I thus rest previous cases on the subject of the importance of clarity of
terminology.
However, should there be discussion on the relative value of quicker and
more crude methods for getting a handle on what's there? As long as one
takes observer error out, Braun-Blanquet (aka "Brown Blanket") and other
methods may still serve some purposes, provided their limitations are
well-recognized and one doesn't attempt to make a silk purse out of a sow's
ear, eh? Take care to know what you are walling in and what you are walling
out, as Frost might say. And that goes triple for leaving out species and
whole groups like grasses, non-vasculars, and even fungi and microorganisms.
Hell, I think that soil organisms should be sampled too--everything that's
relevant (and what isn't?). Speaking of soils, for an excellent brief
treatise on scientific method, read page 4, and, I think, page 5 or so of
"The Micromorphological Features of Soil Geography" by
Walter L. Kubiëna.
WT
----- Original Message -----
From: "Rheinhardt, Rick" <rheinhar...@ecu.edu>
To: <ECOLOG-L@LISTSERV.UMD.EDU>
Sent: Monday, June 03, 2013 3:43 PM
Subject: Re: [ECOLOG-L] plot sampling for density
Concerning my post about the proper way to determine the density of woody
species in fixed plots, contributors to the discussion unanimously agreed
that only species mostly rooted in a plot (>50% within plot) should be
tallied. Otherwise, the true plot size is unknowable if species rooted
outside the plot are included. Rebecca Weissinger provided a link to an
excellent treatise on measuring and monitoring plant populations
http://www.blm.gov/nstc/library/pdf/MeasAndMon.pdf ,which also discusses the
importance of designing studies to meet management and sampling objectives
and statistical analysis of collected data. Of course, as with any study,
one must have a firm grasp on objectives before designing a study and the
pros and cons of various methods that can be used, including limitations
concerning time, effort, and funding constraints. I suspect that various
aspects of designing vegetation studies have been discussed on and off in
this forum already and will continue to be.
Thanks for everyone's input to my basic question about density measurements.
It seems that much of the problem stemmed from the term "stem" being
undefined in the protocol. Funny how the misinterpretation of one word can
wreak so much havoc.
-----Original Message-----
From: Ecological Society of America: grants, jobs, news
[mailto:ECOLOG-L@LISTSERV.UMD.EDU] On Behalf Of Palmer, Mike
Sent: Monday, June 03, 2013 12:25 PM
To: ECOLOG-L@LISTSERV.UMD.EDU
Subject: Re: [ECOLOG-L] plot sampling for density
For those of you interested in questions of sampling and analyzing
vegetation, You are not alone!
I will put in a plug here for the International Association of Vegetation
Science (IAVS) -
On the web:
http://www.iavs.org/
On Facebook:
https://www.facebook.com/#!/groups/iavs.org/?fref=ts
--Mike Palmer, Oklahoma State University
-----Original Message-----
From: Ecological Society of America: grants, jobs, news
[mailto:ECOLOG-L@LISTSERV.UMD.EDU] On Behalf Of Rebecca Weissinger
Sent: Monday, June 03, 2013 9:54 AM
To: ECOLOG-L@LISTSERV.UMD.EDU
Subject: Re: [ECOLOG-L] plot sampling for density
Any well-designed long-term monitoring program should include definitions of
what is "in" and "out" in a plot. For a good discussion of density, see
Chapter 8 Section F in Elzinga et al's Measuring and Monitoring Plant
Populations, particularly Figure 8.3 for discussions of boundaries.
http://www.blm.gov/nstc/library/pdf/MeasAndMon.pdf
The protocol you are using is definitely unusual in counting stems that are
rooted out of the plot. If this program is just starting out, by all means
improve the protocol with definitions of stems and how to treat boundaries.
However, it sounded to me like there is already a reasonably long history of
data collection. If that is the case, I would attempt to analyze the data as
is and keep the methods the same, as the value of a long-term dataset may
outweigh an improved technique that would be unable to incorporate previous
data. If the previous data are unusable because of the slop, then it is
worth attempting to correct the problem. If you can use the old data but
still want to improve the methods, one way to transition is to do both
methods side-by-side for several years to get a "correction factor" that can
be applied to previous years of data.
As examples, the U.S. National Park Service Inventory and Monitoring program
has many long-term monitoring protocols available that could be useful.
https://irma.nps.gov/App/ProtocolTracking
Try searching under Biological Integrity/Forest/Woodland Communities for
examples.
-----
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