Here is the contents of about a dozen messages on
this thread from yesterday and today, which I've
compiled here to save lines in your in box. I think it's about run its course.
David Inouye, ECOLOG-L list owner and moderator
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I'll just simply say that it would be difficult to explain something that you
couldn't describe.
Mike [EMAIL PROTECTED]
Quoting Malcolm McCallum <[EMAIL PROTECTED]>:
> I would say that science is finding patterns in nature AND explaining =
> them. Both are different parts of the scientific process. A major =
...snip...
>
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But surely these two definitions are not mutually
exclusive. We all do both--look for novel
patterns in the processes we study, and look to
explain those patterns perhaps to help us affect the processes that cause them.
Cheers,
-
Ashwani
Vasishth [EMAIL PROTECTED] (818) 677-6137
Assistant Professor
Department of Urban Studies and Planning, ST 206
California State University, Northridge
http://www-rcf.usc.edu/~vasishth
>I can understand your (well stated) position,
but I think that I can illuminate
>my stance on procedural science by modifying your quote of Starker Leopold.
>Instead of, "science is finding patterns in
nature", I would personally say that
>"science is explaining patterns in nature." Taking one definition of science
>over the other greatly changes the way you do science.
>
>Mike Sears
>Assistant Professor
>Department of Zoology
>Southern Illinois University
>Carbondale, IL 62901
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And yet many people try.
Malcolm L. McCallum
Assistant Professor
Department of Biological Sciences
Texas A&M University Texarkana
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I wonder if the booming population of that
recently-evolved nest parasite, the
yellow-bellied grantsucker, will ever crash, or
if the sky will so darken with them that
everything will just go into a deep freeze?
WT
[EMAIL PROTECTED]
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The late Elmer C. Birney, esteemed curator of
mammals at the University of Minnesota and editor
of the Journal of Mammalogy, had this to say:
"Good data are immortal; our interpretation of
those data changes at least every ten years."
In these days of mathematical hyper-analysis, it
remains important to make sure our data have been
collected in legitimate, open-minded ways, and
that those data are accurate recorded.
As a 19th century naturalist in a 21st century
(i.e., statistically driven) world, I'm sometimes
overwhelmed by numbers. When that happens I grab
my binoculars, camera, and field notebook and go
to the woods, leaving behind my laptop and any
analytical tools that may have crept onto its hard drive.
Surrounded by nature, I'm reminded what the
science of ecology is supposed to be about in the first place.
Happy Nature Watching!
BILL
Please visit our web sites (courtesy of Comporium.net):
Hilton Pond Center for Piedmont Natural History at http://www.hiltonpond.org
"Operation RubyThroat: The Hummingbird Project" at http://www.rubythroat.org
[EMAIL PROTECTED]
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Does this imply that the umbrella term 'science' needs to be rethought?
Yes maybe a rhetorical question, but it is
becoming apparent that certain scientific
endeavors do not benefit from a unified scientific method approach.
The question, based on observation, even
hunch, needs to be asked. Some answers may
surface from techniques other than a rigorous scientific approach.
Some of the issues we deal with border on
philosophy, some on acceptance of central
dogmas. The central dogmas live because they
serve well - DNA/RNA/Protein is one of them. But
are alternate mechanisms viable in hitherto undescribed (alien?) life forms?
I surely am not equipped to dispute any of the
central dogmas, but once we invoke dogma, are we
not, ipso facto stepping out of 'science'
Esat Atikkan
David Bryant <[EMAIL PROTECTED]> wrote:
On Mar 9, 2006, at 7:29 AM, Bill Silvert wrote:
> One of the greatest scientific
> events of the past century was the discovery of ecosystems based on
...snip...
> these and other major scientific developments would not pass the
> rigorous
> tests of "correct science".
>
> Bill Silvert
Indeed, in my opinion, most field experiments should start with
adequate recon and descriptive characterization prior to rigorous
experimental manipulations. Shouldn't one know what one is
manipulating first? Descriptive studies often become the basis for
models that can be used to find testable hypotheses and design
appropriate experiments. However has anyone in the last 20 years
received funding for a descriptive study? Moreover when was the last
time any major American journal (Ecology for example) published one?
Referring to previous posts on this thread:
I think it equally myopic to pass judgement on the science of others,
as much of this is personal opinion. Granted however that's the
whole point of peer-review. Lets just try to remember that no
experiment can control for every factor, and sometimes not even those
we hope to, but the data almost always shows us something. I agree
that we could benefit greatly from consulting statisticians a
priori. But I'm sure we've all had to deal with the issue of
publishing a pile of data from a flawed project. Such lessons are
often only learned after the fact.
