Fisheries Management in a Changing Climate – Insights from the Northwest Atlantic Lobster Fishery
Bibliographic record
Abstract
Globally, our oceans are in jeopardy due primarily to pollution, over fishing and climate change. Northwest Atlantic coastal and island communities have been founded on and flourished from their fisheries since the earliest records of human history and they stand to be impacted disproportionality by threats to the surrounding marine territory. Unlike other current day fisheries, the lobster fishery in this region is experiencing abundance. Catch rates and spawning stock biomass have been steadily increasing for over three decades due to the loss of predators, increase in waters temperature and management strategies. The increase in landings and value of the lobster fishery is widely viewed as a rare fisheries success story. However, the lack of economic diversity in the fisheries coupled with rising ocean temperatures and acidification hints at the potential for an economic disaster. We need look no further than the collapse of the northern cod to understand the implications of this for rural communities. In this presentation I provide an overview of scholarly literature on climate and biological science relating to the future of lobster in Atlantic Canada and lay out a case for concern. Then I analyse the formal and informal governance regimes in the lobster fisheries in the Northwest Atlantic for insight into specific management choices that have played a role in sustaining the fishery. Conclusions will be useful for lobster fishery policies and management – formal and informal. Insights may also have implications for other fisheries in the region.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".