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Plot Designs for Ecological Monitoring of
Forest and Range 1
Hans T. Schreuder2
Paul H. Geissler3
Abstract-Given the need of governments today for extensive data
on natural resources for use in national planning, the U.S. Forest
Service has changed its policy from periodic inventory of the
timber resources of the U.S.A. to annual inventories of its much
broader ecological resources. Consequently, the design of the
sample units used in assessment must be reconsidered. We propose
a change, to be implemented gradually over time, from the standard
circular primary unit to a long rectangular one. The advantages
are: more useful data can be provided for both management and
monitoring purposes; special interest surveys can be accommodated
better; assessment is cost efficient because remote sensing can be
used more extensively and, consequently, access to private land and
effect of trampling are minimized. Because of the large number of
variables to be measured for large-scale and management purposes,
the fact that several are best measured on photos, and the fact that
several variables require more than one visit in a season, the need
for averaging one plot per day and additivity of estimates should be
revisited.
It is well known that different sampling units (plots) are
optimal for different sets of variables. For example, variable
radius plot (VRP) designs have been used for a long time in
Forest Inventory and Analysis (FIA) of the U.S. Forest
Service (USFS) because timber volume was the primary
interest. For that objective, probabilistically selecting more
large trees relative to small trees was clearly more efficient.
Similarly, if interest is in the number of trees with equal
interest in each tree, fixed-area plot designs are optimal,
because each tree has an equal probability of selection.
In large-scale surveys such as FIA where a large number
of variables are measured, a compromise is needed. Although different designs are optimal for different variables,
it is more efficient to assess them all on the same plots,
rather than conduct separate surveys, because it allows the
association between combinations of variables to be assessed. Circular plots are favored internationally because
for a given area, the length of the boundary is minimal
relative to plot area and because variable radius plot (VRP)
sampling requires a sweep around the center point for
efficient sampling.
Ipaper presented at the North American Science Symposium: Toward a
Unified Framework for Inventorying and Monitoring Forest Ecosystem
Resources, Guadalajara, Mexico, November 1-6,1998.
2Hans T. Schreuder is a Mathematical Statistician for the USDA Forest
Service, Rocky Mountain Research Station, Fort Collins, CO 80526, U.S.A.
Phone: (970) 498-1294; Fax: (970) 498-1010; e-mail: hschreuderl
nnrs@fs.fed.us
3Paul H. Geissler
180
The increased extensive need for information for management and planning and the dramatic improvements
in remote sensing and geographic positioning systems suggest that a change in plot design may be desirable. In the
U.S.A. there is increased interest in measuring a broad
range of ecological and health variables, in assessing the
association between them, and in modeling forest and range
processes. Accomplishing this is more feasible now with the
highly accurate lasers and geographic positioning systems
(GPS units) which have become available for land surveys.
Combining this new instrumentation with improved plot
design and remote sensing, especially low al ti tude photography and videography, allows for quicker, more reliable
measurement and better yet cheaper information. At the
same time, ground access and trampling of the sample plot
are minimized.
There is a need for closer coordination between mapping
and sampling, including the ability to provide map-type
da ta using techniques such as small-area estimation (Moeur
and Stage (1995). It is also critical to maintain continuity
with current inventory and monitoring efforts and to preserve comparisons with previous surveys. There also are
needs for specialized surveys, coordinated with other major
surveys, and a need to use data from these surveys for local
forest management. Clearly, a compromise among the designs that are optimal for assessing the different variables
and objectives is clearly needed.
Review of Literature
According to the SPAM (1997) report, Ernest Haeckel
coined the term "ecology" in 1866 to define the study of the
multifaceted struggle for existence as presented in "The
Origin of Species" by Charles Darwin according to Kingsland
(1991). Allaby (1994) defined ecology as the study of the
interrelationships among organisms, and between them and
all living and non-living aspects of the environment. It is
clear then that effective monitoring for ecological purposes
requires measurement of attributes associated with these
interrelationships at the same or essentially the same locations. As this has rarely been done in the past, it is pertinent
to begin by describing plot-sampling methods used in various disciplines.
