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Record W4387576102 · doi:10.1002/ldr.4943

Converting natural forests to tea plantations reduced soil phosphorus sorption capacity in subtropical China

2023· article· en· W4387576102 on OpenAlex
Xinlin Wang, Haikuo Zhang, Hongyang Sun, Scott X. Chang, Yang Lin, Yanjiang Cai

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLand Degradation and Development · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsUniversity of Alberta
FundersNational Natural Science Foundation of China
KeywordsSorptionSoil waterLeaching (pedology)Environmental scienceAgronomyEnvironmental chemistryFertilizerCation-exchange capacityChemistrySoil acidificationPhosphorusSoil fertilitySoil pHSoil scienceBiologyAdsorption

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.223
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it