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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 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 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 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. 

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 Auxiliary markers play an essential role in understanding migration, movement, demography, and behavior of migratory birds. Use of such markers relies on the assumption that the markers do not affect the traits of interest. Neck collars, among the most conspicuous of markers, substantially affect risk of harvest, and survival even in the absence of harvest. Effects of less‐conspicuous markers, such as colored plastic tarsal bands, are not well understood. We used 30 years (1986–2015) of banding, recovery, and recapture data from the Yukon‐Kuskokwim Delta in Alaska, USA, to assess differences in direct band recovery rates (DRRs) between black plastic and brightly colored plastic bands applied to black brant (Branta bernicla nigricans). We also assessed the effect of the color of plastic tarsal bands on annual survival, risks of natural mortality harvest, and fidelity to the breeding colony of adult female black brant. When assessing only DRRs we found that brightly colored bands were recovered at higher rates than black plastic bands in the early 2000s, but DRRs for black bands increased more rapidly through time, resulting in similar DRRs for the 2 band colors at the end of the study. Using a Burnham model structure, our results demonstrated that individuals fitted with colored bands had slightly lower hazards of dying from natural causes or hunting than individuals carrying less‐conspicuous black tarsal bands. Differences on annual probability scales were small and credible intervals broadly overlapped between band types, indicating minimal differences between individuals with different band types; however, we could not resolve all confounding in our study design and we suggest that specific studies directed at assessing marker effects are warranted. We encourage education of hunters about their roles as citizen scientists and the potentially detrimental effect of targeting birds with auxiliary markers. 

Abstract Ongoing declines in insect populations have led to substantial concern and calls for conservation action. However, even for relatively well studied groups, like butterflies, information relevant to species‐specific status and risk is scattered across field guides, the scientific literature, and agency reports. Consequently, attention and resources have been spent on a minuscule fraction of insect diversity, including a few well studied butterflies. Here we bring together heterogeneous sources of information for 396 butterfly species to provide the first regional assessment of butterflies for the 11 western US states. For 184 species, we use monitoring data to characterize historical and projected trends in population abundance. For another 212 species (for which monitoring data are not available, but other types of information can be collected), we use exposure to climate change, development, geographic range, number of host plants, and other factors to rank species for conservation concern. A phylogenetic signal is apparent, with concentrations of declining and at‐risk species in the families Lycaenidae and Hesperiidae. A geographic bias exists in that many species that lack monitoring data occur in the more southern states where we expect that impacts of warming and drying trends will be most severe. Legal protection is rare among the taxa with the highest risk values: of the top 100 species, one is listed as threatened under the US Endangered Species Act and one is a candidate for listing. Among the many taxa not currently protected, we highlight a short list of species in decline, includingVanessa annabella,Thorybes mexicanus,Euchloe ausonides, andPholisora catullus. Notably, many of these species have broad geographic ranges, which perhaps highlights a new era of insect conservation in which small or fragmented ranges will not be the only red flags that attract conservation attention.