Migration supports uneven consumer control in a sewage‐enriched river food web
Bibliographic record
Abstract
Summary We studied the response of the St Lawrence River food web to enrichment by primary‐treated sewage from the city of Montreal, Canada. Despite the richness and complexity of this food web, the openness of the system and the limited production possible in this temperate river's short growing season, we found that biomass densities of consumers responded to enrichment according to the qualitative predictions of a simple bioenergetic model. All consumer trophic levels responded to sewage enrichment, but not all members of each trophic level: top piscivores seemed to control small, benthivorous fish but were unable to control larger fish, so the intermediate consumer level became dominated by Catastomidae (suckers). Consequently, the epiphytic prey of small fish were free to respond to sewage enrichment, but the benthic prey of suckers were not. The important elements of complexity seemed to be the factors that determine the realized pattern of feeding linkages: heterogeneity in prey vulnerability (predator–prey size ratios) and predator efficiency (vegetation cover for ambush predators, inaccessibility of epiphytic prey to bottom‐feeding suckers). Because of the openness of the system, the community was able to respond to enrichment by a combination of demographic (production) and behavioural (migration) mechanisms. We argue that the food web model described an energetically favourable state, and that migration provided a ‘shortcut’ for the system to approach this state within a short growing season.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".