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Effect of camera monitoring on survival rates of High-Arctic shorebird nests

2009· article· en· W2066775401 on OpenAlexaffabout
Laura McKinnon, Joël Bêty

Bibliographic record

VenueJournal of Field Ornithology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsArcticGeographyThe arcticZoologyEcologyBiologyFisheryOceanography

Abstract

fetched live from OpenAlex

Monitoring bird nests with cameras provides an opportunity to identify the cause of nest failure and record the behavior of individuals. However, leaving an object continuously within sight of a nest could have potential negative effects on nesting success. We compared daily survival rates of nests monitored using cameras and human visitation to nests tracked via human visitation only to test for potential additional effects of camera monitoring on predation rates. From 2006 to 2008, experiments were conducted on Bylot Island (Nunavut) using 80 artificial nests and 53 real nests of Baird's Sandpipers (Calidris bairdii) and White-rumped Sandpipers (Calidris fuscicollis). Rates of predation on real and artificial nests varied considerably among years. However, survival rates of camera-monitored nests did not differ from those of nests monitored without cameras. Predators of artificial nests included Arctic foxes (Vulpes lagopus), Glaucous Gulls (Larus hyperboreus), and Long-tailed Jaegers (Stercorarius longicaudus), whereas Arctic foxes were responsible for all camera-recorded predation events at real nests. Camera monitoring should be promoted as a viable method for monitoring nests of Arctic shorebirds because our results indicate that placing cameras at nests does not bias estimates of nest survival obtained via nest visits. SINOPSIS El monitoreo con camaras de los nidos de las aves provee una oportunidad para identificar la causa del fallo de los nidos y para documentar el comportamiento de los individuos. Sin embargo, dejar un objeto continuamente a la vista del nido podria tener efectos negativos sobre el exito de la nidificacion. Comparamos las tasas de supervivencia diaria de nidos monitoreados usando camaras y visitacion de personas a la de los nidos que fueron monitoreados solo mediante la visitacion de personas para determinar si existieron efectos adicionales del monitoreo con camaras a las tasas de depredacion. Desde 2006 – 2008, realizamos experimentos en la Isla de Bylot (Nunavut) usando 80 nidos artificiales y 53 nidos naturales de Calidris bairdii y de C. fuscicollis. Las tasas de depredacion de nidos naturales y artificiales variaron considerablemente entre anos. Sin embargo, las tasas de supervivencia de nidos monitoreados con camaras no tuvieron diferencias con los que fueron monitoreados sin camaras. Los depredadores de nidos artificiales incluyeron zoros (Vulpes lagopus) y aves (Larus hyperboreus y Stercorarius longicaudus). Los zoros fueron responsables para todos los eventos de depredacion de los nidos naturales grabados con las camaras. El monitoreo con camaras deberia ser promovido como un metodo viable para el monitoreo de nidos de playeros en el arctico porque nuestros resultados indican que el uso de las camaras no afecta a las estimaciones de la supervivencia de los nidos obtenidas mediante visitas a los nidos.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.296
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations88
Published2009
Admission routes2
Has abstractyes

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