EFFECTS OF HABITAT DISTURBANCE ON REPRODUCTION IN BLACK-CAPPED CHICKADEES (POECILE ATRICAPILLUS) IN NORTHERN BRITISH COLUMBIA
Bibliographic record
Abstract
Avian species that persist in breeding in disturbed habitats are often thought to be less affected by disturbance than habitat specialists lost following disturbances, yet there is growing evidence that human-altered environments may negatively affect reproductive behavior and nest success of those generalists as well. We compared nest success of Blackcapped Chickadees (Poecile atricapillus) in two adjacent habitats: a mature mixed-wood forest (undisturbed) and a forest regenerating after logging (disturbed). Despite similar breeding densities, proportion of nests that successfully fledged young was lower in the disturbed habitat than in the undisturbed habitat. Abandonment was the most common cause of nest failure. A within-habitat comparison of the social rank of birds revealed that low-ranking birds had lower nest success than high-ranking birds in the disturbed, but not in the undisturbed, habitat. Clutch size and brood size of nests that progressed to the point of hatch did not differ significantly between habitats. Average total number of fledglings produced per pair, though not significantly different, was suggestively lower in the disturbed habitat. Across habitats, nests situated in snags with lower amounts of internal decay were more successful. Successful nests were also located in sites with higher canopy height, low understory density below 1 m, and higher understory density between 2 and 3 m—all attributes generally associated with undisturbed, mature forests in the region. Our results provide evidence that disturbed habitats may represent poor-quality habitat for this forest generalist, and that habitat quality differentially affects individuals, depending on their dominance rank.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".