Other effective area-based conservation measure promotes recovery in a cold-water coral reef
Bibliographic record
Abstract
In 2003, a large Lophelia pertusa reef complex was discovered on the southeast edge of the Scotian Shelf, representing the only known cold-water coral reef in Canada. Extensive damage to the reef from bottom fishing activities was apparent, which resulted in the establishment of the 15-km2 Lophelia Coral Conservation Area (LCCA) in 2004 to prevent further damage and allow recovery. Since 2004, the effectiveness of the LCCA in achieving these objectives has never been assessed. Through the analysis of benthic images collected in 2003, 2009, and 2015, we evaluated the effectiveness of the LCCA in terms of its success in facilitating the recolonization and recovery of its target species, L. pertusa, and in conserving local benthic biodiversity. Using multivariate community analyses and generalized linear modelling techniques, we compared changes in the diversity, abundance, and composition of epibenthic megafauna within and outside its boundaries over the 12-year period. We observed an increase in epibenthic megafaunal species density and abundance over time that was higher inside the closure than outside, suggesting that the LCCA has facilitated the recruitment and recovery of the benthic communities within its confines. While recruitment of L. pertusa was low, the recent discovery of numerous undisturbed large mounds of live L. pertusa establishes a local recruitment source, a prerequisite for the reef structure to recover to its pre-disturbed state. We recommend that monitoring of the reef structure occur every 7–10 years to evaluate the settlement and growth of L. pertusa and the other deep-water corals that reside there.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".