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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]

Many animal populations are subject to hunting or fishing in the wild. Detailed knowledge of demographic parameters (e.g. survival, reproduction) and temporal dynamics of such populations is crucial for sustainable management. Despite their relevance for management decisions, structure and size of exploited populations are often not known, and data limited. Recently, joint analysis of different types of demographic data, such as population counts, reproductive data and capture–mark–recapture data, within integrated population models (IPMs) has gained much popularity as it may allow estimating population size and structure, as well as key demographic rates, while fully accounting for uncertainty. IPMs built so far for exploited populations have typically been built as age‐structured population models. However, the age of harvested individuals is usually difficult and/or costly to assess and therefore often not available. Here, we introduce an IPM structured by body size classes, which allows making efficient use of data commonly available in exploited populations for which accurate information on age is often missing. The model jointly analyzes size‐at‐harvest data, capture–mark–recapture–recovery data and reproduction data from necropsies, and we illustrate its applicability in a case study involving heavily hunted wild boar. This species has increased in abundance over the last decades despite intense harvest, and the IPM analysis provides insights into the roles of natural mortality, body growth, maturation schedules and reproductive output in compensating for the loss of individuals to hunting. Early maturation and high reproductive output contributed to wild boar population persistence despite a strong hunting pressure. We thus demonstrate the potential of size‐class‐structured IPMs as tools to investigate the dynamics of exploited populations with limited information on age, and highlight both the applicability of this framework to other species and its potential for follow‐up analyses highly relevant to management. [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]

Population dynamics are the result of an interplay between extrinsic and intrinsic environmental drivers. Predicting the effects of environmental change on wildlife populations therefore requires a thorough understanding of the mechanisms through which different environmental drivers interact to generate changes in population size and structure.In this study, we disentangled the roles of temperature, food availability and population density in shaping short‐ and long‐term population dynamics of the African striped mouse, a small rodent inhabiting a semidesert with high intra‐ and interannual variation in environmental conditions.We parameterized a female‐only stage‐structured matrix population model with vital rates depending on temperature, food availability and population density, using monthly mark–recapture data from 1609 mice trapped over 9 years (2005–2014). We then applied perturbation analyses to determine relative strengths and demographic pathways of these drivers in affecting population dynamics. Furthermore, we used stochastic population projections to gain insights into how three different climate change scenarios might affect size, structure and persistence of this population.We identified food availability, acting through reproduction, as the main driver of changes in both short‐ and long‐term population dynamics. This mechanism was mediated by strong density feedbacks, which stabilized the population after high peaks and allowed it to recover from detrimental crashes. Density dependence thus buffered the population against environmental change, and even adverse climate change scenarios were predicted to have little effect on population persistence (extinction risk over 100 years <5%) despite leading to overall lower abundances.Explicitly linking environment–demography relationships to population dynamics allowed us to accurately capture past population dynamics. It further enabled establishing the roles and relative importances of extrinsic and intrinsic environmental drivers, and we conclude that doing this is essential when investigating impacts of climate change on wildlife populations. Small mammal populations are sensitive to their environment and strongly regulated by density. Using state‐of‐the‐art demographic models, the authors show not only that population dynamics of a semidesert rodent are buffered against environmental change by strong density feedbacks, but quantify through which demographic pathways this regulation works. [ABSTRACT FROM AUTHOR]

Abstract: Body size can have profound impacts on survival, movement, and reproductive schedules shaping individual fitness, making growth a central process in ecological and evolutionary dynamics. Realized growth is the result of a complex interplay between life history schedules, individual variation, and environmental influences. Integrating all of these aspects into growth models is methodologically difficult, depends on the availability of repeated measurements of identifiable individuals, and consequently represents a major challenge in particular for natural populations. Using a unique 30‐yr time series of individual length measurements inferred from scale year rings of wild brown trout, we develop a Bayesian hierarchical model to estimate individual growth trajectories in temporally and spatially varying environments. We reveal a gradual decrease in average juvenile growth, which has carried over to adult life and contributed to decreasing sizes observed at the population level. Commonly studied environmental drivers like temperature and water flow did not explain much of this trend and overall persistent and among‐year individual variation dwarfed temporal variation in growth patterns. Our model and results are relevant to a wide range of questions in ecology and evolution requiring a detailed understanding of growth patterns, including conservation and management of many size‐structured populations. [ABSTRACT FROM AUTHOR]

