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ABSTRACT The Greater Atlantic Region Commercial Fishing Business Cost Survey (Cost Survey) collects essential cost information from federally permitted commercial fishing vessel owners in the Northeast United States to inform management decisions and meet the data needs of multiple statutory requirements. Despite design improvements and a heightened focus on limiting burden on participants prior to the most recent survey effort, the 2022 Cost Survey yielded a lower‐than‐anticipated response rate of 14.8%. When nonresponse is systematic, the data collected may not accurately reflect the full range of economic conditions across fishing fleets, making nonresponse an important area to investigate and mitigate. A nonresponse postcard was distributed for the first time in the Cost Survey's history to investigate the following research objectives: understand survey nonresponders' motivations for choosing not to participate in the effort, explain the dynamic between harvesters and managers using qualitative analysis, and identify actions that can be used to enhance voluntary research participation and relationships among all stakeholders. The results indicate that distrust of the National Oceanic and Atmospheric Administration (NOAA) Fisheries was the primary reason for nonresponse. Qualitative analysis of open‐ended comments identified recurring themes, including concerns about the use of sensitive financial information and an overall dissatisfaction with NOAA Fisheries in the region due to perceptions of overregulation and misaligned management priorities. This research can be used as a case study for both identifying and analysing participation barriers to fisheries data collection and provides diagnostic indicators of broader management challenges. The importance of qualitative analysis is showcased to bridge knowledge gaps between stakeholders and managers in a natural resource context. Approaches are suggested for improving survey engagement, strengthening stakeholder trust and ultimately enhancing the quality of economic data available for cost‐based policy decisions.
Conley et al. (Sun,) studied this question.