Biology 112
Fall 2005
Vegetation Sampling
The immediate goal of any vegetation sampling technique is the quantitative description
of the vegetation of a particular site. Because such information has numerous potential uses,
there is, understandably, a large array of available sampling methods. It is important to keep in
mind the ecological questions you are asking as you choose or design a method of sampling.
During this laboratory session you will have an opportunity to try two of the most
commonly used methods for sampling forest composition: the point-quarter method and the
quadrat method. You will also have an opportunity to compare the results of these methods with
a complete inventory of the sampled forest. This exercise will provide some insight to the
advantages and disadvantages of the methods. While you are using each of the methods, keep in
mind the tradeoffs between the effort invested and the amount of data collected.
A. Field Reconnaissance and Site Selection
It has become something of an old adage that the most important decision an ecologist
makes is where he or she stops the car. It is self-evident that one’s picture of vegetation will be
determined largely by the particular vegetation selected for close scrutiny. Not too strangely,
briar patches are under sampled relative to their importance in the landscape.
Two principal philosophies of site selection are found in the ecological literature. One
group composed primarily of the more mathematically and statistically oriented workers
emphasizes use of randomized sampling. The second group with a disproportionate
representation of experienced field naturalists favors subjective selection of plots to insure more
complete coverage of the major variation. We will use objective methods so as to better allow us
to evaluate the effectiveness of the methods.
In the selection of the actual plot locations, care must be taken to insure that the sites
selected are reasonably homogeneous. While this is difficult to test statistically, you should
make certain that there is no obvious trend in compositional change across your sampling unit.
The area selected for sampling is the “Big Oak Woods” portion of the North Carolina
Botanical Garden’s Mason Farm Reserve. This is an area of relatively uniform forest on gentle
terrain near Chapel Hill. This locality is also known to have poison ivy and biting insects, so be
prepared. In addition, the Big Oak Woods has the advantage that we have previously mapped all
the trees in our study area, thus giving us known values for parameters to be estimated by
sampling.
B. The Quadrat Method
Variations on the quadrat method are as old as ecology. We will use 10 x 10 m quadrats
located at 15 m intervals along grid lines that are 50 m apart. The dbh for all trees (>10 cm dbh)
and saplings (>2 cm and <10 cm dbh) will be recorded. (dbh = diameter at breast height, or 1.3
m above the ground.)
C. Point-Quarter Method
This method was originally designed for sampling flat, homogeneous Midwestern
woodlots of 10 to 40 acres where it is desirable to know the average composition. The technique
is a “plotless” method in that plots are not used. Rather, a grid of approximately 20 to 40 points
is established covering the region to be sampled. While placement can be either random or
regular in design, we will use a regular method. Transects will be established and points located
at 15 m intervals.
At each sampling point two perpendicular lines should be established with one parallel to
the main transect. In each of the resulting four “quarters”, the nearest tree (>= 10cm dbh) is
recorded by species, size, and distance from the point (to the center of the tree, not the edge).
The procedure is then repeated for saplings (>= 2cm dbh but <10cm dbh). [More typically,
saplings are not included, but we feel they constitute an important component of the community.]
The mean distance from the points to the designated trees can be used to obtain a value
for density, or the absolute number of trees per hectare. It can be shown mathematically
(Morisita 1954) that the average distance is the square root of the mean area occupied per tree.
Thus, dividing the square of the average distance into 10,000 (=m2/ha) gives the number of trees
per hectare. (This also means that distances can be recorded independently of species and
diameters.) The method assumes that trees are randomly distributed. If the trees are strongly
aggregated, their density will be underestimated, whereas if they are regular in their distribution
density will be over estimated. Usually this sort of error is rather small and can be ignored.
nearest
sapling
nearest
tree
Quadrat
Centers for point-quarter
method
Quadrat
Point-quarter method
10m
15m
Quadrat
5m
Sampling layout along transect
10m
D. Other methods
Other plotless methods (such as sampling the nearest two trees regardless of quarters - the
random pairs method) have been proposed. The quarter method remains the most popular,
however, for reasons of speed and efficiency of sampling (see Cottam & Curtis 1956, but also
Lindsey et al 1958 for a conflicting opinion).
When sampling vegetation, there are many other measurements which we could take. An
estimation of cover either by strata (canopy, understory, shrub layer, herb layer) or by species is
a common quantification of vegetation. Also, measurements and sampling designs vary
significantly based on the questions being asked. Nested plot designs allow you to determine
how species accumulate with area. If you are simply trying to capture the greatest number of
species in an area, a transect sampling method may be more appropriate.
E. The Assignment
Three datasets from the Big Oak Woods will be distributed:
1) Quadrat method – data from 100 m2 quadrats sampled by the class
2) Point-Quarter method – data from quarter points collected by the class
3) Complete Inventory – a summary of the tree and sapling data from a complete
enumeration of the area sampled in 1 and 2 above.
You will compare parameter estimates calculated from the sample data with “known” values of
the parameters determined for the complete enumeration. Details will be explained when the
data are distributed.
F. Selected References
Barbour, M.G., J.H. Burk & W.D. Pitts. 1980. Terrestrial Plant Ecology. Benjamin
Cummings. Chapter 8.
Bormann, F.H. 1953. The statistical efficiency of sample plot size and shape in forest
ecology. Ecology 34:447-487.
Cottam, G. & J.T. Curtis. 1956. The use of distance measures in phytosociological
sampling. Ecology 37:451-460.
Lindsey, A.A. et al. 1958. Field efficiencies of forest sampling methods. Ecology
39:428-444.