Farm-Scale Mapping of Soil Microbiological Indicators Using Geostatistical Technique

Abstract

Soil microbiological properties viz. soil microbial biomass carbon (MBC) and dehydrogenase activity (DHA) are sensitive soil quality indicators. Spatial modeling and prediction map of soil MBC and DHA were generated for a semiarid agricultural farm, New Delhi, India from 288 geo-referenced grid samples spaced 100 m × 100 m distance using geospatial techniques and geo-statistics. Soil microbial biomass carbon (MBC) ranged from 19.7 to 519.7 µg g-1 with standard deviation of 84.1 and soil DHA varied from 1.2 to 17.2 µg TPF g-1 dry soil hr-1 with sample variance of 10.89. Soil MBC and DHA had high data viability with coefficient of variation (CV) of 42.5 % and 53.2%, respectively. The best fit semivariogram for both soil MBC and DHA was exponential model and had practical spatial range of 1500 m and 1473 m respectively. Environmental disturbances or extrinsic factors dominantly influenced the spatial variability of soil MBC, expressing its weak spatial dependency. Besides, both soil structural/internal factors and extrinsic factors controlled soil DHA variability with moderate level of spatial dependency. Spatial variability map of soil MBC and DHA, prepared with good accuracy through ordinary kriging in GIS software, showed that major area of the farm had soil MBC ranging from 150 to 250 mg kg-1 and had DHA from 1.2 to 10 µg TPF g-1 dry soil hr-1.