Chinook Salmon Oncorhynchus tshawytscha from western Alaska have experienced recent declines in abundance, size, and age at maturity. Declines have led to hardships for the region's subsistence and commercial salmon harvesters, prompting calls to better understand factors affecting the life history of these populations. Western Alaskan Chinook Salmon are thought to spend their entire marine residency in the Bering Sea. The Bering Sea ecosystem demonstrates high interannual variability that is largely driven by the annual extent of sea ice. However, warming is expected to supersede interannual variability in the next several decades as a consequence of climate change. We investigated the influence of sea surface temperatures (SSTs) on the life history of western Alaskan Chinook Salmon by using information from two regional populations subject to long‐term monitoring. We found strong correlations between early marine growth and SSTs. Warmer SSTs appeared to lead to a younger age at maturity, largely through the vector of augmented growth. However, we also present evidence that warmer SSTs may additionally decrease the average age of male recruits through reduced growth thresholds for early male maturation. Our results suggest that the anticipated warming of the Bering Sea will lead to higher early marine growth and a younger average age of maturation for western Alaskan Chinook Salmon.

Spatial and temporal patterns in stream temperature are primary factors determining species composition, diversity and productivity in stream ecosystems. The availability of spatially and temporally continuous estimates of stream temperature would improve the ability of biologists to fully explore the effects of stream temperature on biota. Most statistical stream temperature modeling techniques are limited in their ability to account for the influence of variables changing across spatial and temporal gradients. We identified and described important interactions between climate and spatial variables that approximate mechanistic controls on spatiotemporal patterns in stream temperature. With identified relationships we formed models to generate reach-scale basin-wide spatially and temporally continuous predictions of daily mean stream temperature in four Columbia River tributaries watersheds of the Pacific Northwest, USA. Models were validated with a testing dataset composed of completely distinct sites and measurements from different years. While some patterns in residuals remained, testing dataset predictions of selected models demonstrated high accuracy and precision (averaged RMSE for each watershed ranged from 0.85–1.54 °C) and was only 17% higher on average than training dataset prediction error. Aggregating daily predictions to monthly predictions of mean stream temperature reduced prediction error by an average of 23%. The accuracy of predictions was largely consistent across diverse climate years, demonstrating the ability of the models to capture the influences of interannual climatic variability and extend predictions to timeframes with limited temperature logger data. Results suggest that the inclusion of a range of interactions between spatial and climatic variables can approximate dynamic mechanistic controls on stream temperatures.