Incorporating prey fields into North Atlantic right whale density surface models
Bibliographic record
Abstract
Predictions of North Atlantic right whale Eubalaena glacialis distributions are an increasingly important tool used in conservation efforts for this Critically Endangered species. Right whales feed upon calanoid copepods, primarily Calanus finmarchicus . Incorporating prey distributions and characteristics into right whale density surface models (DSMs) has the potential to improve predicted whale distribution and provide a more mechanistic basis for interpretation. To explore this possibility, we tested different prey and prey proxy covariates to represent prey within a right whale DSM. We then assessed the relationship fitted to each prey or prey proxy covariate and determined which covariates added the most predictive power. The top-performing model included a combination of covariates representing high-density C. finmarchicus , Centropages typicus , and Pseudocalanus spp. aggregations and resulted in density predictions consistent with the observed distribution patterns of right whales. Predicted density was most prominent in the deep basins of the Gulf of Maine and the Great South Channel. Density generally increased in the summer and decreased in the winter, consistent with the current understanding of right whale foraging phenology. Continued monitoring of prey resources and development of prey fields for use in models are imperative to successful conservation of endangered marine predators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 teacher head, 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".