Most soil surveys are based on soil geomorphic, physical and chemical properties, while many classifications are based on morphological properties in soil profile. Typically, microbial properties of the soil(e.g. biomass and functional diversity) or soil biological quality indicators (SBQIs) are not directly considered in soil taxonomic keys, yet soil classification schemes are often used to infer soil biological function relating to policy (e.g. soil pollution attenuation, climate change mitigation). To critically address this, our aimwas to assess whether rates of carbon turnover in a diverse range of UK soils (n > 500) could effectively be described and sub-divided according to broadly defined soil groups by conventional soil classification schemes. Carbon turnover in each soil over a 90 d period was assessed by monitoring the mineralisation of either a labile (14C-labelled artificial root exudates) or more recalcitrant C source\ud (14C-labelled plant leaves) in soil held at field capacity at 10 C. A double exponential first order kinetic\ud model was then fitted to the mineralisation profile for each individual substrate and soil. ANOVA of the\ud modelled rate constants and pool sizes revealed significant differences between soil groups; however,these differences were small regardless of substrate type. Principle component and cluster analysis further separated some soil groups; however, the definition of the class limits remained ambiguous. Exclusive reference values for each soil group could not be established since the model parameter ranges greatly overlapped. We conclude that conventional soil classification provides a poor predictor of C residence time in soil, at least over short time periods. We ascribe this lack of observed difference to the\ud high degree of microbial functional redundancy in soil, the strong influence of environmental factors and the uncertainties inherent in the use of short term biological assays to represent pedogenic processes which have taken ca. 10,000 y to become manifest
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