Schreuder (1978) showed that a combination of sampling
methods applied at a given point in a forest provides highly
efficient and unbiased estimates of number of trees (N),
using a fixed area plot centered at the point and oftotal basal
area (G) using VRP sampling. The sum of tree diameters can
also be estimated without bias but inefficiently using a VRP
sample on the fixed area plot with the above estimates ofN
and G. This approach was based on one suggested by Fender
USDA Forest Service Proceedings RMRS-P-12. 1999
and Brock (1963) who proposed estimating future G by
counting trees after displacing an angle gauge by an amount
that depended on an estimate of expected increment.
Burnham et al. (1980) noted that quadrats are often used
to sample ant colonies, termite colonies, animals living in
the soil, some species of insects, birds and small animals; but
Seber (1986) considers transects to be easier to locate and
more effective than quadrats, which tend to be affected more
by animals moving at the boundary. However, he acknowledges that in dense shrub and rough terrain transects
make it difficult for the observer to observe birds at the
same time as walking quietly.
Burnham et al. (1980) contend that strip transects are
often not appropriate for sampling mobile animals such as
birds but line transects or variable-width transects may be.
Strip transects are used extensively in counting animal
pellets. They are also used in preference to quadrats when
sampling from the air because of ease of location and more
reliable covariate values are available for use in computing
adjustments with ground sampling values in ratio and
regression estimation (Seber 1982, 1986, 1992).
Schreuder and McClure (1991) suggested modifying FIA
sampling procedure to improve detection of change in a
forest and identify possible causes. If additional sample
plots were established and paired with all or a subset of the
existing plots, then potential cause-effect relationships could
be identified with the latter and hypotheses formulated
while the former could be used to test these hypotheses.
To generate descriptive statistics, detect change in these
statistics over time and analyze data to identify potential
cause-effect relationships, Schreuder and Czaplewski (1993)
proposed a multi-level sampling frame consisting of wall-towall digital satellite map generated every 1-4 years to
monitor such variables as forest fragmentation and habitat
corridors, strips or large cluster of plots on aerial photography and/or videography to monitor disturbance and change
in the aerial extent of variables such as forest cover and land
use, clusters of ten 0.1 ha plots measured on the aerial
photography or videography every 1-4 years for some variables such as tree mortality and field measurements on the
ground every 4-16 years for variables such as ecological
health and wood volume.
Olsen and Schreuder (1997) state that data from FIA and
NRI (the Natural Resources Inventory conducted by the
Natural Resources Conservation Service of the USDA) can
be used to identify potential cause-effect relationships, useful cause-effect hypotheses to be tested, and supplementary
data sets to be collected to more clearly establish potential
relationships. Additional key information such as soil quality should be collected to improve the chances of identifying
possible cause-effect hypotheses. Clearly these objectives
call for various sampling efforts to obtain the desired information. Goebel et al. (1998) showed that multidisciplinary
information can and should be collected with a common plot
design even though it was realized that the FIA plot design
used (in combination with transects) was not necessarily the
best plot.
Schreuder et al. (1997) discuss the possibility of combining mapped and statistical information in a more comprehensive package supplementing the USFS Region 6 vegetation inventory and monitoring system (Max et al. 1996). It
is clear that additional information must be collected in
USDA Forest Service Proceedings RMRS-P-12. 1999
follow-up surveys by keying in on relevant information
obtained in that system. Near-continuous information is
needed on weather and possibly pollution variables to develop meaningful models to understand relationships and
processes in the ecoregions and to assess the impact of
management practices on them. However, instrumentation
capable of providing this is not yet readily available.
Both FIA and NRI are going to annualized inventories,
where a subset of existing plots will be measured in each
state each year, probably 20% in the case ofFIA. Both will
be collecting much more ecologically based information
than in the past. Although we focus on plot design for
forestry purposes, i.e. National Forest Systems (NFS) or FIA
needs, this proposal should be useful for NRI purposes too
since FIA and NRI should be integrated and ultimately
merged into one national resource inventory.
