Regularized Latent Trajectory Models for Spatio-temporal Population Dynamics

Climate change impacts ecosystems variably in space and time. Landscape features may confer resistance against environmental stressors, whose intensity and frequency also depend on local weather patterns. Characterizing spatio-temporal variation in population responses to these stressors improves our understanding of what constitutes climate change refugia. We developed a Bayesian hierarchical framework that allowed us to differentiate population responses to seasonal weather patterns depending on their “sensitive” or “resilient” states. The framework inferred these sensitivity states based on latent trajectories delineating dynamic state probabilities. The latent trajectories are composed of linear initial conditions,...

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Using multi-scale spatial models of dendritic ecosystems to infer abundance of a stream salmonid

Understanding patterns of species abundance is essential for planning landscape-level conservation. The complex hierarchies of dendritic ecosystems result in different levels of heterogeneity at distinct geographic scales. Species responses to dynamic environmental drivers may also vary spatially depending on their interactions with landscape features. Monitoring abundance by explicitly quantifying their spatial and temporal variation is important for strategic management. We analysed brook trout (Salvelinus fontinalis) count data collected from 173 sites in western North Carolina between 1989 and 2015. We developed a Bayesian hierarchical model that used single- and multi-pass electro-fishing data and characterized...

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Spatial asynchrony and cross-scale climate interactions in populations of a coldwater stream fish

Climate change affects populations over broad geographic ranges due to spatially autocorrelated abiotic conditions known as the Moran effect. However, populations do not always respond to broad-scale environmental changes synchronously across a landscape. We combined multiple datasets for a retrospective analysis of time-series count data (5–28 annual samples per segment) at 144 stream segments dispersed over nearly 1,000 linear kilometers of range to characterize the population structure and scale of spatial synchrony across the southern native range of a coldwater stream fish (brook trout, Salvelinus fontinalis), which is sensitive to stream temperature and flow variations. Spatial synchrony differed by life stage...

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Final Report: Brook Trout Population Responses to Climate Variation Across the Southeast USA

Brook trout is an iconic freshwater fish species that supports recreational fishing and cultural heritage in the Southeast USA. However, human activities, such as habitat degradation and introduction of non-native species, have led to extensive declines of brook trout populations in the region, and climate change is projected to affect this native coldwater species further. Efforts to save this species occur throughout the region, but financial and other resources are limited: conservation practitioners need to understand the status of trout populations in the large landscape and decide where such efforts should occur to maximize our chances of maintaining brook trout populations. In this project, we assembled data...

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Landscape influences on thermal sensitivity and predicted spatial variability among brook trout streams in the southeastern USA

Warming water temperatures as a result of climate change pose a major threat to coldwater organisms. However, the rate of warming is not spatially uniform due to surface-ground-water interactions and stream and watershed characteristics. Coldwater habitats that are most resistant to warming serve as thermal refugia and identifying their locations is critical to regional aquatic conservation planning. We quantified the thermal sensitivity of 203 streams providing current and potential habitat for brook trout (Salvelinus fontinalis) across nearly 1000 linear km of their native range in the southern and central Appalachian Mountains region, USA, and characterized their spatial variability with landscape variables available...

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