Mark–recapture methods were used to examine watershed-scale survival of coastal cutthroat trout ( Oncorhynchus clarkii clarkii ) from two headwater stream networks. A total of 1725 individuals (≥100 mm, fork length) were individually marked and monitored seasonally over a 3-year period. Differences in survival were compared among spatial (stream segment, subwatershed, and watershed) and temporal (season and year) analytical scales, and the effects of abiotic (discharge, temperature, and cover) and biotic (length, growth, condition, density, movement, and relative fish abundance) factors were evaluated. Seasonal survival was consistently lowest and least variable (years combined) during autumn (16 September – 15 December), and evidence suggested that survival was negatively associated with periods of low stream discharge. In addition, relatively low (–) and high (+) water temperatures, fish length (–), and boulder cover (+) were weakly associated with survival. Seasonal abiotic conditions affected the adult cutthroat trout population in these watersheds, and low-discharge periods (e.g., autumn) were annual survival bottlenecks. Results emphasize the importance of watershed-scale processes to the understanding of population-level survival.
Fishery management decisions are commonly guided by stock assessment models that aggregate outputs across the spatial domain of the species. With refined understanding of spatial population structures, scientists have begun to address how spatiotemporal mismatches among the scale of ecological processes, data collection programs, and stock assessment methods (or assumptions) influence the reliability and, ultimately, appropriateness of regional fishery management (e.g., assigning regional quotas). Development and evaluation of spatial modeling techniques to improve fisheries assessment and management have increased rapidly in recent years. We overview the historical context of spatial models in fisheries science, highlight recent advances in spatial modeling, and discuss how spatial models have been incorporated into the management process. Despite limited examples where spatial assessment models are used as the basis for management advice, continued investment in fine-scale data collection and associated spatial analyses will improve integration of spatial dynamics and ecosystem-level interactions in stock assessment. In the near future, spatiotemporal fisheries management advice will increasingly rely on fine-scale outputs from spatial analyses.
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