scholarly journals A revised scheme of vegetation classification system of China

2020 ◽  
Vol 44 (2) ◽  
pp. 111-127 ◽  
Author(s):  
Ke GUO ◽  
Jing-Yun FANG ◽  
Guo-Hong WANG ◽  
Zhi-Yao TANG ◽  
Zong-Qiang XIE ◽  
...  
Keyword(s):  
Classification System ◽  
Vegetation Classification

An Irish national vegetation classification system for aquatic river macrophytes

2018 ◽  
Vol 21 (2) ◽  
pp. 322-340 ◽  
Author(s):  
Lynda Weekes ◽  
Zygmunt Kącki ◽  
Úna FitzPatrick ◽  
Fiona Kelly ◽  
Ronan Matson ◽  
...  
Keyword(s):  
Classification System ◽  
Vegetation Classification ◽  
National Vegetation Classification

scholarly journals A novel biome concept and classification system based on bioclimate and vegetation – a Neotropical assay

2021 ◽  
Vol 2 ◽  
pp. 159-175
Author(s):  
Gonzalo Navarro ◽  
José Antonio Molina
Keyword(s):  
Classification System ◽  
Vegetation Structure ◽  
Large Scale ◽  
Hierarchical Classification ◽  
Vegetation Classification ◽  
Classification Systems ◽  
Tropical Ecosystems ◽  
Bioclimatic Variables ◽  
Ecological Functionality

The knowledge of biomes as large-scale ecosystem units has benefited from advances in the ecological and evolutionary sciences. Despite this, a universal biome classification system that also allows a standardized nomenclature has not yet been achieved. We propose a comprehensive and hierarchical classification method and nomenclature to define biomes based on a set of bioclimatic variables and their corresponding vegetation structure and ecological functionality. This method uses three hierarchical biome levels: Zonal biome (Macrobiome), Biome and Regional biome. Biome nomenclature incorporates both bioclimatic and vegetation characterization (i.e. formation). Bioclimate characterization basically includes precipitation rate and thermicity. The description of plant formations encompasses vegetation structure, physiognomy and foliage phenology. Since the available systems tend to underestimate the complexity and diversity of tropical ecosystems, we have tested our approach in the biogeographical area of the Neotropics. Our proposal includes a bioclimatic characterization of the main 16 Neotropical plant formations identified. This method provides a framework that (1) enables biome distribution and changes to be projected from bioclimatic data; (2) allows all biomes to be named according to a globally standardized scheme; and (3) integrates various ecological biome approaches with the contributions of the European and North American vegetation classification systems. Taxonomic reference: Jørgensen et al. (2014). Dedication: This work is dedicated to the memory of and in homage to Prof. Dr. Salvador Rivas-Martínez.

Vegetation classification of the Voronezhsky Nature Reserve

2009 ◽  
pp. 63-141 ◽  
Author(s):  
E. A. Starodubtseva ◽  
L. G. Khanina
Keyword(s):  
Classification System ◽  
Nature Reserve ◽  
Steppe Zone ◽  
Alnus Glutinosa ◽  
Vegetation Classification ◽  
Classification Systems ◽  
Ground Vegetation ◽  
Forest Steppe ◽  
Reserve Area ◽  
Species Groups

Voronezhsky nature reserve is situated in the forest-steppe zone of European Russia, on the border between Lipetsk and Voronezh regions. The reserve was estab­lished in 1923; the total area of the reserve is 31 053 ha. We have created the vegetation classification system for the reserve on basis of 1058 phytocoenotic relevés processing. Phytocoenotic relevés have been collected since 1929 by different generations of researchers. All relevés were included into the data processing. Five forest vegetation formations and one herbaceous formation were described. According to the reserve’s forest inventory from 1991, Pinussylvestris formation occupies 32.3% of the reserve area, broad-leaved forest (oak forest) formation — 29.3, Populus tremula formation — 19.3, birch forest formation — 5.7, and Alnus glutinosa formation — 5.2 correspondingly. Her­baceous formation covers 3 % of the area in dry, moderate moistened and moist soils, and swamps occupy 2.5 % of the reserve area (they are not described here). Within the bounds of the vegetation formations, we have distinguished the vegetation association groups on the basis of ground vegetation functional group composition and ordination (DCA) technique. 8 functional species groups (ecologic-coenotic species groups) were used for the classification. The ecologic-coenotic species groups were as follows: 1) nemoral, 2) boreal, 3) nitrophilous, 4) pine-forest, 5) meadow-forest edge, 6) steppe, 7) oligotrophic, and 8) water-swamp. Totally we have described 23 vegetation asso­ciation groups united into the 9 ecologic-coenotic types of vegetation cover. 4 vegetation association groups were described for the herbaceous formation. We described in detail vegetation association groups inclu­ding species, structural diversity and the ecological position calculated by Tsyganov’s ecological species values. We also discuss the group’s history and the succession status. Finally, we have compared the proposed vegetation classification system for the re­serve with some other classification systems.

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

2019 ◽  
Vol 12 (6) ◽  
pp. 1009-1024
Author(s):  
Changcheng Liu ◽  
Thomas R Wentworth ◽  
Xianguo Qiao ◽  
Ke Guo ◽  
Dongjie Hou
Keyword(s):  
Classification System ◽  
Dominant Species ◽  
Vegetation Type ◽  
Plant Cover ◽  
Vegetation Classification ◽  
Classification Systems ◽  
International Standards ◽  
Data Sets ◽  
Diagnostic Species ◽  
The Core

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.

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