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Record W205112333

Influence of Coarse Woody Material (CWM) on Soil Microarthropods in Black Spruce-Feather Moss Forests of Western Quebec

2009· article· en· W205112333 on OpenAlexaboutno aff
Enrique Doblas‐Miranda, Timothy T. Work

Bibliographic record

VenueDigital Commons - USU (Utah State University) · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMossBlack spruceFeatherEcologyBotanyForestryBiologyEnvironmental scienceGeographyTaiga
DOInot available

Abstract

fetched live from OpenAlex

Increasing demands for biofuels have opened the possibility for an overall decrease in the amount of residual coarse woody material (CWM) in forests. While CWM is known to be an important resource for saproxylic species that reside within downed logs, the relative importance of CWM for organisms residing beneath, in the soil is poorly understood. In this context, CWM likely modifies conditions as well as nutrient levels for soil communities that lie beneath. The relative importance of CWM for underlying soil communities may be accentuated in the black-spruce clay-belt region of Western Québec where soil nutrients are extremely limited by paludification and extensive Sphagnum growth. To better understand the importance of CWM for soil microarthropods in this region, we sampled the soil microarthropods directly under CWM and 50 cm. apart, in 20 sites representing different states of development of a black spruce-feather moss forest type. While previous studies in other forest types showed little effect of woody material, our preliminary results suggest that Oribatid mites are influenced by CWM. However, contrary to our expectations, they have lower abundances and diversity in soil directly under logs than in open areas. We hypothesize that as nutrients in the forest floor are rendered inaccessible due to the thick Sphagnum layer of this forest, detritivore mites depend on recent leaf litter as nutrient resource. Conversely, logs in this case are likely to work as a cover to litter fall.

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 score0.059
Threshold uncertainty score0.955

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 studies0.0000.001
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 head0.012
GPT teacher head0.194
Teacher spread0.182 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

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