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Record W2897534636 · doi:10.5061/dryad.ch10ss4

Data from: Soil organic carbon dynamics matching ecological equilibrium theory

2018· article· en· W2897534636 on OpenAlexaff
Tancredi Caruso, Franciska T. de Vries, Richard D. Bardgett, Johannes Lehmann

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Ecology and Soil Science
Canadian institutionsQueen's University
Fundersnot available
KeywordsEcologyMatching (statistics)Soil carbonEnvironmental scienceCarbon fibersSoil waterMathematicsBiologyStatistics

Abstract

fetched live from OpenAlex

The persistence of soil organic carbon (SOC) has traditionally been explained as a combination of recalcitrance properties and stabilization processes, which lead to the formation of complex organic compounds. However, recent conceptual advances and experimental evidence challenge this view. Here, we test these conceptual advances using a dynamic equilibrium theory of SOC founded on classic ecological theory. We postulate that the persistence of SOC is an equilibrium point where SOC losses resulting from continuous decomposition and SOC gains due to SOC protection are balanced. We show that we can describe the temporal dynamics of SOC remarkably well (average and median R2 = 0.75) in publicly available SOC time series from experiments that investigated the effects of agricultural practices in arable soils. The predictive power of our simplistic model is not meant to compete with that of current multi-pool SOC models or recent developments that include microbial loops. The simplicity of our analysis can, however, show how the conceptual distinction between the forces that control SOC loss and gain, and their equilibrium, can shed light on SOC dynamics. Specifically, our analysis shows that, regardless of specific mechanisms, the persistence of SOC will depend on the ultimate equilibrium between SOC gains and losses, which may depend on environmental (e.g., temperature) and ecological (e.g., spatially structured microbial activities) factors and the relative roles of these factors. Future experimental studies should quantify these roles to formulate a new generation of SOC dynamics model.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0040.008
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 head0.018
GPT teacher head0.236
Teacher spread0.218 · 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 teacher head, 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

Citations0
Published2018
Admission routes1
Has abstractyes

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