A new net primary productivity model and new management strategy of grassland classification based on CSCS in China
Huilong Lin A B , Haili Ma A , Charles Nyandwi A , Qisheng Feng A and Tiangang Liang A
+ Author Affiliations
- Author Affiliations
A State Key Laboratory of Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs; College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China.
B Corresponding author. Email: linhuilong@lzu.edu.cn
The Rangeland Journal 43(6) 285-295 https://doi.org/10.1071/RJ20073
Submitted: 19 July 2020 Accepted: 3 November 2020 Published: 16 April 2021
Abstract
The discovery of grassland field, form and biomass in China was central to the sustainable development of grassland. In this study, the realistic spatial distribution patterns of grasslands were clarified through the combination of the International Geosphere-Biosphere Program (IGBP) and the Comprehensive and Sequential Classification System (CSCS). An optimal net primary productivity (NPP) model suitable for Chinese grasslands was introduced by integrating the classification indices-based model (CIM) with the Normalised Difference Vegetation Index (NDVI), and comparing it with the standard classical model (Miami, Schuur, CIM, CASA model). Using the optimal model as the algorithm basis, the net primary production spatial pattern of grassland in China was determined. The results showed that: (1) the total area of grassland was ~374.3 × 104 km2 in 2018, mainly distributed in north-western China. Among the grassland super-class groups, Tundra and alpine steppe were largest, and Warm desert smallest; (2) the optimal modified CIM had the highest prediction efficiency, and the overall accuracy was higher than the standard classical model (Miami, Schuur, CIM, CASA model). It achieved the accurate calculation of grassland NPP in China; (3) different grassland super-class groups had different carbon fixation efficiency per unit area, resulting in huge differences in total NPP. Among the various grassland super-class groups, the temperate humid grassland, steppe, tundra and alpine steppe had high conversion efficiency per unit area of NPP, whereas that for warm desert and the savanna was low. The total NPP was 388.04 × 1012 g C/year in the study area in 2018. The results provide a basis for the rational arrangement of grassland ecological and productive functions, and are significant for developing a new strategy of grassland classification management in China.
Keywords: biomass spatial pattern, China, realistic spatial distribution patterns of grasslands, grassland ecological function, grassland productive function, NPP, simulation, rational management.
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