UC Davis

Anthropogenic emissions of carbon dioxide are warming, deoxygenating, and acidifying the global ocean. In coastal areas, these global trends are much more complicated. Climate change trends can be attenuated, exacerbated, or entirely overridden by local influences such as rivers, pollution, complex circulation patterns, or biological productivity. As such, climate stress in the coastal ocean is more accurately described as a mosaic of stress loci and refugia that shift in space and time. Capturing this complexity is difficult, but is critical for coastal resource managers tasked with sustaining local fisheries and ecosystems over small spatial and temporal scales. In this work, I investigate and identify regions of climate stress in two coastal ecosystems highly vulnerable to warming and acidification: the eastern Bering Sea and the California Current System. In the Bering Sea, I develop species distribution models for adult red king crab to evaluate the effectiveness of modeled oceanographic conditions to predict crab distributions. In the California Current System, I develop the largest synthesis of ocean acidification- and hypoxia-relevant coastal climate observations to date, then use my synthesis to evaluate spatial patterns of vulnerability to single and multiple stressors in four widely dispersed shellfish species. Throughout this work, I interrogate the utility of high-resolution maps to inform resource management decisions and find that, while spatially-explicit information about climate stresses is important, its utility for management is often undermined by uncertainty about species sensitivity to climate stress or distribution. In the California Current System, I also find that accounting for uncertainty shows where oceanographic observations versus better precision in species sensitivity metrics produces the biggest gains in information.