Characterising soil quality clusters in relation to land use and soil order in New Zealand: An application of the phenoform concept

- The multivariate character of a data set (720 sites) of dynamic soil properties was examined.
- Clustering of sites could be related to changes in soil order and land use.
- The cluster centroids also had significance for expression of soil quality properties.
- Dynamic properties in conjunction with the phenoform concept are useful to taxonomic classification.

The multivariate character of seven dynamic soil properties from a national soil quality data set was explored to determine if generalizations can be made about the status of the properties from land use and soil order. The genoform-phenoform concept (where soil phenoforms arise from a genoform due to modification of dynamic soil properties through specific land use history) was used to frame three hypotheses. Hypothesis one proposed that managed sites were distinct from native sites. This was supported by discriminant analysis and permutational multivariate analysis of variance. Hypothesis two proposed that managed sites were clustered into statistically significant distinct classes. This was supported by principal components fuzzy-c means clustering, with recognition of five to seven statistically significant clusters. Hypotheses three proposed that the clusters had functional meaning. This was supported by inspecting the clusters for rational relationships between land use, soil order and soil quality status as estimated by indicator mean values for each cluster. While organic status (e.g., soil C and N) appeared to be the primary driver of clustering, other soil quality indicators (such as macroporosity) were also important in differentiating the effects of land use and soil type on cluster patterns. The results indicate that a taxonomy of phenoforms is possible, but would require input of both inherent and dynamic soil properties. Such a phenoform clustering approach would provide a more quantitative framework for defining intergrades and uncertainty in mapping. Used in conjunction with spatial inherent-property-based databases, the phenoform clustering approach could also be beneficial to assess soil natural capital and to predict susceptibility of specific soils to land-use intensification.