DOI: 10.1111/gcb.13653
论文题名: Designing ecological climate change impact assessments to reflect key climatic drivers
作者: Sofaer H.R. ; Barsugli J.J. ; Jarnevich C.S. ; Abatzoglou J.T. ; Talbert M.K. ; Miller B.W. ; Morisette J.T.
刊名: Global Change Biology
出版年: 2017
卷: 23, 期: 7 起始页码: 2537
结束页码: 2553
语种: 英语
英文关键词: climate bias-correction
; climate change impacts
; climate extremes
; climate variability
; delta method
; ecological projections
英文摘要: Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling. © 2017 John Wiley & Sons Ltd 资助项目: Sofaer, H.R.
; U.S. Geological Survey, Fort Collins Science Center, 2150 Centre Ave, Bldg. C, United States
; 电子邮件: hsofaer@usgs.gov
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/60914
Appears in Collections: 影响、适应和脆弱性
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作者单位: U.S. Geological Survey, Fort Collins Science Center, 2150 Centre Ave, Bldg. C, Fort Collins, CO, United States; University of Colorado, Cooperative Institute for Research in Environmental Sciences at the NOAA Earth System Research Laboratory, Physical Sciences Division, 325 Broadway BoulderCO, United States; Department of Geography, University of Idaho, Moscow, ID, United States; U.S. Geological Survey, Department of the Interior North Central Climate Science Center, Fort Collins, CO, United States; Statistics Department, Colorado State University, Fort Collins, CO, United States
Recommended Citation:
Sofaer H.R.,Barsugli J.J.,Jarnevich C.S.,et al. Designing ecological climate change impact assessments to reflect key climatic drivers[J]. Global Change Biology,2017-01-01,23(7)