nvg meeting, 26 november 2010, soesterberg

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Kin selection theory OK! Tom Wenseleers, Dept. Biology, K.U.Leuven e-mail: [email protected] NVG meeting, 26 November 2010, Soesterberg r.B > C

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r.B > C. Kin selection theory OK! Tom Wenseleers, Dept. Biology, K.U.Leuven e-mail: [email protected]. NVG meeting, 26 November 2010, Soesterberg. Inclusive fitness theory. - PowerPoint PPT Presentation

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Page 1: NVG meeting, 26 November 2010, Soesterberg

Kin selection theory OK!Tom Wenseleers, Dept. Biology,

K.U.Leuvene-mail:

[email protected]

NVG meeting, 26 November 2010, Soesterberg

r.B > C

Page 2: NVG meeting, 26 November 2010, Soesterberg

Inclusive fitness theoryIf you want to know whether a trait will spread or not

you also have to take into account the effects on relatives

)~,cov()ave()~,cov( ddad

aa Pzz)(Dzz )~,cov()ave()~,cov( ddad

aa Pzz)(Dzz )~,cov()ave()~,cov( ddad

aa Pzz)(Dzz

Idea of kin selection or inclusive fitness theory(W.D. Hamilton 1964): helping relatives can be favoured even at a cost to oneself when b.r > c

This inequality is known as the relative inclusive fitness effect. It is the partial effect of the actor’s trait on the actor’s own direct fitness (-c) plus the partial effect of the actor’s trait on the fitness of relatives (b), weighted by relatedness (r).

Puts the individual actor at the center of the analysis, and allows one to predict behaviour on the basis of which strategy maximises the individual’s expected inclusive fitness

W.D. Hamilton (1964) The genetical evolution of social behaviour. Pt I & II. J. Theor. Biol. 7: 1-52. Cited nearly 7,000 times.

Page 3: NVG meeting, 26 November 2010, Soesterberg

Kin selection theory: its rise and fall???

Edward O. Wilson: tries to denounce kin selection and reinstate group selection as the appropriate framework to study social evolution

Wilson Social Research 2005

Wilson & Hölldobler PNAS 2005

Page 4: NVG meeting, 26 November 2010, Soesterberg

Ed Wilson: the rise and fall of the prophet of sociobiology???

Foster, Wenseleers & Ratnieks Trends in Ecol. Evol. 2006

Page 5: NVG meeting, 26 November 2010, Soesterberg

...but it didn’t help...

Wilson BioScience 2007

Wilson & Wilson New Scientist 2007

Wilson & Wilson Amer. Scientist 2007

Wilson & Wilson Q. Rev. Biol. 2007

Page 6: NVG meeting, 26 November 2010, Soesterberg

"It is often said in research reports on social insects that some particular set of empirical data is “consistent with kin selection theory.” But the same can be said of almost any other imaginable result, and the particular connection of data to the theory remains unclear. Hence, kin selection theory is not wrong. It is instead constructed to arrive at almost any imaginable result, and as a result is largely empty of content. Its abstract parameters can be jury-rigged to fit any set of empirical data, but not built to predict them in any detail, nor have they been able to guide research in profitable new directions." "the theory has contributed little or nothing not already understood from field and experimental studies“

(E.O. Wilson BioScience 2008)

Some silly quotes

Page 7: NVG meeting, 26 November 2010, Soesterberg

The love-hate relationship of Ed Wilson with Hamilton’s rule

Wilson (1975) Sociobiology: The New Synthesis:discusses Hamilton’s rule as a special case of group selection and mentions that “Hamilton’s viewpoint is unstructured. The con-vential parameters of population genetics, allele frequencies, mutation rates, epistasis, migration, group size, and so forth, are mostly omitted from the equations. As a result, Hamilton’s mode of reasoning can be only loosely coupled with the remainder of genetic theory, and the number of predictions it can make is unnecessarily limited.” Hölldobler & Wilson (1990) The Ants, p. 182: better treatment of inclusive fitness theory and mentions that“Hamilton’s rule is robust as a theoretical prediction”Hölldobler & Wilson (2009) The Superorganism: authors criticize kin selection theory in one place, support it in others, at one stage admit that kin and group selection are simply alternative bookkeeping methods to measure gene frequency change, but elsewhere maintain that they are not

Page 8: NVG meeting, 26 November 2010, Soesterberg

Also back at Harvard...

