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Ant Colony Foraging Activity without Spatial Information By Balaji Prabhakar Katherine N Dektar Deborah M Gordon Presented by Anusha Reddy Guntakandla Net Id agunta2 April ID: 287602

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The Regulation of Ant Colony Foraging Activity without Spatial Information

ByBalaji Prabhakar, Katherine N. Dektar, Deborah M. Gordon

Presented by

Anusha

Reddy

Guntakandla

Net Id: agunta2

April

9

, 2015Slide2

Outline

IntroductionMethodsResultsConclusionReferencesSlide3

Introduction

Ants are one of the social insects that use local interactions to regulate colony behaviorThey operate without any central control but their collective behavior arises from local interactions among individualsThe authors presented a stochastic model for the process of regulation of foraging activity in harvester ant colonies.Slide4

These ants forages for seeds that are scattered by wind and flooding and a single ant can retrieve a seed on its own.

The model uses an algorithm based on local interactions among individuals in the form of brief antennal contacts, without spatial information such as in pheromone trails.Slide5

The intensity of foraging activity is regulated from moment to moment, and from day to day, to adjust foraging activity to current food availability, and also maintaining sufficient numbers of ants foraging to compete with neighbors of foraging activity.

Regulation of foraging activity depends on the feedback from returning foragers.Forager return rate correspond to food availability, because foragers almost always continues to search until they find a seed, then bring it back to the nestSlide6

Interactions between returning and outgoing foragers that take place in a a narrow tunnel, i.e. 5- 10 cm long, that leads to a deeper chamber.

Authors observe that returning foragers drop their seeds in the tunnel, and then other ants pick up the seeds and take them deeper into the nestExperiments show how quickly an outgoing forager leaves for next trip depends on interactions with returning foragers.Slide7

Foraging activity is closely regulated when foraging rates are high, above a baseline rate at which foragers leave independently of rate of forager return

Authors compared simulations using the model with new data, from field experiments.Slide8

Method

Measures of harvester ant foraging activity Experiments manipulating foraging return rate were performedRates of returning and outgoing foragers along the trail were measured from video film using an image analysis systemMost colonies use more than one foraging direction on a given dayAll the trails were filmed and combined foraging were used for all trailsSlide9

Returning foragers were collected and removed from the foraging trail and thus prevented it from returning to nest for (4-7)min of a 20min observation.Foraging rates were calculated separately before(0-240 sec), during (240-430 sec), and after (500-1100sec)Slide10

Results

Model of the regulation of foraging activityThe data from the period before removal of returning foragers is used to determine the distribution of intervals between the arrival of foragers to the nest.Authors found that the return of foragers to the nest can be described as a Poisson process as the distribution of the intervals between returning foragers is exponentialSlide11

Slide12

Authors began with simple linear model in which the rate of outgoing foragers x(t) is defined as:λ

(t) = λac f(t,τ)x(t) = Poisson (λb)+Poisson (λ (t))Where λ

b

is baseline

rate of outgoing foragers,

λ

ac

sets the no. of outgoing foragers per returning forager and

f(t,τ

)

is no, of returning foragers between times (t-

τ

) and t

Slide13

The most important parameter in this linear model for predicting rate of outgoing foragers is τ.

The model operates in discrete time.Authors denote ‘α’, as rate of outgoing foragers and c >0 as increase in ‘α’ for each food-bearing returning foragerq >0 is the decrease in ‘α’ when each forager leaves the nest.Slide14

Alpha decays by amount d >0 during each time slot.Alpha has a lower bound, α

Authors assume that arrivals occur at the beginning and departures at end of timeslots.An as number of returning food-bearing foragers in nth timeslot and Dn denotes number of outgoing foragers leaving the nestSlide15

Dn was set equal Poisson random variable of mean αn

. Where αn is rate at which ants leave the nest in nth timeslot and αn ≥α ≥0Αn id described by:3) α

n

= max (

α

n-1

−qD

n-1

+cA

n

−

d, α),

α

0

=

0

4)

D

n

~ Poisson

(

α

n

)Slide16

Comparison of model and dataComparison of simulated output of the model with data from field experiments on the response of outgoing foragers to a range of rates of returning foragers.

The data of rate of forager return is used to generate the simulated rate of outgoing foragers which is matched with observed rate of outgoing foragers by adjusting one parameter.Authors examined fit between model and data for one parameter, c.Slide17

Slide18

Examined whether correlation between rates of returning and outgoing foragers was atleast as high as in the simulation as in the data.

The correlation coefficients for the observed rate of returning foragers and the simulated rate of outgoing foragers are higher than those for the observed rate of returning foragers with the observed rate of outgoing foragers.The correlation coefficient with the observed rate of returning foragers increased significantly with foraging rate for the simulated rate of outgoing foragers but does not increase significantly for the observed rate of outgoing foragers.Slide19

Slide20

Conclusion

Authors presented a simple stochastic model of the regulation of foraging by harvester ant colonies which does not use pheromone trails to specific locations. The feedback-based algorithm estimates the effect of each returning forager on the rate at which foragers leave the nest. The model shows how the regulation of ant colony foraging can operate without spatial information, describing a process at the level of individual ants that predicts the overall foraging activity of the colony Slide21

References

Sumpter DJT, Pratt SC (2003) A modelling framework for understanding social insect foraging. Behav Ecol Sociobiol 53: 131–144.http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3767282/Gordon DM, Holmes S, Nacu S (2008) The short-term regulation of foraging inharvester

ants.

Behav

Ecol

19: 217–222.

doi

: 10.1093/

beheco

/

arm125

Gordon DM,

Guetz

A, Greene MJ, Holmes S (2011) Colony variation in the collective regulation of foraging by harvester ants.

Behav

Ecol

22: 429–435.

doi

: 10.1093/

beheco

/

arq218Slide22

Questions..??Slide23

Thank you