As a recent publisher of a descriptive study of coarse woody debris;
I think we could benefit from removing the logs in or own eyes
before looking for the splinters in other's. ;-)
David M Bryant Ph D
University of New Hampshire
Environmental Education Program
Durham, NH 03824
[EMAIL PROTECTED]
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Ecology has, to me at least, been evolving more and more towards more
sophisticated analyses of smaller and smaller collections of data. The
thing that makes science different from other philosophies is the
requirement for a correspondence with nature. If you propose an
explanatory model, nature has to actually behave as your model predicts,
and you have to show it; hence the value of statistics. However, in the
absence of an explanatory model, statistics have no meaning.
It seems to me that the more observations (ie facts) you have in your
colection of data regarding some phenomenon, the more likely you are to
develop a robust model. Unfortunately, going out into the field and
spending a lot of time collecting information on a subject has little
prominence in ecology these days. This leaves us with a lot of
explanatory models with too many sentances explaining too little of
nature. I suspect that if ecologists knew more about the actual
organisms they study, we could come up with models containing far fewer
sentances with far more explanatory power.
Rob Hamilton
"So easy it seemed once found, which yet
unfound most would have thought impossible"
John Milton
________________________________________
Robert G. Hamilton
Department of Biological Sciences
Mississippi College
P.O. Box 4045
200 South Capitol Street
Clinton, MS 39058
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am not sure that all statisticians would agree,
although I do (but I am not a statistician). I
used path analysis quite a bit during the 1970s
and was strongly attacked for doing so by a very
well-known statistician who insisted that one
could not introduce causal reasoning into
statistical models. I interpret this as meaning
that if there is a correlation between having
broken legs and being hit by cars one cannot
infer that being hit by a car can break your leg
- maybe it is just that people with broken legs
have a hard time keeping out of the way of cars.
But as I have argued several times before, we
need to be very wary of letting statisticians
tell us how to do science. And once again I want
to point out that when I refer to modelling I
refer to representations of how the system works,
and not to statistical models, which are just arbitrary fits to the data.
Bill Silvert
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This discussion is getting long and repetitive, and it is about time to end
it. Nevertheless, I would recommend you to read my contribution on "Bias" in
the April 1st (All Fools Day) issue of BEN (Botanical Electronic News):
http://www.ou.edu/cas/botany-micro/ben/ben188.html
All the best,
Adolf
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Adolf Ceska, Ph.D. - Ceska Geobotanical Consulting
P.O. Box 8546, Victoria, BC, Canada V8W 3S2
Phone: 250-477-1211 Cell/Mobile: 250-216-1481
E-mail: [EMAIL PROTECTED] or [EMAIL PROTECTED]
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BEN archive: http://www.ou.edu/cas/botany-micro/ben/
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Dear ecologists --
Hamerstrom Science, as described by Dr. Joe
Schmutz in his published letter in a past issue
of the Journal of Raptor Research, emphasized
uninhibited, massive gathering of data over long
periods of time. There was no formula for the
gathering of the data other than to provide all
the knowledge that could be gathered on a species
or habitat under study, with the goal of gaining
personal knowledge until patterns of nature could
be identified and explained. The Hamerstroms
knew that many patterns of nature could, indeed,
be explained without the process of complex
mathematics, if enough data were gathered to
allow the patterns to reveal themselves to astute observers.
This is in diredt contrast to the rigorous
practice of formulaic science (constricted focus,
specific model, limited sample, limited data
gathering, rigorous mathematical analysis). Here
I will share two recent papers based on
Hamerstrom data that were gathered over many
years without anticipation of the hypotheses of
the final users of their data. In the case of
the prairie chicken genetics paper, this
unanticipated use of Hamerstrom data offers the
unanticipated prospect of resolving a serious
conservation issue that was no doubt
unanticipated at the time of original data
gathering. I will provide further discussion
after presentation of the recent papers, which
were published years after the deaths of both Frederick and Francis Hamerstrom.
Molecular Ecology
Volume 13 Page 2617 - September 2004
doi:10.1111/j.1365-294X.2004.02264.x
Volume 13 Issue 9
Temporal changes in allele frequencies and low
effective population size in greater prairie-chickens
JEFF A. JOHNSON*, M. RENEE BELLINGER, JOHN E. TOEPFER and PETER DUNN*
Abstract
The number of greater prairie-chickens in
Wisconsin has decreased by 91% since 1932. The
current population of approximately 1500 birds
exists primarily in four isolated management
areas. In previous studies of the Wisconsin
populations we documented low levels of genetic
variation at microsatellite loci and the
mitochondrial DNA control region. Here we
investigate changes in genetic structure between
the four management areas in Wisconsin over the
last 50 years. We estimated the harmonic mean
effective population size (Ne) over the last 50
years by comparing allele frequencies from the
early 1950s with those from contemporary samples.
