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Record W2039438925 · doi:10.1139/x01-057

Early colonization of<i>Populus</i>wood by saproxylic beetles (Coleoptera)

2001· article· en· W2039438925 on OpenAlexfundvenueaboutno aff
H.E. James Hammond, David W. Langor, John R. Spence

Bibliographic record

VenueCanadian Journal of Forest Research · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
FundersDirectorate for Biological SciencesAlberta-Pacific Forest IndustriesAlberta Parks
KeywordsSnagAmbrosia beetleBiologyAbundance (ecology)EcologyLonghorn beetleHabitatSpecies diversityWoody plantCurculionidae

Abstract

fetched live from OpenAlex

The early colonization of newly created coarse woody material (CWM) by beetles was studied in aspen mixedwood forests at two locations in north-central Alberta. Healthy trembling aspen (Populus tremuloides Michx.) trees, in old (&gt;100 years) and mature (40–80 years) stands, were cut to provide three types of CWM: stumps, bolts on the ground (logs), and bolts suspended above the ground to simulate snags. Over 2 years, 1049 Coleoptera, representing 49 taxa, were collected. Faunal structure differed little between the two locations. Species diversity was higher in old than in mature stands, and higher in stumps and logs than in suspended bolts; however, these "snags" tended to have higher abundance when compared with stumps and logs. Overall beetle abundance and the catch of wood-boring beetles was significantly higher in the first year post-treatment, mainly because of the ambrosia beetle (Trypodendron retusum (LeConte)) and one of its predators, Rhizophagus remotus LeConte; however, beetle diversity was higher in the second year, suggesting that early wood-boring species may "precondition" the wood for a number of succeeding species. The high turnover rate of taxa and spatial or temporal variation in faunal structure suggests that effort focused on habitat classification of CWM will facilitate management to conserve saproxylic faunal diversity.

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 score0.297
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.041
GPT teacher head0.257
Teacher spread0.215 · 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

Citations92
Published2001
Admission routes3
Has abstractyes

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