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Record W2027858951 · doi:10.4236/ojf.2015.54029

Climate Variation and Disturbance Regime Affect Stand Composition and Structure of the Boreal Forests in Southwest Yukon of Canada

2015· article· en· W2027858951 on OpenAlexaffabout
Shyam K. Paudel, Suzanne W. Simard, Craig R. Nitschke, John L. Innes

Bibliographic record

VenueOpen Journal of Forestry · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTaigaDisturbance (geology)DeciduousBorealSalicaceaeEcologyEnvironmental scienceProductivityBalsamForestryBoreal ecosystemWoody plantStand developmentGeographyBiologyBotany

Abstract

fetched live from OpenAlex

The cold and dry boreal forests of the Southwest Yukon are dominated by white spruce (Picea glauca), trembling aspen (Populus tremuloides) and balsam poplar (Populus balsamifera), and the variability in structure and composition of stands depends on the favourability of disturbance, climate and site conditions for stimulating regeneration. In this study, we investigated relationships between stand structure and ecological, climatic and disturbance factors in the southwest Yukon. We found that white spruce dominates mature forests across the landscape, but it is regenerating proportionately less than trembling aspen. Nevertheless, regeneration of all the three species was abundant following any type or severity of disturbance. Height and diameter of both species varied with several environmental variables, particularly site physiography. Mixed stands of aspen and white spruce were more productive than pure stands of aspen or spruce. However, overall productivity in mixed stand decreased when density of aspen was more than 1000 stems/ ha. These results suggested that mixed stands of deciduous and coniferous species where appropriate should be promoted maintaining aspen density below 1000 stems/ha as the productivity declined beyond this threshold. Similarly, we suggest carrying out selection harvesting of co-dominant trees and regular thinning of intermediate trees to promote the height and diameter growth of the remaining trees.

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 score0.174
Threshold uncertainty score0.350

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.215
Teacher spread0.209 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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