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Wood‐feeding beetles and soil nutrient cycling in burned forests: implications of post‐fire salvage logging

2009· article· en· W2117491409 on OpenAlexafffund
Tyler Cobb, Kirsten Hannam, Barbara E. Kishchuk, David W. Langor, Sylvie A. Quideau, John R. Spence

Bibliographic record

VenueAgricultural and Forest Entomology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsNatural Resources CanadaCanadian Forest ServiceUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Conservation Association
KeywordsSalvage loggingEcologyBiologyLoggingNutrient cycleEcosystemTaigaCoarse woody debrisBiodiversityForest ecologyAgroforestryHabitat

Abstract

fetched live from OpenAlex

Rising economic demands for boreal forest resources along with current and predicted increases in wildfire activity have increased salvage logging of burned forests. Currently, the ecological consequences of post‐fire salvage logging are insufficiently understood to develop effective management guidelines or to adequately inform policy decision‐makers. We used both field and laboratory studies to examine the effects of post‐fire salvage logging on populations of the white‐spotted sawyer Monochamus scutellatus scutellatus (Say) (Coleoptera: Cerambycidae) and its ecological function in boreal forest. Monochamus s. scutellatus adults were relatively abundant in both burned and clear‐cut logged sites but were absent from salvage logged sites. An in situ mesocosm experiment showed that the abundance of M. s. scutellatus larvae in burned white spruce bolts was linked to changes in total organic nitrogen and carbon in mineral soil. Organic nutrient inputs in the form of M. s. scutellatus frass increased mineral soil microbial respiration rates by more than three‐fold and altered the availability of nitrogen. Changes in nitrogen availability corresponded with decreased germination and growth of Epilobium angustifolium and Populus spp. but not Calamagrostis canadensis . Although the present study focused on local scale effects, the reported findings suggest that continued economic emphasis on post‐fire salvage logging may have implications beyond the local scale for biodiversity conservation, nutrient cycling and plant community composition in forest ecosystems recovering from wildfire.

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 score0.220
Threshold uncertainty score0.379

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 studies0.0000.000
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 head0.006
GPT teacher head0.211
Teacher spread0.205 · 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

Citations47
Published2009
Admission routes2
Has abstractyes

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