Distribution Patterns of Migrant and Resident Birds in Successional Forests of the Yucatan Peninsula, Mexico1
Bibliographic record
Abstract
Increasing human activity in the Yucatan peninsula has led to declines in older stages of successional forest, threatening regional habitat diversity. To determine potential effects of this habitat loss on the region's avifauna, we examined the relative use of different forest stages by resident and migrant birds during the nonbreeding season. We used the fixed-width transect method to compare the distribution, abundance, and diversity of forest birds in early (five to ten years old), mid (15–25 years), and late (>50 years) successional forests in the state of Campeche, Mexico, in the south–central part of the peninsula. All stages of successional forest had highly similar bird assemblages and did not differ in bird abundance or diversity. Both migrant and resident birds occurred across the successional gradient. The majority of habitat specialists, however, were resident birds restricted to late-successional forest, indicating that early secondary growth may not be suitable for all species. Furthermore, resident birds that typically participate in mixed-species flocks attained their greatest densities in the oldest forest habitat. Rapid recovery of pre-disturbance physiognomic features, in addition to high levels of habitat connectivity in the region, may contribute to similar bird communities across a range of successional stages. The high degree of edge characterizing much of the forest mosaic also may allow birds access to different seral stages. Loss of late-successional forest, however, is likely to adversely affect the subset of resident avifauna that depends on unique features of mature habitat such as snags, large trees, and climatic buffering. Conservation efforts in Campeche should focus on the specialized requirements of the most habitat-restricted species while preserving the current landscape mosaic characteristic of the small-scale shifting cultivation system.
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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 | 0.000 |
| 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 | 0.000 |
| 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".