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Spatial arrangement, density, and competition between barnyardgrass and tomato: II. Barnyardgrass growth and seed production

Published online by Cambridge University Press:  20 January 2017

Clyde L. Elmore
Affiliation:
Weed Science Program, Department of Vegetable Crops, University of California, Davis, CA 95616
Marcel Rejmánek
Affiliation:
Section of Ecology and Evolution, University of California, Davis, CA 95616
William C. Akey
Affiliation:
Stanford Media Works, Stanford University, Stanford, CA 94305

Abstract

Barnyardgrass was grown at densities of 0, 0.25, 0.5, 1, 2, 5, and more than 50 plants m−1 of tomato crop row in either a regular, random, or clumped pattern. Tomato was established at 0, 5, 10, or 20 plants m−1 of crop row in a regular pattern. Crop density and weed density or spatial arrangement had little effect on phenological development of barnyardgrass. In the absence of tomato, barnyardgrass was estimated to produce over 400,000 seeds plant−1 when not subjected to intraspecific competition (0.25 plants m−1 density), decreasing to about 10,000 seeds plant−1 when weed density exceeded 50 plants m−1 of row. Differences in seed production between plants in the regular and random spatial arrangements were minor, but the clumped distribution resulted in 30 to 50% reduction in seed production at weed densities between 1 and 5 plants m−1 of row. Tomato reduced barnyardgrass seed production. The magnitude of the reduction depended on both tomato density and barnyardgrass density. In the absence of tomato, barnyardgrass produced over 200,000 seeds m−2 in 1993 and over 500,000 seeds m−2 in 1994 at 5 plants m−1 of row. Production was almost 700,000 seeds m−2 when the weed density exceeded 50 plants m−1 of row. Barnyardgrass seed production at the single-season economic threshold density in tomato was sufficient to maintain the seedbank at a level that would mandate high levels of weed control in subsequent crops. Because of the high fecundity of barnyardgrass, our experiments suggest that stopping seed production is the best long-term management strategy for the weed. Spatial arrangement of the weed, at the scale used in these studies, would not be a factor in establishing long-term management guidelines based on weed population biology.

