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草业学报 ›› 2021, Vol. 30 ›› Issue (10): 201-213.DOI: 10.11686/cyxb2020362

• 综合评述 • 上一篇    

草地综合顺序分类法研究新热点:2008-2020年回顾与展望

林慧龙(), 范迪, 冯琦胜, 梁天刚   

  1. 中国草业发展战略研究中心,草地农业生态系统国家重点实验室,农业农村部草牧业创新重点实验室,兰州大学草地农业科技学院,甘肃 兰州 730000
  • 收稿日期:2020-07-28 修回日期:2020-11-16 出版日期:2021-09-16 发布日期:2021-09-16
  • 通讯作者: 林慧龙
  • 作者简介:林慧龙(1965-),男,辽宁沈阳人,教授,博士。Corresponding author. E-mail: linhuilong@lzu.edu.cn
  • 基金资助:
    国家自科基金(32171680);甘肃省林业和草原局年度省级人才发展专项(lzujbky-2021-kb13);兰州大学中央高校基本科研业务费专项资金(lzujbky-2021-kb13)

New focus for the study of the Comprehensive Sequential Classification System for grassland: A review from 2008 to 2020 and prospects for future research

Hui-long LIN(), Di FAN, Qi-sheng FENG, Tian-gang LIANG   

  1. Chinese Center for Strategic Research of Grassland Agriculture Development,State Key Laboratory of Grassland Agro-ecosystems,Key Laboratory of Forage and Livestock Industry Innovation,College of Pastoral Agriculture Science and Technology,Lanzhou University,Lanzhou 730000,China
  • Received:2020-07-28 Revised:2020-11-16 Online:2021-09-16 Published:2021-09-16
  • Contact: Hui-long LIN

摘要:

草地综合顺序分类法(comprehensive and sequential classification system of grassland,CSCS)经过60多年的不断探索和完善,已成为具有中国知识产权的唯一的可数量化的草地分类系统。特别是2008年任继周等在Rangeland Journal专门著文推介CSCS,开启了CSCS在国内外研究的新高潮。本研究以CSCS作为关键词从Wed of Science及中国知网等科技论文数据库检索得2008-2020年发表的中英文文献分别为48和29篇。通过系统梳理,获得最新的研究成果如下:1)将CSCS与国际公认的Holdridge Life Zone、BIOME4分类体系在全球尺度上进行对比验证,论证了CSCS在草地类型划分方面的突出优势;2)使用数字高程模型数据的坡度、坡向和坡度变化率等因子修正传统空间插值法,引入海拔、坡度等变量的多元回归和残差分析插值法,有效解决高海拔和复杂地形所带来的气候数据插值误差,提高了CSCS的模拟精度,也为深入广泛的应用提供了方法论依据;3)基于CSCS发生学特征,研究草地对全球气候变化的响应。现已在区域、全国及全球尺度上研究草地生态系统对全球气候变化的响应,为进一步的草地精细化分类管理和相关政策制定提供了数据基础;4)热量状况和水分条件的组合是草原现象和过程的本质的因素,以CSCS为理论框架,用分类指标为参数构建草地第一性生产力(NPP)分类指数模型,该模型不仅揭示草地类型与其净第一性生产力的内在联系,也为进一步研究地带性草地类型的生产潜力、草地净第一性生产力的区域分布和全球分布提供了可能。在区域、全国和全球尺度上的比较验证可知,基于CSCS的草地NPP模型已发展成为草地生态系统第一性生产力评估及碳汇计算的新工具。未来CSCS研究亟待开展的工作主要有:1)完善CSCS亚类及型的定量分类体系;2)通过开发CSCS方法在草地营养载畜量和生态服务价值评估等方面的应用,完善基于CSCS框架的草地精细化管理。

关键词: 草地综合顺序分类法, 空间插值法, 潜在植被, 植被净初级生产力, 全球气候变化

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