Extinction of canid populations by inbreeding depression under stochastic environments in Southwestern Goiás State: a simulation study
Genetics and Molecular Biology
A frequently addressed question in conservation biology is what is the chance of survival for a population for a given number of years under certain conditions of habitat loss and human activities. This can be estimated through an integrated analysis of genetic, demographic and landscape processes, which allows the prediction of more realistic and precise models of population persistence. In this study, we modeled extinction in stochastic environments under inbreeding depression for two canid
... ion for two canid species, the maned wolf (Chrysocyon brachiurus) and the crab-eating fox (Cerdocyon thous), in southwest Goiás State. Genetic parameters were obtained from six microsattelite loci (Short Tandem Repeats -STR), which allowed estimates of inbreeding levels and of the effective population size under a stepwise mutation model based on heterozygosis. The simulations included twelve alternative scenarios with varying rates of habitat loss, magnitude of population fluctuation and initial inbreeding levels. ANOVA analyses of the simulation results showed that times to extinction were better explained by demographic parameters. Times to extinction ranged from 352 to 844, in the worst and best scenario, respectively, for the large-bodied maned wolf. For the small-bodied crab-eating fox, these same estimates were 422 and 974 years. Simulations results are within the expectation based on knowledge about species' life history, genetics and demography. They suggest that populations can persist through a reasonable time (i.e., more than 200 years) even under the worst demographic scenario. Our analyses are a starting point for a more focused evaluation of persistence in these populations. Our results can be used in future research aiming at obtaining better estimates of parameters that may, in turn, be used to achieve more appropriate and realist population viability models at a regional scale.