Spatial and Temporal Analysis of Weed Seedling Populations Using Geostatistics

An intensive field survey of an eastern Nebraska corn and soybean field was conducted to characterize the spatial structure and temporal stability of broadleaf weed seedling populations over two growing seasons. Anisotropy, the effect of direction on the relationship between observa- tions, is present in the semivariogram for the velvetleaf and common sunflower populations in 1992 and 1993. The direc- tional trends in aggregation are visible in kriged maps as elliptical shapes oriented east to west across the study area. In addition, there are two distinct zones of aggregation from north to south. These two distinct areas of aggregation are reflected as a 'plateau' in the north-south semivariogram. The distance over which this plateau extends indicates that the shape or size of the patch is contracting in the north-south direction (perpendicular to the crop row). The slope of the semivariogram in the east-west direction (aligned with the crop row) remains consistent from 1992 to 1993 suggesting that the shape of the patch is not changing. For sunflower populations, the slope of the north-south empirical semi- variogram changes at 20 m, similar to the velvetleaf popula- tion semivariograms. This change, however, is reflected as a downward trend in the empirical semivariogram. The dis- tance over which this trend occurs increases from 1992 to 1993 suggesting that seedling patch size was smaller in 1993 compared to 1992. Weed seedling establishment resulting from seed dispersal, differential seed and seedling mortality, or emergence may have resulted in the observed patch dy- namics. Nomenclature: Common sunflower, Helianthus an- nuus L. # HELAN; corn, Zea mays L.; soybean, Glycine max (L.) Merr.; velvetleaf, Abutilon theophrasti Medicus #3

[1]  James F. Quinn,et al.  On Hypothesis Testing in Ecology and Evolution , 1983, The American Naturalist.

[2]  Andre G. Journel,et al.  Geostatistics: Models and tools for the earth sciences , 1986 .

[3]  E. Marshall Field‐scale estimates of grass weed populations in arable land , 1988 .

[4]  The problem of weed patchiness. , 1990 .

[5]  P. Thornton,et al.  Spatial weed distribution and economic thresholds for weed control , 1990 .

[6]  Marie-Laure Navas,et al.  Using plant population biology in weed research : a strategy to improve weed management , 1991 .

[7]  Michael Edward Hohn,et al.  An Introduction to Applied Geostatistics: by Edward H. Isaaks and R. Mohan Srivastava, 1989, Oxford University Press, New York, 561 p., ISBN 0-19-505012-6, ISBN 0-19-505013-4 (paperback), $55.00 cloth, $35.00 paper (US) , 1991 .

[8]  C. J. Doyle,et al.  Mathematical models in weed management , 1991 .

[9]  Gail G. Wilkerson,et al.  Value of information about weed distribution for improving postemergence control decisions , 1992 .

[10]  Livy Williams,et al.  Geostatistical description of the spatial distribution of Limonius californicus (Coleoptera : Elateridae) wireworms in the northwestern United States, with comments on sampling , 1992 .

[11]  David J. Mulla,et al.  Geostatistical Tools for Modeling and Interpreting Ecological Spatial Dependence , 1992 .

[12]  Clayton V. Deutsch,et al.  GSLIB: Geostatistical Software Library and User's Guide , 1993 .

[13]  E. A. Roberts,et al.  Spatial Data Representation for Integrated Pest Management Programs , 1993 .

[14]  M. L. Roush,et al.  SEARCHING FOR SOLUTIONS TO WEED PROBLEMS : DO WE STUDY COMPETITION OR DISPERSION ? , 1993 .

[15]  P. C. Robert,et al.  Weed distribution in agricultural fields. , 1993 .

[16]  F. Davis Introduction to Spatial Statistics , 1993 .

[17]  W. Donald,et al.  Geostatistics for Mapping Weeds, with a Canada Thistle (Cirsium arvense) Patch as a Case Study , 1994, Weed Science.

[18]  Alex Martin,et al.  A simulation of herbicide use based on weed spatial distribution , 1995 .

[19]  J. Cardina,et al.  Analysis of Spatial Distribution of Common Lambsquarters (Chenopodium album) in No-Till Soybean (Glycine max) , 1995, Weed Science.