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Record W2038111606 · doi:10.1139/x07-022

Effect of gap harvesting on epiphytes and bark-dwelling arthropods in the Acadian forest of central Maine

2007· article· en· W2038111606 on OpenAlexvenueno aff
Kathryn M. Miller, Robert G. Wagner, Stephen A. Woods

Bibliographic record

VenueCanadian Journal of Forest Research · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsnot available
Fundersnot available
KeywordsEpiphyteLichenBiologyArthropodEcologyBotanyBark (sound)BryophyteAbundance (ecology)Trophic levelMaple

Abstract

fetched live from OpenAlex

Using a long-term silvicultural experiment, we (i) investigated how epiphyte and arthropod communities were affected by height on the stem, bark texture, and stem diameter of red maple ( Acer rubrum L.) trees, (ii) examined how harvest gaps influenced epiphyte and arthropod communities on red maple boles, and (iii) explored whether these effects influenced the relationship between the epiphyte and arthropod communities. Arthropod and epiphyte assemblages dwelling on the bark of red maple trees located in undisturbed forest and harvest gaps varied with height. Bryophytes, Cladonia spp., and cyanolichens were most abundant near the base of the tree, while noncyano, foliose lichens and fruticose lichens were most abundant 4–6 m above the ground. Acari, Araneae, and Collembola were most abundant near the base of the tree, while Diptera were most abundant above 2 m. A previously undocumented assemblage of dipterans (flies), primarily in the suborder Nematocera, was found. Gap harvesting reduced the abundance of bryophytes, Collembola (springtails), Araneae (spiders), and total arthropods on the bark of red maple. Canonical correlation analysis revealed a positive association between bryophytes, Collembola, and Araneae. A strong correlation between Collembola and Araneae suggested a possible trophic interaction that may be affected by gap harvesting through a reduction in bryophyte abundance.

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)0.005
metaresearch head score (Gemma)0.001
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 score0.574
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
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 head0.047
GPT teacher head0.312
Teacher spread0.265 · 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

Citations15
Published2007
Admission routes1
Has abstractyes

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