Landscape classification of the Czech Republic based on the distribution of natural habitats.

We propose the first statistical landscape classification of the Czech Republic based on the distribution of different types of natural habitats (mainly defined in terms of plant communities) that resulted from national habitat mapping. We used occurrences of natural habitats in 2370 grid cells of 5' longitude × 3' latitude covering the whole area of the country. To cluster grid cells with similar habitat composition, we used two methods. First, we applied spatially unconstrained hierarchical clustering to obtain landscape types with maximal internal homogeneity in the range of natural habitats they contain. Second, we added spatial constraints to the classification process in order to obtain spatially cohesive regions. In both cases, the cross-validation technique proposed seven clusters as the optimal result. We also determined the characteristic habitats for each landscape type and region and characterized them using ecologically relevant attributes of abiotic environment and land cover. Irrespective of the method used, our results showed that the separation of individual clusters is primarily determined by altitude and related climatic factors, and differences between the Bohemian Massif and Carpathians. We compared our results with existing expert-based phytogeographical, biogeographical and zoogeographical divisions of the Czech Republic and also with a recently published statistical landscape classification of the Czech Republic based on the abiotic environment. Our landscape classifications closely matched the phytogeographical divisions of the Czech Republic proposed by Skalický (1988) and Dostál (1957, 1966). They differed more when compared with the biogeographical division of the Czech Republic (Culek 1996). However, we do not suggest that any of these classifications is superior to the others, because each of them is based on different principles and data. Both expert-based and statistical classifications can produce multiple meaningful results depending on a priori weighting of input data, number of target units and classification methods used. The advantage of statistical classifications is that input data and classification process are clearly described and therefore their logic can be more easily understood. The classification based on natural habitats presented here is not intended to replace any of the previous classifications, but to provide useful insights into biogeographical patterns in this country in addition to the previous classifications.