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Split diversity in constrained conservation prioritization using integer linear programming.


ABSTRACT: Phylogenetic diversity (PD) is a measure of biodiversity based on the evolutionary history of species. Here, we discuss several optimization problems related to the use of PD, and the more general measure split diversity (SD), in conservation prioritization.Depending on the conservation goal and the information available about species, one can construct optimization routines that incorporate various conservation constraints. We demonstrate how this information can be used to select sets of species for conservation action. Specifically, we discuss the use of species' geographic distributions, the choice of candidates under economic pressure, and the use of predator-prey interactions between the species in a community to define viability constraints.Despite such optimization problems falling into the area of NP hard problems, it is possible to solve them in a reasonable amount of time using integer programming. We apply integer linear programming to a variety of models for conservation prioritization that incorporate the SD measure.We exemplarily show the results for two data sets: the Cape region of South Africa and a Caribbean coral reef community. Finally, we provide user-friendly software at http://www.cibiv.at/software/pda.

SUBMITTER: Chernomor O 

PROVIDER: S-EPMC4392707 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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Split diversity in constrained conservation prioritization using integer linear programming.

Chernomor Olga O   Minh Bui Quang BQ   Forest Félix F   Klaere Steffen S   Ingram Travis T   Henzinger Monika M   von Haeseler Arndt A  

Methods in ecology and evolution 20141206 1


Phylogenetic diversity (PD) is a measure of biodiversity based on the evolutionary history of species. Here, we discuss several optimization problems related to the use of PD, and the more general measure split diversity (SD), in conservation prioritization.Depending on the conservation goal and the information available about species, one can construct optimization routines that incorporate various conservation constraints. We demonstrate how this information can be used to select sets of speci  ...[more]

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