Project Date Range:
As part of an interdisciplinary project with colleagues from the Marine Biological Laboratory, Woods Hole, MA and University of Connecticut, Avery Point Campus, Groton, CT we studied the social and ecological transferability of integrated ecological assessment models. Increased nitrogen loading to estuaries of southeastern New England, mostly as groundwater nitrate, has caused excessive macroalgal and phytoplankton production (eutrophication) at the expense of eelgrass biomass and stem density. Degradation and loss of eelgrass habitat has been associated with declines in fish diversity and abundance in these systems. Although the consequences of elevated nutrient loading to estuaries are broadly known (e.g., bottom water anoxia and loss of fish habitat), the several models that have been developed linking nitrogen loading to land use have not included endpoints of concern to planners such as the likelihood of anoxic events and effects on estuarine fish abundance. Also, the utility of land use and eutrophication models to planners in making scientifically-sound management decisions may be influenced by planners' perceptions of the modeling process.
Our research as part of the broader project focused on characterization of views on ecosystems models and their application in local decision making by modelers and outreach professionals in southern New England.
First, we developed a survey instrument to inquire of local governmental officials’ perceptions about the usefulness and applicability of nitrogen-loading models as decision making aids. We surveyed over 150 planning board, selectboard, and board of health members in small towns in southeastern Massachusetts.
Second, we evaluated the performance of a participatory ecosystem modeling approach as applied in Rhode Island. The cooperative extension service at the University of Rhode Island has developed a nitrogen-loading and risk assessment model called the MANAGE model. For the past five years they have been taking the model in community settings, where they engage local planning board volunteers in running the model. These trainings are also focused around solving an immediate local environmental problem. We studied the way that local board members engaged the model as a decision making aid. Data were gathered through observations and interviews.
Third, we completed interviews with 16 individuals who design computer models or who are professionally engaged with helping local town decision makers use or interpret the results of these models. These interview transcripts were analyzed using qualitative data analysis tools. Several salient themes were extracted.
There is no background information available for this project at this time.