Methods
Although it is clear that the 1-ha circular FIA plot
subsampled by 4 1/60 ha circular subplots has wide acceptance now, it is also true that this configuration has its
origin in timber sampling. It is therefore likely that other
plots shapes and sizes will replace it at some time, because
of changes in objectives and technology. However,
transitioning from the existing plot to a new one over time is
important so we do not lose the ability to estimate change
in critical parameters (mortality, growth, etc.). Hence we
use as our starting point the FIA plot. The suite of variables
to be measured by natural resource agencies has not yet
been defined for range and forest health and soil quality
variables. Consequently, we will focus on a set of variables
fitting the 5 categories described earlier, treat those as the
sole complete set of attributes to be measured, and indicate
how we expect these variables to be measured. The fact that
more than one visit in a season is required for animal
populations offers opportunities for additional measurements of forest health variables such as change in the
chemical content of foliage.
Proposed parameters of interest (measurable and useful):
1. Forestry
a. Trees: Number of trees, tree basal area, length, diameter, and frequency of down woody material, tree
mortality and regeneration, number of diseased and
insect-infested trees, removals by species.
b. Understory: number, mortality, height, % seedlings,
% saplings, % mature shrubs by species.
c. Forbes, grasses: number of species, aerial extent.
2. Soil
a. Depth of organic matter, depth ofA horizon, soil series,
soil quality (SQ), pH
b. Other characteristics: erosion rate, slope and aspect.
3. Animals, relative abundance of
a. Birds
b. Small ground vertebrates (mammals, reptiles, and
amphibians)
c. Ground insects
4. Water
quality, depth, and extent.
Given the numerous attributes to be measured, cost constraints, and the fact that some variables can be obtained
181
accurately from photos and others not, and different plot
configurations are efficient for different variables, it is likely
that some ensconced ideas in FIA should be dropped. Specifically, the idea of additive estimates (acreage at time 2 does
not have to add to acreage at time 1 + change in acreage over
the time period) and I-day plots on average may have to
change. With the tremendous improvement in both remote
sensing and geograp=:': positioning systems, it is highly
probable that, in future, areas will be estimated much more
reliably than they are now. Similarly, when assessing biodiversity and other ecological conditions, it is clear that much
more time will have to be spent on each primary sampling
unit (psu) to collect all the needed information.
Proposed Approach
Either the current FIA plot with the annular circular
subplots or the current Region 6 Current Vegetation System
(CVS) plot (Max et a1. 1996) can provide useful information
for both large-scale and management objectives. Both are
currently used and transitioning to the new plot needs to
allow for both.
As indicated earlier, aerial photography should play
more ofa role in inventorying and monitoring. Besides being
used for direct measurement of some of the variables directly, it can also be used for testing purposes to determine
how remote sensing can be used for more difficult to
measure variables.
The proposed plot design is shown in Fig. 1 with further
elaboration in Fig. 2. Briefly, we plan transitioning from the
A.FIA Plot
B.CVS Plot
C. Proposed 1 ha Plot (40 x 250 m)
d!!!1 "'1" ""i~~;~r~· (~m~;12tY8~'s=~~; " ~bo
D. Proposed Plot Superimponsed On FIA And CVS Plots
Figure 1.-FIA.
182
CVS and Proposed Plot Designs.
B.CVS
A. FIA
c.
Drift Fence D. Stohlgren Biodiversity
o
Meters
50
Figure 2.-Subplot Designs.
current circular plot to a plot for which the information can
be better tied to remote sensing information. It is useful to
think ofthe psu as a population in its own right for management purposes. For example plots are often classified into
condition classes of interest such as biodiversity classes,
timber productivity classes, erosion-control classes, etc. to
assess where treatment needs to be applied when. A lowaltitude or video picture of each plot is taken annually to
serve as a permanent record over time.
The current FIA and CVS plots are compact. Although
they can be established in the field faster than long rectangular plots, they are less efficient for estimation. Because
of spatial correlations, adjacent compact subplots tend to be
similar. Measuring them duplicates much of the work already done and yields relatively little new information.
Long subplots also spread out the observation area reducing
the effect of spatial correlation. To increase the precision of
the estimates for large areas, one seeks to make the plot
estimates as similar as possible. To do this, one includes as
much as the variability as possible within the plot, thus
increasing efficiency. However, long plots have a large
perimeter which increases the number of decisions required
on 'boundary' trees- are they 'in' or 'out'? Long plots are
advantageous for remote sensing, especially low-level aerial
photography and videography. Numerous variables, e.g.
mortality of trees, can be measured with high degree of
reliability on remote sensing imagery. However, sampling
subplots on the ground is desirable at this time to verify the
remote sensed measurements and adjust them by regression estimation if necessary.
