Evaluating mark–resight survey design performance using simulation: A case study of endangered Steller sea lions

Effective monitoring is fundamental to estimating wildlife population parameters with a level of accuracy and precision that is adequate to inform management decisions. However, managers must balance trade-offs between the costs of monitoring and the resulting data quality to identify cost-effective monitoring survey designs. As such, evaluating the expected performance of monitoring surveys relative to monitoring objectives prior to survey implementation is critical. In this study, we present a simulation framework for examining the accuracy and precision of age-specific survival estimates and the probability of detecting a change in survival within the context of mark–resight monitoring programs. We consider 90 survey designs that vary across marked cohort size, marking frequency, study duration, and resight probability (i.e., detection of marked individuals). We apply this approach to the design of a monitoring program for Steller sea lions (Eumetopias jubatus), which is complicated by heterogeneity in rookery accessibility, population sizes, and abundance trends across the species' range. To identify cost-effective survey designs in the absence of actual survey costs, we evaluated performance with respect to a relative-costs schema. Our results highlight survey designs that reliably meet pre-defined precision targets, with precision and accuracy strongly affected by marked cohort size, marking frequency, and study duration. We found that historical mark–resight survey effort for Steller sea lions has been sufficient to reliably achieve precision targets for younger age class survival probabilities only for rookeries where abundance has been stable or increasing. In contrast, the probability of achieving survival estimates with target levels of precision at rookeries where abundance has been declining is low (<25%) due to smaller marked cohort sizes, less frequent marking at remote sites, and fewer years of available data. Our results indicate that the precision of survival estimates for subpopulations of conservation concern can be improved by longer-term monitoring, although the constraints of monitoring small populations may limit the ability of biologists to detect changes in population dynamics on management-relevant time horizons. Our survey design evaluation framework can be applied in a variety of contexts to assist natural resource managers in developing cost-effective monitoring programs.