Rivers and streams cover only about half a percent of the Earth’s land surface, but they play a substantial role in sustaining life on the planet. In addition to supporting complex food webs, strengthening biodiversity and maintaining water quality, river networks are a key participant in the global cycling of carbon.
As atmospheric carbon dioxide increases, global temperatures rise and lands adjacent to watersheds change or are repurposed, scientists are uncertain of the impacts on stream and river ecosystems. To start understanding the effects, scientists like Lauren Koenig, a postdoctoral research associate in the Department of Natural Resources and the Environment (NRE) says we need to first learn more about how rivers and streams transport, transform and store carbon.
“We are specifically focused on primary production and respiration,” says Koenig. “Just like you and I are breathing, rivers do that, too. Rivers and streams create and respire organic carbon. It’s part of a collection of processes we call metabolism. We want to know how they maintain that function to understand the ways climate change and land use changes affect those processes.”
Part of Koenig’s research relies on statistical analysis and computer modeling to create computer-generated river networks. By compiling information about carbon and oxygen content, water temperature and barometric pressure from sites throughout a watershed, she merges these data into a detailed map. From there, she can apply specific modifications, such as raising the temperature of the water, and determine the probable effects to entire fluvial network.
Koenig is part of NRE Assistant Professor Ashley Helton‘s lab, which is currently engaged in a variety of freshwater ecosystem studies. Helton is also an affiliated faculty member with the Center for Environmental Sciences and Engineering. Koenig’s carbon cycling research is part of a collaboration called StreamPULSE, a research program led by Duke University faculty in partnership with researchers from several academic institutions, including UConn, and the United States Geological Survey.
The metabolism of watersheds varies due to daily, seasonal and annual changes. The amount of photosynthetic activity depends on available sunlight and the abundance of organisms that perform photosynthesis and other factors. Temperature as well as floods, droughts and other environmental events can alter productivity. Understanding these many variables and fluxes, while accounting for every rivulet, is crucial to measuring primary production throughout an entire river network. Koenig is tackling this difficult task by patterning recurrent variations to create simulated networks.
“In real rivers, we generally study processes by focusing on one segment of the river,” says Koenig. “It’s just like if you were to go out in a forest and study one patch. You get to know the small scale really well, but that’s not the scale managers are interested in, so we want to use simulated networks.”
“We’ve been collecting data for the past two years, so now we’re starting to have a better understanding of what happens with photosynthesis when a big storm comes or what the factors are that give rise to the variability we see in carbon cycling processes. We’re starting to understand this at local scales and now we’re extrapolating to the dynamic of the whole river network.”
Understanding how river ecosystems respond to changes over different time scales and in reaction to weather, climate and land use changes is valuable information for land and water managers. The goal of the research, Koenig says, is learning how certain decisions or environmental events will affect these areas over the short term and long term and reverberate throughout the entire watershed and beyond. Koenig says computer-generated river networks have been a useful tool for understanding the productivity of real river networks.
“Our job at UConn is to take those small scales and figure out how to translate it to broader scales and predict function across different watersheds,” says Koenig. “So, for instance, if we modify the forest structure and take away riparian forest, which is pretty common in urban and suburbanization, then we know how the ecosystem will respond since the light dynamic changes with that forest gone.”
Koenig is gathering data from five river networks in distinct climates. Watersheds in New Hampshire, Florida, Arizona, North Carolina and Puerto Rico are providing researchers with a variety of environmental characteristics that can help researchers understand the factors and events that dictate aspects of primary production regionally. Koenig says these sites represent extremes in light availability, streamflow seasonality and human impacts. The inclusion of Puerto Rico allows Koenig to compare a tropical biome to a more temperate region. All these data help researchers create more accurate models and predictions concerning ecosystem function.
“Simulated networks allow us to ask questions and see how processes are affected,” says Koenig. “It’s a lot easier than going out and cutting down a forest and measuring to get an answer. Instead, we can know some of those answers and can ask, ‘What if we left the forest intact?’ or ‘What if we bulldoze everything?’ We can also run models where we fell trees in a particular area or models where we see what happens if there’s patchiness. We can use the patterns we’ve generated as hypotheses to inform our next steps since we know how the ecosystem behaves.”
While the work on this grant will continue another year, she anticipates further avenues for research related to river networks.
“There are lots of ways to bridge this to other research,” says Koenig. “For freshwater fisheries, primary production represents a food source for fish species and macroinvertebrates. This work can inform and connect with a lot of research happening at UConn and around the world. We’re continuing to work on this project for about another year, but it will probably lead to more research as we study the distribution of land change and experience further climate change.”
Koenig’s research is part of NSF Macrosystem Biology Grant Award # 1442439.