Numerical response
The numerical response in ecology is the change in predator density as a function of change in prey density. The term numerical response was coined by M. E. Solomon in 1949.[1] It is associated with the functional response, which is the change in predator's rate of prey consumption with change in prey density. As Holling notes, total predation can be expressed as a combination of functional and numerical response.Cite error: A <ref> tag is missing the closing </ref> (see the help page).
Aggregational response
The aggregational response, as defined by Readshaw in 1973, is a change in predator population due to immigration into an area with increased prey population.[2] In an experiment conducted by Turnbull in 1964, he observed the consistent migration of spiders from boxes without prey to boxes with prey. He proved that hunger impacts predator movement.[3]
Riechert and Jaeger studied how predator competition interferes with the direct correlation between prey density and predator immigration.[4][5] One way this can occur is through exploitation competition: the differential efficiency in use of available resources, for example, an increase in spiders' web size (functional response). The other possibility is interference competition where site owners actively prevent other foragers from coming in vicinity.
Ecological relevance
The concept of numerical response becomes practically important when trying to create a strategy for pest control. The study of spiders as a biological mechanism for pest control has driven much of the research on aggregational response. Antisocial predator populations that display territoriality, such as spiders defending their web area, may not display the expected aggregational response to increased prey density.[6]
A credible, simple alternative to the Lotka-Volterra predator-prey model and its common prey dependent generalizations is the ratio dependent or Arditi-Ginzburg model.[7] The two are the extremes of the spectrum of predator interference models. According to the authors of the alternative view, the data show that true interactions in nature are so far from the Lotka-Volterra extreme on the interference spectrum that the model can simply be discounted as wrong. They are much closer to the ratio dependent extreme, so if a simple model is needed one can use the Arditi-Ginzburg model as the first approximation.[8]
References
- ^ Solomon, M. E. "The Natural Control of Animal Populations." Journal of Animal Ecology. 19.1 (1949). 1-35
- ^ Readshaw, J.L. The numerical response of predators to prey density. In: Hughes, Ed., Quantitative Evaluation of Natural Enemy Effectiveness. J. Applied Biol. 10:342-351. 1973.
- ^ Turnbull, A. L. The search for prey by a web-building spider Achaearanea tepidariorum (C. L. Koch) (Araneae, Theridiidae). Canadian Entomologist 96: 568-579. 1964.
- ^ Riechert, Susan E. Thoughts on Ecological Significance of Spiders. BioScience. 24(6): 352-356. 1974.
- ^ Jaeger, R.G. Competitive Exclusion: Comments on survival and extinction of species. BioScience. 24: 33-39. 1974
- ^ Turnbull, A. L. The search for prey by a web-building spider Achaearanea tepidariorum (C. L. Koch) (Araneae, Theridiidae). Canadian Entomologist 96: 568-579. 1964.
- ^ Arditi, R. and Ginzburg, L.R. 1989. Coupling in predator-prey dynamics: ratio dependence. Journal of Theoretical Biology 139: 311-326.
- ^ Arditi, R. and Ginzburg, L.R. 2012. How Species Interact: Altering the Standard View on Trophic Ecology. Oxford University Press, New York, NY.