Characterizing Population Growth Rate of Convolvulus arvensis in Wheat–Sunflower No-Tillage Systems

Convolvulus arvensis L. is an important perennial weed that infests wheat (Triticum aestivum L.) and sunflower (Helianthus annuus L.) in Spain. Many fields of this rotation have been converted to no-tillage or reduced tillage, so perennial weeds such as C. arvensis have become more troublesome since they cannot be reduced in abundance by repeated tillage or cultivation. The population growth rate (PGR) is important in forecasting future population trends, and it can be used to develop weed control strategies in which applications of herbicides are spatially targeted to minimize possible damage. The objectives of this study were to assess and map PGR of C. arvensis in a wheat-sunflower no tillage rotation and to determine the temporal stability of the distribution function of C. arvensis. PGR was calculated over the course of four growing seasons (1999-2002) in a wheat-sunflower crop rotation in no-tillage systems. Spatial variability of PGR was analyzed by geostatistics. Temporal stability of the distribution function of C. arvensis PGR over time was established by a generalization of the two-sample Cramer-von Mises test for a difference between two univariate probability distributions. Year and crop influenced PGR, being larger in the sunflower phase (PGR = 0.52) than in the wheat phase (PGR = 0.16) of a sunflower-wheat rotation system because the density of C. arvensis was greater when growing in competition with wheat than with sunflower. The PGR showed a moderate degree of aggregation in patches in both rotations, although the temporal stability of the PGR distribution function was not observed. Overall, PGR became stable over the four growing seasons. Knowledge of growth rate spatial dynamics could improve C. arvensis management if it were complemented with spatially herbicide targeted applications.

[1]  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 .

[2]  D. L. Karlen,et al.  Spatial Analysis of Soil Fertility Parameters , 2004, Precision Agriculture.

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

[4]  Dawn Y. Wyse-Pester,et al.  Characterizing spatial stability of weed populations using interpolated maps , 1997, Weed Science.

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

[6]  Martin Mortimer,et al.  Dynamics of weed populations , 1995 .

[7]  T. Heisel,et al.  Annual weed distributions can be mapped with kriging , 1996 .

[8]  José Luis González-Andújar,et al.  Spatial distribution of annual grass weed populations in winter cereals , 2003 .

[9]  Francisca López-Granados,et al.  Spatial variability of agricultural soil parameters in southern Spain , 2002, Plant and Soil.

[10]  P. C. Robert,et al.  Managing Spatially Variable Weed Populations , 1995 .

[11]  Svend Christensen,et al.  Weed Managing Model for Patch Spraying in Cereal , 1996 .

[12]  L. Garcia-Torres,et al.  Weed flora in the Middle Valley of the Guadalquivir, Spain , 1989 .

[13]  P. Brain,et al.  Long‐term stability of distribution of Alopecurus myosuroides Huds. within cereal fields , 1991 .

[14]  Francisca López-Granados,et al.  Multi-species weed spatial variability and site-specific management maps in cultivated sunflower , 2003, Weed Science.

[15]  J. Cardina,et al.  Spatial and temporal expansion patterns of Apocynum cannabinum patches , 2000, Weed Science.

[16]  Jim Hone,et al.  Population growth rate and its determinants: an overview. , 2002, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[17]  A. Flint,et al.  Precipitation Estimation in Mountainous Terrain Using Multivariate Geostatistics. Part I: Structural Analysis , 1992 .

[18]  C. Staver,et al.  Ecological Management of Agricultural Weeds: Frontmatter , 2001 .

[19]  L. Wiles,et al.  Spatial dependence of weed seed banks and strategies for sampling , 2002, Weed Science.

[20]  F. López-Granados,et al.  Spatial distribution and mapping of crenate broomrape infestations in continuous broad bean cropping , 2001, Weed Science.

[21]  L. Garcia-Torres,et al.  Weed flora of dryland crops in the Córdoba region (Spain). , 1990 .

[22]  Lisa J. Rew,et al.  Spatial distribution of weeds in arable crops: are current sampling and analytical methods appropriate? , 2001 .

[23]  A. Konopka,et al.  FIELD-SCALE VARIABILITY OF SOIL PROPERTIES IN CENTRAL IOWA SOILS , 1994 .

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

[25]  J. Zadoks A decimal code for the growth stages of cereals , 1974 .

[26]  S. Syrjala,et al.  A statistical test for a difference between the spatial distributions of two populations , 1996 .

[27]  Timothy C. Coburn,et al.  Geostatistics for Natural Resources Evaluation , 2000, Technometrics.

[28]  S. T. Buckland,et al.  An Introduction to the Bootstrap. , 1994 .

[29]  Dieleman,et al.  Characterizing the spatial pattern of Abutilon theophrasti seedling patches , 1999 .

[30]  R. Cousens,et al.  Weed populations and pathogens , 2000 .