Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!ncar!ames!xanth!mcnc!ecsvax!paleo
From: paleo@ecsvax.UUCP (Constantine A. LaPasha)
Newsgroups: sci.bio
Subject: Why reductionism and classical synthesis doesn't work
Keywords: chaos
Message-ID: <6390@ecsvax.UUCP>
Date: 12 Feb 89 18:27:30 GMT
Organization: UNC Educational Computing Service
Lines: 63


(maybe a bit late, but my 2 cents worth...)

There are a few problems with reductionism as a complete method
for studying and characterizing biological (and many physical)
systems.  As I understand it, reductionist thinking goes 
something like this: if I understand the little pieces well
enough, I can then put them together using some underlying
principles (rules) and understand the way the whole works.
Now, understanding the pieces of the problem (system) is 
important, and needs to be studied.  But the problem comes
when we try to put the parts back together.  Many biological
systems are not linear.  That is, the rules needed to explain
how the parts work together are nonlinear.  We can sometimes
approximate nonlinear systems with linear systems, but this
does not always work, and may hide some of the most interesting 
behaviors of the system.

Nonlinear systems have some interesting properties, like 
sensitivity to initial conditions.  (In other words, minute
differences in the values of the starting conditions of the system
get magnified as you follow the behavior of the system until
the behavior of two systems starting at nearly the same initial
conditions no longer resemble each other -- conversly, similar
behavior can be obtained from very different initial conditions.)
So what?  We would like to think that if we know the state
of a system now, and understand all the parts, and the relations
between the parts, we could predict the state of the system
(behavior) at some future time.  Unfortunately, for nonlinear
systems, predictions for even the simplest, best understood systems
are good for only the short term - long term predictions don't
work well.

Another interesting property of nonlinear systems is that the same
system can act very differently when the constants in the
equations are changed slightly.  Small changes in some constants
can cause drastic differences in the behavior of the system.
So... the same mechanism (nonlinear system) can sometimes explain
very different behaviors of a system - you don't need to
invoke different mechanisms to get different behaviors. (an example
is heart rhythm - normal rhythm and fibrilation can be explained
by the same equations if the constants are silghtly altered)

Oh well... so if I understand all the little pieces of the 
puzzle, AND how they all relate to each other, and I put it
all together, I STILL can't predict how the system is going to
behave...

May sound depressing, but actually I think it is very exciting!

Maybe the varying rates of extinction are due to slight changes
in the constants governing this system...hmm...

too long winded, but maybe worth some discussion..

BTW- the study of the behavior of nonlinear systems has come to
be referred to as chaos

-- 
=====================================================================
Kostya LaPasha        paleo@uncecs.edu   or   paleo@ecsvax.uncecs.edu
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