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.

Evolution of Hotel Classification System in Russian Federation

2021 ◽  
Vol 12 (1) ◽  
pp. 277
Author(s):  
Dmitry Aleksandrovich KOZLOV
Keyword(s):  
Russian Federation ◽  
Classification System ◽  
State Standards ◽  
Classification Systems ◽  
International Standards ◽  
Economic Activities ◽  
World Tourism Organization ◽  
The Russian Federation ◽  
Tourism Organization

The main aim of this paper is to analyze the approaches to the system of classification of accommodation facilities in the Russian Federation. The United Nations World Tourism Organization pays great attention to the unification of classification systems for accommodation facilities in all countries of the world, issuing appropriate recommendations on tourism statistics systems, classification of economic activities, as well as criteria for interregional harmonization. In the Russian Federation, there are a number of laws, regulations, state standards, building and sanitary norms and rules concerning the classification of accommodation facilities. They are so imperfect that they have to be revised almost annually or even several times a year. The general statistics of accommodation facilities currently do not correspond to world recommendations. The classification system needs to be revised and brought into line with international standards as much as possible.

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.

scholarly journals Comparison of silhouette-based reallocation methods for vegetation classification

2019 ◽  
Author(s):  
Attila Lengyel ◽  
David W. Roberts ◽  
Zoltán Botta-Dukát
Keyword(s):  
Simulated Data ◽  
Primary Objective ◽  
Vegetation Classification ◽  
Data Sets ◽  
Data Set ◽  
Number Of Clusters ◽  
Silhouette Width ◽  
Diagnostic Species ◽  
Order Of Magnitude ◽  
Initial Classification

AbstractAimsTo introduce REMOS, a new iterative reallocation method (with two variants) for vegetation classification, and to compare its performance with OPTSIL. We test (1) how effectively REMOS and OPTSIL maximize mean silhouette width and minimize the number of negative silhouette widths when run on classifications with different structure; (2) how these three methods differ in runtime with different sample sizes; and (3) if classifications by the three reallocation methods differ in the number of diagnostic species, a surrogate for interpretability.Study areaSimulation; example data sets from grasslands in Hungary and forests in Wyoming and Utah, USA.MethodsWe classified random subsets of simulated data with the flexible-beta algorithm for different values of beta. These classifications were subsequently optimized by REMOS and OPTSIL and compared for mean silhouette widths and proportion of negative silhouette widths. Then, we classified three vegetation data sets of different sizes from two to ten clusters, optimized them with the reallocation methods, and compared their runtimes, mean silhouette widths, numbers of negative silhouette widths, and the number of diagnostic species.ResultsIn terms of mean silhouette width, OPTSIL performed the best when the initial classifications already had high mean silhouette width. REMOS algorithms had slightly lower mean silhouette width than what was maximally achievable with OPTSIL but their efficiency was consistent across different initial classifications; thus REMOS was significantly superior to OPTSIL when the initial classification had low mean silhouette width. REMOS resulted in zero or a negligible number of negative silhouette widths across all classifications. OPTSIL performed similarly when the initial classification was effective but could not reach as low proportion of misclassified objects when the initial classification was inefficient. REMOS algorithms were typically more than an order of magnitude faster to calculate than OPTSIL. There was no clear difference between REMOS and OPTSIL in the number of diagnostic species.ConclusionsREMOS algorithms may be preferable to OPTSIL when (1) the primary objective is to reduce or eliminate negative silhouette widths in a classification, (2) the initial classification has low mean silhouette width, or (3) when the time efficiency of the algorithm is important because of the size of the data set or the high number of clusters.

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.

scholarly journals Different Causal Factors Occur between Land Use/Cover and Vegetation Classification Systems but Not between Vegetation Classification Levels in the Highly Disturbed Jing-Jin-Ji Region of China

2021 ◽  
Vol 13 (8) ◽  
pp. 4201
Author(s):  
Sangui Yi ◽  
Jihua Zhou ◽  
Liming Lai ◽  
Qinglin Sun ◽  
Xin Liu ◽  
...  
Keyword(s):  
Land Use ◽  
Anthropogenic Disturbance ◽  
Vegetation Type ◽  
Ecological Factors ◽  
Vegetation Classification ◽  
Classification Systems ◽  
Environmental Research ◽  
Causal Factors ◽  
Cover System ◽  
Explained Variance

