Hostname: page-component-586b7cd67f-t8hqh Total loading time: 0 Render date: 2024-11-24T16:43:02.441Z Has data issue: false hasContentIssue false

A POPULATION MODEL FOR PLANT GROWTH AND DEVELOPMENT: COUPLING COTTON–HERBIVORE INTERACTION1

Published online by Cambridge University Press:  31 May 2012

Abstract

A general population model for cotton growth and development is presented. The model captures the essential properties of the biological processes, and is sufficiently flexible to the incorporation of complex physiological and behavioral characteristics. The model has been used successfully to simulate the growth and development of Acala SJ-II cotton in California. The mathematical framework for coupling plants and herbivores has been presented, and the biological implications of their damage to the plant examined in a very general way.

Type
Articles
Copyright
Copyright © Entomological Society of Canada 1977

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

Bacheler, J. S. and Bradley, J. R. Jr., 1975. Effect of temperature on development and mortality of the boll weevil egg stage. Environ. Ent. 4: 319320.CrossRefGoogle Scholar
Bacheler, J. S., Jones, J. W., Bradley, J. R., and Bowen, H. D.. 1975. The effect of temperature on development and mortality of boll weevil immature stages. Environ. Ent. 4: 808810.CrossRefGoogle Scholar
Courant, R. and Hilbert, D.. 1962. Methods of mathematical physics, Vol. II. Interscience, New York, London and Sydney.Google Scholar
Cushman, R. A. 1911. Studies in the biology of the boll weevil in the Mississippi delta region of Louisiana. J. econ. Ent. 4: 432448.Google Scholar
Duncan, W. G. 1971. SIMCOT, a simulator of cotton growth and yield. Proc. of workshop on tree growth dynamics and modeling, pp. 115118. Duke Univ.Google Scholar
Duncan, W. G., Baker, D. N., and Hesketh, J. D.. 1971. Simulation of growth and yield in cotton, III. A computer analysis of the nutritional theory, p. 78. Proc. Beltwide Cotton Prod. Res. Conf.Google Scholar
Evans, L. T. 1975. Crop physiology: some case histories. Cambridge Univ. Press. 374 pp.Google Scholar
Fick, G. W. and Loomis, R. S.. 1974. Simulation of sugar beet ecology from physiology information. In Evans, L. T. (Ed.), Crop physiology. Cambridge Univ. Press.Google Scholar
Fye, R. E., Patana, R., and McAda, W. C.. 1969. Developmental periods for boll weevils reared at several constant and fluctuating temperatures. J. econ. Ent. 62: 14021405.Google Scholar
Gutierrez, A. P., Falcon, L. A., Loew, W., Leipzig, P. A., and van den Bosch, R.. 1975. An analysis of cotton production in California: A model for Acala cotton and the effects of defoliators on its yield. Environ. Ent. 4: 125136.CrossRefGoogle Scholar
Gutierrez, A. P., Butler, G. D., Wang, Y., and Westphal, D.. Cotton pink bollworm—weather interactions. Can. Ent. (in press).Google Scholar
Gutierrez, A. P., Christensen, J. B., Merritt, C. M., Loew, W. B., Summers, C. G., and Cothran, W. R.. 1976. Alfalfa and the Egyptian alfalfa weevil (Coleoptera: Curculionidae). Can. Ent. 108: 635648.CrossRefGoogle Scholar
Gutierrez, A. P., Leigh, T. F., Wang, Y., and Cave, R. D.. 1977. An analysis of cotton production in California: Lygus hesperus injury — an evaluation. Can. Ent. 109: 13751386.CrossRefGoogle Scholar
Hesketh, J. D., Baker, D. N., and Duncan, W. G.. 1971. Simulation of growth and yield on cotton: respiration and carbon balance. Crop. Sci. 11: 394398.Google Scholar
Hesketh, J. D., Baker, D. N., and Duncan, W. G.. 1972. II. Simulation of growth and yield in cotton-environmental control of morphogenesis. Crop Sci. 12: 436439.Google Scholar
Isley, D. 1928. Oviposition of the boll weevil in relation to food. J. econ. Ent. 21: 152155.CrossRefGoogle Scholar
Leigh, T. F. 1972. Growth and fruiting of cotton in response to injury by lygus bugs. Proc. West. Cotton Prod. Conf. Pub. by Cooperative Agric. Ext. Serv., Univ. of California.Google Scholar
Leslie, P. H. 1945. On the use of matrices in certain population mathematics. Biometrika 33: 183212.CrossRefGoogle ScholarPubMed
McKinion, J. M., Jones, J. W., and Hesketh, J. D.. 1974. Analysis of SIMCOT: Photosynthesis and growth, pp. 117124. Res. Conf. Proc. Beltwide Cotton Prod., Memphis.Google Scholar
Oster, G. and Takahashi, Y.. 1974. Models for age-specific interactions in a periodic environment. Ecol. Monog. 44: 483501.CrossRefGoogle Scholar
Richtmyer, R. D. and Morton, K. W.. 1967. Finite difference methods for initial value problems. Interscience, New York, London, and Sydney.Google Scholar
Roach, S. H. 1973. Developmental changes in the boll weevil, Anthonomus grandis, studied with time-lapse photography. Ann. ent. Soc. Am. 66: 2427.Google Scholar
Sinko, J. W. and Streifer, W.. 1967. A new model for age-size structure of a population. Ecology 48: 910918.CrossRefGoogle Scholar
Stapleton, H. N., Buxton, D. R., Watson, F. L., Nolting, K. L., and Baker, D. N.. 1973. Cotton: a computer simulation of cotton growth. Tech. Bull. Ariz. agric. Exp. Stn.Google Scholar
Sterling, W. L. and Adkisson, P. L.. 1970. Seasonal rates of increase for a population of the boll weevil, Anthonomus grandis, in the high and rolling plains of Texas. Ann. ent. Soc. Am. 63: 16961700.Google Scholar
Streifer, W. 1975. Realistic models in population ecology. Adv. theor. Ecol.: 199266.Google Scholar
Von Foerster, H. 1959. Some remarks on changing populations. In Stohlman, F. Jr., (Ed.), The mimetics of cellular proliferation. Grune and Stratton, New York.Google Scholar
Wit, C. R. de, Brouwer, R., and Penning de Vries, F. W. T.. 1970. The simulation of photosynthetic systems, pp. 4770. In Prediction and measurement of photosynthetic productivity. PUDOC, Wageningen, The Netherlands.Google Scholar