Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-27T09:16:58.583Z Has data issue: false hasContentIssue false

Weed Demography and Population Dynamics: Implications for Threshold Management

Published online by Cambridge University Press:  12 June 2017

Nicholas Jordan*
Affiliation:
Division of Science, Northeast Missouri State University, Kirksville, MO 63501

Abstract

Threshold weed management methods have recently been elaborated to consider effects of threshold management on weed population dynamics. Such economic optimum thresholds are calculated using population-dynamics models which require detailed information about weed demography, including seed production (as affected by events between germination and seed dispersal), seed dispersal, and seed survival and movement in soil. Factors affecting any of these aspects of demography appear likely to modulate the growth rate of a sub-threshold population and therefore to influence the economic optimum threshold value. To test this conjecture and evaluate weed threshold management, including associated risk, improved understanding is particularly needed of weed seed dispersal, seedbank processes, and unpredictable demographic variation.

Type
Symposium
Copyright
Copyright © 1990 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. Aldrich, R. J. 1984. Weed-Crop Ecology. Wadsworth, Inc., Belmont, No. Scituate, Mass. Google Scholar
2. Altieri, M. A., and Liebman, M. 1988. Weed management: ecological guidelines. p. 331337 in Altieri, M. A., and Liebman, M., eds. Weed Management in Agroecosystems: Ecological Approaches. CRC Press, Boca Raton, Fla. Google Scholar
3. Bauer, T. A., and Mortensen, D. A. 1991. A comparison of economic and economic optimum thresholds for two annual weeds in soybeans. Weed Technol., submitted.Google Scholar
4. Caswell, H. 1989. Matrix Population Models: Construction, Analysis, and Interpretation. Sinauer Associates, Sunderland, Mass. Google Scholar
5. Cavers, P. B. 1983. Seed Demography. Can. J. Bot. 61:35783590.Google Scholar
6. Cavers, P. B., and Benoit, D. L. 1989. Seed banks in arable land. p. 309328 in Leck, M. A., Parker, V. T., and Simpson, R. L., eds. Ecology of Soil Seed Banks, Academic Press, San Diego, Calif. Google Scholar
7. Charudattan, R., and Deloach, C. J. Jr. 1988. Management of pathogens and insects for weed control in agroecosystems. p. 245264 in Altieri, M. A., and Liebman, M., eds. Weed Management in Agroecosystems: Ecological Approaches. CRC Press, Boca Raton, Fla. Google Scholar
8. Cousens, R. D. 1986. The use of population models in the study of the economics of weed control. Proc. Eur. Weed Res. Soc. Symposium 1986, Economic Weed Control. p. 269276.Google Scholar
9. Cousens, R., Doyle, C. J., Wilson, B. J., Cussans, G. W. 1986. Modelling the economics of controlling Avena fatua in winter wheat. Pestic. Sci. 17:1012.Google Scholar
10. Cousens, R. 1987. Theory and reality of weed control thresholds. Plant Prot. Q. 2:1320.Google Scholar
11. Cussans, G. W., Cousens, R. D., and Wilson, B. J. 1986. Thresholds for weed contro–the concepts and their interpretation. Proc. Eur. Weed Res. Soc. Symposium 1986, Economic Weed Control, p. 253260.Google Scholar
12. Darmency, H., and Gasquez, J. 1990. Appearance and spread of triazine resistance in common lambsquarters (Chenopodium album). Weed Technol. 4:173177.Google Scholar
13. Doyle, C. J., Cousens, R., and Moss, S. R. 1986. A model of the economics of controlling Alopecurus myosuroides Huds. in winter wheat Crop. Prot. 5:143150.Google Scholar
14. Forcella, F. 1991. Weed seedling emergence models are practical tools for weed control. Abstr. Weed Sci. Soc. Sci. Am. 31:41.Google Scholar
