Environmental Engineering Reference
In-Depth Information
Dominance or importance: Which species is most important in its influence on
the community or ecosystem? This attribute is often assessed during the analysis
stage by creating composite scores using different attributes, such as relative
cover or density. However, attributes like height or basal area (calculated from
tree diameters) may be important to collect in the field.
Spatial pattern: Is the vegetation dispersed in a clumped, random, or regular
pattern?
5.3.2 The Sample Unit: Plot-Based and Plotless Techniques
The choice of sample unit will depend upon the size of the plants, the resources
available (time and money), and the ease of using the subsequent data to meet the
specific goals for your analysis or report.
Plot-based techniques assess vegetation within an area of pre-defined size and
shape. These techniques have the advantage of leading to relatively straightforward
calculations of density and other summary attributes in the analysis stage, because
they have a known area. The size of the plot typically relates to the size of the
organisms studied. For example, a larger plot will be used to assess trees than to
assess understory vegetation. In order to capture a wide variety of species in
understory vegetation, plot sizes from 0.01 to 1.0 m
2
are typical and sometimes
nested within each other (Elzinga et al.
1998
). A common plot size for trees is
100 m
2
. Plots can frequently be nested around a common point when investigating
multiple strata (e.g., understory, shrubs, trees). Small plots are often called
quadrats. As a general rule, the plot should be roughly twice the size of the largest
organism in your sample (Greig-Smith
1983
). Other researchers suggest that plots
be as large as possible given time and effort constraints (Kenkel and Podani
1991
).
Organism spatial distribution should be considered. If plant populations are clus-
tered, researchers should be sure that plots are not of a size that will result in
numerous empty plots when they land in between plant clumps (Elzinga
et al.
1998
). Another good strategy for choosing plot size is to use previously-
published studies. For a detailed discussion of plot size, see Elzinga et al. (
1998
).
The effects of plot shape have also been debated by ecologists (discussed in
(Krebs
1998
)). Some argue that a rectangular plot is most effective because it
captures the most vegetation heterogeneity (with quadrats oriented to capture
variability within plots as opposed to between). Others argue that circular or square
plots are best because they minimize edge effects and require the least amount of
subjective “in or out of plot” decisions on the part of the worker due to their low
perimeter:area ratio. Choose the plot shape based upon the purpose of your study.
If the purpose is to capture the maximum heterogeneity, a rectangular plot will be
most suitable. If not, choose a square or circular plot in order to maximize accuracy
and minimize edge decisions (U.S. EPA
2002
).
Nested plots (where smaller plots are located within larger plots) are used for
many reasons. The most common use of nested plots is to survey vegetation within
