The effects of trawling and primary production on size-structured food webs in seabed ecosystems
Bibliographic record
Abstract
Understanding how different drivers shape relationships between abundance and body mass (size spectra) is important for understanding trophic and competitive interactions in food webs and for predicting the effects of human pressures. Here, we sample seabed communities from small polychaetes (<0.001 g) to large fish (>1 kg) in the Celtic Sea and the western English Channel to examine how bottom trawling and primary production affect their size spectra and to compare these with predictions from a model that couples predator and detritivore communities. Size spectra were not well approximated by linear fits because of truncation of the size spectra of detritivores. Low primary production resulted in lower abundance of benthic fauna. Bottom trawling reduced the abundance of predators and large detritivores but allowed small detritivores to increase in abundance. These empirical size spectra were partly consistent with predictions from the size spectra model, showing that understanding the structuring of benthic communities requires a consideration of both size and functional group. The findings highlight the need for an ecosystem approach to understanding the effects of exploitation and climate change on marine ecosystems.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".