Comparison of two maximum entropy models highlights the metabolic structure of metacommunities as a key determinant of local community assembly

• Published in: Ecological modelling Vol. 407; p. 108720
• Main Authors: Bertram, Jason, Newman, Erica A., Dewar, Roderick C.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2019
• Subjects: Community assembly; Macroecology; Metabolic requirements; metabolism; prediction; Resource partitioning; species abundance; Species-abundance distribution; Statistical aggregation; Species-abundance distribution; Community assembly; Metabolic requirements; Statistical aggregation; Resource partitioning; Macroecology
• ISSN: 0304-3800; 1872-7026
• DOI: 10.1016/j.ecolmodel.2019.108720

•Maximum entropy models at different levels of community detail are compared.•These levels of detail are bridged by the metacommunity metabolic distribution.•A power law metabolic distribution reproduces observed metabolic patterns. The principle of Maximum Entropy (MaxEnt) promises a novel approach for understanding community assembly. Despite reproducing a variety of observed species abundance patterns, MaxEnt models in ecology have been hampered by disparate model assumptions and interpretations. A recurring challenge is that MaxEnt predictions are highly sensitive to the level of detail used to describe the community being modeled, and there seems to be no reason to prefer one level of detail over another. Here we present of formal unification of two previously developed MaxEnt models which differ in their level of detail, but which are otherwise mathematically similar. The less detailed model, “Maximum Entropy Theory of Ecology” (METE), does not resolve species identity or explicitly represent species-specific traits. The more detailed model, “Very Entropic Growth” (VEG), defines each separate species by its per capita metabolic rate  ε and assumes a “density of species” function ρ(ε) representing the distribution of ε in the metacommunity. A formal comparison of METE and VEG then highlights ρ(ε) as a key determinant of local community assembly. In particular, appropriate choice of ρ(ε) in VEG can produce more realistic predictions for the metabolic-rank distribution of local communities than METE, which does not explicitly account for metacommunity structure. This opens new avenues of inquiry about what determines metacommunity structure in nature and suggests possible ways to improve METE.