Efficiency and fitness consequences of two trapping methods for recapturing ground‐nesting songbirds
Bibliographic record
Abstract
Capturing nesting songbirds is a core component of many field studies. However, avoidance of traps and mist-nets by birds can reduce capture efficiency and bias study results, particularly when individuals need to be recaptured multiple times. We describe a novel capture method—the noose-line—for an alpine population of Horned Larks (Eremophila alpestris) studied during three breeding seasons (2015–2017) in northern British Columbia, Canada. Our objective was to develop a safe, efficient method to recapture individuals that exhibited trap avoidance. We compared the capture efficiency (trap success relative to capture effort) and fitness consequences (nest survival and nest attentiveness) of the noose-line (non-selective method) to those of a more traditional bownet trap (selective method) for both naïve (not previously captured) and previously captured Horned Larks. Mean trapping success for the noose-line was high for both naïve (89.7%) and previously captured (62.9%) birds, whereas mean trapping success for the more visible bownet was strongly influenced by bird experience (naïve = 41.4%, previously captured = 12.1%). However, mean capture effort (time required for successful capture) was greater for noose-lines than the bownet (45.3 min vs. 17.5 min) and noose-lines were more likely to capture non-targeted individuals. The trap type used to capture birds did not influence nest survival. Overall, our results suggest that noose-lines can be an effective option for capturing ground-nesting songbirds, particularly for studies where birds must be recaptured, e.g., to retrieve tracking devices or repeatedly measure body condition. La captura de pájaros cantores anidando es un componente central de muchos estudios de campo. Sin embargo, la evitación de trampas y de redes de niebla por parte de las aves puede reducir la eficiencia de la captura e introducir un sesgo en los resultados del estudio, particularmente cuando los individuos necesitan ser recapturados varias veces. Describimos un nuevo método de captura, la línea de la soga, para una población alpina de alondras cornudas (Eremophila alpestris) estudiada durante tres temporadas de reproducción (2015–2017) en el norte de Columbia Británica, Canadá. Nuestro objetivo fue desarrollar un método seguro y eficiente para recapturar a las aves que demostraron capacidad a evitar la trampa. Comparamos la eficiencia de captura (éxito de la trampa en relación con el esfuerzo de captura) y las consecuencias de la condición física (supervivencia del nido y atención del nido) de la línea de la soga (método no selectivo) con las de una trampa combada con red de malla más tradicional (método selectivo) para ambas alondras cornudas ingenuas (no capturado previamente) y capturadas previamente. El éxito medio de captura para la línea de la soga fue alto tanto para las aves ingenuas (89.7%) como para las capturadas previamente (62.9%), mientras que el éxito promedio de captura para la trampa combada más visible estuvo fuertemente influenciado por la experiencia de las aves (ingenuo = 41.4%, capturado previamente = 12.1%). Sin embargo, el esfuerzo de captura promedio (tiempo requerido para la captura exitosa) fue mayor para las líneas de soga que para la trampa combada (45.3 min vs. 17.5 min) y las líneas de soga fueron más propensas a capturar individuos no objetivo. El tipo de trampa utilizado para capturar aves no influyó la supervivencia del nido. En general, nuestros resultados sugieren que las líneas de soga pueden ser una opción efectiva para capturar aves cantoras que anidan en el suelo, particularmente para estudios en los que las aves deben ser recapturadas, por ejemplo, para recuperar dispositivos de rastreo o medir repetidamente la condición corporal. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".