TROPHIC LEVELS AND TROPHIC TANGLES: THE PREVALENCE OF OMNIVORY IN REAL FOOD WEBS
Bibliographic record
Abstract
The concept of trophic levels is one of the oldest in ecology and informs our understanding of energy flow and top-down control within food webs, but it has been criticized for ignoring omnivory. We tested whether trophic levels were apparent in 58 real food webs in four habitat types by examining patterns of trophic position. A large proportion of taxa (64.4%) occupied integer trophic positions, suggesting that discrete trophic levels do exist. Importantly however, the majority of those trophic positions were aggregated around integer values of 0 and 1, representing plants and herbivores. For the majority of the real food webs considered here, secondary consumers were no more likely to occupy an integer trophic position than in randomized food webs. This means that, above the herbivore trophic level, food webs are better characterized as a tangled web of omnivores. Omnivory was most common in marine systems, rarest in streams, and intermediate in lakes and terrestrial food webs. Trophic-level-based concepts such as trophic cascades may apply to systems with short food chains, but they become less valid as food chains lengthen.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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".