Data synthesis for environmental management: A case study of Chesapeake Bay

Journal of Environmental Management
By: , and 

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Abstract

Synthesizing large, complex data sets to inform resource managers towards effective environmental stewardship is a universal challenge. In Chesapeake Bay, a well-studied and intensively monitored estuary in North America, the challenge of synthesizing data on water quality and land use as factors related to a key habitat, submerged aquatic vegetation, was tackled by a team of scientists and resource managers operating at multiple levels of governance (state, federal). The synthesis effort took place over a two-year period (2016–2018), and the results were communicated widely to a) scientists via peer review publications and conference presentations; b) resource managers via web materials and workshop presentations; and c) the public through newspaper articles, radio interviews, and podcasts. The synthesis effort was initiated by resource managers at the United States Environmental Protection Agencys’ Chesapeake Bay Program and 16 scientist participants were recruited from a diversity of organizations. Multiple short, immersive workshops were conducted regularly to conceptualize the problem, followed by data analysis and interpretation that supported the preparation of the synthetic products that were communicated widely. Reflections on the process indicate that there are a variety of structural and functional requirements, as well as enabling conditions, that need to be considered to achieve successful outcomes from synthesis efforts.

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Publication type Article
Publication Subtype Journal Article
Title Data synthesis for environmental management: A case study of Chesapeake Bay
Series title Journal of Environmental Management
DOI 10.1016/j.jenvman.2022.115901
Volume 321
Year Published 2022
Language English
Publisher Elsevier
Contributing office(s) WMA - Earth System Processes Division
Description 115901, 11 p.
Country United States
Other Geospatial Chesapeake Bay
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