Vegetation analysis

From Sustainability Methods

In short: Vegetation checks make a systematic inventory of the vegetation on a defined sample area.


Out of the urge to gain a more systematic understanding of the vegetation of a respective area, the school of thinking of plant sociology emerged in the early 20th century. The underlying idea was developed mainly by Josias Braun-Blanquet, who developed a method to sample the vegetation within defined homogenous areas. Hence a certain minimum size needs to be accessed, and all so called vegetation relevees are chosen by the scientists to be representative for the wider vegetation of a specific community. These vegetation communities are classified by the presence of so called character species. In a beech forest this would obviously beech trees. Two vegetation communities are differentiated from each other by so called differential species. An example would be Luzula beech forests, which characterise certain environmental condition within this specific forest community. Thanks to the work of Heinz Ellenberg and many other ecologists was a closer understanding of the underlying ecology of a vegetation plot understood, and plants and their occurrence was used as a proxy for environmental conditions. Vegetation checks were thus evolving to generate descriptive but comprehensive representations of the vegetation of a wider area, and served as a basis of a more coherent understanding of the vegetation and its ecology.

What the method does

In a vegetation check which is sometimes also referred to as vegetation relevee in the so called Montpellier school, a defined areas with a certain minimum coverage is measured and checked for all plants. The abundance of plants is usually estimated in percentage of the cover, or in so called Braun-Blanquet classes (see table 1). The cover values may add up to more than 100 % because different strata of vegetation such as herbs, grasses, shrubs or trees are noted separately. Typically, other environmental conditions such as soil parameters, bioturbation and other parameters are noted down as well. Often dozens, hundreds or even thousands of vegetation checked are being compiled, and are then analysed. Vegetation analysis are a prominent examples of the benefit of the rise of computers and statistical software, because multivariate analysis widely replaced the manual paper sorting of past generations. Today, tens of thousands of vegetation checks are compiled in ambitious data bases, and first global analyses testify that the former descriptive analysis are now often amended by deeper ecological pattern recognition in the light of global change.

Strengths and challenges

While within most studies the choice of vegetation relieves is deliberate and thus builds on the experience of the sample yet infers a subjective component. Hence any form of plant sociology is after all a subjective construct widely created by the respective researcher. Furthermore does the quality of each relevee depend widely on the knowledge about plant species and many other parameters that are deeply rooted in the experience of the respective researcher. This makes sampling a sometimes cumbersome effort if conducted by several researchers working within the same project. In addition is the concept of vegetation communities build around a mainly central European perspective, where the conceptual underlying principles can be well argued for. In other parts of the world -notably tropical ecosystems- is the minimum area of a forest almost impossible to tame, since these eco stems are wide-ranging and homogenous in structure yet very diverse in species composition. Lastly, analysis of vegetation data was in the past a deeply subjective process, yet it needs to be noted that multivariate statistics are also more for pattern recognition instead of discrete answers. Hence statistics need to be noted as an analytical process that unravels complex patterns yet does not provide clear and well defined answers to all questions we may have. After al is vegetation data noisy in nature, although safety comes in numbers. This is one of the good news of the lates data bases, that is that long known patterns can often be reproduced by modern statistics. Instead of being dismissed as a shot in the dark is vegetation ecology one of the starting points of modern ecology and biodiversity research. The latest analysis try to bridge the gap between designed experiments and large yet deliberate sample data bases, and to this day is vegetation sampling a standard tool in vegetation conservation and habitat mapping.


A main challenge of vegetation mapping and associated plant sociology is that it is widely subjective in its sampling and analysis, yet the wider discourse of the community kept the body of knowledge somewhat bound within parameters that made plant communities a baseline in Central Europe, and partly beyond. However, compared to North American vegetation description, plant sociology is somewhat say overcomplicating complexity, while other would claim it present the right amount of information reduction. The very location of the vegetation relevee as a deliberate act of researchers themselves is to this day criticised, and while statisticians would demand a random sampling, this does diminish resources somewhat, and may not necessarily lead a superior body of knowledge. What is more, the whole concept of species as constructs and our overall constructed and over-classifying view of the world is seen as. part of the tradition of a post-colonialistic critique.


For now, it is clear that vegetation checks are part not only of the past, but also of the future of ecology. We have still much to learn about the vegetation dynamics of our planet, even while or especially because these are rapidly changing due to global change. Time will tell how genetic analysis and other approaches such as trait analysis will amend of even replace the classic approach to vegetation sampling. Yet as a basis for biodiversity a vegetation check is still a first starting point to many forms of habitat assessment, and unless machine learn that much to make such samples without us, it will be up to us to understand the vegetation and sample it in relevees.

The author of this entry is Henrik von Wehrden.