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Record W2089092342 · doi:10.5558/tfc76747-5

Soil disturbance and aspen regeneration on clay soils: Three case histories

2000· article· en· W2089092342 on OpenAlexvenueno aff
Douglas M. Stone, John D. Elioff

Bibliographic record

VenueThe Forestry Chronicle · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceDisturbance (geology)LoggingClearcuttingSlash (logging)Soil waterFellingHydrology (agriculture)ThinningSuckerAgronomyForestrySoil scienceAgroforestryGeologyBiologyGeography

Abstract

fetched live from OpenAlex

Sustaining forest productivity requires maintaining soil productivity and prompt establishment of adequate regeneration following harvest. We determined effects of commercial, winter-logging of aspen-dominated stands on soil disturbance and development of regeneration on three sites with clay soils. We established transects across each site, recorded pre-harvest stand information, post-harvest site disturbance, and first-year aspen sucker density and height. Use of large logging equipment produced heavy disturbance on 38% of a well-drained site; 45% of the area had no aspen suckers and 82% had less than the recommended minimum of 15 000 (15 k) suckers per ha (6 k ac −1 ). Mean height of dominant suckers was 45 cm (18 in). Hand felling and a small skidder caused heavy disturbance on 12% of a moderately well-drained site. Sucker density averaged 34 k ha −1 (14 k ac −1 ) and height was 97 cm (38 in). Cut-to-length (CTL) equipment produced heavy disturbance on 11% of a somewhat poorly-drained site, mean sucker density of 24 k ha −1 (9.6 k ac −1 ), and height of 101 cm (40 in). These severely disturbed areas essentially are removed from the aspen-producing land base. Retaining the northern hardwood and conifer growing stock would result in less site disturbance and help maintain natural hydrologic and nutrient cycling processes. Key words: aspen management, site disturbance, sustainable management, logging damage, soil rutting, root damage, evapotranspiration, soil aeration, clearcutting with residuals

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 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 score0.297
Threshold uncertainty score0.999

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)0.0020.000

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 head0.011
GPT teacher head0.216
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.

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

Citations27
Published2000
Admission routes1
Has abstractyes

Explore more

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