Electronic monitoring is a tool used to collect fishing data that support and improve stock assessments and ensure that catch limits are sustainable in the long term. NOAA Fisheries is investing in technology that fishermen use to track their catch. These new technologies hold promise in making data collection more timely, accurate, and cost-efficient.
Current Electronic Monitoring Programs
In the U.S., seven electronic monitoring programs have been implemented. These include:
- Several different uses of electronic monitoring in Alaska fisheries, including the small-boat fixed gear program using electronic monitoring to collect data on catch.
- The use of EM to monitor the bycatch of bluefin tuna in the Atlantic pelagic longline fishery.
There are also several electronic monitoring projects and programs under development with some expected to be fully implemented in the next few years. These include:
- Northeast - electronic monitoring in a portion of the multispecies groundfish fishery by May 1, 2021. The New England Fishery Management Council has approved wider adoption targeted for 2022.
- Northeast - electronic monitoring in the Atlantic Herring fishery, programs operating under exempted fishing permits in the mid-water trawl fleet (Spring 2021) and the purse seine fleet (2022).
- West Coast - electronic monitoring in the groundfish fishery, full implementation scheduled for January 1, 2022.
- Current Projects - projects are underway in the Pacific Islands pelagic longline fishery, midwater trawl pollock fishery in Alaska, and several fisheries in the Gulf of Mexico.
Taking Steps to Expand Electronic Monitoring
Working collaboratively with the fishing industry and the private sector, we have provided over $42 million since 2015 to develop and implement electronic technologies in more than 30 electronic reporting and monitoring pilot projects, as well as investments to transition programs out of the pilot phase to final implementation. We have also provided grants to the National Fish and Wildlife Foundation (NFWF) for their external grant program. In 2020 alone, NFWF awarded $4.1M to 16 projects across 14 states and Puerto Rico. However, funding is only one aspect of expanding electronic monitoring across our nation’s fisheries. It is critical to examine the complex challenges of hardware and software development to establish clear guidance and policies such as data confidentiality and data management, and to develop and implement modern data processing tools such as computer vision and artificial intelligence. We are also examining how to integrate electronic monitoring data into stock assessments and its use in monitoring bycatch with protected species.
Electronic Monitoring Policies and National Guidance
NOAA Fisheries has been developing policies and guidance in order to create consistent and clear expectations of electronic monitoring programs where appropriate, but also sharing best practices and lessons learned across regions for regional creativity and flexibility. We have developed a framework for allocating the costs and responsibilities of an electronic monitoring program with different governance structures, published guidance for retaining data when it is stored by a third-party service provider, and received public comments on data retention for federal records:
- Cost Allocation in Electronic Monitoring Programs
- Third-Party Minimum Data Retention
- NARA data storage
Currently, we are developing guidance on how to apply information laws (e.g., Freedom of Information Act, Federal Records Act) to raw imagery from electronic monitoring systems, and how to administer data privacy and confidentiality. We are also working to develop expectations of data access and data use; this will include considerations for incorporating electronic monitoring data into fisheries stock assessments, and how it could be used for monitoring interactions with protected resources, such as marine mammals, sea turtles, and birds.
Electronic Monitoring in the Future
The largest costs of most electronic monitoring programs are manual video review, data transmission, and storage. Computer vision and machine learning applications based on annotated image-training datasets offer the potential of greatly reducing costs while improving accuracy and providing data in near real-time. Currently, these tools are being developed for processing imagery to identify species; estimate weight and length; enumerate fishing gear (e.g., counting hooks on a longline); or simply determine if a vessel is in transit or fishing (i.e., whether catch is on board). There are also several examples of phone-based or tablet-based image capture, these greatly expand the ability to collect and share data from small-scale commercial and recreational fisheries.