Effects of river sediments on coral recruitment, algal abundance benthic community structure on Kenyan coral reefs
Bibliographic record
Abstract
The effects of sediment concentration and season on coral recruitment algal abundance and benthic community structure were studied in Kenyan coral reef lagoons to determine their potential influence on coral recovery.Nutrient levels and recruit numbers were higher during the southeast monsoon (SEM) than during the northeast monsoon (NEM) season and in sediment-exposed compared to nonsediment exposed reefs.Mean algal biomass also exhibited the same seasonal trend (except at one site), but was higher in the non-sediment exposed reef compared to the other reefs.Corals in the sediment exposed reef exhibited morphological differences relative to the other reefs: fewer corymbose and plate-like but more branching, massive and solitary forms and increased colony and corallite sizes.However, sediments did not suppress coral recruitment rates.These morphological changes coupled with the interaction between biological and physico-chemical characteristics have important ecological and geological implications: by potentially modifying calcium carbonate production and ameliorating the adverse effects of climate induced stress events, this may minimize coral mortality and enhance reef recovery.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".