Northern Shrimp in the Gulf of Maine and the Impacts of Climate Change
Bibliographic record
Abstract
Northern Shrimp (Pandalus borealis) populations within the Gulf of Maine collapsed in 2011 following the first year that sea surface temperature surpassed 10ºC. The population collapse resulting in a moratorium in 2014. The waters of the Gulf of Maine have been rising at a rate of 0.045ºC per year, changing predator distribution, prey distribution, as well as Northern Shrimp biological variables. There has been very little recovery to the Northern Shrimp stock despite the fishing moratorium and the answers behind the collapse and lack of recovery remains enigmatic. Therefore, this two-chapter study includes a literature review and a research paper trying to determine the factors and mechanisms behind the Northern Shrimp population crash. The first chapter is a literature review investigating the direct and indirect impacts of increasing water temperatures on the Northern Shrimp stocks in the Gulf of Maine and Eastern Canada. The second chapter is a research paper addressing the question: Are there any patterns between SST and Northern Shrimp biological variables in either the GOM or the Scotian Shelf? The results demonstrate a possible temperature threshold of 10.1ºC for sea surface temperature and 8.1ºC for bottom temperature that above results in both biomass and spawning stock biomass collapse. Temperatures above these thresholds demonstrate high mortality rates in Northern Shrimp larvae and adults. The implications of these findings include Northern Shrimp fishery never returning to the Gulf of Maine and the Scotian Shelf in Eastern Canada possibly being the next location to experience the population collapse.
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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 | 0.000 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".