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[Critical influencing factors on vegetation productivity in sandy land of the Northwestern Liaoning Province,China]. / 辽西北沙化土地植被生产力关键影响因素.
Liu, Hong-Shun; Bu, Ren-Cang; Wang, Zheng-Wen; Chang, Yu; Xiong, Zai-Ping; Qi, Li; Gao, Yue.
Afiliación
  • Liu HS; Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China.
  • Bu RC; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Wang ZW; Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China.
  • Chang Y; Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China.
  • Xiong ZP; Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China.
  • Qi L; Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China.
  • Gao Y; Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China.
Ying Yong Sheng Tai Xue Bao ; 35(1): 49-54, 2024 Jan.
Article en Zh | MEDLINE | ID: mdl-38511439
ABSTRACT
To reveal the key factors influencing vegetation productivity in sandy lands, we conducted a comprehensive analysis of vegetation productivity on regional scale, pixel scale, and plot scale of the sandy lands in northwes-tern Liaoning Province, based on soil physicochemical data, topographical data, climate data, and the intrinsic characteristics of vegetation. On the regional scale, we established a random forest model to explore the impact of topographical factors, climate factors, and vegetation characteristics on vegetation productivity. On the pixel scale, we performed a correlation analysis between vegetation cover and climate factors. On the plot scale, we combined the physicochemical properties of 234 soil samples with topographical factors and vegetation characteristics, and utilized the random forest model to calculate the importance values of each factor. The results showed that soil nutrients could explain 24.8% of the spatial variation in net primary productivity when other factors were excluded. When introducing topographical factors into the model, the model could explain 40% variation of net primary productivity. When further incorporating fractional vegetation coverage and leaf area index into the model, the model could explain 72.8% variation of net primary productivity. Our findings suggested that fractional vegetation coverage and leaf area index were the most influential factors affecting vegetation productivity in this area. Topographical factors ranked second, followed by climate factors, which had a relatively small impact.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Ecosistema / Arena País/Región como asunto: Asia Idioma: Zh Revista: Ying Yong Sheng Tai Xue Bao / Yingyong shengtai xuebao Asunto de la revista: SAUDE AMBIENTAL Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Ecosistema / Arena País/Región como asunto: Asia Idioma: Zh Revista: Ying Yong Sheng Tai Xue Bao / Yingyong shengtai xuebao Asunto de la revista: SAUDE AMBIENTAL Año: 2024 Tipo del documento: Article