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Record W7161772768 · doi:10.82308/17784

Controls on the soil solution partitioning of dissolved organic carbon and nitrogen in the mineral horizons of forested soils

2009· dissertation· en· W7161772768 on OpenAlexaboutno aff
Dolly N. Kothawala

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsDissolved organic carbonPodzolSoil waterSorptionDesorptionAdsorptionLangmuir adsorption modelSoil horizonSoil organic matter

Abstract

fetched live from OpenAlex

The soil-solution partitioning of dissolved organic carbon (DOC) within mineral soil horizons is primarily controlled by processes of adsorption and desorption. These abiotic processes largely occur within a short equilibration time of seconds to minutes, which generally occur faster than microbial processes. To characterise the adsorption of DOC to mineral soils, I used the Langmuir adsorption isotherm, which holds several advantages to the commonly used linear initial mass (IM) isotherm. One advantage to using the Langmuir isotherm is an estimation of the maximum DOC adsorption capacity (Qmax). The Qmax estimates the number of remaining DOC binding sites available on the mineral soil particle surfaces. I modified the traditional Langmuir isotherm in order to estimate the DOC desorption potential of native soil organic matter (SOC). Sorption characteristics were derived for a broad range of52 mineral soils collected from 17 soil profiles spanning across Canada from British Columbia to Quebec. Mineral horizons with the greatest Qmax included the Fe-enriched B horizons of acidic Podzols and Volcanic soils, followed by B horizons not enriched in Fe, followed by A and C horizons. Podzol B horizons were distinct from all other horizons due to significantly higher desorption potential. Soil properties predicting the adsorption characteristics of DOC also predicted the adsorption characteristics of dissolved organic nitrogen (DON). Adsorption of DOC and DON was tightly coupled (R 2 = 0.86), however the ratio of DOC:DON in the final equilibrium solution lowered for 48 out of 52 minerals horizons. These results suggest that DON may be slightly more mobile than DOC. A short-term (32 day) incubation was perform to establish the fate of indigenous soil C, relative to newly adsorbed soil C to four mineral soils with different adsorption characteristics. Soil columns were leached periodically and sampled for DOC and CO2 production. Two Fe-enriched mineral horizons with high adsorption capacity released low amounts of old SOC, yet released almost all of the newly adsorbed SOC. In contrast, two B horizons without Fe-enrichment released greater amounts of old SOC, and retained a greater fraction of the newly adsorbed SOC than the Fe-enriched horizons. These results identify a contrast between the fate of indigenous and newly adsorbed SOC on mineral soils with differing Qmax. The final component of this study examined changes to the molecular structure of DOC after equilibration with mineral soils. Multiple techniques were used to assess changes in the molecular composition of DOC, including the analysis of aromatic content by specific UV absorbance (SUVA) and fluorescence spectroscopy, analysis of molecular weight distribution (MWD) with high performance size exclusion chromatography (HPSEC) and functional group analysis with Fourier transform infra-red spectroscopy (FTIR). The solution phase DOC generally showed a reduced aromatic content, along with the removal of organic compounds with carboxyl groups. The MWD of DOC was reduced after equilibration to mineral soils, and the reduction in average molecular weight was related to the Qmax of mineral soils. The various components of this thesis have contributed to the overall understanding of controls on the adsorption of DOC and DON species to mineral soils of the Canadian temperate and boreal forest.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.321
Threshold uncertainty score0.639

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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 source (direct Gemma or distilled Codex), 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
Published2009
Admission routes1
Has abstractyes

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