Long-term effects of silviculture on soil carbon storage: does vegetation control make a difference?
Bibliographic record
Abstract
Forests and the soils beneath them are Earth's largest terrestrial sinks for atmospheric carbon (C) and healthy forests provide a partial check against atmospheric rises in CO2. Consequently, there is global interest in crediting forest managers who enhance C retention. Interest centres on C acquisition and storage in trees. Less is directed to understorey management practices that affect early forest development. Even less is paid to the largest ecosystem reservoir of all – the mineral soil. Understorey vegetation control is a common management practice to boost stand growth, but the consequence of this on ecosystem C storage is poorly understood. We addressed this by pooling data from five independent groups of long-term studies in the western US. Understorey control increased overstorey biomass universally, but C contents of the forest floor and top 30 cm of mineral soil largely were unaffected. Net soil C increment averaged 1.3 Mg C ha−1 year−1 in the first decade. We conclude that soil C storage is not affected adversely by vegetation management in forests under a Mediterranean climate. However, understorey shrubs can profoundly affect stand susceptibility to wildfire. We propose that C accounting systems be strengthened by assessing understorey management practices relative to wildfire risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".