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Record W2400242403 · doi:10.14288/1.0102007

Soils and forest growth in the Sayward Forest, British Columbia

2011· article· en· W2400242403 on OpenAlexaboutno aff
Nurettin Keser

Bibliographic record

VenuecIRcle (University of British Columbia) · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
Fundersnot available
KeywordsSoil waterForestryEnvironmental scienceOld-growth forestGeographySoil science

Abstract

fetched live from OpenAlex

The sustained-yield policy presently practiced in British Columbia necessitates intensive management of forest land especially in the coastal region of the province. Soils, their nature and distribution, provide an ideal framework for a successful implementation of such management. A mapping system encompassing geology and soil and providing units interpretable for forestry practices was developed for the coastal forested lands of British Columbia. The system contains several steps of mappings corresponding to different intensities or levels of abstraction. These levels are: 1. Bedrock geology, 2. Surficial geology, 3. Geologic units, 4. Geologic unit - drainage classes, 5. Soil associations, and 6. Soil catenas. Mapping employs air-photo interpretation extensively and can be directly undertaken at any desired level for inventory of interpretation purposes. Grouping of units can also be made from any level of mapping. Maps showing the distribution of bedrock types, surficial materials and soils were prepared. Vancouver volcanics, Coastal intrusives and Cretaceous sandstones are the main bedrock formations. The surficial materials encompass the inter-glacial, glacial, post glacial and recent deposits, and consist of glacial tills, glaciofluvial, alluvial and marine sediments. The soils encountered represent the Podzolic, Brunisolic, Regosolic, Gleysolic and Organic Orders. The area is comprised of primarily Douglas-fir plantation, 20 to 30 years of age. Studies involving the soil-stand growth relationship were undertaken on the well drained soils developed on the major surficial materials. Morphological, physical, chemical and minera1ogica1 characteristics of soils and the growth statistics of stands were determined. The growth performance of Douglas-fir varied with the kind of soil. Growth was best on soils developed from marine clay. Soils developed from stony outwash exhibited the slowest growth and lowest productivity. Till soils had productivity between these two extremes. The textural components of soil (coarse sand, medium sand, total sand, total silt, coarse clay, fine clay and total clay), were correlated to growth. With respect to chemical nutrients, organic matter, calcium and magnesium, phosphorus and zinc appeared to be important factors. The soil moisture retention characteristics such as field capacity and available water showed correlation with growth. The relationship between the growth and soil characteristics became more apparent as stand age advanced. Interpretation of soil series and mapping units at different levels was carried out for: productivity for Douglas-fir, species suitability, logging hazard, slash burning hazard, natural regeneration probabi1ity, brush hazard, browsing hazard, thinning prescription, fertilizer recommendation, road construction suitability, and erosion. Two groupings, potential productivity and thinning recommendation for Douglas-fir, were undertaken. The study indicated that knowledge of soils and their distribution are prerequisite to the operational and economical management of forest and soil resources. Consequently, a classification scheme such as the one presented is the first and essential step towards the intensive management of the coastal forested lands in British Columbia.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.007
GPT teacher head0.147
Teacher spread0.140 · 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 source (direct Gemma or distilled Codex), 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
Published2011
Admission routes1
Has abstractyes

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