Stochastic simulation modelling of southern Great Barrier Reef green turtle population dynamics

Abstract

A stochastic simulation model was developed for the southern Great Barrier Reef (sGBR) green sea turtle stock to foster better insight into local population dynamics and to assess the risk of harvesting on long-term stock viability. The model was ageclass-structured with time-varying, nonlinear and stochastic demographic processes that were parameterised using recent findings on sex- and ageclass-specific growth and survivorship and female breeding behaviour subject to environmental stochasticity. Monte Carlo based uncertainty analysis was used to estimate population growth given demographic parameters subject to sampling error and environmental stochasticity. Model validity was based on replication of stock reference behaviours with sensitivity evaluated using parameter perturbation and Monte Carlo simulation within a fractional factorial sampling design. Fertility and adult survival were the most important high level parameters affecting population growth, where fertility is a function of fecundity and temporal variability in breeding likelihood. A dynamic stochastic form of the model was then used to evaluate stock viability given various turtle harvesting scenarios. It was found, given model assumptions, that even limited turtle harvesting would result in the sGBR stock being categorised, as vulnerable under IUCN criteria for listing of threatened species. It is apparent that extensive harvesting of either eggs or turtles is probably not a prudent management policy, if the long-term viability of the sGBR green sea turtle stock is the primary conservation objective.