Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-20T01:22:18.123Z Has data issue: false hasContentIssue false

An Alternative Approach for Evaluating the Efficacy of Potential Biocontrol Agents of Weeds. 1. Inverse Linear Model

Published online by Cambridge University Press:  12 June 2017

Dan J. Pantone
Affiliation:
Dep. Agron. and Range Sci., Univ. California, Davis, CA 95616
William A. Williams
Affiliation:
Dep. Agron. and Range Sci., Univ. California, Davis, CA 95616
Armand R. Maggenti
Affiliation:
Dep. Nematology, Univ. California, Davis, CA 95616

Abstract

Methods for evaluating the efficacy of potential classical biocontrol agents were outlined for a model biocontrol agent-weed-crop system. A proposed biocontrol agent (the fiddleneck flower gall nematode), its weed host (coast fiddleneck), and wheat were used as representative organisms. An additive experimental design (inverse linear model) was used. Regression of the reciprocal of the average plant biomass of each species onto the density of itself and the other plant species yielded competitive indices that measure the competitive ability of the plants. The results of 2 yr of field experiments revealed a dramatic change in the competitive interaction between fiddleneck and wheat due to the nematode. During the 1986–87 season in the absence of the nematode, fiddleneck intraspecific competition was 33 times stronger than interspecific competition with wheat. In the presence of the nematode, intra- and interspecific competition of fiddleneck were nearly equal. Only the coefficients that measure interspecific competition changed significantly in the presence of the nematode while the coefficients for intraspecific competition did not.

Type
Weed Biology and Ecology
Copyright
Copyright © 1989 by the 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

