Modelling habitat associations of the common spider conch in the Cocos (Keeling) Islands
Bibliographic record
Abstract
The type and configuration of benthic habitats can influence community structure of marine fauna and the effectiveness of management actions, such as spatial closures.We quantified the relationship between the distribution and density of Lambis lambis, an exploited marine gastropod, and available benthic habitats at the Cocos (Keeling) Islands.We used 3 modelling approaches to develop a model of the density of L. lambis as a function of habitat: conventional polynomial regression, Moran's eigenvector maps (MEM) and variance partitioning.Distribution and abundance of L. lambis was not uniform throughout the lagoon.Both the amount and configuration of habitat influenced L. lambis density; the highest densities were associated with moderate levels of hard macroalgae and submassive corals, and the lowest densities with seagrass and relict coral.These results illustrate that incorporating information on the distribution and patchiness of preferred habitats is essential to ensure that appropriate habitats are included in the design and implementation of long-term monitoring programs and management tools such as spatial closures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".