title: A theoretical approach to understand spatial organization in complex ecologies.
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.
authors.affiliation: Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Department of Physics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0435, USA.
authors.forename: Ahmed
authors.initials: A
authors.lastname: Roman
authors.affiliation: Booz Allen Hamilton, 575 Herndon Parkway, Herndon, VA 20170, USA.
authors.forename: Debanjan
authors.initials: D
authors.lastname: Dasgupta
authors.affiliation: Department of Physics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0435, USA; Center for Soft Matter and Biological Physics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0435, USA; Academy of Integrated Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0405, USA. Electronic address: pleim@vt.edu.
authors.forename: Michel
authors.initials: M
authors.lastname: Pleimling
mesh_terms: D017753:Ecosystem; D020387:Food Chain; D008962:Models, Theoretical; D013045:Species Specificity
keywords: Emerging space–time patterns; Many species food networks; Matrix approach