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Record W2791581616 · doi:10.1139/cjfr-2017-0410

Carbon balance in production forestry in relation to rotation length

2018· article· en· W2791581616 on OpenAlexvenueno aff
Tomas Lundmark, Bishnu Chandra Poudel, Gustav Stål, Annika Nordin, Johan Sonesson

Bibliographic record

VenueCanadian Journal of Forest Research · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon stockScots pinePicea abiesCarbon fibersProductivityEnvironmental scienceStock (firearms)ForestryRotation (mathematics)BotanyEcologyClimate changePinus <genus>BiologyMathematicsGeographyEconomicsGeometry

Abstract

fetched live from OpenAlex

The choice of a rotation length is an integral part of even-aged forest management regimes. In this study, we simulated stand development and carbon pools in four even-aged stands representing the two most common tree species in Fennoscandia, Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.), growing on high- and low-productivity sites. We hypothesized that increased rotation lengths (+10, +20, and +30 years) in comparison with today’s practice would increase forests’ average carbon stock during a rotation cycle but decrease the average yield. The results showed that for spruce, a moderate increase in rotation length (+10 years) increased both average standing carbon stock and average yield. For the longer alternatives (+20 and +30 years) for spruce and for all pine alternatives, prolonging rotation lengths resulted in increased average standing carbon stocks but decreased average yield, resulting in decreased carbon storage in forest products and decreased substitution effects. Decreasing the rotation lengths (–10 years) always resulted in both decreased average standing carbon stocks and decreased yields. We conclude that a moderate increase of rotation lengths may slightly increase forests’ climate benefits for spruce sites, but for all other alternatives, there was a trade-off between the temporary gain of increasing carbon stocks and the permanent loss in productivity and, consequently, substitution potential.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.688
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.309
Teacher spread0.277 · 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

Citations42
Published2018
Admission routes1
Has abstractyes

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