Mesoscale climatic impacts on the distribution of <i>Homarus americanus</i> in the US inshore Gulf of Maine
Bibliographic record
Abstract
American lobster (Homarus americanus) supports one of the most valuable fisheries in the United States. Spatial distributions of H. americanus are hypothesized to be influenced by climate-driven environmental factors, but such effects have not been quantified. We developed a Tweedie generalized additive model (GAM) to quantify environmental effects on season-, sex-, and size-specific distributions of H. americanus in the inshore Gulf of Maine. Tweedie GAMs were coupled with regional circulation model output to predict spatiotemporal changes in distribution of H. americanus due to mesoscale climate variability. GAM results indicated that bottom temperature and salinity impacts on H. americanus distribution were more pronounced during spring. The coupled climate–niche model predicted significantly higher H. americanus abundance under a warm climatology scenario. This study provides a predictive climate–niche modelling framework that may be useful for planning fishery investments and anticipating management challenges given ongoing climate-driven changes in the Northwest Atlantic.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".