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Record W4241080304 · doi:10.5194/bgd-10-13603-2013

Climate and atmospheric drivers of historical terrestrial carbon uptake in the province of British Columbia, Canada

2013· preprint· en· W4241080304 on OpenAlexafffundabout
Yiran Peng, Vivek K. Arora, Werner A. Kurz, Robbie A. Hember, B. J. Hawkins, John C. Fyfe, A. T. Werner

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsColumbia CollegePacific Institute for Climate SolutionsUniversity of VictoriaNatural Resources CanadaUniversity of British ColumbiaCanadian Forest Service
FundersPacific Institute for Climate SolutionsUniversity of Victoria
KeywordsCarbon sinkSink (geography)Environmental scienceClimate changeCarbon dioxide in Earth's atmosphereCarbon dioxideEcosystemAtmospheric sciencesTerrestrial ecosystemCarbon cycleCarbon fibersPhysical geographyClimatologyGeographyEcologyGeologyMathematics

Abstract

fetched live from OpenAlex

Abstract. The impacts of climate change and increasing atmospheric CO2 concentration on the terrestrial uptake of carbon dioxide since 1900 in the Canadian province of British Columbia are estimated using the process-based Canadian Terrestrial Ecosystem Model (CTEM). Model simulations show that these two factors yield a carbon uptake of around 44 g C m−2 yr−1, during the 1980s and 1990s, and continuing into 2000s, compared to pre-industrial conditions. The increased carbon uptake translates into an increased sink of 41 Tg C yr−1, when multiplied with the 944 700 km2 area of the province. About three-quarters of the simulated sink enhancement in our study is attributed to changing climate, and the rest is attributed to increase in CO2 concentration. The model response to changing climate and increasing CO2 is corroborated by comparing simulated stem wood growth rates with ground-based measurements from inventory plots in coastal British Columbia. The simulated sink is not an estimate of the net carbon balance because the effect of harvesting and insect disturbances is not considered.

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 score0.030
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.004
GPT teacher head0.162
Teacher spread0.158 · 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

Citations8
Published2013
Admission routes3
Has abstractyes

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