Nidicolous beetle species richness is driven by Barn Owl’s nests occupancy and landscape structure
Bibliographic record
Abstract
Abstract Bird nests are specialized habitats because of their particular composition including nest detritus and bird droppings. In consequence, they attract a specialized arthropod community considered as nidicolous, which includes species only found in bird nests (strictly nidicolous) or sometimes found in bird nests (facultatively nidicolous). Because the factors influencing the entomofauna in bird nests are poorly understood, in autumn 2019, we collected nest material in 86 Barn Owl (Tyto alba) nest boxes. We investigated whether the invertebrate species richness was related to Barn Owl nest box occupancy, the density of available nest boxes and the landscape structure. We found 3,321 nidicolous beetle specimens belonging to 24 species. Species richness of strictly nidicolous beetles was 2.7 times higher in nest boxes occupied by a family of Barn Owls the previous spring compared to unoccupied nest boxes. It was also higher in sites that were more often occupied by Barn Owls in the five previous years and in areas surrounded by a higher proportion of crop fields. For facultatively nidicolous beetles, the density of Barn Owl nest boxes enhanced the species richness. In conclusion, our study suggests that the strictly nidicolous beetles benefit from occupied nest boxes of Barn Owls, whereas facultatively nidicolous beetles look for nest boxes independently of whether Barn Owls occupy them. Our study highlights the importance of bird nests for a suite of invertebrates.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".