Combining prior predictions with post-release data to guide ongoing management of a reintroduced population : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Conservation Biology at Massey University, Palmerston North, New Zealand - Macdermid, Kara (Massey University, 2023)
Reintroductions have generally had a low success rate, and lack of monitoring has meant that for most species few data have been available to inform decisions. To help reduce uncertainties in these decisions, adaptive management (AM) provides a framework for improving management based on new information. I used an AM approach for a reintroduced toutouwai (Petroica longipes) population in Turitea Reserve. Prior to the reintroduction, monitoring data from 10 previous reintroductions were combined into a Bayesian hierarchical model to make population predictions based on the site’s rat density and habitat connectivity to the surrounding landscape. This prior model predicted that population establishment and growth were likely, so the reintroduction was conducted. I monitored the population over its first breeding season to collect site-specific survival and fecundity data. These new data were combined with the prior model to create an updated model to improve predictions. Turitea data showed lower adult survival and fecundity compared to the prior model predictions. The combined model estimated a finite rate of increase (l) of 0.97, compared to 1.33 from the prior model, suggesting that persistence was less likely than originally predicted. These updated predictions were used to guide the first post-release management decisions following the end of the first breeding season. As rats are known to impact toutouwai fecundity and female survival, I created a set of alternative management options for different rat control options and modelled population predictions for each of these alternatives. Based on these predictions, stakeholders chose the alternative that best achieved the fundamental objectives of the reintroduction – population growth and minimal cost – which was increasing rat control in a core area around the toutouwai territories. This alternative was implemented before the 2022/2023 breeding season to improve survival and breeding success. I continued to monitor the population over the 2022/2023 breeding season so that models could be updated again once the season was over, continuing the AM cycle. Initial analysis of the 2022/2023 nest success suggested that the management change had a positive effect, with the probability of a nest succeeding nearly doubling compared to the previous season. This project highlights the importance of monitoring reintroduced populations to be able to improve reintroduction outcomes through informed management. I recommend using AM to manage reintroduced populations so that better outcomes can be achieved, and the knowledge gained can also inform future reintroduction decisions.
Keywords: 310307 Population ecology; 410401 Conservation and biodiversity