FIELD ECOLOGY, BIO 303

INSTRUCTOR: DR. JIM TAULMAN

An essential component of any ecological study is a description of the vegetation occurring at the study area. We will discuss the methods and rationale involved in measuring several common forest parameters.

LAYING OUT THE MACROPLOT

We will start by laying out the macroplot which will be used to sample forest habitat at a study area. A number of macroplots are randomly distributed throughout the study area. We measure vegetation in detail at theseplots then extrapolate those measurements out to create an estimate of total values per unit area, like acre, so that they are comparable with measurements taken at other study areas.

It is convenient to install a number of 0.04 hectare (ha) or 0.1 acre plots and measure forest parameters within them. Values can easily be extrapolated to units per ha by multiplying by 25 (25 x 0.04 ha = 1.0 ha) or to extrapolate to acres, multiply by 10 (10 x 0.1 ac = 1.0 acre).

After randomly selecting locations for a number of plot centers and pinning those, we start by laying out the macroplot boundary. We want to lay out a 20 x 20 meter square. That will create a 0.04 ha (400 sq m) plot. You could use 2 people and a tape measure to lay out your plot, but it is just as easily done with one person using a compass and hip chain.

(As a side note, some researchers believe that macroplots should be circular instead of square because a circle has a shorter perimeter than a square of the same area. The idea is that there is less “edge effect” on a circular plot. An ecological edge is a boundary between 2 different habitat types. Ecological edges are zones in which species that inhabit one habitat type may influence species in the adjoining habitat. For that reason, researchers studying a particular community like to be in “interior” areas, far from an ecotone or edge.

However, a plot boundary arbitrarily laid down within an interior portion of a habitat does not divide one vegetation community from another. Where you place a string plot marker within a forest type does not make the forest on one side different from that on the other; it is an arbitrary, artificial boundary that does not have any ecological significance. Nor does the length of the boundary around plots of the same area have any importance, since these are not ecological edges separating different habitats.)

A hip chain is a box with a spool of thread running through a meter that registers meters or feet traveled across the ground. We tie the hip chain thread off at plot center and go 10 m in a cardinal direction. We are now at the new plot boundary. We turn 90° and go another 10 m, making sure that the thread also makes the 90° turn by wrapping it around a twig or sticking a peg into the ground. After going 10 m you will be at your plot corner. You then turn 90° and proceed 20 m, again turning 90° to lay out the next side of the square. You finally come to the first side of the square where you go 10 m until you come to your original turn coming out from the center point.

10 meters 10 meters

10 meters

20 meters

20 meters

Now that the macroplot is finished and thread marks the boundary, you are ready to measure a range of vegetation parameters within it.

THE FIELD DATA SHEET

We need a field data sheet on which to record our measurements to take back to the office and to keep as a permanent record. The sheet will include all the parameters that you intend to measure and should also have room to make notes. A sample data sheet is shown below.

Habitat Type ______________ Plot # ________ Date __________ Crew _____________________

Density Canopy

Board – 10 m 0.25 m 1 m 2 m 3 m Coverage

North

East

South

West

Mean

Soil Soil Soil Horizon Depth Prism BA from

Moisture pH O A B C plot center

Pine/hdwd

Tree Count Percent Estimated Percent Ground Cover

> 2.5 cm and < 10 cm DBH Shrub Cover Down Bare

Pine Hardwood < 2 m height Grass Needles Wood Rock Ground

Tree Species

> 10 cm DBH DBH (cm) Height (m)

Mean DBH SE 95% CI Mean Ht SE 95% CI

Pine

Hardwood

TREE MEASUREMENTS

We will start by measuring all the trees on the plot above 4 inches diameter at breast height (DBH). If you have several species of trees present you may want to keep track of tree data by species. You also may just separate out pines from hardwoods and record them separately. Diameter at breast height is taken in order to get an idea of the girth of the tree trunk above the broad base near the ground. DBH is measured with a tape calibrated in inches or centimeters of diameter when stretched around the perimeter of the trunk. Since the circumference of a circle is π (3.142) x diameter, dividing the circumference by π yields the diameter. This calibration has been built into the DBH tape. If you measure a tree that has a circumference of 126 cm, the DBH tape will read 126/3.142, or 40.1 cm.