15. Froud-Williams, R. J. 1988. Changes in weed flora with different tillage and agronomic management systems. p. 213236 in Altieri, M. A., and Liebman, M., eds. Weed Management in Agroecosystems: Ecological Approaches. CRC Press, Boca Raton, Fla. Google Scholar
16. Harper, J. L., Lovell, P. H., and Moore, K. G. 1970. The shapes and sizes of seeds. Annu. Rev. Ecol. Syst. 1:327356.Google Scholar
17. Maxwell, B. D. 1991. Weed thresholds: the space and time components and considerations for herbicide resistance evolution. Abstr. Weed Sci. Soc. Am. 31:87.Google Scholar
18. Maxwell, B. D., Roush, M. L., and Radosevich, S. R. 1990. Predicting the evolution and dynamics of herbicide resistance in weed populations. Weed Technol. 4:213.Google Scholar
19. Naylor, R.E.L. 1985. Establishment and peri-establishment mortality. p. 95110 in White, J., Ed., Studies on Plant Demography. Academic Press, London.Google Scholar
20. Norris, R. F. 1984. Weed thresholds in relation to long-term population dynamics. Proc. West. Weed Sci. Soc. 37:3844.Google Scholar
21. Norris, R. F. 1989. Seed production and variation in seed size in barnyardgrass, Echinochloa crus-galli (L.) Beauv. Abstr. Weed Sci. Soc. Am. 29:66.Google Scholar
22. Pacala, S. W., and Silander, J. A. Jr. 1985. Neighborhood models of plant population dynamics. I. Single-species models of annuals. Am. Nat. 125:385411.Google Scholar
23. Pacala, S. W., and Silander, J. A. Jr. 1990. Field tests of neighborhood population dynamic models of two annual weed species. Ecol. Monogr. 60:113134.Google Scholar
24. Radosevich, S. R., and Holt, J. S. 1984. Weed Ecology: Implications for Vegetarian Management John Wiley and Sons, New York.Google Scholar
25. Roberts, H. A. 1981. Seed banks in soils. p. 135 in Coaker, T. H., ed. Advances in Applied Biology. Academic Press, London.Google Scholar
26. Roush, M. L., and Radosevich, S. R. 1988. Competition and community dynamics in a summer-annual weed community. Abstr. Weed Sci. Soc. Am. 28:58.Google Scholar
27. Roush, M. L., Jordan, N., and Holt, J. S. 1989. Ecological basis for weed biology in IPM. p. 137156 in National IPM Coordinating Committee, eds. Proceedings National Integrated Pest Management Symposium/Workshop. New York State Agricultural Experiment Station, Geneva, N.Y. Google Scholar
28. Roush, M. L., Radosevich, S. R., and Maxwell, B. D. 1990. Future outlook or herbicide-resistance research. Weed Technol. 4:208214.Google Scholar
29. Sagar, G. R., and Mortimer, A. M. 1976. An approach to the study of the population dynamics of plants with special reference to weeds. Appl. Biol. 1:147.Google Scholar
30. Swartzman, G. L., and Kaluzny, S. P. 1987. Ecological Simulation Primer. Macmillan Publishing Co., New York.Google Scholar
31. Symonides, E. 1988. Population dynamics of annual plants. p. 221248 in Davy, A. J., Hutchings, M. J., and Watkinson, A. R., eds. Plant Population Ecology. Blackwell Scientific Populations, Oxford.Google Scholar
32. Thrall, P. H., Pacala, S. W., and Silander, J. A. Jr. 1989. Oscillatory dynamics in populations of an annual weed species Abutilon theophrasti . J. Ecol. 77:11351149.Google Scholar
33. Weaver, S. E. 1990. Size-dependent economic thresholds for velvetleaf (Abutilon theophrasti Medic.), cocklebur (Xanthium strumarium L.) and jimsonweed (Datura stramonium L.) in soybeans. Abstr. Weed Sci. Soc. Am. 30:100.Google Scholar
34. Wilson, R. G. 1988. Biology of weed seeds in the soil. p. 2539 in Altieri, M. A., and Liebman, M., eds. Weed Management in Agroecosystems: Ecological Approaches. CRC Press, Boca Raton, Fla. Google Scholar