Martin Nowak: found 5 supposedly fundamental rules for the evolution of cooperation

Page 9: NVG meeting, 26 November 2010, Soesterberg

...criticized by others

Laurent Lehmann: not a fundamental classification scheme – all the rules ultimately reduce to Hamilton’s rule

Ohtsuki et al. (2006): “Natural selection favours cooperation, if the benefit of the altruistic act, b, divided by the cost, c, exceeds the average number of neighbours, k, which means b/c > k. ... We note the beautiful similarity of our finding with Hamilton’s rule...”

Lehmann et al. (2007): it is Hamilton’s rule!!!

Page 10: NVG meeting, 26 November 2010, Soesterberg

The latest in the series...

The New York Times: “The scientists argue that studies on animals since Dr. Hamilton’s day have failed to support it.The scientists write that a close look at the underlying math reveals that Dr. Hamilton’s theory is superfluous. It’s precisely like an ancient epicycle in the solar system, said Martin Nowak. The world is much simpler without it.”Others disagree: “This paper, far from showing shortcomings in inclusive fitness theory, shows the shortcomings of the authors”, said Francis Ratnieks of the University of Sussex.

Martin Nowak, Corina Tarnita, Ed Wilson: IF theory is limited in scope and traditional population genetics and game theory are better frameworks to study social evolution

Page 11: NVG meeting, 26 November 2010, Soesterberg

...others also joined in...

Matthijs van Veelen: statistical derivations of Hamilton’s rule based on the Price equation are no good

Arne Traulsen: Hamilton’s rule cannot do evolutionary dynamics and requires weak selection

“Rather than saying the paper is wrong, it would be more fruitful if critics also went back to basics: state model assumptions, derive predictions, test empirically. Such a return to rigour would help the field advance to the next level.”

Page 12: NVG meeting, 26 November 2010, Soesterberg

wΔz (2007)A series of deaths have started occurring in New York; Some are being found mutilated while others have an equation wΔz = Cov (w,z) carved onto their skin. As police investigate they discover each victim was forced to choose between sacrificing their own life or a loved ones' life. Before long it becomes clear that this perpetrator has suffered just such a similar fate...so now is coping by seeking a way of solving this philosophical enigma. Can Captain Maclean and his officers such as Eddie Argo and his new partner Helen Westcott stop this suspect, because he will not until he gets to the end of this equation.

Rated R for strong brutal violence including a rape, gruesome images and pervasive language.

Page 13: NVG meeting, 26 November 2010, Soesterberg

Claim (1) standard natural selection is better than IF theory

Abbot et al. (2010) Nature, in press : “Is there a sharp distinction between IF theory and ‘standard natural selection theory’? No. Natural selection explains the appearance of design in the living world, and IF theory explains what this design is for. Specifically, natural selection leads organisms to become adapted as if they were trying to maximize their IF. IF theory is based on population genetics, and is used to make falsifiable predictions about how natural selection shapes phenotypes, and so it is not surprising that it generates identical predictions to those obtained using other methods.”The power of IF theory is that it led to an increadibly powerful strategic way of thinking about animal behaviour.

Page 14: NVG meeting, 26 November 2010, Soesterberg

Claim (2) IF theory has many limitations

Nowak et al.(2010): IF theory requires weak selection (gradual evolution) cannot deal with synergistic, nonadditive

fitness effects can only deal with pairwise interactions cannot take into account details of genetic

inheritance (e.g. arbitrary dominance)

Each of these claims is manifestly wrong!Corina Tarnita, from

http://smartbabesaresexy.blogspot.com/

Page 15: NVG meeting, 26 November 2010, Soesterberg

Where does the confusion come from?