By taking DBH of all trees on the plot we will derive an estimate of the total tree cross sectional area on the plot and will extrapolate that figure to a per ha or per acre estimate. This will give us an estimate of what is called tree stocking or amount of standing timber density at a study area.

Our metric is called Basal Area and is the cross sectional area of all trees on the plot. From the diameter, which we measure, we compute cross sectional area of the tree, considering the tree to be circular in cross section. We use the formula for area of a circle = π x (radius)². We can add up all the areas of trees on the plot to get a total basal area of trees on the plot. We can also just take a mean of the DBH of all trees we measure and multiply that mean DBH by the number of trees measured to arrive at a total cross sectional area of trees on our plot.

Another way to get a quick but rough estimate of basal area of trees is to use a prism. Sighting through a prism offsets the trunk of the tree. Looking at the tree trunk and through the prism simultaneously you can see whether the prism has offset the trunk so much that one vertical side is moved outside of the line of the opposite vertical side of the real trunk.

If the offset does not move one side of the trunk past the other side, the tree is large enough, or close enough to the observer, to count in a tally, as shown in the 2 trees below.

However, if the one side of the trunk is offset by the prism completely outside of the other vertical side of the trunk, that tree is not large enough, or close enough to the observer, to tally. An example of a tree that does not tally is shown below.

You start at your plot center and sight all trees above a certain minimum size that you want to consider, such as 4 inches DBH, going around in a circle until you get back to the tree you started on. You have to pay close attention to the starting tree so that you don’t count it twice and so that you know when you’re done.

With a 10-factor prism, as shown here, you multiply the number of trees that tally by 10 to arrive at an estimate of the square feet basal area per acre of trees at your site. Since this is just a rough estimate of basal area and will differ depending upon where you stand in a forest, it is common to randomly select a number of sites, say 10-20 different locations, and to do a prism tally at each site in a habitat. Average the estimates at all sites to arrive at an overall BA estimate for the forest area.

You can also do a prism tally at each plot center when measuring macroplots in order to compare prism BA estimates with actualy measured basal area of trees.

Next we would like to get an idea of how much the forest canopy of leaves blocks light from reaching the forest floor. This will have a strong influence on what species of vegetation, and how much, will be able to grow at ground level. This ground-level, and shrub-level vegetation, will determine the suitability of this forest area for many wildlife species.

There are many methods to measure and estimate canopy coverage. We will show a simple and effective method using a tool called a Spherical Densiometer. This produce is available commercially for about $110 from various forestry equipment suppliers. The unit shown here was made from a $2 wide angle mirror from a hardware store. It corresponds to the convex commercial densiometer.

The densiometer is gridded into 24 equal squares. It is held out in front of the body about waist level so that a clear view is given of the forest canopy without the observer shading the grid. Also the observer must move away from any nearby tree so that a tree trunk does not impede the view of the forest canopy.

For each square an estimate is made of the amount of leavy vegetation shading the clear sky. You can also estimate the number of squares taken up by open sky and then subtract that total open sky from 100% to arrive at closed canopy cover if the canopy is very dense. It is recommended to count coverage or open sky, depending on which parameter is easiest to estimate. In a sparse forest with mostly open sky on the grid, count covered squares.

After taking the first estimate in one cardinal direction, you turn 90° and take another reading. You continue until you have taken 4 canopy coverage readings in each of the cardinal directions from a given location, say your macroplot center point.

Since there are 24 squares on the grid, once you have taken 4 readings you will have counted coverage in 96 squares. You then multiply that total by 1.04 to achieve an estimate based on 100% coverage, 96/100.

In the above example, though the grid squares are a bit hard to distinguish in this photo, you might estimate that about 5 squares total were represented by open sky. Say you had open sky estimates at the other 3 directions of 4, 7, and 8. The total number of squares of open sky at this location would then be 5 + 4 + 7 + 8 = 24 out of 96 total squares surveyed. Multiplying this by 1.04 = 25 % open sky, or 75 % canopy coverage at this location.

MIDSTORY AND UNDERSTORY VEGETATION MEASUREMENTS

Now that we have described the overstory trees and their canopy coverage influence on the macroplot, we are ready to account for the midstory and understory vegetation. In order to make our job easier we will simply do stem counts of trees greater than 1 inch (2.5 cm) and under 4 inches (10 cm) DBH. Depending upon the composition of your forest or the goals of the research, you may separate these trees on your data sheet by species or just group them by pines and hardwoods. It is convenient to have one person at plot center taking down count data as another person actually walks around inside the plot counting trees. It is easy for the person doing the counting to get mixed up and to lose his place, with the result that he can either miss some trees or count others twice. The person taking down the data can keep an eye out to where the counter has been and direct him to areas that haven’t been tallied yet.

