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Reply to Mike Zwick

Mike Zwick mezwick at ucdavis.edu
Thu Apr 28 15:06:50 EST 1994

In article <2poo23$9ji at canopus.cc.umanitoba.ca>, xia at cc.umanitoba.ca (Xuhua
Xia) wrote:

> The trick here is that the phage may not be able to carry on DNA
> replication and instead may take the lysogenic pathway. In this case
> all the head and tail proteins synthesized would simply represent a
> burden on the bacterial host. This burden will reduce the fitness of
> the phage because its fitness in a lysogenic cycle depends on the fitness 
> of its host). If the host is burdened, it will replicate slower, so will
> the phage DNA.
I am not arguing the biology of the situation, only your assertion that a
certain optimality model gives a sole prediction for a biological system. 
Clearly one can change parameter values or change the model and get very
different predictions.  It seems more likely to me that the true history of
phage genetics is one where people did experiments first and made an
optimally model afterwards.  It seems unlikely that they made the model

> This represents a  misconception of optimality models, i.e.
> optimality models assume optimality without constraints. In fact, the
> appropriate use of optimality models always depends on one's ability
> to identify the constraints. What does Mike mean by "optimum phenotype"?
> There is no optimum phenotype without specifying constraints. If you
> have to define such an optimum phenotype, then it is one that can 
> increase the fitness of its underlying genotype at an infinitely large
> rate. Neither natural selection nor optimality models requires such
> an optimum phenotype to work.

I was not refering to constraints (linkage, developmental, genetic
variation etc.), which can be included in a model(albet w/difficulty and
often are not).  Rather I was refering to the underlying assumption of
optimality models that the "optimum phenotype" can be reached prior to the
optimum phenotype itself changing.  Clearly, in temporally and spatially
varying selection scenaros, there may be optimum that are predicted
(correctly) by the model, but the population never reaches the optimum
because the environment is changing more rapidly (i.e. due to rapid change
of parameter values).  It is not clear what use an optimality model may be
in these situations.

> Xuhua Xia
> University of Manitoba
> xia at ccu.umanitoba.ca
> >-- 
> >mike zwick
> >mezwick at ucdavis.edu
> >Department of Ecology and Evolution
> >Center for Population Biology
> -- 
> Xuhua Xia
> University of Manitoba
> xia at ccu.umanitoba.ca

mike zwick
mezwick at ucdavis.edu
Department of Ecology and Evolution
Center for Population Biology

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