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Record W2994070165 · doi:10.5194/soil-6-195-2020

Boreal-forest soil chemistry drives soil organic carbon bioreactivity along a 314-year fire chronosequence

2020· article· en· W2994070165 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSOIL · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsMinistère des Ressources naturelles et des ForêtsNatural Resources CanadaUniversité du Québec en Abitibi-TémiscamingueCanadian Forest ServiceNatural Sciences and Engineering Research Council of Canada
FundersMitacs
KeywordsChronosequenceSoil carbonEnvironmental chemistrySoil waterMossSoil organic matterSoil pHSoil textureTaigaChemistrySoil chemistryTotal organic carbonEnvironmental scienceSoil scienceDominance (genetics)AgronomyEcologyBiology

Abstract

fetched live from OpenAlex

Abstract. Following a wildfire, organic carbon (C) accumulates in boreal-forest soils. The long-term patterns of accumulation as well as the mechanisms responsible for continuous soil C stabilization or sequestration are poorly known. We evaluated post-fire C stock changes in functional reservoirs (bioreactive and recalcitrant) using the proportion of C mineralized in CO2 by microbes in a long-term lab incubation, as well as the proportion of C resistant to acid hydrolysis. We found that all soil C pools increased linearly with the time since fire. The bioreactive and acid-insoluble soil C pools increased at a rate of 0.02 and 0.12 MgC ha−1 yr−1, respectively, and their proportions relative to total soil C stock remained constant with the time since fire (8 % and 46 %, respectively). We quantified direct and indirect causal relationships among variables and C bioreactivity to disentangle the relative contribution of climate, moss dominance, soil particle size distribution and soil chemical properties (pH, exchangeable manganese and aluminum, and metal oxides) to the variation structure of in vitro soil C bioreactivity. Our analyses showed that the chemical properties of podzolic soils that characterize the study area were the best predictors of soil C bioreactivity. For the O layer, pH and exchangeable manganese were the most important (model-averaged estimator for both of 0.34) factors directly related to soil organic C bioreactivity, followed by the time since fire (0.24), moss dominance (0.08), and climate and texture (0 for both). For the mineral soil, exchangeable aluminum was the most important factor (model-averaged estimator of −0.32), followed by metal oxide (−0.27), pH (−0.25), the time since fire (0.05), climate and texture (∼0 for both). Of the four climate factors examined in this study (i.e., mean annual temperature, growing degree-days above 5 ∘C, mean annual precipitation and water balance) only those related to water availability – and not to temperature – had an indirect effect (O layer) or a marginal indirect effect (mineral soil) on soil C bioreactivity. Given that predictions of the impact of climate change on soil C balance are strongly linked to the size and the bioreactivity of soil C pools, our study stresses the need to include the direct effects of soil chemistry and the indirect effects of climate and soil texture on soil organic matter decomposition in Earth system models to forecast the response of boreal soils to global warming.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score1.000

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 head0.012
GPT teacher head0.198
Teacher spread0.186 · 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