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Functional Relationships of Growth and Competitiveness in Perennial Weeds and Cotton (Gossypium hirsutum)

Published online by Cambridge University Press:  12 June 2017

Jodie S. Holt  and
Deborah R. Orcutt
Jodie S. Holt
Affiliation:
Dep. Botany and Plant Sci. Univ. California, Riverside, CA 92521
Deborah R. Orcutt
Affiliation:
Dep. Botany and Plant Sci. Univ. California, Riverside, CA 92521
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Abstract

Growth characteristics and competitive relationships of cotton and three perennial weeds (johnsongrass, purple nutsedge, and yellow nutsedge) were investigated at the USDA Cotton Research Station in Shafter, CA. In growth analysis experiments, yellow nutsedge and johnsongrass had highest values for height, biomass, leaf area production, growth rate, and photosynthetic efficiency. The weeds exhibited greater overall resource use and production efficiency than cotton, while cotton attained greater leafiness and canopy closure than weeds over the 10-wk experiment. Linear correlation indicated that most growth variables were significantly correlated with aggressivity (competitiveness); however, all correlation coefficients were less than 0.80. Stepwise multiple regression, using aggressivity as the dependent variable, defined 4 growth variables out of 12 that best described competitiveness. These were unit leaf rate (ULR), height, relative growth rate (RGR), and initial propagule weight (PWT). Thus, parameters of light utilization (ULR, height) and early establishment (RGR, PWT) were best predictors of competitive success in this system.

Keywords

Johnsongrass, Sorghum halepense (L.) Pers. # SORHApurple nutsedge, Cyperus rotundus L. #CYPROyellow nutsedge, C. esculentus L. #CYPEScotton, Gossypium hirsutum L. Acala‘SJ2′Aggressivitygrowth analysisinterferencereplacement seriesCYPESCYPROSORHA
Type
Weed Biology and Ecology
Information
Weed Science , Volume 39 , Issue 4 , December 1991 , pp. 575 - 584
Copyright
Copyright © 1992 by the Weed Science Society of America 