Using a pseudo-likelihood approach that accounted
for migration, estimates of Ne (1532
prairie-chickens within each management area)
were 10 times lower than census numbers from
booming-ground counts. These low estimates of Ne
are consistent with increased habitat
fragmentation and an increase in genetic
isolation between management areas over the last
50 years. The reduction of gene flow between
areas has reduced Ne, increased genetic drift
and, consequently, reduced genetic variation.
These results have immediate consequences for the
conservation of the prairie-chicken, and
highlight the importance of how mating systems
and limited dispersal may exacerbate the loss of
genetic variation in fragmented populations.
Seasonal Variation in Sex Radtio of Fledgling
American Kestrels: A Long Term Study. The
Wilson Bulletin, Volume 114 (4): 474-478,
(2002). Griggeo, Matteo, Hamerstrom, Frances,
Rosenfield, Robert N., Taveccia, Giacomo.
The Early Bird Hypothesis predicts that males
fledged early in the breeding season have an
advantage over their later-fledged counterparts
during competition for breeding sites. We tested
this hypothesis by examining the sex ratio of
1,025 fledglings from 265 broods of American
kestrels, breeding in nest boxes in Wisconsin
during the period 1968-1997. We found a seasonal
shift in the sex ratio, the sex ratio of
fledglings was biased towards males early in the
breeding season, but became increasingly biased
towards females as the season progressed. Our
results provide support for the Early Bird
Hypothesis and suggest that the steepness of this
trend may decrease with increasing lattitude.
Discussion: The Hamerstroms were graduate
students of Aldo Leopold at the University of
Wisconsin-Madison. Frederick was one of only
three Leopold students to attain a PhD and Fran
was the only woman graduate student at attained a
Master's Degree under Leopold. The Hamerstroms
worked together on greater prairie chicken
ecology under Leopold, but Fran found it
difficult to separate his prairie chicken work
from Frederick's in preparation for a thesis, and
suggested to Leopold that she write up results of
a private project she worked on in study of
dominance in a winter flock of chickadees, in
which she used innovative field techniquest to
mark chickadees in her home garden, a project
which was unknown to Leopold until Fran completed it.
The Hamerstroms resumed their prairie dhicken
project in Wisconsin after their schooling and a
delay related to WWII and a short tint at a
nature preserve in Michigan. The goal of prairie
chicken work was to understand the ecology of
these grouse so as to devise management
strategies to conserve the rapidly dwindling
population of these birds in Wisconsin.
Little was known about the behaviors and ecology of these lekking birds.
What was the meaning of behaviors on the booming
grounds? Where did the hens go to nest, how far
from the booming grounds, what happened to the
cocks after displaying, what did they heat, how
did they roost, how did they survive the winter
in frigid Wisconin? All these questions were
subjects for investigation and the Hamerstroms
quickly realized that they could not gather
adequate data with their own personal
resources. So, the Hamerstroms recruited help
from literally thousands of volunteers around the
state who they trained to gather and record data
from blinds on booming grounds. The volunteers
were trained, housed, fed, and debriefed on a
daily basis for weeks at a time during the
breeding season, and the Hamerstroms also
trapped, banded, took feather samples, etc. of
prairie chickens on a large study area in drained
marshes near their residence in Plainfield, Wisconsin.
Meanwhile, Fran noticed the sky dancing of
northern harriers and began asking questions
about harriers, which she decided to investigate
in her "spare time". So she also trapped and
banded and innovatively marked
harriers. Phenology of arrival of migrant
harriers to nesting grounds was recorded. Nest
success was documented. Prey availability was
documented by prey censusing and compared to
nesting success of harriers, and dynamics of
polygamy by male harriers during seasons of high vole abundance was documented.
Meanwhle, Fran noticed that American kestrels
were present in the Marsh but hardly nested. A
hypothesis suggesting that lack of nesting
substrates limited kestrel breeding was
formulated and nesting boxes were built and
installed. Voluminous data on kestrel nesting,
egg laying, molt, reproductinve success,
competition with other animals for provided nest boxes, etc. was documented.
This was not done according to modeling
formulas. The data gathering was voluminous and
awaited analysis until patterns became virtually
self-defining. Much was learned and published in the scentific literature.
