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Monitoring and influencing factors of grassland livestock overload in Xinjiang from 1982 to 2020.
Ma, Lisha; Zheng, Jianghua; Pen, Jian; Xiao, Xianghua; Liu, Yujia; Liu, Liang; Han, Wanqiang; Li, Gangyong; Zhang, Jianli.
Afiliação
  • Ma L; College of Geography and Remote Sensing Science, Xinjiang University, Urumqi, China.
  • Zheng J; College of Geography and Remote Sensing Science, Xinjiang University, Urumqi, China.
  • Pen J; Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China.
  • Xiao X; Xinjiang Uygur Autonomous Region Grassland Station, Urumqi, China.
  • Liu Y; Xinjiang Uygur Autonomous Region Grassland Station, Urumqi, China.
  • Liu L; College of Geography and Remote Sensing Science, Xinjiang University, Urumqi, China.
  • Han W; College of Geography and Remote Sensing Science, Xinjiang University, Urumqi, China.
  • Li G; College of Geography and Remote Sensing Science, Xinjiang University, Urumqi, China.
  • Zhang J; Xinjiang Uygur Autonomous Region Grassland Station, Urumqi, China.
Front Plant Sci ; 15: 1340566, 2024.
Article em En | MEDLINE | ID: mdl-38601311
ABSTRACT
It is crucial to estimate the theoretical carrying capacity of grasslands in Xinjiang to attain a harmonious balance between grassland and livestock, thereby fostering sustainable development in the livestock industry. However, there has been a lack of quantitative assessments that consider long-term, multi-scale grass-livestock balance and its impacts in the region. This study utilized remote sensing and empirical models to assess the theoretical livestock carrying capacity of grasslands. The multi-scale spatiotemporal variations of the theoretical carrying capacity in Xinjiang from 1982 to 2020 were analyzed using the Sen and Mann-Kendall tests, as well as the Hurst index. The study also examined the county-level grass-livestock balance and inter-annual trends. Additionally, the study employed the geographic detector method to explore the influencing factors. The results showed that (1) The overall theoretical livestock carrying capacity showed an upward trend from 1982 to 2020; The spatial distribution gradually decreased from north to south and from east to west. In seasonal scale from large to small is growing season > summer > spring > autumn > winter; at the monthly scale, the strongest livestock carrying capacity is in July. The different grassland types from largest to smallest are meadow > alpine subalpine meadow > plain steppe > desert steppe > alpine subalpine steppe. In the future, the theoretical livestock carrying capacity of grassland will decrease. (2) From 1988 to 2020, the average grass-livestock balance index in Xinjiang was 2.61%, showing an overall increase. At the county level, the number of overloaded counties showed an overall increasing trend, rising from 46 in 1988 to 58 in 2020. (3) Both single and interaction factors of geographic detectors showed that annual precipitation, altitude and soil organic matter were the main drivers of spatiotemporal dynamics of grassland load in Xinjiang. The results of this study can provide scientific guidance and decision-making basis for achieving coordinated and sustainable development of grassland resources and animal husbandry in the region.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Plant Sci Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Plant Sci Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China