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.

Keywords

Boundary detection; community change; Fisher information; regime shifts; spatial regimes; spatial resilience

Published in

Ecology Letters
2017, Volume: 20, number: 1, pages: 19-32

SLU Authors

• Angeler, David

  • Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
    

Sustainable Development Goals

SDG13 Take urgent action to combat climate change and its impacts


UKÄ Subject classification

Environmental Sciences related to Agriculture and Land-use


Publication identifier

DOI: https://doi.org/10.1111/ele.12709

Permanent link to this page (URI)

https://res.slu.se/id/publ/88772