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Abstract BackgroundSince the 1980s, Pacific Black Brant (Branta bernicla nigricans, hereafter brant) have shifted their winter distribution northward from Mexico to Alaska (approximately 4500 km) with changes in climate. Alongside this shift, the primary breeding population of brant has declined. To understand the population-level implications of the changing migration strategy of brant, it is important to connect movement and demographic data. Our objectives were to calculate migratory connectivity, a measure of spatial and temporal overlap during the non-breeding period, for Arctic and subarctic breeding populations of brant, and to determine if variation in migration strategies affected nesting phenology and nest survival. MethodsWe derived a migratory network using light-level geolocator migration tracks from an Arctic site (Colville River Delta) and a subarctic site (Tutakoke River) in Alaska. Using this network, we quantified the migratory connectivity of the two populations during the winter. We also compared nest success rates among brant that used different combinations of winter sites and breeding sites. ResultsThe two breeding populations were well mixed during the winter, as indicated by a migratory connectivity score close to 0 (− 0.06) at the primary wintering sites of Izembek Lagoon, Alaska (n = 11 brant) and Baja California, Mexico (n = 48). However, Arctic birds were more likely to migrate the shorter distance to Izembek (transition probability = 0.24) compared to subarctic birds (transition probability = 0.09). Nest survival for both breeding populations was relatively high (0.88–0.92), and we did not detect an effect of wintering site on nest success the following year. ConclusionsNest survival of brant did not differ among brant that used wintering sites despite a 4500 km difference in migration distances. Our results also suggested that the growing Arctic breeding population is unlikely to compensate for declines in the larger breeding population of brant in the subarctic. However, this study took place in 2011–2014 and wintering at Izembek Lagoon may have greater implications for reproductive success under future climate conditions. 

Abstract Estimating correlations among demographic parameters is an important method in population ecology. A recent paper by Deane et al. (Ecology and Evolution13:e9847, 2023) attempted to explore the effects of different priors for covariance matrices on inference when using mark‐recovery data. Unfortunately, Deane et al. (2023) made a mistake when parameterizing some of their models. Rather than exploring the effects of different priors, they examined the effects of the use of incorrect equations on inference. In this manuscript, we clearly describe the mistake in Deane et al. (2023). We then demonstrate the use of an alternative and appropriate method and reach different conclusions regarding the effects of priors on inference. Consistent with other recent literature, informative inverse Wishart priors can lead to flawed inference, while vague priors on covariance matrix components have little impact when sample sizes are adequate. 

ABSTRACT It has recently been recognised that populations are rarely in demographic equilibrium, but rather in a ‘transient’ state. To examine how transient dynamics influence our empirical understanding of the links between changes in demographic rates and population growth, we conducted a 32‐year study of Columbian ground squirrels. The population increased rapidly for 10 years, followed by a 2‐year crash, and a gradual 19‐year recovery. Transient life table response experiment (LTRE) analysis showed that demographic stochasticity accounted for approximately one‐fourth of the variation in population growth, leaving the majority to be explained by environmental influences. These relatively small rodents appeared to have a slow pace of life. But unlike the general pattern for large mammals with slow life histories, ground squirrel survival did not exhibit low variation associated with environmental ‘buffering’; instead, survival varied substantially over time and contributed substantially (78%) to changes in abundance over the long‐term study, with minor contributions from reproduction and unstable stage structure. 

Abstract Identifying the specific environmental features and associated density‐dependent processes that limit population growth is central to both ecology and conservation. Comparative assessments of sympatric species allow for inference about how ecologically similar species differentially respond to their shared environment, which can be used to inform community‐level conservation strategies. Comparative assessments can nevertheless be complicated by interactions and feedback loops among the species in question. We developed an integrated population model based on 61 years of ecological data describing the demographic histories of Canvasbacks (Aythya valisineria) and Redheads (Aythya americana), two species of migratory diving ducks that utilize similar breeding habitats and affect each other's demography through interspecific nest parasitism. We combined this model with a transient life table response experiment to determine the extent that demographic rates, and their contributions to population growth, were similar between these two species. We found that demographic rates and, to a lesser extent, their contributions to population growth covaried between Canvasbacks and Redheads, but the trajectories of population abundances widely diverged between the two species during the end of the twentieth century due to inherent differences between the species life histories and sensitivities to both environmental variation and harvest pressure. We found that annual survival of both species increased during years of restrictive harvest regulations; however, recent harvest pressure on female Canvasbacks may be contributing to population declines. Despite periodic, and often dramatic, increases in breeding abundance during wet years, the number of breeding Canvasbacks declined by 13% whereas the number of breeding Redheads has increased by 37% since 1961. Reductions in harvest pressure and improvements in submerged aquatic vegetation throughout the wintering grounds have mediated the extent to which populations of both species contracted during dry years in the Prairie Pothole Region. However, continued degradation of breeding habitats through climate‐related shifts in wetland hydrology and agricultural conversion of surrounding grassland habitats may have exceeded the capacity for demographic compensation during the nonbreeding season. 

