Invasive Species
Plot Sampling: Density
How do scientists measure the size of plant populations in a study area? They could count every
individual plant, but you could imagine how long this would take for small plants in a large area – just
imagine trying to count all of the individual blades of grass in a football field! When conducting plant
ecology research on invasive or other species, scientists often select several smaller sample plots
inside a larger study area. The scientists thoroughly study the smaller areas, and use information from
these plots to make generalizations about the larger study area.
For plants that are large and relatively easy to count, scientists typically count each stem in a sample
plot to determine the density. Density is the number of plants per area. For information on how to
measure smaller plants, read about Protocol 2 and percent cover in Invasion Ecology. In this protocol
we have included instructions for measuring density in 1 m2 plots. If this area is too big (for example,
because plants are too dense), or too small (for example, because plants are too sparse), you may alter
it to suit your needs.
Before you make measurements on your plants, you will need to determine what species you hope to
study and in what study areas you will work. Refer to the Early Detection Protocol for information on
how to select a study area and study species.
Once you have determined your study area and what species you will be measuring, you need to
select sample plots. There are many ways to select plots, but using an accepted method will help you
avoid bias. For example, imagine a research project on the side of a steep mountain. Getting to plots
at the top of the mountain takes more effort than getting to plots closer to the bottom, so at the end of
a long day of fieldwork, researchers might – perhaps unknowingly – select more plots near the bottom.
To avoid this and other types of bias, scientists have developed several methods to locate plots in a
large study area. Read about two methods you may use for locating your sample plots.
Materials
• Quadrat frame (building a quadrat frame)
Procedure
1. Decide how many plots (also called quadrats) you will sample. A rule of thumb is either a
minimum of ten plots or one 1 m2 plot per 100 m2. The number of people you are working with
may affect how many plots you use.
2. Locate the sampling plot using either random or stratified selection methods.
3. Lay out the 1 m2 quadrat on the ground at the first sampling point you have chosen.
4. Count the number of stems in the plot (i.e., density). Record this number separately for each
species. If the stems are numerous, you can avoid double counting by starting at one corner of
the plot and moving systematically across the plot. You also can hold or mark stems you have
counted, or place a plastic wand or thin stick between the counted and uncounted stems. For
information on measuring percent cover (as opposed to density), read about Invasion Ecology.
Percent cover measurements are useful in plots containing a large number of smaller plants.
5. If you encounter species you cannot identify, (a) describe the species (for example, 1 m tall,
purple flowers), (b) collect a sample from outside your plots, (c) try to identify the species using
identification keys or by asking experts, and (d) press the specimen for use as reference for
future surveys.
6. Repeat this procedure for all of your plots.
Analysis
You can use the data from your plot surveys to make generalizations about density in the larger study
area. To do this, you will need to compile the results for all the plots in a particular area. You can
determine the average density for each of the species you measured for all your plots. After gathering
together all the plot data, calculate the average density for each species found in your large study area
using the formula below.
Average species density = [ (density in plot 1) + (density in plot 2) + (density in plot X)
] / total number of plots
For example, consider a series of 5 plot surveys conducted in a schoolyard. Each plot is 1 m2. Purple
loosestrife was found in 4 of the plots in the following amounts: a) 85 stems, b) 53 stems, c) 64 stems,
d) 33 stems.
Average species density = [ 85 + 53 + 64 + 33 + 0 ] / 5 = 47 stems/m2
You can use the average density to compare different species, to compare the same species from
several different sites, and/or to compare sites where control measures have and have not been
implemented. However, you cannot compare species measured using density with species measured
using percent cover.
A Look at Variability
How much variability did you find in your results? Was the species density similar in all of your
plots? For example, did some of your plots have very few or no plants, while other plots had a great
number of plants (high variability)? Do you think your average species density is an accurate
representation of what is growing in the larger study area? If not, would sampling more plots help?
What could be some reasons for any variability you see?
Questions to consider
You may be interested in designing experiments that will help you answer some of the following
questions.
1. Did you find any species that were present in all plots or had very high densities? What are
some reaons that would explain this? How could you test your reasons? What about species that
were not present in all plots or had very low densities?
2. How did the density of the invasive species compare with the other species in the study area? If
you go back to the same site during several seasons, you may be able to monitor a change – if
so, what is the change?
3. If you have more than one study area, how do the densities of a single species compare between
the two sites? Are the densities very similar, or are they very different? What are some reasons
that might explain this?
Invasion Ecology, an EI publication, has additional protocols and suggestions for how you can
measure the impact invasive species have an ecosystems.
Copyright © 2009 Environmental Inquiry, Cornell University and Penn State University
http://ei.cornell.edu