ORCID Profile
0000-0003-0765-7518
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Publisher: Elsevier BV
Date: 10-2019
Publisher: Authorea, Inc.
Date: 04-11-2020
Publisher: Elsevier BV
Date: 07-2009
Publisher: University of Tasmania
Date: 2020
Publisher: Wiley
Date: 24-05-2022
DOI: 10.1111/FAF.12676
Abstract: By‐catch is the most significant direct threat marine megafauna face at the global scale. However, the magnitude and spatial patterns of megafauna by‐catch are still poorly understood, especially in regions with very limited monitoring and expanding fisheries. The Indian Ocean is a globally important region for megafauna bio ersity and for tuna fisheries, but has limited by‐catch data. Anecdotal and scattered information indicates high by‐catch could be a major threat. Here, we adapt a Productivity Susceptibility Analysis tool designed for data‐poor contexts to present the first spatially explicit estimates of by‐catch risk of sea turtles, elasmobranchs, and cetaceans in the three major tuna fishing gears (purse seines, longlines, and drift gill nets). Our assessment highlights a potential opportunity for multi‐taxa conservation benefits by concentrating management efforts in particular coastal regions. Most coastal waters in the northern Indian Ocean, including countries that have had a minimal engagement with regional management bodies, stand out as high risk for fisheries interactions. In addition to species known to occur in tuna gears, we find high vulnerability to multiple gear types for many poorly known elasmobranchs that do not fall under any existing conservation and management measures. Our results indicate that current by‐catch mitigation measures, which focus on safe‐release practices, are unlikely to adequately reduce the substantial cumulative fishing impacts on vulnerable species. Preventative solutions that reduce interactions with non‐target species (such as closed areas or seasons, or modifications to gear and fishing tactics) are crucial for alleviating risks to megafauna from fisheries.
Publisher: American Physical Society (APS)
Date: 13-11-2007
Publisher: Springer Science and Business Media LLC
Date: 27-12-2016
Publisher: figshare
Date: 2020
Publisher: Elsevier BV
Date: 03-2011
Publisher: Springer Science and Business Media LLC
Date: 02-03-2021
Publisher: figshare
Date: 2020
Publisher: Springer Science and Business Media LLC
Date: 29-05-2022
Publisher: Springer Science and Business Media LLC
Date: 12-01-2021
Publisher: Proceedings of the National Academy of Sciences
Date: 28-05-2019
Abstract: We independently reconstructed vessels number, engine power, and effort of the global marine fishing fleet, in both the artisanal and industrial sectors. Although global fishing capacity and effort have more than doubled since 1950 in all but the most industrialized regions, the nominal catch per unit of effort (CPUE) has comparatively decreased. Between 1950 and 2015 the effective CPUE, among the most widely used indicator to assess fisheries management and stocks well being, has decreased by over 80% for most countries. This paper highlights the large differences in the development of sectorial fishing fleets regionally. This detailed paper empowers future exploration of the drivers of these changes, critical to develop sector and regionally specific management models targeting global fisheries sustainability.
Publisher: Frontiers Media SA
Date: 16-10-2020
Publisher: Elsevier BV
Date: 03-2022
Publisher: American Physical Society (APS)
Date: 21-11-2011
Publisher: Wiley
Date: 19-07-2021
DOI: 10.1111/FAF.12593
Abstract: Implementation of the United Nations Sustainable Development Goals requires assessments of the global state of fish populations. While we have reliable estimates of stock status for fish populations accounting for approximately half of recent global catch, our knowledge of the state of the majority of the world's “unassessed” fish stocks remains highly uncertain. Numerous publications have produced estimates of the global status of these unassessed fisheries, but limited quantity and quality of data along with methodological differences have produced counterintuitive and conflicting results. Here, we show that despite numerous efforts, our understanding of the status of global fish stocks remains incomplete, even when new sources of broadly available data are added. Estimates of fish populations based primarily on catch histories on average performed 25% better than a random guess. But, on average, these methods assigned fisheries to the wrong FAO status category 57% of the time. Within these broad summaries, the performance of models trained on our tested data sources varied widely across regions. Substantial improvements to estimates of the state of the world's exploited fish populations depend more on expanded collection of new information and efficient use of existing data than development of new modelling methods.
No related grants have been discovered for Yannick Rousseau.