Regulation of trophic architecture across spatial scales in a major river network
Bibliographic record
Abstract
Abstract Moving beyond species count data is an essential step to better understand the effects of environmental perturbations on biodiversity and ecosystem functions, and to eventually better predict the strength and direction of those effects. Here, coupling an integrative path analysis approach with data from an extensive countrywide monitoring program, we tested the main spatial, environmental and anthropogenic drivers of change in stream macroinvertebrate trophic structure along the entire Swiss Rhine river catchment. Trophic structure was largely driven by inherent altitudinal variation influencing and cascading to regional scaled factors such as land use change and position in the riverine network, which, in turn, transformed local habitat structure variables. Those cascading effects across scales propagated through the biotic community, first affecting preys and, in turn, predators. Our results illustrate how seemingly less important factors can act as essential transmission belts, propagating through direct and indirect pathways across scales to generate the specific context in which each trophic group will strive or not, leading to characteristic landscape wide variations in trophic community structure.
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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 | 0.001 | 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".