4.5 Years of Data
(Jan ’12 – Jun ’17)
- 641 vessels capable of transshipping fish at sea.
- 71,468 Potential Rendezvous: Transshipment-capable vessels going slow enough and long enough to transship.
- 5,783 Likely Rendezvous: Potential rendezvous in which a fishing vessel was also recorded traveling slow enough, close enough, and long enough to transship.
In 2017, we released an original report that revealed remarkable new insights about what goes on between fishing vessels at sea. In our report, The Global View of Transshipment*, our analyses created the first global footprint of rendezvous behavior within the ocean fishing industry. It is the first comprehensive picture of potential transshipment ever published, and it lays the groundwork for significant reductions in Illegal, Unreported, and Unregulated catch entering the global seafood market.
Vessels meet at sea for multiple reasons, such as refueling and exchanging crew, but in the commercial fishing industry, they also meet to transfer catch, or transship. Large vessels with refrigerated holds collect catch from multiple fishing boats and carry it back to port. By enabling fishing vessels to remain on the fishing grounds, transshipment reduces fuel costs and ensures catch is delivered to port more quickly. It also leaves the door open for mixing illegal catch with legitimate catch, drug smuggling, forced labor and human rights abuses aboard fishing vessels that remain at sea for months or years at a time. As a pathway for illegal catch to enter the global market, transshipment prevents an accurate measurement of the amount of marine life being taken from the sea. It obscures the seafood supply chain from hook to port and hobbles efforts to manage fisheries sustainably.
For these reasons, transshipment is illegal in many cases, but it has been largely invisible and nearly impossible to manage, because it often occurs far from shore and out of sight. Until now. Identifying when and where transshipment happens can play a significant role in reducing illegal activity at sea.
Patterns Revealed by a Global View
Our report emphasized that transshipment is a significant pan-national problem involving ships registered to a diverse array of countries operating on the high seas and in offshore waters far from their home ports.
We identified important patterns in the data noting that:
- Transshipment in offshore coastal waters is more common in regions with a high proportion of Illegal, Unreported, and Unregulated (IUU) fishing than in regions where management is strong such as in North America and Europe.
- Clusters of transshipment activity occur along Exclusive Economic Zone (EEZ) borders of some countries, and inside those zones of nations with high corruption ratings and with limited monitoring capabilities.
These correlations do not provide any proof of specific illegal behavior but they raise important questions and can lead to more informed international efforts by fisheries management organizations to prevent or better regulate transshipment.
Applying Machine Learning to Detect Transshipment
With two hundred thousand ships on the ocean, spotting a refrigerated cargo vessel meeting up with a fishing vessel could take an analyst months on end. The analytical tools developed for our report do it automatically in days or hours. Using machine learning, we processed more than 21 billion Automatic Identification System (AIS) signals broadcast from ships at sea to identify vessels capable of receiving transshipments and analyze their movements. Those vessels include fish tenders, live fish carriers, factory/processors and refrigerated cargo vessels. Verifying our results with confirmed fishery registries and open source online resources, we identified 641 vessels capable of transshipping fish at sea between 2012 and July 2017, and 71,468 incidents in which one of these vessels exhibited telltale transshipment behavior patterns such as drifting slowly enough and long enough to receive a transfer of catch.
The vast majority of those occurrences were not accompanied by signals from fishing vessels, and their activity cannot be verified, but, given that many fishing vessels turn off their AIS device when they do not want to be detected, and some fishing vessels do not have AIS, these events must be considered “potential rendezvous.” Drilling down through the 71,468 occurrences, we identified 5,783 instances in which a fishing vessel was also confirmed to exhibit this behavior within close proximity of the transshipment vessel. We have labeled these “likely rendezvous.” Our algorithm was verified by matching a subset of “likely rendezvous” to known transshipments recorded by fishing registries.
Release of this report and the related datasets represent our first steps toward revealing vessel behaviors that are often hidden at sea. We are currently developing a transshipment layer to add to our fishing activity map and permanently lift the veil from the previously invisible practice of transshipment. With these new analytical tools, developed using AIS data, fisheries managers will be able to identify and monitor transshipment anywhere in the world. We are also expanding our view of fishing vessels and rendezvous activity as we incorporate additional data sources, including government Vessel Monitoring System (VMS) data, and continue to mine our data for a deeper understanding of vessel rendezvous patterns and potential transshipment activity.
Others are also working with our transshipment data and analyses to make important discoveries that can reduce the illegal activity associated with transshipment and influence policymaking. Some of their stories are included under in the Related Posts on this page.
* The original report published in February, 2017 was revised in August 2017 to reflect an update to terminology and the database.
The report and associated datasets are free for download.
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This work was supported by a grant to SkyTruth from the Walton Family Foundation and made possible by Google through the in-kind use of Google’s cloud computing platforms and technical and project guidance.