study of predator vs prey relationships wikipeida

Ī credible, simple alternative to the Lotka-Volterra predator-prey model and its common prey dependent generalizations is the ratio dependent or Arditi-Ginzburg model. Antisocial predator populations that display territoriality, such as spiders defending their web area, may not display the expected aggregational response to increased prey density. The study of spiders as a biological mechanism for pest control has driven much of the research on aggregational response. The concept of numerical response becomes practically important when trying to create a strategy for pest control. The other possibility is interference competition where site owners actively prevent other foragers from coming in vicinity.

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). Riechert and Jaeger studied how predator competition interferes with the direct correlation between prey density and predator immigration. He proved that hunger impacts predator movement. In an experiment conducted by Turnbull in 1964, he observed the consistent migration of spiders from boxes without prey to boxes with prey. 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. Parasites can demonstrate a more pronounced numerical response to changes in host density since there is often a more direct connection (less time lag) between food and reproduction in that both needs are immediately satisfied by its interaction with the host. Numerical response in parasitism is still measured by the change in number of adult parasites relative to change in host density. In parasitism, functional response is measured by the rate of infection or laying of eggs in host, rather than the rate of prey consumption as it is measured in predation. If an organism has more net energy, then the organism will sacrifice less energy dedicated to survival per reproductive effort and will therefore increase its reproduction rate. The relationship between available energy and reproductive efforts can be explained with the life history theory in the trade-off between fecundity and growth/survival. In contrast, the functional response consists of a change in conversion efficiency (a) or capture rate (c). Likewise if the energy intake increases (due to greater food availability) and a decrease in energy output (from foraging), then predator mortality (m) will decrease and predator growth rate (dP/dt) will increase. For example, if V increases, then predator growth rate (dP/dt) will increase. This concept can be articulated in the Lotka-Volterra Predator-Prey Model.ĭ P / d t = a c V P − m P Ī = conversion efficiency: the fraction of prey energy assimilated by the predator and turned into new predatorsĭemographic response consists of a change in dP/dt due to a change in V and/or m. This is different from an increase in energy intake due to increased foraging efficiency, which is considered a functional response.

The increase in prey availability translates into higher energy intake and reduced energy output. The demographic response consists of changes in the rates of predator reproduction or survival due to a changes in prey density. For example, there is often a scarcity of predators when the prey population is increasing. The numerical response is not necessarily proportional to the change in prey density, usually resulting in a time lag between prey and predator populations. The numerical response has two mechanisms: the demographic response and the aggregational response. As Holling notes, total predation can be expressed as a combination of functional and numerical response.

It is associated with the functional response, which is the change in predator's rate of prey consumption with change in prey density. The term numerical response was coined by M. The numerical response in ecology is the change in predator density as a function of change in prey density.

Study of predator vs prey relationships wikipeida