Original version of IF theory (the “gradient” version) was indeed derived in the limit of weak selection

Hamilton (1964) was actually explicit about this: “Considering that, the present use of the coefficients of reIationships is only valid when selection is slow”

The “gradient” version of IF theory was further extended in the ESS IF maximisation methods of Peter Taylor & Steve Frank (1996) and the IF methods of François Rousset (2004), it is also this version that is used by NWT

But there is also a more general, statistical version of IF theory, first derived from the Price equation by Hamilton (1970), which also works under strong selection

Page 16: NVG meeting, 26 November 2010, Soesterberg

Simplest gradient version of Hamilton’s rule:

w = fitness of actor, w’ = fitness of recipientg = breeding value for actor’s level of cooperation

E.g. with additive fitness effects :w = 1-C.g + B.g’, w’=1-C.g’ + B.g → increase in level of cooperation when -C + B.r > 0

E.g. with nonadditive fitness effects:w = 1-C.g + B.g’ + D.g.g’, w’=1-C.g’ + B.g + D.g.g’ → increase in level of cooperation when (-C+D.g) + (B+D.g).r > 0 ESS level of cooperation g*=(C-B.r)/(D(1+r))

Gradient version of IF theory

0./'/ rgwgw-c b relatedness

Frank 1997, Wenseleers et al. 2010

Page 17: NVG meeting, 26 November 2010, Soesterberg

Can deal with nonadditive fitness interactions since weak selection linearises all nonlinearities + extensions for dominance

Can easily be extended to interactions between > 2 individuals by adding more terms for additional relatives that are affected

Realistic model for continuous traits, probabilistically expressed traits or discrete traits with strong selective effect that are only rarely expressed (low penetrance)

Weak selection is usually realistic since distribution of fitness effects of new mutations usually follows an exponential distribution (most mutants only deviate slightly from wild type)

Also good (1st order) approximation for when selection is strong

IF theory provides an easier, more powerful & general method for finding ESS’s than traditional population genetic theory

Gradient version of IF theory

Page 18: NVG meeting, 26 November 2010, Soesterberg

Gradient version of IF theoryW.D. Hamilton (1995): “...my confidence that I had proved maximisation of inclusive fitness, with or without multiple alleles under weak selection was important to me. I was and still am a Darwinian gradualist for most of the issues of evolutionary change. Most change comes, I believe, through selected alleles that make small modifications to existing struc-ture and behaviour. If one could understand just this case in social situ-ations, who cared much what might happen in the rare cases where the gene changes were great and happened not be disastrous? Whether under social or classical selection, defeat and disappearance would, as always, be the usual outcome for genes that cause large changes. I think that a lot of the  objection to so-called 'reductionism' and 'bean-bag reasoning' directed at Neodarwinist theory comes from people, who, whether through inscrutable private agendas or ignorance, are not gradualists, being instead inhabitants of some imagined world of super-fast progress. Big changes, strong interlocus interactions, hopeful monsters, mutations so abundant and so hopeful that several may be under selection at one time -- these have to be the stuff of their dreams if their criticisms are to make sense. ...”

Page 19: NVG meeting, 26 November 2010, Soesterberg

The Price equation

Hamilton (1970) also derived a more general version ofhis rule based on a population genetic theorem known as the Price equation (also see Queller 1992, Frank 1997, Gardner et al. 2007, Wenseleers et al. 2010)

Trait (e.g. gene for altruism) will spread in a population

when Covariance between relative fitness and individual

allele frequency (or breeding value) + mean fitness-weighted change across inheritance paths (transmission biases, e.g. due to meiotic drive or biased mutation)

No transmission biases →

)~,cov()ave()~,cov( ddad

aa Pzz)(Dzz )~,cov()ave()~,cov( ddad

aa Pzz)(Dzz )~,cov()ave()~,cov( ddad

aa Pzz)(Dzz

0)(ave),~cov( gwgwg

0.),~cov( ~ ggw Vgw

George Price

Page 20: NVG meeting, 26 November 2010, Soesterberg

Statistical version of Hamilton’s rule

The expected neighbour-modulated fitness of a random individual can be written in an additive way as

β‘s: average effect of being more cooperative than average and of interacting with an individual that is more cooperative than average, defined in terms of partial least-square regressions

(neighbour-modulated fitness condition)

