Hostname: page-component-8448b6f56d-dnltx Total loading time: 0 Render date: 2024-04-19T18:38:33.026Z Has data issue: false hasContentIssue false
  • English
  • Français

Spatial Distribution and Temporal Stability of Prostrate Knotweed (Polygonum aviculare) and Corn Poppy (Papaver rhoeas) Seed Bank in a Cereal Field

Published online by Cambridge University Press:  20 January 2017

J. Izquierdo ,
J. M. Blanco-Moreno ,
L. Chamorro ,
J. Recasens  and
F. X. Sans
J. Izquierdo*
Affiliation:
Departament d'Enginyeria Agroalimentària i Biotecnologia, Universitat Politècnica de Catalunya, Avenida Canal Olímpic s/n, E-08860, Castelldefels, Catalunya, Spain
J. M. Blanco-Moreno
Affiliation:
Departament de Biologia Vegetal, Universitat de Barcelona, Avenida Diagonal 645, E-08028 Barcelona, Catalunya, Spain
L. Chamorro
Affiliation:
Departament de Biologia Vegetal, Universitat de Barcelona, Avenida Diagonal 645, E-08028 Barcelona, Catalunya, Spain
J. Recasens
Affiliation:
Departament d'Hortofructicultura, Botànica i Jardineria, Universitat de Lleida, Avenida Rovira Roure 191, E-25198 Lleida, Catalunya, Spain
F. X. Sans
Affiliation:
Departament de Biologia Vegetal, Universitat de Barcelona, Avenida Diagonal 645, E-08028 Barcelona, Catalunya, Spain
*
Corresponding author's E-mail: jordi.izquierdo@upc.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

The knowledge of weed distribution in a field is a key factor to manage weeds effectively. The feasibility of using weed distribution maps for site-specific weed control will largely depend on the stability of the spatial distribution of the populations. Seed banks are the most reliable way of telling the area's weediness, but the effect of regular herbicide applications on its stability is largely unknown. A field experiment was conducted during 3 yr in a winter wheat field under herbicide treatments with the aim of studying the seed bank's spatial distribution of prostrate knotweed and corn poppy and the spatiotemporal stability of their populations. Soil samples were taken each year on the same locations, and seed abundance was measured by germination in greenhouse. Both species accounted for more than 10% of the broad-leaved weed seed bank and they were selected for further analysis. Prostrate knotweed seed-bank density decreased 76% and corn poppy 88% in 3 yr. Spatial distribution was described by spherical isotropic semivariograms. Distance of spatial dependence (range) of prostrate knotweed and corn poppy decreased 33 and 11% respectively, and the spatial variability (sill) decreased 96 and 99%. Yearly spatial seed distribution was compared for each species and no temporal stability was observed over a 3-yr period. The lack of stability was attributed to the important decrease of seed density over time and the increase in the short-range variability (nugget). However, for prostrate knotweed, the location of minima and maxima were roughly the same between years, allowing farmers to extend the period of use of the weed distribution maps. Although spatial distribution of seed banks can be affected by processes that promote fast changes in the densities of weed populations, this fact does not mean that weed distribution maps could not be used in consecutive seasons.

Keywords

Corn poppy, Papaver rhoeas L.prostrate knotweed, Polygonum aviculare Lwinter wheat, Triticum aestivum L.Spatial dependencesemivariogramCramér–von Mises nonparametric testmappingherbicideweed managementgeostatistics
Type
Weed Biology and Ecology
Information
Weed Science , Volume 57 , Issue 5 , October 2009 , pp. 505 - 511
Copyright
Copyright © Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

