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Patterns and abiotic drivers of soil organic carbon in perennial tea (Camellia sinensis L.) plantation system of China.
Yang, Xiangde; Yi, Xiaoyun; Ni, Kang; Zhang, Qunfeng; Shi, Yuanzhi; Chen, Linbo; Zhao, Yuanyan; Zhang, Yongli; Ma, Qingxu; Cai, Yanjiang; Ma, Lifeng; Ruan, Jianyun.
Afiliación
  • Yang X; Tea Research Institute, Chinese Academy of Agriculture Sciences, Key Laboratory of Biology, Genetics and Breeding of Special Economic Animals and Plants, Ministry of Agriculture and Rural Affairs, Hangzhou, 310008, China.
  • Yi X; Tea Research Institute, Chinese Academy of Agriculture Sciences, Key Laboratory of Biology, Genetics and Breeding of Special Economic Animals and Plants, Ministry of Agriculture and Rural Affairs, Hangzhou, 310008, China.
  • Ni K; Tea Research Institute, Chinese Academy of Agriculture Sciences, Key Laboratory of Biology, Genetics and Breeding of Special Economic Animals and Plants, Ministry of Agriculture and Rural Affairs, Hangzhou, 310008, China.
  • Zhang Q; Tea Research Institute, Chinese Academy of Agriculture Sciences, Key Laboratory of Biology, Genetics and Breeding of Special Economic Animals and Plants, Ministry of Agriculture and Rural Affairs, Hangzhou, 310008, China.
  • Shi Y; Tea Research Institute, Chinese Academy of Agriculture Sciences, Key Laboratory of Biology, Genetics and Breeding of Special Economic Animals and Plants, Ministry of Agriculture and Rural Affairs, Hangzhou, 310008, China.
  • Chen L; Tea Research Institute, Yunnan Academy of Agricultural Sciences, Yunnan Provincial Key Laboratory of Tea Science, 2 Jingnan Road, Menghai, Yunnan, 666201, China.
  • Zhao Y; Pu'er Tea Science Research Institute, Pu'er, 665000, China.
  • Zhang Y; Tea Research Institute, Chinese Academy of Agriculture Sciences, Key Laboratory of Biology, Genetics and Breeding of Special Economic Animals and Plants, Ministry of Agriculture and Rural Affairs, Hangzhou, 310008, China.
  • Ma Q; Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
  • Cai Y; State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou, 311300, China.
  • Ma L; Tea Research Institute, Chinese Academy of Agriculture Sciences, Key Laboratory of Biology, Genetics and Breeding of Special Economic Animals and Plants, Ministry of Agriculture and Rural Affairs, Hangzhou, 310008, China. Electronic address: malf@mail.tricaas.com.
  • Ruan J; Tea Research Institute, Chinese Academy of Agriculture Sciences, Key Laboratory of Biology, Genetics and Breeding of Special Economic Animals and Plants, Ministry of Agriculture and Rural Affairs, Hangzhou, 310008, China. Electronic address: jruan@mail.tricaas.com.
Environ Res ; 237(Pt 1): 116925, 2023 Nov 15.
Article en En | MEDLINE | ID: mdl-37598641
Understanding soil organic carbon (SOC), the largest carbon (C) pool of a terrestrial ecosystem, is essential for mitigating climate change. Currently, the spatial patterns and drivers of SOC in the plantations of tea, a perennial leaf crop, remain unclear. Therefore, the present study surveyed SOC across the main tea-producing areas of China, which is the largest tea producer in the world. We analyzed the soil samples from tea plantations under different scenarios, such as provinces, regions [southwest China (SW), south China (SC), south Yangtze (SY), and north Yangtze (NY)], climatic zones (temperate, subtropical, and tropical), and cultivars [large-leaf (LL) and middle or small-leaf (ML) cultivars]. Preliminary analysis revealed that most tea-producing areas (45%) had SOC content ranging from 10 to 20 g kg-1. The highest SOC was recorded for Yunnan among the various provinces, the SW tea-producing area among the four regions, the tropical region among the different climatic zones, and the areas with LL cultivars compared to those with ML cultivars. Further Pearson correlation analysis demonstrated significant associations between SOC and soil variables and random forest modeling (RF) identified that total nitrogen (TN) and available aluminum [Ava(Al)] of soil explained the maximum differences in SOC. Besides, a large indirect effect of geography (latitude and altitude) on SOC was detected through partial least squares path modeling (PLS-PM) analysis. Thus, the study revealed a high spatial heterogeneity in SOC across the major tea-producing areas of China. The findings also serve as a basis for planning fertilization strategies and C sequestration policies for tea plantations.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Res Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Res Año: 2023 Tipo del documento: Article País de afiliación: China