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This study compares alternative implementations of species distribution models (SDMs) for quantifying static and dynamic patterns in marine habitat use, with a case study focusing on juvenile salmon in the eastern Bering Sea. We compare the performance of two prevalent SDM frameworks—generalized additive models (GAMs) and vector autoregressive spatio-temporal (VAST) models—in predicting juvenile salmon distributions and assessing interannual variation in habitat utilization. The two SDM frameworks produced similar spatial predictions but performed differently in tests of within-sample and out-of-sample predictive power. Our findings indicate that VAST models may provide more precise estimates of distribution compared to GAMs. Maps of predicted juvenile salmon distributions showed highest salmon densities in habitats within the 50 m isobath of the continental shelf, underscoring the importance of these coastal areas, although among-species differences were evident. Model performance results suggested evidence for spatial variation in juvenile salmon species’ distributions through time. Our findings suggest that an SDM approach can be effective for estimating static and dynamic juvenile salmon distributions, and for providing insights that are useful in spatial fisheries management contexts. 

Understanding how species are responding to environmental change is a central challenge for stewards and managers of fish and wildlife who seek to maintain harvest opportunities for communities and Indigenous peoples. This is a particularly daunting but increasingly important task in remote, high‐latitude regions where environmental conditions are changing rapidly and data collection is logistically difficult. The Arctic–Yukon–Kuskokwim (AYK) region encompasses the northern extent of the Chinook Salmon Oncorhynchus tshawytscha range where populations are experiencing rapid rates of environmental change across both freshwater and marine habitats due to global climate change. Climate–salmon interactions in the AYK region are a particularly pressing issue as many local communities have a deep reliance on a subsistence way of life. Here, we synthesize perspectives shared at a recent workshop on Chinook Salmon declines in the AYK region. The objectives were to discuss current understandings of climate–Chinook Salmon interactions, develop a set of outstanding questions, review available data and its limitations in addressing these questions, and describe the perspectives expressed by participants in this workshop from diverse backgrounds. We conclude by suggesting pathways forward to integrate different types of information and build relationships among communities, academic partners, and fishery management agencies. 

Abstract Recent empirical studies have quantified correlation between survival and recovery by estimating these parameters as correlated random effects with hierarchical Bayesian multivariate models fit to tag‐recovery data. In these applications, increasingly negative correlation between survival and recovery has been interpreted as evidence for increasingly additive harvest mortality. The power of these hierarchal models to detect nonzero correlations has rarely been evaluated, and these few studies have not focused on tag‐recovery data, which is a common data type. We assessed the power of multivariate hierarchical models to detect negative correlation between annual survival and recovery. Using three priors for multivariate normal distributions, we fit hierarchical effects models to a mallard (Anas platyrhychos) tag‐recovery data set and to simulated data with sample sizes corresponding to different levels of monitoring intensity. We also demonstrate more robust summary statistics for tag‐recovery data sets than total individuals tagged. Different priors led to substantially different estimates of correlation from the mallard data. Our power analysis of simulated data indicated most prior distribution and sample size combinations could not estimate strongly negative correlation with useful precision or accuracy. Many correlation estimates spanned the available parameter space (−1,1) and underestimated the magnitude of negative correlation. Only one prior combined with our most intensive monitoring scenario provided reliable results. Underestimating the magnitude of correlation coincided with overestimating the variability of annual survival, but not annual recovery. The inadequacy of prior distributions and sample size combinations previously assumed adequate for obtaining robust inference from tag‐recovery data represents a concern in the application of Bayesian hierarchical models to tag‐recovery data. Our analysis approach provides a means for examining prior influence and sample size on hierarchical models fit to capture–recapture data while emphasizing transferability of results between empirical and simulation studies. 

Abstract Disentangling the influences of climate change from other stressors affecting the population dynamics of aquatic species is particularly pressing for northern latitude ecosystems, where climate‐driven warming is occurring faster than the global average. Chinook salmon (Oncorhynchus tshawytscha) in the Yukon‐Kuskokwim (YK) region occupy the northern extent of their species' range and are experiencing prolonged declines in abundance resulting in fisheries closures and impacts to the well‐being of Indigenous people and local communities. These declines have been associated with physical (e.g., temperature, streamflow) and biological (e.g., body size, competition) conditions, but uncertainty remains about the relative influence of these drivers on productivity across populations and how salmon–environment relationships vary across watersheds. To fill these knowledge gaps, we estimated the effects of marine and freshwater environmental indicators, body size, and indices of competition, on the productivity (adult returns‐per‐spawner) of 26 Chinook salmon populations in the YK region using a Bayesian hierarchical stock‐recruitment model. Across most populations, productivity declined with smaller spawner body size and sea surface temperatures that were colder in the winter and warmer in the summer during the first year at sea. Decreased productivity was also associated with above average fall maximum daily streamflow, increased sea ice cover prior to juvenile outmigration, and abundance of marine competitors, but the strength of these effects varied among populations. Maximum daily stream temperature during spawning migration had a nonlinear relationship with productivity, with reduced productivity in years when temperatures exceeded thresholds in main stem rivers. These results demonstrate for the first time that well‐documented declines in body size of YK Chinook salmon were associated with declining population productivity, while taking climate into account. 

In this paper we prove an equivalence theorem originally observed by Robert MacPherson. On one side of the equivalence is the category of cosheaves that are constructible with respect to a locally cone-like stratification. Our constructibility condition is new and only requires that certain inclusions of open sets are sent to isomorphisms. On the other side of the equivalence is the category of functors from the entrance path category, which has points for objects and certain homotopy classes of paths for morphisms. When our constructible cosheaves are valued in Set we prove an additional equivalence with the category of stratified coverings.