Nonideal habitat selection by a North American cavity excavator: pecking up the wrong tree?
Bibliographic record
Abstract
Nonideal habitat selection occurs when preferred habitat attributes differ from those associated with increased fitness. These mismatches have been widely studied in open cup-nesting birds, but the relationship between habitat-associated preferences and fitness in cavity-nesting birds has received relatively little attention. We studied patterns of preference and fitness during 2006–2007 in an Idaho, USA, population of Red-naped Sapsuckers ( Sphyrapicus nuchalis S.F. Baird, 1858). Using a suite of nonparametric tests, we examined the associations between habitat attributes and both nesting-area preferences and nest productivity (number of fledglings per pair) across four spatial scales. Nest productivity was associated with tree- and cavity-scale attributes, whereas preference was associated with attributes of home ranges. Live trees and southeasterly oriented cavities had higher nest productivity but were not preferred. Microclimates in nests with these attributes may enhance nestling survival, whereas nonpreference for these attributes may be due to energetic constraints in some individuals. Additional studies comparing patterns of nonideal habitat selection between open-cup nesters and cavity nesters should advance our understanding of how life-history characteristics influence selection patterns.
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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 | 0.001 |
| 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".