Self-Organization of Patchy Landscapes: Hidden Optimization of Ecological Processes
- *Corresponding Author:
- Cédric Gaucherel
Head of the Department of Ecology
French Institute of Pondicherry
(UMIFRE 21 CNRS-MAEE)
11, St Louis Street
Pondicherry 605001, India
E-mail: [email protected]
Received Date: October 29, 2011; Accepted Date: November 07, 2011; Published Date: November 09, 2011
Citation: Gaucherel C (2011) Self-Organization of Patchy Landscapes: Hidden Optimization of Ecological Processes. J Ecosys Ecograph 1:105. doi:10.4172/2157-7625.1000105
Copyright: © 2011 Gaucherel C. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and and source are credited.
One of the main barriers in the understanding of landscape dynamics is the high spatial variability of the surface patterns (vegetation and land cover) to which ecological processes are intimately linked. The aim of this paper is to present some newly found scaling properties for forested landscapes. Furthermore, it is advocated that patchy landscapes can sometimes be self-organized by optimizing some effective functional. A neutral landscape model has been developed in order to test this self-organization hypothesis. This model was built on the basis of a simple function, called the "Hamiltonian" analogically to physical and biological systems. The Hamiltonian is then minimized to optimize the identified landscape interactions. Fully controlled data coming from five different hundred-year runs of a process-based model appeared to be self-similar over five magnitude orders, without being explicitly simulated. The neutral model is able to reproduce the studied observations and to easily model Optimal Patchy Landscapes. The limits to this parsimonious approach that requires only one parameter (the Hamiltonian slope in loglog plot) are also discussed. The links between the effective Hamiltonian and the ecological processes still need to be investigated. Finally, such landscape Hamiltonian function appears to be a fruitful theoretical framework to describe various landscapes and potentially opens the way to a more complete dynamic landscape theory.