DOI: 10.1111/gcb.12090
论文题名: Uncertainty in assessing the impacts of global change with coupled dynamic species distribution and population models
作者: Conlisk E. ; Syphard A.D. ; Franklin J. ; Flint L. ; Flint A. ; Regan H.
刊名: Global Change Biology
ISSN: 13541013
出版年: 2013
卷: 19, 期: 3 起始页码: 858
结束页码: 869
语种: 英语
英文关键词: Annual plant
; Climate change
; Conservation management
; Coupled model
; Habitat suitability
; Invasive plants
; Land-use change
; Uncertainty
Scopus关键词: annual plant
; biodiversity
; climate change
; climate effect
; endangered species
; global change
; land use change
; parameterization
; population density
; sensitivity analysis
; species diversity
; uncertainty analysis
; article
; biodiversity
; climate change
; population dynamics
; theoretical model
; uncertainty
; Biodiversity
; Climate Change
; Models, Theoretical
; Population Dynamics
; Uncertainty
; Acanthomintha ilicifolia
英文摘要: Concern over rapid global changes and the potential for interactions among multiple threats are prompting scientists to combine multiple modelling approaches to understand impacts on biodiversity. A relatively recent development is the combination of species distribution models, land-use change predictions, and dynamic population models to predict the relative and combined impacts of climate change, land-use change, and altered disturbance regimes on species' extinction risk. Each modelling component introduces its own source of uncertainty through different parameters and assumptions, which, when combined, can result in compounded uncertainty that can have major implications for management. Although some uncertainty analyses have been conducted separately on various model components - such as climate predictions, species distribution models, land-use change predictions, and population models - a unified sensitivity analysis comparing various sources of uncertainty in combined modelling approaches is needed to identify the most influential and problematic assumptions. We estimated the sensitivities of long-run population predictions to different ecological assumptions and parameter settings for a rare and endangered annual plant species (Acanthomintha ilicifolia, or San Diego thornmint). Uncertainty about habitat suitability predictions, due to the choice of species distribution model, contributed most to variation in predictions about long-run populations. © 2012 Blackwell Publishing Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62523
Appears in Collections: 影响、适应和脆弱性
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作者单位: Department of Biology, Center for Conservation Biology, University of California, 900 University Ave, Riverside, CA 92521, United States; Conservation Biology Institute, 10423 Sierra Vista Ave., La Mesa, CA, 91941, United States; School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ, 85287-5302, United States; USGS California Water Science Center, 6000 J Street, Sacramento, CA, 95819, United States; USGS California Water Science Center, 6000 J Street, Sacramento, CA, 95819, United States; Department of Biology, University of California, 900 University Ave, Riverside, CA, 92521, United States
Recommended Citation:
Conlisk E.,Syphard A.D.,Franklin J.,et al. Uncertainty in assessing the impacts of global change with coupled dynamic species distribution and population models[J]. Global Change Biology,2013-01-01,19(3)