Asking the pikas politely…
John Harte,1,2,3* The Maximum Entropy Theory of Ecology (METE) predicts the shapes of macroecological met- Kaito Umemura4 and rics in relatively static ecosystems, across spatial scales, taxonomic categories and habitats, using Micah Brush5 constraints imposed by static state variables. In disturbed ecosystems, however, with time-varying state variables, its predictions often fail. We extend macroecological theory from static to dynamic by combining the MaxEnt inference procedure with explicit mechanisms governing disturbance. In the static limit, the resulting theory, DynaMETE, reduces to METE but also predicts a new scaling relationship among static state variables. Under disturbances, expressed as shifts in demo- graphic, ontogenic growth or migration rates, DynaMETE predicts the time trajectories of the state variables as well as the time-varying shapes of macroecological metrics such as the species abundance distribution and the distribution of metabolic rates over individuals. An iterative pro- cedure for solving the dynamic theory is presented. Characteristic signatures of the deviation from static predictions of macroecological patterns are shown to result from different kinds of distur- bance. By combining MaxEnt inference with explicit dynamical mechanisms of disturbance, Dyna- METE is a candidate theory of macroecology for ecosystems responding to anthropogenic or natural disturbances.
Knowledge graph centered on DynaMETE: a hybrid MaxEnt-plus-mechanism theory of with 64 nodes and 258 connections. Top connected: Maximum information entropy: a foundation for ecol, Biodiversity scales from plots to biomes with a un, Lepidoptera, small mammals, species diversity.
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