Little is known about how metrics of biodiversity and abundance scale in ecologically disturbed and disrupted systems. Natural disturbances have a fundamental role in structuring ecological communities, and the study of these processes and extension to novel ecological disruptions is of increasing importance due to global change and mounting human impacts. The Maximum Entropy Theory of Ecology (METE) takes a macroecological approach to estimating plot- to landscape- to biome-scale species diversity, abundance, and energetics metrics, using only the relationships between four non-adjustable state variables S0 (total species), A0 (area under consideration), N0 (total abundance), and E0 (total metabolic energy), and no adjustable parameters to characterize the scaling of diversity and abundances of species in a system. Until this work, METE has mainly been tested in steady-state and minimally disturbed systems.
Here, we census plants in several ecosystems with known histories of ecological disruption, including (1) different-age post-fire stands of Bishop pine (Pinus muricata), a plant community that is largely structured by a dominant, disturbance-dependent species, and (2) sub-alpine Sierra meadows, browsed by large, non-native herbivores. Natural disturbance regimes and landscapes affected by anthropogenic disruptions have both been largely overlooked by macroecological theory.
Results/Conclusions
Comparing two Bishop Pine stands in a natural disturbance regime, we find that ecological patterns in the mature stand more closely match METE predictions than do data from the more recently disturbed stand. This suggests METE’s predictions are more robust in late successional, slowly changing, or steady-state systems than those in rapid flux with respect to species composition, abundances, and body sizes.
In 18 replicate plots in Sierra meadows, we find singleton species are better indicators of ecological disruption than the shape of the species-abundance distribution in systems where the differences in community structure are subtle. We also find that the METE-predicted spatial aggregation of species performs better than all other models tested for both browsed and unbrowsed plots. We suggest ways of augmenting METE tests for management relevance.
Taken together, our results indicate that it is possible to extend macroecological theory to ecosystems that experience natural disturbances and other ecological disruptions. Regular deviations of data from METE predictions may suggest where ecological processes may influence the shape of empirical macroecological distributions. I provide a framework for comparing and eventually predicting the various effects of disturbance on biodiversity, in the contexts of disturbance regimes, anthropogenic change, and mixtures of both.