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Record W2588551296 · doi:10.3390/f8020041

Using Macronutrient Distributions within Trees to Define a Branch Diameter Threshold for Biomass Harvest in Sugar Maple-Dominated Stands

2017· article· en· W2588551296 on OpenAlexafffund
Samuel Royer‐Tardif, Sylvain Delagrange, Philippe Nolet, David Rivest

Bibliographic record

VenueForests · 2017
Typearticle
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsUniversité du Québec en OutaouaisUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNutrientYellow birchBiomass (ecology)SugarEnvironmental scienceBiomass partitioningMapleAgronomyBotanyBiologyEcology

Abstract

fetched live from OpenAlex

As the use of forest harvesting residues for energy production gains popularity, debate continues regarding the long-term sustainability of whole tree harvesting (WTH). This practice removes nutrient-rich twigs that only account for a small fraction of harvest residues, emphasising the need to develop nutrient-efficient alternatives to WTH. This study assessed N, P, K, Ca, and Mg distributions within sugar maple (Acer saccharum Marshall) and yellow birch (Betula alleghaniensis Britton) branches of various sizes in order to determine the branch diameter threshold that would represent the best compromise between the quantity of harvested biomass and nutrient losses that were generated. Quantities of nutrients that were exported with harvesting were then modelled at the stand level using different biomass harvest scenarios to explore what factors ultimately drove total quantities of nutrients exported with harvest. We found that the branch diameter threshold for biomass harvesting should be set at 2 cm for most nutrients in both tree species. An exception was Mg in yellow birch, for which the harvesting of branches larger than 10 cm would always generate larger nutrient export than gains in terms of biomass. At the stand scale, we provide evidence that the intensity of biomass harvest (i.e., the number of branch compartments harvested) is the principal factor responsible for the quantity of nutrient that is exported with harvesting.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.985

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 studies0.0000.000
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 head0.034
GPT teacher head0.284
Teacher spread0.250 · 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

Citations3
Published2017
Admission routes2
Has abstractyes

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