Population dynamics of the ruddy-capped nightingale thrush (<i>Catharus frantzii</i>) in Chiapas, Mexico: influences of density, productivity and survival
Bibliographic record
Abstract
Abstract: We used long-term population data for the ruddy-capped nightingale thrush (Catharus frantzii Cabanis), to examine the influence of forest conditions on annual productivity, survival and growth rate (λ) in a montane forest reserve of Chiapas, southern Mexico, from 1995 to 2003. Productivity was higher in primary, mature forest than in secondary, young forest. More adults were captured in primary forest (n = 132) than in secondary forest (n = 64). Adult survival (φ = 0.79) and encounter rate (ρ = 0.36) did not vary across habitats. Males and females had similar survival between primary and secondary forests (φ = 0.80 vs. 0.83, and 0.77 vs. 0.79, respectively). Juvenile survival (φ = 0.67) was only 12% lower than for adults. Overall, the population of C. frantzii appeared to be declining at 3% y−1 (λ = 0.97, SE = 0.09, 95% CI = 0.88–1.03). Productivity and survival correlated positively with λ across years within habitats, although survival was the primary, significant demographic parameter determining λ. Although habitat alteration may have reduced the carrying capacity and productivity in secondary forest, there was no apparent negative effect on population persistence in this habitat. Thus, secondary forests represent habitats that may facilitate the long-term persistence of C. frantzii populations.
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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 | 0.000 | 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".