The Ecology of <i>Terpios hoshinota </i>in the Maldives Based on Three Decades of Observation
Bibliographic record
Abstract
Coral reefs are experiencing significant degradation caused by anthropogenic environmental changes. Sponges, such as the cyanobacteriosponge Terpios hoshinota, are becoming increasingly abundant in these ecosystems. This study examines the likelihood that T. hoshinota is invasive, identifies the types of corals that are overgrown, and investigates patterns and possible drivers of T. hoshinota outbreaks on Maldivian reefs over the past 23 years. From 1990 to 2012 reefs throughout the Maldives were surveyed using transects, photoquadrats and visual surveys. The types of corals overgrown and possible correlations between sponge prevalence and environmental variables were noted. T. hoshinota was first observed in South Malé Atoll in 1990 and has since been found in many Maldivian atolls, predominantly overgrowing massive and encrusting corals. Both large and small blooms of the sponge have been transient, possibly periodic, and increased in magnitude after 1998. Both corals and T. hoshinota exhibit boom-bust population ecologies. For corals vulnerable to bleaching, these cycles are relatively predictable and largely driven by environmental factors like sea surface temperature (SST) (Morais et al. 2021). In contrast, the ecology of T. hoshinota is poorly understood and apparently shaped by stochastic environmental factors. Interactions between the sponge and corals seem to be influenced by the effects of environmental changes on the competitive balance between the two. If current trends continue, the survival of both organisms may be at risk as the degradation of reef structures accelerates.
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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 | 0.001 | 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".