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Spatial-temporal Patterns And Driving Factors Of Grassland Carrying Capacity In Northern China

Posted on:2024-08-13Degree:MasterType:Thesis
Country:ChinaCandidate:W J SongFull Text:PDF
GTID:2543307139486724Subject:Grass science
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Northern grassland is an important part of the Eurasia grassland,and the main part of natural grassland in China,which play as an important ecological security barrier in the north.For a long time,grasslands not only provide high-quality forage for livestock production,but also provide important ecological functions such as water conservation,climate regulation,biodiversity maintenance,carbon sequestration.Grazing is the most direct way to utilize these natural grassland.Currently,long-term overgrazing is the most important factor leading to grassland degradation.Therefore,determining reasonable grazing intensity and understanding the spatial and temporal patterns of grassland carrying capacity and its driving factors are conducive to promoting compensatory plant growth and the maintenance of grassland productivity and stability.Based on the meta-analysis118 grazing studies,the remote sensing data,and the statistical data to clarify the trends of spatial and temporal patterns of grassland carrying capacity in northern China,as well as the key biotic and abiotic factors affecting the carrying capacity of grassland,and to provide a basic theoretical basis for realizing the sustainable development of grassland husbandry and the scientific allocation of grassland ecological and production functions.The main findings and conclusions are as follows:(1)The plant communities of northern grasslands in China were generally in a state of under-compensated growth,and the compensatory growth of plant above-ground plant parts was maintained at the expense of their below-ground biomass.The reasonable carrying capacities(sheep units/ha,SU hm-2)as follows:5.1 SU hm-2 for dry and hot savanna-like grassland,4.3 SU hm-2 for tropical shrubby grassland,4 SU hm-2 for warm grassland,3.8 SU hm-2 for hot grassland,3.6 SU hm-2 for shrubby grassland,2.7 SU hm-2for temperate meadow steppe,2.4 SU hm-2 for montane meadow,1.8 SU hm-2 for lowland meadow,1.5 SU hm-2 for alpine meadow,1.4 SU hm-2 for bog,1.1 SU hm-2 for temperate steppe,0.5 SU hm-2 for alpine meadow steppe,0.2 SU hm-2 for alpine steppe,0.2 SU hm-2 for temperate desert steppe,0.1 SU hm-2 for temperate steppe desert,0.07 SU hm-2 for alpine desert steppe,and 0.07 SU hm-2 for temperate desert.(2)In general,the carrying capacity of northern grasslands showed an increasing trend during 2000-2020.At the 250 m raster scale,the carrying capacity of grasslands showed an divergent spatial pattern with the decreasing trend from east to west and from south to north.At the regional scale,the absolute value of compensatory growth of plant communities increased with mean annual precipitation and plant species richness,and the specific response characteristics varied with grassland type.(3)During 2000-2020,the multi-year average carrying index(actual carrying capacity/reasonable carrying capacity)of pastoral and semi-pastoral counties was 1.87 and1.78,respectively,both of which were in a serious overloading state.Overall,among the268 pastoral and semi-pastoral counties,196 counties were overloaded and only 72counties were not overloaded.The average multi-year forage demand gap in pastoral and semi-pastoral counties in China was 50 million tons/year.Therefore,in practice,the ecological and production functions of grasslands should be reasonably configured according to the suitable carrying capacity of different regions and different grassland types,changes in biotic and environmental factors,and the current status and degree of grassland degradation,so as to accelerate the restoration and rehabilitation of degraded grasslands and achieve a win-win situation for the sustainable use of grassland resources and regional ecological security.
Keywords/Search Tags:Grassland carrying capacity, Plant compensatory growth, Forage consumption rate, Spatial-temporal pattern, Carrying index, Optimization of production functions and ecological functions
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