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

Jason Bertram, Erica A. Newman and Roderick C. Dewar

Ecological Modelling, 2019, vol. 407, issue C, -

Abstract: 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.

Keywords: Community assembly; Macroecology; Metabolic requirements; Resource partitioning; Species-abundance distribution; Statistical aggregation (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380019302200
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:407:y:2019:i:c:1

DOI: 10.1016/j.ecolmodel.2019.108720

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().