Complex effects of different types of acid rain on root growth of Quercus acutissima and Cunninghamia lanceolata saplings
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background Soil acidification caused by acid rain (AR) can damage plant roots, which in turn negatively impacts plant health. In response to changing AR types, research efforts to elucidate their specific impacts on plants have become intense. Methods For this study, we investigated the effects of simulated sulfuric, nitric, and mixed AR on the root systems of Quercus acutissima Carr. and Cunninghamia lanceolata (Lamb.) Hook. under different acidity levels. Results As the AR S/N ratio and pH decreased, the height growth rate (HGR), basal diameter growth rate (DGR), total root length (TRL ) and total root surface area (TRS) of C. lanceolata decreased, whereas the TRL and TRS of Q. acutissima remained the same. When the NO 3 − concentration in AR was increased, the root activity, superoxide dismutase (SOD) and catalase (CAT) activities of C. lanceolata roots revealed a downward trend; however, the root activity of Q. acutissima and the peroxidase (POD) activity of C. lanceolata roots revealed an upward trend. Further, redundant analysis and structural equation models indicated that AR pH had a greater impact on the HGR of Q. acutissima than that of C. lanceolata , while the impact of the AR S/N ratio on C. lanceolata growth rates was greater than that of Q. acutissima . Conclusions Our results suggested that the root systems of different tree species had variable responses to AR, and the AR S/N ratio was an important factor affecting plant root growth. This might facilitate new strategies for the cultivation and protection of plantations in the future.
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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 | 0.001 |
| 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 it