MOLT PATTERNS AND SEXING AND AGING CRITERIA FOR TEN SPECIES OF HIGH ELEVATION LANDBIRDS FROM SOUTHEASTERN PERU
Bibliographic record
Abstract
Abstract ∙ Knowledge of molt patterns and their resulting plumages is useful for aging and sexing birds and, in mono‐ chromatic species, morphometric measurements can help to discern males from females. However, these data are largely undescribed for the majority of the world’s bird species, especially in the tropics. We sought to classify the molt strategy for 10 species of Neotropical passerines during their breeding seasons and considered whether a combination of wing chord, tail length and mass could be used to determine their sex. We used banding data from three years of mark‐recapture study at Wayqecha Biological Station (2900 m a.s.l.) along the east slope of the Andes in southeastern Peru to characterize molt and estimate morphological measurements. Each of the species exhibited a complete definitive prebasic molt and either a partial (nine species) or partial‐incomplete (one species) preformative molt, which we interpreted to be consistent with a complex basic molt strategy. For five of the 10 species, we found that wing, tail, and body mass measurements were useful in distinguishing between males and females. This study contributes to our understanding of tropical bird molt by providing previously undescribed aging and sexing criteria for some tropical landbirds common to high elevations of southern Peru.Resumen ∙ Patrones de muda y criterios para categorizar sexo y edad en diez especies de aves altoandinas en el sureste de Perú Los patrones de muda en la mayoría de las aves Neotropicales son poco conocidos y en especial se desconoce si las medidas corporales pueden ser usadas para determinar el sexo en especies sin dimorfismo sexual. En este trabajo clasificamos la estrategia de muda para 10 especies de paserinos Neotropicales y también exploramos si una combi‐ nación de medidas de longitud del ala, longitud de la cola y masa corporal pueden ser usadas para la determinación del sexo. Usamos datos de anillamiento de tres años de un estudio de recaptura en la Estación Biológica Wayqecha (2900 m s.n.m.) en el flanco oriental de los Andes al sureste de Perú. Cada especie exhibió una estrategia básica compleja de muda con una muda prebásica definitiva compleja, y una muda preformativa parcial (nueve especies) o parcial‐incompleta (uno especie). Para cinco de cada 10 especies, la combinación de medidas de la longitud del ala, la cola, y la masa corporal sirvieron para distinguir entre machos y hembras. Este estudio contribuye a la creciente literatura sobre los patrones de muda en aves tropicales y provee herramientas para clasificar la edad y el sexo de aves con plumaje sexualmente monocromático.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".