METHODS—Daubenmire

b Ten Cover Classes Where narrower and more numerous classes are preferred,
a ten-cover class system can be used.

c Collecting Cover Data As the quadrat frame is placed along the tape at the
specified intervals, estimate the canopy coverage of each plant species. Record
the data by quadrat, by species, and by cover class on the Daubenmire form (see
Illustration 9). Canopy coverage estimates can be made for both perennial and
annual plant species.

(1) Observe the quadrat frame from directly above and estimate the cover
class for all individuals of a plant species in the quadrat as a unit. All other
kinds of plants are ignored as each plant species is considered separately.

(2) Imagine a line drawn about the leaf tips of the undisturbed canopies (ignor-
ing inflorescence) and project these polygonal images onto the ground. This
projection is considered “canopy coverage.” Decide which of the classes the
canopy coverage of the species falls into and record on the form.

(3) Canopies extending over the quadrat are estimated even if the plants are
not rooted in the quadrat.

(4) Collect the data at a time of maximum growth of the key species.

(5) For tiny annuals, it is helpful to estimate the number of individuals that
would be required to fill 5% of the frame (the 71- x 71-mm area). A quick
estimate of the numbers of individuals in each frame will then provide an
estimate as to whether the aggregate coverage falls in Class 1 or 2, etc.

(6) Overlapping canopy cover is included in the cover estimates by species;
therefore, total cover may exceed 100 percent. Total cover may not reflect
actual ground cover.

9. Calculations Make the calculations and record the results in the appropriate
columns on the Daubenmire form (see Illustrations 9 and 10).

a Canopy Cover Calculate the percent canopy cover by species as follows:
(1) On the Daubenmire form (Illustration 9) count the number of quadrats in
each of the six cover class (by species) and record in the Number column

on the Daubenmire Summary form (Illustration 10).

(2) Multiply this value times the midpoint of the appropriate cover class
(Illustration 10).

(3) Total the products for all cover classes by species.
(4) Divide the sum by the total number of quadrats sampled on the transect.

(5) Record the percent cover by species on the form.



Comparative Yield

Page ——of —__

Study Number

Date

Examiner

Pasture

Allotment Name & Number

Number of Quadrats

Quadrat Size

Study Location

Sampled Quadrats

Harvested Quadrat

Rank (1)

Tally (2)

Rank x Tally (3)

Clip Rank (4)

Clip Weight (5)

(0)

5

1

1.5

2.5

3.5

45

Total

Average

Notes

lilustration 24



IV. ATTRIBUTES

The following is a matrix of monitoring techniques and vegetation attributes that are de-
scribed in this reference. The X indicates that this is the primary attribute that the tech-
nique collects. Some techniques have the capability of collecting other attributes; the «
indicates the secondary attribute that can be collected or calculated.

Method Frequency Cover Density Production | Structure | Composition

Frequency x .

Dry-weight-
Rank . ° xo

Daubenmire .

Line Intercept

Step Point

|X| xX |X
°

Point Intercept

Density Xx °

Double Weight
Sampling x .

Harvest x .

Comparative
Yield xX .

Cover Board xX xX
Robel Pole . x

A. Frequency

1. Description Frequency is one of the easiest and fastest methods available for
monitoring vegetation. It describes the abundance and distribution of species and
is useful to detect changes in a plant community over time.

Frequency has been used to determine rangeland condition but only limited work
has been done in most communities. This makes the interpretation difficult. The
literature has discussed the relationship between density and frequency but this

relationship is only consistent with randomly distributed plants (Greig-Smith 1983).

3 Species composition is calculated using production data, Frequency data should not be used to calculate
species composition





. 1981. Arid land resource inventories: developing cost-efficient methods. U.S.
Dept. of Agr., For. Ser., Gen. Tech. Rep. WO-28. 620 p.

. 1962. Range Research Methods - a Symposium. USDA Forest Service, Misc Publ.
940, Denver, CO.

——. 1994. Rangeland Analysis and Management Training Guide, Rocky Mountain
Region USDA Forest Service Denver, CO.

USDA, Soil Conservation Service. 1976. National Range Handbook. 154 p.

US. Department of Interior, Bureau of Land Management, Vegetation Attributes Reference
Card. BLM Phoenix Training Center.

——.. 1982. Big Game Studies, BLM Manual 6630.

—.. 1983. Inventory and Monitoring Coordination, BLM Manual 1734.

——. 1984 (rev. 1990). National Range Handbook 4410-1. Washington, D.C.

——.. 1984. Rangeland Monitoring: Planning for Monitoring, TR4400-1.

—. 1985. Rangeland Monitoring - Trend Studies, TR4400-4.

—.. 1987. Riparian Inventory and Monitoring, Montana BLM Riparian Tech. Bull. No.1.
—. 1993. Rangeland Monitoring - Supplemental Studies, TR4400-5.

USDI, Fish & Wildlife Service. 1981. Estimating wildlife habitat variables. FWS/OBS -
81/47. 111 p.

Van Dyne, George M. 1960. A procedure for rapid collection, processing, and analysis of
line intercept data. J. Range Manage. 13:247-251.

Van Dyne, George M., W.G. Vogel, and H.G. Fisser. 1963. Influence of small plot size and
shape on range herbage production estimates. Ecology 44:746-759.

Waller, S.S., JK. Lewis, M.A. Brown, T.W. Heintz, R.I. Butterfield, and ER. Gartner. 1978.
Use of 35mm aerial photography in vegetation sampling. In: Proceedings, First
International Rangeland Congress. Hyder, D.N. (ed), Soc. for Range Manage., Denver,
CO. pp. 517-520.

Wells, K.F. 1971. Measuring vegetation changes on fixed quadrats by vertical ground
stereophotography. J. Range Manage. 24:233-236.

West, N.E. 1985. Shortcomings of plant frequency-based methods for range condition and
trend. William C. Krueger, Chairman. Proc., 38th Annual Meeting Soc. for Range
Manage. Feb. 1985. Salt Lake City. Soc. for Range Manage. 87-90.

147



Sampling Vegetation Attributes

Interagency Technical Reference
Cooperative Extension Service

U.S. Department of Agriculture
— Forest Service —

Natural Resource Conservation Service,
Grazing Land Technology Institute

US. Department of the Interior

— Bureau of Land Management —

1996

Supersedes BLM Technical Reference 4400-4, Trend Studies, dated May 1985

Edited, designed, and produced by the Bureau of Land Management's
National Applied Resource Sciences Center

BLM/RS/ST-96/002+1730


METHODS—Comparative Yield

a Site Selection The most important factor in obtaining usable data is selecting
representative areas (critical or key areas) in which to run the study (see Section
ILD). Study sites should be located within a single plant community within a
single ecological site. Transects and sampling points need to be randomly
located within the critical or key areas (see Section III).

b Pilot Studies Collect data on several pilot studies to determine the number of
samples (transects or observation points) and the number and size of quadrats
needed to collect a statistically valid sample (see Section III.B.8).

c Selecting Quadrat Size The criteria for selecting the proper size quadrat is
the same as any weight estimate procedure (see Section IJI.B.6.d).

(1) Determine the proper size quadrat(s) to use by doing preliminary sampling
with different size frames.

(2) Use the same size quadrat throughout a study and for rereading the study.

d Number of Transects Establish one transect on each study site; establish more
if needed.

e Study Layout Production data can be collected using the baseline, macroplot,
or linear study designs described in Section III.A.2 beginning on page 8. The
linear technique is the one most often used.

f Reference Post or Point Permanently mark the location of each study with a
reference post and a study location stake (see beginning of Section III).

g Study Identification Number studies for proper identification to ensure that
the data collected can be positively associated with specific sites on the ground
(see Appendix B).

h Study Documentation Document pertinent information concerning the study
on the Study Location and Documentation Data form (see beginning of Section
Ill and Appendix A).

. Taking Photographs The directions for establishing photo plots and for taking
close-up and general view photographs are given in Section V.A.

. Sampling Process In addition to collecting the specific study data, general
observations should be made of the study sites (see Section II.F).

a A set of reference quadrats must be established. The sample quadrats will be
compared and rated back to these reference quadrats. The reference quadrats
represent the range in dry weight of standing crop that will be commonly found
during sampling.

117



METHODS—Li ercept - —

10.

11.

plants, along with rosette-forming plants, at ground level. For forbs, shrubs, and
trees, measure the vertical projection of the foliar cover intercepting one side of
the tape. Be sure not to inadvertently move the tape to include or exclude certain
plants. If the measurements are made in 10ths and 100ths of feet, the totals are
easily converted to percentages. The measurements are recorded by species on the
Line Intercept form (Illustration 12).

. Calculations Make the calculations and record the results on the Line Intercept

form (see Illustration 12).
a Cover

(1) Calculate the percent cover of each plant species by totaling the intercept
measurements for all individuals of that species along the transect line and
convert this total to a percent.

(2) Where the measurements are made in 10ths and 100ths of feet along a
100-foot transect, the totals for each species are the cover percentages.

(3) Calculate the total cover measured on the transect by adding the cover
percentages for all the species. This total could exceed 100% if the inter-
cepts of overlapping canopies are recorded.

b Composition With this method, species composition is based on the percent
cover of each species. Calculate percent composition by dividing the percent
cover for each plant species by the total cover for all plant species.

Data Analysis It is important to realize that each transect is a single sampling
unit. For trend analysis permanent sampling units are suggested. If permanent
transects are monitored, use the appropriate paired analysis technique. Use either
a paired t-test or the nonparametric Wilcoxon signed rank test when testing for
change between years. When comparing more than two sampling periods, use
repeated measures ANOVA. If the transects are not permanently marked, use the
appropriate nonpaired test.

References

Brun, Jorge M. and Thadis W. Box. 1963. Comparison of line intercepts and

random point frames for sampling desert shrub vegetation. J. Range Manage.
16:21-25.

Buckner, D.L, 1985. Point-Intercept Sampling in Revegetation Studies: Maximizing
Objectivity and Repeatability. Paper presented at American Society for Surface
Mining and Reclamation Meeting, Denver, CO. 1985.

Canfield, R-H. 1941. Application of the line interception method in sampling
range vegetation. J. Forestry 39:388-394.

Canfield, R.H. 1944. Measurement of grazing use by the line intercept Method.
Jour. For. 42(3):192-194



Page ——_of —_

Study Location & Documentation Data

Study Method

Study Number

Allotment Name & Number

Pasture

District

Resource Area

Ecological Site

Plant Community

Date Established Established by (Name) Map Reference
Elevation Slope Exposure Aerial Photo Reference
Township Range Section 1/4 1/4 1/4
Scale: ___ inches
Location equals one mile
Key Species
1 2 3

Distance and bearing between reference post or reference point and the transect

location stake, beginning of transect, or plot

Ut

Distance and bearing between location stake and bearing stake

Transect Bearing

Vertical Distance Between Ground & Aligned Tape

Length of Transect

Plot/Frame Size

Sampling Interval

] Total Number of Samples

a

Notes (Description of study location, diagram of transect/plot layout, description of photo points, etc. If more
space is needed, use reverse side or another page.)

Note: Depending on the study method, fill in the blocks that apply when a study is established. This
documentation enables the examiners to conduct follow-up studies in a consistant manner to provide
comparable data for analysis, interpretation, and evaluation.



METHODS—Step Point

Diagrammatic Sketches of Sample Units (Hits)
and Recording Procedures

The data from the above illustrated sample units (hits) are recorded on the Cover Data Form
as follows:

BASAL and FOLIAR

BSL or grnd-lev Foliar-level 1 Foliar-level 2 Foliar-level 3
Line 1— B AGSP PUTR 2 AIED
line2—| ARTRZ LCPIEDJ
Line 3 — AGSP CHNA 2
Line 4— L AGSP

Note — To count as a basal hit on live vegetation, the plant crown at or below a 1-inch height above the
ground must be intercepted by the pin.

— Dead vegetation in the canopy is counted as litter.

— Enclose plant species codes for vegetation cover hits more than 20 feet above ground level in
brackets [ ].

Illustration 14



STUDY DESIGN AND ANALYSIS

xX <——Transect Bearing Stake

End Point of Transect __+f-]

—_ Quadrats

100-Meter Tape ———*|

JUUUUU

Midpoint of Transect ———»

OUUUUCU0UO

\

|

Beginning Point of Transect _ sf

xX +— Study Location Stake

Figure 4. Study layout for the linear technique. | 13 |



METHODS—Visual Obstruction—Robel Pole

13. References

Robel, R.J., JN. Briggs, A.D. Dayton, and L.C. Hulbert. 1970. Relationships
Between Visual Obstruction Measurements and Weight of Grassland Vegetation,
J, Range Manage. 23:295.

Robel, RJ. 1970. Possible Role of Behavior in Regulating Greater Prairie
Chicken’s Populations, J. Wildlife Manage. Vol 34:306-312.

Snyder, W.D. 1991. Wheat stubble as nesting cover for ring necked pheasants in
northern Colorado. Wildlife Soc. bulletin vol 194).

USDA, Forest Service. 1994. Rangeland Analysis and Management Training
Guide, Rocky Mountain Region USDA Forest Service Denver, Colorado.



GLOSSARY oe

browse: (1) the part of shrubs, half shrubs, woody vines, and trees available for animal
consumption; or (2) to search for or consume browse.

browse plant or browse species: a shrub, half shrub, woody vine, or tree capable of produc-
ing shoot, twig, and leaf growth suitable for animal consumption.

Cc

canopy cover: the percentage of ground covered by a vertical projection of the outermost
perimeter of the natural spread of foliage of plants. Small openings within the canopy are
included. Canopy cover is synonymous with crown cover.

class of livestock: the age and/or sex groups of a kind of livestock.

community: an assemblage of populations of plants and/or animals in a common spatial
arrangement.

composition: the proportions of various plant species in relation to the total on a given area.
It may be expressed in terms of relative cover, relative density, relative weight, etc.

cool season species: plants whose major growth occurs during the late fall, winter and early
spring.

crown cover: (See canopy cover.)

critical area: an area which should be treated with special consideration because of inherent
site factors, size, location, condition, values, or significant potential conflicts among uses.

D

density: numbers of individuals or stems per unit area (does not equate to any kind of cover
measurement).

E

ecological site: a kind of rangeland with a specific potential natural community and specific
physical site characteristics, differing from other kinds of rangeland in its ability to pro-
duce vegetation and to respond to management. Ecological sites are defined and de-
scribed with soil, species composition, and production emphasis. Ecological site is synony-
mous with range site and ecological type (FS).

ecological status: the present state of vegetation of an ecological site in relation to the
potential natural community for the site. Ecological status is independent of use. It is an
expression of the relative degree to which the kinds, proportions, and amounts of plants in
a community resemble that of the potential natural community. The four ecological
status classes correspond to 0-25, 26-50, 51-75, or 76-100 percent similarity to the poten-
tial natural community and are called early-seral, mid-seral, late-seral, and potential natural
community, respectively.

estimated use: the use made of forage on an area by wildlife, wild horses, wild burros, and/
or livestock where actual use data are not available. Estimated use may be expressed in

terms of animal unit months or animal months.



* _ METHODS—Step

(3)

(4)

int

the boot and vertically lower the pin until it either intersects an herbaceous
plant or the ground for the specified number of hits. It is recommended
that the interval be a minimum of 5 paces. To lengthen the transect,
increase the distance between hits (10 paces, 20 paces, etc.).

When obstructions such as juniper trees, cholla cactus, or ledge rock, etc.,
are encountered, sidestep at 90° from the transect line and continue pacing
parallel to the transect to avoid the obstructions. Return to the original
transect line as soon as possible by sidestepping at 90° in the opposite
direction. Continue pacing along the transect bearing. If the obstruction
(juniper tree, cholla cactus, or ledge rock) is determined to be a highly
important component of the community, this information can be recorded
qualitatively on the back of the form.

In most cases, do not count hits along portions of a transect that have been
unnaturally disturbed, such as roads or trails. When such areas are
encountered, proceed three paces past the disturbance before resuming the
reading of hits along the transect line.

b Collecting Cover Data At each observation point, identify the ground level
or basal hit with the point of the pin and record the data by dot count tally by
category and/or plant species code in the appropriate section of the Cover Data
form (see Illustrations 13 and 14). If there is a vegetation canopy layer, lower
the pin through the vegetation until a basal or ground level hit is determined.
Record the basal or ground level hit and any subsequent vegetation layers that
intersect the pin. For vegetation structure above 3-feet (length of pin), a visual
observation of plant intercepts above the notch in the boot can be made and
recorded as additional canopy or foliar level hits on the data form.

io)

Ground-level or basal hits

(a) Ground-level hits (excluding basal vegetation hits) will fall into four
cover categories. They can be redefined and/or additional categories
added, depending on the data needed. The four categories are:

L - Litter

B - Bare ground

G - Gravel (particle sizes between 1/12 inch and 10 inches)
S - Stone (greater than 10 inches)

(b) Record the ground-level hits by dot count tally by ground-level cover
category in the Ground-Level Cover section of the form, except where
there are ground-level and, basal or canopy cover hit combinations. In
this situation, use the Basal and Canopy/Foliar Cover section of the form.

(c) Basal hits on live vegetation are identified by species (includes mosses
and lichens more than 1/16 inch thick). To count as a basal hit on live
vegetation, the plant crown at or below a l-inch height above the
ground MUST be intercepted by the pin.





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METHODS—Frequency

B. Frequency Methods - Pace Frequency, Quadrat
Frequency, and Nested Frequency Methods

1. General Description All three methods consist of observing quadrats along
transects, with quadrats systematically located at specified intervals along each
transect. The only differences in these technique are the size and configuration of
the quadrat frames and the layout of the transect. The following vegetation
attributes are monitored with this method:

° Frequency
© Basal cover and general cover categories (including litter)

¢ Reproduction of key species (if seedling data are collected)

It is important to establish a photo plot (see Section V.A) and take both close-up
and general view photographs. This allows the portrayal of resource values and
conditions and furnishes visual evidence of vegetation and soil changes over time.

2. Areas of Use This method is applicable to a wide variety of vegetation types
and is suited for use with grasses, forbs, and shrubs.

3. Advantages and Limitations

a Frequency sampling is highly objective, repeatable, rapid, and simple to perform,
and it involves a minimum number of decisions. Decisions are limited to
identifying species and determining whether or not species are rooted within
the quadrats (presence or absence).

b Frequency data can be collected in different-sized quadrats with the use of the
nested frame. When a plant of a particular species occurs within a plot, it also
occurs in all of the successively larger plots. Frequency of occurrence for various
size plots can be analyzed even though frequency is recorded for only one size
plot. This eliminates problems with comparing frequency data from different
plot sizes. Use of the nested plot configuration improves the chance of selecting
a proper size plot for frequency sampling.

c Cover data can also be collected at the same time frequency data is gathered.
However, cover data collected in this manner will greatly overestimate cover;
unless the tines are honed to a fine point, observer bias will come into play.
Another limitation is that the use of one size quadrat will likely result in values
falling outside the optimum frequency range (greater than 20 percent to less
than 80 percent) for some of the species of interest.

