Ecological Tracers Can Quantify Food Web Structure and Change
Bibliographic record
Abstract
Disruption of natural food webs is becoming a commonplace occurrence as a result of human activities. Considering this, there is a need to improve our ability to define food web structure as well as to detect and understand the implications of trophodynamic change. This requires the development, validation, and application of ecologicaltracers that can provide insights into the movement of energy, nutrients, and contaminants through food webs. In this study, we examine the utility of two groups of naturally occurring intrinsic tracers (stable nitrogen isotopes and fatty acids) to provide such information in a predatory seabird, the herring gull (Larus argentatus). Spatial and temporal patterns in gull trophic position (inferred from egg stable nitrogen isotope values) were related to gull diet composition (inferred from egg fatty acid concentrations). These two independent groups of ecological tracers provided corroborating evidence that gull trophic position was related to the degree to which aquatic foods, namely fish, were consumed. The use of these tracers in concert led to a better understanding of routes of energy flow and contaminant transfer in food webs and how these pathways may be affected by ecosystem change.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".