1. Brown, V. K. 1982. The phytophagous insect community and its impact on early successional habitats. Pages 205213 in Visser, J.H.J. and Minks, A. K., eds. Proc. 5th Int. Symp. on Insect-plant Relationships. Pudoc, Wageningen.Google Scholar
2. Charudattan, R. and Walker, H. L. 1982. Biological Control of Weeds with Plant Pathogens. John Wiley and Sons, New York. 293 pp.Google Scholar
3. Cottam, D. A., Whittaker, J. B., and Malloch, A.J.C. 1986. The effects of chrysomelid beetle grazing and plant competition on the growth of Rumex obtusifolius . Oecologia 70:452456.Google Scholar
4. Cullen, J. M. 1976. Evaluating the success of the programme for the biological control of Chondrilla juncea L. Pages 117121 in Freeman, T. E., ed. Proc. 4th Int. Symp. on the Biol. Control of Weeds. Univ. Florida, Gainesville.Google Scholar
5. Cullen, J. M., Kable, P. F., and Catt, M. 1973. Epidemic spread of a rust imported for biological control. Nature 244:462464.Google Scholar
6. Draper, N. and Smith, H. 1981. Applied Regression Analysis. 2nd ed. Pages 241250. John Wiley and Sons, New York.Google Scholar
7. Friend, D. A. 1977. The ecology of Amsinckia in wheat crops in Victoria. J. Aust. Inst. Agric. Sci. 152:11311137.Google Scholar
8. Godfrey, G. H. 1940. Ecological specialization in the stem- and bulb-infesting nematode, Ditylenchus dipsaci var. Amsinckiae . Phytopathology 38:4153.Google Scholar
9. Goeden, R. D. 1983. Critique and revision of Harris' scoring system for selection of insect agents in biological control of weeds. Prot. Ecol. 5: 287301.Google Scholar
10. Groves, R. H. and Williams, J. D. 1975. Growth of skeletonweed (Chondrilla juncea L.) as affected by growth of subterranean clover (Trifolium subteraneum L.) and infection by Puccinia chondrillina Bubak. & Syd. Aust. J. Agric. Res. 26:975983.CrossRefGoogle Scholar
11. Harper, J. L. 1960. Factors controlling plant numbers. Pages 119132 in Harper, J. L., ed. The Biology of Weeds. Blackwell, Oxford.Google Scholar
12. Harper, J. L. 1977. Population Biology of Plants. Pages 483512. Academic Press, London.Google Scholar
13. Harris, P. 1973. The selection of effective agents for the biological control of weeds. Can. Entomol. 105:14951503.CrossRefGoogle Scholar
14. Harris, P. 1973. Insects in the population dynamics of plants. Pages 201209 in Emden, H. F., ed. Insect/plant Relationships. Blackwell, Oxford.Google Scholar
15. Harris, P. 1985. Biocontrol of weeds: Bureaucrats, botanists, beekeepers and other bottlenecks. Pages 312 in Delfosse, E. S., ed. Proc. VI Int. Symp. Biol. Control Weeds. Agric. Canada.Google Scholar
16. Harris, P. 1986. Biological control of weeds. Pages 123138 in Franz, J. M., ed. Biological Plant and Health Protection, Biological Control of Plant Pests and Vectors of Human and Animal Diseases. Gustav Fischer Verlag, New York.Google Scholar
17. Hasan, S. and Wapshere, A. J. 1973. The biology of Puccinia chondrillina, a potential biological control agent of skeletonweed. Ann. Appl. Biol. 74:325332.CrossRefGoogle Scholar
18. Huffaker, C. B. 1957. Fundamentals of biological control of weeds. Hilgardia 27:101157.CrossRefGoogle Scholar
19. Huffaker, C. B. 1964. Fundamentals of biological weed control. Pages 74117 in DeBach, P. and Schlinger, E. I., eds. Biological Control of Insect Pests and Weeds. Chapman and Hall, London.Google Scholar
20. Huffaker, C. B. and Kennett, C. E. 1952. Ecological tests on Chrysolina gemellata (Rossi) and C. Hyperici Forst, in the biological control of Klamath weed. J. Econ. Entomol. 454:1061–64.Google Scholar
21. Julien, M. H., Kerr, J. D., and Chan, R. R. 1984. Biological control of weeds: an evaluation. Prot. Ecol. 7:325.Google Scholar
22. McBrien, H., Harmsen, R., and Crowder, A. 1983. A case of insect grazing affecting plant succession. Ecology 64:10351039.Google Scholar
23. Myers, J. H. How many insect species are necessary for successful biocontrol of weeds? Pages 7782 in Delfosse, E. S., ed. Proc. VI Int. Symp. Biol. Control Weeds. Agric. Canada.Google Scholar
24. Nagamine, C. and Maggenti, A. R. 1980. Blinding of shoots and a leaf gall in Amsinckia intermedia induced by Anguina amsinckiae (Steiner and Scott, 1934) (Nemata, Tylenchidae), with a note on the absence of a rachis in A. amsinckiae . J. Nematol. 12:129132.Google Scholar
25. Pantone, D. J., Brown, S. M., and Womersley, C. 1985. Biological control of fiddleneck. Calif. Agric. 39:45.Google Scholar
26. Pantone, D. J. and Womersley, C. 1986. The distribution of flower galls caused by Anguina amsinckiae on the weed, common fiddleneck (Amsinckia intermedia). Rev. de Nematol. 9:185189.Google Scholar
27. Radosevitch, S. R. 1987. Methods to study interactions among crops and weeds. Weed Technol. 1:190198.Google Scholar
28. Rice, K. J. and Menke, J. W. 1985. Competitive reversals and environment dependent resource partitioning in Erodium . Oecologia 67: 430434.Google Scholar
29. SAS Institute. 1985. SAS User's Guide: Statistics. Version 5 ed. Pages 433506 and 655–709. SAS Inst., Cary, NC.Google Scholar
30. Sibma, L. J., Kort, J., and de Wit, C. T. 1964. Experiments on competition as a means of detecting possible damage by nematodes. Jaarb. Inst. voor Biologisch en Scheikundig 1964:119124.Google Scholar
31. Spitters, C.J.T. 1983. An alternative approach to the analysis of mixed cropping experiments. 1. Estimation of competition effects. Neth. J. Agric. Sci. 31:111.Google Scholar
32. Templeton, G. E. and Smith, R. J. Jr. 1977. Managing weeds with pathogens. Pages 167176 in Horsfall, J. G. and Cowling, E. B., eds. Plant Disease: An Advanced Treatise. Volume 1. Academic Press, New York.Google Scholar
33. Whittaker, J. B. 1979. Invertebrate grazing competition and plant dynamics. Pages 207222 in Anderson, R. M., Turner, B. D., and Taylor, L. R., eds. Population Dynamics: the 20th Symp. Br. Ecol. Soc. Blackwell Scientific Publications, Oxford.Google Scholar
34. Wilson, F. 1960. A review of the biological control of insects and weeds in Australia and Australian New Guinea. Tech. Communications of the Commonwealth Inst. Biol. Control. No. 1. 102 pp.Google Scholar
35. Wonnacott, R. J. and Wonnacott, T. H. 1979. Econometrics. 2nd ed. John Wiley and Sons, New York. 580 pp.Google Scholar
36. Zar, J. H. 1974. Biostatistical Analysis. Page 268. Prentice-Hall, Englewood Cliff, NJ.Google Scholar