There is an increased emphasis on biodiversity such as
iden ti ty of species present and species richness . Particularly
in regards to maintaining rare native species and detecting
exotic species while they still can be eradicated if necessary.
Rare species are a major component of biodiversity but
traditional forest inventories have ignored them. For example, Stohlgren et a1. (1998) reported that almost half of
the prairie plant species had less than one percent foliar
cover. To observe rare species, it is important to search as
large and diverse an area as possible. Maximizing the
heterogeneity within a plot is also desirable for this reason.
USDA Forest Service Proceedings RMRS-P-12. 1999
In transitioning, the three CVS or FIA subplots contained within the 40 x 250-m primary sampling units serve
a useful role in change estimation as the plot design changes.
If estimates of change based on them and measurement of
all or part of the new psu are insufficiently reliable for the
FIA standards set, the other subplots in the original CVS or
FIA plots would have to be remeasured too.
Mter transi tioning to the proposed psu, we then have a set
of 40 x 250 m rectangular plots for which low-altitude
photography or videography coverage should be acquired
annually as a permanent record over time. On the ground,
the 250 m long center axis of these plots are permanently
established and marked in an unobtrusive way and serve as
starting points to subsample the psu in various ways for
various attributes. The 10 x 40 m center area is used only for
benchmarking purposes and to protect against excessive
trampling as now often occurs since the center is the focal
point of all current sampling efforts in both FIA and CVS.
For large-scale government planning estimation and analyses purposes, all 6 subplots are subsampled at a low intensity. Research is needed on how best to do this. The primary
interests being how to meet national and regional objectives
set for precision of the estimates and how to attain sufficient precision at the plot level to enable reliable equations
to be established in conjunction with remote sensing information for predicting the parameters associated with
covariates that can be measured on the photography. Because of the large number of variables to be collected,
different sets of variables may have to be measured on
different subplots to avoid excessive trampling and disturbance on the subplots. Although some variables can be
measured more accurately and completely on aerial photography, these should also be sampled on the ground to
document their accuracy or precision.
All 6 subplots are subsampled at a high intensity on
federal lands. Research is also needed here, the primary
interests being to establish meaningful interactions between the variables of interest and to determine the need
Figure 2 includes a proposed biodiversity plot of Stohlgren
et al. (1995, 1998) for comparison with the FIA and CVS
plots. Important features of Stohlgren's approach include a
relatively long rectangular plot with subplots, observations
with four different sized subplots to observe biodiversity at
different scales. Percent cover and vegetation height is only
measured on the smallest subplots, but the presence of
species is recorded for all subplots.
We recommend the long rectangular 1-ha plot (250 m x
40 m) for future inventory (Fig. 1c). This is an easy plot to
photograph from the air, encompasses 3 out of the respectively 4 or 5 subplots of the FIA and CVS plots and with
proper laser instrumentation should be easy to establish on
the ground. It is divided into 640 x 40 m subplots which can
be measured or subsampled for various variables as indicated in Fig. 2. A center 10 x 40 m subplot is primarily used
for plot establishment purposes. Down the middle of the long
plot we also have a 250 m long transect which is divided into
6 40-m segments that can be measured or subsets of which
can be measured for the variables indicated in Fig. 2. The
transects should be a vital part of the plot design, which they
are not with the current FIA plot.
As a first step in increasing the efficiency of the plots, we
consider maintaining the same subplot design, and arranging the subplots in 40 x 250 m plots. This design accommodates the current plot designs best for change detection
while spacing out the subplots to be used after transitioning
to increase efficiency. This approach presumes that boundary issues are more important for measurements made on
the smaller subplots and that matching ground and air
measurement are more important for the plot and larger
subplots. Longer and narrower plots (25 x 400 m or 20 x
500 m) may be even more desirable in the future but do not
allow for transitioning as well as 40 x 250 m plots since fewer
of the CVS or FIA subplots can be accommodated.
Table 1 summarizes some of the attributes of the current FIA and CVS plot designs, the plot design we propose
and longer narrower plots for the sake of interest).