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References

Literature Cited

1. Austin, M. P. 1982. Use of a relative physiological performance value in the prediction of performance in multispecies mixtures from monoculture performance. J. Ecol. 70:559–570.CrossRefGoogle Scholar
2. Baker, H. G. 1974. The evolution of weeds. Annu. Rev. Ecol. Syst. 5:1–24.Google Scholar
3. Black, C. C., Chen, T. M., and Brown, R. H. 1969. Biochemical basis for plant competition. Weed Sci. 17:338–344.Google Scholar
4. Bleasdale, J.K.A. 1960. Studies on plant competition. Pages 133–142 in Harper, J. L., ed. The Biology of Weeds. Blackwell Sci. Publ., Oxford, UK.Google Scholar
5. Bridges, D. C. and Chandler, J. M. 1988. Influence of cultivar height on competitiveness of cotton (Gossypium hirsutum) with johnsongrass (Sorghum halepense). Weed Sci. 36:616–620.Google Scholar
6. Daniel, C. and Wood, F. S. 1980. Fitting Equations to Data: Computer Analysis of Multifactor Data. 2nd ed. John Wiley and Sons, New York. Pages 83–104.Google Scholar
7. Draper, N. R. and Smith, H. 1981. Applied Regression Analysis. 2nd ed. John Wiley and Sons, New York. Pages 141–192, 294–379.Google Scholar
8. Ehleringer, J. R. 1978. Implications of quantum yield differences on the distributions of C3 and C4 grasses. Oecologia 31:255–267.Google Scholar
9. Elmore, C. D., Brown, M. A., and Flint, E. P. 1983. Early interference between cotton (Gossypium hirsutum) and four weed species. Weed Sci. 31:200–207.Google Scholar
10. Epp, G. A. and Aarssen, L. W. 1989. Predicting vegetation patterns from attributes of plant growth in grassland species. Can. J. Bot. 67:2953–2959.CrossRefGoogle Scholar
11. Erickson, R. O. 1976. The modeling of plant growth. Annu. Rev. Plant Physiol. 27:407–434.Google Scholar
12. Evans, G. C. 1972. The Quantitative Analysis of Plant Growth. Blackwell Scientific Publications, Oxford, UK. Pages 246–332.Google Scholar
13. Gaudet, C. L. and Keddy, P. A. 1988. A comparative approach to predicting competitive ability from plant traits. Nature 334:242–243.Google Scholar
14. Gleeson, A. C. and McGilchrist, C. A. 1980. Mixture diallel experiments with unequal proportions of genotypes. J. Agric. Sci. 95:525–532.Google Scholar
15. Goodell, P. B., Plant, R. E., Kerby, T. A., Strand, J. F., Wilson, L. T., Zelinski, L., Young, J. A., Corbett, A., Horrocks, R. D., and Vargas, R. N. 1990. CALEX/Cotton: an integrated expert system for cotton production and management. Calif. Agric. 44:18–21.Google Scholar
16. Grace, J. B. 1990. On the relationship between plant traits and competitive ability. Pages 51–65 in Grace, J. B. and Tilman, D., eds. Perspectives on Plant Competition. Academic Press, New York.Google Scholar
17. Grime, J. P. 1979. Plant Strategies and Vegetation Processes. John Wiley and Sons, Inc., Chichester, UK. Pages 7–78.Google Scholar
18. Grime, J. P. and Hunt, R. 1975. Relative growth rate, its range and adaptive significance in a local flora. J. Ecol. 63:393–422.Google Scholar
19. Harper, J. L. 1977. The Population Biology of Plants. Academic Press, London, UK. Pages 151–381.Google Scholar
20. Holm, L. G., Plucknett, D. L., Pancho, J. V., and Herberger, J. P. 1977. The World's Worst Weeds: Distribution and Biology. Univ. Press of Hawaii, Honolulu. Pages 8–24, 54–61, 125–133.Google Scholar
21. Holt, J. S. and Orcutt, D. R. 1988. Cotton/weed community dynamics as a function of germination, growth parameters, and temperature responses. Calif. Cotton Prog. Rep., Univ. Calif. Coop. Ext. Rep. Pages 51–54.Google Scholar
22. Holt, J. S. 1988. Ecological and physiological characteristics of weeds. Pages 7–23 in Altieri, M. A. and Liebman, M. Z., eds. Weed Management in Agroecosystems: Ecological Approaches. CRC Press, Inc., Boca Raton, FL.Google Scholar
23. Horak, M. J. and Holt, J. S. 1986. Isozyme variability and breeding systems in populations of yellow nutsedge (Cyperus esculentus). Weed Sci. 34:538–543.Google Scholar
24. Horak, M. J., Holt, J. S., and Ellstrand, N. C. 1987. Genetic variation in yellow nutsedge (Cyperus esculentus). Weed Sci. 35:506–512.Google Scholar
25. Horowitz, M. 1973. Competitive effects of Cynodon dactylon, Sorghum halepense, and Cyperus rotundus on cotton and mustard. Exp. Agric. 9:263–273.Google Scholar
26. Hunt, R. 1982. Plant Growth Curves: The Functional Approach to Plant Growth Analysis. Univ. Park Press, Baltimore, MD. Pages 14–60.Google Scholar
27. Hunt, R. 1978. Plant Growth Analysis. Edward Arnold, Ltd., London, England. Pages 8–25, 39–49.Google Scholar
