Abstract: The maximum information entropy (MacEnt) principle is a successful method of statistical inference that has recently been applied to ecology. Here, we show how MaxEnt can accurately predict patterns such as species-area relationships and abundance distributions in macro-ecology and be a foundation of the principle why it often produces accurate predictions of probability distributions in science despite not incorporating explicit mechanisms, and how mismatches between predictions and data can shed lights on driving mechanism in ecology. We also review possible future extensions of the maximum entropy theory of ecology, a potentially important foundation for future developments in ecological theory.
Maximum information entropy: a foundation for ecological theory
John Harte, Erica A. Newman
Trends in Ecology and Evolution, July 2014 Vol. 29, No. 7