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Tagging

The Tagging Project is a collaborative effort between Homarus, the Prince Edward Island Fishermen's Association (PEIFA), and the Canadian Lobster Research Network (CLRN) to better understand lobster movement and behaviour in Atlantic Canada. The project responds directly to concerns from fishers about changing lobster landings and seeks to provide new insights into migration patterns, habitat use, and how environmental changes may be influencing local stocks.

Large-scale lobster tagging has not been conducted in the southern Gulf of St. Lawrence in more than two decades. Building on previous Department of Fisheries and Oceans (DFO) studies from 1980–1997, this renewed effort uses both traditional streamer tags and modern satellite tags to track lobster movement within and between Lobster Fishing Areas (LFAs) 23 and 24.
 
Tagging began in fall 2024 in LFA 23, where local fishers had reported lower lobster landings and wanted to better understand how lobsters move within the area. Early results revealed interesting movement patterns and sparked interest from other fishing communities.

In 2025, tagging efforts are expanding to include new sites in Caraquet, Neguac, Petit Rocher, and Val Comeau in New Brunswick, as well as Tignish, Malpeque, North Rustico, Savage Harbour, and North Lake in LFA 24 around Prince Edward Island’s north shore. These sites were chosen for their strategic locations, particularly near the Baie des Chaleurs and the LFA 23/25 boundary, where fishers have raised questions about seasonal migrations and the overlap of spring and fall fisheries.

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Project Goals
 

  • Monitor lobster movement across LFA boundaries and within key fishing grounds.

  • Establish a 2025 baseline of lobster behaviour and movement in the southern Gulf.

  • Provide science-based information to help fishers and managers adapt to changing ocean conditions.


Analysis and Knowledge Sharing

Tag return data and satellite information will be analyzed to estimate movement distances, identify patterns related to lobster size or sex, and compare findings with historical studies. The satellite data will help model seasonal behaviour.

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