Abstract We describe a new population viability tool: Spatial PVA. Spatial \PVA\ is an individual-based spatially-explicit \PVA\ application which employs a novel stochastic dispersal algorithm that models how animals move through habitat patches. It also includes a non-random breeding algorithm that simulates pedigrees and inbreeding depression. The model repeatedly steps through annual cycles of chance environmental, dispersal and demographic events for a specified time period. We provide a case study to demonstrate how one can compare simulated kinship coefficients with sampled genetic data to test model assumptions and inputs. We also provide a translocation example for an Australian rangelands species, the Yellow-footed Rock-wallaby (Petrogale xanthopus xanthopus).
%0 Journal Article
%1 lethbridge2015novel
%A Lethbridge, Mark R.
%A Strauss, Jessica C.
%D 2015
%J Environmental Modelling & Software
%K PVA conservation_genetics methods pedigrees population_viability_analysis software wallabys
%P 83 - 97
%R http://dx.doi.org/10.1016/j.envsoft.2015.02.002
%T A novel dispersal algorithm in individual-based, spatially-explicit Population Viability Analysis: A new role for genetic measures in model testing?
%U http://www.sciencedirect.com/science/article/pii/S136481521500050X
%V 68
%X Abstract We describe a new population viability tool: Spatial PVA. Spatial \PVA\ is an individual-based spatially-explicit \PVA\ application which employs a novel stochastic dispersal algorithm that models how animals move through habitat patches. It also includes a non-random breeding algorithm that simulates pedigrees and inbreeding depression. The model repeatedly steps through annual cycles of chance environmental, dispersal and demographic events for a specified time period. We provide a case study to demonstrate how one can compare simulated kinship coefficients with sampled genetic data to test model assumptions and inputs. We also provide a translocation example for an Australian rangelands species, the Yellow-footed Rock-wallaby (Petrogale xanthopus xanthopus).
@article{lethbridge2015novel,
abstract = {Abstract We describe a new population viability tool: Spatial PVA. Spatial \{PVA\} is an individual-based spatially-explicit \{PVA\} application which employs a novel stochastic dispersal algorithm that models how animals move through habitat patches. It also includes a non-random breeding algorithm that simulates pedigrees and inbreeding depression. The model repeatedly steps through annual cycles of chance environmental, dispersal and demographic events for a specified time period. We provide a case study to demonstrate how one can compare simulated kinship coefficients with sampled genetic data to test model assumptions and inputs. We also provide a translocation example for an Australian rangelands species, the Yellow-footed Rock-wallaby (Petrogale xanthopus xanthopus). },
added-at = {2015-11-19T07:06:18.000+0100},
author = {Lethbridge, Mark R. and Strauss, Jessica C.},
biburl = {https://www.bibsonomy.org/bibtex/2b1337167c27be1981460fae1413a53ee/peter.ralph},
doi = {http://dx.doi.org/10.1016/j.envsoft.2015.02.002},
interhash = {3dadbf735f6d8e7ffd58b017a6f19460},
intrahash = {b1337167c27be1981460fae1413a53ee},
issn = {1364-8152},
journal = {Environmental Modelling & Software },
keywords = {PVA conservation_genetics methods pedigrees population_viability_analysis software wallabys},
pages = {83 - 97},
timestamp = {2015-11-19T07:06:18.000+0100},
title = {A novel dispersal algorithm in individual-based, spatially-explicit Population Viability Analysis: A new role for genetic measures in model testing? },
url = {http://www.sciencedirect.com/science/article/pii/S136481521500050X},
volume = 68,
year = 2015
}