Monitoring is an essential part of reintroduction programs, but many years of data may be needed to obtain reliable population projections. This duration can potentially be reduced by incorporating prior information on expected vital rates (survival and fecundity) when making inferences from monitoring data. The prior distributions for these parameters can be derived from data for previous reintroductions, but it is important to account for site‐to‐site variation. We evaluated whether such informative priors improved our ability to estimate the finite rate of increase (λ) of the North Island robin (Petroica longipes) population reintroduced to Tawharanui Regional Park, New Zealand. We assessed how precision improved with each year of postrelease data added, comparing models that used informative or uninformative priors. The population grew from about 22 to 80 individuals from 2007 to 2016, with λ estimated to be 1.23 if density dependence was included in the model and 1.13 otherwise. Under either model, 7 years of data were required before the lower 95% credible limit for λ was > 1, giving confidence that the population would persist. The informative priors did not reduce this requirement. Data‐derived priors are useful before reintroduction because they allow λ to be estimated in advance. However, in the case examined here, the value of the priors was overwhelmed once site‐specific monitoring data became available. The Bayesian method presented is logical for reintroduced populations. It allows prior information (used to inform prerelease decisions) to be integrated with postrelease monitoring. This makes full use of the data for ongoing management decisions. However, if the priors properly account for site‐to‐site variation, they may have little predictive value compared with the site‐specific data. This value will depend on the degree of site‐to‐site variation as well as the quality of the data.

Long-term data are needed to assess the impact of management initiatives such as mammalian predator-exclusion fences, but long-term monitoring programmes can be difficult to maintain. We used annual line transect distance sampling data collected by undergraduate students to model trends in native bird densities at Bushy Park, New Zealand, from 2002 to 2018, including 14 years of data collection following the installation of a predator-exclusion fence in 2005. We corrected for known breaches to the distance sampling assumptions for North Island robins/toutouwai (Petroica longipes) by calibrating raw transect counts with mark-recapture data. Two of the three reintroduced species, North Island robins and North Island saddlebacks/ tieke (Philesturnus rufusater), showed marked increases in density, and were the numerically dominant species in Bushy Park by the end of the study. The distance data for hihi (Notiomystis cincta), which were reintroduced in 2013, were too sparse to show a trend. Comparison with independent data for these three species showed that uncorrected distance data greatly overestimated densities of robins (6-fold) and hihi (9-fold) but were accurate for saddlebacks. The methodology used to calibrate North Island robin estimates could be applied to hihi if the current intensive monitoring for that species is discontinued. In contrast to the reintroduced species, densities of the original bird populations all remained relatively constant (kereru Hemiphaga novaeseelandiae, tomtit Petroica macrocephala) or declined (grey warbler/riroriro Gerygone igata, fantail/piwakawaka Rhipidura fuliginosa, silvereye/tauhou Zosterops lateralis) after the installation of the fence, or had too few observations to estimate densities (tui Prosthemadera novaeseelandiae, bellbird/korimako Anthornis melanura). This study demonstrates that simple low-intensity monitoring data collected by non-experts can provide useful information on long-term trends in bird densities. However, we stress the importance of including uncertainty in estimates when inferring population trends, and the potential need to calibrate distance data with independent density estimates.

Detailed data on juvenile survival are rare in the literature. Although many studies estimate recruitment, if you cannot distinguish between permanent dispersal and mortality, the management implications for a population may be unclear. We estimated juvenile survival in a reintroduced North Island robin (Petroica longipes) population in a protected sanctuary surrounded by an unprotected landscape where the species is extirpated. The population has had marginal population growth due to poor recruitment so we modeled 3 types of data (resighting of fledglings, radio‐telemetry of independent juveniles, resighting of adults) in an integrated framework to determine the life stages where high mortality was occurring, and to distinguish mortality from dispersal. Approximately 16% of birds that fledged (n = 109) were present at the start of the next breeding season, consistent with recruitment rates from previous years. Low survival in the first 6 weeks after fledging was the primary cause of poor recruitment. Only 50% survived to independence (4 weeks after fledging), and 18% survived to the end of the radio‐tracking period (14 weeks), after which juvenile survival matched adult survival. No dispersal from the sanctuary occurred during the radio‐tracking period. Juveniles moved between adjacent forest fragments within the sanctuary, but did not leave the sanctuary. This information, which demonstrates the importance of distinguishing between natal mortality and dispersal, is important for ongoing management of the site and selection of future reintroduction sites for this species. © 2019 The Wildlife Society.