Habitat degradation and fishing effects on the size structure of coral reef fish communities
Bibliographic record
Abstract
Overfishing and habitat degradation through climate change pose the greatest threats to sustainability of marine resources on coral reefs. We examined how changes in fishing pressure and benthic habitat composition influenced the size spectra of island-scale reef fish communities in Lau, Fiji. Between 2000 and 2006 fishing pressure declined in the Lau Islands due to declining human populations and reduced demand for fresh fish. At the same time, coral cover declined and fine-scale architectural complexity eroded due to coral bleaching and outbreaks of crown-of-thorns starfish, Acanthaster planci. We examined the size distribution of reef fish communities using size spectra analysis, the linearized relationship between abundance and body size class. Spatial variation in fishing pressure accounted for 31% of the variation in the slope of the size spectra in 2000, higher fishing pressure being associated with a steeper slope, which is indicative of fewer large-bodied fish and/or more small-bodied fish. Conversely, in 2006 spatial variation in habitat explained 53% of the variation in the size spectra slopes, and the relationship with fishing pressure was much weaker (approximately 12% of variation) than in 2000. Reduced cover of corals and lower structural complexity was associated with less steep size spectra slopes, primarily due to reduced abundance of fish < 20 cm. Habitat degradation will compound effects of fishing on coral reefs as increased fishing reduces large-bodied target species, while habitat loss results in fewer small-bodied juveniles and prey that replenish stocks and provide dietary resources for predatory target species. Effective management of reef resources therefore depends on both reducing fishing pressure and maintaining processes that encourage rapid recovery of coral habitat.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".