Dynamic Monitoring And Prediction Of Aboveground Biomass Of Natural Grassland

In recent years, the development of natural grassland ecosystem has draw great attention, meanwhile, the health condition of grassland ecosystem and the balance between livestock and forage are also the focus of research. Based on EVI time series data from 2000 to 2009, the growth dynamics of natural grassland vegetation and aboveground biomass prediction method of the natural grassland in Xiahe County of Gansu Province were studied by using 3S technologies and grassland vegetation dynamic monitoring methods, and function of compensatory growth of vegetation in natural grassland was sidcussed as well.The major results are as follows:1) Based on the dynamic monitoring of natural grassland in Xiahe County, the variation patterns of vegetation growth and forage intake of moutaine meadow and alpine meadow under zero grazing condition were established. The research results could provide support to the further research on the methods for dynamic prediction of aboveground biomass of natural grasslands.2) Due to the vast area and the wide distribution range of natural grassland vegetation, its compensatory growth status of vegetation can not be quantitatively estimated at a limited time duration, but is a gradually changing process which interacts with water and heat conditions, vegetation types, time, forage intake, and many other environmental factors.3) As a whole system, the compensatory growth status of vegetation will show over-compensation from the beginning of grazing at any grazing intensity, and the time to show under-compensation is depend on grazing intensity and environmental factors.4) Vegetation growth status of of mountaine meadow and alpine meadow in Xiahe County of Gansu Province was relatively similar in same year,the average status in recent 10 years showed that the forage production in 2002, 2005 and 2009 was sufficient, and that in 2004, 2006, 2007 and 2008 was average, and it was deficient in 2000, 2001 and 2003.5) Because of the problem of NDVI saturation, EVI is more suitable for grassland monitoring in the high-density vegetation areas compared to the NDVI.6) Based on the time series of aboveground biomass of mountaine meadow and alpine meadow in Xiahe County, the aboveground biomass in a previous time duration was use to estimate the biomass in followed time duration. And the actual data under average grazing density in 2009 were used to justify the prediction accuracy. The prediction accuracy for mountaine meadow and alpine meadow was 92.09% and 88.82% respectively. The T-test results indicated that the correlation between actual data and estimated data was significant (mountaine meadow: r=0.988**, P<0.01; alpine meadow: r=0.956**, P<0.01). It could be concluded that the prediction method is feasible.