Using stable carbon isotopes of lignin derived methoxy groups to investigate the impact of historical land use change on sediment/particulate matter dynamics 
Bibliographic record
Abstract
Land-use specific sediment source apportionment using compound specific isotopic tracers occurs with challenges from both contributions from aquatic and particulate organic matter sources. Additionally, compound specific tracers have often occurred with co-linearity. Challenging our current understanding of erosion processes, previous studies using compound-specific isotopic tracers regularly indicate forests as the dominant source of sediment. We hypothesized that this estimation may be attributed to misclassifying particulate organic matter as a sediment contribution from forests.This study is based in Lake Baldegg (Lucerne, Switzerland) and utilizes the δ13C values of lignin-derived methoxy groups and alkane average chain length as an additional land-use-specific tracer to δ13C fatty acids. Three Suess corrections using different tracer residence times are applied to constrain the changing δ13C values of CO2 in the atmosphere over the last 130 years. To identify changes in sediment sources over the last 130 years, contributions of particulate organic matter are determined, and subsequently removed to apportion only the mineral associated soil fraction. To determine the confidence which can be applied to the model’s output, the model's performance is evaluated with 300 mathematical mixtures. The potential misclassification of forest contributions is investigated by merging particulate organic matter and forest sources to simulate tracers which are unable to discriminate between these two sources.The incorporation of δ13C values of lignin methoxy groups and alkane average chain length as additional tracers successfully expands the problematic one-dimensional mixing line. Mathematical mixtures demonstrate the improvement of the model’s performance when using both the average chain length and δ13C values of lignin-derived methoxy groups as an additional tracer. Furthermore, they also demonstrate an underestimation of arable contribution. Changes in dominant sediment sources (Forest: pre-1990, Pasture: 1910-1940, Arable: post-1940) highlight the influence of policy-induced land-use changes. Additionally, the study reveals a 37% overestimation of forest contributions to the sediment core due to the inability to discriminate between particulate organic matter and forest sources.The use of δ13C values of lignin methoxy groups as an additional tracer enables the identification of critical points in the 130-year sediment history of Lake Baldegg. We emphasize the importance of incorporating multiple Suess corrections to constrain the effect of multiple turnover times of tracers. While merging forest and particulate organic matter sources did not alter the dominant source over the last 130 years, it highlighted the need of separating these sources for more accurate apportionment. The study contributes valuable insights to sediment dynamics and land-use impacts, offering guidance for environmental management strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".