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A comparative framework for broad‐scale plot‐based vegetation classification
Author(s) -
De Cáceres Miquel,
Chytrý Milan,
Agrillo Emiliano,
Attorre Fabio,
BottaDukát Zoltán,
Capelo Jorge,
Czúcz Bálint,
Dengler Jürgen,
Ewald Jörg,
FaberLangendoen Don,
Feoli Enrico,
Franklin Scott B.,
Gavilán Rosario,
Gillet François,
Jansen Florian,
JiménezAlfaro Borja,
Krestov Pavel,
Landucci Flavia,
Lengyel Attila,
Loidi Javier,
Mucina Ladislav,
Peet Robert K.,
Roberts David W.,
Roleček Jan,
Schaminée Joop H.J.,
Schmidtlein Sebastian,
Theurillat JeanPaul,
Tichý Lubomír,
Walker Donald A.,
Wildi Otto,
Willner Wolfgang,
Wiser Susan K.
Publication year - 2015
Publication title -
applied vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.096
H-Index - 64
eISSN - 1654-109X
pISSN - 1402-2001
DOI - 10.1111/avsc.12179
Subject(s) - vegetation classification , plot (graphics) , scale (ratio) , computer science , data mining , vegetation (pathology) , classification scheme , biological classification , set (abstract data type) , machine learning , geography , cartography , mathematics , statistics , biology , medicine , pathology , evolutionary biology , programming language
Aims Classification of vegetation is an essential tool to describe, understand, predict and manage biodiversity. Given the multiplicity of approaches to classify vegetation, it is important to develop international consensus around a set of general guidelines and purpose‐specific standard protocols. Before these goals can be achieved, however, it is necessary to identify and understand the different choices that are made during the process of classifying vegetation. This paper presents a framework to facilitate comparisons between broad‐scale plot‐based classification approaches. Results Our framework is based on the distinction of four structural elements (plot record, vegetation type, consistent classification section and classification system) and two procedural elements (classification protocol and classification approach). For each element we describe essential properties that can be used for comparisons. We also review alternative choices regarding critical decisions of classification approaches; with a special focus on the procedures used to define vegetation types from plot records. We illustrate our comparative framework by applying it to different broad‐scale classification approaches. Conclusions Our framework will be useful for understanding and comparing plot‐based vegetation classification approaches, as well as for integrating classification systems and their sections.