Integrating high-frequency data, ecosystem models, and forecasts to understand the effects of global change on carbon dynamics in freshwater reservoirs

Abstract

Freshwater ecosystems are increasingly threatened due to anthropogenic global change, leading to changes in water quality and ecosystem functioning. Notably, global change, through changing land use, warmer temperatures, and changing hydrology, is altering freshwater dissolved organic matter (DOM) dynamics. DOM influences many components of freshwater ecosystem functioning, including carbon cycling, microbial and plankton food webs, metals complexation, and light attenuation, among others. Given the important role of DOM in freshwater ecosystems, I leveraged field, lab, modeling, and forecasting techniques through my dissertation to answer the question: How do DOM dynamics in reservoirs vary over temporal and spatial scales? First, I explored the effect of changing winter conditions on ecosystem metabolism rates, which govern rates of DOM production and respiration in freshwaters. I analyzed six years of high-frequency oxygen data in an intermittently ice-covered reservoir in the southern Appalachian Mountains and found that shorter winters did not affect annual metabolism rates. This finding contrasts with previous work conducted in northern lakes with prolonged ice cover, suggesting that ecosystems with intermittent ice cover may have already crossed ecologically meaningful tipping points. Second, I conducted monthly spatial field surveys across a reservoir watershed over a year to understand changes in DOM concentration and composition across the lotic (stream inflow) to lentic (reservoir basin) gradient. My findings suggest that important transformations in DOM occur at the lotic-lentic boundary in backwater and shallow cove sites in reservoirs, highlighting that these understudied transitional zones may be hotspots of biogeochemical cycling. Third, I tested the importance of catchment (terrestrial) and water column (aquatic) processes in driving reservoir DOM concentrations using a suite of contrasting models to generate 1 to 30 day-ahead predictions of reservoir DOM. I found that both catchment and water column drivers can be important controls on reservoir DOM but that their relative importance may vary seasonally, suggesting that multiple modeling approaches and drivers may be needed to accurately predict and understand reservoir DOM variability. Finally, I developed the first (to our knowledge) near-term iterative forecasts of reservoir DOM across three reservoirs using multiple modeling approaches. I found that forecast accuracy was consistent across reservoirs but not among seasons over one year of evaluation. Altogether, my dissertation identified high spatial and temporal variability in DOM cycling within and across three reservoirs over minute to year time scales. My work has provided fundamental understanding and tools to understand DOM dynamics that will be needed as DOM dynamics and freshwater ecosystems are increasingly influenced by global change.