Testing the level of ant activity associated with quorum sensing: An empirical approach leading to the establishment and test of a null-model.
On the basis of experimental observations, this paper develops two well-defined mathematical models for the level of activity of Pharaoh's ants within their nesting area, with the aim of providing a more general understanding of animal activity. Under specific conditions, we observe that the activity of ants within their nesting area appears to show no dependence on their density. Making the assumption that all ants move independently of one another, this behaviour can be mathematically modelled as a random process based on the binomial distribution. Developing the model on this basis allows an exponential distribution to be exposed that underlies the time-intervals between ants leaving the nesting area. Such a distribution is present, irrespective of whether the ant population in the nesting area remains constant or steadily depletes, and suggests that ant-ant interactions do not play any significant role in determining ant activity under the experimental conditions adopted. The mathematical framework presented plays the role of a null model that will have a wide range of applications for detecting other determinants of activity-level (not addressed in this study) including environmental and social factors such as food availability, temperature, humidity, presence of pheromone trails, along with intraspecific and interspecific interactions outside the nest and, indeed, more generally. The null model should have applications to a range of organisms. Lastly, we discuss our data in relation to a recent study of ants leaving their nest (Richardson et al., 2010) in which the null model was rejected in favour of record dynamics, where ant-ant interactions were conjectured to play a role.
Nouvellet
P
P
School of Life Sciences, University of Sussex, Brighton BN1 9QG, Sussex, UK. pierrenouvellet@hotmail.com
Bacon
J P
JP
Waxman
D
D
D000818:Animals; D001000:Ants / Q000502:physiology*; D008954:Models, Biological; D016012:Poisson Distribution; D053038:Quorum Sensing / Q000502:physiology*; D013269:Stochastic Processes; D013997:Time Factors