Table 1.-Some geometric characteristics of plot designs discussed.
Plot/Subplot
Plot
Area
Radius/Dimensions
Perimeter
Large Subplot
Area
Radius/Dimensions
Perimeter
Medium Subplot
Area
Radius/Dimensions
Perimeter
Small Subplot
Area
Radius/Dimensions
Perimeter
Micro Subplot
Area
Radius/Dimensions
Perimeter
FIA
cvs
1.000 ha
56.42 m
354m
1.000 ha
56.42 m
354 m
0.101 ha
17.95 m
113 m
25 x 400 m
20 x 500 m
1.000 ha
40 x 250 m
580 m
1.000 ha
25 x 400 m
850m
1.000 ha
20 x 500 m
1040 m
0.076 ha
15.58 m
98m
0.100 ha
25 x 40 m
130 m
0.100 ha
20 x 50 m
130 m
0.100 ha
25 x 40 m
140 m
0.100 ha
20 x 50 m
140 m
0.017 ha
7.32m
46 m
0.020 ha
8.02m
50m
0.020 ha
10 x 20 m
60 m
0.020 ha
10 x 20 m
60m
0.020 ha
10 x 20 m
60m
0.010 ha
5x20 m
50 m
0.001 ha
2.07m
13 m
0.004 ha
3.60m
23m
0.020 ha
10 x 20 m
60m
0.020 ha
2x5 m
60m
0.001 ha
10 x 20 m
20 m
0.001 ha
2x5m
20 m
USDA Forest Service Proceedings RMRS-P-12. 1999
40 x 250 m
Stohlgren
0.0001 ha
0.5 x2 m
5m
183
for and assess the effect of management practices on the
resource.
For cause-effect purposes, a subset of the psu's is measured either completely or sampled at a high intensity.
Special monitoring devices could be established on these
psu's such as automatic weather and pollution monitoring
stations, non-destructive chemical analysis machinery, etc.
Special surveys can be accommodated in this scheme too.
A representative subset of the psu's would be selected for
the "client." The variables of interest can then be remeasured
at the government planning or management intensity level,
or on a representative subset of the subplots.
Before we make more specific recommendations, the following gives a general overview of our thinking relative to
advantages of different subplot sizes and shapes (Schreuder
et al. 1993: 293-296).
• Long rectangular plots are advantageous for low altitude photography measurements and plant biodiversity
estimates.
• A rectangular plot is easier to fly and interpret and a
1 ha plot is a convenient size to fly and photointerpret.
• To assess plant biodiversity (species richness and identification of species), ideally we want to cover as many
habitat conditions as possible and as large an area as
possible to find rarer species. Boundary issues are relatively less important because one only has to check to
see if the occasional species not found in the subplots is
in or out of the plot. This suggests that a long narrow plot
or transect is desirable.
• Circular subplots are advantageous for VRP sampling
where boundary issues are important as in regeneration
subplots.
• Transects are advantageous for traversing a large area
to measure scatter or rare objects such as down woody
debris.
Animals are more difficult to observe than plants. Birds
are frequently counted because they are active during the
day and are easily observed. However, birds cover large
areas and their populations may reflect conditions outside
the plot. Many birds migrate, and so their populations will
also reflect conditions on the wintering areas. Counts of
birds are also influenced by the time of day and the weather.
Dawn and dusk are the best times to count birds, but
observers often are unable to do this because of the danger
in accessing the sample sites at these times. If bird counts
are used, the point count method (Ralph et al. 1995) is
recommended. Recording the distance to observed birds
allows an adjustment for visibility differences (Buckland
et al. 1993). As the points should be at1east 250 m apart to
avoid counting the same birds, counts should be made at
the ends of the 40 x 250 m plot. Additional points can be
located 250 m out in each direction so the 4 points form a line,
separating the points as much as possible. One solution is to
install automatic recorders for a few weeks to record bird
calls and those of some amphibians, insects and possibly
bats (Peterson and Dorcas 1994). Highly skilled people are
required to identify bird calls. Recording their calls allows
birds to be identified without requiring an expert to visit the
plot. We recommend that one recorder be located at the
center point. It should be installed after the vegetation
measurements are made and left in place for about 3 weeks.
