Underlying factors promoting nestedness of bird assemblages in cays of the Jardines de la Reina archipelago, Cuba
Bibliographic record
Abstract
Underlying factors promoting nestedness of bird assemblages in cays of the Jardines de la Reina archipelago, Cuba.-Assessing the factors associated with nestedness patterns is a crucial aspect in studies of community structure.Bird assemblages in the Jardines de la Reina archipelago have a stable nested structure but the underlying influences have not been evaluated.We constructed a presence-absence data matrix based on a bird inventory obtained from 43 cays of this archipelago.We calculated nestedness using the NODF metric based on the overlap and decreasing fill and evaluated its significance by running 1,000 iterations of four null models.The matrix columns were rearranged to evaluate seven factors possibly related to the nestedness of bird communities.Bird assemblages exhibited a significant nested pattern (67.93) and all factors contributed (p < 0.01) to the nestedness patterns of bird communities.Habitat diversity and cay area and perimeter were the factors that contributed most to the nested structure.The nestedness pattern in the bird assemblages of the Jardines de la Reina archipelago was potentially caused by the interaction of selective extinction and differential colonization of species, with the former having a more remarkable effect.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".