Geostatistical Characterization of the Spatial Distribution of Adult Corn Rootworm (Coleoptera: Chrysomelidae) Emergence

Geostatistical methods were used to characterize spatial variability in western ( Diabrotica virgifera virgifera LeConte) and northern ( Diabrotica barberi Smith & Lawrence) corn rootworm adult emergence patterns. Semivariograms were calculated for adult emergence density of corn rootworm populations in fields of continuous corn and rotated (corn/soybean) corn. Adult emergence densities were generally greater for northern corn rootworms than for western corn rootworms. The spatial structures of the adult rootworm emergence were aggregated as described by spherical spatial models for western corn rootworm and exponential models for northern corn rootworm. Range of spatial dependence varied from 180 to 550 m for western corn rootworm and 172 to 281 m for northern corn rootworm. Semivariograrn models were used to produce contour density maps of adult populations in the fields, based on grid sampling of actual emerging adult populations

Analysis of Spatial Distribution of Canada Thistle (Cirsium Arvense) in Notill Soybean (Glycine Max)

The nonuniform spatial distribution of weeds across a field landscape complicates sampling and modeling, but allows site specific rather than broadcast management of weed populations. Where weeds are aggregated, densities measured at random locations are not independent, but rather spatially related or autocorrelated. Geostatistical methods were used to describe and map nonrandom distribution and variation of shoot density across ten well established patches of Canada thistle, a perennial weed, in a 65 hectare notillage soybean field in Moody county, South Dakota in 1996. Canada thistle densities were determined by counting the number of shoots present in a 20 by 50 cm (0.1m2 ) rectangle. Shoot densities were recorded at 3.04 m increments in 8 .directions from the center of each patch using adaptive sampling. The boundary of the thistle patch on each axis was arbitrarily defined as having 2 consecutive measurements of 0 shoots per 0.1 m2 . Contour maps of weed densities were generated and overlaid on field topography maps. A contour map was generated to estimate the size and density of each thistle patch. Generally, the highest densities of Canada thistle appear in the center of the patches. Shoot density within the patches declined as the distance from the center of the patch increased. Near infrared images were generated with a digital camera and compared to weed maps produced with ground scouting

Field Scale Variability of Nitrogen and δ15N in Soil and Plants

Understanding the factors that influence soil and plant nitrogen (N) spatial variability may improve our ability to develop management systems that maximize productivity and minimize environmental hazards. The objective of this study was to determine the field (65 ha) scale spatial variability of N and δ15N in soil and corn (Zea mays). Soil, grain, and stover samples were collected from grids that ranged in size from 30 by 30 m to 60 by 60 m. Plant samples, collected following physiological maturity in 1995, were analyzed for total N and δ15N. Soil samples, collected prior to planting in the spring of 1995 and 1996, were analyzed for inorganic‐N, total N, and δ15N. All parameters showed strong spatial relationships. In an undrained portion of the field containing somewhat poorly and poorly drained soils there was a net loss of 95 kg N ha‐1, while in an adjacent area that was tile drained there was a net gain of 98 kg N ha‐1. Denitrification and N mineralization most likely were responsible for losses and gains, respectively. Differences between the N balances of these areas (193 kg N ha‐1) provide a relative measure of the impact of tile drainage on plant N availability and greenhouse gas production in a wet year

Influence of Yellow Foxtail on Corn Growth and Yield

Yellow foxtail [Setaria pumila syn. Setaria glauca (L.) Beauv.] competitive influence on corn (Zea mays L.) growth and yield was investigated at Brookings, South Dakota, and Morris, Minnesota, in 1995 and 1996. Yellow foxtail was seeded at different densities, and at Morris, two levels of nitrogen (N) were applied. Corn biomass measured at V‐6 or V‐8, silking, and harvest and grain yield were correlated negatively to foxtail biomass and density, but the loss differed between years and sites. Nitrogen increased corn growth and decreased yield loss. Defining a single foxtail density or biomass that resulted in a maximum yield loss of 10% was not possible. The most conservative estimate was 3 yellow foxtail plants m−2 or 24 g m−2 of yellow foxtail biomass, but ranged up to 55 plants m−2 and 256 g m−2 when weather conditions and N were optimal