Land use/cover and vegetation patterns are influenced by many ecological factors. However, the effect of various factors on different classification systems and different levels of the same system is unclear. We conducted a redundancy analysis with 10 landscape metrics and ecological factors in four periods (1986–2005/2007, 1991–2005/2007, 1996–2005/2007, 2001–2005/2007) to explore their effects on the land use/cover system, vegetation group and vegetation type, and formation and subformation levels of the vegetation classification system in the Jing-Jin-Ji region. Soil, temperature and precipitation from 1986–2005, 1991–2005, and 2001–2005 were the important causal factors, and anthropogenic disturbance and atmospheric factors in 1996–2005 were causal factors at the land use/cover level. The total explained variance from 1996–2005 and 2001–2005 was higher than that from 1986–2005 and 1991–2005 at the land use/cover level. Causal factors and the variance explained by causal factors at the vegetation group, vegetation type, and formation and subformation levels were similar but different in the land use/cover system. Geography, soil and anthropogenic disturbance were the most important causal factors at the three vegetation levels, and the total explained variance from 2001–2007 was higher than that from 1986–2007, 1991–2007, and 1996–2007 at the three vegetation levels. In environmental research, natural resource management and urban or rural planning, geographic factors should be considered at the vegetation group, vegetation type and formation and subformation levels while atmospheric and temperature factors should be considered at the land use/cover level.

DIVERSITY AND DISTRIBUTION OF ORIBATID MITE FAUNA(ACARI: ORIBATIDA) IN THE FOREST FLOOR OF SATKOSIA BASIPALLY WILD LIFE SANCTUARY, ODISHA, INDIA

2017 ◽  
Vol 23 (1) ◽  
Author(s):  
SHELLEY ACHARYA ◽  
ADITI DUTTA
Keyword(s):  
Forest Floor ◽  
Dominant Species ◽  
Oribatid Mite ◽  
Soil Condition ◽  
Silica Content ◽  
Soil Mites ◽  
The Core ◽  
Humid Condition ◽  
Core Areas ◽  
Wild Life

The studies were mostly concentrated in Nine forest ranges of the WLS including the core areas. The soil of this region mostly is dry, red and with iron and silica content. Though the soil mites are prevalent in moist humid condition, we got a diversed population of 20 different species under 14 genera which is less than average probably due to the soil condition. Protoribates magnus is the dominant species in this study. The species with larger ranges were Scheloribates curvialatus.

Classification of woody-shrub vegetation of the forest-steppe complex of Privolzhskaya Upland

2009 ◽  
pp. 27-53
Author(s):  
A. Yu. Kudryavtsev
Keyword(s):  
Plant Community ◽  
Plant Communities ◽  
Dominant Species ◽  
Large Scale ◽  
Nature Reserve ◽  
Vegetation Mapping ◽  
Vegetation Classification ◽  
Forest Steppe ◽  
Mapping Data

Diversity of plant communities in the nature reserve “Privolzhskaya Forest-Steppe”, Ostrovtsovsky area, is analyzed on the basis of the large-scale vegetation mapping data from 2000. The plant community classi­fication based on the Russian ecologic-phytocoenotic approach is carried out. 12 plant formations and 21 associations are distinguished according to dominant species and a combination of ecologic-phytocoenotic groups of species. A list of vegetation classification units as well as the characteristics of theshrub and woody communities are given in this paper.

scholarly journals Toward the Development of a Comprehensive Clinically Oriented Patient Profile: A Systematic Review of the Purpose, Characteristic, and Methodological Quality of Classification Systems of Adult Spinal Deformity

Neurosurgery ◽  
2021 ◽  
Author(s):  
Kenny Yat Hong Kwan ◽  
J Naresh-Babu ◽  
Wilco Jacobs ◽  
Marinus de Kleuver ◽  
David W Polly ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Classification System ◽  
Methodological Quality ◽  
Literature Search ◽  
Adult Spinal Deformity ◽  
Classification Systems ◽  
Systematic Literature Search ◽  
Patient Profile

Abstract BACKGROUND Existing adult spinal deformity (ASD) classification systems are based on radiological parameters but management of ASD patients requires a holistic approach. A comprehensive clinically oriented patient profile and classification of ASD that can guide decision-making and correlate with patient outcomes is lacking. OBJECTIVE To perform a systematic review to determine the purpose, characteristic, and methodological quality of classification systems currently used in ASD. METHODS A systematic literature search was conducted in MEDLINE, EMBASE, CINAHL, and Web of Science for literature published between January 2000 and October 2018. From the included studies, list of classification systems, their methodological measurement properties, and correlation with treatment outcomes were analyzed. RESULTS Out of 4470 screened references, 163 were included, and 54 different classification systems for ASD were identified. The most commonly used was the Scoliosis Research Society-Schwab classification system. A total of 35 classifications were based on radiological parameters, and no correlation was found between any classification system levels with patient-related outcomes. Limited evidence of limited quality was available on methodological quality of the classification systems. For studies that reported the data, intraobserver and interobserver reliability were good (kappa = 0.8). CONCLUSION This systematic literature search revealed that current classification systems in clinical use neither include a comprehensive set of dimensions relevant to decision-making nor did they correlate with outcomes. A classification system comprising a core set of patient-related, radiological, and etiological characteristics relevant to the management of ASD is needed.

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