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Global Fisheries Responses to Culture, Policy and COVID-19 from 2017 to 2020
Remote Sensing ; 13(22):4507, 2021.
Article in English | MDPI | ID: covidwho-1512553
ABSTRACT
Global Fishing Watch (GFW) provides global open-source data collected via automated monitoring of vessels to help with sustainable management of fisheries. Limited previous global fishing effort analyses, based on Automatic Identification System (AIS) data (2017–2020), suggest economic and environmental factors have less influence on fisheries than cultural and political events, such as holidays and closures, respectively. As such, restrictions from COVID-19 during 2020 provided an unprecedented opportunity to explore added impacts from COVID-19 restrictions on fishing effort. We analyzed global fishing effort and fishing gear changes (2017–2019) for policy and cultural impacts, and then compared impacts of COVID-19 lockdowns across several countries (i.e., China, Spain, the US, and Japan) in 2020. Our findings showed global fishing effort increased from 2017 to 2019 but decreased by 5.2% in 2020. We found policy had a greater impact on monthly global fishing effort than culture, with Chinese longlines decreasing annually. During the lockdown in 2020, trawling activities dropped sharply, particularly in the coastal areas of China and Spain. Although Japan did not implement an official lockdown, its fishing effort in the coastal areas also decreased sharply. In contrast, fishing in the Gulf of Mexico, not subject to lockdown, reduced its scope of fishing activities, but fishing effort was higher. Our study demonstrates, by including the dimensions of policy and culture in fisheries, that large data may materially assist decision-makers to understand factors influencing fisheries’ efforts, and encourage further marine interdisciplinary research. We recommend the lack of data for small-scale Southeast Asian fisheries be addressed to enable future studies of fishing drivers and impacts in this region.

Full text: Available Collection: Databases of international organizations Database: MDPI Language: English Journal: Remote Sensing Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: MDPI Language: English Journal: Remote Sensing Year: 2021 Document Type: Article