Detailed Information on Publication Record
2015
Formalized classification of species-poor vegetation: a proposal of a consistent protocol for aquatic vegetation
LANDUCCI, Flavia, Lubomír TICHÝ, Kateřina ŠUMBEROVÁ and Milan CHYTRÝBasic information
Original name
Formalized classification of species-poor vegetation: a proposal of a consistent protocol for aquatic vegetation
Authors
LANDUCCI, Flavia (380 Italy, guarantor, belonging to the institution), Lubomír TICHÝ (203 Czech Republic, belonging to the institution), Kateřina ŠUMBEROVÁ (203 Czech Republic) and Milan CHYTRÝ (203 Czech Republic, belonging to the institution)
Edition
Journal of Vegetation Science, Wiley, 2015, 1100-9233
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10600 1.6 Biological sciences
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 3.151
RIV identification code
RIV/00216224:14310/15:00081458
Organization unit
Faculty of Science
UT WoS
000356811300018
Keywords in English
Aquatic vegetation; Assignment rules; Association; Cocktail method; Consistency; Functional species group; Physiognomy; Releve; Supervised classification; Vegetation classification; Vegetation database
Tags
International impact, Reviewed
Změněno: 13/3/2018 10:31, Mgr. Lucie Jarošová, DiS.
Abstract
V originále
Aims: Most vegetation classification systems developed for large areas include various inconsistencies. Therefore, we (1) propose a new consistent Cocktail-based approach to redefine the traditional phytosociological classification of species-poor vegetation; (2) apply it to create a classification protocol for aquatic vegetation; (3) implement this protocol in a computer expert system; and (4) test it with a data set previously classified using an older version of the Cocktail method. Methods: The new approach uses formal logic to provide formal definitions of vegetation units. In the classification protocol for aquatic vegetation we defined consistent criteria for delimitation of associations according to the concepts that are predominantly used in phytosociology, based on species cover, dominance patterns and functional species groups. We applied these criteria in a computer expert system running in the JUICE 7.0 program, and applied them to a test data set of 12171 vegetation plots from the Czech Republic containing at least one aquatic species. The new classification was compared with (1) the previous national Cocktail classification based on species cover values and in few cases on sociological species groups, and (2) a non-formalized expert-based classification. Results: Thirteen functional species groups were created to build logical formulas of 64 aquatic associations and 5297 (44% of the total data set) vegetation plots were assigned to these associations, i.e. by 4% and 12% more than in the previous Cocktail and expert-based classifications, respectively. There was 94% and 83% classification agreement with the previous Cocktail and expert-based classification. Conclusions: The new approach produces a formal, consistent and unequivocal classification of species-poor vegetation with several advantages over similar approaches. It provides not only a set of formal definitions of vegetation units, but also a set of rules for building such definitions. All associations with common characteristics are defined by structurally identical formulas, ensuring consistency of the classification. While similar approaches for species-rich vegetation use sociological species groups, which are not applicable to species-poor vegetation, the new approach introduces the use of functional species groups, which reflect vegetation physiognomy and spatial structure and, in combination with species dominance, enable the classification of species-poor vegetation in a similar manner as in traditional phytosociology.
Links
GAP505/11/0732, research and development project |
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GB14-36079G, research and development project |
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3SGA5613, interní kód MU |
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