Collaborative Research: A new dynamic equilibrium for river networks: impacts of a natural ecosystem engineer on watershed carbon transport and storage

Freshwater ecosystems provide many benefits to American citizens including water for irrigation, industry, data centers and drinking. Freshwater habitats improve water quality through natural processes, creating habitat for fish and other organisms, and they store large amounts of carbon. After near-extinction in the early 1900s, North American beaver populations have been rebounding over the last several decades, dramatically changing freshwater ecosystems. As nature's freshwater ecosystem engineers, beavers build dams and transform flowing streams and rivers into mosaics of ponds and wetlands. While beaver ponds and wetlands are becoming more prevalent across the globe, most of the understanding of freshwater ecosystems is based on science that occurred when beaver were relatively scarce. In forested regions, it is also difficult to map and predict where beaver-engineered ecosystems occur across the landscape. This project leverages and integrates satellite remote sensing, artificial intelligence (AI), field measurements, and simulation modeling to map beaver-engineered ecosystems and quantify their structure and function at the landscape-scale, in the Northeastern United States. Investigators will develop a transferable framework for detecting and characterizing beaver created ecosystems and will engage the public by developing an online mapping tool designed to aid decision-makers (e.g., watershed associations, land trusts, municipal and state governments) in land management decisions. The project supports education through the development of middle-high school inquiry-based case studies, development of a graduate-level course to train students in multi-institution, interdisciplinary team science, and providing experiential training in research for multiple graduate and undergraduate students. This project will advance knowledge of how hydrologic networks contribute to watershed dynamics by embracing the fundamental landscape-scale changes beaver have made to aquatic ecosystems as they return from near-extinction across North America. The overarching goal is to characterize beaver-engineered ecosystems over space and time, and to evaluate how they alter carbon dynamics at the watershed-scale. The approach couples remote sensing, field measurements, and river network models across three temperate forested watersheds in the northeastern United States to map, measure, and scale beaver-engineered ecosystems and their effects on carbon cycling. Researchers will pair remotely sensed imagery with artificial intelligence-enabled image analysis to detect and characterize beaver-engineered ecosystems. They will intensively sample these ecosystems across three watersheds to quantify the distribution of habitat types within ecosystems, and associated carbon storage and accumulation rates, by using a combination of drone-based remote sensing, ground penetrating radar, and soil core analysis. They will also measure natural gas emissions via diffusive, ebullitive, and plant-mediated transport pathways. Finally, they will apply river network simulation models to scale beaver-engineered ecosystem dynamics to the watershed-scale. The project will benefit the U.S. public directly through the development of an online mapping tool designed to engage a wide range of audiences, from middle and high school students learning about the role of beavers in the landscape to community and government organizations evaluating water use for agriculture, data center development and household consumption. Graduate and undergraduate students will be trained through experiential research in interdisciplinary science using novel and emerging field and technological approaches, including in the AI national priority area. Maps and upscaled carbon estimates will improve regional budgets and earth systems modeling efforts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectua NSF Award ID: 2536107 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Wilfred Wollheim | Institution: University of New Hampshire, DURHAM, NH | Award Amount: $437,916 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2536107 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2536107.html