Simulating Demography, Monitoring, and Management Decisions to Evaluate Adaptive Management Strategies for Endangered Species

Abstract

Adaptive management (AM) remains underused in conservation, partly because optimization-based approaches require real-world problems to be substantially simplified. We present an approach to AM based in management strategy evaluation, a method used largely in fisheries. Managers define objectives and nominate alternative adaptive strategies, whose future performance is simulated by integrating ecological, learning and decision processes. We applied this approach to conservation of hihi (Notiomystis cincta) across Aotearoa-New Zealand. For multiple extant and prospective hihi populations, we jointly simulated demographic trends, monitoring, estimation, and decisions including translocations and supplementary feeding. Results confirmed that food supplementation assisted recovery, but was more intensive and expensive. Over 20 years, actively pursuing learning, for example by removing food from populations, provided little benefit. Recovery group members supported continuing current management or increasing priority on existing populations before reintroducing new populations. Our simulation-based approach can complement formal optimization-based approaches and improve AM uptake, particularly for programs involving many complex and coordinated decisions.