A novel dispersal algorithm in individual-based, spatially-explicit Population Viability Analysis: A new role for genetic measures in model testing?. (June 2015) - Lethbridge, Mark R.; Strauss, Jessica C.
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 ). Highlights: Spatial PVA employs a novel stochastic dispersal algorithm that models how animals move through habitat patches. The software includes a non-random breeding algorithm that simulates pedigrees and inbreeding depression. Can be used as a decision planning tool for exploring likely population outcomes under a range of different management scenarios.