DocumentCode :
3673207
Title :
A comparison of incremental community assembly with evolutionary community selection
Author :
Daniel Ashlock;Meghan Timmins
Author_Institution :
Department of Mathematics and Statistics at the University of Guelph, in Guelph, Ontario, Canada, N1G 2W1
fYear :
2015
Firstpage :
1
Lastpage :
8
Abstract :
Given a set of potential species and a replicator dynamic model of their interaction, the community assembly problem seeks the maximal set of species that can co-exist indefinitely without extinction. In this study we compare a standard model, which assembles a community one species at a time, with an evolutionary algorithm that selects sets of species directly. The comparison is performed using a standard competition model. The system is tested with three different available species pools of one hundred species. The diversity of communities located with the evolutionary algorithm substantially exceeds that of those located by serial addition of single species. In agreement with past research, the serial species addition algorithm located communities that, while not the largest, were highly resistant to invasion by a single additional species. A comparison of the diversity between the communities located by the two algorithms demonstrated that the evolutionary algorithm located a very much larger variety of community types. For all three species pools, the communities found in different runs of the serial species addition algorithm shared large common cores of species.
Keywords :
"Biological system modeling","Evolutionary computation","Assembly","Mathematical model","Ecology","Sociology","Statistics"
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2015 IEEE Conference on
Type :
conf
DOI :
10.1109/CIBCB.2015.7300311
Filename :
7300311
Link To Document :
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