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Changes in plant lignin components and microbial necromass matter with subtropical forest restoration

2024· article· en· W4394008357 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.

Bibliographic record

VenueGeoderma · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsLakehead University
FundersNational Natural Science Foundation of China
KeywordsLigninSubsoilTopsoilSoil carbonSoil organic matterChemistryOrganic matterEnvironmental chemistryEnvironmental scienceSoil waterSoil scienceOrganic chemistry

Abstract

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Soil organic carbon (SOC) represents the largest carbon reservoir in terrestrial ecosystems. Therefore, understanding how to enhance SOC is crucial for the global carbon cycle and atmospheric CO2 removal. While there has been reported on SOC accumulation following forest restoration efforts, changes in plant lignin and microbial necromass across soil fractions and depths remain unclear. To address this gap, we investigated the SOC-standardized concentrations of lignin phenols and amino sugars in bulk soil and soil fractions (particulate organic matter (POM) and mineral-associated organic matter (MAOM)) during subtropical forest restoration, as tracers for change in plant lignin components and microbial necromass respectively. Our findings indicate that forest restoration does not affect SOC concentrations, but does result in changes in plant lignin and microbial necromass. Specifically, in the subsoil, lignin phenols and amino sugars concentrations in bulk soil and soil fractions rise significantly with restoration time, with lignin phenols and amino sugars concentrations in bulk soil rising by 29.6% and 53.0%, respectively. This suggests that as forests recover, lignin and microbial necromass have a higher contribution to SOC accumulation in the subsoil, while the contribution of low-molecular plant-derived organic matter decreases. The relative change rate of lignin phenols (relative to SOC) is greater than that of amino sugars in POM in the topsoil, while in the subsoil, the relative change rate of amino sugars in MAOM is greater than that of lignin phenols. These results indicate that lignin in POM declines more rapidly than amino sugars during restoration, whereas in MAOM, amino sugars accumulate faster than lignin. Overall, these findings provide important insights into the regulation of SOC accumulation during forest restoration by the combination of plant lignin and microbial necromass in various stabilization pathways.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score0.982

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 head0.014
GPT teacher head0.195
Teacher spread0.181 · 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