Response of Scotian Shelf silver hake (<i>Merluccius bilinearis</i>) to environmental variability
Bibliographic record
Abstract
Abstract Commercially‐exploited fish populations are not only shaped by fishing pressure, but also by the dynamics of their environment. By quantifying the influence of environmental variability, fisheries management advice can be improved and uncertainties reduced. To this end, we developed statistical models of the response of Scotian Shelf silver hake stock metrics to variability in zooplankton community composition and phenology over the past 18 years and in the physical environment since 1985. Dominant modes of variability in these pelagic habitat indicators were characterized using principal component analysis, and the relationships of silver hake condition, abundance, and recruitment to pelagic habitat variability were assessed using generalized additive models. Condition was largely modulated by the onset and duration of the spring bloom, which controls food availability. In contrast, adult abundance was governed by composition of the zooplankton community and bottom‐water temperature, which dictates the distribution of silver hake. Finally, recruitment was affected by both thermal conditions and food availability. Our results presented here form the basis for qualitative assessment of ecosystem attributes and the influence on silver hake stock productivity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.048 | 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 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".