A generalized neutral theory explains static and dynamic properties of biotic communities
Michael Kalyuzhny, Ronen Kadmon, Nadav M. Shnerb

TL;DR
This paper extends neutral theory by incorporating environmental stochasticity, enabling it to accurately predict both static and dynamic properties of ecological communities, as demonstrated with tropical forest data.
Contribution
It introduces a generalized neutral theory that combines niche differences and stochasticity, improving predictions of community dynamics while maintaining simplicity.
Findings
Better fits to short-term fluctuation distributions
Improved modeling of temporal scaling of fluctuations
Accurate prediction of community compositional decay over time
Abstract
Understanding the forces shaping ecological communities is crucially important to basic science and conservation. In recent years, considerable progress was made in explaining communities using simple and general models, with neutral theory as a prominent example. However, while successful in explaining static patterns such as species abundance distributions, the neutral theory was criticized for making unrealistic predictions of fundamental dynamic patterns. Here we incorporate environmental stochasticity into the neutral framework, and show that the resulting generalized neutral theory is capable of predicting realistic patterns of both population and community dynamics. Applying the theory to real data (the tropical forest of Barro-Colorado Island), we find that it better fits the observed distribution of short-term fluctuations, the temporal scaling of such fluctuations, and the…
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Taxonomy
TopicsEcology and Vegetation Dynamics Studies · Species Distribution and Climate Change · Animal Ecology and Behavior Studies
