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Sting, Carry and Stock: How Corpse Availability Can Regulate De-Centralized Task Allocation in a Ponerine Ant Colony.

Schmickl T, Karsai I - PLoS ONE (2014)

Bottom Line: The common stomach is able to establish and to keep stabilized an effective mix of workforce to exploit the prey population and to transport food into the nest.The model is compared to previously published models that followed a different modeling approach.Based on our model analysis we also suggest a series of experiments for which our model gives plausible predictions.

View Article: PubMed Central - PubMed

Affiliation: Department of Zoology, Karl-Franzens-University, Graz, Austria.

ABSTRACT
We develop a model to produce plausible patterns of task partitioning in the ponerine ant Ectatomma ruidum based on the availability of living prey and prey corpses. The model is based on the organizational capabilities of a "common stomach" through which the colony utilizes the availability of a natural (food) substance as a major communication channel to regulate the income and expenditure of the very same substance. This communication channel has also a central role in regulating task partitioning of collective hunting behavior in a supply&demand-driven manner. Our model shows that task partitioning of the collective hunting behavior in E. ruidum can be explained by regulation due to a common stomach system. The saturation of the common stomach provides accessible information to individual ants so that they can adjust their hunting behavior accordingly by engaging in or by abandoning from stinging or transporting tasks. The common stomach is able to establish and to keep stabilized an effective mix of workforce to exploit the prey population and to transport food into the nest. This system is also able to react to external perturbations in a de-centralized homeostatic way, such as to changes in the prey density or to accumulation of food in the nest. In case of stable conditions the system develops towards an equilibrium concerning colony size and prey density. Our model shows that organization of work through a common stomach system can allow Ectatomma ruidum to collectively forage for food in a robust, reactive and reliable way. The model is compared to previously published models that followed a different modeling approach. Based on our model analysis we also suggest a series of experiments for which our model gives plausible predictions. These predictions are used to formulate a set of testable hypotheses that should be investigated empirically in future experimentation.

No MeSH data available.


Related in: MedlinePlus

Time plots of our model’s system variables (S, T, Φ, Ω, Ψ, η) in simulations were the colony was exposed to a specific regime of perturbations in the supply of prey and corpses.Perturbations: P+: Prey influx increased (500 min −1000 min); P-: prey influx decreased (2500 min −3000 min); C+: influx of corpses increased (4500 min −5000 min); C-: corpse influx decreased (6500 min −7000 min); N+: influx of corpses in the nest increased (8500 min −9000 min) and N-: influx of corpses in the nest decreased (10500 min −11000 min). The baseline (horizontal line) shows a simulation run made with our standard parameters (see Table 1). Lines above this baseline represent runs with increased values (adding +0.02, +0.04, …, +0.2 to the standard fluxes). Lines below the standard line represent similar simulation runs, except that the influxes were decreased at the same extent as they were increased previously.
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pone-0114611-g010: Time plots of our model’s system variables (S, T, Φ, Ω, Ψ, η) in simulations were the colony was exposed to a specific regime of perturbations in the supply of prey and corpses.Perturbations: P+: Prey influx increased (500 min −1000 min); P-: prey influx decreased (2500 min −3000 min); C+: influx of corpses increased (4500 min −5000 min); C-: corpse influx decreased (6500 min −7000 min); N+: influx of corpses in the nest increased (8500 min −9000 min) and N-: influx of corpses in the nest decreased (10500 min −11000 min). The baseline (horizontal line) shows a simulation run made with our standard parameters (see Table 1). Lines above this baseline represent runs with increased values (adding +0.02, +0.04, …, +0.2 to the standard fluxes). Lines below the standard line represent similar simulation runs, except that the influxes were decreased at the same extent as they were increased previously.

Mentions: Increasing the prey influx results in strong increases in prey and corpses at the hunting site and in the nest. Decreasing the prey influx mirror these effects (Fig. 10). A perturbation which is induced by changing the influx of corpses shows a weak effect on the stingers and on the saturation of prey densities. Furthermore it has a prominent effect on the number of transporters and on the number of corpses in the field and in the nest. However, such perturbations affect the efficiency of the colony in a significant way. Perturbing the colony by changing the influx of corpses into the nest has the weakest effect on system variables in general, except on the saturation of the nest with corpses.


