MétaCan
Menu
Back to cohort

DO OVENBIRDS (SEIURUS AUROCAPILLUS) AVOID BOREAL FOREST EDGES? A SPATIOTEMPORAL ANALYSIS IN AN AGRICULTURAL LANDSCAPE

2003· article· en· W2173611801 on OpenAlexafffund
Daniel F. Mazerolle, Keith A. Hobson

Bibliographic record

VenueThe Auk · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsGeographyTaigaBorealAgricultureEcologyAgroforestryForestryEnvironmental scienceBiologyArchaeology

Abstract

fetched live from OpenAlex

Abstract Previous studies suggest that Ovenbirds (Seiurus aurocapillus) are area sensitive and apparently avoid forest edges. In 1999 and 2000, we used radiotelemetry to investigate how breeding male Ovenbirds respond to forest edges. Twenty-one males with home ranges abutting edges of seven forest fragments surrounded by agriculture were tracked for an average of two weeks. We found that sightings of males were situated 8 ± 10 m closer to edges than random locations within each home range. However, the mean time of day for edge sightings (1139 hours, 95% CI = 1052–1227 hours) occurred significantly later than the mean for sightings in the interior of forest fragments (0936 hours, 95% CI = 0856–1016 hours). That indicates that previous studies focusing on morning singing locations to delineate home-range use have likely underestimated use of edges by birds. Habitat characteristics also varied in relation to edges. Forest canopy was lower, shrubs were denser, leaf-litter thicker, and soils dryer near edges than in the portion of home ranges facing the interior of forest fragments. Arthropod biomass varied little in relation to edges, except biomass of larvae, which was greatest at edges. Boreal forest edges abutting agricultural fields do not appear to reduce habitat use or quality for breeding male Ovenbirds, and so we suggest that the generalized association between area sensitivity and edge avoidance for Ovenbirds in forest fragments be reassessed.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.237
Teacher spread0.224 · 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.

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

Citations23
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueThe AukSame topicAvian ecology and behaviorFrench-language works237,207