This is identical to the inclusive fitness condition

since normally

)~,cov()ave()~,cov( ddad

aa Pzz)(Dzz )~,cov()ave()~,cov( ddad

aa Pzz)(Dzz )~,cov()ave()~,cov( ddad

aa Pzz)(Dzz

0.. when0. ''.~'.~~~ rbcV ggggwggwgwggw

)'.().()'.().(ˆ '.~'.~ ggbggcwggggww ggwggw

0.. ''.'~'.~ rbcggggwggw

'.'~'.~ ggwggw

Page 21: NVG meeting, 26 November 2010, Soesterberg

Statistical version of Hamilton’s rule

That the expected neighbour-modulated fitness is written in an additive way doesn’t mean that fitness has to be frequency independent and that you can’t have synergy, since the costs & benefits can be a function of the behaviour of the other individual(s)

E.g. with discrete strategies (X=Y=0: defect, X=Y=1: cooperate) Gardner et al. (2007) and Wenseleers et al. (2010): under haploidy average costs & benefits can be calculated using least-square regression calculus as

)~,cov()ave()~,cov( ddad

aa Pzz)(Dzz )~,cov()ave()~,cov( ddad

aa Pzz)(Dzz )~,cov()ave()~,cov( ddad

aa Pzz)(Dzz

YXDYBXCYXw ....1),(

DrprrBb

DrprrCc

ggw

ggw

1).1(

1).1(

'.'~

'.~

Page 22: NVG meeting, 26 November 2010, Soesterberg

Statistical version of Hamilton’s rule

Cooperation spreads when –c + b.r > 0 i.e. when –C + B.r + D.(r+(1-r).p) > 0, pure ESS p*=(C-(B+D)r)/(D(1-r))

The Price equation and Hamilton’s rule are dynamically sufficient and can do evolutionary dynamics provided that explicit model assumptions are made, e.g. about the fitness function and how genotypes form, etc...

Costs, benefits & relatedness may change from generation to generation but split in direct & indirect fitness effects always possible

E.g. in the absence of relatedness, cost=-C+p.D No surprise that cost of cooperating is frequency dependent!!

If you work with breeding values the approach also works for arbitrary dominance

)~,cov()ave()~,cov( ddad

aa Pzz)(Dzz )~,cov()ave()~,cov( ddad

aa Pzz)(Dzz )~,cov()ave()~,cov( ddad

aa Pzz)(Dzz

Page 23: NVG meeting, 26 November 2010, Soesterberg

Parallels with an old controversy...

Late 1800's and early 1900's: debate between Mendelian geneticists (e.g. Bateson) and biometrical (i.e. statistical) geneticists (e.g. Pearson)

R.A. Fisher (1918): showed how to integrate bothapproaches by resort to least-square regressionmethods

Showed that one can define the average effect of an allele

Generalised Hamilton’s rule: defines costs & benefits in terms of the average effect of an allele (or strategy) on yourself and on your partners’ fitness using least-square regression calculus

Just as with the average effect, costs & benefits may then become “ecology-dependent”

Page 24: NVG meeting, 26 November 2010, Soesterberg

Claim (3) IF theory has little predictive power and empirical support

Research Area

Correlational

studies?

Experimental

studies?

Interplay between

theory and data?

Sex allocation Policing Conflict resolution Cooperation Altruism Spite Kin discrimination Parasite virulence Parent-offspring conflict

Sibling conflict Selfish genetic elements

Genomic imprinting Cannibalism Dispersal Alarm calls Eusociality

Abbot et al. (2010) Nature

Page 25: NVG meeting, 26 November 2010, Soesterberg

Claim (3) IF theory has little predictive power and empirical support

Abbot et al. (2010) Nature

Trait examined Explanatoryvariables

Correlational

studies?

Experimental

studies?

Interplay between

theory and data?

Altruistic helping Haploidiploidy vs diploidy

Worker egg laying Costs, benefits and relatedness

Caste determination

Relatedness

Policing Relatedness Level of cooperation

Costs, benefits and relatedness

Work rate Need for work and probability of becoming queen

Sex allocation Relatedness asymmetries due to variation in queen survival, queen number & mating frequency

Resource availability Competition for mates between related males

Nr. of individuals trying to become reproductive

Presence of old queens

Workers killing queens

Presence of workers, reproductives or other queens

Exclusion of non-kin

Colony membership

Page 26: NVG meeting, 26 November 2010, Soesterberg

Wenseleers et al. J. Evol. Biol. 2003; Ratnieks & Wenseleers Science 2006

Melipona stingless beesgreatly overproduce queens: ca. 10%-20% of all female larvae develop as queens, most are killed soon after eclosion

Why? Mystery for >50 years.

