Research Methods

• Study Design
• Sampling Earthworms
• Sampling Plants
• Sampling Trees
• Sampling Soils

How many plots and what size of plots should I use for sampling plant communities?

A common plot size for sampling vegetation is 10 x 10 meters, which is large enough for sampling trees and understory plants, but not so large as to be difficult to sample or replicate. There is no magic size that is inherently better than another. You want to select a plot size that is large enough to capture some of the variability in your plant community (usually at least 1m2 for understory plants), but not so large that it becomes impractical. The size and distribution of the particular plants of interest also affect the plot size. For example, if you are sampling trees, you need a much larger plot than if you are only sampling small understory plants. Sometimes it is necessary to use one sized plot for some plants (like trees) and another size plot for others (like understory plants). Perhaps more important than the size of the plots, is the total area sampled. You want to sample enough plots so that the total area sampled accurately captures the composition and diversity of the plant community of interest. Calculating a species-area curve for your study site is a very good way to assure that this goal is met (click here to read more about species-area curves).

Sampling plant species diversity

Plant diversity seems like a simple thing to measure, simply count the number of species, right? Well, yes and no. For example, say there are two sites that each contains 15 plant species. In one site, two of those species account for 90% of the total plant community with the other 13 species being present at very low levels, while in the other site, all 15 species are about equally abundant. Do these sites have the same diversity?

Sometimes, it is desirable to have a measure of diversity that includes both richness (number of species present) and their relative abundance. Several indices of diversity have been developed to help you do just that (see table 3 below). One that is very commonly used in plant communities is the Shannon Diversity Index, indicated by the symbol H’. I can be very interesting to see how the different measures of diversity can sometimes give different impressions of the same plant community!

Sampling plant abundance

The two most common measures of plant abundance include stem counts and percent cover. Each has their pro’s and con’s. Depending on the questions you are asking, sometimes it is desirable to use both.

Stem counts are accurate when determining the population size of a particular plant species, but can be time consuming in areas with dense plant communities. Plus it is always a challenge to figure out how to count clonal species like grasses that have many stems for each individual. Also, individuals of different species can vary a lot in size! For example, when using stem counts, a small violet is counted the same as a very large fern. When examining plant population dynamics within species, stem counts are the way to go. But when looking at overall plant communities, sometimes a measure of “how much space” a particular species occupies is a valuable thing to know. That’s where percent cover can be helpful.

Percent cover is a method of determining relative abundance based on the amount of space they take up. In this method, rather than counting the number of individuals you assign each species to a “percent cover class” based on a visual estimate of how much of the sample plot they occupy (see figure 1 below). The reason most scientists use cover classes, rather than assigning a species number, like 16% or 48%, is that most people would not select the same number if they were looking at the same sample plot, it’s just too subjective. However, research has shown that most of the time, most people will select the same cover class when looking at the same sample plot, so it is a more reliable measure of plant abundance.

The Braun-Blanquet cover/abundance scale (adapted from “Aims and methods of vegetation ecology” by D. Mueller-Dombois and H. Ellenberg. 1974. Wiley New York) is perhaps the most commonly used in plant ecology:

A 1 x 1 meter sample plot for sampling the understory plant community.	Visiually dividing the sample plot into sub-sections can help in estimating the percent of the sample plot occupied by different species.
Osmorhiza claytonii (sweet cicely) Cover class 3 = 25-50%	Matteuccia struthiopteris (ostrich fern) Cover class 2 = 5-25%
Maianthemum canadense (Canada May Flower) Cover class + = few individuals less than 5%	Viola pubescens (Canada Violet) Cover class 2 = 5-25%
Acer saccharum (sugar maple) Cover class 2 = 5-25%	Asarum canadense (wild ginger) Cover class 2 = 5-25%
Bare soil Cover class 2 = 5-25%	Total cover of all plants combined Cover class 5 = 75-100%
Figure 1. This series of images illustrate how percent cover was assigned to each of the understory plant species a 1 x 1 meter sample plot. When estimating percent cover it is handy to divide the plot visually into subdivisions of known percent and then try to visualize whether the cover of a given species will fit into a given space. For larger plots, marking the sided of the plot with flagging at several locations can help visualize this. Notice that percent cover values were recorded for “bare soil” and “total cover of all plants combined” as well as for each species. These can be very important parameters to measure since they indicate what proportion of the forest floor is shaded by plants and what proportion plants are not growing in. You can also see that the sum of the cover values of the individual plant species can be more than 100% because they may overlap, that’s another reason it’s a good idea to record the total cover for all plant species combined.

Sampling different layers of a forest
In addition to plant species, forests also have structural layers, and it is often the case that the plants occupying different structural change as you move from the seedling layer to the herbaceous plant layer to the sapling layer, and on up through the forest. How the species and relative abundance change with structural layer in the forest call provide insight into the past history and the future succession of the forest. For example, many oak dominated forests today have thick sapling layers of sugar maple due to historic fire suppression, indicating that as the mature oak trees begin to die back, they will probably be replaced by sugar maple and this has implications for forest organisms, nutrient cycling and other ecosystem processes.

The structural layers of most interest in hardwood forests of the Great Lakes region include:

1. Tree layer (canopy) – includes all tree species with diameter at breast height (dbh) greater than or equal to 10 cm.

2. Large Saplings & Shrubs (sub-canopy layer) – includes all woody species, large tree saplings and shrubs greater than or equal to 2m tall and <10cm diameter at breast height (dbh).

3. Small Saplings and Shrubs (sapling layer) – includes all woody species, small tree saplings and shrubs greater than 0.5m tall and less than 2m tall.

