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Detecting spatial regimes in ecosystems
Author(s) -
Sundstrom Shana M.,
Eason Tarsha,
Nelson R. John,
Angeler David G.,
Barichievy Chris,
Garmestani Ahjond S.,
Graham Nicholas A.J.,
Granholm Dean,
Gunderson Lance,
Knutson Melinda,
Nash Kirsty L.,
Spanbauer Trisha,
Stow Craig A.,
Allen Craig R.
Publication year - 2017
Publication title -
ecology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.852
H-Index - 265
eISSN - 1461-0248
pISSN - 1461-023X
DOI - 10.1111/ele.12709
Subject(s) - ecoregion , ecology , spatial analysis , spatial ecology , warning system , environmental change , temporal scales , multivariate statistics , climate change , geography , environmental resource management , environmental science , computer science , biology , remote sensing , telecommunications , machine learning
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.