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Record W2257420856 · doi:10.14288/1.0075567

The effects of ground-based harvesting on coastal British Columbia soils : mitigating the negative consequences

2013· article· en· W2257420856 on OpenAlexaboutno aff
Steve Trommel

Bibliographic record

VenuecIRcle (University of British Columbia) · 2013
Typearticle
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsnot available
Fundersnot available
KeywordsSoil waterEnvironmental scienceGroundwaterGeologyGeotechnical engineeringSoil science

Abstract

fetched live from OpenAlex

The recent downturn in British Columbia’s coastal forest industry, together with an increased proportion of timber harvest from second growth stands has increased pressure on harvest operations to reduce costs. Using ground-based harvest methods, primarily with skidders and hoe-chuckers, harvest operations can lower costs compared to cable yarding. Skidders and hoe-chuckers have the potential to negatively affect future site productivity and natural hydrological processes. The complexity of factors influencing the amount of soil disturbance resulting from skidder and hoe-chucker use makes the interpretation of research results difficult. The strongest factors are soil moisture at time of harvest and soil texture. Short term research on seedling growth has found a decrease in growth on machine trails of 20 to 53 percent (Senyk & Craigdallie, 1997). The difference in growth between machine trails and undisturbed areas decreases over time. Increased growth on the margins of machine trails has been shown to partially offset losses to growth on trails. Direct hydrological impacts from ground-based machinery have not been researched in great depth as hydrological processes are also complex. Case studies have shown the potential of ground-based harvesting to change water flow patterns resulting in mass wasting and drainage structure failures. The negative of consequences of ground-based harvesting can be mitigated by reducing harvest during very wet periods and through the use of designated trails, rehabilitating trails, proper equipment choice and operator training.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.582

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 studies0.0010.001
Scholarly communication0.0010.000
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 head0.005
GPT teacher head0.155
Teacher spread0.150 · 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
Published2013
Admission routes1
Has abstractyes

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