While all fishing gears have advantages and disadvantages (like everything else in life!) I have a special thing for longline…. While in most gears, physics and oceanography (they are closely related), the longline has a lot of chemistry… I explored that in my thesis on the development of a selective bait for the Longlining Fishery of Snapper (Pagrus auratus) and maintained an interest in it over the years, as you can read here, here, here and all over here, just to mention a few…, yet always from the perspective of understanding how a longliner catches a group of fishes but never thought on how longlines fish as a group.
So when I was approached by Tim Frawley (whose work I already blogged about here) to be involved in a paper he was writing with others on longliner fleet operations across the pacific, I was immediately interested. And finally, the paper was published (my 3rd paper in 3 years), and on top of that got published on my birthday!
From management, we see longlining in an almost binary approach: tropical and southern. In zone or HS, landing or transhipping… yet the reality is much more complex because longliners are never just one thing catching one type of fish in one place… reality ought to be more complex… and it is… substantially more complex!
Despite their value and ocean impacts, many longline fisheries remain opaque, so we characterised and analysed 11 distinct fishing fleets across the Pacific using public data sources.
In any case , and as usual, I recommend you read the original: Clustering of disaggregated fisheries data reveals functional longline fleets across the Pacific, as it is free. I just will quote the key parts of it, as I’m quite proud of my minimal role in this paper.
With improvements in technology, big ocean data are increasingly used to describe ocean uses and prioritize management action. Within fisheries, much of the discourse to date has concerned the identification of flag states responsible for illegal fishing and/or interactions with protected species. Yet, little guidance exists regarding how recent advances can be leveraged to inform the development of sustainable and equitable harvest-control rules. Here we link vessel movement and registration data with catch reports to characterize “functional fishing fleets” across the Pacific.
Considering the strengths and limitations of each data source, we argue they are more valuable when used collectively to support the evolution of existing management operations than as the sum of their parts deployed in isolation. Indeed, the future sustainability of high seas fisheries may hinge on increased cooperation and transparency required to harness and democratize the benefits of the digital ocean ecosystem for improved governance.
Summary
Ensuring the long-term sustainability of tuna, billfish, and other transboundary fisheries resources begins with data on the status of stocks, as well as information concerning who catches what fish, when, where, and how. Despite recent improvements in fisheries monitoring and surveillance, such dynamics remain poorly understood across the high seas. Here we delineate and describe pelagic longline activity in the Pacific Ocean using a framework that integrates descriptive vessel information and tracking data with species-specific catch reports.
When parsed by distinct vessel behaviors and attributes, disaggregated fisheries data highlight the existence of multi-national, multi-specific (i.e., targeting multiple species) fishing fleets, many of which target waters that span more than one management area.
Our findings emphasize the need for increased coordination across regional and sub-regional governance bodies and suggest that effective and equitable management of the sector may require efforts to move beyond single-species, single-area controls and operational distinctions based primarily on vessel flag and/or gear type alone.
Conclusions and future directions
This characterization of the activity patterns of pelagic longline fishing fleets in the Pacific is just the beginning of a more nuanced understanding of the sector. Undoubtedly, as data quantity, quality, and availability increase, additional fleets with unique behaviors and attributes will emerge from those we have described.
Nevertheless, our results provide valuable evidence of the utility of disaggregated fisheries analyses that integrate descriptive vessel information and tracking data with catch reports to identify and describe the behaviors and attributes of distinct fishing fleets. In the future, such classified groups have great potential to serve as a foundation for a more differentiated and targeted approach to fisheries research, monitoring, and management. Across other disciplines, the utility of disaggregated units is already recognized as critical for the monitoring and management of human-environment interactions.
For transboundary fisheries in the Pacific Ocean, fleet-disaggregated analyses could be used to:
Address the differential effects of time/area closures and catch quotas,
Analyze the competition for space among sectors (i.e., large-scale versus small-scale, longline versus purse-seine) and emerging ocean users (i.e., offshore wind farms and deep-sea mining claims),
Study the socioeconomic attributes and/or environmental associations of different fishing livelihood strategies,
Estimate bycatch and non-target species interactions, and
Audit self-reported logbook records.
Given the degree to which concerns regarding the relative distribution of costs and benefits continue to impede the adoption of pelagic longline management and conservations measures and recent research regarding the asymmetrical impacts of climate change on regional fishery landings and revenue, we suggest such applications are particularly salient for transboundary fisheries across the Pacific.