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Record W3155495511 · doi:10.1126/science.abf3903

Carbon loss from boreal forest wildfires offset by increased dominance of deciduous trees

2021· article· en· W3155495511 on OpenAlex
Michelle C. Mack, Xanthe J. Walker, Jill F. Johnstone, Heather D. Alexander, April M. Melvin, Mélanie Jean, Samantha Miller

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 · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversité de MonctonYukon UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsDeciduousTaigaDominance (genetics)BorealOffset (computer science)Environmental scienceCarbon stockEcologyForestryPhysical geographyGeographyAgroforestryAtmospheric sciencesBiologyClimate changeGeologyComputer science

Abstract

fetched live from OpenAlex

In boreal forests, climate warming is shifting the wildfire disturbance regime to more frequent fires that burn more deeply into organic soils, releasing sequestered carbon to the atmosphere. To understand the destabilization of carbon storage, it is necessary to consider these effects in the context of long-term ecological change. In Alaskan boreal forests, we found that shifts in dominant plant species catalyzed by severe fire compensated for greater combustion of soil carbon over decadal time scales. Severe burning of organic soils shifted tree dominance from slow-growing black spruce to fast-growing deciduous broadleaf trees, resulting in a net increase in carbon storage by a factor of 5 over the disturbance cycle. Reduced fire activity in future deciduous-dominated boreal forests could increase the tenure of this carbon on the landscape, thereby mitigating the feedback to climate warming.

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)0.001
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 score0.122
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.003
GPT teacher head0.198
Teacher spread0.195 · 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