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CDM eta POP : an individual‐based, eco‐evolutionary model for spatially explicit simulation of landscape demogenetics
Author(s) -
Landguth Erin L.,
Bearlin Andrew,
Day Casey C.,
Dunham Jason
Publication year - 2017
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12608
Subject(s) - selection (genetic algorithm) , population , fitness landscape , function (biology) , population viability analysis , population genetics , ecology , computer science , geography , evolutionary biology , biology , machine learning , habitat , demography , sociology , endangered species
SummaryCombining landscape demographic and genetics models offers powerful methods for addressing questions for eco‐evolutionary applications. Using two illustrative examples, we present Cost–Distance Meta‐POPulation, a program to simulate changes in neutral and/or selection‐driven genotypes through time as a function of individual‐based movement, complex spatial population dynamics, and multiple and changing landscape drivers. Cost–Distance Meta‐POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.