Monday, 7 November 2005
9

Spatial and Seasonal Patterns of C and N Mineralization in an Irrigated Potato Rotation.

Harold Collins, USDA-ARS, Vegetable and Forage Crops Research Unit, 24106 N Bunn Rd, Prosser, WA 99350, Ekaterini Riga, Washington State University, IAREC, 24106 N Bunn. RD, Prosser, WA 99350, and Francis Pierce, WA St.Univ-Irr Ag Res. & ExCtr, 24106 N. Bunn Rd, Prosser, WA 99350-8694, Albania.

Spatial and temporal dependence of biological systems are particularly important due to the "patchy" distribution of soil organisms as well as soil resources and abiotic variables. Our objective was to quantify and predict the relationships between spatial and temporal patterns of C and N transformations in an irrigated cropping system. The study was conducted from 2001-2004 in a 2 ha research field located at the WSU Experiment Station in Prosser, WA. The field had been cropped to various row crops and various cropping experiments since the 1920s but had been fallowed in 1999 and 2000. A cropping system study was imposed on the main area from 2002-2004 that included four 0.4 ha blocks in a potato-wheat-corn rotation and a continuous small grain. In the spring of 2001, a geostatistical grid was established on the field consisting of an unaligned regular design with 12 m spacing with cluster points at 1, 3, and 6 m spacings at 25 randomly selected grid points. An additional 25 sampling points were selected randomly and used as validation points to assess errors of prediction from interpolations. At each grid point, soils were sampled by taking 12-2.5 cm diameter probes to a depth of 30 cm and composited for later analysis. The spatial sample was performed five times over the four year period. Total organic carbon was analyzed for the fall 2002 sampling only. Soils from five sampling dates were extracted for available NO3 and NH4 using a standard KCl extraction procedure and N and C mineralization potentials and microbial biomass were determined. Descriptive statistics were applied to characterize the distribution of each parameter for the field and data were subjected to geostatistical analysis to assess spatial structure.

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