4. Equipment The following equipment is needed (see also the equipment list in
Section V.A, page 31, for the establishment of the photo plot):

Study Location and Documentation Data form (see Appendix A)
Frequency form (see Illustration 4)

Nested Frequency form (see Illustration 5)

Permanent yellow or orange spray paint

Frequency frames (see Illustrations 6 and 7)

oeoeee



APPENDIX D

The formula for using these decimal random numbers for selecting a sampling unit or
point is:

{uxN]+1

Where: u = random number (expressed as decimal)
total population size
[ ] = used to indicate that only the integer part of the product is used in the
calculation

To illustrate how this formula works, let’s say that our baseline is 200 meters long. Here
we need to select numbers between 0 and 200 as points along a baseline. Consider
these points as a “population” of 200 possible points. Using the first of the six random
numbers we came up with above, 0.32978, we calculate:

[0.32978 x 200] +1
[65.956] +1

654+1

66

not i

Thus, 66 is the first point. Using the second random number we have:

[0.59902 x 200] + 1
[119.80400] +1
119+1

120

noueou

Now we have the second point, 120. We continue in this manner until we have the five
points we need. Although the formula may look difficult, a hand-held calculator or
computer program with a random number generator makes it easy.

The reason for adding the 1 to the integer of the product of the random number and N
is that only whole numbers will be used. Without adding 1, it would be impossible to
obtain the number 200. Consider the highest possible random number we could obtain,
0.99999. If we multiply this number by 200, we obtain 199.99800; taking the whole
integer of this number yields the number 199. Adding 1 makes it 200.

Asa rule of thumb, you should make sure the random numbers have more digits on the
right side of the decimal point than the number of digits in N. In the example above, N
is 200 and we are using random numbers with five digits to the right of the decimal
point, so we are okay.

Note that this process is much more efficient than the first method because we do not
need to reject any numbers. Given the fact that there is only a ] in 5 chance of any
three-digit number falling between 1 and 200, we would—on the average—have to
examine 25 three-digit numbers to come up with five points under the first method.
Using the second method, on the other hand, we can use the first five random numbers
from the table to select the same five points.

| 162



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Mlustration 10



Society for Range Management. 1974. A glossary of terms used in range management. 2nd
Ed. M.M. Kothmann (ed.), SN4 Publ. 36 p.

. 1975. Rangeland reference areas. William A. Laycock (ed.), SN4 Publ , Range
Science Series, No. 3. 66 p.

. 1983. Guidelines and terminology for range inventories and monitoring. Report of
the Range Inventory Standardization Committee. 13 p.

——. 1985. Proceedings of Special Symposium - Rangeland Monitoring.

Spalinger, D.E. 1980. Vegetation Changes on Eight Selected Deer Ranges in Nevada Over a
15-Year Period. Nevada State Office Bureau of Land Management.

Stanton, F.W. 1960. Ocular Point Frame. J. Range Manage. 13:153.

Steel, Robert G.D. and James H. Torrie. 1980. 2nd Ed. Principles and procedures of statistics.
McGraw-Hill Book Co., New York, NY. 633 p.

Stoddart, Laurence A., Arthur D. Smith, and Thadis W. Box. 1975. Range management. 3rd
Ed. McGraw-Hill Book Co., New York. 532 p.

Tueller, Paul T. 1977. Large scale 70mm photography for range resources analysis in the
western United States. In: Proc. 11th Int’l. Symp. on Remote Sensing, Ann Arbor, MI.
pp. 1507-1514.

—_——. 1979. Some aspects of the use of dichotomous keys to aid in the interpretation of
color aerial photographs for vegetation mapping. In: Proc. ASP 7th Annual Workshop
on Color Aerial Photography in the Plant Sciences, Davis, CA. pp. 189-200.

. 1988. Vegetation Science Applications for Rangeland Analysis and Management.
Kluwer Academic Publishers, Boston, MA. 642 p.

Tueller, Paul T., Garwin Lorain, Karl Kipping, and Charles Wilkie. 1972. Methods for
measuring vegetation changes on Nevada rangelands. Agr. Exp. Sta., Univ. of Nevada,
Reno, NV. T16. 55 p.

Tueller, Paul T. and D. Terry Booth. 1974. Photographic remote sensing techniques for
erosion on wildlands. BLM Contract 08550-CTS-2, Coll. of Agr., Univ. of Nevada,
Reno, NV. 97 p.

Uresk, D.W., R.O. Gilbert, and WH. Rickard. 1977. Sampling big sagebrush for phytomass.
J. Range Manage. 30:311-314.

USDA, Forest Service. 1959. Techniques and methods of measuring understory vegetation.
Proc. of Symp. at Tifton, Georgia, Oct. 1958. U.S. Dept. of Agr., For. Ser., Southern For.
Exp. Sta. and Southeastern For. Exp. Sta. 174 p.

. 1963. Range research methods. Proc. of Symp., Denver, CO, May 1962. U.S.
Dept. of Agr., Misc. Publ. No. 940. 172 p.



10.

METHODS—Photographs

camera, film, and local knowledge of photo point location; given these, they are
easy to set up and retake, Agencies can encourage participation by external groups
or permittees by providing the photographer with film and development. Double
prints allow the agency and photographer to keep copies of photographs for their
files. Negatives should generally be kept and filed at the agency office.

Video Images Video cameras, i.e., camcorders, are now available and are able to
record multiple images of landscapes for monitoring. While video images provide
new ways to record landscape images, limitations in their use should also be
considered. Video tapes, especially the quality of the image, may begin to deterio-
rate within 5 years. These images can be protected by conversion to digital com-
puter images (expensive) or rerecording the original tape onto a new blank tape.

Comparing repeat video images is difficult, especially if the same landscape se-
quences are not repeated in the same way on subsequent video recordings. Video
cameras are also more susceptible to dust and heat damage and cost considerably
more than 35-mm cameras. Advantages and disadvantages of video cameras
should be carefully considered prior to implementing a video monitoring system.

Repeat Pictures When repeat pictures are taken, follow the same process used
in taking the initial pictures. Include the same area and landmarks in the repeat
general view pictures that were included in the initial pictures. Take repeat pictures
at approximately the same time of year as the original pictures.

General Observations General observations concerning the sites on which
photographs are taken can be important in interpreting the photos. Such factors as
rodent use, insect infestation, animal concentration, fire, vandalism, and other site
uses can have considerable impact on vegetation and soil resources. This informa-
tion can be recorded on note paper or on study method forms themselves if the
photographs are taken while collecting other monitoring data.

References

USDI, Bureau of Land Management. 1985. Rangeland monitoring - Trend
studies TR4400-4.

USDA, Forest Service. 1994. Rangeland Analysis and Management Training
Guide, Rocky Mountain Region USDA Forest Service Denver, CO.



METHO! ine Intercept

b Pilot Studies Collect data on several pilot studies to determine the number of
samples (transects or observation points) and the number and size of quadrats
needed to collect a statistically valid sample (see Section III.B.8).

c Number of Transects Establish the minimum number of transects to achieve
the desired level of precision for the key species in each study site (see Section III.B).

d Length of Transect The length of a transect is based on the density and
homogeneity of the vegetation. If the vegetation is sparse, a longer transect is
needed. Transects may be any length (eg. 100 feet, 200 feet, or even longer).

e Study Layout Line Intercept data can be collected using either the baseline or
linear study design described in Section III.A.2 beginning on page 8. The
baseline technique is the recommended study design.

(1) The study location stake is placed at the beginning of the baseline. After
determining the bearing of the study, a stake is placed at the end of the
baseline. Transects are run perpendicular to and at random distances along
the baseline. Transect location stakes are placed at the beginning and end
of each transect. The distance between the stakes dependents on the length
of the transect. The height of the stakes depends on the height of the
vegetation. (Directions for randomly selecting the location of transects to be
run off of a baseline using random number tables are given in Appendix D).

Transect location stakes may be left in place as permanent markers or
removed at the conclusion of the study. Permanently marking transects
will result in greater power to detect change.

(2) Stretch the transect tapes between stakes as close to the ground as possible,
with the zero point of the tape aligned on the baseline (the beginning point
of the transect). Do not allow vegetation to deflect the alignment of the tape.

f Reference Post or Point Permanently mark the location of each study with a
reference post and a study location stake (see beginning of Section III).

g Study Identification Number studies for proper identification to ensure that
the data collected can be positively associated with specific sites on the ground.
(see Appendix B).

h Study Documentation Document pertinent information concerning the study

on the Study Location and Documentation Data form (see beginning of Section
Ill and Appendix A).

: Taking Photographs The directions for establishing photo plots and for taking
close-up and general view photographs are given in Section V.A.

. Sampling Process In addition to collecting the specific studies data, general
observations should be made of the study sites (see Section II.F).

Proceed down the tape stretched along the transect line and measure the horizontal
linear length of each plant that intercepts the line. Measure grasses and grass-like

fs |



METHODS—Double Weight Sampling

J.

Double-Weight Sampling

1. General Description This technique has been referred to by some as the
Calibrated Weight Estimate method. The objective of this method is to determine
the amount of current-year above-ground vegetation production on a defined area.
The following vegetation attributes are monitored:

¢ Peak standing crop, which is the above-ground annual production of each plant
species

¢ Species composition by weight

It is important to establish a photo plot (see Section V.A) and take both close-up

and general view photographs. This allows the portrayal of resource values and

conditions and furnishes visual evidence of vegetation and soil changes over time.
2. Areas of Use This method can be used in a wide variety of vegetation types. It

is best suited to grasslands and desert shrubs. It can also be used in large shrub and

tree communities, but the difficulties increase.

3. Advantages and Limitations

a Double-weight sampling measures the attribute historically used to determine
capabilities of an ecosystem.

b It provides the basic data currently used for determining ecological status.

c Seasonal and annual fluctuations in climate can influence plant biomass.

d Measurements can be time-consuming.

e Current year’s growth can be hard to separate from previous years’ growth.

f Accurate measurements require collecting production data at peak production
periods, which are usually short, or using utilization and phenology adjustment
factors.

g Green weights require conversion to air-dry weights.

h In most areas, the variability in production between quadrats and the accuracy
of estimating production within individual quadrats requires the sampling of

large numbers of quadrats in order to detect reasonable levels of change.

4, Equipment The following equipment is needed (see also the equipment listed in
Section V.A, page 31, for the establishment of the photo plot):

Study Location and Documentation Data form (see Appendix A)
Production form (Illustration 22)

Sampling frames or hoops

One stake: 3/4- or 1-inch angle iron not less than 16 inches long



REPORT DOCUMENTATION PAGE

Form Approved
OMB No. 0704-0188

Public reporting burden for this collection of Information is estimatad to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and
maintaining tha data neaded, and completing and reviewing the collection of information. Send comments cagarding this burden estimate or any other aspect of this collection of information,
including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jetferson Davis Highway, Suite 1204, Arlington,

VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188), Washington, DC 20503.

4. AGENCY USE ONLY (Leave blank) 2. REPORT DATE

June 1996

3. REPORT TYPE AND DATES COVERED

Final

FS

. TITLE AND SUBTITLE

Sampling Vegetation Attributes

2

. AUTHOR(S)
Interagency Technical Team

5. FUNDING NUMBERS

~

. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

U.S. Department of the Interior

Bureau of Land Management - National Applied Resource Sciences Center
P.O. Box 25047

Denver, CO 80225-0047

8. PERFORMING ORGANIZATION

REPORT NUMBER

BLMI/RS/ST-96/002+1730

2

SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)

10, SPONSORING/MONITORING

AGENCY REPORT NUMBER

11. SUPPLEMENTARY NOTES

12a, DISTRIBUTION/AVAILABILITY STATEMENT

12b. DISTRIBUTION CODE

13. ABSTRACT (Maximum 200 words)

This interagency technical reference provides the basis for consistent, uniform, and
standard vegetation attribute sampling that is economical, repeatable, statistically
reliable, and technically adequate. While not all inclusive, this reference does include
the primary vegetation sampling methods used across the West (frequency methods, dry
weight rank method, Daubenmire, line intercept, density method, comparative yield,
etc.).

14. SUBJECT TERMS

+ Rangeland inventory
* Rangeland monitoring
« Rangeland evaluation

* Vegetation attributes
* Vegetation sampling

1. NUMBER OF PAGES
172, including covers

16, PRICE CODE

17. SECURITY CLASSIFICATION
OF REPORT
Unclassified

18, SECURITY CLASSIFICATION
OF THIS PAGE
Unclassified

19. SECURITY CLASSIFICATION
OF ABSTRACT

Unclassified

20, LIMITATION OF ABSTRACT

UL

NSN 7540-01-280-5500

Standard Form 298 (Rev. 2-89)



METHODS: ual Obstruction—Robel Pole

a Site Selection The most important factor in obtaining usable data is selecting
representative areas (critical or key areas) in which to run the study (see Section
IL.D). Study sites should be located within a single plant community within a
single ecological site. Transects and sampling points need to be randomly
located within the critical or key areas (see Section III).

b Pilot Studies Collect data on several pilot studies to determine the number of
samples (transects or observation points) and the number and size of quadrats
needed to collect a statistically valid sample (see Section III.B.8).

c Vertical Cover Classes Establish the number of vertical cover classes and
height limits for each class based on objectives. These cover classes must be
developed locally for each ecological site or plant community. The following is
an example of cover classes established for upland bird nesting cover on the Fort
Pierre National Grasslands:

Cover Classes Visual Obstruction Height
1 0.0-1.9
2 2.0-2.9
3 3.0 -3.9
4 40+

d Number of Transects Establish the minimum number of transects to achieve the
desired level of precision for the key species in each study site (see Section III.B).

e Number of Observation Points The number of observation points will
depend on the objectives, level of precision required, etc.; however, it is recom-
mended that a minimum of 50 be read per transect. Additional observation
points should be read, depending on the pilot study.

f Study Layout Data can be collected using the baseline, macroplot, or linear
study designs described in Section III.A.2 beginning on page 8. The linear
technique is the one most often used.

g Reference Post or Point Permanently mark the location of each study with a
reference post and a study location stake (see beginning of Section III).

h Study Identification Number studies for proper identification to ensure that
the data collected can be positively associated with specific sites on the ground
(see Appendix B).

i Study Documentation Document pertinent information concerning the study
on the Study Location and Documentation Data form (see beginning of Section
III and Appendix A).

7. Taking Photographs The directions for establishing photo plots and for taking
close-up and general view photographs are given in Section V.A.



METHODS—Frequency

Tueller, Paul T., Garwin Lorain, Karl Kipping, and Charles Wilkie. 1972. Methods
for measuring vegetation changes on Nevada rangelands. Agr. Exp. Sta., Univ.
of Nevada, Reno, NV. T16. 55 p.

USDI, Bureau of Land Management. 1985. Rangeland monitoring - Trend studies
TR4400-4.

West, N.E. 1985. Shortcomings of plant frequency-based methods for range
condition and trend. William C. Krueger, Chairman. Proc., 38th Annual
Meeting Soc. for Range Manage. Feb. 1985. Salt Lake City. Soc. for Range
Manage. 87-90.

Whysong, G.L. and W.W. Brady, 1987. Frequency Sampling and Type II Errors, J.
Range Manage. 40:172-174.



METHODS—Point Intercept

Example of a Point Frame

Illustration 17 Ea



INTRODUCTION _ : oo

G. Coordination Monitoring programs will be coordinated with interested publics

and other appropriate state and federal agencies. Monitoring should be planned and
implemented on an interdisciplinary basis.

Electronic Data Recorders Electronic data recorders are handheld “com-
puters” that are constructed to withstand the harsh environmental conditions found in
the field. They are used to record monitoring data in a digital format that can be
transferred directly to a personal computer for storage and retrieval. They require
minimal maintenance, are generally programmable, and allow easy data entry using a
wand and bar codes.

Recording field data using an electronic data recorder takes approximately the same
amount of time as using printed forms. The advantage with electronic data recorders
is that they improve the efficiency by reducing errors associated with entering data
into a computer for analysis. They can also reduce the time needed for data compila-
tion and summarization.

The cost of electronic data recorders and computer software programs is considerable
and should be evaluated prior to purchase. It is also important to have good computer
support assistance available to assist users in operating, downloading, and trouble-
shooting electronic data recorders, especially during the initial use period.

Refer ence Areas Reference areas are rangelands where natural biological and
physical processes are functioning normally. Reference areas serve as benchmarks for
comparing management actions on rangelands. Reference areas differ from key areas
in that they represents rangeland where impacts are minimal. Reference areas are

found in grazing exclosures, natural areas, or areas that receive minimal grazing impacts.

Reference areas should be included in any monitoring program to evaluate the influ-
ences of natural variables (especially climate) on vegetation. Cause-and-effect rela-
tionships are better determined if the effects of climate on vegetation can be separated
from management effects. Monitoring studies, especially trend studies, should there-
fore be established both on key areas and reference areas located on the same ecologi-
cal sites. Of course, monitoring priorities and funding resources must be considered in
planning and establishing monitoring studies on reference areas.



PREFACE
[. PREFACE

The intent of this interagency monitoring guide is to provide the basis for consistent,
uniform, and standard vegetation attribute sampling that is economical, repeatable,
statistically reliable, and technically adequate. While this guide is not all inclusive, it does
include the primary sampling methods used across the West. An omission of a particular
sampling method does not mean that the method is not valid in specific locations; it simply
means that it is not widely used or recognized throughout the western states. (See Section
V.N, Other Methods.)

Proper use and management of our rangeland resources has created a demand for uniformity
and consistency in rangeland health measurement methods. As a result of this interest, the
USDI Bureau of Land Management (BLM) and USDA Forest Service met in late 1992 and
agreed to establish an interagency technical team to jointly oversee the development and
publishing of vegetation sampling field guides.

The 13-member team currently includes representatives from the Forest Service, BLM, the
Grazing Land Technology Institute of the Natural Resource Conservation Service (NRCS),
and the Cooperative Extension Service.

The interagency technical team first met in January 1994 to evaluate the existing rangeland
monitoring techniques described in BLM’s Trend Studies, Technical Reference TR 4400-4. The
team spent 2 years reviewing, modifying, adding to, and eliminating techniques for this
interagency Sampling Vegetation Attributes technical reference. Feedback from numerous
reviewers, including field personnel, resulted in further refinements.



