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Record W1930021590 · doi:10.1126/science.aaa1668

The dominant role of semi-arid ecosystems in the trend and variability of the land CO <sub>2</sub> sink

2015· article· en· W1930021590 on OpenAlexfundno aff
Anders Ahlström, Michael Raupach, Guy Schurgers, Benjamin Smith, Almut Arneth, Martin Jung, Markus Reichstein, Josep G. Canadell, Pierre Friedlingstein, Atul K. Jain, Etsushi Kato, Benjamin Poulter, Stephen Sitch, Benjamin D. Stocker, Nicolas Viovy, Ying‐Ping Wang, Andy Wiltshire, Sönke Zaehle, Ning Zeng

Bibliographic record

VenueScience · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
FundersNatural Environment Research CouncilNatural Sciences and Engineering Research Council of CanadaU.S. Geological SurveyU.S. Department of EnergyKungliga Fysiografiska Sällskapet i LundNational Aeronautics and Space AdministrationMinistry of EnvironmentNational Oceanic and Atmospheric AdministrationSight Research UKSeventh Framework ProgrammeCommonwealth Scientific and Industrial Research OrganisationVetenskapsrådetNational Science Foundation
KeywordsBiosphereEnvironmental scienceAridEcosystemShrublandCarbon sinkCarbon cycleSink (geography)Water cycleAtmospheric sciencesPrecipitationCarbon dioxideTropicsTerrestrial ecosystemProductivityEcologyGeographyGeologyBiologyMeteorology

Abstract

fetched live from OpenAlex

The growth rate of atmospheric carbon dioxide (CO2) concentrations since industrialization is characterized by large interannual variability, mostly resulting from variability in CO2 uptake by terrestrial ecosystems (typically termed carbon sink). However, the contributions of regional ecosystems to that variability are not well known. Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, we show that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions. Whereas the mean sink is dominated by highly productive lands (mainly tropical forests), the trend and interannual variability of the sink are dominated by semi-arid ecosystems whose carbon balance is strongly associated with circulation-driven variations in both precipitation and temperature.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.194
Teacher spread0.189 · 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

Citations1,478
Published2015
Admission routes1
Has abstractyes

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