Taxonomic nestedness based on guilds? Bird assemblages of the Jardines de la Reina National Park, Cuba, as study case
Bibliographic record
Abstract
Nestedness is a widely known structuring model in insular and fragmented biotas that has often been assessed, but most studies to date have used a taxonomic approach. However, the relevance of an approach using functional groups has become increasingly highlighted in community ecology research. In this study, we evaluated the occurrence of nested structure in the Jardines de la Reina National Park bird assemblages as a whole, and its trophic guilds by following three different grouping criteria. We constructed species presence–absence matrices for each guild and estimated the degree of nestedness with the metric based on the overlap and decreasing fill, assessing its significance by means of two null models. Overall bird assemblage was significantly nested (NODF = 76.99; p = 0.01) whereas terrestrial insectivores (NODF = 81.32) and insectivores (NODF = 80.04) were the only trophic guilds (out of 19) that showed significant nestedness (p ≤ 0.01). These results could provide evidence of the structural and functional cohesion of avifauna at the study site, especially among its insect–eating taxa. Taxonomic nestedness based on a guilds approach may help identify suitable conservation strategies for avian communities inhabiting naturally fragmented areas such as the Jardines de la Reina National Park.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".