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Record W2112114797 · doi:10.5194/bg-9-3185-2012

An assessment of the carbon balance of Arctic tundra: comparisons among observations, process models, and atmospheric inversions

2012· article· en· W2112114797 on OpenAlexaff
A. David McGuire, Torben R. Christensen, Daniel J. Hayes, A. Heroult, E. S. Euskirchen, John S. Kimball, Charles D. Koven, Peter M. Lafleur, Paul Miller, Walter C. Oechel, Philippe Peylin, Yonghong Yi

Bibliographic record

VenueBiogeosciences · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsTrent University
FundersBiological and Environmental ResearchNatural Environment Research CouncilOffice of ScienceLunds UniversitetSvenska Forskningsrådet FormasU.S. Geological SurveyU.S. Department of EnergyU.S. Fish and Wildlife ServiceEuropean CommissionSight Research UKNational Aeronautics and Space AdministrationVetenskapsrådetNational Science Foundation
KeywordsTundraEnvironmental scienceArcticAtmospheric sciencesBiosphereEcosystemClimatologyGlobal warmingGreenhouse gasTerrestrial ecosystemClimate changeBiosphere modelCarbon cycleSink (geography)Climate modelCarbon sinkEcologyGeographyGeology

Abstract

fetched live from OpenAlex

Abstract. Although Arctic tundra has been estimated to cover only 8% of the global land surface, the large and potentially labile carbon pools currently stored in tundra soils have the potential for large emissions of carbon (C) under a warming climate. These emissions as radiatively active greenhouse gases in the form of both CO2 and CH4 could amplify global warming. Given the potential sensitivity of these ecosystems to climate change and the expectation that the Arctic will experience appreciable warming over the next century, it is important to assess whether responses of C exchange in tundra regions are likely to enhance or mitigate warming. In this study we compared analyses of C exchange of Arctic tundra between 1990 and 2006 among observations, regional and global applications of process-based terrestrial biosphere models, and atmospheric inversion models. Syntheses of flux observations and inversion models indicate that the annual exchange of CO2 between Arctic tundra and the atmosphere has large uncertainties that cannot be distinguished from neutral balance. The mean estimate from an ensemble of process-based model simulations suggests that Arctic tundra has acted as a sink for atmospheric CO2 in recent decades, but based on the uncertainty estimates it cannot be determined with confidence whether these ecosystems represent a weak or a strong sink. Tundra was 0.6 °C warmer in the 2000s compared to the 1990s. The central estimates of the observations, process-based models, and inversion models each identify stronger sinks in the 2000s compared with the 1990s. Some of the process models indicate that this occurred because net primary production increased more in response to warming than heterotrophic respiration. Similarly, the observations and the applications of regional process-based models suggest that CH4 emissions from Arctic tundra have increased from the 1990s to 2000s because of the sensitivity of CH4 emissions to warmer temperatures. Based on our analyses of the estimates from observations, process-based models, and inversion models, we estimate that Arctic tundra was a sink for atmospheric CO2 of 110 Tg C yr−1 (uncertainty between a sink of 291 Tg C yr−1 and a source of 80 Tg C yr−1) and a source of CH4 to the atmosphere of 19 Tg C yr−1 (uncertainty between sources of 8 and 29 Tg C yr−1). The suite of analyses conducted in this study indicate that it is important to reduce uncertainties in the observations, process-based models, and inversions in order to better understand the degree to which Arctic tundra is influencing atmospheric CO2 and CH4 concentrations. The reduction of uncertainties can be accomplished through (1) the strategic placement of more CO2 and CH4 monitoring stations to reduce uncertainties in inversions, (2) improved observation networks of ground-based measurements of CO2 and CH4 exchange to understand exchange in response to disturbance and across gradients of climatic and hydrological variability, and (3) the effective transfer of information from enhanced observation networks into process-based models to improve the simulation of CO2 and CH4 exchange from Arctic tundra to the atmosphere.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.074
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.073
GPT teacher head0.292
Teacher spread0.219 · 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

Citations395
Published2012
Admission routes1
Has abstractyes

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