Sensitivity analysis for models of population viability Original Research Article

A method of sensitivity analysis for population viability models is presented that uses logistic regression to evaluate the importance of model parameters that influence the risks of extinction. This approach is used to evaluate the importance of fecundity parameters and the initial number of non-breeding birds in a stochastic stage-structured model of helmeted honeyeater Lichenostomus melanops cassidix population dynamics. The regression analysis indicates which model parameters have the greatest impact on the risk of population decline. The results demonstrate that a simple expression containing the parameters of the model can encapsulate predictions of risk. This technique is proposed as an efficient alternative method of sensitivity analysis for population viability models. Of four fecundity parameters, the mean fecundity of intact pairs had the greatest influence on the risks faced by the helmeted honeyeater population. Mean fecundity of split pairs and the sex ratio of offspring were also important parameters. Over the range of parameters considered in this paper, environmental variation in fecundity and the initial number of non-breeding birds had little influence on the risks of decline. The importance of interactions between parameters was analysed.