Type
Research Article
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Auld, B. A., Kemp, D. R., and Medd, R. W. 1983. The influence of spatial arrangement on grain yield in wheat. Aust. J. Agric. Res. 34:99108.Google Scholar
Bruinsma, J. 1966. Analysis of growth, development and yield in a spacing experiment with winter rye (Secale cereale L.). Neth. J. Agric. Sci. 14:198213.Google Scholar
Cardina, J., Johnson, G. A., and Sparrow, D. H. 1997. The nature and consequence of weed spatial distribution. Weed Sci. 45:364373.Google Scholar
Cardina, J. and Norquay, H. M. 1997. Seed production and seedbank dynamics in subthreshold velvetleaf (Abutilon theophrasti) populations. Weed Sci. 45:8590.Google Scholar
Cardina, J., Sparrow, D. H., and McCoy, E. L. 1995. Analysis of spatial distribution of common lambsquarters (Chenopodium album) in notill soybean (Glycine max). Weed Sci. 43:258268.Google Scholar
Chancellor, R. J. 1970. Seed production by Avena fatua populations in various crops. Proc. 10th British Weed Control Conference, Brighton, pp. 711.Google Scholar
Dessaint, F., Chadoeuf, R., and Barralis, G. 1996. Spatial pattern analysis of weed seeds in the cultivated soil seed bank. J. Appl. Ecol. 28:721730.Google Scholar
Firbank, L. G. and Watkinson, A. R. 1986. Modelling the population dynamics of an arable weed and its effects upon crop yield. J. Appl. Ecol. 23:147159.Google Scholar
Fischer, R. A. and Miles, R. E. 1973. The role of spatial pattern in the competition between crop plants and weeds. A theoretical analysis. Math. Biosci. 18:335350.Google Scholar
Heywood, J. S. and Levin, D. A. 1986. Interactions between seed source, planting arrangement, and soil treatment in determining plant size and root allocation in Phlox drummondii . Oecologia 68:285290.Google Scholar
Holm, L. G., Plucknett, D. L., Pancho, J. V., and Herberger, J. P. 1977. The Worlds Worst Weeds: Distribution and Biology. Honolulu, HA: University of Hawaii Press, pp. 3240.Google Scholar
Légère, A. and Deschenes, J.-M. 1990. Effects of duration of hemp-nettle (Galeopsis tetrahit) interference in oats (Avena sativa) and alfalfa (Medicago sativa). Can. J. Plant Sci. 70:809816.Google Scholar
Lindquist, J. L., Dielman, J. A., Mortensen, D. A., Johnson, G. A., and Wyse-Pester, D. Y. 1998. Economic importance of managing spatially heterogeneous weed populations. Weed Technol. 12:713.Google Scholar
Maun, M. A. and Barrett, S.C.H. 1986. The biology of Canadian weeds. 77. Echinochloa crus-galli (L.) Beauv. Can. J. Plant Sci. 66:739759.Google Scholar
Medd, R. W., Auld, B. A., Kemp, D. R., and Murison, R. D. 1985. The infuence of wheat density and spatial arrangement on annual ryegrass, Lolium rigidum Gaudin, competition. Aust. J. Agric. Res. 36:361371.Google Scholar
Mithen, R., Harper, J. L., and Weiner, J. 1984. Growth and mortality of individual plants as a function of “available area.” Oecologia 62:5760.Google Scholar
Norris, R. F. 1992a. Case history for weed competition/population ecology: barnyardgrass (Echinochloa crus-galli) in sugarbeets (Beta vulgaris). Weed Technol. 6:220227.Google Scholar
Norris, R. F. 1992b. Predicting seed rain in barnyardgrass (Echinochloa crusgalli). IX Colloquium on Weed Biology and Ecology, Dijon, France: European Weed Res. Soc., pp. 377386.Google Scholar
Norris, R. F. 1996. Weed population dynamics: seed production. 2nd Int. Weed Control Cong., Copenhagen, Denmark, pp. 1520.Google Scholar
Norris, R. F. 1999. Ecological implications of using thresholds for weed management. Pages 3158 In Buhler, D. D., ed. Expanding the context of weed management. New York, NY: Food Products Press, The Haworth Press Inc.Google Scholar
Norris, R. F., Elmore, C. L., Rejmánek, M., and Akey, W. C. 2001. Spatial arrangement, density, and competition between barnyardgrass and tomato: crop growth and yield. Weed Sci. 49:6168.Google Scholar
Ottman, M. J. and Welch, L. F. 1989. Planting patterns and radiation interception, plant nutrient concentration, and yield in corn. Agron. J. 81:167174.Google Scholar
Park, S. J., Reinbergs, E., and Song, L.S.P. 1977. Grain yield and its components in spring barley under row and hill plot conditions. Euphytica 26:521526.Google Scholar
Quakenbush, L. S. and Anderson, R. L. 1984. Effect of soybean (Glycine max) interference on eastern black nightshade (Solanum ptycanthum). Weed Sci. 32:638645.Google Scholar
Silander, J. A. Jr. and Pacala, S. W. 1985. Neighborhood predictors of plant performance. Oecologia (Berlin) 66:256263.Google Scholar
Silvertown, J., Holtier, S., Johnson, J., and Dale, P. 1992. Cellular automata models of interspecific competition for space: the effect of pattern on process. J. Ecol. 80:527534.Google Scholar
Thompson, B. K., Weiner, J., and Warwick, S. I. 1991. Size-dependent reproductive output in agricultural weeds. Can J. Bot. 69:442446.Google Scholar
Thornton, P. K., Fawcett, R. H., Dent, J. B., and Perkins, T. J. 1990. Spatial weed distribution and economic thresholds for weed control. Crop Prot. 9:337342.Google Scholar
Van Groenendael, J. M. 1988. Patchy distribution of weeds and some implications for modeling population dynamics: a short literature review. Weed Res. 28:437441.CrossRefGoogle Scholar
Weiner, J. 1982. A neighborhood model for annual-plant interference. Ecology 63:12371241.Google Scholar
Weiner, J. 1988. The influence of competition on plant reproduction. Pages 228245 In Lovett Doust, J. and Lovett Doust, L., eds. Plant Reproductive Ecology; Patterns and Strategies. New York, NY: Oxford University Press, Inc.Google Scholar
Wiles, L. J., Oliver, G. W., York, A. C., Gold, H. J., and Wilkerson, G. G. 1992. Spatial distribution of broadleaf weeds in North Carolina soybean (Glycine max) fields. Weed Sci. 40:554557.CrossRefGoogle Scholar
Zanin, G., Berti, A., and Riello, L. 1998. Incorporation of weed spatial variability into the weed control decision-making process. Weed Res. 38:107118.Google Scholar
Zanin, G. and Sattin, M. 1988. Threshold level and seed production of velvetleaf (Abutilon theophrasti Medicus) in maize. Weed Res. 28:347352.Google Scholar