Factors influencing home range size and overlap in nonbreeding Kirtland’s Warblers on Eleuthera, The Bahamas
Bibliographic record
Abstract
Knowledge of space use provides insight into a species’ habitat requirements needed for conservation. Little is known about space use of the near threatened Kirtland’s Warbler (Setophaga kirtlandii) wintering in The Bahamas, and how the warbler’s home range size and core area overlap among individuals and vary with sex and age, food availability, winter season, and habitat characteristics. To address these knowledge gaps, we used radio telemetry to determine sedentary home range size (95% adaptive kernel), core area (50% AK), and overlap for 27 radio-tagged warblers during two winters on Eleuthera, The Bahamas. Warblers monitored for ~3 weeks each had a median sedentary home range of 8.87 ha (range: 0.53–118.50 ha) and a median core area of 1.04 ha (range: 0.05–12.69 ha). Foliage of the warbler’s principal fruit species (Lantana involucrata, Erithalis fruticosa, Chiococca alba) was present in more warbler core area plots than in outlier plots (telemetry fix points outside the 95% AK home range) or in random plots within the landscape. Both size of home range and core areas increased with site disturbance age – consistent with declines in fruit abundance associated with age of vegetation. Warbler core areas displayed little pairwise overlap in two sites, “RS” and “MR,” examined during October–December (RS, x̄ = 1.49%; MR, x̄ = 0.55%) and at a site in January–February (MR, x̄ = 3.32%), indicating areas of exclusive use or territoriality. In contrast, a fruit-rich site (“OH”) in March–April had higher pairwise overlap in core areas (OH, x̄ = 8.56%), which may have resulted in competition for fruit. Our findings re-emphasize the importance of conservation at a landscape scale if spatiotemporal variation in food resources increases or become more concentrated prior to migration with extreme weather due to global climate change.
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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".