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HABITAT USE AND PRODUCTIVITY OF SHARP-SHINNED HAWKS NESTING IN AN URBAN AREA

2002· article· en· W2023130220 on OpenAlexafffundabout
Joanna L. Coleman, David M. Bird, Eugene A. Jacobs

Bibliographic record

VenueThe Wilson Bulletin · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsMcGill University
FundersMcGill University
KeywordsNest (protein structural motif)HabitatDeciduousEcologyAvian clutch sizeProductivityAccipiterGeographyPopulationAccipitridaeAbundance (ecology)CanopyHome rangeArboreal locomotionPopulation densityVegetation (pathology)BiologyReproductionPredationDemography

Abstract

fetched live from OpenAlex

We measured productivity and vegetation parameters of habitat quality at 16 Sharp-shinned Hawk (Accipiter striatus) nests in and near the greater Montreal area in order to evaluate nesting habitat use and its possible relationship to reproductive success in an urban setting. Mean clutch size was 4.4 and hatching success was 3.8 eggs per nest. At least one egg hatched in 11 of 16 nests (68.8%), 10 (62.5%) pairs raised young to a bandable age (≥10 days old), and 8 (50%) pairs successfully produced at least one fledgling. Immature individuals comprised 33.3% of male and 38.5% of female breeders. Mean values in the habitat assessment included nest tree height, 14.0 m; tree density, 955/ha; total canopy cover, 88.1%; coniferous cover, 39.7%; mean dbh, 17.6 cm; and distance to the nearest forest opening, 19.7 m. Sharp-shinned Hawks nested in a range of forest types, from mature conifer plantations to young, almost purely deciduous stands, and this population exhibited considerable flexibility with respect to most of the habitat features that we measured. Their use of older stands with more deciduous cover than those used by conspecifics elsewhere may reflect regional differences in habitat availability as well as in the abundance of competitor species. Breeding in an urbanized area does not seem to be detrimental to Sharp-shinned Hawks, as evidenced by this population’s relatively large proportion of immature breeders and normal productivity, which appeared to be independent of all the assessed parameters of habitat quality.

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 score0.006
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.215
Teacher spread0.179 · 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

Citations15
Published2002
Admission routes3
Has abstractyes

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