Whitman, W.C. and E.I. Siggeirsson. 1954. Comparison of line interception and point
contact methods in the analysis of mixed range vegetation. Ecology 35:431-436.

Whysong, G.L. and W.W. Brady, 1987. Frequency Sampling and Type II Errors, J. Range
Manage. 40:172-174.

Wiegert, R.G. 1962. The selection of an optimum quadrat size for sampling the standing
crop of grasses and forbs. Ecology 43:125-129.

Williams, B. 1978. A sampler on sampling. John Wiley & Sons, New York, NY.

Willoughby, John W. 1993. Sampling and analysis problems associated with Bureau of Land
Management Technical Reference 4400-4 (Trend Studies), Personal Information Memo-
randum.

Wilm, H.G., D.F. Costello, and GE. Klipple. 1944. Estimating forage yield by the double-
sampling method. Amer. Soc. Agron. J. 36:194-203.

Winkworth, R.E., R.A. Perry, and C.V. Rossetti. 1962. A comparison of methods of esti-
mating plant cover in an arid grassland community. J. Range Manage. 15:194-196.

Winkworth, R.E. and D.W. Goodall. 1962. A Crosswire Sighting Tube for Point-Quadrat
Analysis. Ecology 43:342-343.

Wright, Henry A. 1967. Contrasting responses of squirreltail and needle-and-thread to
herbage removal. J. Range Manage. 20:398-400.

Zar, Jerrold H. 1984. Biostatistical analysis, 2nd Ed. Prentice-Hall, Inc., Englewood Cliffs,
NJ. 718 p.



METHODS—Frequency —

transected, add additional paces or distance (20 paces, 50 feet) between quadrats.
Additional transects can be added to obtain an adequate sample.

(1) Start each transect by placing the rear corner of the quadrat frame at the
starting point along the baseline tape.

(2) Place the quadrat frame at the designated interval along a transect perpen-
dicular to the baseline until the specified number of quadrats have been
read. The interval between quadrats can be measured or estimated by
pacing.

(3) When a transect is completed, move to the next starting point on the
baseline tape and run the next transect.

b Collecting Cover Data Record, by dot count tally, the cover category at each
of the four corners and at the tip of any tines on the frame. Enter this data in
the Cover Summary section of the Frequency and Nested Frequency forms (see
Illustrations 4 and 5). The cover categories are bare ground (gravel less than
1/12 inch in diameter is tallied as bare ground), litter, and gravel (1/12 inch and
larger). Additional cover categories can be added as needed. Vegetation is
recorded as basal hits or canopy layers in the bottom portion of the form. Up to
three canopy layers can be recorded. For additional information on collecting
vegetation cover data, see Section V.F.8.b on page 72. Cover data can also be
recorded on the Cover Data form, Illustration 13, page 75.

Read the same points on the frame and the same number of points at each
placement of the frame throughout a study and when rereading that study.

c Collecting Frequency Data Collect frequency data for all plant species.
Record the data by species within each quadrat using the Frequency form
(Illustration 4). Only one record is made for each species per quadrat, regard-
less of the number of individual plants of a species that occurs within the
quadrat.

(1) Herbaceous plants (grasses and forbs) must be rooted in the quadrat to be
counted.

(2) On many occasions, rooted frequency on trees and shrubs (including half
shrubs) does not provide an adequate sample (occurring within 20% of the
plots). To increase the sample size on trees and shrubs, the canopy over-
hanging the quadrat can be counted.

(3) Annual plants are counted whether green or dried.

(4) Specimens of the plants that are unknown should be collected and marked
for later identification.

(5) Frequency occurrence of seedlings by plant species should be tallied
separately from mature plants.



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METHODS—Step ft

categories, know how to collect canopy or foliar cover data, and know how to
collect cover data using a pin and notch in the boot.

. Establishing Studies Careful establishment of studies is a critical element in
obtaining meaningful data.

a Site Selection The most important factor in obtaining usable data is selecting
representative areas (critical or key areas) in which to run the study (see Section
II.D). Study sites should be located within a single plant community within a
single ecological site. Transects and sampling points need to be randomly
located within the critical or key areas. (see Section III).

b Pilot Studies Collect data on several pilot studies to determine the number of
samples (transects or observation points) and the number and size of quadrats
needed to collect a statistically valid sample (see Section III.B.8).

c Number of Transects Establish the minimum number of transects to achieve
the desired level of precision (see Section III.B).

d Study Layout Data can be collected using either the baseline or linear study
designs described in Section II].A.2 beginning on page 8. The linear technique
is the one most often used.

e Reference Post or Point Permanently mark the location of each study with a
reference post and a study location stake (see beginning of Section III).

f Study Identification Number studies for proper identification to ensure that
the data collected can be positively associated with specific sites on the ground
(see Appendix B).

g Study Documentation Document pertinent information concerning the study
on the Study Location and Documentation Data form (see beginning of Section III
and Appendix A).

. Taking Photographs The directions for establishing photo plots and for taking
close-up and general view photographs are given in Section V.A.

. Sampling Process In addition to collecting the specific studies data, general
observations should be made of the study sites (see Section II.F).

a Running a Transect Determine the transect bearing and select a prominent
distant landmark such as a peak, rocky point, etc., that can be used as the
transect bearing point.

(1) Start a transect by randomly selecting a point along the transect bearing
and reading the first hit (observation point).

(2) Read hits at specified intervals by placing the heel of the boot on the
ground with the sole of the boot at a 30-degree angle to the ground. Place
the pin into the 3/16th inch wide by 1/8th inch deep notch in the toe of



METHODS—Point Intercept —_

8. Sampling Process In addition to collecting the specific studies data, general
observations should be made of the study sites (see Section II.F).

a Transects Run a series of transects perpendicular to the baseline in both
directions. The beginning points for each transect are randomly selected points
along the baseline and the direction of each transect is also randomly determined
(see Section ITL.A.2).

To ensure that both transects and points/point frames are independent, spacing
between transects and between points/point frames on each transect should be greater
than the average diameter of the largest plants likely to be sampled. (If only basal cover
is to be sampled, this diameter is the basal diameter; otherwise, it is canopy diameter.)

b Sampling along Transects The first point/point frame read on each transect
should be randomly determined. After the first point/point frame is read, all
others are spaced the predetermined interval from the first point. If a tape is
used for the transects, always read on the same side of the tape.>

¢ Sighting Device Determine hits by sighting through the device and recording
the cover category in the cross hairs.

¢ Pin/point frames Determine hits by recording the cover category intercepted
by each of the points. For pin frames, this is the cover category hit by each
pin; for grid frames, this is the cover category determined by sighting through
the “cross hairs” formed by each of the intersections of strings.

Hits are recorded on the Cover Data form (Illustration 13) in the following
categories: vegetation (by plant species), litter, gravel, stone, and bare ground.
Prior to recording data, the examiner needs to determine if canopy/foliar cover
or basal cover (or both) will be recorded and if hits will be recorded in more
than one canopy layer. For sighting devices and some pin/point frames, record-
ing hits in more than one canopy layer requires that upper layers be temporarily
moved out of the way to provide a direct line of sight to the lower canopy layers.

c Paired Samples If the data are to be analyzed as paired samples, each transect
should be permanently marked the first year at both ends. In each subsequent
year of measurement, a tape should be run from one end to the other and the
points/point frames read at the selected intervals along the transect. This
process should then be repeated for each transect.

d Independent Samples If the data are to be analyzed as independent samples,
the transects do not have to be permanently marked. In this case, it is sufficient
to pace each transect, taking measurements at each specified pace interval. The
observer must ensure, however, that no bias is introduced by subconsciously
“choosing” the point to be read. Such bias can be avoided by looking at the
horizon when placing the tripod down.

=

5 One of the devices manufactured by ESCO employs a mounting arm that is exactly 0.5 m long from tripod
pivot to the axis of point projection. With this device, two points along each transect can be read with each
placement of the tripod (assuming that 1 m is the selected interval between points). If this device is used, the
tripod is placed at 2 m intervals along the tape (or at a number of paces approximating 2 m if no tape is used),
the arm is rotated toward the baseline, the intercepted object is recorded, the arm rotated 180°, the next
intercepted object is recorded, and so on.



SAMPLING VEGETATION
ATTRIBUTES

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INTERAGENCY TECHNICAL REFERENCE
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METHODS—Double Weight Sampling

a

(6)

i)

(b) The number of quadrats harvested depends on the number estimated.
At least one quadrat should be harvested for each seven estimated to
adequately correct the estimates (see table 3).

Table 3

Number of quadrats Minimum Number of
Estimated Quadrats to be Weighed
1-7
8-14
14-21
22-28
29-35
36 - 42

DuUaAWNY

Harvest, weigh, and record the weight of each species in the quadrats
selected for harvesting. Harvest all herbaceous plants originating in the
quadrat at ground level. On rangeland, harvest all of the current leaf, twig,
and fruit production of woody plants located in the quadrats, On native
pasture and grazable woodland, harvest the current leaf, twig, and fruit
production of woody plants within the plot up to a height of 4 1/2 feet
above the ground. For further clarification see Illustration 23.

Correct estimated weights by dividing the harvested weight of each species
by the estimated weight for the corresponding species on the harvested
quadrats. This factor is used to correct the estimates for that species in
each quadrat. A factor of more than 1.0 indicates that the estimate is too
low. A factor lower than 1.0 indicates that the estimate is too high.

After quadrats are estimated and harvested and correction factors for
estimates are computed, air-dry percentages are determined by air-drying
the harvested materials or by selecting the appropriate factor from an air-
dry percentage table. Values for each species are then converted to air-dry
pound per acre or kilograms per hectare for all quadrats. Average weight
and percentage composition can then be computed for the sample area.

10. Calculations The weights collected for each species per quadrat placement are
recorded on the Production form (see Illustration 22).

Record estimated weights for each species occurring in each quadrat in the
appropriate column (Estimated or Clipped Weight sections of the form.)

Quadrats that were harvested are circled. The estimate weights for these
quadrats are totaled and shown in column 4. The total harvested weights are
shown in column 5. Harvested weights for each quadrat for each species are
not shown on the form, only the total for each species.

Column 6 is the actual dry weight for each species from the quadrats that were
clipped.



truction—Robel Pole

Robel Pole
11/8"

157"

48"

39"

eee

1. Pole is 1.125 inches in diameter and 48 inches long.

2. Pole is painted with alternating 1-inch bands of flat white and
gray colors, starting with white on the bottom. Alternating 1-inch
bands can be extended to the top of the pole if needed.

3. A single 157-inch (4m) cord is attached to the pole at a height
of 39 inches (1m) to standardize the distance and height at which
readings are taken.

4. Narrow black numbers corresponding to the number of bands
are painted on the white bands. For example, the bottom white
band is "1," the next white band is "3," and so on.

5. A spike is attached to the bottom of the pole so that it can be
pushed into the ground, allowing one examiner to make the
readings. The spike can be removed if not needed.

Illustration 26 EJ



APPENDIX C

Photo Identification Label

157



TABLE OF CONTENTS

Illustration
Number

... Photo Plot - 3 X 3 Plot Frame Diagram ...

... Daubenmire Summary Form .

TABLE OF CONTENTS (continued)

Title

Photo Plot - 5 X 5 Plot Frame Diagram
Permanent Photo Plot Location .
Frequency Form ...........
Nested Frequency Form
Frequency Frame...
Nested Plot Frame.
Dry Weight Rank Form
Daubenmire Form........

Daubenmire Frame ..
Line Intercept Form.
Cover Data Form.....
Sample Units (Hits) and Recording Procedures .
Examples of Sighting Devices
Examples of Pin Frames ..
Example of a Point Frame
Cover Board Method: Density Board Form
Cover Board Method: Profile Board Form
Examples of Cover Board:
Density Form....
Production Form
Weight Estimate Quadrat

Comparative Yield Form . 121-122
Robel Pole Form 127-128
Robel Pole ..c.ceccccccseeessceresescesessessesneseseeeseessseseeeesseneseseceesseeeecsisenssessseeeees 129



Table 4
(# of plots x size = total area)
(10x096 = 9.6 ft) multiply grams times 100 = pounds per acre
(10x1.92 = 19.2 ft?) multiply grams times 50 = pounds per acre
(10x240 = 24.0 ft?) multiply grams times 40 = pounds per acre
(10x4.80 = 48.0 ft?) multiply grams times 20 = pounds per acre
(10x9.60 = 96.0 ft?) multiply grams times 10 = pounds per acre
(10x96.0 = 960.0 ft’) multiply grams times 1 = pounds per acre
11. Data Analysis This technique involves destructive sampling (clipped plots), so

12.

METHODS—Double Weight Sampling

d The Quadrat Correction Factor (QCF)column 7 is calculated by dividing
column 5 by column 4.

f Column 8 is determined by dividing the dry weight by the green weight. In the
example shown on Illustration 22, the clipped weights were not air dried; the
percent dry weights shown in column 8 were taken from the dry weight conver-
sion table.

g The total estimated weights for each species for the entire transect are shown in
column 9.

h The average yield (column 10) is determined by multiplying the Total Esti-
mated Weight of each species (column 9) times the Quadrat Correction Factor
(column 7) to adjust for the error in estimating weights and then multiplying
that times the percent dry weight (column 8) to determine the adjusted dry
weight or the Average Yield (column 10).

i The Average Yield for each species (column 10) is totaled at the bottom of the
form for the composition totals.

j Percent Composition (column 11) is calculated by dividing the average yield for
each species (column 10) by the composition totals.

k If peak standing crop is collected in grams, it can be easily converted to pounds
per acres if the total area sampled is a multiple of 9.6 ft?.

Use table 4 to convert grams to pounds per acre:

permanent transects or quadrats are not recommended. Since the transects are not
permanently marked, use the appropriate nonpaired test. When comparing more
than two sampling periods, use ANOVA.

References

Cook, C. Wayne and James Stubbendieck, 1986. Range Research: Basic Problems
and Techniques. Society for Range Management. Denver, CO.

Laycock, W.A. 1987. Setting Objectives and Picking Appropriate Methods for
Monitoring Vegetation on Rangelands. Rangeland Monitoring Workshop
Proceedings. U.S, Department of Interior. Bureau of Land Management.
Golden, CO.

107



ATTRIBUTES

b Standing crop and peak standing crop are the measurements most often used in
trend studies. Peak standing crop is generally measured at the end of the growing
season. However, different species reach their peak standing crop at different
times. This can be a significant problem in mixed plant communities.

c Often, the greater the diversity of plant species or growth patterns, the larger
the error if only one measurement is made.

d Other problems associated with the use of plant biomass are that fluctuations in
climate and biotic influences can alter the estimates. When dealing with large
ungulates, exclosures are generally required to measure this parameter. Several
authors have suggested that approximately 25% of the peak standing crop is
consumed by insects or trampled; this is rarely discussed in most trend studies.

e Collecting production data also tends to be time and labor intensive. Cover and
frequency have been used to estimate plant biomass in some species.

E. Structure

1. Description Structure of vegetation primarily looks at how the vegetation is
arranged in a three-dimensional space. The primary use for structure measure-
ments is to help evaluate a vegetation community’s value in providing habitat for
associated wildlife species.

Vegetation is measured in layers on vertical planes. Measurements generally look
at the vertical distribution by either estimating the cover of each layer or by
measuring the height of the vegetation.

2. Advantages and Limitations Structure data provide information that is
useful in describing the suitability of the sites for screening and escape cover,
which are important for wildlife. Methods used to collect these data are quick,
allowing for numerous samples to be obtained over relatively large areas. Methods
that use visual obstruction techniques to evaluate vegetation height have little
observer bias. Those techniques that estimate cover require more training to
reduce observer bias. Structure is rarely used by itself when describing trend.

F Composition

1. Description Composition is a calculated attribute rather than one that is directly
collected in the field. It is the proportion of various plant species in relation to the
total of a given area. It may be expressed in terms of relative cover, relative density,
relative weight, etc.

Composition has been used extensively to describe ecological sites and to evaluate
rangeland condition.

To calculate composition, the individual value (weight, density, percent cover) for
a species or group of species is divided by the total value of the entire population.



METHODS—Cover Boa:

c Number of Transects Establish the minimum number of transects to achieve the
desired level of precision for the key species in each study site (see Section IIIB).

d Study Layout Data can be collected using either the baseline or linear study

designs described in Section III.A.2 beginning on page 8. The linear technique
is the most often used procedure.

(1) Linear transect

(a) Determine the transect bearing and select a prominent distant land-
mark such as a peak, rocky point, etc., that can be used as the transect
bearing point.

(b) Randomly select an observation point along the transect. The cover
board will be placed 15 feet from this observation point in a random
direction. One way to select a random direction is by using the second
hand on a standard watch. Look at the watch and note the direction
the second hand is pointing. Another way is to randomly select a three
digit number between 0 and 360 from a random number table to
represent the degrees on a compass (see Appendix D for directions
and a table of random digits). After taking the initial reading, remain
at the observation point on the transect and take three additional
readings at 90-degree angles from the original bearing and at the same
distance (15 feet). Additional observation points can be established at
specified intervals from the initial observation point along the transect
bearing. A piece of angle iron or rebar should be placed at each
observation point for easy relocation.

(c) Be sure to record the bearing from the observation point to each cover
board location on the Cover Board form (see Illustrations 18 and 19).

(2) Center location

(a) An alternative method of establishing a transect is to randomly select a
center point within an area to be sampled. Set angle iron or rebar at
four randomly selected points 15 feet from the center point. Place the
cover board at each rebar, facing the center post. Take readings and
photographs of the cover board from the center point. Additional
center points can be established as needed.

(b) Be sure to record the bearing and distance to each center point
location from the reference post on the Cover Board form (see
Illustrations 18 and 19).

e Reference Post or Point Permanently mark the location of each study with a
reference post and a study location stake (see beginning of Section III).

f Study Identification Number studies for proper identification to ensure that
the data collected can be positively associated with specific sites on the ground
(see Appendix B).



METHODS—Point Intercept

11.

b Transects Not Permanent If the transects are not permanent, that is, if they
are randomly located in each sampling period, then the samples are indepen-
dent and the points can be treated as the sampling units.

Sighting Devices: Analysis consists of a Chi Square contingency table analysis
to test for significant change between years in numbers of “hits” on the key
species, other plant species, or cover classes.

Point Frames: Analysis consists of testing for significant changes in average
cover between sampling periods using the independent sample t test or the
nonparametric Mann Whitney U test. Independent sample analysis of variance
or the nonparametric Kruskal-Wallis test is used to test for significant changes in
average cover between three or more years.

References

Bonham, C.D. 1989. Measurements for Terrestrial Vegetation, John Wiley and
Sons, 338 p.

