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Record W2187573315 · doi:10.1139/x11-145

Avian responses to experimental harvest in southern boreal mixedwood shoreline forests: implications for riparian buffer management

2011· article· en· W2187573315 on OpenAlexaffvenue
Kevin J. Kardynal, Jacques Morissette, Steven L. Van Wilgenburg, Erin M. Bayne, Keith A. Hobson

Bibliographic record

VenueCanadian Journal of Forest Research · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsEnvironment and Climate Change CanadaDucks Unlimited CanadaUniversity of AlbertaUniversity of Saskatchewan
Fundersnot available
KeywordsRiparian zoneRiparian bufferHabitatTaigaBorealForest managementEcologyAbundance (ecology)Riparian forestWetlandShrubEnvironmental scienceUnderstoryBuffer stripShoreGeneralist and specialist speciesGeographyBiologyFisheryCanopySurface runoff

Abstract

fetched live from OpenAlex

Conventional management of shoreline forest in harvested boreal landscapes involves retention of treed buffer strips to provide habitat for wildlife species and protect aquatic habitats from deleterious effects of harvesting. With shoreline forests being considered for harvest in several jurisdictions, it is important to determine the potential impacts of this disturbance on birds. In this study, responses of riparian- and upland-nesting birds to three levels of harvest (0%–50%, 50%–75%, and 75%–100% within 100 m of the water) in shoreline forests around boreal wetlands were assessed 1 year before and each year for 4 years after harvest relative to unharvested reference sites. Upland-nesting species showed variable responses to harvest, with greatest declines in abundance of interior forest nesting species (e.g., Ovenbird, Seiurus aurocapillus L.) with the highest levels of harvest. Shrub-nesting and generalist species increased in abundance in harvest treatments relative to reference sites. Riparian birds showed little response to harvest, suggesting that shoreline forest harvest has little effect on their abundance up to 4 years after harvest. Retention of small buffers may not be an effective management strategy for conservation of birds occupying shoreline forests, particularly interior forest nesting species. We suggest that alternatives to conventional buffer management be explored.

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 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 score0.617
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.068
GPT teacher head0.324
Teacher spread0.256 · 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

Citations17
Published2011
Admission routes2
Has abstractyes

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