Diversity and habitat selectivity of harpacticoid copepods from sea grass beds in Pujada Bay, the Philippines
Bibliographic record
Abstract
The spatial diversity of meiofauna from sea grass beds of Pujada Bay (the Philippines), was studied with special emphasis on harpacticoid copepods. Sediment cores were obtained from areas adjacent to the different species of sea grasses. Meiofauna was enumerated at higher taxon level and harpacticoid copepods were identified to genus level. Diversity indices were calculated corresponding to the hierarchical levels of spatial biodiversity, i.e. alpha, beta and gamma. Nematodes were the most abundant meiofaunal group in all sediment layers and along the entire tidal gradient (37–92%); harpacticoids were second in abundance (3.0–40.6%) but highly diverse (N0: 9.33–15.5) at the uppermost sediment layer (0–1 cm) near all beds of sea grass species. There was a sharp turnover of harpacticoid genera along the tidal gradient, thus suggesting a relatively low proportion of shared genera among benthic communities in different sea grass zones. The families of Tetragonicipitidae and Miraciidae were the dominant harpacticoid groups occurring in all sediment layers of all sea grass species. The presence of the epiphytic genera of Metis at the deepest sediment layers in some sea grass species was striking. Overall, the major contributor to gamma (total) diversity of harpacticoid copepods in Pujada Bay is the high local (alpha) diversity (N0: 80.6%, H′: 94.7% of total diversity); hence, the habitat heterogeneity among sediment layers in sea grass beds is most relevant for the total diversity and richness of harpacticoid copepod genera in the area.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".