Since the mid 1990s, the number of black brant (Branta bernicla nigricans; brant) nests on the Yukon-Kuskokwim Delta (YKD), Alaska, USA, the historically predominant breeding area of brant, has declined steadily. This has caused researchers and managers to question if arctic breeding populations can compensate for the reduction in brant nests on the YKD. An important component of the assessment of brant population dynamics is having current estimates of first-year and adult survival. We banded brant at 4 locations in Arctic Alaska and western Canada, and at 1 location in the subarctic, the Tutakoke River (TR) colony on the YKD, 1990-2015. We used joint live and dead mark-recapture models to estimate first-year and adult (!1 yr old) survival of brant. We also used band recovery rates from a Brownie model to assess temporal trends in band recovery rates of adult brant. First-year survival of brant hatched at TR declined from approximately 0.60 to <0.20 and, although first-year survival generally was higher for goslings marked in the Arctic, their survival declined from approximately 0.70 in the early 1990s to 0.45 in the 2010s. Annual survival of adult females decreased from an average of 0.881 (95% CI ¼ 0.877-0.885) to 0.822 (95% CI ¼ 0.815-0.829) at TR and from 0.851 (95% CI ¼ 0.843-0.860) to 0.821 (95% CI ¼ 0.805-0.836) in the Arctic, from 1990 to 2014. Band recovery rates of adults generally were <1.25% until the last several years of study, when they reached 3.5%. Although the current harvest rates may be partially additive to natural mortality, we do not believe that harvest is the main influence on the declines in survival. The general decline in survival rates of brant breeding across a large geographic area may be influenced by a reduction in the quality of migration and wintering ground habitats. We suggest an analysis of seasonal survival of brant to test the hypothesis that declining habitat quality on wintering or spring migration areas is reducing survival. Our results suggest that the number of breeding pairs at TR will continue to decline and also brings into question the ability of arctic breeding populations to grow at a rate necessary to offset the declines on the YKD. Researchers should continue to closely monitor survival and harvest rates of brant, and assess methods currently used to monitor their abundance. Ó 2017 The Wildlife Society.KEY WORDS band recovery rates, Branta bernicla nigricans, Brownie models, joint live and dead mark-recapture, population dynamics, Seber reporting rate.

Integrated population models (IPMs) have become increasingly popular for the modelling of populations, as investigators seek to combine survey and demographic data to understand processes governing population dynamics. These models are particularly useful for identifying and exploring knowledge gaps within life histories, because they allow investigators to estimate biologically meaningful parameters, such as immigration or reproduction, that were previously unidentifiable without additional data. As IPMs have been developed relatively recently, there is much to learn about model behaviour. Behaviour of parameters, such as estimates near boundaries, and the consequences of varying degrees of dependency among datasets, has been explored. However, the reliability of parameter estimates remains underexamined, particularly when models include parameters that are not identifiable from one data source, but are indirectly identifiable from multiple datasets and a presumed model structure, such as the estimation of immigration using capture‐recapture, fecundity and count data, combined with a life‐history model. To examine the behaviour of model parameter estimates, we simulated stable populations closed to immigration and emigration. We simulated two scenarios that might induce error into survival estimates: marker induced bias in the capture–mark–recapture data and heterogeneity in the mortality process. We subsequently fit capture–mark–recapture, state‐space and fecundity models, as well as IPMs that estimated additional parameters. Simulation results suggested that when model assumptions are violated, estimation of additional, previously unidentifiable, parameters using IPMs may be extremely sensitive to these violations of model assumption. For example, when annual marker loss was simulated, estimates of survival rates were low and estimates of immigration rate from an IPM were high. When heterogeneity in the mortality process was induced, there were substantial relative differences between the medians of posterior distributions and truth for juvenile survival and fecundity. Our results have important implications for biological inference when using IPMs, as well as future model development and implementation. Specifically, using multiple datasets to identify additional parameters resulted in the posterior distributions of additional parameters directly reflecting the effects of the violations of model assumptions in integrated modelling frameworks. We suggest that investigators interpret posterior distributions of these parameters as a combination of biological process and systematic error.

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