The effects of temperature and predator densities on the consumption of walleye pollock (<i>Gadus chalcogrammus</i>) by three groundfish in the Gulf of Alaska
Bibliographic record
Abstract
Many multispecies models have assumed that prey density determines per-capita predator consumption rates, following a functional response relationship. However, empirical evidence suggests that a predator’s diet can also be influenced by a variety of environmental factors, including interactions with other predators. We used diet and abundance data from National Marine Fisheries Service (NMFS) bottom trawl surveys for three groundfish predators (Pacific cod (Gadus macrocephalus), Pacific halibut (Hippoglossus stenolepis), and sablefish (Anoplopoma fimbria)) in the Gulf of Alaska (GOA) to determine whether temperature or other species influence the consumption of walleye pollock (Gadus chalcogrammus). Using an information-theoretic approach, we tested for relationships between walleye pollock observed in predator stomachs and predator length, bottom temperature, prey availability (walleye pollock catch per unit effort (CPUE) scaled by observed prey lengths), and CPUE of the three predators and arrowtooth flounder (Atheresthes stomias). Predator length was positively related to walleye pollock presence and proportion of total diet mass in all predators. Increased temperatures negatively affected consumption of walleye pollock by Pacific halibut, but not the other predators. We found evidence for a number of interpredator effects of co-occurring predators, both positive (facultative) and negative (competitive). Surprisingly, observed prey density was not statistically significant with respect to consumption for these predators, suggesting that trawls sample the environment far differently than walleye pollock predators or species interactions are more complex than those used in previous multispecies models. These factors should be considered for future models contributing to ecosystem-based management.
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 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) | 0.000 | 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".