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Research Highlight: Christian, M., Oosthuizen, W. C., Bester, M. N., & de Bruyn, P. N. (2024). Robustly estimating the demographic contribution of immigration: Simulation, sensitivity analysis and seals. Journal of Animal Ecology. https://doi.org/10.1111/1365‐2656.14053. Immigration can have profound consequences for local population dynamics and demography, but collecting data to accurately quantifying it is challenging. The recent rise of integrated population models (IPMs) offers an alternative by making it possible to estimate immigration without the need for explicit data, and to quantify its contribution to population dynamics through transient Life Table Response Experiments (tLTREs). Simulation studies have, however, highlighted that this approach can be prone to bias and overestimation. In their new study, Christian et al. address one of the root causes of this issue by improving the estimation of time variation in vital rates and immigration using Gaussian processes in lieu of traditionally used temporal random effects. They demonstrate that IPM‐tLTRE frameworks with Gaussian processes produce more accurate and less biased estimates of immigration and its contribution to population dynamics and illustrate the applicability of this approach using a long‐term data set on elephant seals (Mirounga leonida). Results are validated with a simulation study and suggest that immigration of breeding females has been central for population recovery of elephant seals despite the species' high female site fidelity. Christian et al. thus present new insights into population regulation of long‐lived marine mammals and highlight the potential for using Gaussian process priors in IPMs. They also illustrate a suite of 'best practices' for state‐of‐the‐art IPM‐tLTRE analyses and provide an inspirational example for the kind of ecological modelling workflow that can be invaluable not just as a starting point for fellow ecologists picking up or improving their own IPM‐tLTRE analyses, but also for teaching and in contexts where model estimates are used for informing management and conservation decision‐making. [ABSTRACT FROM AUTHOR]

Many migratory species are in decline across their geographical ranges. Single‐population studies can provide important insights into drivers at a local scale, but effective conservation requires multi‐population perspectives. This is challenging because relevant data are often hard to consolidate, and state‐of‐the‐art analytical tools are typically tailored to specific datasets.We capitalized on a recent data harmonization initiative (SPI‐Birds) and linked it to a generalized modelling framework to identify the demographic and environmental drivers of large‐scale population decline in migratory pied flycatchers (Ficedula hypoleuca) breeding across Britain.We implemented a generalized integrated population model (IPM) to estimate age‐specific vital rates, including their dependency on environmental conditions, and total and breeding population size of pied flycatchers using long‐term (34–64 years) monitoring data from seven locations representative of the British breeding range. We then quantified the relative contributions of different vital rates and population structure to changes in short‐ and long‐term population growth rate using transient life table response experiments (LTREs).Substantial covariation in population sizes across breeding locations suggested that change was the result of large‐scale drivers. This was supported by LTRE analyses, which attributed past changes in short‐term population growth rates and long‐term population trends primarily to variation in annual survival and dispersal dynamics, which largely act during migration and/or nonbreeding season. Contributions of variation in local reproductive parameters were small in comparison, despite sensitivity to local temperature and rainfall within the breeding period.We show that both short‐ and long‐term population changes of British breeding pied flycatchers are likely linked to factors acting during migration and in nonbreeding areas, where future research should be prioritized. We illustrate the potential of multi‐population analyses for informing management at (inter)national scales and highlight the importance of data standardization, generalized and accessible analytical tools, and reproducible workflows to achieve them. [ABSTRACT FROM AUTHOR]

