Questions: Do ordination patterns differ when based on vegetation samples recorded in plots of different size? If so, how large is the effect of plot size relative to the effects of data set heterogeneity and of using presence/absence or cover-abundance data? Can we combine plots of different size in a single ordination?
Methods: Two homogeneous and two heterogeneous data sets were sampled in Czech forests and grasslands. Cover-abundances of plant species were recorded in series of five or six nested quadrats of increasing size (forest 49-961 m2; grassland 1-49 m2). Separate ordinations were computed for plots of each size for each data set, using either species presences/absences or cover-abundances recorded on an ordinal scale. Ordination patterns were compared with Procrustean analysis. Also, ordinations of data sets jointly containing plots of different size were calculated; effects of plot size were evaluated using a Monte Carlo test in constrained ordination.
Results: The results were consistent between forest and grassland data sets. In homogeneous data sets, the effect of presence/absence vs. cover-abundance was similar to, or larger than, the effect of plot size; for presence/absence data the differences between ordinations of differently sized plots were smaller than for cover-abundance data. In heterogeneous data sets, the effect of plot size was larger than the effect of presence-absence vs. cover-abundance. The plots of smaller size (= 100 m2 in forests, = 4 m2 in grasslands) yielded the most deviating ordination patterns. Joint ordinations of differently sized plots mostly did not yield patterns that would be artifacts of different plot size, except for plots from the homogeneous data sets that differed in size by a factor of four or higher.
Conclusions: Variation in plot size does influence ordination patterns. Smaller plots tend to produce less stable ordination patterns, especially in data sets with low ß-diversity and species cover-abundances. Data sets containing samples from plots of different sizes can be used for ordination if they represent vegetation with large ß-diversity. However, if data sets are homogeneous, i.e. with low ß-diversity, the differences in plot sizes should not be very large, in order to avoid the danger of plot size differences distorting the real vegetation differentiation in ordination patterns.