Abstract
Understanding the spatiotemporal patterns of the forage-livestock balance is imperative for regionally arranging animal husbandry production while ensuring sustainable grassland-ecosystem service use. The Xilin Gol steppe is an important native grassland resource in Inner Mongolia Autonomous Region, China. This study aimed to elucidate the dynamics of the forage-livestock balance in the Xilin Gol steppe during the period 2000–2015. We evaluated the forage production and corresponding livestock carrying capacity (LCC) in the growing seasons of 2000–2015 using remote sensing data and field surveys. The spatiotemporal patterns of the forage-livestock balance were then assessed at regional, city (including city, county and banner), and village scales using statistical and household survey data. The results showed that both forage production and LCC decreased in the Xilin Gol steppe from east to west. During the period 2000–2015, the regional average forage production and corresponding LCC fluctuated without following a distinct trend, but were consistent with the variations in precipitation. The forage-livestock balance varied with time, space, and scale. At the regional scale, steppes were overgrazed in the early 2000s, but a forage-livestock balance or even grazing potential was achieved in other years. At the city scale, approximately half of the region exhibited a "forage-livestock balance" since 2000. However, about half of the region still experienced overgrazing, which mainly located in the southwest sandy zones. Such changes may have been affected by the variations in grassland quality, forage production, compensation payment, and so on. We suggest a location-specific management scheme for grazing constraints, ecological compensation payment, and industry development to aid in harmonizing animal husbandry and environmental restoration, while promoting sustainable development goals by 2030.
基金项目
National Natural Science Foundation of China(41971130)
Sustainable Utilization of Desertified Lands in the Otindag Sandy Land, China" Program. We thank Dr. ZHANG Shuai, Dr. SAI Ke()
国家科技期刊平台
NSTL
万方数据