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Record W2982511501 · doi:10.1126/sciadv.aax2546

Degradation and forgone removals increase the carbon impact of intact forest loss by 626%

2019· article· en· W2982511501 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience Advances · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversity of Northern British Columbia
FundersJohn D. and Catherine T. MacArthur Foundation
KeywordsDefaunationCarbon sequestrationDeforestation (computer science)Environmental scienceGreenhouse gasCarbon fibersCarbon accountingForest degradationClimate changeLoggingAtmospheric carbon cycleGlobal warmingNatural resource economicsEnvironmental protectionAgroforestryLand useForestryCarbon dioxideEcologyGeographyLand degradationChemistryBiologyEconomics

Abstract

fetched live from OpenAlex

Intact tropical forests, free from substantial anthropogenic influence, store and sequester large amounts of atmospheric carbon but are currently neglected in international climate policy. We show that between 2000 and 2013, direct clearance of intact tropical forest areas accounted for 3.2% of gross carbon emissions from all deforestation across the pantropics. However, full carbon accounting requires the consideration of forgone carbon sequestration, selective logging, edge effects, and defaunation. When these factors were considered, the net carbon impact resulting from intact tropical forest loss between 2000 and 2013 increased by a factor of 6 (626%), from 0.34 (0.37 to 0.21) to 2.12 (2.85 to 1.00) petagrams of carbon (equivalent to approximately 2 years of global land use change emissions). The climate mitigation value of conserving the 549 million ha of tropical forest that remains intact is therefore significant but will soon dwindle if their rate of loss continues to accelerate.

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.

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 score0.016
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.005
GPT teacher head0.259
Teacher spread0.254 · 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