life in numbers
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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. - PowerPoint PPT PresentationTRANSCRIPT
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Life in Numbers
Collective Decision Making
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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?
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Bacteria
• Capable of forming complex 3-d structures• Requires collective organisation and ability to
sense cell population numbers
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Diffusion of Signal and Feedback
Cell Density
Sig
nal
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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.
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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.
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Collective Decisions in Ants
Nest
Time
Con
c
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Stickland et al 1995
50 50
5050
5050
Colony
Foraging Sites1 2 3 4 5 6 7 8
Update bias by Influence (I)
60 40
4060
6040
A simple model
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Main Characteristics
• Quick decision (and less exploration) when– There are more ants– Ants emerge more quickly– Influence (I) is greater
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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!!
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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
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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
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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
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Choice of new nest: good or mediocreQ
uoru
m th
resh
old
Dec
isio
n Ti
me Number of ants carried to the
mediocre nest site
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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
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Decisions in Swarming Models
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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.
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Conflict of Information
n1 = n2 n1 = n2-1 n1+1 = n2 -1
Couzin et al. 2005.
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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
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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.
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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…
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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