centre for Ecology & Hydrology, Benson Lane, Wallingford, United Kingdom; Wolfson Centre for Mathematical Biology, Mathematical Institute, Radcliffe Observatory Quarter, Woodstock Road, Oxford, United Kingdom; Department of Evolution, Ecology and Behaviour, University of Liverpool, Biosciences Building, Crown Street, Liverpool, United Kingdom

Recommended Citation:
Santini L.,Cornulier T.,Bullock J.M.,et al. A trait-based approach for predicting species responses to environmental change from sparse data: how well might terrestrial mammals track climate change?[J]. Global Change Biology,2016-01-01,22(7)
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