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:[email protected]] On Behalf Of Rebecca Weissinger
Sent: Monday, June 03, 2013 9:54 AM
To: [email protected]
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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