Lianne M. Allen-Jacobson, Andrew W. Jones, Anna J. Mercer, Steven X. Cadrin, Benjamin Galuardi, Doug Christel, Angela Silva, Andrew Lipsky, Janne B. Haugen
{"title":"通过比较精细和粗略渔业相关数据评估海上风电开发对渔业作业的潜在影响","authors":"Lianne M. Allen-Jacobson, Andrew W. Jones, Anna J. Mercer, Steven X. Cadrin, Benjamin Galuardi, Doug Christel, Angela Silva, Andrew Lipsky, Janne B. Haugen","doi":"10.1002/mcf2.10233","DOIUrl":null,"url":null,"abstract":"<p>Climate change will disrupt many aspects of the marine environment, with anticipated effects for half of northeastern U.S. fisheries. To mitigate effects of climate change, the United States has designated 90,650 km<sup>2</sup> (35,000 mi<sup>2</sup>) of ocean for offshore wind energy development, but this growing industry could impact fisheries in the region. Hence, there is a need to measure the spatial distribution of fishing operations to support multiple goals, including spatial planning and compensatory mitigation. In the U.S. Northeast, National Oceanic and Atmospheric Administration Fisheries developed fishing footprints previously by using logbooks. However, logbook footprints rely on coarse data: a single location, the center point of fishing trips reported in logbooks. Therefore, we evaluated bias in these logbook footprints by restricting the size of logbook footprints and by generating active-fishing footprints from fine-scale location data collected by a reference fleet operating in the same region. Active-fishing footprints act as a benchmark approximating the “true” fishing footprint and exposure to wind farms. We focused on the longfin inshore squid <i>Doryteuthis pealeii</i> fishery, including 336 trips from 2016 to 2019, and 38 wind farms in southern New England and the Middle Atlantic Bight. Compared to the benchmark active-fishing footprints, unrestricted logbook footprints detected all exposed trips. As we restricted the logbook footprints, the logbook analysis failed to detect exposed trips but better approximated the amount of exposed revenue. Finally, unrestricted logbook footprints underestimated the exposed revenue for high-impact wind farms and overestimated the exposed revenue for low-impact wind farms, and this bias declined with logbook footprint restriction. We show how restricting logbook footprints could improve exposure analysis that depends on coarse-scale data when fine-scale data are unavailable. Furthermore, our analysis highlights the limits of coarse-scale data (i.e., logbook footprints). Therefore, we recommend additional incentives for voluntary participation in programs collecting fine-scale data. These incentives should be prioritized because informed, time-sensitive decisions depend on data collected prior to construction of offshore wind farms.</p>","PeriodicalId":51257,"journal":{"name":"Marine and Coastal Fisheries","volume":"15 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mcf2.10233","citationCount":"0","resultStr":"{\"title\":\"Evaluating Potential Impacts of Offshore Wind Development on Fishing Operations by Comparing Fine- and Coarse-Scale Fishery-Dependent Data\",\"authors\":\"Lianne M. Allen-Jacobson, Andrew W. Jones, Anna J. Mercer, Steven X. Cadrin, Benjamin Galuardi, Doug Christel, Angela Silva, Andrew Lipsky, Janne B. 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Therefore, we evaluated bias in these logbook footprints by restricting the size of logbook footprints and by generating active-fishing footprints from fine-scale location data collected by a reference fleet operating in the same region. Active-fishing footprints act as a benchmark approximating the “true” fishing footprint and exposure to wind farms. We focused on the longfin inshore squid <i>Doryteuthis pealeii</i> fishery, including 336 trips from 2016 to 2019, and 38 wind farms in southern New England and the Middle Atlantic Bight. Compared to the benchmark active-fishing footprints, unrestricted logbook footprints detected all exposed trips. As we restricted the logbook footprints, the logbook analysis failed to detect exposed trips but better approximated the amount of exposed revenue. Finally, unrestricted logbook footprints underestimated the exposed revenue for high-impact wind farms and overestimated the exposed revenue for low-impact wind farms, and this bias declined with logbook footprint restriction. We show how restricting logbook footprints could improve exposure analysis that depends on coarse-scale data when fine-scale data are unavailable. Furthermore, our analysis highlights the limits of coarse-scale data (i.e., logbook footprints). Therefore, we recommend additional incentives for voluntary participation in programs collecting fine-scale data. 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Evaluating Potential Impacts of Offshore Wind Development on Fishing Operations by Comparing Fine- and Coarse-Scale Fishery-Dependent Data
Climate change will disrupt many aspects of the marine environment, with anticipated effects for half of northeastern U.S. fisheries. To mitigate effects of climate change, the United States has designated 90,650 km2 (35,000 mi2) of ocean for offshore wind energy development, but this growing industry could impact fisheries in the region. Hence, there is a need to measure the spatial distribution of fishing operations to support multiple goals, including spatial planning and compensatory mitigation. In the U.S. Northeast, National Oceanic and Atmospheric Administration Fisheries developed fishing footprints previously by using logbooks. However, logbook footprints rely on coarse data: a single location, the center point of fishing trips reported in logbooks. Therefore, we evaluated bias in these logbook footprints by restricting the size of logbook footprints and by generating active-fishing footprints from fine-scale location data collected by a reference fleet operating in the same region. Active-fishing footprints act as a benchmark approximating the “true” fishing footprint and exposure to wind farms. We focused on the longfin inshore squid Doryteuthis pealeii fishery, including 336 trips from 2016 to 2019, and 38 wind farms in southern New England and the Middle Atlantic Bight. Compared to the benchmark active-fishing footprints, unrestricted logbook footprints detected all exposed trips. As we restricted the logbook footprints, the logbook analysis failed to detect exposed trips but better approximated the amount of exposed revenue. Finally, unrestricted logbook footprints underestimated the exposed revenue for high-impact wind farms and overestimated the exposed revenue for low-impact wind farms, and this bias declined with logbook footprint restriction. We show how restricting logbook footprints could improve exposure analysis that depends on coarse-scale data when fine-scale data are unavailable. Furthermore, our analysis highlights the limits of coarse-scale data (i.e., logbook footprints). Therefore, we recommend additional incentives for voluntary participation in programs collecting fine-scale data. These incentives should be prioritized because informed, time-sensitive decisions depend on data collected prior to construction of offshore wind farms.
期刊介绍:
Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science publishes original and innovative research that synthesizes information on biological organization across spatial and temporal scales to promote ecologically sound fisheries science and management. This open-access, online journal published by the American Fisheries Society provides an international venue for studies of marine, coastal, and estuarine fisheries, with emphasis on species'' performance and responses to perturbations in their environment, and promotes the development of ecosystem-based fisheries science and management.