184
Small mammals, reptiles, and amphibians have smaller
home ranges and do not migrate. Thus their populations
more closely reflect conditions on the plot, although they
are more difficult to observe. However, drift fences can be
used to direct animals moving· through an area to a spot
where they can be observed (Corn 1994). Pitfall traps are
commonly used, but it is impractical to check them daily. An
automated camera can be left in place for a few weeks to
record animals. We suggest two drift fences in the end 40 x
40 m subplots where drift fences are typically 5 m to 15 m
long, 50 cm wide and buried 20 cm in the soil. Because of the
cost o(the camera, a single drift fence in a central subplot
may be used. We suggest a drift fence with three 15-m
spokes, with a back turn at each end to turn animals back
towards the center, and an automated camera in the middle
(Fig. 2c). They should be installed after the vegetation
measurements are made and left in place for about 3 weeks.
Pitfall traps can also be used to observe ground insects.
The traps are 600 ml (one pint) plastic containers buried
flush with the ground with ethylene glycol in the bottom to
preserve insects falling in. They also can be left on the plot
for a few weeks. The insect populations reflect conditions on
the plot. A great variety of species at different trophic levels
can be captured easily and well-established protocols exist
for doing this. Specimens are taken back to the laboratory for
identification. Although species identification is difficult, it
is feasible if only selected taxa are identified. We recommend
4 pitfall traps in each of the 40 x 40 m subplots. Again, they
should be installed after the vegetation measurements are
completed and left in place for about 3 weeks.
To indicate the implementation opportunities we give
examples below of how to collect the necessary information
for the variables enumerated on above. The actual subsampling schemes to be used should be investigated to
determine what the optimum might be relative to efficiency,
accuracy of estimation, correlations with the aerial photo
plot information, etc.:
We have six 40 x 40 m subplots subsampled as follows for
the attributes:
1. For government planning information:
a. Use circular subplots- say a 0.017 ha subplot (1/24
acre) in each of the subplots for number of trees, basal
area, number of insect and disease infected trees,
removals, and mortality.
b. Use two 40-m transects in each of the subplots for
length, diameter, and frequency of down woody material and for number of species of forbes and grasses.
These might, for example, be located at the 10- and
30-m points along the center axis in each of the
subplots. These can also be used for measuring erosion
rates and slopes.
2. For management purposes- use one or two of the corresponding CVS or annular FIA subplots for each of the
6 subplots. Similarly use 4 or more transects in each of
the 6 subplots for the down woody material. These
transects can also be used to measure erosion rates
and slopes.
3. For tree regeneration, understory vegetation, counts of
forbes and shrubs, depth of the organic matter layer
and A horizon and pH we recommend use of a larger
number, smaller subplots in each of the 40 x 40 m
USDA Forest Service Proceedings RMRS-P-12. 1999
subplots. For example we might sample five 0.001 ha
subplots (2.07 m radius) per 40 x 40 m subplot for
government planning purposes and ten for management purposes.
4. Obtain soil quality and soil series measurements from a
series of respectively 5 and 10 cores for government
planning and management purposes in each of the
six 40 x 40 m subplots. How to best do that in a nonor essentially non-destructive manner will soon be
decided upon.
5. Animal relative abundance is measured by traps and
recorders left on the plot for 3 weeks:
a. Small mammals, reptiles, and amphibians are sampled
by a 3-spoked 15 m drift fence with an automatic
camera in one of the central 40 x 40 m subplots.
b. Ground insects are sampled by 4 pitfall traps in each
of the 40 x 40 m subplots.
c. Calling birds, bats and insects are sampled by an
automatic audio recorder located at the central point.
Traditionally, only a single visit is made to a psu. However, it is very difficult to obtain repeatable animal observations with one visit, because counts are influenced by
weather, time of day, and other factors. Leaving recording
equipment in the field for a few weeks would sample animals
at all times, day and night, and under varying weather
conditions, making the observations much more repeatable.
An important advantage of automatic recorders is that
nocturnal and shy animals can be observed. Similarly,
additional useful ;"'formation such as change in chemical
content of foliage could be measured if more than one visit
per season was acceptable in either FIA or similar natural
resources surveys.
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