English

A theoretical approach to understand spatial organization in complex ecologies

Populations and Evolution 2016-08-31 v1 Statistical Mechanics

Abstract

Predicting the fate of ecologies is a daunting, albeit extremely important, task. As part of this task one needs to develop an understanding of the organization, hierarchies, and correlations among the species forming the ecology. Focusing on complex food networks we present a theoretical method that allows to achieve this understanding. Starting from the adjacency matrix the method derives specific matrices that encode the various inter-species relationships. The full potential of the method is achieved in a spatial setting where one obtains detailed predictions for the emerging space-time patterns. For a variety of cases these theoretical predictions are verified through numerical simulations.

Keywords

Cite

@article{arxiv.1605.02028,
  title  = {A theoretical approach to understand spatial organization in complex ecologies},
  author = {Ahmed Roman and Debanjan Dasgupta and Michel Pleimling},
  journal= {arXiv preprint arXiv:1605.02028},
  year   = {2016}
}

Comments

14 pages, 3 figures, accepted for publication in the Journal of Theoretical Biology

R2 v1 2026-06-22T13:55:02.525Z