28. Joenje, W. and Kropff, M. J. 1987. Relative time of emergence, leaf area development and plant height as major factors in crop-weed competition. Br. Crop Prot. Conf. – Weeds. 3:971–978.Google Scholar
29. Keeley, P. E. (coordinator). 1973. Survey of weeds on cotton farms in the San Joaquin Valley. Proc. Calif. Weed Conf. 27:37–47.Google Scholar
30. Keeley, P. E. and Thullen, R. J. 1989. Growth and interaction of johnsongrass (Sorghum halepense) with cotton (Gossypium hirsutum). Weed Sci. 37:339–344.Google Scholar
31. Keeley, P. E. and Thullen, R. J. 1983. Influence of yellow nutsedge (Cyperus esculentus)-free periods on yield of cotton (Gossypium hirsutum). Weed Sci. 31:803–807.Google Scholar
32. Keeley, P. E. and Thullen, R. J. 1978. Light requirements of yellow nutsedge (Cyperus esculentus) and light interception by crops. Weed Sci. 26:10–16.Google Scholar
33. Kropff, M. J. 1988. Modelling the effects of weeds on crop production. Weed Res. 28:465–471.Google Scholar
34. Lapham, J. 1987. Population dynamics and competitive effects of Cyperus esculentus (yellow nutsedge) – prediction of cost-effective control strategies. 1987 Br. Crop Prot. Conf. – Weeds 3:1043–1050.Google Scholar
35. McWhorter, C. G. 1989. History, biology, and control of johnsongrass. Rev. Weed Sci. 4:85–121.Google Scholar
36. Miller, T. E. and Schemske, D. W. 1990. An experimental study of competitive performance in Brassica rapa (Cruciferae). Am. J. Bot. 77:993–998.Google Scholar
37. Patterson, D. T. 1982. Shading responses of purple and yellow nutsedges (Cyperus rotundus and C. esculentus). Weed Sci. 30:25–30.Google Scholar
38. Patterson, D. T. 1985. Comparative ecophysiology of weeds and crops. Pages 101–129 in Duke, S. O., ed. Weed Physiology. Vol. I. Reproduction and Ecophysiology. CRC Press, Inc., Boca Raton, FL.Google Scholar
39. Patterson, D. T., Meyer, C. R., and Quimby, P. C. Jr. 1978. Effects of irradiance on relative growth rates, net assimilation rates, and leaf area partitioning in cotton and three associated weeds. Plant Physiol. 62:14–17.CrossRefGoogle ScholarPubMed
40. Patterson, M. G., Buchanan, G. A., Street, J. E., and Crowley, R. H. 1980. Yellow nutsedge (Cyperus esculentus) competition with cotton (Gossypium hirsutum). Weed Sci. 28:327–329.Google Scholar
41. Pearcy, R. W., Tumosa, N., and Williams, K. 1981. Relationships between growth, photosynthesis and competitive interactions for a C3 and a C4 plant. Oecologia 48:371–376.Google Scholar
42. Potter, J. R. and Jones, J. W. 1977. Leaf area partitioning as an important factor in growth. Plant Physiol. 59:10–14.Google Scholar
43. Radosevich, S. R. and Holt, J. S. 1984. Weed Ecology: Implications for Vegetation Management. John Wiley and Sons, New York. Pages 93–241.Google Scholar
44. Ross, M. A. and Harper, J. L. 1972. Occupation of biological space during seedling establishment. J. Ecol. 60:77–88.Google Scholar
45. Ross, M. A. and Lembi, C. A. 1985. Applied Weed Science. Burgess Publishing Co., Minneapolis, MN. Pages 216–230.Google Scholar
46. Roush, M. L., Jordan, N., and Holt, J. S. 1989. Ecological basis for weed biology in IPM. Pages 137–156 in Glass, E. H., ed. Proc. National IPM Symposium/Workshop on Targeting Research for IPM Implementation. National IPM Coordinating Comm. Google Scholar
47. Roush, M. L. and Radosevich, S. R. 1985. Relationships between growth and competitiveness of four annual weeds. J. Appl. Ecol. 22:895–205.CrossRefGoogle Scholar
48. SAS Institute, Inc. 1985. SAS® User's Guide: Statistics. (Version 5 ed.) SAS Inst., Inc., Cary, NC.Google Scholar
49. Shaw, W. C. 1982. Integrated weed management systems technology for pest management. Weed Sci. Suppl. 30:2–12.Google Scholar
50. Sokal, R. R. and Rohlf, F. J. 1981. Biometry: The Principles and Practices of Statistics in Biological Research. 2nd ed. W. H. Freeman & Co., New York. Pages 617–642.Google Scholar
51. Steel, R.G.D. and Tome, J. H. 1980. Principles and Procedures of Statistics. A Biomedical Approach. 2nd Edition. McGraw-Hill Book Co., New York. Pages 172–284.Google Scholar
52. Stoller, E. W. and Sweet, R. D. 1987. Biology and life cycle of purple and yellow nutsedges (Cyperus rotundus and C. esculentus). Weed Technol. 1:66–73.Google Scholar
53. Wit, C. T. de. 1960. On competition. Versl. Landbouwkd. Onderz. 66:1–82.Google Scholar
54. Zimdahl, R. L. 1980. Weed Crop Competition: A Review. Int. Plant Prot. Ctr., Corvallis, OR. Pages 61–65.Google Scholar