Re: Natural selection and favorable traits how were they measured ?

On Jan 30, 10:24 am, noshellswill <noshellsw...@xxxxxxxxx> wrote:

where DO you creationists get the stupidity that you think is so
profound? do you realize  you're making trash of your religion?

wf3h:

I trust you HAVE studied this basic science? I mean, you are
currently attending at least high-school. Eh?
Which one of the words " quantitative prediction " do you NOT understand?


incidentally, i know that, because it's not in your church bulletin,
you don't know how to google, but a google search on 'mathematical
predictions of evolution' found

http://www.washingtonpost.com/wp-dyn/content/article/2005/09/25/AR2005092501177.html

Using a mathematical formula that emerges from evolutionary theory,
they should be able to predict the number of harmful mutations in
chimpanzee DNA by knowing the number of mutations in a different
species' DNA and the two animals' population sizes.

"That's a very specific prediction," said Eric Lander, a geneticist at
the Broad Institute of MIT and Harvard in Cambridge, Mass., and a
leader in the chimp project.

Sure enough, when Lander and his colleagues tallied the harmful
mutations in the chimp genome, the number fit perfectly into the range
that evolutionary theory had predicted.

and then there's the intensively mathematical paper at:

http://www.iop.org/EJ/article/1742-5468/2005/10/L10002/jstat5_10_l10002.html

Abstract. We present a statistical analysis of biological evolution
processes. Specifically, we study the stochastic replication-mutation-
death model where the population of a species may grow or shrink by
birth or death, respectively, and additionally, mutations lead to the
creation of new species. We rank the various species by the
chronological order by which they originate. The average population Nk
of the kth species decays algebraically with rank, Nk ~ Mμk - μ, where
M is the average total population. The characteristic exponent μ = (α
- γ)/(α + β - γ) depends on α, β, and γ, the replication, mutation,
and death rates. Furthermore, the average population Pk of all
descendants of the kth species has a universal algebraic behaviour, Pk
~ M k - 1.


http://cse.ucdavis.edu/public/events/comparison-between-predictions-and-biological-experiments-on-robustness

In my talk, I will discuss a successful systems biology approach to
this outstanding problem, by integrating relevant information at all
levels: physics, chemistry, DNA, protein, function. It allows us a
parameter-free modeling: in making predictions, all our parameters are
fixed by other experimental measurements. In additional to obtaining a
quantitative agreement between known experimental data, one of our
predictions was recently confirmed by an independent experiment.

http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6WMD-491RPK1-3&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=b614264c4c5119fb635a9c2160239afa

Abstract
I present a framework to study the evolution of traits that allow an
organism to survive life-threatening but rare risks. Specifically, I
am concerned with risks so rare that any one individual in a
population may not experience the risk-causing event in its lifetime.
A theory of rare risk management is virtually absent in evolutionary
biology, although it is well developed in economics. This is
surprising because of the great influence economics had on
evolutionary biology, and because biology is full of examples for
evolved risk management traits. They include the ability of bacteria
to sporulate, of pathogens to survive antibiotic treatment, of
temperate bacteriophages to enter a lytic life cycle, as well as
traits that allow higher organisms to survive rare environmental
disasters, such as sporadic wildfires and irregular flooding. I make
predictions about the sustenance of risk management traits under two
scenarios, one where the catastrophic events cause individual deaths,
and another one where catastrophic events cause population extinction.
A well-developed theory of risk management will not only predict the
distribution of risk management traits, but may also serve other
purposes, such as to reconstruct the spectrum of environments that an
organism encountered in its evolutionary history from the record
stored in its genome's memory.

http://www.blackwell-synergy.com/doi/abs/10.1034/j.1600-0706.2000.880218.x

Community matrix theory has been proposed as a means of predicting
whether a particular set of species will form a stable mixture.
However, the approach has rarely been used with data from real
communities. Using plant competition experiments, we use community
matrix theory to predict the stability and competitive structuring of
a lawn community.
Seven species from the lawn, including the six most abundant, were
grown in boxes, in conditions very similar to those on the lawn. They
were grown alone (monocultures), and in all possible pairs.
The species formed a transitive hierarchy of competitive ability, with
most pairs of species showing asymmetric competition. Relative
competitive ability (competitive effect) was positively correlated
with published estimates of the maximum relative growth rate (RGRmax)
for the same species.
A seven-species community matrix predicted the mixture of species to
be unstable. Simulations revealed two topological features of this
community matrix. First, the matrix was closer to the stability/
instability boundary than predicted from a range of null (random)
models, suggesting that the lawn may be close to stability. Second,
the tendencies of the lawn species to compete asymmetrically, and to
be arranged in competitive hierarchies, were found to be positively
associated with stability, and hence may be contributing factors to
the near-stability seen in the matrix.

.

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