Season and seagrass: drivers of fish assemblage structure in the Banc d'Arguin, Mauritania
Bibliographic record
Abstract
The Banc d’Arguin is the most ecologically significant coastal wetland of West Africa, a UNESCO Marine World Heritage area with one of the most extensive seagrass areas on Earth, used by many marine species as breeding and/or feeding habitat. However, little is known about the subtidal biodiversity supported by these extensive seagrass meadows. This study aimed to assess the influence of subtidal seagrass vegetation on fish assemblages, using beach seines to compare vegetated and unvegetated habitat. Effects of season and site were also assessed. We sampled fish communities predominantly composed of juveniles (98.7%). Specifically, we analyzed differences in abundance, species richness, diversity, evenness, and assemblage structure across these factors. Season was the most influential driver of fish assemblage structure, even more than habitat, as expected in a nursery area where fish reproduce seasonally. Notably, four species - Atherina boyeri , Eucinostomus melanopterus , Mugil capurrii , and Chelon dumerili - accounted for 53.7% and 49.2% of the variation in assemblages across habitat and season, respectively. Moreover, four times as many species were found exclusively in seagrass habitats compared to unvegetated areas, underscoring the critical role of seagrass meadows in the Banc d'Arguin in supporting species that depend on such shallow sheltered habitats, enhancing regional biodiversity, and contributing to the sustainability of fisheries.
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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 | 0.001 | 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".