A comparative framework for broad‐scale plot‐based vegetation classification

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2015-06-13Author
De Cáceres, Miquel
Chytrý, Milan
Agrillo, Emiliano
Attorre, Fabio
Botta-Dukát, Zoltán
Capelo, Jorge
Czúcz, Bálint
Dengler, Jürgen
Ewald, Jörg
Faber-Langendoen, Don
Feoli, Enrico
Franklin, Scott B.
Gavilán, Rosario
Gillet, François
Jansen, Florian
Jiménez-Alfaro, Borja
Krestov, Pavel
Landucci, Flavia
Lengyel, Attila
Loidi Arregui, Javier
Mucina, Ladislav
Peet, Robert K.
Roberts, David W.
Roleček, Jan
Schaminée, Joop H.J.
Schmidtlein, Sebastian
Theurillat, Jean-Paul
Tichý, Lubomír
Walker, Donald A.
Wildi, Otto
Willner, Wolfgang
Wiser, Susan
Suggested citation
De Cáceres, Miquel;
Chytrý, Milan;
Agrillo, Emiliano;
Attorre, Fabio;
Botta-Dukát, Zoltán;
Capelo, Jorge;
...
Wiser, Susan.
(2015)
.
A comparative framework for broad‐scale plot‐based vegetation classification.
Applied Vegetation Science, 2015, vol. 18, núm. 4, p. 543-560.
https://doi.org/10.1111/avsc.12179.
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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.