Abstract Nest‐site fidelity is a common strategy in birds and is believed to be adaptive due to familiarity with local conditions. Returning to previously successful nest sites (i.e., the win‐stay lose‐switch strategy) may be beneficial when habitat quality is spatially variable and temporally predictable; however, changes in environmental conditions may constrain dispersal decisions despite previous reproductive success. We used long‐term (2000–2017) capture‐mark‐reencounter data and hierarchical models to examine fine‐scale nest‐site fidelity of emperor geese (Anser canagicus) on the Yukon–Kuskokwim Delta in Alaska. Our objectives were to quantify nest‐site dispersal distances, determine whether dispersal distance is affected by previous nest fate, spring timing, or major flooding events on the study area, and determine if nest‐site fidelity is adaptive in that it leads to higher nest survival. Consistent with the win‐stay lose‐switch strategy, expected dispersal distance for individuals that failed their nesting attempt in the previous year was greater (207.7 m, 95% HPDI: 151.1–272.7) than expected dispersal distance for individuals that nested successfully in the previous year (125.5 m, 95% HPDI: 107.1–144.9). Expected dispersal distance was slightly greater following years of major flooding events for individuals that nested successfully, although this pattern was not observed for individuals that failed their nesting attempt. We did not find evidence that expected dispersal distance was influenced by spring timing. Importantly, dispersal distance was positively related to daily survival probability of emperor goose nests for individuals that failed their previous nesting attempt, suggesting an adaptive benefit to the win‐stay lose‐switch strategy. Our results highlight the importance of previous experience and environmental variation for informing dispersal decisions of a long‐lived goose species. However, it is unclear if dispersal decisions based on previous experience will continue to be adaptive as variability in environmental conditions increases in northern breeding areas. 

Abstract Climate and land use change are two of the primary threats to global biodiversity; however, each species within a community may respond differently to these facets of global change. Although it is typically assumed that species use the habitat that is advantageous for survival and reproduction, anthropogenic changes to the environment can create ecological traps, making it critical to assess both habitat selection (e.g. where species congregate on the landscape) and the influence of selected habitats on the demographic processes that govern population dynamics.We used a long‐term (1958–2011), large‐scale, multi‐species dataset for waterfowl that spans the United States and Canada to estimate species‐specific responses to climate and land use variables in a landscape that has undergone significant environmental change across space and time. We first estimated the effects of change in climate and land use variables on habitat selection and population dynamics for nine species. We then hypothesized that species‐specific responses to environmental change would scale with life‐history traits, specifically: longevity, nesting phenology and female breeding site fidelity.We observed species‐level heterogeneity in the demographic and habitat selection responses to climate and land use change, which would complicate community‐level habitat management. Our work highlights the importance of multi‐species monitoring and community‐level analysis, even among closely related species.We detected several relationships between life‐history traits, particularly nesting phenology, and species' responses to environmental change. One species, the early‐nesting northern pintail (Anas acuta), was consistently at the extreme end of responses to land use and climate predictors and has been a species of conservation concern since their population began to decline in the 1980s. They, and the blue‐winged teal, also demonstrated a positive habitat selection response to the proportion of cropland on the landscape that simultaneously reduced abundance the following year, indicative of susceptibility to ecological traps.By distilling the diversity of species' responses to environmental change within a community, our methodological approach and findings will help improve predictions of community responses to global change and can inform multi‐species management and conservation plans in dynamic landscapes that are based on simple tenets of life‐history theory. 

Abstract The estimation of demographic parameters is a key component of evolutionary demography and conservation biology. Capture–mark–recapture methods have served as a fundamental tool for estimating demographic parameters. The accurate estimation of demographic parameters in capture–mark–recapture studies depends on accurate modeling of the observation process. Classic capture–mark–recapture models typically model the observation process as a Bernoulli or categorical trial with detection probability conditional on a marked individual's availability for detection (e.g., alive, or alive and present in a study area). Alternatives to this approach are underused, but may have great utility in capture–recapture studies. In this paper, we explore a simple concept:in the same way that counts contain more information about abundance than simple detection/non‐detection data, the number of encounters of individuals during observation occasions contains more information about the observation process than detection/non‐detection data for individuals during the same occasion. Rather than using Bernoulli or categorical distributions to estimate detection probability, we demonstrate the application of zero‐inflated Poisson and gamma‐Poisson distributions. The use of count distributions allows for inference on availability for encounter, as well as a wide variety of parameterizations for heterogeneity in the observation process. We demonstrate that this approach can accurately recover demographic and observation parameters in the presence of individual heterogeneity in detection probability and discuss some potential future extensions of this method. 

