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How ants use quorum sensing to estimate the average quality of a fluctuating resource.

Franks NR, Stuttard JP, Doran C, Esposito JC, Master MC, Sendova-Franks AB, Masuda N, Britton NF - Sci Rep (2015)

Bottom Line: By using a quorum threshold, namely the number of ants within a new nest site, to determine their choice, the ants are in effect voting with their feet.Our results show that such quorum sensing is compatible with homogenization theory such that the average value of a new nest site is determined by ants accumulating within it when the nest site is of high quality and leaving when it is poor.Hence, the ants can estimate a surprisingly accurate running average quality of a complex resource through the use of extraordinarily simple procedures.

View Article: PubMed Central - PubMed

Affiliation: School of Biological Sciences, University of Bristol.

ABSTRACT
We show that one of the advantages of quorum-based decision-making is an ability to estimate the average value of a resource that fluctuates in quality. By using a quorum threshold, namely the number of ants within a new nest site, to determine their choice, the ants are in effect voting with their feet. Our results show that such quorum sensing is compatible with homogenization theory such that the average value of a new nest site is determined by ants accumulating within it when the nest site is of high quality and leaving when it is poor. Hence, the ants can estimate a surprisingly accurate running average quality of a complex resource through the use of extraordinarily simple procedures.

No MeSH data available.


Flow chart of the mathematical model.For more details, please see the text.
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f5: Flow chart of the mathematical model.For more details, please see the text.

Mentions: The model is that of Pratt et al. (2002)21, modified to account for the different experimental set-up. The possible states of the active ants and the fluxes between these states are shown in Fig. 5. Whilst passive ants or brood items remain at the original nest, the dynamics are given by:where X is the number of active ants that have not yet discovered a new nest, Zi is the number of ants assessing nest i (i = 1, 2), Yi is the number of ants that are potential transporters to nest i, in that they have made a positive assessment of it and will transport to it when the quorum threshold has been attained, and Bi is the numbers of passive ants and brood items in new nest i. The parameter T is the quorum threshold, so that when the number Yi of potential transporters exceeds T they will begin to transport to nest i, at a per capita rate ϕi. The function H is the Heaviside step function, so that H(Yi − T) = 0 when Yi < T and H(Yi − T) = 1 when Yi > T. The parameter μ is the per capita rate of discovery of each new nest. The parameter ki is the per capita rate at which assessors of nest i become potential transporters to it. The parameter ρi is the per capita rate at which assessors of or potential transporters to nest i abandon it and return to the pool X of active ants, from where they may become assessors of and then potential transporters to the other nest. This is an indirect process of switching, in contrast to the direct switching process assumed by Pratt et al. (2002)21, and is one of the differences between our model and theirs. There are two reasons why we prefer indirect switching here. First, tandem running was very rare in these experiments suggesting that recruitment prior to the attainment of quorum thresholds is negligible and that here scouts discover the new nest sites independently. Second, direct switching was based in part on the notion that individual ants actively seek to compare different nest sites. This is now in question3536. Hence, here we favour the simpler indirect switching hypothesis. The other difference is that, in accordance with the experimental observations, no tandem running is incorporated into our model. Note that, if nest 1 is the CN and nest 2 the FN, then k1 and ρ1 will be constant, while k2 and ρ2 will vary following the variations in quality of the FN, taking high and low values (low abandonment rate), respectively, when the nest quality is high, and low and high values, respectively, when the nest quality is low.


How ants use quorum sensing to estimate the average quality of a fluctuating resource.

Franks NR, Stuttard JP, Doran C, Esposito JC, Master MC, Sendova-Franks AB, Masuda N, Britton NF - Sci Rep (2015)

Flow chart of the mathematical model.For more details, please see the text.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4495386&req=5

f5: Flow chart of the mathematical model.For more details, please see the text.
Mentions: The model is that of Pratt et al. (2002)21, modified to account for the different experimental set-up. The possible states of the active ants and the fluxes between these states are shown in Fig. 5. Whilst passive ants or brood items remain at the original nest, the dynamics are given by:where X is the number of active ants that have not yet discovered a new nest, Zi is the number of ants assessing nest i (i = 1, 2), Yi is the number of ants that are potential transporters to nest i, in that they have made a positive assessment of it and will transport to it when the quorum threshold has been attained, and Bi is the numbers of passive ants and brood items in new nest i. The parameter T is the quorum threshold, so that when the number Yi of potential transporters exceeds T they will begin to transport to nest i, at a per capita rate ϕi. The function H is the Heaviside step function, so that H(Yi − T) = 0 when Yi < T and H(Yi − T) = 1 when Yi > T. The parameter μ is the per capita rate of discovery of each new nest. The parameter ki is the per capita rate at which assessors of nest i become potential transporters to it. The parameter ρi is the per capita rate at which assessors of or potential transporters to nest i abandon it and return to the pool X of active ants, from where they may become assessors of and then potential transporters to the other nest. This is an indirect process of switching, in contrast to the direct switching process assumed by Pratt et al. (2002)21, and is one of the differences between our model and theirs. There are two reasons why we prefer indirect switching here. First, tandem running was very rare in these experiments suggesting that recruitment prior to the attainment of quorum thresholds is negligible and that here scouts discover the new nest sites independently. Second, direct switching was based in part on the notion that individual ants actively seek to compare different nest sites. This is now in question3536. Hence, here we favour the simpler indirect switching hypothesis. The other difference is that, in accordance with the experimental observations, no tandem running is incorporated into our model. Note that, if nest 1 is the CN and nest 2 the FN, then k1 and ρ1 will be constant, while k2 and ρ2 will vary following the variations in quality of the FN, taking high and low values (low abandonment rate), respectively, when the nest quality is high, and low and high values, respectively, when the nest quality is low.

Bottom Line: By using a quorum threshold, namely the number of ants within a new nest site, to determine their choice, the ants are in effect voting with their feet.Our results show that such quorum sensing is compatible with homogenization theory such that the average value of a new nest site is determined by ants accumulating within it when the nest site is of high quality and leaving when it is poor.Hence, the ants can estimate a surprisingly accurate running average quality of a complex resource through the use of extraordinarily simple procedures.

View Article: PubMed Central - PubMed

Affiliation: School of Biological Sciences, University of Bristol.

ABSTRACT
We show that one of the advantages of quorum-based decision-making is an ability to estimate the average value of a resource that fluctuates in quality. By using a quorum threshold, namely the number of ants within a new nest site, to determine their choice, the ants are in effect voting with their feet. Our results show that such quorum sensing is compatible with homogenization theory such that the average value of a new nest site is determined by ants accumulating within it when the nest site is of high quality and leaving when it is poor. Hence, the ants can estimate a surprisingly accurate running average quality of a complex resource through the use of extraordinarily simple procedures.

No MeSH data available.