Adaptive Harvesting of Source Populations for Translocation: a Case Study with New Zealand Robins

Abstract

Reintroductions are conducted frequently throughout the world, and some source populations are harvested repeatedly to provide animals for translocation. The responses of these source populations to harvest should be monitored, and the resulting data used to refine population models will guide management. After North Island Robins ( Petroica longipes) were reintroduced to Tiritiri Matangi, New Zealand, in 1992, the population became a source for robins for additional reintroductions in the region. We constructed an initial model for the population on the basis of the data collected from 1992 to 1998 and used it to predict the population's response to the first translocation of robins from the island in the autumn (March) of 1999. We then analyzed postharvest data on survival (with mark-recapture analysis) and fecundity (with generalized linear-mixed modeling) to reassess and update the model. In the initial model, juvenile survival was assumed to be limited by the island's fixed carrying capacity, with excess juveniles dying over winter; hence, the autumn harvest was expected to cause an immediate increase in juvenile survival. In postharvest analysis, however, most juvenile mortality occurred before autumn, and the best predictor of juvenile survival was the number of breeding pairs present the previous spring (start of the breeding season). Consequently, the updated population model predicted sustainable harvest levels about half those given by the initial model, and this model has been used to guide the number of individuals removed for two subsequent translocations. The ongoing development of the model has been invaluable for assuring conservation authorities that the population is not being unsustainably harvested, which has allowed surplus animals to be used to establish new populations. Our case study illustrates the value of an adaptive approach to harvesting source populations for reintroduction and illustrates the value of such studies for understanding the density-dependent mechanisms regulating populations.