Abstract
Grassland biomass is an essential part of the regional carbon cycle. Rapid and accurate estimation of grassland biomass is a hot topic in research on grassland ecosystems. This study was based on field-measured biomass data and satellite remote sensing data from the Moderate resolution imaging spectroradiometer (MODIS). A generalized linear model (GLM) was used to analyze the aboveground biomass (AGB), dynamic changes, and relevance of climatic factors of the typical/desert steppe in Inner Mongolia during the growing seasons from May 2009 to October 2015. The results showed that: (1) The logarithmic function model with the ratio vegetation index (RVI) as the independent variable worked best for the typical steppe area in Inner Mongolia, while the power function model with the normalized differential vegetation index (NDVI) as the independent variable worked best for the desert steppe area. The R2 values at a spatial resolution of 250 m were higher than those at a spatial resolution 500 m. (2) From 2009 to 2015, the highest values of AGB in the typical steppe and desert steppe of Inner Mongolia both appeared in 2012, and were 41.9 Tg and 7.0 Tg, respectively. The lowest values were 30.7 Tg and 5.8 Tg, respectively, in 2009. (3) The overall spatial distribution of AGB decreased from northeast to southwest. It also changed considerably over time. From May to August, AGB at the same longitude increased from south to north with seasonal variations; from August to October, it increased from north to south. (4) A variation partitioning analysis showed that in both the typical steppe and desert steppe, the combined effect of precipitation and temperature contributed the most to the aboveground biomass. The individual effect of temperature contributed more than precipitation in the typical steppe, while the individual effect of precipitation contributed more in the desert steppe. Thus, the hydrothermal dynamic hypothesis was used to explain this pattern. This study provides support for grassland husbandry management and carbon storage assessment in Inner Mongolia.
Highlights
Grassland is one of the most abundantly distributed terrestrial ecosystems on the earth [1,2]
In the mid-western part of Inner Mongolia, the typical steppe and desert steppe areas are sensitive to global changes due to the fragility and volatility of their climatic conditions and the complex social factors associated with human activities [12]
Regression analysis showed that the logarithmic function model with ratio vegetation index (RVI) of the typical steppe area as the independent variable had the highest accuracy; the power function model with normalized differential vegetation index (NDVI) of the desert steppe area as the independent variable had the highest accuracy
Summary
Grassland is one of the most abundantly distributed terrestrial ecosystems on the earth [1,2]. Grassland biomass represents primary productivity, determines the livestock capacity of the pasture, and is the main carbon pool [3,4,5]. An accurate understanding of grassland’s biomass and its changing patterns is important for the carbon cycle of a study area and the proper use of grassland resources [6,7]. In the mid-western part of Inner Mongolia, the typical steppe and desert steppe areas are sensitive to global changes due to the fragility and volatility of their climatic conditions and the complex social factors associated with human activities [12]. Many researchers around the world have made tremendous efforts to simulate Inner Mongolia grassland and national-scale grassland biomass [12,13,14,15,16]. Due to limitations in observational data and research methods, there is still great uncertainty in the estimation of biomass
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