# Calculating Species Importance Values

Overview:

Plant species vary in their responses to environmental factors. A given species will have a unique set of tolerances to environmental variables, such as light, temperature, moisture, and nutrients. At the community level, these differences in tolerances will cause various species to have competitive advantages, depending on the nature of those environmental factors.

We will examine the distribution of tree species with respect to terrain properties. Several major environmental variables are impacted by terrain, including light, temperature and moisture. Steep slopes and ridgetops tend to be drier due to drainage. Temperature drops with elevation. Sunlight intensity and duration varies with aspect (i.e. the angle of the slope plane with respect to north). Solar radiation is greatest for south facing slopes in the Northern Hemisphere. Soil depth and nutrient concentrations typically decrease with elevation, although this relationship can be quite complex depending on hillslope geomorphology.

In any terrestrial watershed, then, we will expect to see vegetation controlled by terrain attributes. We hypothesize that tree species distributions will differ with respect to hillslope position (streamside vs ridgetop). As a first step, you must decide on your research question.

Using data gathered at our study site, we will analyze vegetation distribution and abundance using the point-quarter sampling method. We will estimate the density, frequency, and coverage of mature trees and calculate the importance values. Then, we will compare these values to another site. The methods used come from Chap 3 in Brower, Zar and von Ende (1997).

Vocabulary:

Point-quarter sampling method

Quadrants

DBH

Mean point-to-plant distance

Relative density

Absolute density

Frequency

Relative Frequency

Coverage

Relative Coverage

Importance Value

Importance Percentage

Materials:

1. Data Sheet

2. Measuring Tape

3. Compass

Procedure:

1- Each team will calculate importance value for their study sub-plots. Make sure your class has set out the transect, and your team has set out its sub-plot before proceeding. Select a number of randomly determined points (e.g., within each study sub-plot, or, within the subplots for each habitat type being studied, e.g., streamside, ridge). Each point represents the center of four compass directions (N, S, E, W) that divide the sampling site into four “quarters” or quadrants.

2- In each quadrant, measure the distance and slope angle from the center point to the center of the nearest individual, regardless of species. Only one plant per quadrant is measured, so that a total of four plants are recorded for each point sampled.

3- Identify the plant, and record its diameter at a height of 137 cm above the ground. This is known as DBH, or diameter at breast height.

The center of the rooted stem or the center of the crown of a clump of stems should be used when measuring the point-to-plant distance. If two plants are fairly close, be sure to measure the distance of both and record the smaller distance from the center point. Do not depend on visual perception of the distance to judge the closest plant, since there is a tendency to judge the larger of two plants as the closer. Record all measurements in your field book, using the format specified.

Calculations:

1- Sum all point-to-plant distances taken for all species and compute the mean: d-bar = Σdi/Σni (d-bar is the mean point-to-plant distance, di is the point-to-plant distance for an individual plant, and Σni is the total number of individuals measured)

The mean area in which a single plant occurs is equal to the mean distance squared. This relation can be visualized as one individual in a square area in which the side of the square is equal to the mean point-to-plant distance A-bar = (d-bar)2 (A-bar is the mean area per plant)

2- Calculate Relative density (RD) for each species, which is RDi = ni/Σni (ni is the number of individuals of a given species counted and RDi is the relative density of the given species).

The absolute density (D) for a species is Di = (ni/Σni)(u/A-bar) (u represents the number of area units to be used in expressing density. When hectare is used as the standard unit, u equals 10000 m2. [note that Di is also equal to RDi*TD, where TD is total density for all species, TD = u/A-bar])

3- Frequency is the chance of finding a given species within a sample, and is given by fi = ji/k (fi is the frequency of a species, ji is the number of sampling points at which the species was counted, and k is the total number of points sampled.)

Calculate Relative frequency. (Rf) is the frequency of a given species (fi) as a proportion of the sum of the frequencies for all species (Σf) Rfi = fi/Σf

4- Coverage (C) is the proportion of the ground occupied by a vertical projection to the ground from the aerial parts of the plant, and is given by Ci = (ai)(Di)/ni (ai is the sum of the basal areas (computed from DBH) for a species, Di is the density of the species, and ni is the total number of individuals sampled for that species.)

Calculate Relative coverage for a species, which is RCi = Ci/ΣC (ΣC is the total coverage or basal area for all species.)

5- The sum of the above three relative measures for a species is an index called the Importance Value (IVi) IVi = RDi + Rfi + RCi The value of IV may range from 0 to 3.00 (or 300%). Dividing IV by 3 will result in a figure that ranges from 0 to 1.00 (or 100%). This value is referred to as the importance percentage. The importance value, or the importance percentage, gives an overall estimate of the influence of importance of a plant species in the community.

Results:

Determine the two most dominant tree species in your sub-plot, compare these values to another site, and use the appropriate statistical tests to determine if (a) their mean diameters differ by sample location, and (b) if there is any difference in frequency by sample location.

Discussion:

Were there differences in species composition and biomass as hypothesized in your research question?

Thanks to Dr. Alan Yeakley for this write up.