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Record W2042926930 · doi:10.1139/z03-167

Influence of prey abundance on northern spotted owl reproductive success in western Oregon

2003· article· en· W2042926930 on OpenAlexvenueno aff
Daniel K. Rosenberg, Keith A. Swindle, Robert G. Anthony

Bibliographic record

VenueCanadian Journal of Zoology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyPredationAbundance (ecology)PeromyscusEcologyReproductive successSeasonal breederBiomass (ecology)ZoologyPopulationDemography

Abstract

fetched live from OpenAlex

The hypothesis that high temporal variability of northern spotted owl (Strix occidentalis caurina) reproductive success is a response to prey abundance remains largely untested. We evaluated this relationship in the Oregon Cascade Mountains. Despite similar biomass of northern flying squirrels (Glaucomys sabrinus) (169 ± 13.9 g/ha) and deer mice (Peromyscus maniculatus) (160 ± 18.8 g/ha), flying squirrels dominated the breeding season diet based on both biomass (49%) and numbers (40%). Abundance of flying squirrels and western red-backed voles (Clethrionomys californicus) was more variable spatially ([Formula: see text]38% of process variation) than temporally (15%–24%), whereas abundance of deer mice was more similar across stands (12% spatial variation) than among years (68% temporal variation). Spotted owl reproductive success was statistically associated only with the abundance of deer mice (number of young per territory: r 2 = 0.68). However, deer mice comprised only 1.6 ± 0.5% of the biomass consumed. The low temporal variability of the dominant prey species provided evidence that simple prey relationship models were not likely to explain the highly synchronous and temporally dynamic patterns of spotted owl reproductive performance. Reproductive success was likely a result of the interaction of both weather and prey and the life history strategy of this long-lived owl.

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 score0.549
Threshold uncertainty score0.768

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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

Citations40
Published2003
Admission routes1
Has abstractyes

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