A convenient method for recording small diameter tree counts is what is called the Dot Tally. This method is quick, easy to read, and takes up a minimum of space on the data sheet. To record counts by a dot tally you create a square using the first 4 counts as dots on the outer corners. The next 4 counts are lines connecting the sides of the square. The final 2 counts to total 10 are crosses between the diagonal corners of the square.

· · = 4 · · = 6 = 8 = 10

· · · ·

Tree stem counts in the 1 to 4 inch diameter class will give you a good idea about the composition of the midstory and about regeneration, or the amount of young trees that are present and will grow to form the forest of the future at this site.

Next we want to describe vegetation density in the lower strata of the forest, from the ground level up to lower midstory height. This is done effectively by viewing a brightly colored board horizontally at several heights and estimating the percent of the board that is covered by leafy vegetation. The density of understory and midstory vegetation gives an indication of light reaching the ground level, as well as the abundance of important shrub-level and forest floor vegetation, which is often an important source and food and refuge for wildlife.

This density board has been constructed 0.5 meter on a side to give an area of 0.25 square meters. It is attached to a 1-meter stick. It can be used easily to view vegetation at 4 strata: ground level, 1 meter high, 2 meters high, and 3 meters high. The board as shown, resting on the ground is viewed by the observer sighting through a mirror mounted on a stick at a 45° angle and held where the mirror will sight horizontally across to the center of the board at 0.25 m height. This is the ground level estimate of vegetative density.

The observer stands at plot center and the person holding the board stands at a consistent distance of 10 or 15 meters away at the 4 cardinal directions. For ease in properly positioning the person holding the board, a 10-factor prism and tape measure can be used to mark a dark vertical line on the back of the board, positioned so that at the proper distance that mark lines up exactly with the edge of the density board. The person at plot center can thus sight the proper azimuth in his compass and give the person with the density board the proper distance in a rapid manner.

In this example shown above, the first row of squares (25 % of the board) is obscured by grass and forbs. The second row is about ½ obscured (12.5 %, and there is some slight coverage noted on the third row of squares. This reading represents about 40 % coverage at the 0.25 m stratum. Next a reading is made at 1 meter by the observer crouching on one knee and viewing the board held with the center at 1 meter height.

The third reading is made at 2 meters, with the board held with the center at 2 meters, just above head height and the observer standing up straight.

The fourth reading is made at 3 meters height, with the board held at arm’s length on the stick and the observer holding the mirror at arm’s length and sighting across to the board. These measurements are repeated at each cardinal direction from plot center and the 4 estimates at each stratum averaged to give a mean reading of vegetation density on the macroplot for each horizontal stratum.

Comparing density board estamates for shrub level and understory vegetation between different habitat types will provide a good indication of differences in the amount of vegetation growing there. For example, the coverages viewed at a distance of 10 meters at heights of 2 and 3 meters at a sample of 5 macroplots in the open forest above showed mean coverages of 3.6 % and 5.8 %, respectively. Coverage estimates from 5 macroplots in the forest shown below at the 2 and 3 meter strata showed means of 13.5 % and 29.4 %, respectively.

With a bit of experience one can come to associate density board coverage estimates with a mental picture of the amount of understory and shrub-level vegetation at a study site. The board and mirror are easily and cheaply constructed from hardware-store components.

This method will work equally well at grassland sites.

The last measurements taken at the macroplot consist of estimates of percentage cover of the various ground cover materials on the plot. These parameters are important in describing the organic components that will decompose to become incorporated into the soil. They also give an indication of water retention ability of the ground layer and wildlife habitat and nutrient stores available in down wood and litter.

In the data sheet provided here we have included categories of percent shrub coverage below 2 meters in height (to account for the presence of shrubs and seedling trees that were not counted in the 1-4 inch diameter class stem tally). We also estimated the ground coverage of grass and herbaceous plants, pine needles, down wood, rock, and bare ground. If you are at a site that has other important components in the ground cover, you would want to include those.