As ecological boundaries shift in response to climate change and other anthropogenic forces, detecting regime shifts using spatial data on animal communities, in place of vegetation communities used to define ecoregions, may provide more accuracy.
Using Fisher information, an information theory approach suitable for capturing patterns in system dynamics from multi-variate data, Sundstrom and colleagues used data from avian and zooplankton communities to identify spatial regimes and compare how well they line up with existing ecological boundaries determined using classification methods. The boundaries detected using animal data were considered to reflect ecological reality more than boundaries defined by the classification systems, suggesting that the approach could help with tracking shifting boundaries over time.
The authors also found the Fisher information approach consistently identified spatial regime shifts. They suggest that further research could help managers to select subgroups of species to monitor ecological stability within a community. Craig Allen, one of the paper's co-authors states "we believe the idea of spatial regimes is much more useful, potentially, in identifying impacts and responses to climate change than individually modelling species' responses".
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. and Allen, C. R. (2017), Detecting spatial regimes in ecosystems. Ecol Lett, 20: 19-32. doi:10.1111/ele.12709