Brown, Dorothy. 1954. Methods of surveying and measuring vegetation. Common-
wealth Bureau of Pastures and Field Crops. Bulletin No. 42. Commonw. Agr.
Bur., Farmham Royal, Bucks, England. 223 p.

Brun, Jorge M. and Thadis W. Box. 1963. Comparison of line intercepts and
random point frames for sampling desert shrub vegetation. J. Range
Management. 16:21-25.

Buckner, D.L. 1985. Point-intercept sampling in revegetation studies; maximizing
objectivity and repeatability. Proceedings of the American Society of Surface
Mining and Reclamation. 1985 Annual Meeting, Denver, CO.

Goodall, D.W. 1952. Some considerations in the use of point quadrats for the
analysis of vegetation. Aust. J. Sci. Res., Series B 5:1-41

Greig-Smith, P. 1983. Quantitative plant ecology. 3rd Ed. University of California
Press Berkeley and Los Angeles.

Floyd, D.A., and JE. Anderson. 1983. A new point interception frame for estimating
cover of vegetation. Idaho National Engineering Laboratory Radioecology and
Ecology Programs 1983 Progress Report, pp.107-113~

Levy, E.B. and E.A. Madden. 1933. The Point method for Pasture Analysis. New
Zealand J. Agric. 46: 267-279.

Mueller-Dombois, Dieter and Heinz Ellenberg. 1974. Aims and methods of
vegetation ecology. John Wiley & Sons, New York. 547 p.

Stanton, FW. 1960. Ocular Point Frame. J. Range Manage. 13:153.

Winkworth, R.E. and D.W. Goodall. 1962. A Crosswire Sighting Tube for Point-
Quadrat Analysis. Ecology 43:342-343.



STUDY DESIGN AND ANALYSIS

Macroplot size also depends on the size and shape of the quadrats that will be
used to sample it. The sides of the macroplot should be of dimensions that are
multiples of the sides of the quadrats.

(1) Macroplot layout Pick one corner of the macroplot to serve as the beginning
for sampling purposes. Drive an angle iron location stake into the ground
at this corner. Determine the bearing of the macroplot side that will serve
as the x-axis, run a tape in that direction and put an angle iron stake at the
selected distance. This serves as another corner of the macroplot. Leave
the x-axis tape in place for sampling purposes. Return to the origin and
determine the bearing of the y-axis, which will be perpendicular to the x-
axis. Run a second tape along the y-axis and put an angle iron stake in the
ground at the selected distance. This serves as the third corner of the
macroplot. If desired, a fourth stake may be placed at the remaining
corner, but this is not necessary for sampling since sampling will be done
using the two tapes serving as the x- and y-axes. See Figure 2 for an
example. Leave the tapes in place until the first year’s sampling is completed.

50m
A angle iron
om —A
om 100m
|

Figure 2. The two sides of a 50 m x 100 m macroplot, delineated by two tape measures. Both tapes begin
with their 0 point at the beginning. Note placement of angle irons at three of the corners.

Be sure to document the directions of the x- and y-axes so that the
macroplot can be reconstructed if one of the angle iron stakes is missing.

(2) Quadrat locations Quadrats are located in the macroplot using a coordi-
nate system to identify the lower left-hand corner of each quadrat.

(a) For example it has been determined from the pilot study that 40
samples are needed using a 1 m by 16 m quadrat. The quadrats are to
be positioned so that the long side is parallel to the x-axis. On a 40 m
x 80 m study site (see Figure 3), the x-axis would be the 80 m side.
The total number of quadrats (N) that could be placed in that 40 m x
80 m rectangle without overlap comprises the sampled population. In
this case, N is equal to 200 quadrats.

(b) Along the x-axis there are 5 possible starting points (which always occur
at the lower left-hand corner of each quadrat) for each 1 mx 16m
quadrat (at points 0 m, 16 m, 32 m, 48 m, and 64 m). Number these
points 0 to 4 (in whole numbers) accordingly. Along the y-axis there are
40 possible starting points for each quadrat (at points 0 m, 1 m, 2 m,3 m,
4 m, and so on until point 39 m). Number these points 0 to 39 accord-
ingly (again in whole numbers)



METHODS—Dry Weight Rank

10.

11.

After the quadrat location has been determined, the observer decides which three
species in the quadrat have the greatest yield of current year's growth on a dry
matter basis. The species with the highest yield is given a rank of 1, the next 2,
and the third highest a 3. Data are record by quadrat on the Dry Weight Rank
form, Illustration 8. All other species present are ignored. If there are not three
species present in the quadrat, a multiple rank is assigned.

The Dry Weight Rank method assumes that a rank of 1 corresponds to 70%
composition, rank 2 to 20%, and rank 3 to 10%. If only one species is found in a
quadrat, it would be ranked 1, 2 and 3 (100%). If two species are found, one may
be given ranks of 1 and 2 (90%), ranks 1 and 3 (80%), or ranks 2 and 3 (30%),
depending on the relative weight for the two species (see Illustration 8). For each
species, record the number of 1, 2, or 3 ranks received in the sample.

Data can also be collected and recorded for each quadrat for use in conjunction
with the Comparative Yield Method.

. Calculations

a For each species multiply the number of ranks of 1, 2, and 3 by 7, 2, and 1,
respectively, and record under the appropriate weight column. Add the
amounts in the weight columns of each species and record in the weighted
column.

b Total the weighted column for all species. The total of this column will always
be ten times the number of quadrats.

c Divide the value recorded for each species in the weighted column by the total
of the weighted column to get percent composition for each species. Percent
composition, by definition, should total 100 percent.

Data Analysis Chi Square analysis can be used to determine if the frequency
of each species in each rank tally group (1,2, or 3) has changed from one sampling
period to another. Each species must be analyzed separately.

References

Despain, D.W., P.R. Ogden, and E.L. Smith. 1991. Plant frequency sampling for
monitoring rangelands. In: G.B. Ruyle, ed. Some Methods for Monitoring
Rangelands and other Natural Area Vegetation. Extension Report 9043,
University of Arizona, College of Agriculture, Tucson, AZ.



_
Density Method

1. General Description Density is the number of individuals of a species in a

1.

given unit of area. For rhizomatous and other species for which the delineation of
separate individual plants is difficult, density can also mean the number of stems,
inflorescences, culm groups, or other plant parts per unit area.

2. Areas of Use This method has wide applicability and is suited for use with

grasses, forbs, shrubs, and trees.

3. Advantages and Limitations

a Generally, the density of mature perennial plants is not affected as much by
annual variations in precipitation as are other vegetation attributes such as
canopy cover or herbage production.

b Density is a quantifiable and absolute attribute.

c Density is sensitive to changes in the adult population caused by long-term
climatic conditions or resource uses.

d Density provides useful information on seedling emergence, survival, and mortality.

e Sampling is often quick and easy with certain life forms (e.g., trees, shrubs,
bunchgrasses).

f Plant communities on the same ecological sites can be compared using density
estimates on specific species or lifeforms.

g Density can be useful in estimating plant responses to management actions.

h It can often be difficult to delineate an individual, especially when sampling sod
forming plants (stoloniferous, or rhizomatous plants) and multi-stemmed
grasses or closely spaced shrubs. Although in these cases a surrogate plant part
(e.g., upright stems, inflorescences, culm groups) can be counted, the usefulness
of such estimates is limited to the biological significance of changes in these
surrogates.

i Sampling may be slow and tedious in dense populations; this also raises the risk
of non-sampling errors.

j There is no single quadrat size and shape that will efficiently and adequately
sample all species and life forms. For this reason, density estimations are usually
limited to one or a few key species.

. Equipment The following equipment is needed (see also the equipment listed in

Section V.A, page 31, for the establishment of the photo plot):

¢ Study Location and Documentation Data form (see Appendix A)
¢ Density form (see Illustration 21)





METHODS—Step

(d) Enter the appropriate plant species code in the Basal or Ground-Level
Column in the Basal and Canopy/Foliar Cover section of the form.

(e) Enter a dot count tally for each basal hit on a species in the Dot Count
Column in the Basal and Canopy/Foliar Cover section of the form
when the plant species code is first entered on the form. Enter an
additional dot count tally each time there is a basal hit on that species
on the transect, except where there are basal and canopy/foliar cover
hit combinations.

(2) Ground-level or basal and canopy/foliar cover hit combinations

(a) Identify the ground-level or basal hit, as well as any canopy cover
hit(s) below 3 feet in height, intercepted at each point by the pin. For
canopy cover above 3 feet, use line-of-sight observations directly
perpendicular to the notch in the boot.

(b) Enter the appropriate ground-level cover category code and/or plant
species code for each level of hit (up to four levels) in the appropriate
columns in the Basal and Canopy/Foliar Cover section of the form (see
Illustration 13).

(c) Enter a dot count tally for each ground-level or basal and canopy/foliar
cover hit combination when it is first entered on the form and each
time this same combination is encountered on the transect.

(d) Enclose plant species codes for vegetation cover hits more than 20 feet
above ground level in brackets [ J.

9. Calculations Calculate the percent cover for each cover category by dividing
the number of hits for each category by the total number of hits for all categories,
including hits on vegetation.

a Ground Cover Ground cover is determined by dividing the total number of
hits for all categories except bare ground by the total number of hits (including
bare ground).

b Canopy/Foliar Cover Canopy/Poliar cover is determined by dividing the total
number of hits on vegetation (includes all basal and canopy/foliar hits) by the
total number of hits.

c Basal Cover Basal cover is determined by dividing the number of basal hits by
the total number of hits.

10. Data Analysis

a When transects are the sampling units: For trend analysis, permanent sampling
units are suggested. If permanent transects are monitored, use the appropriate
paired analysis technique to compare change in average cover by species and
cover class. When comparing more than two sampling periods, use repeated



METHODS—Photographs

Rangeland Monitoring

Photo Plot Frame - 3- x 3-foot

Hinge
>

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steel rods

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v

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METHODS—Harvest

Use the following table to convert grams to pounds per acre:

Table 5
(# of plots x size = total area)
(0x0.96 = 9.6 ft?) multiply grams times 100 = pounds per acre
(10x1.92 = 19.2 ft?) multiply grams times 50 = pounds per acre
(10x2.40 = 24.0 ft’) multiply grams times 40 = pounds per acre
(10x4.80 = 48.0 ft’) multiply grams times 20 = pounds per acre
(10x9.60 = 96.0 ft’) multiply grams times 10 = pounds per acre
(10x96.0 = 960.0 ft”) multiply grams times 1 = pounds per acre

10. Data Analysis This technique involves destructive sampling (clipped plots), so
permanent transects or quadrats are not recommended. Since the transects are not
permanently marked, use the appropriate nonpaired test. When comparing more
than two sampling periods, use ANOVA.

11. References

Cook, C. Wayne and James Stubbendieck, 1986. Range Research: Basic Problems
and Techniques. Society .for Range Management. Denver, CO.

Laycock, W.A. 1987. Setting Objectives and Picking Appropriate Methods for
Monitoring Vegetation on Rangelands. Rangeland Monitoring Workshop
Proceedings. U.S. Department of Interior. Bureau of Land Management.
Golden, CO.

Pechanec, J.F. and G.D. Pickford. 1937. A weight-estimate method for the deter-
mination of range or pasture production. J. Amer. Soc. Agron, 29:894-904.

Riser, Paul G. 1984. Methods for Inventory and Monitoring of Vegetation, Litter,
and Soil Surface Condition. Developing Strategies for Rangeland Monitoring.
National Research Council National Academy of Sciences.

USDA, Soil Conservation Service. 1976, National Range Handbook. 154 p.

USDI, Bureau of Land Management. 1984 (rev. 1990). National Range Handbook
4410-1. Washington D. C.

Van Dyne, George M., W.G. Vogel, and H.G. Fisser. 1963. Influence of small plot
size and shape on range herbage production estimates. Ecology 44:746-759.



METHODS—Dry Weight Rank

(see Section II.D). Study sites should be located within a single plant community
within a single ecological site. Transects and sampling points need to be randomly
located within the critical or key areas (see Section III).

b Pilot Studies Collect data on several pilot studies to determine the number of
samples (transects or observation points) and the number and size of quadrats
needed to collect a statistically valid sample (see Section III.B.8).

c Selecting Quadrat Size Adapt the size and shape of quadrats to the vegetation
community to be sampled.

(1) Select a plot size on the premise that most plots should contain three
species.

(2) Determine the proper size quadrat to use by doing preliminary sampling
with different size frames (see Illustration 6).

(3) Use the same size quadrat throughout a study and for rereading the study.
If frequencies approach the extremes of either 0 or 100 percent, it may be
necessary to change the quadrat size.

d Number of Studies At least one Dry Weight Rank study should be established
on each study site, depending on the objectives; establish more if needed (see
Sections II.D and III.B). Evaluate the rangeland plant communities where
studies will be located and determine the number of transects and quadrats
needed. The purpose is to collect the best possible sample for the greatest
number of species in any plant community.

e Study Layout The Dry Weight Rank data can be collected using the baseline,
macroplot, or linear study designs described in Section III.A.2 beginning on
page 8. The linear technique is the one most often used.

f Reference Post or Point Permanently mark the location of each study with a
reference post and a study location stake (see beginning of Section III).

g Study Identification Number studies for proper identification to ensure that
the data collected can be positively associated with specific sites on the ground
(see Appendix B).

h Study Documentation Document pertinent information concerning the study
on the Study Location and Documentation Data form (see beginning of Section
Ill and Appendix A).

. Taking Photographs The directions for establishing photo plots and for taking
close-up and general view photographs are given in Section V.A.

. Sampling Process In addition to collecting the specific study data, general
observations should be made of the study sites (see Section II.F).

Determine the transect bearing and select a prominent distant landmark such as a
peak, rocky point, etc., that can be used as the transect bearing point.



S

sample: a set of sampling units, as opposed to a single measurement.

sampling unit: units on which observations are made. They could be a finite point, plots or
quadrats, distance measures, a weight unit, or a transect.

savanna: a grassland with scattered trees, whether as individuals or clumps; often a
transitional type between true grassland and forest.

seral community: one of a series of biotic communities that follow one another in time on
any given area. Seral community is synonymous with successional community.

seral stage: the developmental stages of an ecological succession; synonymous with
successional stage.

shrub: a plant that has persistent woody stems and a relatively low growth habit, and that
generally produces several basal shoots instead of a single bole. It differs from a tree by its
low stature—less than 5 meters (16 feet)—and nonarborescent form.

shrubland: land on which the vegetation is dominated by shrubs. Nonforested lands are
classified as shrubland if shrubs provide more than 20 percent of the canopy cover, ex-
cluding trees. Lands not presently shrubland that were originally or could become
shrubland through natural succession may be classified as potential natural shrubland.

special status plant: a species that is either Federally listed as threatened or endangered,
officially proposed (or a candidate) for Federal listing as threatened or endangered, State
listed as threatened or endangered, or listed by a BLM State Director as sensitive.

stone: descriptive term applied to rock fragment ground cover where the longest dimension
is greater than 10 inches.

stratification: subdividing an area into units which are, more or less, internally homogeneous
with respect to the (those) characteristic(s) of interest.

succession: the orderly process of community change; it is the sequence of communities
that replace one another in a given area.

successional community: (See seral community.)
successional stage: (See seral stage.)

T

tree: a woody perennial, usually single-stemmed plant that has a definite crown shape and
characteristically reaches a mature height of at least 5 meters (16 feet). Some plants, such
as oaks (Quercus spp.), may grow as either trees or shrubs.

trend: the direction of change in ecological status or in resource value ratings observed over
time. Trend in ecological status is described as “toward” or “away from” the potential
natural community or as “not apparent.” Appropriate terms are used to describe trends in



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Cover Data

Page_4 of _4_

Study Number Rea Feather #2

Date 7/28/95 | ExaminerJosh Gibson

Pasture /

Allotment Name & Number
Red feather 473

Study Location Zise wiles sours of | Number of Points
Heakpuarters Well on west
Side of r0oaxk

S00

Ground-Level Cover

Category ene L Litter G one) S Pers Vegetation | Total
Dot . .
Count vae Das . & T: . 3/
Total
Hits 9 /2 6 2 6/ /00
% Cover 7 2 16 2 é/ /00
Basal and Canopy/Foliar Cover
Bsl or Grnd-Lev Level 1 Level 2 Level 3 Dot Count Total Hits
4 Bocu Bw: 12
G BOGR 2 D Cuunre 7 |* !
BOGR2 Junip Re 20
G Bocy _ os Y
SIHY : 2
L ERIOG : z
6 srHy RHTR __ : 2
B VIGLIT 2 2
G ZL WGUT as Y
B Bocu __ : zZ
B Bowl 2 2” 3
Lh BOGR 2 Bocu Py 2
Bocu L : 2
OPUNT : /
BOGR 2 Bocy : 2
|
Total 6/

Notes (use other side or another page)

Mlustration 13



H. Cover Board Method

1.

General Description The Cover Board method uses a profile board or density board
to estimate the vertical area of a board covered by vegetation from a specified distance
away. This technique is designed to evaluate changes in the vegetation structure over
time. Quantifying the vegetation structure for statistical comparison was described by
Nudds (1977). The following vegetation attributes are monitored using this method:

¢ Vertical cover
¢ Structure

It is important to establish a photo plot (see Section V.A) and take both close-up
and general view photographs. This allows the portrayal of resource values and
conditions and furnishes visual evidence of vegetation and soil changes over time.

. Areas of Use This method is applicable to a wide variety of vegetation types. It should

be used with those that show potential for changes, such as woody riparian vegetation.

. Advantages and Limitations The Cover Board technique is a fast and easily dupli-

cated procedure. The size of the board can be modified to meet the purpose of the study.

Equipment The following equipment is needed (see also the equipment listed in
Section V.A, page 31, for the establishment of the photo plot):

Study Location and Documentation Data form (Appendix A)
Cover Board Method forms (see Illustrations 18 and 19)

Cover board (see Illustration 20)

One stake: 3/4- or 1-inch angle iron not less than 16 inches long
Hammer

Permanent yellow or orange spray paint

Compass

Steel post and driver

eececeeo eee

Training The accuracy of the data depends on the training and ability of the
examiners. They must receive adequate and consistent training in laying out
transects. A minimum of training is needed to make sure the examiners under-
stand how to position the cover board and estimate percent cover. Examiners
must also be able to identify plant species if estimates are to be made be species.

