Resource matching across habitats is limited by competition at patch scales in an estuarine-opportunist fish
Bibliographic record
Abstract
I used field observations, assays, and experiments with the euryhaline cottid Cottus aleuticus to evaluate the extent to which average resource availability drives the large-scale distribution of these fish among upstream and estuarine habitats and how interspecific competition from a congener affects its performance in the estuary. Population densities of C. aleuticus were only consistent with resource densities across years during two of five study years, indicating a lack of resource matching at large temporal scales. On shorter temporal scales, fish growth rates that were two to three times higher in the estuary compared with the stream were inconsistent with the predictions of resource matching theory. A manipulation of C. aleuticus density showed that the estuary could support at least twice the number of individuals that occurred there; thus, the profitable estuary is underutilized. Interspecific competition with Cottus asper was partially responsible for this underutilization as indicated by a substantial reduction in growth and condition among C. aleuticus individuals in experimental manipulations that compared intra- and inter-specific effects. Observed spatial overlap between these two cottids combined with the results of the competition experiment suggests that C. aleuticus is more strongly limited in its ability to use estuarine habitats opportunistically by interspecific competition than by intraspecific competition.
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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 | 0.000 | 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 | 0.001 | 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) | 0.001 | 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".