4. Seedling layer – includes all woody species, tree seedlings and low shrubs, less than or
   equal to 0.5m tall.

5. Herbaceous Plant layer – includes all non-woody herbaceous, grass and grass-like plant species, irrespective of how tall they are.

   NOTE: Sometimes the seedling and herbaceous layers are combined since they occupy the same physical space. However, depending on the questions being asked, it is sometimes desirable to keep them separate.

Estimating percent cover of plants by structural layer is done in the same manner as described above, but the cover estimates only include plants in the given structural layer. For example, a tree sapling who’s top reaches the uppermost canopy, but has a dbh of 9cm, would be included in the “Large Sapling & Shrub” structural layer, not the “tree” layer; or if a sapling is tall enough to be considered a “Large Sapling” but has most of it’s foliage below 2 meters, you still record that coverage in the “Large Sapling & Shrub” layer. Similarly, estimates for individual species within a given structural layer only include individuals in that structural layer. So, you may have the same species, especially tree species, present in more than one structural layer.

When estimating the total cover of a layer, you would generally include coverage from plants rooted outside the plot if they extend into the space above the plot. However, when assigning a percent cover value to individual species you would generally only include those plants that are rooted in the sample plot. If there is a large plant rooted outside the plot that contributes a lot of cover, you can record it simply as “OP” for “out of plot” so that information is not lost. In some analysis this data may be included; in others it may be excluded.

Sampling Trees

Because trees are large and ecologically very central to forest ecosystems, in addition to species composition, diversity and percent cover, an estimate of the basal area and density of trees in a forest can be important.

Dbh Tape

To measure the dbh of a tree, wrap the DBH tape around the trunk at “breast height” which is 1.4meters from the ground.

When measuring DBH, pull the tape tight around the tree so the ends overlap and then read the measurement to the nearest 10th of a centimeter. In this example, the dbh of the tree being measured is 32.8cm

Density is simply the number of trees per unit area and is generally reported as the number of trees per hectare (1 hectare = 2.47 acres). There are 10,000 m² per hectare (abbreviated as “ha”), so once you determine the mean (average) number of trees per plot you can easily convert it to this unit. For example, a 10m x 10m plot  = 100m². If you had an mean of 18 trees per plot, then the density would be 18 x 100 = 1800 trees/hectare.

Basal Area is the cross-sectional area of trees stem (trunk) at breast height. For individual trees, basal area is expressed as in square meters (i.e. 0.25m²). When estimating the average basal area of a forest stand it is generally reported as m² per hectare (i.e. 35m2/hectare). The basal area of a forest can be measured directly using a dbh tape or estimated by using a wedge prism.

A dbh tape is a specially calibrated tape that reads the diameter of the tree directly. The tape has a normal ruler on one side and the dbh scale on the other. Be sure to use a dbh tape calibrated for diameter in centimeters unless you want to convert from English to metric units.
Also, be sure to use the correct side of the dbh tape.  Wrap the tape around the tree at a dbh (~4 ft above the average ground surface), holding the tape tight against the bark and record the dbh as read from the dbh side of the tape (usually marked with a slash through a circle at the very tip of the tape).  Recording the dbh of trees is most easily done by two people working together, where one person measures and one records.

Once you have the diameter measurement of the tree, you can calculate its basal area using the formula for the area of a circle. The area of a circle = π x radius² , where pi (π) is equal to 3.14 and the radius is half the diameter.

So, if the diameter of your tree is 24cm, the radius is 12cm and the basal area would be:

Basal Area  = 3.14 x (12cm x 12cm) = 452.2 cm²

To convert the basal area to square meters, either

1. convert the original measurement to meters. In our example, 12 cm = 0.12 m. So, Basal Area  = 3.14 x (0.12cm x 0.12cm) = 0.045 m²
2. convert the final value from cm² to m² by multiplying it by 0.0001. In our example, basla area = 452.2 cm² x 0.0001 = 0.045 m²

A wedge prism is a forester’s tool for quickly determining basal area. The prism is cut in a particular way that shifts the position of the image of the tree trunk when you look at the tree through the prism. If the edge of the shifted image of the tree in the prism overlaps with the edge of the tree above the prism, then the tree is tallied. If the edges of the tree trunk don’t overlap the image in the prism, the tree is not tallied.  If the edged exactly meet, the tree is recorded as “borderline” and every other one borderline tree is included in the tally (see Figure 2 below).

The wedge prism survey is often done in conjunction with surveys done in a plot. In these cases, to estimate the basal area of the plot, you stand near the center the plot, holding the prism at the exact center. View trees at dbh height (diameter at breast height  = 1.4 m above the ground). Start tallying trees and move in a full circle until all potential trees have been examined. To ensure an accurate tally of trees to include, be sure the prism stays over the center of the plot when you view trees and then you rotate around it as you go.

Figure 2. This diagram showing the images you see through the wedge prism when a tree is to be counted, not counted or is borderline.

Once you have tallied the trees at your sample location, you multiply the tally by the basal area factor (BAF) of your particular prism to get the estimated basal area for that sample location. So, if you tallied 12 trees and your prism had a BAF of 10 (in English units), the basal area of that location would be 12 square feet/acre. In eastern hardwood forests, most people us a wedge prism calibrated in such a way that each tree tallied is equal to 10 square feet of basal area per acre, (BAF = 10). There are other BAF values (10, 15, 20, etc.) and you can get them in either English or metric units, so just be aware of what the BAF and units are for the prism you are using. No matter which prism you use, the process is the same, tally the trees and multiply the tally by the BAF of your prism to get the basal area, voila! Quick and easy!

If you use a prism calibrated in English units (ft²/acre), be sure to convert it to metric (m²/hectare).