Establishing Studies Careful establishment of studies is a critical element in
obtaining meaningful data (see Section III).

a Site Selection The most important factor in obtaining usable data is selecting
representative areas (critical or key areas) in which to run the study (see Section
ILD). Study sites should be located within a single plant community within a
single ecological site. Transects and sampling points need to be randomly
located within the critical or key areas (see Section III).

b Pilot Studies Collect data on several pilot studies to determine the number of
samples (transects or observation points) and the number and size of quadrats
needed to collect a statistically valid sample (see Section III.B.8).



. Calculations Make the calculations and record the results in the appropriate
columns on the Frequency form (see Illustration 4).

a

Nested Plot Method Collect frequency data for all plant species. For
uniformity in recording data, the four nested plots in a quadrat are numbered
from 1 through 4, with the largest plot size corresponding with the higher
number. Each time the quadrat frame is placed on the ground, determine the
smallest size plot each species occurs in and record the plot number for that
quadrat on the Nested Frequency form (Illustration 5).

Cover Calculate the percent cover for each cover category by dividing the
number of hits for each category by the total number of hits for all categories,
including hits on vegetation, and multiplying the value by 100. The total of the
percent cover for all cover categories equals 100 percent. Additional informa-
tion on calculating ground cover, canopy cover, and basal cover can be found in
Section F.9 on page 73.

Frequency: Single Plot On the Frequency form, Illustration 4, total the
frequency hits by species, Calculate the percent frequency for each plant
species by dividing the total number of hits for that species by the total number
of quadrats sampled along the transect and multiplying the value by 100.
Record the percent frequency on the form.

Frequency: Nested Plot Percent frequency by species can be calculated for
each transect and/or for the total of all transects.

()

(2)

METHODS—Frequency

Compiling data Determine the number of occurrences for each species for
each plot size.

(a) Count the number of occurrences of a species in plot 1 and record the
value in the Hits portion of column 1 in the Frequency Summary
portion of the Nested Frequency form (see Illustration 5).

(6) Count the number of occurrences of the same species in plot 2 and
add this number to the number recorded for plot 1. Record this total
in the Hits portion of column 2.

(c) Count the number of occurrences of the same species in plot 3 and
add this number to the number recorded for plot 2. Record this total
in the Hits portion of column 3.

(d) Count the number of occurrences of the same species in plot 4 and
add this number to the number recorded for plot 3. Record this total
in the Hits portion of column 4.

Frequency for each transect Calculate the percent frequency of a plant
species by plot size for a transect by dividing the number of occurrences by
the number of quadrats sampled and multiplying the value by 100. Record
in the “% Freq” section of the Frequency Summary portion.



Robel Pole

Page ——of —_

Study Number

Date

Examiner

Allotment Name & Number

Pasture

Sampling Interval

Study Location

Transect

#41

#

Station

vO

vO

VO

vo

vO

vo

VO

vO

1

elNi|ola}laAlolnr

10

11

12

13

14

15

16

17

18

19

20

24

22

23

24

25

Total

Grand
Total

Average

illustration 25

127



METHODS—Double Weight Sampling

Weight Estimate Quadrat

Record weights
of all plants within
the vertical projection
of the quadrat
even though the
base is notwithin |

vy
i iin

1
i) 1
I

Tr i)
the quadrat. I it |
' I 1 1
| 1 ' 1
/ | i
at i! '
wy i | 1
4a it '
aff | i | !
van 1

Vo 1
ats} 1 i
Nhe 1

A nl ! (
Won i ||
NAG Mo Ly i
VY hie | I
INE Nite My i
Ups tt 1
i , | 1
it H

I
i)
1
1
i}
i}
1
i]
i]
i)
{

Do not record weights of portions of plants outside the vertical
projection of the quadrat even though the base is within the quadrat

Illustration 23 } 111 |



METHODS—Comparative Yield

Table 6
(# of plots x size = total area)
(10x096 = 9.6 ft?) multiply grams times 100 = pounds per acre
(10x192 = 19.2 ft?) multiply grams times 50 = pounds per acre
(10x2.40 = 24.0 ft?) multiply grams times 40 = pounds per acre
(10x4.80 = 48.0 ft?) multiply grams times 20 = pounds per acre
(10x9.60 = 96.0 ft?) multiply grams times 10 = pounds per acre
(10x 96.0 = 960.0 ft?) multiply grams times 1 = pounds per acre

To convert to kilograms per hectare, first determine the number of quadrats in a
hectare by dividing the number of square meters in a hectare (10,000m2) by the
total area (in square meters) of the quadrat. Then divide the number of quadrats
in a hectare by 1,000 to arrive at the conversion factor used to convert grams per
quadrat into kilograms per hectare.

For example, if the quadrat size is 40 X 40 centimeters (0.4 X 0.4 meters), then
the quadrat area would be 0.4 multiplied by 0.4, or .16m2. The number of quad-
rats in a hectare is calculated by dividing 10,000 by .16, which works out to
62,500 quadrats per acre. Dividing this number by 1,000 results in the conversion
factor, which is 62.5. The final step is to multiply the average yield per quadrat
obtained from the final equation above by 62.5 to arrive at kilograms per hectare.

10. Data Analysis For trend analysis, permanent sampling units are suggested. If
permanent transects are monitored, use the appropriate paired analysis technique.
If the transects are not permanently marked, use the appropriate nonpaired test.
When comparing more than two sampling periods, use repeated measures ANOVA.

11. References

Despain, D.W., P.R. Ogden, and E.L. Smith. 1991. Plant frequency sampling for
monitoring rangelands. In: G.B. Ruyle, ed. Some Methods for Monitoring
Rangelands and other Natural Area Vegetation. Extension Report 9043,
University of Arizona, College of Agriculture, Tucson, AZ.



8. Sampling Process In addition to collecting the specific studies data, general

10.

11.

12.

observations should be made of the study sites (see Section II.F).
This technique is most effectively accomplished with two individuals.

a Determine the transect bearing and select a prominent distant landmark such as
a peak, rocky point, etc., that can be used as the transect bearing point.

b Start a transect by randomly selecting a point along the transect. Two Visual
Obstruction (VO) measurements are taken at each observation point from
opposite directions along the contour. One examiner holds the Robel pole at
the observation point, while the second examiner holds the end of the cord
perpendicular to the transect. The Visual Observation (VO) measurement is
made by determining the highest 1-inch band totally or partially visible and
recording the height on the Robel Pole form (Illustration 25).

c Continue the transect by taking readings at specified intervals along the transect
bearing until the transect is complete. The distance between observation points
can be increased to expand the area sampled.

Calculations

a Total the visual obstruction measurements on the Robel Pole form (Illustration 25)
for both readings at each observation point and record at the bottom of the
form. Add these two totals and divide by the total number of readings. This
will yield the average visual obstruction.

b The average height or visual obstruction value can be used to determine the
cover class.

Production Data from the Robel pole method can be correlated to forage
production or standing crop. This correlation can be established by clipping and
weighing the standing crop within a specified quadrat frame directly in front of the
Robel pole after the readings are made. Depending on the vegetation community
approximately 25 quadrat frames need to be clipped to get a good correlation
between visual obstruction readings and standing crop. Note that this will be an
estimate of standing plant biomass. It will include not only this year’s production,
but also herbage remaining from prior years. After the correlation is made be-
tween the pole readings and production, the pole can then be used to quickly
estimate production across the entire plant community.

Data Interpretation The average Visual Obstruction value can be used to
determine success at meeting objectives. The average Visual Obstruction value
determined from the Robel Method form is compared with the cover classes and
the residue levels to determine if overall objectives have been meet.

Data Analysis This technique involves destructive sampling (clipped plots), so
permanent transects or quadrats are not recommended. Since the transects are not
permanently marked, use the appropriate nonpaired test. When comparing more
than two sampling periods, use ANOVA.



APPENDIX A

Study Location and Documentation Data Form



APPENDIX B—STUDY AND PHOTOGRAPH
IDENTIFICATION

A. Numbering Studies studies should be numbered to assure positive identifi-
cation. These numbers can also be used to identify photographs. Following are three
alternative schemes for numbering studies:

1. Numbering Scheme 1. Consecutive numbers may be assigned to studies within
an allotment. For example, Mooncreek #] and Mooncreek #2 would be studies
Number 1 and 2 within the Mooncreek Allotment. A disadvantage to using the names
of allotments in a numbering scheme is that these names can, and often do, change.

2. Numbering Scheme 2. Studies may be numbered based on their location
within a township, range, and section. A 10-character number can be assigned in
the following manner:

a The first three characters are the township (03S), the second three are the range
(27W), the next two are the section (08), and the last two are simply a series number
(01) assigned to a study based on the number of studies located within a section.

b The numbers for studies located in Section 8 would be 03S-27W-08-01, 03S-
27W-08-02, and so forth.

c Depending on the local situation, this scheme can be modified by adding characters
to the code where there are fractional townships or ranges, where there are more
than 99 sections/tracts within a township, and/or where there is more than one
public land survey principal meridian and baseline within the area of jurisdiction.

3. Numbering Scheme 3. Studies may be numbered based on their location
relative to the initial point of survey (principal meridian and baseline governing
public land survey).

a Under this scheme, the first character is a letter assigned to a principal meridian
and baseline quadrant. Using the initial point of the survey as the center point,
the northeast quadrant (townships located to the north and east of the initial
point) is coded “A’. The northwest, southwest, and southeast quadrants are
coded “B”, “C”, and “D”, respectively. For example:

ee Salt Lake Meridian

(initial point)

—__ ee - Oo eooOTOO/


TABLE OF CONTENTS

IT. PREFACE uoccscccccccseesesessssesessesissessseseseesssnessastessesessssrseesssssassisssesrssissesisieersnsarsesecene i

II. INTRODUCTION

A. Terms and Concepts .
Techniques Not Addresse
Guidelines...
Location of Study Sites .
Key Species
General Observations
Coordination ...........
. Electronic Data Recorders
Reference Areas

STAM OOW
DADUAWWNHE

Ill. STUDY DESIGN AND ANALYSIS .
A. Planning the Study........
B. Statistical Considerations .
C. Other Important Considerations.

IV. ATTRIBUTES
Frequency
Cover ..
Density .
Production
Structure ..
Composition

ETHODS ..
- Photographs .
Frequency Methods ..
Dry Weight Rank Metho
Daubenmire Method ....
Line Intercept Metho:
Step-Point Method...
Point-Intercept Method

. Cover Board Method
Density Method...
Double-Weight Sampling
Harvest Method ............
Comparative Yield Metho

. Visual Obstruction Method - Robel Pol an
Other Methods vio. ccccesecseeses reese sssneusseessesseseesesnesnseseeesssesserseesseeeeees

VI. GLOSSARY OF TERMS o....ccccccccsssseseessesesesnsssenesesseesessstesseesssessseneseatensaseneasaeees 131
VIL. REFERENCES .....cccccssecseseseesesessesssecesesneusssssucasssssnssseneseestasesessesessarsessunasseseseraness 139

APPENDIXES
Appendix A Study Location and Documentation Data Form
Appendix B Study and Photograph Identification
Appendix C Photo Identification Label we
Appendix D Selecting Random Samples (Using Random Number Tables) ........0.0:000 161

OBIAHAWW NNwON

ZECASMLOMBUOEPE Mm OM>



REFERENCES

Mack, R. and D.A. Pyke. 1979. Mapping individual plants with a field portable digitizer.
Ecology 60:459-461.

McDougald, Neil K. and Richard C. Platt. 1976. A method of determining utilization for
wet mountain meadows on the Summit Allotment, Sequoia National Forest, California.
J. Range Manage. 29:497-501.

McQuisten, Richard and Karl A. Gebhardt. 1983. Analytical reliability in the decision
making process—the numbers game. J. Range Manage. 36:126-128.

Meyer, Merle, Fred Batson, and Duane Whitmer. 1982. Helicopter-borne 35mm aerial
photography applications to range and riparian studies. LAFHE RSL Res. Rep. 82-1, Coll.
of Forestry and Agricultural Experiment Station, Univ. of Minn., St. Paul, MN. 80 p.

Meyer, Merle and Phillip Grumstrup. 1978. Operating manual for the 35mm aerial
photography system, 2nd Rev. IAFHE RSL Res. Rep. 78-1, Coll. of Forestry, Univ. of
Minn., St. Paul, MN. 62 p.

Milne, A. 1959. The centric systematic area-sample treated as a random sample. Biometrics
15:270-297.

Morris, Meredith J. 1973. Estimating understory plant cover with rated microplots. U.S.
Dept. of Agr., For. Ser., Rocky Mtn. For. and Range Exp. Sta., Ft. Collins, CO., Research
Paper RM-104. 12 p.

Morrison, R.G. and G.A. Yarranton. 1970. An instrument for Rapid and Precise Point-
sampling of Vegetation. Can. J. Bot. 48: 293-297.

Mueggler, W.F. 1976. Number of plots required for measuring productivity of mountain
grasslands in Montana. U.S. Dept. of Agr., For. Ser., Res. Note INT-207. Intermountain
For. and Range Exp. Sta., Ogden, UT. 6 p.

Mueller-Dombois, Dieter and Heinz Ellenberg. 1974. Aims and methods of vegetation
ecology. John Wiley & Sons, New York, NY. 547p.

Murphy, Alfred H. 1970. Predicted forage yield based on fall precipitation in California
annual grasslands. J. Range Manage. 23:363-365.

Myers, Wayne L. and Ronald L. Shelton. 1980. Survey methods for ecosystem management.
A Wiley-Interscience Publication, John Wiley & Sons, New York, NY. 403 p.

National Academy of Sciences/National Research Council. 1962. Basic problems and
techniques in range research. NAS/NRC Publ. 890. 341 p.

National Wildlife Federation. 1978. Application of remote sensing data to wildlife
management. Sioux Falls, $.D., Pecora IV, Proceedings of the Symposium, National
Wildlife Federation Scientific and Tech. Series 3. 397 p.

Nevada Range Studies Task Group. 1984. Nevada Rangeland Monitoring Handbook. Bureau
of Land Management Nevada State Office, Reno, NV. 50p.

143



METHODS—Double Weight Sampling

g Study and Documentation Document pertinent information concerning the
study on the Study Location and Documentation Data form (see beginning of
Section III and Appendix A).

@)

(2)

(3)

(4)

Q)

(2)
(3)
(4)
(5)
(6)

()

(2)
(3)

7. Taking Photographs The directions for establishing photo plots and for taking
close-up and general view photographs are given in Section V.A.

8. Weight Units Double sampling requires the establishment of a weight unit for
each species occurring in the area to be sampled. All weight units are based on
current year’s growth.

a Procedures For Establishing Weight Units:

Decide on a weight unit that is appropriate for each species. A weight unit
could be an entire plant, a group of plants, or an easily identifiable portion
of a plant, and can be measured in either pounds or grams.

Visually select a representative weight unit.

Harvest and weigh the plant material to determine the actual weight of the
weight unit.

Maintain proficiency in estimating by periodically harvesting and weighing
to check estimates of production.

b Estimating Production of a Single Quadrat:

Estimate production by counting the weight units of each species in the
quadrat.

Convert weight units for each species to grams or pounds.

Harvest and weigh each species to check estimate of production.
Repeat the process until proficiency is attained.

Periodically repeat the process to maintain proficiency in estimating.

Keep the harvested material, when necessary, for air-drying and weighing to
convert from green weights to air-dry weights.

c Alternate Method of Establishing Weight Units:

Decide on a weight unit that is appropriate for each species. A weight unit
could be an entire plant, a group of plants, or an easily identifiable portion
of a plant, and can be measured in either pounds or grams.

Visually select a representative weight unit.

Instead of weighing the material, save it by securing it with rubber bands so
portions are not lost.



METHODS—Line Intercept _

E. Line Intercept Method
1.

General Description The Line Intercept method consists of horizontal, linear
measurements of plant intercepts along the course of a line (tape). It is designed
for measuring grass or grass-like plants, forbs, shrubs, and trees. The following
vegetation attributes are monitored with this method:

¢ Foliar and basal cover
* Composition (by cover)

It is important to establish a photo plot (see Section V.A) and take both close-up
and general view photographs. This allows the portrayal of resource values and
conditions and furnishes visual evidence of vegetation and soil changes over time.

. Areas of Use This method is ideally suited for semiarid bunchgrass-shrub

vegetation types.

. Advantages and Limitations The Line Intercept method is best suited

where the boundaries of plant growth are relatively easy to determine. It can be
adapted to sampling varying densities and types of vegetation. It is not well
adapted, however, for estimating cover on single-stemmed species, dense grassland
situations, litter, or gravel less than 1/2 inch in diameter. It is best suited to esti-
mating cover on shrubs.

. Equipment The following equipment is needed (see also the equipment listed in

Section V.A, page 31, for the establishment of the photo plot):

Study Location and Documentation Data form (see Appendix A)

Line Intercept form (see Illustration 12)

Hammer

Permanent yellow or orange spray paint

Two stakes: 3/4 - or l-inch angle iron not less than 16 inches long.

Two tapes: 100- or 200-foot, delineated in tenths and hundredths, or a metric
tape of the desired length

¢ Compass

© Steel post and driver

eoceeee

Training A minimum of training is needed to make sure the examiners under-
stand how to lay out baselines and transects and how to make the measurements.
The examiner must also be able to identify the plant species.

. Establishing Studies Careful establishment of studies is a critical element in

obtaining meaningful data (see Section III).

a Site Selection The most important factor in obtaining usable data is selecting
representative areas (critical or key areas) in which to run the study (see
Section II.D). Study sites should be located within a single plant community
within a single ecological site. Transects and sampling points need to be randomly
located within the critical or key areas (see Section II).



METHODS—Dry Weight Rank a

C. Dry Weight Rank Method
1.

General Description The Dry Weight Rank method is used to determine
species composition. It consists of observing various quadrats and ranking the
three species which contribute the most weight in the quadrat.

It is important to establish a photo plot (see Section V.A) and take both close-up
and general view photographs. This allows the portrayal of resource values and
conditions and furnishes visual evidence of vegetation and soil changes over time.

Areas of Use This method has been tested in a wide variety of vegetation types
and is generally considered suitable for grassland/small shrubs types or understory
communities of large shrub or tree communities. It does not work well on large
shrubs and trees.

. Advantages and Limitations

a One advantage of the Dry Weight Rank Method is that a large number of
samples can be obtained very quickly. Another advantage is that it deals with
estimates of production, which allows for better interpretation of the data to
make management decisions. It can be done in conjunction with frequency,
canopy cover, or comparative yield methods. Because it is easier to rank the top
three species in a quadrat, there is less observer bias.

b The limitation with this technique is that, by itself, it will not give a reliable
estimate of plant standing crop, and it assumes there are few empty quadrats.
In many large shrub or sparse desert communities, a high percentage of quadrats
are empty or have only one species present. The quadrat size required to
address these concerns is often impractical.

