Cooperative Fish and Wildlife Research Units Program: Georgia
Education, Research and Technical Assistance for Managing Our Natural Resources


Crawford, B. A., C. T. Moore, T. M. Norton, and J. C. Maerz. 2018. Integrated analysis for population estimation, management impact evaluation, and decision-making for a declining species. Biological Conservation 222:33-43. https://doi.org/10.1016/j.biocon.2018.03.023

Abstract

A challenge for making conservation decisions is predicting how wildlife populations respond to multiple, concurrent threats and potential management strategies, usually under substantial uncertainty. Integrated modeling approaches can improve estimation of demographic rates necessary for making predictions, even for rare or cryptic species with sparse data, but their use in management applications is limited. We developed integrated models for a population of diamondback terrapins (Malaclemys terrapin) impacted by road-associated threats to (i) jointly estimate demographic rates from two mark-recapture datasets, while directly estimating road mortality and the impact of management actions deployed during the study; and (ii) project the population using population viability analysis under simulated management strategies to inform decision-making. Without management, population extirpation was nearly certain due to demographic impacts of road mortality, predators, and vegetation. Installation of novel flashing signage increased survival of terrapins that crossed roads by 30%. Signage, along with small roadside barriers installed during the study, increased population persistence probability, but the population was still predicted to decline. Management strategies that included actions targeting multiple threats and demographic rates resulted in the highest persistence probability, and roadside barriers, which increased adult survival, were predicted to increase persistence more than other actions. Our results support earlier findings showing mitigation of multiple threats is likely required to increase the viability of declining populations. Our approach illustrates how integrated models may be adapted to use limited data efficiently, represent system complexity, evaluate impacts of threats and management actions, and provide decision-relevant information for conservation of at-risk populations.