Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1111/gcb.13653 |
Designing ecological climate change impact assessments to reflect key climatic drivers | |
Sofaer, Helen R.1; Barsugli, Joseph J.2; Jarnevich, Catherine S.1; Abatzoglou, John T.3; Talbert, Marian K.4,5; Miller, Brian W.4; Morisette, Jeffrey T.4 | |
2017-07-01 | |
发表期刊 | GLOBAL CHANGE BIOLOGY |
ISSN | 1354-1013 |
EISSN | 1365-2486 |
出版年 | 2017 |
卷号 | 23期号:7 |
文章类型 | Review |
语种 | 英语 |
国家 | USA |
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. |
英文关键词 | climate bias-correction climate change impacts climate extremes climate variability delta method ecological projections |
领域 | 气候变化 ; 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000402514900003 |
WOS关键词 | STOCHASTIC WEATHER GENERATORS ; HYDROLOGICALLY BASED DATASET ; NORTH-AMERICAN CLIMATE ; LAND-SURFACE FLUXES ; PRECIPITATION EXTREMES ; HEAVY-PRECIPITATION ; CHANGE SCENARIOS ; IMPROVE PREDICTIONS ; DAILY TEMPERATURE ; BIAS CORRECTION |
WOS类目 | Biodiversity Conservation ; Ecology ; Environmental Sciences |
WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/16951 |
专题 | 气候变化 资源环境科学 |
作者单位 | 1.US Geol Survey, Ft Collins Sci Ctr, 2150 Ctr Ave,Bldg C, Ft Collins, CO 80526 USA; 2.Univ Colorado, Cooperat Inst Res Environm Sci, NOAA, Earth Syst Res Lab,Phys Sci Div, 325 Broadway, Boulder, CO 80305 USA; 3.Univ Idaho, Dept Geog, Moscow, ID 83844 USA; 4.US Geol Survey, Dept Interior North Cent Climate Sci Ctr, Ft Collins, CO 80523 USA; 5.Colorado State Univ, Dept Stat, Ft Collins, CO 80523 USA |
推荐引用方式 GB/T 7714 | Sofaer, Helen R.,Barsugli, Joseph J.,Jarnevich, Catherine S.,et al. Designing ecological climate change impact assessments to reflect key climatic drivers[J]. GLOBAL CHANGE BIOLOGY,2017,23(7). |
APA | Sofaer, Helen R..,Barsugli, Joseph J..,Jarnevich, Catherine S..,Abatzoglou, John T..,Talbert, Marian K..,...&Morisette, Jeffrey T..(2017).Designing ecological climate change impact assessments to reflect key climatic drivers.GLOBAL CHANGE BIOLOGY,23(7). |
MLA | Sofaer, Helen R.,et al."Designing ecological climate change impact assessments to reflect key climatic drivers".GLOBAL CHANGE BIOLOGY 23.7(2017). |
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