Abstract The management of sustainable harvest of animal populations is of great ecological and conservation importance. Development of formal quantitative tools to estimate and mitigate the impacts of harvest on animal populations has positively impacted conservation efforts.The vast majority of existing harvest models, however, do not simultaneously estimate ecological and harvest impacts on demographic parameters and population trends. Given that the impacts of ecological drivers are often equal to or greater than the effects of harvest, and can covary with harvest, this disconnect has the potential to lead to flawed inference.In this study, we used Bayesian hierarchical models and a 43‐year capture–mark–recovery dataset from 404,241 female mallardsAnas platyrhynchosreleased in the North American midcontinent to estimate mallard demographic parameters. Furthermore, we model the dynamics of waterfowl hunters and habitat, and the direct and indirect effects of anthropogenic and ecological processes on mallard demographic parameters.We demonstrate that density dependence, habitat conditions and harvest can simultaneously impact demographic parameters of female mallards, and discuss implications for existing and future harvest management models.Our results demonstrate the importance of controlling for multicollinearity among demographic drivers in harvest management models, and provide evidence for multiple mechanisms that lead to partial compensation of mallard harvest. We provide a novel model structure to assess these relationships that may allow for improved inference and prediction in future iterations of harvest management models across taxa. 

Abstract Seasonal variation in the availability of essential resources is one of the most important drivers of natural selection on the phasing and duration of annually recurring life-cycle events. Shifts in seasonal timing are among the most commonly reported responses to climate change and the capacity of organisms to adjust their timing, either through phenotypic plasticity or evolution, is a critical component of resilience. Despite growing interest in documenting and forecasting the impacts of climate change on phenology, our ability to predict how individuals, populations, and species might alter their seasonal timing in response to their changing environments is constrained by limited knowledge regarding the cues animals use to adjust timing, the endogenous genetic and molecular mechanisms that transduce cues into neural and endocrine signals, and the inherent capacity of animals to alter their timing and phasing within annual cycles. Further, the fitness consequences of phenological responses are often due to biotic interactions within and across trophic levels, rather than being simple outcomes of responses to changes in the abiotic environment. Here, we review the current state of knowledge regarding the mechanisms that control seasonal timing in vertebrates, as well as the ecological and evolutionary consequences of individual, population, and species-level variation in phenological responsiveness. Understanding the causes and consequences of climate-driven phenological shifts requires combining ecological, evolutionary, and mechanistic approaches at individual, populational, and community scales. Thus, to make progress in forecasting phenological responses and demographic consequences, we need to further develop interdisciplinary networks focused on climate change science. 

Abstract Harvest of wild organisms is an important component of human culture, economy, and recreation, but can also put species at risk of extinction. Decisions that guide successful management actions therefore rely on the ability of researchers to link changes in demographic processes to the anthropogenic actions or environmental changes that underlie variation in demographic parameters.Ecologists often use population models or maximum sustained yield curves to estimate the impacts of harvest on wildlife and fish populations. Applications of these models usually focus exclusively on the impact of harvest and often fail to consider adequately other potential, often collinear, mechanistic drivers of the observed relationships between harvest and demographic rates. In this study, we used an integrated population model and long‐term data (1973–2016) to examine the relationships among hunting and natural mortality, the number of hunters, habitat conditions, and population size of blue‐winged tealSpatula discors, an abundant North American dabbling duck with a relatively fast‐paced life history strategy.Over the last two and a half decades of the study, teal abundance tripled, hunting mortality probability increased slightly (), and natural mortality probability increased substantially () at greater population densities. We demonstrate strong density‐dependent effects on natural mortality and fecundity as population density increased, indicative of compensatory harvest mortality and compensatory natality. Critically, an analysis that only assessed the relationship between survival and hunting mortality would spuriously indicate depensatory mortality due to multicollinearity between abundance, natural mortality and hunting mortality.Our findings demonstrate that models that only consider the direct effect of hunting on survival or natural mortality can fail to accurately assess the mechanistic impact of hunting on population dynamics due to multicollinearity among demographic drivers. This multicollinearity limits inference and may have strong impacts on applied management actions globally.