Science Serving Maryland's Coasts


An Integrated Ecosystem Assessment of the Potomac River Estuary

Principal Investigator: 

Lora Harris

Start/End Year: 

2011 to 2014


Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science

Co-Principal investigator: 

Lisa A. Wainger, Hongsheng Bi, Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science

Strategic focus area: 

Resilient ecosystem processes and responses


OBJECTIVES : 1. Develop a priori guiding models of potential drivers and responses for the Potomac River estuary using the best available research and by eliciting experiences and concerns of government stakeholders. 2. Based upon the guiding models and their specifications of appropriate time and space scales for analysis, build a database for monitored and derived indicators from socioeconomic, climate, and ecosystem data series. 3. Using emergent correlative structures of the indicators, refine sets of indicators and test/modify the guiding model. Evaluate support of the accepted model with indicators using path regression analysis. 4. Use data-tested conceptual models of the interactions between climate change/human drivers on ecosystem condition to inform multiple stakeholders on ecosystem indicators that are likely sensitive to climate change and human drivers. 5. Develop a prospectus for conducting a similar IEA approach in either portions of the Chesapeake Bay or its entirety.

METHODOLOGY: Guiding models that present conventional and alternate relationships and feedbacks between human/climate drivers and ecosystem response (several presented in this proposal) will be developed. Classes of variables (drivers and responses) will be identified, pre-processed to reveal relevant temporal and spatial scales, and evaluated in correlative univariate and multivariate analyses to assess variable relevance, redundancy, sensitivity, and error. Selected variables will then be used in path regression analysis, which permits intervening variables to be analyzed as both a driver and response indicator. This analysis will compare multivariate correlative structures against model expectations, and contrast performance of alternate models for revealing variable significance and interactions. We will structure an iterative assessment-analysis-decision cycle within our team of diverse scientists to select indicators and conceptual models for exploration and refinement. Further, we will engage a specific group of stakeholders into the indicator decision process to promote the applicability of results to management needs.

RATIONALE: Ecosystem-based management in the Chesapeake Bay requires that goals are matched with assessments of ecosystem variables that are relevant and responsive to management objectives and ecosystem change. The current indicator-based approaches to assessing ecosystem responses to management and other stressors are often arbitrary, reductionist or overly simplistic given current perspectives on ecosystem complexity, climate change, hysteresis, uncertainty, and coupled human and ecological systems. The IEA approach has been adopted by NOAA and other governing agencies as a tractable means of evaluating classes of drivers and system responses in an adaptive management framework. The Potomac River estuary is a tractable ecosystem that epitomizes the Chesapeake Bay as a whole. The IEA proposed here not only brings in novel elements (guiding models and path analysis), but represents an important pilot effort in developing an IEA (or IEAs) for the Chesapeake Bay.


This section describes how this project has advanced scientific knowledge and/or made a difference in the lives of coastal residents, communities, and environments. Maryland Sea Grant has reported these details to the National Oceanic and Atmospheric Administration (NOAA), one of our funding sponsors.

RECAP: Large investments in water quality and fisheries monitoring on the Potomac River have resulted in extensive datasets that cover a long time period. In this ongoing project, researchers have created a model that can use these data to answer questions and help with the management and restoration of the estuary.

RELEVANCE: Currently various organizations use indicator-based approaches to assess ecosystem responses to stressors. These approaches are often overly simplistic given current perspectives on ecosystem complexity, climate change, and coupled human and ecological systems. The Integrated Ecosystem Assessment (IEA) approach has been adopted by the National Oceanic and Atmospheric Administration (NOAA) and other governing agencies as a tractable way of evaluating drivers and ecosystem responses. Conducting an IEA for the Potomac River, one of the Chesapeake Bay’s major tributaries, will represent an important pilot effort in developing an IEA (or IEAs) for the entire Bay. As a beneficial part of this project, the researchers came up with a new model to help natural-resource managers to predict blooms of a harmful algae called microcystis, which can reduce the quality of public water supplies and cause fish kills.

RESPONSE: The principal investigators of this project are Lora Harris, Lisa Wainger, and Hongsheng Bi of the University of Maryland Center for Environmental Science, Chesapeake Biological Laboratory. 

RESULTS: The researchers continued to develop an IEA model for the Potomac River during this reporting period. As part of the modeling work, the researchers examined an older model for forecasting blooms of microcystis algae that that had been used since the 1980s in the District of Columbia area. The researchers determined that the older model did not accurately describe the current causes of the algae blooms, including high concentrations observed on the Potomac in 2011. The researchers considered additional variables, including pH, and developed the new model using a regression analysis of historical data. The research team has presented the results to the Maryland Department of Natural Resources. The findings could help inform the department to forecast microcystis blooms based on prevailing environmental conditions; to target the department’s water-sampling efforts toward bloom-prone waters before blooms expand there; and to issue timely and accurate public-health warnings. The model also determined that after the major wastewater treatment plant on the Potomac – the Blue Plains Advanced Wastewater Treatment Plant, which serves Washington, D.C. – reduced its nitrogen effluent beginning in the 1980s, the plant’s discharge ceased to be an important explanatory variable for rates of algae blooms in the tidal Potomac. This finding retrospectively confirmed the importance and value of these expensive treatment-plant upgrades.