Macroinvertebrate Diversity and Tourism Impacts in Coral Reef Ecosystems: Comparative Analysis and Sustainable Management Implications from Tabuhan Island and Bangsring Underwater Beach, Indonesia
Bibliographic record
Abstract
Understanding the effects of tourism pressure on macroinvertebrate diversity is essential for sustainable coral reef management.This study compared the community structure of macroinvertebrates in two coral reef ecosystems in East Java, Indonesia-Tabuhan Island and Bangsring Underwater Beach-using the Reef Check method along 100-meter transects at three stations in each site.Tabuhan Island supported six out of nine indicator species, with diversity index (H') values ranging from 0.66 to 1.14, evenness (E) up to 0.90, and dominance (C) between 0.39 and 0.63.In contrast, Bangsring Underwater Beach exhibited a sharp decline, recording only one indicator species, with both diversity and evenness indices at zero and dominance at 1.00.Although water quality parameters in both locations met optimal standards for coral reefs, the drastic difference in macroinvertebrate community structure was strongly associated with the intensity of tourism activities, including visitor numbers exceeding 1.1 million in Bangsring over three years.These findings highlight that anthropogenic pressures, particularly from tourism, outweigh abiotic factors in shaping macroinvertebrate assemblages and reef resilience.The study recommends strict visitor regulations, spatial zoning of tourism, community engagement in monitoring, and habitat restoration to safeguard coral reef biodiversity.This research provides vital baseline data to inform sustainable management strategies and supports the achievement of Sustainable Development Goals, especially SDG 14 (Life Below Water) and SDG 12 (Responsible Consumption and Production), offering a replicable model for similar high-pressure coastal tourism regions.
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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".