An annual Data Update process between American lobster stock assessments was recommended during the 2020 stock assessment to more closely monitor changes in stock abundance. The objective of this process is to present information—including any potentially concerning trends—that could support additional research or consideration of changes to management. Although a stock assessment was completed in 2025, the American Lobster Management Board (Board) requested at its August 2025 meeting that a Data Update also be conducted and presented at the February 2026 Board meeting.
Committee Summaries and Reports to the Board
Detailed analyses and recommendations from technical committees, including working groups, sub-committees, plan development teams, and plan review teams, on specific scientific and management issues related to fisheries.
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An annual Data Update process between American lobster stock assessments was recommended during the 2020 stock assessment to more closely monitor changes in stock abundance. The objective of this process is to present information—including any potentially concerning trends—that could support additional research or consideration of changes to management. Although a stock assessment was completed in 2025, the American Lobster Management Board (Board) requested at its August 2025 meeting that a Data Update also be conducted and presented at the February 2026 Board meeting.
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In the absence of a commercial fishery, five trawlers and four trappers participated in a six-week pilot winter sampling program to collect northern shrimp samples in the Gulf of Maine during February – March 2025 under a research set-aside quota of 26.5 mt (or approximately 58,400 pounds). In total, the nine participants caught 70 individual northern shrimp weighing approximately 2.42 pounds, representing less than 1% of the research set-aside quota.
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Request for Board Guidance on Biological Reference Points and Spatial Management
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This memo describes the 2026 harvest recommendation for Delaware Bay Region horseshoe crabs using the methods from the Adaptive Resource Management (ARM) Framework (ASMFC 2022a).
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