An initial classification of 10-km squares in Great Britain from a land characteristic data bank

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In a pilot classification of 282 10-km squares in Great Britain, data on physiography, climate and geology were extracted. Parallel classifications were run using these variables and also using spatial location. Two classification methods were compared: minimum within-group variance and indicator species analysis. Similarities between the resulting classifications were considered, and the groups were assessed for geographic coherence. Their validity for use as stratifications were tested using analysis of variance and also by matching the classifications with known distributions of a number of bird and plant species. Classifications using spatial variables were geographically more coherent than those without. The different methods resulted in different groupings of the squares which were partly a result of the differences in weightings applied to the four types of variable. However, the analysis of variance showed that either classification method provided a good stratification of the country, in particular with respect to altitude and rainfall. Some bird and plant species distributions correlated well with the classifications, but others did not, dependent on the factors limiting those distributions.