草原模式植物群落监测方法应用样例

模式植物群落是指能够反映某种植被分类单元基本特征,并可作为准确描述该植被类型"标准"的典型植物群落。草原模式植物群落监测是中国生物多样性监测与研究网络——草原/荒漠植物多样性监测网的核心内容,已初步确定了一套监测方法。本文应用这套方法分别建立了克氏针茅(Stipa krylovii)群系和百里香(Thymus mongolicus)群系模式植物群落监测固定样地,作为中国生物多样性监测与研究网络——草原/荒漠植物多样性监测网的样例。介绍了这两个模式植物群落监测样地选取与设置的过程、群落调查方法和数据分析结果。通过实际观测和案例分析,验证了"中国草原/荒漠植物多样性监测网模式植物群落监测方案"中监测方法的可行性,同时根据监测中出现的问题,提出了模式植物群落样地、监测频率和监测日期的选择原则,以及监测过程中的操作规范等,完善了模式植物群落监测内容、方法和指标体系的建议,为开展草原模式植物群落监测提供了可借鉴的实例与技术储备。

Stipa steppes in scantily explored regions of the tibetan Plateau:classification,community characteristics and climatic distribution patterns

Aims As a unique geographical unit of the earth,the tibetan Plateau is extensively covered by various Stipa communities.However,their vegetation features have not been reported systematically till now,especially in some scantily explored regions.In this study,we endeavor to reveal the community types,quantitative charac-teristics and climatic distribution patterns of Stipa steppes in these areas based on primary relevés obtained from fieldwork.Methods We collected a total of 223 plots in 79 study sites in the Changthang Plateau and the Yarlung Zangbo Valley,ranging from 79°E to 91°E.the categories of Stipa formations were identified according to the classification scheme in Vegetation of China and then verified by Nonmetric Multidimensional Scaling.We performed detrended correspondence analysis and detrended canonical correspondence analysis to hunt for the alteration of Stipa communities along the precipitation gradient.Quantitative characteristics including species richness,coverage,biomass as well as importance values(IV)of dominant species were calcu-lated and visualized,respectively.Important Findings Stipa steppes in scantily explored regions of the tibetan Plateau are classified into 11 formations but major formations are rather limited in number.Formation(form.)Stipa purpurea is the most widespread Stipa assemblages not only in scantily explored regions but also across the whole tibetan Plateau.the characteristics of Stipa com-munities,including coverage,species richness,productivity and IV of dominant species,demonstrate the features of typical alpine steppes on the tibetan Plateau.Precipitation proves to be the prime climatic factor controlling the distribution patterns of Stipa assemblages.Form.Stipa subsessiliflora var.basiplumosa and form.Stipa glareosa normally distribute in arid habitats,but rainfall for the former is of greater variance.Form.Stipa roborowskyi and form.Stipa capillacea favor moderately moist environment.Form.Stipa purpurea and form.Stipa roborowskyi can tolerate a fairly broad range of precipitation.

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

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 plotbased 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.