Persistent soil organic carbon deficits from converting primary forests to plantations and secondary forests in subtropical China
Bibliographic record
Abstract
Soil organic carbon (SOC) plays a critical role in supporting key ecosystem functions and services for humanity. Despite the widespread conversion of primary forests to plantations and secondary forests, it remains uncertain how it affects the content and distribution of SOC. We evaluated SOC content, its components in two fractions, particulate organic carbon (a mean residence time shorter than decades) and mineral-associated organic carbon (a mean residence time of multiple decades to centuries), and the fine root characteristics (biomass, necromass, and C: N of dead fine roots) across Chinese fir plantations and secondary forests during stand development (5–41 years old) in subtropical China, employing primary forests as a reference. We found that SOC content differed significantly between forest types and soil depths, but not with stand age within plantations or secondary forests. In the topsoil (0–10 cm), the SOC content of primary and secondary forests was 47 % and 25 % higher than that of Chinese fir plantations, respectively. The SOC content in the subsoil (40–60 cm) was approximately 6 ± 1.7 mg C g−1 and did not change significantly with forest types or stand ages. The higher SOC contents in primary forests and secondary forests in topsoil resulted primarily from particulate organic carbon accumulation caused by higher fine root biomass and dead root C: N. The fraction of mineral-associated organic carbon to SOC increased with soil depth and was higher in Chinese fir plantations than in secondary forests, suggesting that more SOC is composed of mineral-associated organic carbon that was associated with a higher amount of fine root necromass. Contrary to our expectations, we found SOC content or its fractions did not increase with 40 years of plantation and secondary forest development. Our results reveal persistent SOC deficits from converting primary forests to plantations and secondary forests and highlight the urgent need to conserve the remaining primary forests and protect secondary forests and plantations from disturbances, allowing them to evolve towards older-aged primary forests.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".