Stakeholder Values and Scientific Modeling in the Neuse River Watershed

Journal Article (Journal Article)

In 1998, the North Carolina Legislature mandated a 30% reduction in the nitrogen loading in the Neuse River in an attempt to reduce undesirable environmental conditions in the lower river and estuary. Although sophisticated scientific models of the Neuse estuary exist, there is currently no study directly relating the nitrogen-reduction policy to the concerns of the estuarine system's stakeholders. Much of the difficulty lies in the fact that existing scientific models have biophysical outcome variables, such as dissolved oxygen, that are typically not directly meaningful to the public. In addition, stakeholders have concerns related to economics, modeling, implementation, and fairness that go beyond ecological outcomes. We describe a decision-analytic approach to modeling the Neuse River nutrient-management problem, focusing on linking scientific assessments to stakeholder objectives. The first step in the approach is elicitation and analysis of stakeholder concerns. The second step is construction of a probabilistic model that relates proposed management actions to attributes of interest to stakeholders. We discuss how the model can then be used by local decision makers as a tool for adaptive management of the Neuse River system. This discussion relates adaptive management to the notion of expected value of information and indicates a need for a comprehensive monitoring program to accompany implementation of the model. We conclude by acknowledging that a scientific model cannot appropriately address all the stakeholder concerns elicited, and we discuss how the remaining concerns may otherwise be considered in the policy process.

Full Text

Duke Authors

Cited Authors

  • Borsuk, M; Clemen, R; Maguire, L; Reckhow, K

Published Date

  • December 1, 2001

Published In

Volume / Issue

  • 10 / 4

Start / End Page

  • 355 - 373

International Standard Serial Number (ISSN)

  • 0926-2644

Digital Object Identifier (DOI)

  • 10.1023/A:1011231801266

Citation Source

  • Scopus