Making structured decisions for reintroduced populations in the face of uncertainty

Structured decision‐making (SDM) has become popular in natural resource management but has been underused in reintroduction programs. We illustrate how conservation managers can use SDM to guide management decisions after initial reintroduction, when data are still limited and uncertainty around vital rates estimates is high. In 2013, the hihi (Notiomystis cincta), an endangered New Zealand forest bird, was reintroduced to Bushy Park (BP), a managed conservation reserve. High post‐release mortality in females led to the population remaining small after 2 years, raising the question of whether more females should be released. We built a model to evaluate three management alternatives, including no further translocation and translocations of 15 additional females (from the only possible source population) in either 2015 or 2016. The fundamental objectives identified were to maximize the number and persistence of female hihi in BP, minimize the impact on the source population, and minimize costs. Our decision analysis incorporated uncertainties in parameter estimation, model selection, and demographic stochasticity. It produced distributions of final scores for each management alternative based on population projections for both the BP population and source population, and objective weights assigned by stakeholders. Although the distributions of final scores overlapped greatly, the “no translocation” alternative was largely stochastically dominant over other management options, that is, it was clearly the best choice in most projections and the choice was ambiguous in the remaining projections. The decision was also unaffected by variation in stakeholder values. Although the underlying modeling was complex, the output provided a simple visualization of outcomes that allowed the recovery group to make an informed decision (no further translocation) that fully considered the uncertainties

Using Bayesian mark-recapture modelling to quantify the strength and duration of post-release effects in reintroduced populations

Translocated animals often suffer elevated mortality during some acclimation period after release. Such post-release effects must be accounted for when estimating normal survival rates and therefore predicting population persistence. The standard approach for doing this is to nominate a fixed acclimation period, and either i) exclude survival data over that period, or ii) use model selection criteria to test whether survival differs over that period. We present a more flexible approach where the acclimation period is treated as unknown and is estimated simultaneously with the pre- and post-acclimation survival probabilities. We illustrate this approach using survival data for six reintroduced populations involving three New Zealand forest bird species. Analyses of the complete data sets (22–73 surveys conducted over 4–14 years) indicated that significant post-release effects occurred in at least one sex in five of the six populations, with 30–84% mortality attributable to post-release effects over acclimation periods ranging from 1 to 9 months. When we applied the approach to just the first year of data for each population, the estimated normal survival rates were consistent with those obtained from the complete data sets, and always at least as accurate as our previous approach of excluding data up to the next breeding season after translocation. The flexible approach therefore appears to be effective for accounting for post-release effects in survival estimation, and is beneficial in quantifying both the strength and duration of those effects so that pre- and post-release management strategies are better informed