Perhaps much can still be learned from Hamerstrom
data if subjected to further analysis.
In years after the death of the Hamerstroms, some
colleagues, such as Dr. John Toepfer understood
the potential additional benefits that might be
obtained by further analysis of stored Hamerstrom
data. Dr.Toepfer was concerned about possible
genetic bottlenecking of prairie chickens, and
subjected Hamerstrom-gathered tissue samples to
genetic analysis, uncovering disturbing patterns
indicating that gene flow had become seriously
constricted over the decades by habitat
fragmentation and isolation of breeding stock from other subpopulations.
FINAL THOUGHTS
The rigorous practice of formulaic science is by
its very definition, constrictive of focus. It
constrains data collection. It limits what can
be learned in the pursuit of precise answers to
precise questions with unbiased precision in
analysis. This is well and good, and when this
form of science is practiced in experimental
studies or in studies designed to measure the
impacts of management or natural change, it is
vital that such self-limiting focus be preserved.
Hamerstrom Science was different. It had an
expanding focus. It was more descriptive and
less experimental. It was able to identify and
explain patterns in nature, both by the
Hamerstroms and by collaborators after the death
of the Hamerstroms using analytical tools unknown
or unanticipated by the Hamerstroms
themselves. I see further possiblity of
interesting patterns being explained, in full or
in part, by Hamerstrom Science and Hamerstrom
data. For instance, the Hamerstroms gathered
data on the phenology of egg-laying by American
kestrels. An interesting hypothesis that could
be investigated with Hamerstrom field data would
suggest that Kestrel egg laying dates have moved
forward seasonally in correlation with the
anticipated impacts of global climate change over time.
Lastly, though the Hamerstroms were not mentioned
in the following paper, the philosophy inherent
in Hamerstrom Science was well-described in a
very nice paper that I recommend as follows:
"Wildlife Biology and Natural History: Time for
a Reunion". Steven G. Herman. Journal of Wildlife Management 66 (4): 933-946
Abstract: I find considerable evidence that
wildlife management has broken partially free of
its roots, and is showing signs of
malnourishment. It is also best with various
ailments, including addiction to technology, lust
for statistics, professional hubris, and the
delusion that research and management are
synonymous. The wildlife management disclipline
started as applied natural history, and most of
its star practitioners were broad-based
naturalists, intimate with the landscapes and organisms in their charge.
There are reasons to believe that the wildlife
profession would do well to regraft itself to
those natural history roots, especially in view
of the changing roles that will be manifest as this century comes of age.
I am friends with Dr. Steve Herman and I am sure
that neither he or I are particularly relgious,
but I think Steve with not mind if I responded to
his paper by saying "Amen, brother".
Cheers! (and apologiies for any typographic
errors -- this took a while to type and I don't
quite feel like editing this from the computer screen and send it out "as is")
Stan Moore San Geronimo, CA [EMAIL PROTECTED]
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To me, science is a framework for learning and
most importantly communicating the insights
gained. It is certainly not one "coherent" and
prescriptive method that tells me how to do
research step by step in a recipe like fashion.
The single largest value of science to me is that
it helps to communicate results efficiently and
most importantly to convince other people more
effectively than most other forms of
communication. The "convincing" part is important
to me, because I believe that knowledge is mostly
intersubjective agreement. The scientific method
allows a certain trust in research and its
results among the people who use it and beyond
through transparency and repeatability. Those are
the real values of science to me.
Statistics play a mixed role in this paradigm.
Partly, they help elucidating otherwise obscure
or at least uncertain bits of information.
However, they are often also used to obfuscate
weaknesses in the research approach or
uncertainties in the results and their interpretation.
Personally, I think that the least talked about,
least taught and most obscure step in research is
the creative part. One is supposed to think up
hypotheses, ideally several competing ones, that
are all plausible, construct an experiment to
differentiate between them and so on. But ideas
don't grow on trees. There is much guidance in
science teaching on how to proceed, once good
ideas are present, but where does the inspiration
come from? The literature? The amount of
literature out there is so overwhelming, that it
surely can be inspiring good ideas but also
thwart them because of the nagging fear that
certainly someone else must have already had this
idea and published on it - I just haven't found
it yet. There is certainly no paucity of
interesting ideas out there, and I'm sure that
many of you have stores of interesting ideas that
you never found time to pursue. But the problem
is finding a GOOD idea, that is groundbreaking, doable, and publishable.
Cheers
Volker
[EMAIL PROTECTED]
