Short-term impacts of forest clear-cut on soil structure and consequences for organic matter composition and nutrient speciation: A case study
Bibliographic record
Abstract
Clear-cuts of forests severely affect soil structure and thus soil organic matter (SOM) and nutrient cycling dynamics therein, though with yet unknown consequences for SOM composition as well as phosphorus (P) and sulfur (S) chemical form within the soil microaggregate size fraction. To determine the effects of conventional clear-cutting on soil chemistry in a Cambisol of the Wüstebach Forest (northwestern Germany), we sampled the mineral A- and B-horizons prior to clear-cut as well as 10 and 24 month thereafter. We measured the SOM composition of soil microaggregates using pyrolysis field ionization mass spectrometry (Py-FIMS), as well as P and S chemical form and speciation using wet-chemical extractions and X-ray absorption near edge structure (XANES) spectroscopy. We found that clear-cut led to an increase of the microaggregate size fraction up to 6% due to break-down of macroaggregates and initially significantly increased total elemental concentrations (C, N, P, S) due to the introduction of slash-residues. The SOM of slash-residues consisted to a substantial amount of sterols and was generally found to be of low thermal stability and probably did not contribute to aggregate stability. Deterioration of the aggregate structure probably led to an exposure of originally inaccessible sites within aggregates to the attack by soil microorganisms and thus to an increased P and S turnover as reflected in a significantly reduction of available P proportions (4 to 7%) and a reduction of the most reduced S forms (5%). A probable increased microbial activity and contribution to SOM after clear-cut is also reflected in the significantly increasing hexose:pentose ratio by 0.25 between 10 and 24 month after clear-cut, significantly increasing the general thermal stability of SOM in the microaggregate size fraction and believed to contribute to aggregate stability. This indicated that a first deterioration of the aggregate structure after clear-cut might in the long-term be remediated with time.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".