Simplification of seagrass food webs across a gradient of nutrient enrichment
Bibliographic record
Abstract
Anthropogenic nutrient enrichment has resulted in significant changes in food web structure. Although such changes have been associated with the loss of diversity and ecosystem services, little empirical work has been done to study food webs of similar systems across a nutrient enrichment gradient. We examined 11 seagrass beds along a gradient of increasing δ15N of primary consumers, where δ15N is used as an indicator of sewage-derived nutrients. Observations across this gradient revealed corresponding increases in consumer density and changes in distinct functional groups, whereas consumer diversity, seagrass canopy, and macrodetrital biomass decreased. However, maximum overall primary consumer diversity and minimum density occurred at intermediate levels along the nutrient gradient. We hypothesize that higher species diversity at low to moderate levels of nutrient enrichment depends on the persistence of grazer-resistant seagrass. This seagrass canopy, and the significant macrodetritus it generates, facilitates a variety of food and shelter resources. Overgrazed and simplified habitats may occur when densities of generalist urchins, capable of direct producer consumption, are no longer controlled through competition, predation, and intraguild predation. We hypothesize that high and stable urchin populations appear possible with the increased availability of allochthonous phytoplankton and associated particulate detritus that is a well-known consequence of nutrient enrichment in aquatic systems.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".