Improvement and Application of Key Pasture Theory for the Evaluation of Forage–Livestock Balance in the Seasonal Grazing Regions of China’s Alpine Desert Grasslands

Hui Liu,Yu Liu,Wang Wen,Xiaodi Liu,Xiaoyu Song,Zhiqiang Hu,Lin Qin

doi:10.3390/su12176794

Abstract

The calculation of theoretical carrying capacity (TCC) is one of the most fundamental tasks for the evaluation of the forage–livestock balance on grassland pastures. At present, the main methods for calculating TCC are the traditional theory (TT) and key pasture theory (KPT), but they both have obvious limitations in practical applications for the seasonal grazing regions in the alpine desert grasslands of China. In this study, the pastures in Wulan County (PWC) were selected as the research area. The unique features of the research area as well as the faulty applications of TT and KPT were fully analyzed, and then a new method named dynamic key pasture theory (DKPT) was established for calculating TCC by improving KPT with the introduction of the two dynamic factors of the livestock slaughter rate (α) and coefficient of grassland productivity (β). TT, KPT and DKPT were respectively used to calculate the TCC of the PWC under different precipitation scenarios. The forage–livestock balance in the PWC determined using DKPT was assessed by the forage–livestock balance index (FLBI). The results showed that the natural processes of grassland supply and livestock demand were significantly imbalanced in time and space and formed a dynamic cycle with four subprocesses, which was the supporting basis of DKPT; DKPT effectively improved the rationality of TCC and offered greater guidance for the evaluation of the forage–livestock balance in the seasonal grazing regions of China’s alpine desert grasslands. In the PWC, the TCCs of different pastures calculated by DKPT were clearly different from those calculated by TT and KPT; the areas of the pastures divided were extremely imbalanced, with a huge surplus of more than 50% in cool-season pastures; in the representative year of 2016, the pastures in the Xisai Basin were underloaded (FLBI = −35.19%) on the whole, while the pastures in the Chaka Basin were overloaded (FLBI = 24.34%).

Highlights

Grasslands are among the major ecosystems in the world, providing various ecosystem and social service functions [1,2,3,4]
Compared with the results from the traditional theory (TT) and key pasture theory (KPT) methods, the theoretical carrying capacity (TCC) of the warm-season pastures calculated by the dynamic key pasture theory (DKPT) method were 7.07–8.71% higher, whereas the TCCs of the cool-season pastures decreased by nearly half (40.78–44.23%); as a consequence, the TCCs of the whole year calculated by the DKPT method decreased by 15.83–19.25% compared with the corresponding values determined by the TT or KPT methods
For the seasonal grazing regions in the alpine desert grasslands of China, the grassland productivity and TCCs of pastures were significantly affected by the phonological period and regional precipitation as well as the dynamic changes in livestock numbers

Summary

Introduction

Grasslands are among the major ecosystems in the world, providing various ecosystem and social service functions [1,2,3,4]. Animal husbandry is the mainstay of economic and social development in grassland regions, and maintaining the forage–livestock balance is crucial to the sustainable development of grassland animal husbandry [5,6,7,8,9,10,11]. The forage–livestock balance means that, in order to maintain the beneficial cycles of the grassland ecosystem, the total amount of forage provided by the grasslands, as well as other sources, should be in dynamic balance with the amount of forage needed to raise the livestock [12,13]. The estimate of the forage–livestock balance based on TT is nearly static [19,20], providing little guidance of significance for the operation and management of animal husbandry and the sustainability of grassland ecosystems, and even proved to be counterproductive,

Methods

Results

Discussion

Conclusion