A novel dispersal algorithm in individual-based, spatially-explicit Population Viability Analysis: A new role for genetic measures in model testing?
Authored by Mark R Lethbridge, Jessica C Strauss
Date Published: 2015
DOI: 10.1016/j.envsoft.2015.02.002
Sponsors:
No sponsors listed
Platforms:
C++
C
Model Documentation:
Other Narrative
Flow charts
Mathematical description
Model Code URLs:
Model code not found
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). (C) 2015 Elsevier Ltd. All rights reserved.
Tags
Simulation
Conservation
Metapopulation
landscape genetics
Climate-change
Sensitivity-analysis
Approximate bayesian computation
Petrogale-xanthopus gray
Footed
rock-wallaby
Extinction risk