Equipment The following equipment is needed (see also the equipment listed in
Section V.A, page 31, for the establishment of the photo plot):

Study Location and Documentation Data form (see Appendix A)
Dry Weight Rank form (see Illustration 8)

Quadrat frame

Hammer

Permanent yellow or orange spray paint

One stake: 3/4 - or 1-inch angle iron not less than 16 inches long
Compass

Steel post and driver

eoeoee eee

. Training Examiners must be able to identify the plants. Experience in weight

estimate is desirable, but those with experience must break the habit of assigning
percentages and just rank the species, as well as not debating over the close calls.
The large number of sampling units tends to reduce the problems with close calls.

. Establishing Studies

a Site Selection The most important factor in obtaining usable data is select-
ing representative areas (critical or key areas) in which to run the study



METHODS—Density

Salzer, D. 1994. An introduction to sampling and sampling design for vegetation
monitoring. Unpublished papers prepared for Bureau of Land Management
Training Course 1730-5. BLM Training Center, Phoenix, Arizona. These pa-
pers, together with material prepared for a class exercise, present the basic
concepts of the Density Method. The Density Method is in rather widespread
use in The Nature Conservancy and, increasingly, by the Bureau of Land
Management and the Forest Service, particularly as a means of estimating
numbers of special status plant species.



ATTRIBUTES

Frequency is the number of times a species is present in a given number of sampling
units. It is usually expressed as a percentage.

2. Advantages and Limitations

a Frequency is highly influenced by the size and shape of the quadrats used.
Quadrats or nested quadrats are the most common measurement used; how-
ever, point sampling and step point methods have also been used to estimate
frequency. The size and shape of a quadrat needed to adequately determine
frequency depends on the distribution, number, and size of the plant species.

b To determine change, the frequency of a species must generally be at least 20%
and no greater than 80%. Frequency comparisons must be made with quadrats
of the same size and shape. While change can be detected with frequency, the
extent to which the vegetation community has changed cannot be determined.

c High repeatability is obtainable.

d Frequency is highly sensitive to changes resulting from seedling establishment.
Seedlings present one year may not be persistent the following year. This
situation is problematic if data is collected only every few years. It is less of a
problem if seedlings are recorded separately.

e Frequency is also very sensitive to changes in pattern of distribution in the
sampled area.

f Rooted frequency data is less sensitive to fluctuations in climatic and biotic
influences.

g Interpretation of changes in frequency is difficult because of the inability to
determine the vegetation attribute that changed. Frequency cannot tell which
of three parameters has changed: canopy cover, density, or pattern of distribution.

3. Appropriate Use of Frequency for Rangeland Monitoring If the pri-
mary reason for collecting frequency data is to demonstrate that a change in
vegetation has occurred, then on most sites the frequency method is capable of
accomplishing the task with statistical evidence more rapidly and at less cost than
any other method that is currently available (Hironaka 1985).

Frequency should not be the only data collected if time and money are available.
Additional information on ground cover, plant cover, and other vegetation and site
data would contribute to a better understanding of the changes that have occurred
(Hironaka 1985).

West (1985) noted the following limitations: “Because of the greater risk of
misjudging a downward than upward trend, frequency may provide the easiest
early warning of undesirable changes in key or indicator species. However, because
frequency data are so dependent on quadrat size and sensitive to non-random
dispersion patterns that prevail on rangelands, managers are fooling themselves if
they calculate percentage composition from frequency data and try to compare
different sites at the same time or the same site over time in terms of total species



STUDY DESIGN AND ANALYSIS

4L

35h

N Plants Average
1,00
1.50
1.00
3.00
3.40
4.00
3.57
3.13
3.67
3.40
3.09
2.83
2.92
3.00
2.93
275
2.82
2.67
2.89
3.00
3.00
291
3.17
3.33
3.24
3.15
3.33
3.46
3.41
3.60
3.52
3.69
3.76
3.85
3.91
3.83
3.89
3.87
3.79
3.73

Example of a sequential sampling graph

Average 2

SD 32

QSe-LLILILIII III Pitt 40
5 0 15 20 25 30 35 40

3.85,
3.83,
3.81
3.75
3.82
3.80
3.81
3.92
3.92
3.84

45 50 4!
Sample size ie

8
CR OR ON 20004 = OOH OVO OF ONVOE=AVOAOUVOR ONE ROOK DOAN MOONS

Figure 5. Example of a sequential sampling graph. The running average and standard deviation are plotted
for sample sizes of n=5 up to n=50. Sampling was conducted in an area of 50 m x 100 m with a quadrat size
of 1mx5TMm. Actual values are shown on the right.

9. Sample size determination An adequate sample is vital to the success of any
monitoring effort. Adequacy relates to the ability of the observer to evaluate
whether the management objective has been achieved. It makes little sense, for
example, to set a management objective of increasing the density of a rare plant
species by 20 percent when the monitoring design and sample size is unlikely to
detect changes in density of less than 50 percent. The question of sample size
determination is addressed in much more detail in the Interagency Technical
Reference, Planning for Monitoring.

Formulas for calculating sample sizes are given in the Technical Reference, Plan-
ning for Monitoring. Because these formulas are rather unwieldy, you may choose
to use a computer program. There are several microcomputer programs that will
calculate sample size, most of which are available for reasonable cost. Examples
are the programs DESIGN (by SYSTAT), EXSAMPLE, N, Nsurv, PASS, and

sD

0.50
0.79
3.52
3.15
3.12
3.04
3.05
3.24
3.16

3.12
3.01

SOLO Power Analysis. Goldstein (1989) reviews 13 different computer programs

that can calculate sample sizes. STPLAN Version 4.0, a DOS-based program
developed by Brown et al. (1993), is available as freeware from the following



Herbage Yield Tables for Trees by Height, DBH, or Canopy
Clippers

Paper bags

Kilogram and gram spring-loaded scales with clip
Tree diameter measuring tape

Steel post & driver

Oven for drying vegetation

Air-dry weight conversion tables

Rubber bands

Pin flags

Compass

. Training The accuracy of the data depends on the training and ability of the
examiners. Examiners must be able to identify plant species and determine current
year’s growth.

. Establishing Studies Careful establishment of studies is a critical element in
obtaining meaningful data (see Section III).

a Site Selection The most important factor in obtaining usable data is selecting
representative areas (critical or key areas) in which to run the study (see Section
ILD). Study sites should be located within a single plant community within a
single ecological site. Transects and sampling points need to be randomly
located within the critical or key areas (see Section III).

(1) The number of quadrats selected depends on the purpose for which the
estimates are to be used, uniformity of the vegetation, and other factors
(see Section III.B for Statistical Considerations).

(2) The size and shape of quadrats must be adapted to the vegetation
community to be sampled (see Section III.B.6).

b Pilot Studies Collect data on several pilot studies to determine the number of
samples (transects or observation points) and the number and size of quadrats
needed to collect a statistically valid sample (see Section III.B.8).

c Study Layout Production data can be collected using either the baseline,
macroplot or linear study designs described in Section III.A.2 beginning on
page 8. The linear technique is the one most often used.

d Number of Transects Establish the minimum number of transects to achieve the
desired level of precision for the key species in each study site (see Section IIIB).

e Reference Post or Point Permanently mark the location of each study with a
reference post and a study location stake (see beginning of Section III).

f Study Identification Number studies for proper identification to ensure that
the data collected can be positively associated with specific sites on the ground
(see Appendix B).

METHODS—Double Weight Sampling





Table of Random Digits (Zar 1984)

APPENDIX D

00-04 | 05-09 | 10-14 | 15-19 | 20-24 | 25-29 | 30-34 | 35-39 | 40-44 | 45-49
00 22808 | 04391 | 45529 | 53968 | 57136 | 98228 | 85485 | 13801 | 68194 | S6382
01 49305 | 36965 | 44849 | 64987 | 59501 | 35141 | 50159 | 57369 | 76913 | 75739
02 81934 | 19920 | 73316 | 69243 | 69605 | 17022 | 53264 | 83417 | 55193 | 92929
03 10840 | 13508 | 48120 | 22467 | 54505 | 70536 | 91206 | 81038 | 22418 | 34800
04 99555 | 73289 | S9605 | 3710S | 24621 | 44100 | 72832 | 12268 | 97089 | 68112
0s 32677 | 45709 | 62337 | 35132 | 45128 | 96761 | 08745 | 53388 | 98353 | 46724
06 0940] | 75407 | 27704 | 11569 | 52842 | 83543 | 44750 | 03177 | SOS11 | 15301
07 73424 | 31711 | 65519 | 74069 | 56744 | 40864 | 75315 | 89066 | 96563 | 75142
08 37075 | 81378 | 59472 | 71858 | 86903 | 66860 | 03757 | 32723 | 54273 | 45477
09 02060 | 37158 | 55244 | 44812 | 45369 | 78939 | 08048 | 28036 | 40946 | 03898
10 94719 | 43565 | 40028 | 79866 | 43137 | 28063 | 52513 | 66405 | 71511 | 66135
11 70234 | 48272 | 59621 | 88778 | 16536 | 36505 | 41724 | 24776 | 63971 | 01685
12 07972 | 71752 | 92745 | 86465 | 01845 } 27416 | 50519 | 48458 | 68460 | 63113
13 $8521 | 64882 | 26993 | 48104 | 61307 | 73933 | 17214 | 44827 | 88306 | 78177
14 32580 | 45202 | 21148 | 09684 | 39411 | 04892 | 02055 | 75276 | 51831 | 85686
1S 88796 | 30829 | 35009 | 22695 | 23694 | 11220 | 71006 | 26720 | 39476 | 60538
16 31525 | 82746 | 78935 | 82980 | 61236 }| 28940 | 96341 | 13790 | 66247 | 33839
W7 02747 | 35989 | 70387 | 89571 | 34570 | 17002 | 79223 | 96817 | 31681 | 15207
18 46651 | 28987 | 20525 | 61347 | 63981 | 41085 | 67412 | 29053 | 00724 | 14841
19 43598 | 14436 | 33521 | 55637 | 39789 | 26560 | 66404 | 71802 | 18763 | 80560
20 30596 | 92319 | 11474 | 64546 | 60030 | 73795 | 60809 | 24016 | 29166 | 36059
21 56198 | 64370 | 85771 | 62633 | 78240 | 05766 | 32419 | 35769 | 14057 | 80674
22 68266 | 67544 | 06464 | 84956 | 18431 | 04015 | 89049 | 15098 | 12018 | 89338
23 31107 | 28597 | 65102 | 75599 | 17496 | 87590 | 68848 | 33021 | 69855 | 54015
24 37555 | 05069 | 38680 | 87274 | 55152 | 21792 | 77219 | 48732 | 03377 | 01160
25 90463 | 27249 | 43845 | 94391 | 12145 | 36882 | 48906 | 52336 | 00780 | 74407
26 99189 | 8873] } 93531 | 52638 | 54989 | 04237 | 32978 | 59902 | 05463 | 09245
27 37631 | 74016 | 89072 | 59598 | 55356 | 27346 | 80856 | 80875 | 52850 | 36548
28 73829 | 21651 | 50141 | 76142 | 72303 | 06694 | 61697 | 76662 | 23745 | 96282
29 15634 | 89428 | 47090 | 12094 | 42134 | 62301 | 87236 | 90110 | 53463 | 46969
30 00571 | 45172 | 78532 | 63863 | 98597 | 15742 | 41967 | 11821 | 91389 | 07476
31 83374 | 10184 | 56384 | 27050 | 77700 | 13875 | 96607 | 76479 | 80535 | 17454
32 78666 | 85645 | 13181 | 08700 | 08289 | 62956 | 54439 | 39150 | 95690 | 18555
33 47890 | 88197 | 21358 | 65254 | 35917 | 54035 | 83028 | 84636 | 38186 | 50581
34 56238 | 13559 | 79344 | 83198 | 94542 | 35165 | 40188 | 21456 | 67024 | 62771
35 35369 | 32234 | 38129 | 59963 | 99237 | 72648 | 66504 | 99065 | 61161 | 16186
36 42934 | 34578 | 28968 | 74028 | 42164 | 55647 | 76805 | 61023 | 33099 | 48293
37 09010 | 15226 | 43474 | 30174 | 26727 | 39317 | 48508 | 55438 | 85336 | 40762
38 83897 | 90073 | 72941 | 85613 | 85569 | 24183 | 08247 | 15946 | 02957 | 68504
39 82206 | 01230 | 93252 | 89045 | 25141 | 91943 | 75531 | 87420 | 99012 | 80751
40 14175 | 32992 | 49046 | 41272 | 94040 | 44929 | 98531 | 27712 | 05106 | 35242
4l 58968 | 88367 |. 70927 | 74765 | 18635 | 85122 | 27722 | 95388 | 61523 | 91745
42 62601 | 04595 | 76926 | 11007 | 67631 | 64641 | 07994 | 04639 | 39314 | 83126
43 97030 | 71165 | 47032 | 85021 | 65554 | 66774 | 21560 | 04121 | 57297 | 85415
44 89074 | 31587 | 21360 | 41673 | 71192 | 85795 | 82157 | 52928 | 62586 | 02179
45 07806 | 81312 | 81215 }| 99858 | 26762 | 28993 | 74951 | 64680 | 50934 | 32011
46 91540 | 86466 | 13229 | 76624 | 44092 | 96604 | 08590 | 89705 | 03424 | 48033
47 99279 | 27334 | 33804 | 77988 | 93592 | 90708 | 56780 | 70097 | 39907 | 51006
48 63224 | 05074 | 83941 | 25034 | 43516 | 22840 | 35230 | 66048 | 80754 | 46302
49 98351 | 97513 | 27529 | 65419 | 35328 | 19738 | 82366 | 38573 | 50967 | 72754





METHODS—Photographs

c Angle iron stakes are driven into the ground at two diagonal corners of the
frame to permanently mark a photo plot (see Illustration 3). Paint the stakes
with bright-colored permanent spray paint (yellow or orange) to aid in reloca-
tion. Repaint these stakes when subsequent pictures are taken.

d The Photo Identification Label is placed flat on the ground immediately adja-
cent to the photo plot frame (see Appendix C).

e The camera point, or the location from which the close-up picture is taken,
should be on the north side of the photo plot so that repeat pictures can be
taken at any time during the day without casting a shadow across the plot.

f To take the close-up pictures, stand over the photo plot with toes touching the
edge of the frame. Include the photo label in the photograph. Use a 35-mm
camera with a 28-mm wide-angle lens.

g Astep ladder is needed to take close-up pictures of photo plots larger than
3- x 3-foot.

5. General View Pictures General view pictures present a broad view of a study
site. These pictures are often helpful in relocating study sites.

a Ifa linear design is used, general view pictures may be taken from either or both
ends of the transect. The points from which these pictures are taken are deter-
mined at the time the studies are established. Document the location of these
points on the Study Location and Documentation Data form to expedite
relocation (see Appendix A).

b The Photo Identification Label is placed in an upright position so that it will
appear in the foreground of the photograph (see Appendix C).

c To take general view pictures, stand at the selected points arid include the photo
label, a general view of the site, and some sky in the pictures.

d A picture of a study site taken from the nearest road at the time of establishment
of the study facilitates relocation.

6. Photo Points General view photographs taken from a permanent reference
point are often adequate to visually portray dominant landscape vegetation. It is
important that the photo point location be documented in writing and that the
photo include a reference point in the foreground (fencepost, fence line, etc.),
along with a distinct landmark on the skyline. Photographs taken from photo
points should be brought to the field to assist in finding the photo point and to
ensure that the same photograph (bearing, amount of skyline, etc.) is retaken. The
photograph should be taken at roughly the same time each year to assist in inter-
preting changes in vegetation. As always, recording field notes to supplement the
photographs is a good idea.

Photo points are especially well adapted for use by external groups who are
interested in monitoring selected management areas. Photo points require a



METHODS—Harvest

Clippers

Paper bags

Kilogram and gram spring-loaded scales with clip
Tree diameter measuring tape

Steel post and driver

Oven for drying vegetation

Air-dry weight conversion tables

Rubber bands

Compass

. Training The accuracy of the measurement depends on the training and ability
of the examiners. Examiners must be able to identify plant species and determine
current year’s growth.

. Establishing Studies Careful establishment of studies is a critical element in
obtaining meaningful data (see Section III).

a Site Selection The most important factor in obtaining usable data is selecting
representative areas (critical or key areas) in which to run the study (see Section
ILD). Study sites should be located within a single plant community within a
single ecological site. Transects and sampling points need to be randomly
located within the critical or key areas (see Section III).

(1) Select transects at random (see Section III.B. 2).

(2) The number of quadrats selected depends on the purpose for which the
estimates are to be used, uniformity of the vegetation, and other factors
(see Section III.B for Statistical considerations.)

(3) Adapt the size and shape of quadrats to the vegetation community to be
sampled (see Section III.B.6).

b Pilot Studies Collect data on several pilot studies to determine the number of
samples (transects or observation points) and the number and size of quadrats
needed to collect a statistically valid sample (see Section III.B.8).

c Study Layout Production data can be collected using either the baseline,
macroplot, or linear study designs described in Section III.A.2 beginning on
page 8. The linear technique is the one most often used.

d Reference Post or Point Permanently mark the location of each study with a
reference post and a study location stake (see beginning of Section III).

e Study Identification Number studies for proper identification to ensure that
the data collected can be positively associated with specific sites on the ground
(Appendix B).

f Study Documentation Document pertinent information concerning the study
on the Study Location and Documentation Data form (see beginning of Section
Ill and Appendix A).

_



grazable woodland: forestland on which the understory includes, as an integral part of the
forest plant community, plants that can be grazed without detrimental impact to other
forest values.

ground cover: The percentage of material, other than bare ground covering the land sur-

face. It may include live and standing dead vegetation, litter cobble, gravel, stones, and
bedrock. Ground cover plus bare ground would total 100 percent.

H

half shrub: a plant with a woody base whose annually produced stems die each year.

herbaceous: vegetation growth with little or no woody component; nonwoody vegetation
such as graminoids and forbs.

hedging: (1) the appearance of browse plants that have been browsed so as to appear
artificially clipped; or (2) consistent browsing of terminal buds of browse species that
results in excessive lateral branching and a reduction in upward and outward growth.

herbage: the above-ground material of any herbaceous plant (grasses and forbs).
I

interpretation: explaining or telling the meaning of something and presenting it in under-
standable terms.

inventory: the systematic acquisition and analysis of information needed to describe, charac-
terize, or quantify resources for land-use planning and management of the public lands.