Exogenous and endogenous environmental factors can have simultaneous additive as well as interacting effects on life-history traits. Ignoring such interactions can lead to a biased understanding of variability in demographic rates and consequently population dynamics. These interactions have been the focus of decades-long debates on the mechanisms underlying small mammal population fluctuations. They have often been studied indirectly through seasonal effects, but studies considering them directly and more mechanistically are rare. We investigated the joint effects of exogenous (temperature, food availability) and endogenous (population density) factors on the demographic rates of a group-living diurnal rodent, the African striped mouse Rhabdomys pumilio using nine-year mark-recapture data from a population in the Succulent Karoo, South Africa. In general, higher temperatures and lower food availability were associated with higher survival, whereas high population densities were either beneficial or detrimental to survival depending on interacting food availability. High reproductive rates were related to lower temperatures, higher food availability and lower population density, and interactions among environmental factors mediated the strength of these relationships. Our study highlights the complex ways in which different environmental factors can interact to shape demographic rates and emphasizes the importance of explicitly including interactions among exogenous and endogenous factors into studies of population dynamics. [ABSTRACT FROM AUTHOR]

Despite much criticism, black-or-white null-hypothesis significance testing with an arbitrary P -value cutoff still is the standard way to report scientific findings. One obstacle to progress is likely a lack of knowledge about suitable alternatives. Here, we suggest language of evidence that allows for a more nuanced approach to communicate scientific findings as a simple and intuitive alternative to statistical significance testing. We provide examples for rewriting results sections in research papers accordingly. Language of evidence has previously been suggested in medical statistics, and it is consistent with reporting approaches of international research networks, like the Intergovernmental Panel on Climate Change, for example. Instead of re-inventing the wheel, ecology and evolution might benefit from adopting some of the 'good practices' that exist in other fields. It has been known for decades that there are severe problems associated with null-hypothesis significance testing (NHST) based on arbitrary P -value thresholds (e.g., P = 0.05). A small literature review indicates that much of the current research in ecology and evolution is still disregarding the warnings and frequently relies on binary decisions based on P -values to report statistical significance. While the P -value itself is a sound mathematical concept that does not have to be banned when used correctly, we should stop using the term 'statistical significance' and replace it with a gradual notion of evidence. Language matters and 'evidence' is an intuitive concept that honestly reflects what the data really tell us. To facilitate rewriting scientific results, we offer generic examples of how to translate (binary) significance language into a gradual language of evidence. [ABSTRACT FROM AUTHOR]

The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long‐term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad‐scale global issues (e.g. climate change).To solve data integration issues and enable a new scale of ecological and evolutionary research based on long‐term studies of birds, we have created the SPI‐Birds Network and Database (www.spibirds.org)—a large‐scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI‐Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting.SPI‐Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community‐derived data and meta‐data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta‐data language).The encouraging community involvement stems from SPI‐Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI‐Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community‐specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much‐needed large‐scale ecological data integration. [ABSTRACT FROM AUTHOR]

Evaluating the effectiveness of conservation actions is challenging for migratory species because a population can be impacted anywhere along its route. Conservation actions for the critically endangered Fennoscandian lesser white-fronted goose population include culling of red foxes in the breeding area and habitat improvements and reduction of illegal hunting in the non-breeding areas. One goal of the predator control strategy is to prevent adult birds from using an autumn migration route through western Asia, where mortality is believed to be higher than on the migration route through eastern Europe. We used 23 years of count data obtained at different staging areas to parameterize a seasonal state-space model describing the full-annual cycle dynamics of this population and evaluate whether the recent population recovery was linked to these conservation efforts. The results did not provide evidence that predator control influenced population recovery, as survival on the European route did not appear higher than on the allegedly riskier Asian route. However, adult survival at staging areas on both routes and at wintering sites may have improved in the last decade, suggesting a positive effect of the other conservation initiatives. These results emphasize the importance of including the non-breeding dynamics in population assessments of migratory species and highlight the challenge of evaluating the efficacy of separate conservation actions when a proper experimental design is unfeasible. Our study, which is a unique case of cross-national, coordinated conservation efforts, exemplifies how to model complex population dynamics to assess the influence of costly conservation initiatives. • The Fennoscandian population of lesser white-fronted goose is endangered and managed. • No evidence that predator control in the breeding areas influenced population recovery. • Conservation actions in non-breeding areas may have been beneficial. • Non-breeding dynamics should be included in assessments of migratory species. [ABSTRACT FROM AUTHOR]