Stochastic Spatial Models in Ecology: A Statistical Physics Approach View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-07

AUTHORS

Simone Pigolotti, Massimo Cencini, Daniel Molina, Miguel A. Muñoz

ABSTRACT

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D=2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories. More... »

PAGES

44-73

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10955-017-1926-4

DOI

http://dx.doi.org/10.1007/s10955-017-1926-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1092838844


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