K

key area: a relatively small portion of a range selected because of its location, use or grazing
value as a monitoring point for grazing use. It is assumed that key areas, if properly
selected, will reflect the overall acceptability of current grazing management over the
range.

key species: (1) forage species whose use serves as an indicator to the degree of use of
associated species. (2) those species which must, because of their importance, be
considered in the management program.

kind of livestock: species of domestic livestock—cattle, sheep, horses, burros, and goats.

life-form: characteristic form or appearance of a species at maturity, e.g., tree, shrub, herb, etc.

M

monitoring: the orderly collection, analysis, and interpretation of resource data to evaluate
progress toward meeting objectives.

io



METHODS—Daubenmire

single ecological site. Transects and sampling points need to be randomly
located within.the critical or key areas (see Section III).

b Pilot Studies Collect data on several pilot studies to determine the number of

samples (transects or observation points) and the number and size of quadrats
needed to collect a statistically valid sample (see Section III.B.8).

Number of Studies Establish a minimum of one study on each study site;
establish more if needed (see Section II.D and III.B).

Study Layout Data can be collected using the baseline, macroplot, or linear
study designs described in Section III.A.2 beginning on page 8. The linear
technique is the one most often used.

(1) Align a tape (100-, or 200-foot, or metric equivalent) in a straight line by
stretching it between the transect location and the transect bearing stakes.
Do not allow vegetation to deflect the alignment of the tape. A spring and
pulley may be useful to maintain a straight line. The tape should be
aligned as close to the ground as possible.

(2) Drive steel pins almost to the ground surface at the zero point on the tape
and at the end of the transect. A pin may also be driven into the ground at
the midpoint of the transect. (see Figure 4 on page 13)

Reference Post or Point Permanently mark the location of each study with a
reference post and a study location stake (see beginning of Section III).

Study Identification Number studies for proper identification to ensure that
the data collected can be positively associated with specific sites on the ground
(See Appendix B).

Study Documentation Document pertinent information concerning the study
on the Study Location and Documentation Data form (see beginning of Section III
and Appendix A).

7. Taking Photographs The directions for establishing photo plots and for taking
close-up and general view photographs are given in Section V.A.

8. Sampling Process In addition to collecting the specific studies data, general
observations should be made of the study sites (see Section II.F).

a Cover Classes This method uses six separate cover classes (Daubenmire 1959).

The cover classes are:

Cover Class Range of Coverage Midpoint of Range
1 0 - 5% 2.5%
2 5 - 25% 15.0%
3 25 - 50% 37.5%
4 50 - 75% 62.5%
5 75 - 95% 85.0%
6 95 - 100% 97.5%



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Illustration 22



METHODS—Step Poi

measures ANOVA. If the transects are not permanently marked, use the
appropriate nonpaired test.

b When points are the sampling units: To determine if the change between
sampling periods is significant, use Chi Square analysis of variance for cover data.

11. References

Bonham, C.D. 1989. Measurements for Terrestrial Vegetation, John Wiley and
Sons, New York, NY. 338 p.

Evans, Raymond A. and R. Merton Love. 1957. The step-point method of sam-
pling—a practical tool in range research. J. Range Manage. 10:208-212.

Goodall, DW. 1952. Some considerations in the use of point quadrats for the
analysis of vegetation. Aust. J. Sci. Res., Series B 5:1-41

Mueller-Dombois, Dieter and Heinz Ellenberg. 1974. Aims and methods of
vegetation ecology. John Wiley & Sons, New York, NY. 547 p.

USDI, Bureau of Land Management. 1985. Rangeland monitoring - Trend studies
TR4400-4.



ATTRIBUTES

2. Advantages and Limitations

a

a

Ground cover is most often used to determine the watershed stability of the
site, but comparisons between sites are difficult to interpret because of the
different potentials associated with each ecological site.

Vegetation cover is a component of ground cover and is often sensitive to
climatic fluctuations that can cause errors in interpretation. Canopy cover and
foliar cover are components of vegetation cover and are the most sensitive to
climatic and biotic factors. This is particularly true with herbaceous vegetation.

Overlapping canopy cover often creates problems, particularly in mixed com-
munities. If species composition is to be determined, the canopy of each spe-
cies is counted regardless of any overlap with other species. If watershed
characteristics are the objective, only the uppermost canopy is generally
counted.

For trend comparisons in herbaceous plant communities, basal cover is generally
considered to be the most stable. It does not vary as much due to climatic
fluctuations or current-year grazing.

C. Density

1. Description Density has been used to describe characteristics of plant communi-
ties. However, comparisons can only be based on similar life-form and size. This is
why density is rarely used as a measurement by itself when describing plant com-
munities. For example, the importance of a particular species to a community is
very different if there are 1,000 annual plants per acre versus 1,000 shrubs per
acre. It should be pointed out that density was synonymous with cover in the
earlier literature.

Density is basically the number of individuals per unit area. The term refers to the
closeness of individual plants to one another.

2. Advantages and Limitations

Density is useful in monitoring threatened and endangered species or other
special status plants because it samples the number of individuals per unit area.

Density is useful when comparing similar life-forms (annuals to annuals, shrubs
to shrubs) that are approximately the same size. For trend measurements, this
parameter is used to determine if the number of individuals of a specific species
is increasing or decreasing.

The problem with using density is being able to identify individuals and com-
paring individuals of different sizes. It is often hard to identify individuals of
plants that are capable of vegetative reproduction (e.g., rhizomatous plants like
western wheatgrass or Gambles oak). Comparisons of bunchgrass plants to
rhizomatous plants are often meaningless because of these problems. Similar
problems occur when looking at the density of shrubs of different growth forms



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Illustration 19



Ill. STUDY DESIGN AND ANALYSIS

The rangeland monitoring methods described in Section V have a number of common
elements. Those that relate to permanently marking and documenting the study location
are described in detail below.

Also discussed in this section are statistical considerations (target populations, random
sampling, systematic sampling, confidence intervals, etc.) and other important factors
(properly identifying plant species and training people so they follow the correct procedures).

It is important to read this chapter before referring to the specific methods described in
Section V, since the material covered here will not be repeated for each of them.

Permanently Marking the Study Location Permanently mark the location of each study
by means of a reference post (steel post) placed about 100 feet from the actual study
location. Record the bearing and distance from the post to the study location. An alter-
native is.to select a reference point, such as a prominent natural or man-made feature, and
record the bearing and distance from that point to the study location. If a post is used, it
should be tagged to indicate that it marks the location of a monitoring study and should
not be disturbed.

Permanently mark the study location itself by driving angle iron stakes into the ground at
randomly selected starting points. The baseline technique requires that both ends of the
baseline be permanently staked. With the macroplot technique, a minimum of three
corners need to be permanently staked. If the linear technique is used, only the beginning
point of the study needs to be permanently staked. Establish the study according to the
directions found in Section JII.A.2 beginning on page 8.

Paint the transect location stake with brightly colored permanent spray paint (yellow or
orange) to aid in relocation. Repaint this stake when subsequent readings are made.

Study Documentation Document the study and transect locations, number of transects,
starting points, bearings, length, distance between transects, number of quadrats, sampling
interval, quadrat frame size, size of plots in a nested plot frame technique, number of
cover points per quadrat frame, and other pertinent information concerning a study on the
Study Location and Documentation Data form (see Appendix A). For studies that use a
baseline technique, record the location of each transect along the baseline and the direc-
tion (left or right).

Be sure to document the exact location of the study site and the directions for relocating
it. For example: 1.2 miles from the allotment boundary fence on the Old County Line Road.
The reference post is on the south side of the road, 5O feet from the road.

Plot the precise location of the study on detailed maps and/or aerial photos.



Page —_of ___

Cover Data
Study Number Date Examiner Pasture
Allotment Name & Number Study Location Number of Points

Ground-Level Cover

Category

Bare
Ground

L

i Gravel
utter |G ammo |S

Stone
(>10")

Vegetation

Total

Dot
Count

Total
Hits

% Cover

Basal and Canopy/Foliar Cover

Bs! or Grnd-Lev

Level 1

Level 2 Level 3

Dot Count

Total Hits

Total

Notes (use other side or another page)

Illustration 13



METHODS—Point Intercept
9. Calculations Make the calculations and record the results on the Cover Data

form (see Illustration 13, page 75).
a Cover of Individual Plants, Litter, Gravel, Stone, and Bare Ground

(1) Paired samples Calculate the percent cover of each species along each
transect by totaling all of the “hits” for that species along the transect,
dividing the hits by the total number of points along the transect, and
multiplying by 100. Calculate the total percent cover for the species in the
sampled area by adding together all the transect cover values for the
species and dividing by the number of transects. Do the same for litter,
gravel, stone, and bare ground.

When point frames are used, the point frames themselves can be analyzed
as sampling units. In this case, percent cover of each species is calculated
for each point frame. Percent cover is calculated by totaling all of the “hits”
for that species in one frame, dividing the hits by the total number of
points in that frame, and multiplying by 100. In this situation, cover data
for each frame must be recorded separately on one form or on separate forms.

(2) Independent samples: Sighting device and pin frames Calculate the
percent cover of each species in the study area as a whole by totaling all
the “hits” for that species along all of the transects, dividing by the total
number of points in the study, and multiplying by 100. Do the same for
litter, gravel, stone, and bare ground.

(3) Independent samples: Point frames For independent samples, the frames
themselves can be considered the sampling units. Calculate the percent
cover of each species in each point frame by totaling all the “hits” for that
species in the frame, dividing the hits by the total number of points in the
frame, and multiplying by 100. Calculate the total percent cover for the
species in the sampled area by adding together all of the point frame cover
values for the species and dividing by the number of point frames. Do the
same for litter, gravel, stone, and bare ground.

(4) Total vegetation cover Calculate total vegetation cover by adding the
study area cover percentages for all plant species. This total could exceed
100 percent if multiple hits (overlapping canopies) were recorded at each
point along the transect.

b Species Composition Species composition is based on the percent cover of
the various species, Calculate percent composition by dividing the percent
cover for each plant species by the total cover for all plant species.

10. Data Analysis The method of data analysis depends upon whether or not the
transects are permanent.

a Permanent Transects If the transects are permanent, the transects or point
frames are the sampling units. Either a paired t test or the nonparametric Wilcoxon
signed rank test is used to test for significant change in average cover between two
sampling periods. Repeated measures analysis of variance is used to test for
significant change in average cover between three or more sampling periods.



INTRODUCTION

Guidelines The techniques described here are guides for establishing and sampling
vegetation attributes. They are not standards. Vegetation sampling techniques and
standards need to be based on management objectives. Techniques can be modified
or adjusted to fit specific resource situations or management objectives as long as the
principles of the technique are maintained. Before a modified technique is used, it
should be reviewed by agency monitoring coordinators, cooperators, and other quali-
fied individuals. A modified technique should be clearly identified and labeled as
“MODIFIED.” All modifications such as changes in quadrat size or transect layout
should be clearly documented each time the method is used.

Location of Study Sites Proper selection of study sites is critical to the
success of a monitoring program. Errors in making these selections can result in
irrelevant data and inappropriate management decisions.

The site selection process used should be documented. Documentation should
include the management objectives, the criteria used for selecting the sites, and the
kinds of comparisons or interpretations expected to be made from them.

Cofnmon locations for studies include critical areas and key areas. Some of the site
characteristics and other information that may be considered in the selection of study
sites are:

Soil

Vegetation (kinds and distribution of plants)

Ecological sites

Seral stage

Topography

Location of water, fences, and natural barriers

Size of pasture

Kind and/or class of forage animals—livestock, wildlife, wild horses, and wild burros
Habits of the animals, including foraging

Areas of animal concentration

Location and extent of critical areas

Erosion conditions

Threatened, endangered, and sensitive species—both plant and animal
Periods of animal use

Grazing history

Location of salt, mineral, and protein supplements

Location of livestock, wildlife, wild horse, and/or wild burro trails

1. Critical Area Critical areas are areas that should be evaluated separately from
the remainder of a management unit because they contain special or unique
values. Critical areas could include fragile watersheds, sage grouse nesting grounds,
riparian areas, areas of critical environmental concern, etc.

2. Key Areas Key areas are indicator areas that are able to reflect what is happen-
ing on a larger area as a result of on-the-ground management actions. A key area
should be a representative sample of a large stratum, such as a pasture, grazing
allotment, wildlife habitat area, herd management area, watershed area, etc.,
depending on the management objectives being addressed by the study. Key areas

La



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METHODS—Point Intercept

¢ Tripod for mounting sighting device

¢ Panhead for tripod (makes possible rapid positioning of sighting device)

¢ Pin or point frame. This can be a pin frame (see Illustration 16), usually with
10 pins (Bonham 1989; Pieper 1973) or a point frame (see Illustration 17),
consisting of two superimposed string grids mounted one above the other on
three adjustable legs (Floyd and Anderson 1983). The design of Floyd and
Anderson (1983) produces a sighting grid of 36 points per frame.

Hammer

Permanent yellow or orange spray paint

Tally counter (optional) . .

Two stakes: 3/4 - or l-inch angle iron not less than 16 inches long

Compass

Steel post and driver

Tape: 50-, 100-, or 200-foot delineated in tenths and hundreds or a metric tape
of the desired length.

. Training A minimum of training is needed to make sure the examiners under-
stand how to lay out baselines and transects and position and read the specific
sighting device or pin/point frame being employed. The examiners must also be
able to identify the plant species.

. Establishing Studies Careful establishment of studies is a critical element in
obtaining meaningful data.

a Site Selection The most important factor in obtaining usable data is selecting
representative areas (critical or key areas) in which to run the study (see Section
ILD). Study sites should be located within a single plant community within a
single ecological site. Transects and sampling points need to be randomly
located within the critical or key areas (see Section III).

b Pilot Studies Collect data on several pilot studies to determine the number of
samples (transects or observation points) and the number and size of quadrats
needed to collect a statistically valid sample (see Section III.B.8).

c Study Layout Data can be collected using either the baseline or linear study
designs described in Section III.A.2 beginning on page 8. The baseline
technique is the recommended procedure.

d Reference Post or Point Permanently mark the location of each study with a
reference post and a study location stake (see beginning of Section III).

e Study Identification Number studies for proper identification to ensure that
the data collected can be positively associated with specific sites on the ground
(see Appendix B).

f Study Documentation Document pertinent information concerning the study
on the Study Location and Documentation Data form (see beginning of Section III
and Appendix A).

. Taking Photographs The directions for establishing photo plots and for taking
close-up and general view photographs are given in Section V.A.



METHODS—Double Weight Sampling

(4) Use this as a visual model for comparison at each quadrat in the transect.
Record on the proper forms only the number of weight units. Do not
record the estimated weights.

(5) Weigh each weight unit at the conclusion of the transect. Weighing the
weight unit before the conclusion of the transect might influence the
weight estimates.

(6) Convert the weight units on the form to actual weight by multiplying the
number of units by the weight of the unit.

(7) Harvested weight unit material is not saved for determining air-dry weight
conversion. Air-dry conversions are determined from clipped quadrats.

9. Sampling Process 1n addition to collecting the specific studies data, general
observations should be made of the study sites (see Section II.F).

a Transect Bearing Determine the transect bearing and select a prominent
distant landmark such as a peak, rocky point, etc., that can be used as the
transect bearing point.

b Double Sampling

(1) Randomly select the starting point along the transect bearing. Take the
specified number of paces and read the first quadrat.

(2) Temporarily mark the quadrat by placing a pin flag next to the quadrat so
that it can be relocated later if this quadrat is selected for clipping. Be sure
to flag every quadrat.

(3) Estimate and record the weight of each species in the quadrat by means of
the weight-unit method.

When estimating or harvesting plants, include all parts of all plants within
the quadrat. Exclude all parts of herbaceous plants and shrubs outside the
vertical projection of the quadrat, even though the base is within the
quadrat (see Illustration 23).

(4) Continue the transect by establishing additional quadrats at specified pace
intervals. To change the length of the transect, adjust the number of paces
between quadrats.

(5) After weights have been estimated on all quadrats, select the quadrats to be
harvested.

(a) The quadrats selected should include all or most of the species in the
estimated quadrats. If an important species occurs on some of the
estimated quadrats but not on the harvested quadrats, it can be
clipped individually on one or more other quadrats.



Cover Board Method

Density Board

/ /

Page —_of —_

Study Number Deck Basin */

Date 7/25/95"

Examiner C&ris /Vass

Allotment Name & Number Deck Basin (5150

Pasture Red River

Density Board Location -

of stream. Reaodlings are taken at Y8% 199) 2285 and 7/8°.

SO paces west of Countyline Road on left side

Percent Cover
Plot 1 Plot 2 Plot 3 Plot 4 Avg. Cover
5 (2) (o) 2s 25 O 25 50 50 22
4 /O | 10 20 25 20 50 BO 50 27
3 | 20 30 25 25 30 50 50 75 38
2 50 100 100 /00 75 75 75 75 8!
1 | 100 | 100 | 75 | 00 | (00 | 75 75 | 100 W
$2

Total Average Cover-

Illustration 18



METHODS—Daubenmire

10.

11.

b Frequency Calculate the percent frequency for each plant species by dividing
the number of occurrences of a plant species (the number of quadrats in which
a plant species was observed) by the total number of quadrats sampled along
the transect. Multiply the resulting value by 100. Record the percent fre-
quency on the form (Illustration 10).

c Species Composition With this method, species composition is based on
canopy cover of the various species. It is determined by dividing the percent
canopy cover of each plant species by the total canopy cover of all plant species.
Record the percent composition on the form (Illustration 10).

Data Analysis Tests should be directed at detecting changes in cover of the
species and/or in major ground cover classes. Tests for changes in minor species
will have low power to detect change. If quadrats are spaced far enough apart on
each transect so as to be considered independent, the quadrat can be analyzed as
the sampling unit. Otherwise, the transects should be considered the sampling
units. If the transects are treated as the sampling unit, and given that the transects
are permanent, either the paired t-test or the nonparametric Wilcoxon signed rank
test should be used to test for change between two years. Repeated measures
ANOVA can be used to test for differences between 3 or more years. If the
quadrats are treated as the sampling units, care must be taken to ensure they are
positioned the same along each transect in each year of measurement. A paired
t-test, Wilcoxon signed rank test, or ANOVA is then used as described above for
transects.

References

Daubenmire, Rexford. 1959. A Canopy-coverage method of vegetational analysis.
Northwest Science 33:43-64.

1968. Plant communities: a textbook of plant synecology. Harper and
Row, New York. 300 p.

USDI, Bureau of Land Management. 1985. Rangeland monitoring - Trend Studies
TR4400-4.



