Linking resource availability and habitat structure to stream organisms: an experimental and observational assessment
Bibliographic record
Abstract
An experiment and a mark‐recapture field study of juvenile coho salmon (Oncorhynchus kisutch) were conducted to identify controls of key energy flow chains in river food webs. In the small‐scale experiment, we investigated the individual and interactive effects of physical habitat structure (PHS) as small wood and resource availability (tissue of adult Chinook salmon, O. tshawytscha) on nutrients, algae, invertebrates, and fish predators including juvenile coho. In the field, we quantified the effects of natural variation in prey availability (invertebrate drift biomass), PHS (wood), and local fish density on summer growth of juvenile coho across multiple stream reaches. Adding salmon tissue to experimental channels resulted in strong bottom‐up effects on select invertebrates including increased population biomass of chironomids and baetids, the numerically dominant invertebrates, and faster growth of juvenile coho. We link the enhanced growth of coho to chironomid productivity: for instance, adult chironomid flux was 4.3× higher and coho consumption of these animals 3× higher in salmon‐subsidized channels. PHS in experimental channels was associated with reduced algal biomass, potentially in response to increased invertebrate consumption, and invertebrate flux or export. The field study revealed coho growth was negatively related to PHS and total fish density and positively related to Diptera drift biomass; however, the effects of fish density and drift biomass on coho growth were relatively weak. The field study also indicated that prey resource availability and coho growth were associated with differences in canopy cover, with prey biomass and coho growth 2–4× higher in reaches receiving more sunlight. As in the experiment, coho in natural stream reaches predominantly fed on adult chironomids and other Diptera, indicating that these taxa and life‐stages are a key link between the benthic food web and mobile vertebrate predators. Our study showed that bottom‐up processes initiated by salmon subsidies and possibly light flux determined key trophic interactions in the Cedar River food web. Moreover, we speculate that PHS may modify some of these interactions indirectly through its effects on the movement of organisms through the environment.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".