globalchange  > 气候减缓与适应
DOI: 10.1111/ele.12709
Scopus记录号: 2-s2.0-85006364866
论文题名:
Detecting spatial regimes in ecosystems
作者: Sundstrom S.M.; Eason T.; Nelson R.J.; Angeler D.G.; Barichievy C.; Garmestani A.S.; Graham N.A.J.; Granholm D.; Gunderson L.; Knutson M.; Nash K.L.; Spanbauer T.; Stow C.A.; Allen C.R.
刊名: Ecology Letters
ISSN: 1461023X
EISSN: 1461-0248
出版年: 2017
卷: 20, 期:1
起始页码: 19
结束页码: 32
语种: 英语
英文关键词: Boundary detection ; community change ; Fisher information ; regime shifts ; spatial regimes ; spatial resilience
Scopus关键词: boundary layer ; climate change ; community dynamics ; community structure ; ecoregion ; information management ; land use change ; spatial data ; Animalia ; Aves ; animal ; animal dispersal ; bird ; climate change ; ecosystem ; physiology ; zooplankton ; Animal Distribution ; Animals ; Birds ; Climate Change ; Ecosystem ; Zooplankton
英文摘要: Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change. � 2016 John Wiley & Sons Ltd/CNRS
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/107676
Appears in Collections:气候减缓与适应

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作者单位: School of Natural Resources, University of Nebraska-Lincoln, 103 Hardin Hall, 3310 Holdrege St.NE, United States; U.S. Environmental Protection Agency, National Risk Management Research Laboratory, CincinnatiOH, United States; Department of Biology-Centre for Biomedical Research, University of Victoria, Victoria, BC, Canada; Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Box�7050, Uppsala, Sweden; Zoological Society of London, Regents Park, London, United Kingdom; Lancaster Environment Centre, Lancaster University, Lancaster, United Kingdom; U.S. Fish & Wildlife Service, Bloomington, MN, United States; Department of Environmental Sciences, Emory University, Atlanta, GA, United States; Region 3 U.S. Fish & Wildlife Service, La Crosse, WI, United States; Centre for Marine Socioecology, Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, TAS, Australia; National Research Council, U.S. Environmental Protection Agency, Cincinnati, OH, United States; National Oceanographic and Atmospheric Administration Great Lakes Environmental Research Laboratory, Ann Arbor, MI, United States; U.S. Geological Survey - Nebraska Cooperative Fish & Wildlife Research Unit, University of Nebraska, Lincoln, NE, United States

Recommended Citation:
Sundstrom S.M.,Eason T.,Nelson R.J.,et al. Detecting spatial regimes in ecosystems[J]. Ecology Letters,2017-01-01,20(1)
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