Tree cavity density is a limiting factor for a secondary cavity nester in second-growth Andean temperate rainforests
Bibliographic record
Abstract
Abstract Cavity-nesting bird populations are most frequently limited by the number of tree cavities available in second-growth forests. However, this possible limitation of a key resource is less clear in old-growth forests. We compared forest attributes (i.e., basal area, density of larger trees, density of dead trees, and tree cavity density) in second-growth and old-growth stands in Andean temperate rainforests in southern Chile. To examine the role of nest-site availability in limiting the populations of Aphrastura spinicauda (Thorn-Tailed Rayadito), we monitored their populations in both forest types during a 5-year period (2008-2013), while we conducted an experiment in which nest boxes were added and then, after two years, removed by blocking cavity entrances. In old-growth forests, as compared to second-growth forests, we found a more than double basal area (99.6 vs. 43.7 m2 ha−1), a 3 times higher density of larger trees (88.2 vs. 36.4 trees ha−1), and a 1.5 times higher number of small cavities (25.9 vs. 10.3 cavities ha−1). The density of cavities also strongly increased with tree diameter and basal area. In second-growth forests, A. spinicauda showed a strong response to the addition, and later to the removal of nest boxes, with population abundance increasing by 13% and then decreasing by 50%, respectively. In contrast, we found no impact on old-growth stands. Our experiment emphasizes the importance of maintaining large and dead trees in second-growth, disturbed, and managed forests. These trees provide suitable cavities for A. spinicauda, and likely many other secondary cavity nesters, increasing their abundance in a Globally significant Biodiversity Hotspot in southern South America. A Spanish translation of this manuscript is available as Supplementary Material.
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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 | 0.001 | 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".