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Spatiotemporal tradeoffs and synergies in vegetation vitality and poverty transition in rocky desertification area.
Zhao, Sen; Wu, Xiuqin; Zhou, Jinxing; Pereira, Paulo.
Afiliação
  • Zhao S; School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; Key Laboratory of Soil and Water Conservation of State Forestry Administration, Beijing Forestry University, Beijing 100083, China; Jianshui Research Station, School of Soil and Water Conservation, Beijing For
  • Wu X; School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; Key Laboratory of Soil and Water Conservation of State Forestry Administration, Beijing Forestry University, Beijing 100083, China; Jianshui Research Station, School of Soil and Water Conservation, Beijing For
  • Zhou J; School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; Key Laboratory of Soil and Water Conservation of State Forestry Administration, Beijing Forestry University, Beijing 100083, China; Jianshui Research Station, School of Soil and Water Conservation, Beijing For
  • Pereira P; Environment Management Laboratory, Mykolas Romeris University, Ateities g. 20, LT-08303 Vilnius, Lithuania. Electronic address: pereiraub@gmail.com.
Sci Total Environ ; 752: 141770, 2021 Jan 15.
Article em En | MEDLINE | ID: mdl-32889264
Vegetation recovery and poverty alleviation are critical problems in the karst national designed poor counties (NPDC) in southwest China. However, little information is available about the relationship between poverty and vegetation dynamics in these areas. In this study, we used remote sensing and statistical datasets from 2000 to 2015 to identify the relations between vegetation dynamics and poverty among the NPDC in southwest rocky desertification areas. We estimated the vegetation dynamics using the Normalized Difference Vegetation Index and poverty with the rural per capita net income. Local indicator of spatial association and the space-time transition type of poverty were applied to identify spatial patterns of the poverty spatial distribution relationship and transition. Also, poverty, natural and ecological governance factors were assessed using the Geo-detector method to uncover the driving factors of karst vegetation. The results showed that vegetation increased significantly (p < 0.05) in karst NPDC (82.82%) and rocky desertification control counties (78.77%). The karst NPDC was significantly clustered. The hot spots of rural per capita net income changed from west and north (2000) to only north (2015) and cold spots changed from east and south (2000) to only south (2015). The rural per capita net income spatiotemporal transition was higher in 2000 than in 2015. We found a weak synergy between vegetation change and poverty type transition in 42.86% of the browning counties, 45.45% in the slowly greening counties, and 43.65% in stable greening counties. However, 57.50% of counties in the quick greening counties showed a tradeoff relationship with the poverty type transition. The rocky desertification rate and ecological engineering measures affected vegetation dynamics importantly. The results will help decision-makers to understand the interdependence between vegetation and poverty. This will contribute to better policies formulation to tackle poverty in the karst rocky desertification area.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article