J Plant Ecol ›› 2019, Vol. 12 ›› Issue (6): 1009-1024.doi: 10.1093/jpe/rtz028

Previous Articles     Next Articles

Vegetation classification at the association level under the China Vegetation Classification System: an example of six Stipa steppe formations in China

Changcheng Liu1,2,*, Thomas R. Wentworth2, Xianguo Qiao1,3, Ke Guo1,3,* and Dongjie Hou1,3   

  1. 1State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
    2Department of Plant and Microbial Biology, North Carolina State University, Box 7612, Raleigh, NC 27695-7612, USA
    3University of Chinese Academy of Sciences, Beijing 100049, China
    *Correspondence address. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China. Email: greatwall01@ibcas.ac.cn (C.L.); guoke@ibcas.ac.cn (K.G.)
  • Received:2019-01-15 Revised:2019-03-20 Accepted:2019-05-09 Online:2019-10-30 Published:2019-12-01

Abstract:

Aims

The latest China Vegetation Classification System (China-VCS) for natural/semi-natural vegetation has eight hierarchical levels: Association < Association-group < Subformation < Formation < Formation-group < Vegetation-subtype < Vegetation-type < Vegetation-type-group. The classification is based on dominant species and their growth forms and has been completed at the formation level. The principal challenge today in Chinese vegetation classification is to develop the China-VCS at levels below the formation in a way that is consistent with current international standards. We explored the following question: how can existing vegetation plot data help develop the China-VCS and improve its compatibility with other international classification systems?

Methods

We compiled 401 plots having plant cover and/or aboveground biomass measurements collected in six Stipa steppe formations and divided them into those with cover data (299 plots) and/or biomass data (283 plots). We applied a combination of hierarchical clustering and ordination to partition the cover and biomass data sets into formations and constituent associations. We then used supervised noise clustering to improve the classification and to identify the core plots representing each association. Diagnostic species were also identified at both association and formation levels. Finally, we compared the classification results based on cover and biomass data sets and combined these results into a comprehensive classification framework for the six formations.

Important Findings

Our results using cover data were comparable with those using biomass data at both formation and association levels. Three Stipa formations were classified into associations based on cover data, two based on biomass data and one based on both biomass and cover data. Twenty-seven associations were defined and proposed within the six formations, using cover or biomass data as consistent classification sections (CCSs). Both dominant species in the dominant stratum and diagnostic species from multiple strata of the core plots were used to characterize vegetation types at both formation and association levels, improving the compatibility of our classification with the International Vegetation Classification. Temperature and precipitation were found to be important climatic factors determining the distribution pattern and species composition of Stipa-dominated vegetation. We propose a framework for plot-based vegetation classification in the China-VCS, using our work with Stipa-dominated steppe vegetation as an example. We applied the concept of CCS to make optimal use of available data representing both plant cover and biomass. This study offers a model for developing the China-VCS to the association level in a way that is consistent with current international standards.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] Shen Man;Wang Ming-xiu and Huang Min-ren. Advances in Research on Chilling-resistance Mechanisms of Plants[J]. Chin Bull Bot, 1997, 14(02): 1 -8 .
[2] Zhonghua Wang;*;Tingjie Yu. Research Advances in the Key Enzymes Involved in Rice Starch Quality Regulation[J]. Chin Bull Bot, 2008, 25(06): 741 -752 .
[3] . [J]. Chin Bull Bot, 2008, 25(02): 254 .
[4] Zhiqiang Xia;Yikun He;Shilai Bao;Kang Chong. Molecular mechanism of plant flowering regulated by histone methylation[J]. Chin Bull Bot, 2007, 24(03): 275 -283 .
[5] GAO Guo-Qing CHU Cheng-Cai LIU Xiao-Qiang LI Yang-Rui. Current Progress on WRKY Superfamily of Plant Transcription Factors[J]. Chin Bull Bot, 2005, 22(01): 11 -18 .
[6] Rongfeng Cui;Zheng Meng. Functional Conservation and Diversity of Floral Homeotic MADS-box Genes in Angiosperms[J]. Chin Bull Bot, 2007, 24(01): 31 -41 .
[7] . [J]. Chin Bull Bot, 1998, 15(专辑): 1 -6 .
[8] WANG Lin-Xiang WANG Shi-Heng. Simulation and Calculation of the Penetration Depth and Concentration Distribution for Titanium ions with Low Energy Implanted into the Dry Cotton seed[J]. Chin Bull Bot, 2005, 22(06): 697 -702 .
[9] DING Zi-Mian WANG Yu-Ping HAO Xue-Jing SUN Qun SUN Bao-Qi ZHANG Xu. Studies of the Inflorescence Differentiation Process in Bupleurum chinese[J]. Chin Bull Bot, 2005, 22(06): 692 -696 .
[10] Tao Jun-rong. Indicated to Palaeolimate fossils plants palibinia[J]. Chin Bull Bot, 1983, 1(01): 50 -52 .