Temporal changes in soil C‐N‐P stoichiometry over the past 60 years across subtropical China
Bibliographic record
Abstract
Abstract Controlled experiments have shown that global changes decouple the biogeochemical cycles of carbon (C), nitrogen (N), and phosphorus (P), resulting in shifting stoichiometry that lies at the core of ecosystem functioning. However, the response of soil stoichiometry to global changes in natural ecosystems with different soil depths, vegetation types, and climate gradients remains poorly understood. Based on 2,736 observations along soil profiles of 0–150 cm depth from 1955 to 2016, we evaluated the temporal changes in soil C‐N‐P stoichiometry across subtropical China, where soils are P‐impoverished, with diverse vegetation, soil, and parent material types and a wide range of climate gradients. We found a significant overall increase in soil total C concentration and a decrease in soil total P concentration, resulting in increasing soil C:P and N:P ratios during the past 60 years across all soil depths. Although average soil N concentration did not change, soil C:N increased in topsoil while decreasing in deeper soil. The temporal trends in soil C‐N‐P stoichiometry differed among vegetation, soil, parent material types, and spatial climate variations, with significantly increased C:P and N:P ratios for evergreen broadleaf forest and highly weathered Ultisols, and more pronounced temporal changes in soil C:N, N:P, and C:P ratios at low elevations. Our sensitivity analysis suggests that the temporal changes in soil stoichiometry resulted from elevated N deposition, rising atmospheric CO 2 concentration and regional warming. Our findings revealed that the responses of soil C‐N‐P and stoichiometry to long‐term global changes have occurred across the whole soil depth in subtropical China and the magnitudes of the changes in soil stoichiometry are dependent on vegetation types, soil types, and spatial climate variations.
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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 | 0.001 | 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".