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
10factor 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 1020 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
groundlevel, and shrublevel 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 shrublevel 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
1meter 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 10factor 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 shrublevel vegetation at
a study site. The board and mirror are
easily and cheaply constructed from hardwarestore 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 14 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.