The functional response of drift-feeding Arctic grayling: the effects of prey density, water velocity, and location efficiency
Bibliographic record
Abstract
An important aspect of a predatorprey system is the functional response of the predator to changing prey densities. We studied the feeding rate response of drift-feeding Arctic grayling (Thymallus arcticus) on a small invertebrate prey, Daphnia middendorffiana, at densities ranging from 0.01 L1 to 1.8 L1 and current velocities of 25, 32, and 40 cm·s1. We videotaped the feeding of grayling to determine the duration of the search and pursuit components of the feeding cycle and the location efficiency of grayling feeding at different current velocities. Feeding rate increased approximately as the prey density to the 0.4 power from 0.01 to 1.25 prey·L1, above which the feeding rate dropped. Current velocity had no significant effect on feeding rate. Search and pursuit times dropped with increasing prey density, but neither was affected by current velocity. However, current velocity reduced both maximum location distance and location efficiency. The lack of increase in feeding rate with increasing current velocity may be due to a trade-off between the increasing likelihood of encounter and decreasing location efficiency as current velocity increases. These data suggest that grayling could effectively feed in a variety of stream habitats with different current velocity.
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 | 0.000 |
| 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".