Drivers of nitrogen transfer in stream food webs across continents
Bibliographic record
Abstract
Abstract Studies of trophic‐level material and energy transfers are central to ecology. The use of isotopic tracers has now made it possible to measure trophic transfer efficiencies of important nutrients and to better understand how these materials move through food webs. We analyzed data from thirteen 15 N‐ammonium tracer addition experiments to quantify N transfer from basal resources to animals in headwater streams with varying physical, chemical, and biological features. N transfer efficiencies from primary uptake compartments (PUCs; heterotrophic microorganisms and primary producers) to primary consumers was lower (mean 11.5%, range <1% to 43%) than N transfer efficiencies from primary consumers to predators (mean 80%, range 5% to >100%). Total N transferred (as a rate) was greater in streams with open compared to closed canopies and overall N transfer efficiency generally followed a similar pattern, although was not statistically significant. We used principal component analysis to condense a suite of site characteristics into two environmental components. Total N uptake rates among trophic levels were best predicted by the component that was correlated with latitude, DIN:SRP, GPP:ER, and percent canopy cover. N transfer efficiency did not respond consistently to environmental variables. Our results suggest that canopy cover influences N movement through stream food webs because light availability and primary production facilitate N transfer to higher trophic levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".