[Taxacom] Reproducibility of phylogenetic analysis
s.thorpe at auckland.ac.nz
Sun Jan 24 17:08:42 CST 2010
Best not to call it "intuition" - sounds very unscientific! In fact, it is a mix of experience and talent. An expert can often place a specimen into the correct taxon (not necessarily to species) at first glance, because "it looks like one". This phenomenon has great value - imagine if we always had to key every specimen out from first principles - we wouldn't get far ...
From: taxacom-bounces at mailman.nhm.ku.edu [taxacom-bounces at mailman.nhm.ku.edu] On Behalf Of Richard Zander [Richard.Zander at mobot.org]
Sent: Monday, 25 January 2010 11:58 a.m.
To: Bob Mesibov; TAXACOM
Subject: Re: [Taxacom] Reproducibility of phylogenetic analysis
Bob Mesibov has made a good point. Regarding subjectivity and intuition
in systematics, I here paste a pertinent passage from an article of mine
recently rejected by a Very Good Journal:
" A third method of scientific analysis is intuition, long
lambasted as illogical and subjective though often defended as "common
sense." The well-known psychologist-statistician G. Gigerenzer and his
group have pointed out recently (Gigerenzer, 2007; Gigerenzer & Selton,
2001; Hutchinson & Gigerenzer, 2005) that intuition has a clear,
describable and amazingly effective methodology even though largely an
unconscious feature of human intelligence. Basically, intuition is an
insensible mental implementation of genetic algorithms for rule-set
production (GARP). The GARP method may include anything from
trial-and-error of simple solutions until one is successful to
sequential Darwinian evolution of more and more complex formulae until
one is most successful according to some stopping rule. Formal genetic
algorithms (Stockwell, 1999; Stockwell & Peters, 1999; Stockwell &
Nobel, 1992) for scientific use are well known to floristics specialists
and ecologists in the GARP software DesktopGarp (Scachetti-Pereira,
2002) and certain other software that solve problems fast with brute
speed. Gigerenzer's main point is that intuition involves both long-term
(e.g. lifetime of a culture) and short-term (such as solving an
immediate puzzle) unconscious solutions to problems involving
uncertainty or paucity of data. The process develops heuristics
(rules-of-thumb) that rapidly provide solutions to difficult or
intractable problems that cannot be easily or rapidly solved by exact
methods (deductive or inductive, falsificationist or verificationist).
Hutchinson & Gigerenzer (2005) give many examples in the field of
Gestalt or omnispection methods of the past have a large element
of intuition. The closure or past experience principles of Gestalt
psychology demonstrate the remarkable ability of the human mind to
complete patterns (notes in a melody, a picture from a partial drawing),
but this power must be trained, and doubtless heuristics as described
above are involved.
I here suggest that over the past 250 years of Linnaean
taxonomy, heuristics have been developed, accumulated, and used to
create classifications (the more modern based on evaluations of
evolutionary relationships) that are fully successful when judged by
consilient analyses using molecular data. Given the faults and
inadequacies of both morphological and molecular exact methods of
evolutionary reconstruction, intuitive systematics as an integrative,
evolving method is in fact a triumph of human scientific endeavor."
The main references are:
Gigerenzer, G. 2007. Gut Feelings: The Intelligence of the Unconscious.
Viking Penguin, New York.
Gigerenzer, G. & Selten, R. 2001. Bounded Rationality: The Adaptive
Toolbox. MIT Press, Cambridge, Mass.
Hutchinson, J. M. C. & Gigerenzer, G. 2005. Simple heuristics and rules
of thumb: Where psychologists and behavioural biologists might meet.
Behavioural Processes 69: 97-124.
Scachetti-Pereira, R. 2002. DesktopGarp, ver. 1.1.6. University of
Kansas Biodiversity Research Center, Lawrence, Kansas.
Stockwell, D. R. B. 1999. Genetic algorithms II. Pp. 123-144 in: A. H.
Fielding (ed.), Machine Learning Methods for Ecological Applications.
Kluwer Academic Publishers, Boston.
Stockwell, D. R. B. & Peters, D. P. 1999. The GARP modelling system:
Problems and solutions to automated spatial prediction. Intern. J.
Geogr. Inform. Systems 13: 143-158.
Stockwell, D. R. B. & Noble, I. R. 1992. Induction of sets of rules from
animal distribution data: A robust and informative method of analysis.
Mathematics and Computers in Simulation 33: 385-390.
The main objection of the reviewer was that " the "triumph" of
heuristics in evolutionary biology has been quite well demonstrated by
previous authors, most eloquently by Michael Ghiselin (1969; many new
editions) in his classic "The triumph of the Darwinian method" and my
paper apparently fell short. Strangeness prevails since our subjects are
clearly different. I shall, however, cite this robust book in my next
resubmission, to a Different Very Good Journal.
Richard H. Zander
Missouri Botanical Garden
PO Box 299
St. Louis, MO 63166-0299 USA
richard.zander at mobot.org
Web sites: http://www.mobot.org/plantscience/resbot/
Modern Evolutionary Systematics Web site:
From: taxacom-bounces at mailman.nhm.ku.edu
[mailto:taxacom-bounces at mailman.nhm.ku.edu] On Behalf Of Bob Mesibov
Sent: Sunday, January 24, 2010 4:28 PM
Subject: [Taxacom] Reproducibility of phylogenetic analysis
is relevant to systematics, as it highlights an aspect of
algorithm-based phylogenetic analysis which troubles some systematists.
In the past, some Taxacomers have worried aloud that phylogenetic
inference is a house of cards, implying (incorrectly, IMO) that if even
one of the analytical steps is flawed, then the whole process is
worthless. I and others have suggested here that algorithm-based
phylogenetic inference is a closed, self-consistent process whose
results are not tested by other means. Richard Zander has proposed an
explicit statistical procedure to clarify the nature of Bayesian
results, but I suspect his paper has been widely ignored.
I'm not sure that any of this skepticism will make systematists any less
enthusiastic about filling the literature with analyses, because trees
are very useful and systematists are keen to build them using whatever
tools are acceptable to their peers and their editors. What's worth
keeping in mind is that most (imagine your own percentage here) of
animal and plant taxonomy has been built by morphologists who made
'non-reproducible' and subjective judgements about similarities and
Some of those judgements were wrong, and it's easy to feel superior to
systematists who didn't have today's analytical tools. It would be a
mistake, though, as the Ars Technica article implies, to try to escape
responsibility for bad judgements by saying, 'Well, we used these data
and these methods and got these results, so if they're wrong it's not
Dr Robert Mesibov
Honorary Research Associate
Queen Victoria Museum and Art Gallery, and
School of Zoology, University of Tasmania
Home contact: PO Box 101, Penguin, Tasmania, Australia 7316
(03) 64371195; 61 3 64371195
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