Stock Status and Management in Tuna Fisheries: from data-rich to data-poor

Thesis (Ph.D.)--University of Washington, 2018Tunas and billfishes are large migratory species managed by Regional Fisheries Management Organizations (tRFMOs). The current status of these species is well known, and most of the large commercial tuna stocks are managed at sustainable levels. We found that most of the overfished tuna and billfish populations are showing signs of rebuilding as a consequence of the implementation of strong management measures such as fishing quotas. However, management performance among tRFMOs is highly variable among oceans and it is mainly correlated with the overall economic dependence of individual members of the tRFMOs on tuna fisheries. When countries with low governance capacity account for the greatest proportion of total tuna catches, management controls are, on average, harder to implement. On the other hand, some non-commercial valuable tuna stocks, such as mackerels and bonitos, managed under the umbrella of tRFMOs remain unassessed, mainly because of insufficient quantitative data, particularly total catch. Preliminary assessments for these stocks based only on length composition data from the catch, showed that some of these stocks are experiencing overfishing. These results should encourage the management body in the Atlantic Ocean to take management actions to protect these stocks from overfishing as well as improve data collection programs. When comparing the performance of some length-based and catch-based data limited assessment methods, we found that in many cases, length-based assessments performed as well as other catch-based models. Nevertheless, the performance of different data-limited methods depended not only on the type of data available, but on prior knowledge about the exploitation history of the stock and the biology of each species. We hope that this dissertation helps to improve the current management system for data-rich tuna stocks by highlighting successful management strategies, as well as to improve the estimation of stock status for data-poor tuna fisheries