Assessing Fisheries Effort in Two Dynamic Pelagic Ecosystems

As human impacts on the global oceans increase, the effective protection of biodiversity and sustainable management of ocean resources has become increasingly important. Complicating these efforts is the fact that sixty-four percent of the surface area of the ocean is beyond national jurisdiction, but many pelagic ecosystems cross between national and international waters. In recent years, there have been efforts to create integrated, area-based management for these transboundary ecosystems, with the Costa Rica Thermal Dome in the Eastern Tropical Pacific Ocean and the Sargasso Sea in the North Atlantic emerging as potential candidates. This MP is a part of a larger project which will create an integrated model of ecology and human impacts, an analysis of existing policies and a set of conclusions aimed at informing and improving governance for each ecosystem. As a preliminary part of this larger analysis, this project characterized the spatial extent of commercial fisheries in each region. Fisheries are one of the largest direct impacts on pelagic ecosystems. The project relied on fishing effort data from Global Fishing Watch, which uses a machine learning algorithm to estimate fishing effort based on vessel track activity. Global Fishing Watch provides the data in an aggregated format, providing total fishing hours from each vessel in 0.1-degree cells. Global Fishing Watch also estimates fishing gear type and provides the flag for each vessel. These data were utilized to characterize fishing effort over six years, 2015–2020. Additionally, this analysis examined drivers of the spatial distribution of this effort. Two drivers were examined: jurisdiction and an environmental variable for each region. The fishing effort was categorized as either on the high seas or within national waters. In the Costa Rica Thermal Dome, water temperature at 35 meters depth was utilized as a proxy for the location of the Dome to see if fishing effort was tracking the upwelling area. In the Sargasso Sea, sea surface temperature was utilized as previous studies have found that sea surface temperature was a primary determinant of the spatial distribution of longlining. In both regions, fishing effort varies both seasonally and across years. In the Costa Rica Thermal Dome, three types of fishing were detected, with tuna purse seine fishing and drifting longline making up 99% of detected fishing effort by hour. Purse seine fishing was detected each year and varied seasonally. Drifting longline fishing increased substantially over the six years, with most of the effort conducted by 13 vessels flagged to Taiwan in 2019 and 2020. In the Sargasso Sea, four types of fishing were detected, with drifting longline making up 98% of detected fishing effort by hour. The analysis revealed that it is likely that multiple environmental and political factors drive the distribution of fishing effort in these two regions. In the Dome, the drifting longlining activity overlapped with the upwelling area while the purse seine fishing did not. In the Sargasso Sea, the drifting longlining fleet distribution appeared to be driven both by flag state and sea surface temperature. In both regions, vessels flagged to the coastal state conducted most of the fishing effort detected in its national waters. A notable exception to this is Costa Rica, where no Costa Rican flagged vessels were detected fishing, but vessels from many other states were. Limitations in the dataset, most notably catch data, make broad conclusions challenging. But these data indicate that it is likely that both political and environmental drivers are driving the spatial distribution of fisheries effort. Future research should consider the synergistic impacts of environmental and political factors in the spatial distribution of high seas commercial fishing effort. Additionally, the increase in drifting longline fishing and absence of squid jigging detected in the regions point to a need for proactive, rather than reactive, management.