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Life in Numbers

Life in Numbers. Collective Decision Making. Quorum Sensing. “The number (as a majority) of officers or members of a body that when duly assembled is legally competent to transact business”. How do independent individuals come to a decision?. Bacteria.

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Life in Numbers

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  1. Life in Numbers Collective Decision Making

  2. Quorum Sensing • “The number (as a majority) of officers or members of a body that when duly assembled is legally competent to transact business”. • How do independent individuals come to a decision?

  3. Bacteria • Capable of forming complex 3-d structures • Requires collective organisation and ability to sense cell population numbers

  4. Diffusion of Signal and Feedback Signal Cell Density

  5. Quorum Sensing Effects • Production of virulence factors • Tissue damage, bloodstream invasion • Biofilm development • Protection from antibiotics & UV • Swarming motility • Cooperative propulsion • Diggle et al. 2007. Nature • Williams et al. 2007.

  6. Evolutionary Consequences • Cheaters are predicted • Kin selection mediates this propensity • Cooperation increases with relatedness • Need to invest in costly signalling decreases • Diggle et al 2007. Phil Trans R Soc B.

  7. Collective Decisions in Ants Conc Time Nest

  8. 50 60 50 40 50 60 50 40 50 40 50 60 A simple model Colony Update bias by Influence (I) 4 5 7 8 1 2 3 6 Foraging Sites Stickland et al 1995

  9. Main Characteristics • Quick decision (and less exploration) when • There are more ants • Ants emerge more quickly • Influence (I) is greater

  10. Finding the Best Site • Influence factor (I) only has a significant effect. • Rate of emergence and number of ants do not affect success. • Lower influence means higher success rate!!

  11. Colony choice in L albipennis • Leptothorax albipennis readily form ant colonies under microscope slides • Destroy their current nest and they will move to a nearby vacant one • Error of judgement not of omission: i.e. has full information and simply makes a mistake

  12. The migration process • Scouting • Assess potential sites • Eg floor area • Recruitment • tandem running • Quorum reached • Recruitment by carrying(x3 faster than tandem running) • Active use of time-lags to allow flexibility in the decision

  13. Speed Vs Accuracy • 2 Environments • Benign (B) • Harsh (H) • Wind blowing over the habitat • These ants don’t like wind • Franks et al. 2003 • Quorum threshold is lower in harsh conditions

  14. Choice of new nest: good or mediocre Number of ants carried to the mediocre nest site Quorum threshold Decision Time

  15. Findings • Ants found the better nest site in all trials • However, conditions influenced speed and accuracy of the process • Quicker decision made in harsh conditions • But more errors made as indicated by the number of ants carried to the mediocre site

  16. Decisions in Swarming Models

  17. Persuasion • Most individuals have no preferred direction • A proportion do • Larger groups need smaller proportion of informed individuals to reach a quorum. Couzin et al. 2005.

  18. Conflict of Information n1 = n2 n1 = n2-1 n1+1 = n2 -1 Couzin et al. 2005.

  19. Conclusions • Collectives can spontaneously reach a quorum and make a collective decision • Positive feedbacks can be a vital part of this process • Decision making process can be flexible depending on conditions • Conflict can be resolved by very slight biases in the quantity of information

  20. Overall Conclusions • “Self-organisation theory does not suggest that natural selection has had no role in the creation of certain patterns in biology – rather it suggests that natural selection has had rather less to do than one might expect given the complexity of the global structure”Franks 2001.

  21. Suggested Reading • Stickland et al. 1995. Complex trails and simple algorithms in ant foraging. Proc Roy Soc B, 260, 53-58. url (this one is on JSTOR) • West, S. et al. Social evolution theory for microorganisms. Nature Review Microbiology 4, 597-607. • Diggle et al. 2007. Quorum Sensing. Current Biology 17, R907-R910. (and his other papers http://www.nottingham.ac.uk/quorum/diggle2.htm) • Diggle et al 2007. Cooperation and conflict in quorum-sensing bacterial populations. Nature 450, 411-416 • Diggle et al 2007. Evolutionary theory of bacterial quorum sensing: when is a signal not a signal? Phil Trans R Soc B 362, 1241-1249. • Williams et al. 2007. Look who’s talking: communication and quorum sensing in the bacterial world. Phil Trans Roy Soc B 362, 1119-1134. • Osman et al. 2000. Mechanisms of speed-accuracy tradeoff: evidence from covert motor processes. Biological Psychology 51, 173-199. • Franks 2001. Evolution of mass transit systems in ants: a tale of two societies. In Insect Movement: Mechanisms and Consequences (eds. J Woiwood, C Thomas & D Reynolds) pp 281-298. Proceedings of the 20th Symposium of the Royal Entomological Society, CAB International. • Couzin et al. 2005. Effectice leadership and decision making in animal groups on the move. Nature 433, 513-516. • Dyer, J.R.G., Ioannou, C.C., Morrell, L.J., Croft, D.P., Couzin, I.D., Waters, D.A. & Krause, J (2007) Consensus decision-making in human crowds, Animal Behaviour, in press. You might find this online…

  22. Next Week • Read and prepare to discuss • Couzin et al. 2002. Collective memory and spatial sorting in animal groups. J Theor Biol. 218, 1-11. doi • Jackson, A.L., Ruxton, G.D. & Houston, D.C. 2008. The effect of social facilitation on foraging success in vultures: a modelling study. Biology Letters 4(3) 311-313. doi

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