Year: 2016
Type: article
Abstract: 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.
Source: Ecology Letters
DOI: 10.1111/ele.12709
Institutions: University of Nebraska–Lincoln, Environmental Protection Agency, University of Victoria, Swedish University of Agricultural Sciences, Zoological Society of London, Lancaster University, United States Fish and Wildlife Service, Emory University, University of Tasmania, Centre for Marine Socioecology, Institute for Marine and Antarctic Studies, National Academies of Sciences, Engineering, and Medicine, National Oceanic and Atmospheric Administration, NOAA Great Lakes Environmental Research Laboratory, United States Geological Survey
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: hybrid
Estimated APC paid: $5,300
OpenAlex ID: W2565360508
