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Record W2025904152 · doi:10.1890/11-1594.1

Survival analysis of a critical resource for cavity‐nesting communities: patterns of tree cavity longevity

2012· article· en· W2025904152 on OpenAlexafffundabout
Amanda B. Edworthy, Karen L. Wiebe, Kathy Martin

Bibliographic record

VenueEcological Applications · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMediterranean and Iberian flora and fauna
Canadian institutionsEnvironment and Climate Change CanadaUniversity of SaskatchewanUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLongevityNesting (process)EcologyResource (disambiguation)Tree (set theory)GeographyBiologyComputer scienceEngineeringMathematics

Abstract

fetched live from OpenAlex

Tree cavities are a vital multi-annual resource used by cavity-nesting birds and mammals for nesting and shelter. The abundance of this resource will be influenced by the rates at which cavities are created and destroyed. We applied the demographic concepts of survival and longevity to populations of tree holes to investigate rates of loss for cavities in three tree species, as well as how characteristics of nest trees, habitat type, and species of excavator affected the persistence of tree cavities in trembling aspen, Populus tremuloides (95% of cavities were in aspen trees), in interior British Columbia, Canada. By modeling survival of 1635 nesting cavities in aspen over a time span of 16 years, we found that the decay stage of the nest tree was the most important factor determining cavity longevity. Cavities in trees with advanced decay had a relatively short median longevity of 7 years (95% CI 6-9 years), whereas those in living trees had a median longevity of more than 15 years. We found that cavity longevity was greater in continuous forest than in aspen grove habitat. Interestingly, cavities formed by weak excavators survived as long as those created by Northern Flickers (Colaptes auratus), despite occurring in more decayed tree stems. Thus, weak excavators may be selecting for characteristics that make a tree persistent, such as a broken top. Our results indicate that retention of cavities in large, live aspen trees is necessary to conserve persistent cavities, and that cavity longevity will have a large effect on the structure and function of cavity-using vertebrate communities.

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)0.001
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 score0.133
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.073
GPT teacher head0.297
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.

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

Citations85
Published2012
Admission routes3
Has abstractyes

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