Factors Influencing Spatial Variability of Soil Apparent Electrical Conductivity

Soil apparent electrical conductivity (ECa) can be used as a precision farming diagnostic tool more efficiently if the factors influencing ECa spatial variability are understood. The objective of this study was to ascertain the causes of ECa spatial variability in soils developed in an environment with between 50 and 65 cm of annual rainfall. Soils at the research sites were formed on calcareous glacial till parent materials deposited approximately 10,000 years ago. Soil samples (0–15 cm) collected from at least a 60 by 60 m grid in four fields were analyzed for Olsen phosphorus (P) and potassium (K). Elevation was measured by a carrier phase single frequency DGPS and ECa was measured with an EM 38 (Geonics Ltd., ON, Canada) multiple times between 1995 and 1999. Apparent electrical conductivity contained spatial structure in all fields. Generally, the well drained soils in the summit areas and the poorly drained soil in the toeslope areas had low and high ECa values, respectively. The landscape differences in ECa were attributed to: (i) water leaching salts out of summit areas and capillary flow combined with seepage transporting water and salts from subsurface to surface soils in toeslope areas; (ii) lower water contents in summit than toeslope soils; and (iii) water erosion which transported surface soil from summit/shoulder areas to lower backslope/footslope areas. A conceptual model based on these findings was developed. In this model, topography followed a sine curve and ECa followed a cosine curve. Field areas that did not fit the conceptual model were: (i) areas containing old animal confinement areas; (ii) areas where high manure rates had been applied; and (iii) areas where soils were outside the boundary conditions of the model, i.e., soils not developed under relatively low rainfall conditions in calcareous glacial till with temperatures ranging between mesic and frigid. This research showed that the soil forming processes as well as agricultural management influenced ECa and that by understanding how landscape position influences salt loss and accumulation, water redistributions following precipitation, and erosion areas that do not fit the conceptual model can be identified. This information can be used to improve soil sampling strategies

Theoretical Derivation of Stable and Nonisotopic Approaches for Assessing Soil Organic Carbon Turnover

Techniques for measuring soil organic C (SOC) turnover in production fields are needed. The objectives of this study were to propose and test nonisotopic and 13 C stable isotopic techniques for assessing SOC turnover. Based on SOC equilibrium and mass balance relationships, an equation was derived: NHC/SOC initial=[1/(SOC× k NHC)](dSOC/dt)+ k SOC/k NHC, where dSOC/dt is the annual change in SOC, NHC is nonharvested C returned to soil, k SOC is the annual mineralization rate of SOC, and k NHC is the annual mineralization rate of NHC. This equation was used to calculate maintenance rates. An isotopic approach based on simultaneously solving the equations was developed to determine C budgets:(i) SOC retained=[SOC final (Δ soil final− Δ PCR)/(Δ SOCretained− Δ PCR)];(ii) Δ SOC retained= Δ soc initial−[ε ln (SOC retained/SOC initial)],(iii) Δ PCR= Δ NHC−[ε ln (PCR/NHC)]; and (iv) SOC fina

Precision Farming Protocols: Part 1. Grid Distance and Soil Nutrient Impact on the Reproducibility of Spatial Variability Measurements

To determine temporal changes in soil nutrient status, reproducible results must be obtained at each time step. The objective of this paper was to determine the impact of grid distance on the reproducibility of spatial variability measurements. Soil samples from the 0 to 15 cm depth were collected from a 30 by 30 m grid in May 1995 in a 65 ha notill corn (Zea mays L.) field. Each bulk sample contained 15 individual cores, collected at sample points located every 11.4 cm along a transect that transversed 3 corn rows (57 cm). At each sampling point latitude, longitude, elevation, landscape position, and soil series were determined. The 30 m grid was used to develop 4 and 9 independent data sets having a 60 and 90 m, grids, respectively. Semivariograms, nugget to sill ratios, and mean squared errors were calculated for each data set. At 60 m: (i) the total N, total C, and pH semivariograms, of different start points, were similar, while semivariograms for Olsen P, K, and Zn were different; (ii) the spatial dependence ratings, based on the nugget to sill ratio, for total N, total C, and pH semivariograms were consistent and suggested moderate spatial dependence; (iii) the spatial dependence rating for Olsen P, K, and Zn for the 4 semivariograms were not consistent and ranged from weak to moderate spatial dependence. At 90 m all soil nutrients had different semivariograms for each start point, while the spatial dependence rating for each total N, total C, and pH start point were consistent and showed moderate spatial dependence. The total C, P, K, Zn, and pH MSE values at 60 m, were 30, 30, 41, 28, and 72% lower than the variance, respectively. This study showed that semivariogram, semivariance, MSE, and nugget to sill ratios reproducibility were dependent on soil nutrient and grid distance