Modelling predation in functional response

Ecological Modelling

Volumn 198, Issue 1-2, 2006, Pages 154-162

  Fenlon, John S ^a   Faddy, Malcolm J ^b  

^a UNIVERSITY OF WARWICK   (United Kingdom)

^b QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

Beta binomial distribution; Counting processes; Maximum likelihood; Over dispersed binomial distribution; Predator prey; Stochastic models

Indexed keywords

BIODIVERSITY; DATA REDUCTION; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; RANDOM PROCESSES;

BETA-BINOMIAL DISTRIBUTION; COUNTING PROCESSES; OVER-DISPERSED BINOMIAL DISTRIBUTION; PREDATOR PREY SYSTEMS;

BIOASSAY;

BIOASSAY; DATA INTERPRETATION; DISPERSION; ECOLOGICAL MODELING; FUNCTIONAL RESPONSE; PREDATION; PREDATOR-PREY INTERACTION; PREY AVAILABILITY; STOCHASTICITY;

EID: 33747856459     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolmodel.2006.04.002     Document Type: Article

References (32)

1. Bancroft J.S., and Margolies D.C. An individual-based model of an acarine tritrophic system: lima bean, Phaseolus lunatas L., two-spotted spider mite, Tetranychus urticae (Acari: Tetranychidae) and Phytoseiulus persimilis (Acari: Phytoseiidae). Ecol. Model. 123 (1999) 161-181
2. Beddington J.R., Hassell M.P., and Lawton J.H. The components of arthropod predation II: the predator rate of increase. J. Anim. Ecol. 45 (1976) 165-185
3. Bernstein C. A simulation model for an acarine predator-prey system (Phytoseiulus persimilis-Tetranychus urticae). J. Anim. Ecol. 45 (1985) 165-185
4. Casas J., and Hulliger B. Statistical analysis of functional response experiments. Biocontrol Sci. Technol. 4 (1994) 133-145
5. Collett D. Modelling Binary Data. second ed. (2002), Chapman and Hall/CRC, Boca Raton 408 pp
6. Cox D.R., and Miller H.D. The Theory of Stochastic Processes (1965), Chapman and Hall, London 398 pp
7. Curry G.L., and DeMichelle D.W. Stochastic analysis for the description and synthesis of predator-prey systems. Can. Entomol. 109 (1977) 1167-1174
8. Curry G.L., and Feldman R.M. Stochastic predation model with depletion. Can. Entomol. 111 (1979) 465-470
9. Faddy M.J. Extended Poisson process modelling and analysis of count data. Biometrical J. 39 (1997) 431-440
10. Faddy M.J., and Fenlon J.S. Stochastic modelling of the invasion process of nematodes in fly larvae. Appl. Stat. 48 (1999) 31-37
11. Fernando M.H.J.P., and Hassell M.P. Predator-prey responses in an acarine system. Res. Popul. Ecol. 22 (1980) 301-322
12. Finney D.J. Probit Analysis. third ed. (1971), Cambridge University Press, Cambridge 333 pp
13. Genstat. In: Payne R.W. (Ed). The Guide to Genstat Release 6.1 3 vol. (2002), VSN International, Oxford, UK
14. Hassell M.P., Lawton J.H., and Beddington J.R. Sigmoidal functional responses by invertebrate predators and parasitoids. J. Anim. Ecol. 46 (1977) 249-262
15. Hassell M.P. The Spatial and Temporal Dynamics of Host-Parasitoid Interactions (2000), Oxford University Press, Oxford 208 pp
16. Holling C.S. The components of predation as revealed by a study of small mammal predation of the European pine sawfly. Can. Entomol. 91 (1959) 293-320
17. Holling C.S. Some characteristics of simple types of predation and parasitism. Can. Entomol. 91 (1959) 385-398
18. Juliano S.A. Nonlinear curve fitting. In: Scheiner S.M., and Gurevitch J. (Eds). Design and Analysis of Ecological Experiments (2001), Oxford University Press 178-196
19. Legaspi Jr. B.C., Carruthers R.I., and Morales-Ramos J.A. Functional response as a component of a dynamic simulation in biological control: the Catolaccus-boll weevil system. Ecol. Model. 89 (1996) 43-57
20. Lindsey J.K. Models for Repeated Measurements. second ed. (1999), Oxford University Press 515 pp
21. ®, 1997. Version 5 User's Guide. The MathWorks, Inc., Natick, MA, USA.
22. Mills N.J., and Getz W.M. Modelling the biological control of insect pests: a review of host-parasitoid models. Ecol. Model. 92 (1996) 121-143
23. Morales-Ramos J.A., Legaspi Jr. B.C., and Carruthers R.I. Modification of the random-search type II functional response equation for incorporation into simulation models. Ecol. Model. 91 (1996) 249-253
24. Morgan B.J.T. Analysis of Quantal Response Data (1992), Chapman and Hall, London 512 pp
25. Morgan B.J.T. Applied Stochastic Modelling (2000), Arnold, London 297 pp
26. Nachman G. Systems analysis of acarine predator-prey interactions. I: a stochastic simulation model of spatial processes. J. Anim. Ecol. 56 (1987) 247-265
27. Rogers D.J. Random search and insect population models. J. Anim. Ecol. 41 (1972) 369-383
28. Rogers D.J., and Hassell M.P. General models for insect parasite and predator searching behaviour: interference. J. Anim. Ecol. 43 (1974) 239-253
29. Skirvin D.J., and Fenlon J.S. Plant species modifies the functional response of phytoseiulus persimilis (Acari: Phytoseiidae) to Tetranychus urticae (Acari: Tetranychidae): implications for biological control. Bull. Entomol. Res. 91 (2001) 61-67
30. Skirvin D.J., De Courcy Williams M.E., Fenlon J.S., and Sunderland K.D. Modelling the effects of plant species on biocontrol effectiveness in ornamental nursery crops. J. Appl. Ecol. 39 (2002) 469-480
31. Solomon M.E. The natural control of animal populations. J. Anim. Ecol. 18 (1949) 1-35
32. Trexler J.C., McCulloch C.E., and Travis J. How can the functional response best be determined?. Oecologia 76 (1988) 206-214