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Climate change is increasingly threatening coastal communities around the world. This article reviews the literature on climate change impacts and adaptation in the Chesapeake Bay region (USA). We reviewed both climate impacts and adaptation literature (n = 283) published in the period 2007–2018 to answer the questions: (i) how are indicators of climate impacts measured and reported by different types of authors (e.g., scientists, government, and NGOs), document types (e.g., academic articles or reports), and geographic focus (e.g., State, region, county, or municipal level)? (ii) what are the current approaches for measuring the most pressing climate impacts in the Chesapeake Bay? We found that scientists produce the most amount of data but are increasingly shifting towards engaging with practitioners through reports and online resources. Most indicators focus on the Chesapeake Bay scale, but data is most needed at the local level where adaptive policies are implemented. Our analysis shows emerging approaches to monitoring climate hazards and areas where synergies between types of authors are likely to increase resilience in the 21st century. This review expands the understanding of the information network in the Chesapeake Bay and explores the institutional landscape of stakeholders involved in the production and consumption of environmental and social change data. The analysis and insights of this review may be extended to similar regions around the planet experiencing or anticipating similar climate hazards to the Chesapeake Bay.

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Participatory research engages a transdisciplinary team of stakeholders in all aspects of the research process. Such engagement can lead to shifts in the research design, as well as who is considered a participant. We detail our experiences of studying an evolving stakeholder network in the context of a 2.5-year transdisciplinary, participatory project. We show how participation leads to shifts in the network boundary overtime and how a transdisciplinary effort was needed to retrospectively redefine the network boundary. Through tacking back and forth between ethnographic insights, research aims, and modeling assumptions, the team eventually reached agreement on what determined network membership and how to code network members according to their timing and level of participation. Our account advances literature on boundary and modeling approaches to shifting, evolving networks by demonstrating how participatory transdisciplinarity can be both a driver of, and solution to, capturing the complexity of evolving networks.