Abstract:

The Comprehensive Sequential Classification System for grassland （CSCS） has become the only quantifiable grassland classification system with Chinese intellectual property rights after more than 60 years of continuous development and improvement. Notably， in 2008， Ren et al publicised the CSCS in the Rangeland Journal， stimulating a new upsurge of CSCS research in China and abroad. In this paper， we report a literature review using CSCS as the keyword. We retrieved 48 Chinese papers from the China national knowledge internet and 29 English papers from Web of Science， published from 2008 to 2020. From this systematic review， the conclusions are as follows： 1） Comparing CSCS with two internationally recognized classification systems， Holdridge Life Zone and BIOME4 on a global scale， it emerges that CSCS has outstanding advantages in grassland classification. 2） A digital elevation data model （DEM） taking account of slope gradient， slope direction， rate of slope change， and other similar factors has been constructed to modify traditional spatial interpolation methods， and introduce altitude， slope and other variables into multiple regression and residual analysis interpolation. This has efficiently solved climate data interpolation errors arising from high altitude and complex terrain， making CSCS classification more accurate and providing a methodological basis for extensive application. 3） Because of the structural characteristics of CSCS， it provides a framework and a new technique to study grassland response to global climate change. Responses of grassland ecosystems to global climate change have been studied at regional， national and global scales， providing the base data for further precise grassland management and related policymaking. 4） The combination of heat and moisture conditions at a locality is the most fundamental factor determining grassland phenomena and processes. In the theoretical framework of the CSCS， a classification index model has been built by using classification indices as parameters. This model not only reveals the inner connection between grassland types and their net primary productivity （NPP）， but also makes it possible to further study the production potential of zonal grassland types and regional and global distributions of grassland NPP. After comparative validation at regional， national and global levels， the grassland NPP model based on the CSCS has become a new tool for primary productivity assessment and carbon sink calculation of grassland ecosystems. In the future， the following tasks are urgently needed： 1） To improve the quantitative classification system of CSCS subclasses and types； 2） To improve the precision of grassland management based on the CSCS through development of CSCS protocols defining grassland nutrient carrying capacity， and facilitating ecological service value assessment， and other relevant tools.

Key words: Comprehensive Sequential Classification System for grassland, spatial interpolation, potential vegetation, net primary productivity of vegetation, global climate change