Barroso, J., Fernández-Quintanilla, C., Ruiz, D., Hernaiz, P., and Rew, R. J. 2004. Spatial stability of Avena sterilis ssp ludoviciana populations under annual applications of low rates of imazamethabenz. Weed Res. 44:178–186.Google Scholar
Blanco-Moreno, J. M., Chamorro, L., and Sans, F. X. 2006. Spatial and temporal patterns of Lolium rigidum-Avena sterilis mixed populations in a cereal field. Weed Res. 46:207–218.Google Scholar
Cambardella, C. A. and Karlen, D. L. 1999. Spatial analysis of soil fertility parameters. Precis. Agric. 1:5–11.Google Scholar
Cardina, J., Sparrow, D. H., and McCoy, E. L. 1996. Spatial relationships between seedbank and seedling populations of common lambsquarters (Chenopodium album) and annual grasses. Weed Sci. 44:298–308.Google Scholar
Cardina, J., Johnson, G. A., and Sparrow, D. H. 1997. The nature and consequence of weed spatial distribution. Weed Sci. 45:364–373.Google Scholar
Cavers, P. B. and Benoit, D. L. 1989. Seed banks in arable land. Pages 309–326. In Leck, M. A., Paker, V. T., and Simpson, R. L. Ecology of Soil Seed Banks. London Academic Press.Google Scholar
Cirujeda, A., Recasens, J., and Taberner, A. 2003. Dormancy cycle and viability of buried seeds of Papaver rhoeas . Weed Res. 46:327–334.Google Scholar
Colbach, N., Forcella, F., and Johnson, G. A. 2000. Spatial and temporal stability of weed populations over five years. Weed Sci. 48:366–377.Google Scholar
Costea, M. and Tardif, F. J. 2005. The biology of Canadian weeds. 131. Polygonum aviculare L. Can. J. Plant Sci. 85:481–506.Google Scholar
Cousens, R. D., Brown, R. W., McBratney, A. B., Whelan, B., and Moerkek, M. 2002. Sampling strategy is important for producing weed maps: a case study using kriging. Weed Sci. 50:542–546.Google Scholar
De Bolòs, O., Vigo, J., Masalles, R. M., and Ninot, J. M. 2005. Flora Manual dels Països Catalans. Barcelona Editorial Pòrtic. 1310.Google Scholar
Dieleman, J. A. and Mortensen, D. A. 1999. Characterizing the spatial pattern of Abutilon theophrasti seedling patches. Weed Res. 39:455–467.Google Scholar
Gerhards, R., Sökefeld, M., Schulze-Lohne, K., Mortensen, D. A., and Kühbauch, W. 1997. Site specific weed control in winter wheat. J. Agron. Crop. Sci. 178:219–225.Google Scholar
Gibson, D. J. 2002. Methods in comparative plant population ecology. New York Oxford University Press. 344.Google Scholar
González-Andújar, J. L. 1996. High control measures cannot produce extinction in weed populations. Ecol. Model. 91:293–294.Google Scholar
Isaaks, E. H. and Srivastava, R. M. 1989. An Introduction to Applied Geostatistics. New York Oxford University Press. 537.Google Scholar
Johnson, G. A., Mortensen, D. A., and Gotway, C. A. 1996. Spatial and temporal analysis of weed seedling populations using geostatistics. Weed Sci. 44:704–710.Google Scholar
Jurado-Expósito, M., López-Granados, F., González-Andújar, J. L., and García-Torres, L. 2005. Characterizing population growth rate of Convolvulus arvensis in wheat–sunflower no-tillage systems. Crop Sci. 45:2106–2112.Google Scholar
Luschei, E. C., Van Wychen, L. R., Maxwell, B. D., Bussan, A. J., Buschena, D., and Goodman, D. 2001. Implementing and conducting on-farm weed research with the use of GPS. Weed Sci. 49:536–542.Google Scholar
Lutman, P. J. W., Cussans, G. W., Wright, K. J., Wilson, B. J., Wright, G. M., and Lawson, H. M. 2002. The persistence of seeds of 16 weed species over six years in two arable fields. Weed Res. 42:231–241.Google Scholar
Mickelson, J. A. and Stougaard, R. N. 2003. Assessment of soil sampling methods to estimate wild oat (Avena fatua) seed bank populations. Weed Sci. 51:226–230.Google Scholar
Nordmeyer, H. 2005. Site specific weed control and spatial distribution of a weed seedbank. Pages 139–146. In Stattford, J. V. Precision Agriculture '05. Uppsala, Sweden Wageningen Academic Publishers.Google Scholar
Pannatier, Y. 1996. VARIOWIN: Software for Spatial Data Analysis in 2D. New York Springer-Verlag. 82.Google Scholar
Riba, F., Recasens, J., and Taberner, A. 1990. Flora arvense de los cereales de invierno de Catalunya. Pages 239–246. in. Actas de la Reunión de la Sociedad Española de Malherbología. Madrid Sociedad Española de Malherbología.Google Scholar
Sans, F. X., Blanco, J. M., Chamorro, L., Carreras, J., Izquierdo, J., Masalles, R. M., and Recasens, J. 2002. Spatial pattern of Lolium rigidum seedling patches in a wheat field in the Mediterranean region. Pages 412–413. in. Proceedings of the 12th European Weed Research Society Symposium. The Netherlands European Weed Research Society.Google Scholar
Syrjala, S. E. 1996. A statistical test for a difference between the spatial distributions of two populations. Ecology. 77:75–80.Google Scholar
Tellaeche, A., BurgosArtizzu, X. P., Pajares, G., Ribeiro, A., and Fernández-Quintanilla, C. 2008. A new vision-based approach to differential spraying in precision agriculture. Comput. Electron. Agric. 60:144–155.Google Scholar
Walter, A. M. 1996. Temporal and spatial stability of weeds. Pages 125–130. in. Proceedings of the Second International Weed Control Congress, Sheffield. Flakkebjierg, Denmark Academic Press.Google Scholar
Webster, R. and Oliver, M. A. 2001. Geostatistics for Environmental Scientists. Chichester, United Kingdom Wiley. 271.Google Scholar
Wiles, L. and Brodahl, M. 2004. Exploratory data to identify factors influencing spatial distributions of weed seed banks. Weed Sci. 52:936–947.Google Scholar
Wiles, L. and Schweizer, E. 2002. Spatial dependence of seed banks and strategies for sampling. Weed Sci. 50:595–606.Google Scholar
Wilson, B. J. and Brain, P. 1991. Long-term stability of distribution of Alopecurus myosuroides Huds. within cereal fields. Weed Res. 31:367–373.Google Scholar