Investigation of Anthropogenic Processes on the Molecular Composition and Stability of Natural Organic Matter in Agroecosystems and Deep Geological Repository Conditions
Bibliographic record
Abstract
Varied environmental conditions (e.g., soil physiochemical properties, temperature, precipitation, plant litter quality) and anthropogenic disturbance (i.e., land-use change to cultivation, agricultural land management) may alter natural organic matter (NOM) biogeochemical dynamics. Among these constraints, which environmental factors mainly regulate NOM composition and solubility and how human activities will change these relationships still needs to be studied. Moreover, how NOM composition and reactivity in Wyoming-type bentonite (MX-80) will change after being exposed to deep geological repository (DGR) conditions is still unknown, which is one of the key factors to evaluate the reliability of the long-term used nuclear fuel storage plan. To fill these gaps, molecular-level NOM characterization was performed in agroecosystems and DGR conditions. The quality and solubility of terrestrial-derived dissolved organic matter (DOM) were observed to be directly related to the chemistry of soil organic matter (SOM) and the soil physicochemical properties, and land-use change to cultivation altered these relationships considerably. The accumulation of relatively long-lived SOM components (i.e., long-chain aliphatic lipids) in mineral-associated soil carbon pools was observed by the molecular-level analysis of SOM in response to diversified crop rotations. Both quantity and quality analyses of SOM confirmed that the long-term crop rotational diversity enhanced soil carbon storage. The NOM composition and solubility in MX-80 bentonite after accumulated radiation and heat (100 kGy+80°C) exposure did not observe significant changes. Assessments of targeted NOM compound concentrations in MX-80 bentonite after relatively longer heat exposure periods (14 - 42 days at 90°C) detected nanogram-level differences in comparison to the control sample. The assessment also found minor DOM compositional differences after salinity and heat exposure. With broader assessments of NOM characteristics, the relatively short-term of (in comparison to the long lifetime of the DGR) heat, radiation and salinity exposure with the proposed DGR conditions were unlikely to alter NOM chemistry (including both chemical signature and organic carbon content) in MX-80 bentonite. Overall, this thesis investigated NOM stability and compositional differences in response to varied environmental factors in both agroecosystems and DGR conditions. Since the quantitative analysis may not always indicate variations, molecular-level analysis is crucial in assessing the biogeochemical dynamics of NOM under different environmental circumstances.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".