Worldwide patterns of invertebrate drift abundance with implications for drift-feeding fishes
Bibliographic record
Abstract
Food abundance influences the distribution and productivity of animal populations. Invertebrates drifting in streams are a primary food source for many fishes, but the range and extent of drift abundance and factors that influence variability across streams are largely unknown. The way fishes encounter drift suggests prey handling time should limit ingestion rates as food abundance rises, but studies on drift foraging thresholds are limited. Here, we compiled data from 70 studies to assess drift abundance across a large spatial scale and examined how drift varies across environmental gradients. We also collected fish foraging rates from 31 studies to evaluate how drift foraging rates change with prey abundance. Most studies reported low drift densities, but overall variation was correlated with elevation, global position of streams, and precipitation. We found foraging rates paralleled drift abundance, and fish foraging initially increased with prey density but leveled off producing a type II functional response. Our study provides insight into factors that influence drift abundance but also indicates that food limitation may constrain productivity in fish populations from streams.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".