Converting natural forests to tea plantations reduced soil phosphorus sorption capacity in subtropical China
Bibliographic record
Abstract
Abstract Converting natural forests to agricultural lands has been widespread globally due to increasing population and the demand for food. Phosphorus (P) is often applied to agricultural lands in excessive amounts which can saturate the natural P sorption capacity of the soil, leading to P leaching and subsequent off‐site water eutrophication. We studied the effect of land‐use conversion from natural forests to tea plantations on total soil P, P fractions, and P sorption capacity in subtropical China. Compared to natural forests, total soil P concentrations increased significantly in both 0–20 and 20–40 cm depths in tea plantations, indicative of the accumulation of P fertilizer. The increases in total soil P were primarily found in NaOH‐extractable inorganic P and residual P fractions in both depths, suggesting that P fertilizer was sorbed and occluded into more stable forms due to the high abundance of sorbents (i.e., iron [Fe], aluminum [Al] minerals, and clay). Across all soil samples, oxalate‐extractable Fe was the best predictor of soil maximum P sorption capacity (r = 0.94, p < 0.001). Surprisingly, the conversion from natural forests to tea plantations decreased both oxalate‐extractable Fe concentration and soil maximum P sorption capacity, hereby increasing the degree of P saturation in soils. Depletion of P sorbents (i.e., soil amorphous Fe) is likely a consequence of Fe removal through tea production and soil erosion, indicating soil degradation. Plantation soils have also shown other signs of degradation including the loss of nutrients (e.g., total soil nitrogen and oxalate‐extractable calcium) and soil organic matter. Our results demonstrate that the conversion of natural forests to tea plantations reduced the ability of the soil to sorb P by both saturating the natural P sorption capacity and depleting P sorbents. Soil degradation resulting from land‐use conversion has increased the environmental risk of P leaching loss, emphasizing the need for improved P fertilization management.
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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 | 0.000 |
| 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) | 0.001 | 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".