Assessing food-web structure, matter fluxes, and system attributes of a Central European mountain stream by performing mass-balanced network analysis
Bibliographic record
Abstract
Trophic interactions and cycling of matter within the community in a soft-water mountain stream were analyzed on the basis of a compartment food-web model. The model describes (i) the structure of the food web, quantifying biomass, production, and consumption of individual elements as well as of the entire system, and (ii) the flow of matter between compartments as well as trophic levels. Detritus and primary producers sustain a broad variety of invertebrate consumers. Fishes are the top predators; sculpin (Cottus gobio) and a compartment consisting of brown trout (Salmo trutta) and rainbow trout (Oncorhynchus mykiss) are at the highest trophic level. Heterotrophic microorganisms (227.1 g dry mass (DW)·m2·year1) and aufwuchs algae (150.1 g DW·m2·year1) have the highest production. Secondary production of fishes and macroinvertebrates amounts to 2.56 and 19.9 g DW·m2·year1, respectively. Total consumption amounts to 1136.41 g DW·m2·year1. Main flows occur between the lower trophic levels. Food intake is greatest for microorganisms and Ephemeroptera. A relatively high fraction of invertebrate production is consumed by predators. For 10 of 19 compartments, over 95% of production is used as food by other organisms. Transfer efficiencies are generally low (<10%). A large proportion of matter transfer occurs at the lower discrete trophic levels of the stream.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".