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International Conference on Complex Systems (ICCS2006)

Application of a genetic algorithm to generate non-random assembly sequences of a community assembly model

Pascal Côté
Complex Systems Laboratory / Université de Montréal

Lael Parrott
Complex Systems Laboratory / Université de Montréal

     Full text: Not available
     Last modified: January 31, 2006

Abstract
In community assembly models (CAM), species are introduced from a pool of species, identified as the regional species pool (RSP), according to a sequence of invasion. Results from the study of CAM show that different sequences can lead to a branching of possibilities, emphasizing the importance of historical events on community composition. Most CAM use random sequences of invasion, probably because the number of possible assembly sequences one can generate is extremely large for a high diversity RSP. However, random sequences represent only a small subset of the space composed of all possible sequences and they do not constitute an appropriate and efficient tool to explore the entire parameter search space of such CAM. We present a new approach based on genetic algorithms (GA) which generates non-random sequences in order to maximize the diversity of assembled communities using a model based on Lotka-Volterra dynamics. The GA must also meet the constraint that the food web of the community constructed in this fashion have a specified connectance. The results show that the optimized sequences produce communities with a higher diversity than those generated from random assembly sequences. In addition, the GA is able to generate sequences that produce food webs that have different expected connectances from identical RSP . Our approach demonstrates the effectiveness of GA for optimizing parameters in ecological assembly models and we conclude that the use of an optimization technique provides an interesting approach to analyze the structure of assembly sequences. As CAM have recently received increased interest in restoration ecology because of the influence of historical events reported in most literature, the study of assembly sequences provides a promising avenue to investigate the impact of historical events in recreating ecological communities.




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