Looking for biological indicators of soil using hierarchical clustering

Abstract

Soil microbial activity (SMA) is related to the use and management of soil we hypothesized that a single change in the sequence of crop rotation could be detected through changes in the biological and microbial activity of the soil. We analyzed SMA from and agricultural typic argiudoll soil under no-tillage (NT) with different crop rotation (corn-oat-soybean(COS), corn-soybean (C-S) and undisturbed soil as control (N.C)). We measured dehydrogenase activity, B glucosidade activity, community level physiological profiles, taxonomic microbial grops and the physiologycal broup involved in the carbon cycle (cellulose-and_amylose-decomposing micro-organisms) to detect changes in microbial activity. We also measured carbon from microbial biomass, total organic carbon, soil respiration, sustrate induced respiration, biological quotient and metabolic quotient (QCO2) to detect changes in biological activity. Dependence on the variables analyzed by Bartlett's test allowed us the apply correspondence analysis and principal components analysis (PCA). PCA showed three different soil conditions and a negative correlation between qCO2 and the other variables. Hierarchical clustering analysis using ward algorithm confirmed that qCO2 and BMC showed the three soil conditions. In fact qCO2 and BMC explained the maximum sensitivity against contrasting management situations. Increased enzymatic activities in rotation with the highest crop residues expedite mineralization and mobilization of available nutritient. We observed a quick response of the SMA to a single change in the crop rotation.