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Record W4393371103 · doi:10.1016/j.soilbio.2024.109413

Restructuring of soil food webs reduces carbon storage potential in boreal peatlands

2024· article· en· W4393371103 on OpenAlexafffund
Carlos Barreto, Robert W. Buchkowski, Zoë Lindo

Bibliographic record

VenueSoil Biology and Biochemistry · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsAlgoma UniversityWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDecomposerEnvironmental scienceBiomass (ecology)Soil carbonFood webGlobal warmingNitrogen cyclePeatTrophic levelCarbon cycleEcologyEcosystemAgronomyNitrogenSoil scienceChemistrySoil waterClimate changeBiology

Abstract

fetched live from OpenAlex

Microbial and faunal decomposers regulate the flux of carbon and nitrogen belowground, thus controlling the storage/release of carbon and nitrogen in soil systems. Warming is anticipated to alter decomposer biomass, and accelerate organismal metabolism and soil carbon release. We parameterized six soil food webs using empirical data for 18 trophic nodes at two boreal peatland sites under three climate scenarios (control, +2 °C, +4 °C), and model carbon and nitrogen flux, loss and retention using an energetic ecostoichiometric food web model. Differences in microbial biomass between sites dictated flux under warming. The community biomass of the fungi-dominated site was more impacted by warming, but fluxes were more responsive to warming at the bacterial-dominated site. Decreased metabolic efficiency of the soil food web at both sites in response to warming led to greater per capita carbon losses, indicating the long-term carbon storage potential of both systems is diminished.

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)0.000
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 score0.036
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.004
GPT teacher head0.213
Teacher spread0.209 · 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

Citations20
Published2024
Admission routes2
Has abstractyes

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