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Effects of Postfire Snag Removal on Breeding Birds of Western Labrador

2006· article· en· W2201001584 on OpenAlexaffabout
Francis E. Schwab, Neal P. P. Simon, STEVEN W. STRYDE, Graham J. Forbes

Bibliographic record

VenueJournal of Wildlife Management · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of New BrunswickCumulative Environmental Management AssociationGovernment of Newfoundland and LabradorCollege of the North Atlantic
FundersInnovative Research Group Project of the National Natural Science Foundation of China
KeywordsSnagEcologyGeographyZoologyBiologyHabitat

Abstract

fetched live from OpenAlex

The issue of snags in wildlife management has progressed from speculation about their importance (Elton 1966), to statements of wildlife dependence on them (Thomas et al. 1979), to objectives for maintaining snags to conserve biodiversity during timber extraction (e.g., Woodley and Forbes 1997, Lehmkuhl et al. 2003). Snag management usually involves the maintenance of a small proportion of snags or dying trees (e.g., 10 trees or snags .50-cm dbh per ha). More problematic is the management of entire stands of dead trees (snag-forests) resulting from fire or insect epizootics. Demands for wood products require managers to rapidly harvest snag-forests to reclaim lost timber, but large-scale salvage (e.g., 28,000 km in Oreg. and Wash. in the 1980s [Youngblood and Wickman 2002]) likely effects snag-dependent wildlife (DellaSalla et al. 1995, McIver and Starr 2001, Nappi et al. 2004). Fire suppression and insect spray programs have further reduced the extent of snagforests (Trani et al. 2001) while the focus on maintaining old-growth forest has deflected attention from snag-forest conservation (Askins 2001, Hunter et al. 2001). From a wildlife perspective, snag-forests are a combination of early successional vegetation and large dead trees that are short-lived as snags. These ephemeral forests are critical for birds dependent on Coleoptera larvae (Raphael et al. 1987, Hutto 1995, Nappi et al. 2003). Despite the ecological importance of snag-forests, salvage-logging effects are poorly understood (McIver and Starr 2001). The few existing studies are correlative, focusing on snag-nesting species (Saab and Dudley 1998, McIver and Starr 2001). Salvage logging should affect the entire bird community (Hutto 1995, LeCoure et al. 2000, Morrisette et al. 2002) because snags are the dominant structure on early burns. Several studies associate noncavity nesters with snagforests (Hutto 1995, Schwab et al. 2001, Simon et al. 2002), but it is unclear whether they are attracted to the early successional vegetation or to the snags. This makes it impossible to draw firm conclusions about the effects of salvage logging. The few studies on salvage logging (e.g., LeCoure et al. 2000, Morrisette et al. 2002) did not examine different intensities of logging required to provide managers with options. As a result, we conducted a before and after experiment with 3 intensities of snag removal in western Labrador, Canada. Our objective is to provide forest managers with opening-size thresholds for specific bird species to help guide salvage logging in snag-forests.

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 score0.442
Threshold uncertainty score0.607

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)0.0000.000

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 head0.004
GPT teacher head0.200
Teacher spread0.195 · 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

Citations20
Published2006
Admission routes2
Has abstractyes

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