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Record W2179108203 · doi:10.1139/x07-148

Residual-tree growth responses to partial stand harvest in the black spruce (<i>Picea mariana</i>) boreal forestThis article is one of a selection of papers published in the Special Forum IUFRO 1.05 Uneven-Aged Silvicultural Research Group Conference on Natural Disturbance-Based Silviculture: Managing for Complexity.

2007· article· en· W2179108203 on OpenAlexafffundvenueabout
H. C. Thorpe, Sean C. Thomas, John P. Caspersen

Bibliographic record

VenueCanadian Journal of Forest Research · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsUniversity of Toronto
FundersCanadian Forest ServiceNatural Sciences and Engineering Research Council of Canada
KeywordsChronosequenceBlack spruceSilvicultureTaigaBorealStand developmentForest managementResidualWood productionPostharvestForestryLoggingEnvironmental scienceAgroforestryEcologyBiologyEcosystemGeographyHorticultureMathematics

Abstract

fetched live from OpenAlex

Variants of partial harvesting are gaining favour as means to balance ecosystem management and timber production objectives on managed boreal forest landscapes. Understanding how residual trees respond to these alternative silvicultural treatments is a critical step towards evaluating their potential from either a conservation or a wood supply perspective. We used dendroecological techniques combined with a chronosequence approach to quantify the temporal radial growth response pattern of residual black spruce ( Picea mariana (Mill.) BSP) trees to partial harvest in northeastern Ontario. At its peak, 8–9 years after harvest, radial growth of residual trees had doubled. The growth pattern was characterized by a 2-year phase of no response, a subsequent period of increase 3–9 years after harvest, and a stage of declining rates 10–12 years after harvest. The magnitude of tree growth response depended strongly on tree age: peak postharvest growth was substantially higher for young trees, while old trees displayed only modest growth increases. Both the large magnitude and the time delay in postharvest growth responses have important implications for the development of more accurate quantitative tools to project future yields and, more generally, for determining whether partial harvesting is a viable management option for the boreal forest.

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)0.012
metaresearch head score (Gemma)0.002
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 score0.886
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.047
GPT teacher head0.302
Teacher spread0.255 · 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

Citations68
Published2007
Admission routes4
Has abstractyes

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