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Figure 7 Dendrogram showing the clustering of soil characteristics.
In this investigation, we consider different architectures of the dispersion and clustering of soil macropore space as deviations from the linear pattern of log-log lacunarity functions.
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T-RFLPs profiles identified different clusters of soil rhizospheric Archaea and Eubacteria in treatments of both organic and mineral fertilizers.
Cluster analysis of soil characteristics revealed 3 clusters, one of which including Hg species.
Cluster analysis of soil characteristics has confirmed the hypothesis of the anthropogenic origin of Hg in the area contaminated by the chlor-alkali industry by grouping Hg species in the same cluster, distinct from that including natural components of soil such as aluminosilicates.
Cluster and factor analyses of soil chemical and physical parameters confirm the redistribution of local sediments as a dominant factor behind the measured variables.
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.
In actively grazed sites, domestic livestock grazing also appears to lead to clustered, rather than random, spatial distribution of soil resources.
Figure 1 Dendogram showing the clustering of trace metals and physicochemical soil properties.
Figure 3 Block clustering of the metal concentrations in soil, nettle leaves, and snail hepatopancreas.
cluster-of-cluster Gaussians.
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