Nesting habitat requirements of two species of North African woodpeckers in native oak forest
Bibliographic record
Abstract
Capsule Nests of Levaillant's Woodpecker Picus vaillantii and Great Spotted Woodpecker Dendrocopos major were associated with higher densities of snags and downed wood than foraging locations.Aims To quantify the nesting requirements of two sympatric woodpecker species in Tunisian oak forests.Methods We compared habitat structure around nests and foraging locations for both woodpecker species using logistic regression. We examined evidence for preferences in nesting substrates using resource selection indices. Then, we used discriminant function analysis to identify variables separating nesting, foraging, and unused habitat of each species.Results The probability of presence of nests of both species was significantly related to densities of downed wood and snags. Nests of Levaillant's Woodpecker were located in areas with slightly higher snag densities. Habitat structure differed between nesting and foraging locations of Great Spotted, but not Levaillant's WoodpeckerConclusion Both Levaillant's and Great Spotted Woodpecker showed high requirements for large-diameter trees and snags, which provide substrates for both nesting and foraging. Nesting habitat requirements may not always be higher than those associated with foraging, but the fact that they were for the Great Spotted Woodpecker calls for caution when planning for woodpecker conservation.
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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) | 0.001 | 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".