Fisheries stock assessments depend on data about species’ population size, harvest rates, and geographic distribution to estimate how many fish are present and where they are located. These assessments are also shaped by assumptions about the timing and location of key biological processes. However, increasing climate variability is shifting the distribution, abundance, and biological traits of marine species, challenging those assumptions. Incorporating spatial and temporal dynamics into assessments can help reduce uncertainty and support more effective, adaptive management decisions. My dissertation explored the range of practical approaches for integrating spatial information into US marine fisheries stock assessments and the factors that support their implementation. I applied some of these approaches to examine the recent increase in Atlantic menhaden (Brevoortia tyrannus) landings in the northeastern US– an important forage fish for marine fishes, mammals, and birds along the east coast. Results show that spatiotemporal methods are used most often in stock assessments of large-bodied, pelagic, and commercially valuable species, largely due to the availability of data, resources, and regional management structures to support implementation. Spatiotemporal analyses reveal that although Atlantic menhaden is expanding northward, and warming water temperature is a factor, their distribution remains highly patchy and variable. This suggests that additional ecological factors, potentially operating at local scales, may play a role in predicting menhaden distribution and should be considered when projecting future trends. While a comprehensive spatiotemporal understanding of a fishery may require high-resolution data that exceed available resources, informed decisions that balance management needs with data quality and uncertainty can still drive meaningful improvements.