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Record W2161729288 · doi:10.1676/09-105.1

Short-Term Effects of Fire on Breeding Birds in Southern Appalachian Upland Forests

2010· article· en· W2161729288 on OpenAlexaff
Nathan A. Klaus, Scott A. Rush, Tim S. Keyes, John Petrick, Robert J. Cooper

Bibliographic record

VenueThe Wilson Journal of Ornithology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsSpecies richnessSpecies evennessEcologyHabitatAbundance (ecology)Disturbance (geology)GeographyPrescribed burnSpecies diversityEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

We investigated how variation in fire severity (control or no fire; low, medium, and high severity fires) and interval (1–2 years vs. 3–6 years after fires) affected habitat and avian abundance, species diversity, richness, and evenness in the southern Appalachian Mountains. Fire severity and interval had significant implications for both habitat and avian communities. Species richness within 2 years of fires was on average 26% higher in areas receiving medium and high severity treatments than in unburned control units. Species diversity and species richness were markedly greater 3–6 years after fires within high severity treatments (12 and 44%, respectively), compared to unburned controls. Relative abundance and species evenness did not vary with fire severity or time since fire. The short-term effects of low severity fires, or high severity fires with short rotation periods (≤2 years) may have limited positive effects on avian communities. Facilitation of disturbance regimes including mid to high severity fires, which foster uneven-aged forests, can be an effective conservation tool for restoring avian 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 score0.116
Threshold uncertainty score0.380

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 integrity0.0000.001
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 head0.006
GPT teacher head0.225
Teacher spread0.218 · 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

Citations22
Published2010
Admission routes1
Has abstractyes

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