| Summary: | Thesis (Master's)--University of Washington, 2020 Streamwater chemistry forms the base of aquatic food webs and reflects both watershed and instream controls, yet the balance of these controls has not been quantified across large river networks. Boreal river networks in particular are subject to rapid environmental change under a warming climate and growing developmental pressures from industrial activities such as mining. The impacts of these changes to nutrient and organic matter availability and contaminant loading to aquatic food webs is currently not well understood. In this thesis, I used recently developed spatial stream network models (SSNMs) that explicitly account for stream network topology, flow direction, and flow magnitude to quantify the effects of watershed versus instream transport processes on streamwater chemistry in the Kuskokwim River in western Alaska. This approach leverages a combination of instream sampling and broad scale, publicly available geospatial data. The Kuskokwim is America’s largest free-flowing river network and is predominantly a pristine watershed that supports an array of ecosystem services. The Kuskokwim is also home to numerous subsistence communities that rely on fish as a primary protein source. In chapter 1 I examined watershed controls on streamwater biogeochemical patterning and identify the scales at which watershed controls operate. For this chapter I studied a suite of streamwater constituents ranging from labile nutrients to conservative tracers to understand the effect of instream transport processes on network-wide dissolved organic carbon (DOC) concentrations. I show that conditions such as watershed morphology and geology in small, headwater catchments are disproportionately important drivers of streamwater biogeochemical patterning across the Kuskokwim River network, and that bulk measures of DOC reflect conservative transport behavior. In chapter 2 I extended this analysis to examine spatial patterning of mercury (Hg) contamination in tissue of slimy ...
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