Changing patterns in coastal cutthroat trout (<i>Oncorhynchus clarki clarki</i>) diet and prey in a gradient of deciduous canopies
Bibliographic record
Abstract
We examined the influence of riparian vegetation patterns on coastal cutthroat trout Oncorhynchus clarki clarki diet and prey from the summer of 2001 through the spring of 2002. Benthic and drifting invertebrates, allochthonous prey, and fish diet were collected from deciduous, conifer, and mixed sections of three Oregon coastal watersheds. The nine sites were best characterized as a continuum of deciduous cover, and shrub cover and proportion of deciduous canopy were positively correlated (r = 0.74). Most sources of prey (benthic invertebrate biomass, allochthonous invertebrate inputs, aquatic and total invertebrate drift) and aquatic prey ingested by coastal cutthroat trout were greater where shrub cover was more abundant. Only aquatic drift, total invertebrate drift, and allochthonous invertebrates were positively correlated with deciduous vegetation. Compared with coniferous sites, allochthonous invertebrates under deciduous and mixed canopies were almost 30% more abundant. Stream discharge likely influenced seasonal fluxes of aquatic invertebrate biomass in the benthos and drift. Aquatic insects dominated gut contents during this study; however, terrestrial prey were most common in the diet during the summer and fall. In the Pacific northwest, systematic removal of deciduous riparian vegetation to promote conifers may have unintended consequences on food resources of coastal cutthroat trout and aquatic food web interactions.
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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 | 0.000 |
| 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".