IF theory: becoming a queen with a probability of 14-20% is the individual IF optimum of developing larvae.

Successful predictions (1) caste determination

z*=(1-Rf)/(1+Rm)

Page 27: NVG meeting, 26 November 2010, Soesterberg

Successful predictions (2) policing

A priori prediction: workers should be selected to prevent or ‘police’ each others’ reproduction particularly in species with multiple mated queens (Starr 1984, Ratnieks 1988)

Ratnieks & Visscher Nature 1989: experimental confirmating of the occurrence of worker policing in the polyandrous honeybee

Wenseleers & Ratnieks Am. Nat. 2006: meta-analysis of data from 100 species of ants, bees and wasps showing that worker policing occurs more frequently in species with multiple mated queens

Starr 1984, Ratnieks Am. Nat. 1988, Ratnieks & Visscher Nature 1989; Wenseleers & Ratnieks Am. Nat. 2006

Page 28: NVG meeting, 26 November 2010, Soesterberg

Successful predictions (3) number of repr.

workersA priori prediction: in colonies with a queen: when policing is more effective fewer workers should try to reproduce in the first place, in queenless colonies: species with low sister-sister relatedness shold have more reproductive workers (Wenseleers et al. 2004)

IF optimum percentage of egg-laying workers derived in terms in parameters such as sister-sister relatedness, avg. colony size, policing effectiveness, queen fecundity, etc...

Wenseleers & Ratnieks Nature 2006: both predictions empirically confirmed!

Wenseleers et al. J. Evol. Biol. 2004, Wenseleers & Ratnieks Nature 2006, Ratnieks & Wenseleers TREE 2008

effectiveness of the policing

leve

l of s

elfis

hnes

s1009998959080705030

0

5

10

30

% o

f egg

-layi

ng w

orke

rs Asian paper wasp

tree waspNorwegian wesp

median wesp

honeybee

red wesp

saxon wasp

hornet

German waspcommon wasp

Page 29: NVG meeting, 26 November 2010, Soesterberg

Successful predictions (4) male parentage

M. beecheii

M. asilvai

M. scutellaris

M. bicolorM. subnitida

M. marginata

M. quadrifasciata

M. favosa

70 75 80 85 90 95 100

% female eggs laid by queen

0

20

40

60

80

100

% m

ales

wor

kers

' son

s

n=8 speciesSpearman R=0.95, p=0.0003

Parameters:0.04 new cells built/day/worker (n=8 sp.)worker life expectancy: 46.5 days (n=4 sp.)

ESS

Stingless bee colonies: no variation in relatedness structure (single once-mated queen) but huge variation in % of males that are workers’ sons (0-95%).

Why the variation?

Inclusive fitness model: due to variation in the benefit of replacing an average queen-laid egg with a son caused by variation in the % of the queen’s eggs that are female, i.e. variation in costs & benefits.

Cost in terms of reduced colony productivity calculated using a differential equation model.

Page 30: NVG meeting, 26 November 2010, Soesterberg

Thanks

T. Wenseleers, A. Gardner & K. R. Foster (2010) Social evolution theory: a review of methods and approaches. In: Social behaviour: genes, ecology and evolution (T. Szekely, A. J. Moore & J. Komdeur, eds). Cambridge University Press.

P. Abbot, ... , T. Wenseleers, S.A. West, ...., J.A. Zeh & A. Zink (2010) Inclusive fitness theory and eusociality. Nature, in press.

F.L.W. Ratnieks & T. Wenseleers (2008) Altruism in insect societies and beyond: voluntary or enforced? Trends in Ecology and Evolution 23: 45-52.

F.L.W. Ratnieks, K.R. Foster & T. Wenseleers (2006) Conflict resolution in insect societies. Annual Review of Entomology 51: 581-608.

Kin selection theory OK!!!