Developing qualitative ecosystem service relationships with the Driver-Pressure-State-Impact-Response framework: A case study on Cape Cod, Massachusetts. (January 2018)

• Record Type: Journal Article
• Authors: Martin, David M.; Piscopo, Amy N.; Chintala, Marnita M.; Gleason, Timothy R.; Berry, Walter
• Is Part Of: Ecological indicators. Volume 84(2018)
• Page Start: 404
• Page End: 415
• Publication Date: 2018-01
• Subjects: DPSIR -- Interaction strength -- Qualitative models -- Water quality management; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2017.08.047
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Accounting for ecosystem services in resource management decisions is important. We present a qualitative modeling method for data-poor situations. Our method uses the Driver-Pressure-State-Impact-Response framework. We apply the method for water quality management on Cape Cod, Massachusetts. Abstract: Understanding the effects of environmental management strategies on society and the environment is critical for evaluating their effectiveness but is often impeded by limited data availability. In this article, we present a method that can help scientists to support environmental managers' thinking about causal effects on ecosystem services in coupled human and natural systems. Our method aims to model qualitative cause-effect relationships between management strategies and ecosystem services, using information provided by knowledgeable participants, and the tradeoffs between strategies. We select and organize management strategies, environmental variables, and ecosystem services as indicators using the Driver-Pressure-State-Impact-Response framework. We evaluate the relationship between indicators using a decision tree and numerical representations of interaction strength. We use a matrix multiplication procedure to model direct and indirect interaction effects, and we provide guidelines for combining effects. Results include several data tables from which information can be visualized to understand the plausible interaction effects of implementing management strategies on ecosystem services. We illustrate our method with a coastal water quality management case study on Cape Cod, Massachusetts.