Sting, Carry and Stock: How Corpse Availability Can Regulate De-Centralized Task Allocation in a Ponerine Ant Colony.

Schmickl T, Karsai I - PLoS ONE (2014)

Time plots of our model’s system variables (S, T, Φ, Ω, Ψ, η) in simulations were the colony was exposed to a specific regime of perturbations in the supply of prey and corpses.Perturbations: P+: Prey influx increased (500 min −1000 min); P-: prey influx decreased (2500 min −3000 min); C+: influx of corpses increased (4500 min −5000 min); C-: corpse influx decreased (6500 min −7000 min); N+: influx of corpses in the nest increased (8500 min −9000 min) and N-: influx of corpses in the nest decreased (10500 min −11000 min). The baseline (horizontal line) shows a simulation run made with our standard parameters (see Table 1). Lines above this baseline represent runs with increased values (adding +0.02, +0.04, …, +0.2 to the standard fluxes). Lines below the standard line represent similar simulation runs, except that the influxes were decreased at the same extent as they were increased previously.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4262436&req=5

pone-0114611-g010: Time plots of our model’s system variables (S, T, Φ, Ω, Ψ, η) in simulations were the colony was exposed to a specific regime of perturbations in the supply of prey and corpses.Perturbations: P+: Prey influx increased (500 min −1000 min); P-: prey influx decreased (2500 min −3000 min); C+: influx of corpses increased (4500 min −5000 min); C-: corpse influx decreased (6500 min −7000 min); N+: influx of corpses in the nest increased (8500 min −9000 min) and N-: influx of corpses in the nest decreased (10500 min −11000 min). The baseline (horizontal line) shows a simulation run made with our standard parameters (see Table 1). Lines above this baseline represent runs with increased values (adding +0.02, +0.04, …, +0.2 to the standard fluxes). Lines below the standard line represent similar simulation runs, except that the influxes were decreased at the same extent as they were increased previously.
Mentions: Increasing the prey influx results in strong increases in prey and corpses at the hunting site and in the nest. Decreasing the prey influx mirror these effects (Fig. 10). A perturbation which is induced by changing the influx of corpses shows a weak effect on the stingers and on the saturation of prey densities. Furthermore it has a prominent effect on the number of transporters and on the number of corpses in the field and in the nest. However, such perturbations affect the efficiency of the colony in a significant way. Perturbing the colony by changing the influx of corpses into the nest has the weakest effect on system variables in general, except on the saturation of the nest with corpses.

Bottom Line: The common stomach is able to establish and to keep stabilized an effective mix of workforce to exploit the prey population and to transport food into the nest.The model is compared to previously published models that followed a different modeling approach.Based on our model analysis we also suggest a series of experiments for which our model gives plausible predictions.

View Article: PubMed Central - PubMed

Affiliation: Department of Zoology, Karl-Franzens-University, Graz, Austria.

ABSTRACT
We develop a model to produce plausible patterns of task partitioning in the ponerine ant Ectatomma ruidum based on the availability of living prey and prey corpses. The model is based on the organizational capabilities of a "common stomach" through which the colony utilizes the availability of a natural (food) substance as a major communication channel to regulate the income and expenditure of the very same substance. This communication channel has also a central role in regulating task partitioning of collective hunting behavior in a supply&demand-driven manner. Our model shows that task partitioning of the collective hunting behavior in E. ruidum can be explained by regulation due to a common stomach system. The saturation of the common stomach provides accessible information to individual ants so that they can adjust their hunting behavior accordingly by engaging in or by abandoning from stinging or transporting tasks. The common stomach is able to establish and to keep stabilized an effective mix of workforce to exploit the prey population and to transport food into the nest. This system is also able to react to external perturbations in a de-centralized homeostatic way, such as to changes in the prey density or to accumulation of food in the nest. In case of stable conditions the system develops towards an equilibrium concerning colony size and prey density. Our model shows that organization of work through a common stomach system can allow Ectatomma ruidum to collectively forage for food in a robust, reactive and reliable way. The model is compared to previously published models that followed a different modeling approach. Based on our model analysis we also suggest a series of experiments for which our model gives plausible predictions. These predictions are used to formulate a set of testable hypotheses that should be investigated empirically in future experimentation.

No MeSH data available.


Related in: MedlinePlus