Climate change has different and sometimes divergent effects on terrestrial and marine food webs, and in coastal ecosystems, these effects are tightly interlinked. Responses of opportunistic coastal predators and scavengers to climate change may thus be complex and potentially highly flexible, and can simultaneously serve as indicators of, and have profound impacts on, lower trophic levels. Gaining mechanistic understanding of these responses is therefore important, but often not feasible due to lack of long‐term data from marked individuals. Here, we used a Bayesian integrated population model (IPM) to elucidate the effects of arctic warming and concurrent changes in terrestrial and marine resource availability on population dynamics of the opportunistic arctic fox (Vulpes lagopus) in Svalbard. Joint analysis of four types of data (den survey, age‐at‐harvest, placental scars, mark‐recovery) revealed relatively stable population size and age structure over the last 22 yr (1997–2019) despite rapid environmental change linked to climate warming. This was related to the fact that terrestrial resources (reindeer carcasses, geese) became more abundant while the availability of marine resources (seal pups/carrion) decreased, and was driven by divergent trends in different vital rates (e.g., increased pregnancy rate but decreased pup survival). Balanced contributions of survival vs. reproduction and of immigration vs. local demography further stabilized population size. Our study thus sheds light on the mechanisms underlying population dynamics of opportunistic carnivores exploiting terrestrial and marine resources and suggests that exploitation of resources across different ecosystems can buffer predators against climate change. Additionally, it highlights the large potential of IPMs as tools to understand and predict the effects of environmental change on wildlife populations, even when data on marked individuals are sparse. [ABSTRACT FROM AUTHOR]

Evidence‐based management of natural populations under strong human influence frequently requires not only estimates of survival but also knowledge about how much mortality is due to anthropogenic vs. natural causes. This is the case particularly when individuals vary in their vulnerability to different causes of mortality due to traits, life history stages, or locations.Here, we estimated harvest and background (other cause) mortality of landlocked migratory salmonids over half a century. In doing so, we quantified among‐individual variation in vulnerability to cause‐specific mortality resulting from differences in body size and spawning location relative to a hydropower dam.We constructed a multistate mark–recapture model to estimate harvest and background mortality hazard rates as functions of a discrete state (spawning location) and an individual time‐varying covariate (body size). We further accounted for among‐year variation in mortality and migratory behaviour and fit the model to a unique 50‐year time series of mark–recapture–recovery data on brown trout (Salmo trutta) in Norway.Harvest mortality was highest for intermediate‐sized trout, and outweighed background mortality for most of the observed size range. Background mortality decreased with body size for trout spawning above the dam and increased for those spawning below. All vital rates varied substantially over time, but a trend was evident only in estimates of fishers' reporting rate, which decreased from over 50% to less than 10% throughout the study period.We highlight the importance of body size for cause‐specific mortality and demonstrate how this can be estimated using a novel hazard rate parameterization for mark–recapture models. Our approach allows estimating effects of individual traits and environment on cause‐specific mortality without confounding, and provides an intuitive way to estimate temporal patterns within and correlation among different mortality sources. [ABSTRACT FROM AUTHOR]

Interactions between density and environmental conditions have important effects on vital rates and consequently on population dynamics and can take complex pathways in species whose demography is strongly influenced by social context, such as the African lion, Panthera leo. In populations of such species, the response of vital rates to density can vary depending on the social structure (e.g. effects of group size or composition). However, studies assessing density dependence in populations of lions and other social species have seldom considered the effects of multiple socially explicit measures of density, and—more particularly for lions—of nomadic males. Additionally, vital‐rate responses to interactions between the environment and various measures of density remain largely uninvestigated. To fill these knowledge gaps, we aimed to understand how a socially and spatially explicit consideration of density (i.e. at the local scale) and its interaction with environmental seasonality affect vital rates of lions in the Serengeti National Park, Tanzania. We used a Bayesian multistate capture–recapture model and Bayesian generalized linear mixed models to estimate lion stage‐specific survival and between‐stage transition rates, as well as reproduction probability and recruitment, while testing for season‐specific effects of density measures at the group and home‐range levels. We found evidence for several such effects. For example, resident‐male survival increased more strongly with coalition size in the dry season compared with the wet season, and adult‐female abundance affected subadult survival negatively in the wet season, but positively in the dry season. Additionally, while our models showed no effect of nomadic males on adult‐female survival, they revealed strong effects of nomads on key processes such as reproduction and takeover dynamics. Therefore, our results highlight the importance of accounting for seasonality and social context when assessing the effects of density on vital rates of Serengeti lions and of social species more generally. [ABSTRACT FROM AUTHOR]