Plot sites in the field are positioned in vegetation stands that are relatively homogeneous in terms of structure, species composition, and environment, so that variation is minimized within and maximized between plots.
The traditional sampling strategy in phytosociology, preferential sampling, in which the researcher selects stands that are considered as representative of some vegetation units, has several disadvantages: it is not repea-table by other researchers, tends to neglect some vegetation types and oversample others, and produces a nonrepresentative sample of vegetation diversity in the study area. In spite of these disadvantages, probabilistic sampling strategies, such as random or systematic sampling, have never received wider acceptance in phytosociology. While providing reliable estimates of vegetation attributes, probabilistic sampling is less suited to phytosociology's goal of representing maximum variation in vegetation diversity across a study area, as it tends to undersample or even miss rare types. GIS and global positioning system (GPS) technology have made strati-fied-random sampling schemes increasingly popular in phytosociology. Based on the overlay of digital maps in a GIS, the study area can be stratified into patches with certain combinations of land-cover types and environmental variables that are supposed to correlate with plant distribution. Within each of these strata, plot positions are randomly placed and subsequently found in the field with a GPS receiver. A related sampling strategy is a gradient-oriented transect or gradsect, which establishes plot sites along a landscape transect that runs parallel to an important environmental gradient.
Phytosociological plots are usually squares or rectangles, which, as a rule of thumb, are roughly as large in square meters as the vegetation is high in decimeters (e.g., 200 m2 for a forest of 20 m height). Despite this rule and other suggestions in textbooks, actual plot sizes used may span more than one order of magnitude within the same vegetation type. Standardization of plot sizes is hindered by the vague and misleading concept of 'minimal area', which is thought to be a certain plot size specific for each vegetation type, beyond which any further enlargement has negligible effects on species richness and composition. However, plot size strongly influences estimates of species richness and other vegetation parameters. Joint use of differently sized releves in a single analysis may thus produce artifacts in classification, ordination, and calculation of fidelity of species to vegetation units. To safeguard data compatibility, standard plot sizes have been proposed for use within certain structural formations, for example, 200 m in forest vegetation; 50 m in scrub vegetation; 16 m in grassland, heathland, and other herbaceous vegetation; and 4 m2 in aquatic and low-growing herbaceous vegetation.
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