Biogeographic variation in coral species diversity on coral reefs in three regions of Indonesia
Bibliographic record
Abstract
Abstract . This paper assesses variation in coral species diversity within the Indonesian archipelago, and the influence of regional species pools, geomorphology and anthropogenic pollution on coral species diversity and occurrence. We obtained transects from 33 sites on 14 reefs in three regions of Indonesia: Ambon (Moluccas), South Sulawesi and the Java Sea. We determined the within‐site species richness by using species‐sampling curves. Cluster analysis and multi‐dimensional scaling showed that land‐based pollution was the primary determinant of coral species diversity and species occurrence on reefs. Relatively unaffected reference sites in eastern Indonesia were approximately 20% more diverse than Java Sea reference sites. Rare species formed a higher proportion of the coral fauna on eastern Indonesian sites, and eastern Indonesian apparent endemic species contributed approximately 25% of the total species pool sampled. Between‐site variation in species occurrence was lower on Java Sea reefs than on eastern Indonesian reefs. A larger species pool in eastern Indonesia than in the Java Sea probably accounted for most of the difference in within‐site species diversity between eastern Indonesian and Java Sea reference sites. High fishing intensity in the Java Sea, including destructive fishing practices, may have also contributed to reduced within‐site species diversity on Java Sea reference reefs. Despite the fact that the Java Sea was exposed during Pleistocene lowstands, and was recolonized by marine organisms only within the last 10 000 years, coral species diversity and assemblage composition on the Java Sea reefs was largely similar to open ocean reefs in eastern Indonesia.
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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".