Overview
Our research seeks to understand large-scale ecological patterns and changes at the ecosystem to macrosystem scale. Our projects focus predominantly on freshwater ecosystems to develop and test ecological theory and forecast the future state of our critical freshwater resources. We currently have several active externally-funded projects underway that are described below. For a sense of our past research activities, visit our Products page.
Browning-induced ecological tipping points
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The concentration of dissolved organic matter is increasing in many lakes, giving water a brown "tea-like" color. These increases, termed "browning" have multiple ecological impacts. Dissolved organic matter absorbs light, altering the vertical distribution of photosynthesis and heat, which in turn regulate numerous other aspects of these ecosystems. Dissolved organic matter may also be an important nutrient source.
With support from the NSF LTREB program, we are tracking long-term changes in dissolved organic matter and a suite of physical, chemical, and biological characteristics in three lakes in the Pocono region of Pennsylvania, USA. Our long-term data, experiments, and models indicate that lake browning may represent an ecological tipping point. Many lakes are likely crossing browning-induced thresholds that alter their trophic status, greenhouse gas emissions, and habitat quality. |
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Water resources in Southern Africa
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The transboundary Limpopo River Basin includes portions of Botswana, Zimbabwe, South Africa, and Mozambique. At over 400,000 square kilometers, the Basin is home to 18 million people living in both rural and urban areas where water-intensive practices such as agriculture and mining are growing rapidly. The Basin also contains some of the most biodiverse ecosystems on the planet that are threatened by land use change, climate change, and water extraction. This US AID-funded project addresses the urgent need for improved environmental data, training programs, and forecasting algorithms to understand variations in water quantity and quality in the Limpopo River Basin, regional reservoirs, and throughout the broader southern Africa region. Our lab group's work focuses on deploying a network of in situ high-frequency sensors to characterize variability in aquatic ecosystems, developing training programs in statistical programming and remote sensing, and conducting research that advances ecological theory exploring the covariance between water quantity and quality in space and time. Learn more about this research from our US AID fact sheet and our project website, hosted by the Limpopo Resilience Lab.
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Ecological heterogeneity and aquatic biogeochemistry
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Lakes often exhibit substantial and dynamic structural heterogeneity in physical, chemical, and biological attributes. This heterogeneity challenges the ability to understand and forecast important features such as carbon cycling and dissolved oxygen concentrations and dynamics. Theoretically, carbon dioxide and dissolved oxygen are stoichiometrically coupled via metabolic processes, but departures from expectations based on stoichiometry and partial pressure in the atmosphere regularly occur. Understanding what causes these departures may provide insights into underlying biogeochemical processing in lakes, and may enable more accurate predictions of continental-scale carbon dioxide emissions and dissolved oxygen dynamics in lakes. With support from a NSF CAREER award, this project seeks to advance ecological theory by combining high-frequency sensor observations, manually collected data, long-term data sets and ecosystem modeling to understand the dynamics of lake carbon dioxide and dissolved oxygen across large environmental gradients.
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Understanding and forecasting harmful algal blooms
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Harmful algal blooms impair ecosystem services and threaten human health. However, despite their impacts blooms have so far generally resisted prediction in onset, duration, or intensity. Theoretical advancements are required to improve bloom forecasting. In partnership with scientists and engineers at IBM Research and the Jefferson Project at Lake George, this project seeks to identify and characterize the essential mechanistic processes that regulate bloom dynamics, and identify the most robust statistical indicators of bloom emergence, duration, and senesce. To do this, the project integrates data from large-scale synoptic lake surveys, high-frequency sensors, and process-based modeling to understand bloom dynamics and forecast blooms before they occur. on a wide range of freshwater lakes. Complementing these in situ research efforts, our research also seeks to understand the implications of harmful algal blooms for nearby air quality and human health toxin risk exposures.
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