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The net GHG balance and budget of the permafrost region (2000-2020) from ecosystem flux upscaling

2023· preprint· en· W4386709401 on OpenAlexaff
Justine Ramage, McKenzie A. Kuhn, Anna- Maria Virkkala, Carolina Voigt, Maija E. Marushchak, Ana Bastos, Christina Biasi, Josep G. Canadell, Philippe Ciais, Efrèn López‐Blanco, Susan M. Natali, David Olefeldt, Stefano Potter, Benjamin Poulter, Brendan M. Rogers, Ted A.G. Schuur, Claire C. Treat, Merritt R. Turetsky, Jennifer D. Watts, Gustaf Hugelius

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPermafrostEnvironmental scienceEcosystemGreenhouse gasSink (geography)Carbon sinkFlux (metallurgy)Atmospheric sciencesClimate changePrimary productionHydrology (agriculture)Physical geographyGeographyEcologyGeologyOceanography

Abstract

fetched live from OpenAlex

The northern permafrost region has been projected to shift from a net sink to a net source of carbon under global warming. However, estimates of the contemporary net greenhouse gas (GHG) balance and budgets of the permafrost region remain highly uncertain. Here we construct the first comprehensive bottom-up budgets of CO2, CH4, and N2O across the terrestrial permafrost region using databases of more than 1000 in-situ flux measurements and a land cover-based ecosystem flux upscaling approach for the period 2000-2020. Estimates indicate that the permafrost region emitted a mean annual flux of 0.36 (-620, 652) Tg CO2-C y-1, 38 (21, 53) Tg CH4-C y-1, and 0.62 (0.03, 1.2) Tg N2O-N y-1 to the atmosphere throughout the period. While the region was a net source of CH4 and N2O, the CO2 budget was near neutral with large uncertainties. Terrestrial ecosystems remained a CO2 sink, but emissions from fire disturbances and inland waters largely offset the sink in vegetated ecosystems. Including lateral fluxes, the permafrost region was a net source of C and N, releasing 136 (-517, 821) Tg C y-1 and 3.2 (1.9, 4.8) Tg N y-1. Large uncertainty ranges in these estimates point to a need for further expansion of monitoring networks, continued data synthesis efforts, and better integration of field observations, remote sensing data, and ecosystem models to constrain the contemporary net GHG budgets of the permafrost region and track their future trajectory.

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)0.001
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 score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.230
Teacher spread0.196 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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