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STUDY DESIGN AND ANALYSIS. _ -

b Cover In general, quadrats are not recommended for estimating cover (Floyd
and Anderson 1987; Kennedy and Addison 1987). Where they are used, the
same types of considerations given below for density apply: long, thin quadrats
will likely be better than circular, square, or shorter and wider rectangular
quadrats (Krebs 1989). Each situation, however, should be analyzed separately.
The amount of area in the quadrat is a concern with cover estimation. The
larger the area, the more difficult it is to accurately estimate cover.

c Density Long, thin quadrats are better (often very much better) than circles,
squares, or shorter and wider quadrats. How narrow the quadrats can be de-
pends upon consideration of problems of edge effect, although problems of
edge effect can be largely eliminated by developing consistent rules for deter-
mining whether to include or exclude plants that fall directly under quadrat
edges. One recommendation is to count plants that are rooted directly under
the top and left sides of the quadrat but not those directly rooted under the
bottom and right quadrat sides. The amount of area within the quadrat is
limited by the degree of accuracy with which one can count all the plants
within each quadrat.

d Plant Biomass For the same reason as given for density, long, thin quadrats are
likely to be better than circular, square, or shorter and wider rectangular quad-
rats (Krebs 1989). Edge effect can result in significant measurement bias if the
quadrats are too small (Wiegert 1962). Since above-ground vegetation must be
clipped in some quadrats, circular quadrats should be avoided because of the
difficulty in cutting around the perimeter of the circle with hand shears and the
likely measurement bias that would result. If plant biomass is collected in
grams, it can be easily converted to pounds per acres if the total area sampled is
a multiple of 9.6 ft?.

Use the following table to convert grams to pounds per acre:

Table 1
(# of plots x size = total area)
(10x0.96 = 9.6 ft’) multiply grams times 100 = pounds per acre
(10x1.92 = 19.2 ft) multiply grams times 50 = pounds per acre
(10x2.40 = 24.0 ft) multiply grams times 40 = pounds per acre
(10x4.80 = 48.0 ft’) multiply grams times 20 = pounds per acre
(10x9.60 = 96.0 ft”) multiply grams times 10 = pounds per acre
(10x96.0 = 960.0 ft?) multiply grams times 1 = pounds per acre

7. Interspersion One of the most important considerations of sampling is good
interspersion of sampling units throughout the area to be sampled (the target
population).

The basic goal should be to have sampling units as well interspersed as possible
throughout the area of the target population. The practice of placing all of the
sampling units, whether they be quadrats or points, along a single transect or even
a few transects should be avoided, because it results in poor interspersion of
sampling units and makes it unlikely that the sample will provide a representative
sample of the target population. This is true even if the transect(s) is randomly
located.



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Rangeland Monitoring

Nested Plot Frame

The frames are made of 3/8-inch

iron rod and 1-inch angle iron

or 1 1/4-inch x 3/16-inch flat iron.
Place tines at the proper intervals
along the rear of the frame and
parallel to the sides to create quadrats
of smaller sizes.

It is convenient to have a 30-, 20-,

15-, 12-, 10-, 6-, and 3-inch quadrat
available. These different size quadrats
can be combined in three frames.

The 30-inch and 15-inch quadrats can
be combined in one frame.

The 20-inch and 10-inch quadrats can
be combined in one frame.

The 12-inch, 6-inch, and 3-inch quadrats
can be combined in one frame.

Mlustration 7

METHODS—Frequency

The ends of the tines
(both front and rear)

are tapered to points

as illustrated. These
points are used to collect
cover data.



METHODS—Point Intercept 7

G. Point-Intercept Method - Sighting Devices, Pin Frames,
and Point Frames

1. General Description The Point-Intercept method consists of employing a sighting
device or pin/point frame along a set of transects to arrive at an estimate of cover. It
measures cover for individual species, total cover, and species composition by cover.

It is important to establish a photo plot (see Section V.A) and take both close-up
and general view photographs. This allows the portrayal of resource values and
conditions and furnishes visual evidence of vegetation and soil changes over time.

2. Areas of Use This method is suited to all vegetation types less than about 1.5
meters in height. This is because sighting devices and pin/point frames require the
observer to look down on the vegetation from above in a vertical line with the
ground. If the sighting device allows upward viewing, the method can also be used
to estimate the canopy cover of large shrubs and trees.

3. Advantages and Limitations Point interception measurements are highly
repeatable and lead to more precise measurements than cover estimates using
quadrats. The method is more efficient than line intercept techniques, at least for
herbaceous vegetation, and it is the best method of determining ground cover and
the cover of the more dominant species. Given the choice between sighting
devices and pin/point frames, the optical sighting device is preferable.

A limitation of point-intercept sampling is the difficulty in picking up the minor species in
the community without using a very large number of points. In addition, wind will increase
the time required to complete a study because of the need to view a stationary plant.

One limitation that is specific to the use of point frames is that a given number of
points grouped in frames gives less precise estimates of cover than the same number of
points distributed individually (Goodall 1952; Greig-Smith 1983). In fact, single-pin
measurements require only one-third as many points as when point frames are used
(Bonham 1989). Another problem with frames is that they overestimate the cover of
large or clumped plants because the same plant is intercepted by different points on
the same frame (Bonham 1989). This problem is overcome with the method
described here by treating the frames as the sampling units (rather than using the
individual points as sampling units). However, this approach doesn’t change the
fact that more points must be read than when the points are independent.

Use of a pin frame device (as opposed to a grid frame made of crossing strings) will
result in overestimation of cover because the pins have finite diameter. The use of
a sharpened pin will greatly reduce overestimation when only the point of the pin
is used to record a hit or a miss.

4. Equipment The following equipment is needed (see also the equipment listed in
Section V.A, page 31, for the establishment of the photo plot):

© Study Location and Documentation Data form (see Appendix A)
* Cover Data form (see Illustration 13 on page 75)
¢ Sighting device (see Illustration 15)*

4 A sighting device is available commercially from ESCO, P.O, Box 18775, Boulder, Colorado 80308.



eee REFERENCES

Crocker, R.L. and N.S. Tiver. 1948. Survey methods in grassland ecology. Journal of the
British Grassland Society 3: 1-26.

Cuplin, Paul. 1978. The use of large scale color infrared photography for stream habitat
inventory. U.S. Dept. of the Interior, BLM Tech. Note No. 325. 11 p.

Daubenmire, Rexford. 1959. A Canopy-coverage method of vegetational analysis. North-
west Science 33:43-64.

. 1968. Plant communities: a textbook of plant synecology. Harper and Row, New
York. 300 p.

Dawson, Bruce E. 1981. Relative effectiveness of true-color, color infrared, black and white
infrared and red-band sensitive films in identification of plant species. M.S. Thesis.
Humboldt St. Univ., Arcata, CA. 101 p.

Dayton, W.A. 1950. Glossary of Botanical Terms Commonly Used in Range Research,
USDA Miscellaneous Publication No 110, 40 p.

Despain, D.W., P.R. Ogden, and E.L. Smith. 1991. Plant frequency sampling for monitoring
rangelands. In: G.B. Ruyle, ed. Some Methods for Monitoring Rangelands and other
Natural Area Vegetation. Extension Report 9043, University of Arizona, College of
Agriculture, Tucson, AZ.

DeVries, P.G. 1979. Line intersect sampling-statistical theory, applications, and suggestions
for extended use in ecological inventory. In: R.M. Cormack, G.P. Patil and D.S. Robson,
eds., Sampling Biological Populations, Vol. 5: Statistical Ecology, pp. 1-70. International
Cooperative Publishing House, Fairland, MD.

Dixon, WJ., and FJ. Massey, Jr. 1983. Introduction to statistical analysis, 4th ed. McGraw-
Hill, New York, NY.

Duncan, Don A. and Robert G. Woodmansee. 1975. Forecasting forage yield from
precipitation in California’s annual rangeland. J, Range Manage. 28:327-329.

Eckert, Richard E., Jr. and John S. Spencer. 1986. Vegetation response on allotments grazed
under rest rotation management. Soc. for Range Manage. 39 (2): 166-173.

Ellison, Lincoln, A.R. Croft, and Reed W. Bailey. 1951. Indicators of condition and trend on
high range-watersheds of the Intermountain Region. U.S. Dept. of Agr., For. Ser., Agr.
Handbook No. 19. 66 p.

Evans, Raymond A. and R. Merton Love. 1957. The step-point method of sampling a
practical tool in range research. J. Range Manage. 10:208-212.

Everitt, JH., A.H. Gerbermann, N.A. Alaniz, and R.L. Bowen. 1980. Using 70-mm aerial
photography to identify rangeland sites. Photogrammetric Engineering and Remote
Sensing 46:1339-1348.

Fisser, H.G. and G.M. Van Dyne. 1966. Influence of number and spacing of points on
accuracy and precision of basal cover estimates. J. Range Manage. 19:205-211.

140



GLOSSARY

evaluation: (1) an examination and judgment concerning the worth, quality, significance,
amount, degree, or condition of something; or (2) the systematic process for determining
the effectiveness of on-the-ground management actions and assessing progress toward
meeting objectives.

F

foliar cover: the percentage of ground covered by a downward vertical projection of the
aerial portion of plant foliage, excluding small openings in the canopy, Foliar cover is
always less than canopy cover. Total foliar cover of all species may exceed 100 percent.

forage: (1) browse and herbage which is available and can provide food for animals or be
harvested for feeding; or (2) to search for or consume forage.

forage production: the weight of forage that is produced within a designated period of time
or a given area. Production may be expressed as green, air dry, or oven dry weight. The
term may also be modified as to time of production such as annual, current year, or
seasonal forage production.

forb: (1) any herbaceous plant other than those in the Gramineae (true grasses),
Cyperaceae (sedges), and Juncaceae (rushes) families—i.e., any nongrass-like plant having
little or no woody material on it; or (2) a broadleaved flowering plant whose above-
ground stem does not become woody and persistent.

forestland: land on which the vegetation is dominated by trees. Lands are classified forest-
land if the trees now present will provide 25 percent or greater canopy cover at maturity.
Lands not presently forestland that were originally or could become forested through
natural succession may be classified as potential natural forestland.

frequency: a quantitative expression of the presence or absence of individuals of a species in
a population. It is defined as the percentage of occurrence of a species in a series of
samples of uniform size.

G

goal: the desired state or condition that a resource management policy or program is de-
signed to achieve. A goal is usually not quantifiable and may not have a specific date by
which it is to be completed. Goals are the base from which objectives are developed.
(See objective.)

grass: any plant of the family Gramineae.

grassland: land on which the vegetation is dominated by grasses, grasslike plants, and/or
forbs. Non-forested lands are classified as grassland if herbaceous vegetation provides at
least 80 percent of the canopy cover excluding trees. Lands not presently grassland that
were originally or could become grassland through natural succession may be classified as
potential natural grassland.

grasslike plant: a plant of the Cyperaceae or Juncaceae families which vegetatively re-
sembles a true grass of the Gramineae family.



axis 16m

STUDY DESIGN AND ANALYSIS

32m 48m 64m 80m

39

30

20

10

ox”

() 1
Beginning Point Stake

Figure 3. A 40 m x 80 m macroplot showing the 200 possible quadrats of size 1 m x 16 m that could be
placed within it (assuming the long side of the quadrats is oriented along the x-axis).

()

@)

(2)

axis

Now, using a random number table or a random number generator on
a computer or handheld calculator, choose at random 40 numbers
from 0 to 4 for the x axis and 40 numbers from 0 to 39 for the y axis.
(Directions on the use of random number tables and random number
generators are given in Appendix D of this document and in the
Interagency Technical Reference, Planning for Monitoring.

At the end of this process, 40 pairs of coordinates will be selected. If
any pair of coordinates is repeated, the second pair is rejected and
another pair picked at random to replace it (because sampling is
without replacement). Continue until there are 40 unique pairs of
coordinates.

These 40 pairs of coordinates mark the points at which quadrats will
be positioned.

Both to increase sampling efficiency and to reduce impacts to the
sampling units by examiners, the coordinates should be ordered from
smallest to largest first on the axis parallel to the longest side of the
quadrat and then on the other axis. For example, the following four
sets of coordinates have been randomly selected (presented in the
order they were selected):

X-axis y-axis
3 (48.0 m)} 27.0m
4(64.0m)  34.0m
3 (48.0 m) 8.0m
1 (16.0 m) 28.0 m

RWNE



—
N

native pasture: land on which native vegetation (climax or natural potential plant commu-
nity) is forest but which is used and managed primarily for production of native plants for
forage. Native pasture includes cutover forest land and forested areas that were cleared
and used as cropland.

0

objective: planned results to be achieved within a stated time period. Objectives are
subordinate to goals, are narrower in scope and shorter in range, and have increased
possibility of attainment. The time periods for completion, and the outputs or achieve-
ments that are measurable and quantifiable, are specified. (See goal.)

overstory: the upper canopy or canopies of plant, usually referring to trees, shrubs, and vines.

pasture: a grazing area enclosed and separated from other areas by a fence or natural barrier.

potential natural community (PNC): the biotic community that would become established
if all successional sequences were completed without interference by human beings under
the present environmental conditions. Natural disturbances are inherent in development.
PNCs can include naturalized non-native species.

proper use: (1) a degree of utilization of current year’s growth which, if continued, will
achieve objectives and maintain or improve the long-term productivity of the site; or (2)
the percentage of a plant that is utilized when the rangeland as a whole is properly uti-
lized. Proper use varies with time and systems of grazing. Proper use is synonymous with
proper utilization.

public lands: any land and interest in land outside of Alaska owned by the United States
and administered by the Secretary of the Interior through the Bureau of Land Management
(see 43 CFR 4100.0-5).

R

rangeland: a kind of land on which the native vegetation is predominantly grasses, grass-like
plants, forbs, or shrubs. Includes lands revegetated naturally or artificially when routine
management of that vegetation is through manipulation of grazing. Rangelands include
natural grasslands, savannas, shrublands, most deserts, tundra, alpine communities, coastal
marshes, and wet meadows.

range site: (See ecological site.)
riparian zone: the banks and adjacent areas of water bodies, water courses, seeps, and springs
whose waters provide soil moisture sufficiently in excess of that otherwise available locally

so as to provide a more moist habitat than that of contiguous flood plains and uplands.

rock fragment: an individual fragment of solid mineral material which occurs naturally on
the earth’s crust and ranges in size from gravel to boulder.



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APPENDIX D—
SELECTING RANDOM SAMPLES

Selecting random points along a baseline from which to run transects:

1. Select Direction If the baseline bisects the middle of the sample area, the first deter-
mination for selecting the location of a transect is to determine the direction each
transect will be run perpendicular to the baseline. A simple flip of a coin could be used.
Another way of selecting directions is to arbitrarily decide that odd numbers represent
transects to the right of the baseline and even numbers represent transects to the left of
the baseline. If five transects are required along a 100-meter baseline, start at some
arbitrary point anywhere on the random digit table below and select the first five single
digit numbers from left to right. As an example, the process could begin with the
number sequence in row 15, column 4 (22695). Transects 1, 2, and 3 would be run to
the left (numbers 2, 2, and 6), and transects 4 and 5 would be run to the right (9 and 5).

2. Select Location To select the location of each transect along the baseline, again start
at some arbitrary point on the table of random numbers. In this case, use two-digit
sequences. If row 19, column 3, is selected as the starting point, the five two-digit
sequences would be 33, 52, 15, 56, and 37. Transects would be run at the 15-, 33-, 37-,
52-, and 56- meter marks along the baseline. Care should be taken to ensure that
adjoining transects do not overlap. Depending on the ecological site and vegetation
community, any interval can be selected as the minimum distance between transects. In
this case, 10 meters has been established as the distance between transects. In the above
example, the second and third transects (at the 33- and 37-meter marks) are within 10
meters of each other on the same side of the baseline. If they were to be run in opposite
directions, there would be no problem. Since they are to be run in the same direction,
discard the transect at the 37-meter mark and select the next two-digit sequence. A
transect at the 39-meter mark (the next two digits in the table) is still within 10 meters
of the previous transect. Continue the process until all transects are separated by 10
meters. With the next two-digit number sequence being 78, transect locations are now
at the 15-, 33-, 52-, 56-, and 78- meter marks. Since the new third and fourth transects
(52 and 56) are in opposite directions, the five transect locations have been determined.

The table of random numbers could also be used for baselines over 100 meters. If the
baseline is 200 meters, use a three-digit sequence to select the location of each transect.
Only those three-digit numbers that fall between 1 and 200 would be used. This
method requires the selection of many numbers because most will not fall between 1
and 200.

There is a more efficient method of selecting random samples, particularly for two-,
three-, and higher-digit numbers. To use this method, the random numbers must be
treated as decimals. In our set of random digits, we would simply place a decimal point
in front of every group of five digits and treat each group as one random number. Thus,
if we entered the table at row 26, column 7, and read across, we would have the follow-
ing six random numbers: 0.32978, 0.59902, 0.05463, 0.09245, 0.37631, and 0.74016.

If we used a random number generator, it would be even easier since these provide
random numbers as decimals falling between 0 and 1.



METHODS=—Step Point

F. Step-Point Method

1. General Description The Step-Point Method involves making observations
along a transect at specified intervals, using a pin to record cover “hits.” It mea-
sures cover for individual species, total cover, and species composition by cover.

It is important to establish a photo plot (see Section V.A) and take both close-up
and general view photographs. This allows the portrayal of resource values and
conditions and furnishes visual evidence of vegetation and soil changes over time.

2. Areas of Use This method is best suited for use with grasses and forbs, as well

as low shrubs. The greater the structure to the community, the more difficult it
becomes to determine “hits” due to parallax, observer bias, wind, etc. This method
is good for an initial overview of an area not yet subjected to intensive monitoring.

3. Advantages and Limitations This method is relatively simple and easy to

use as long as careful consideration is given to the vegetation type to which it is
applied. It is suitable for measuring major characteristics of the ground and veg-
etation cover of an area. Large areas can easily be sampled, particularly if the
cover is reasonably uniform. It is possible to collect a fairly large number of
samples within a relatively short time.

A limitation of this method is that there can be extreme variation in the data
collected among examiners when sample sizes are small. Tall or armored vegeta-
tion reduces the ability to pace in a straight line, and the offset for obstructions
described in the procedures adds bias to the data collection by avoiding certain
components of the community. Another limitation is that less predominant plant
species may not be hit on the transects and therefore do not show up in the study
records. The literature contains numerous studies utilizing point intercept
procedures that required point densities ranging from 300 to 39,000 in order to
adequately sample for minor species. One major consideration in the use of this
method is to assure that a sharpened pin is used and that only the point is used to
record “hits.” Pins have finite diameters and therefore overestimate cover (Goodall
1952). Another limitation of this method is that statistical analysis of the data is
suspect unless two and preferably more transects are run per site (see Section III -
Study Design and Analysis).

4, Equipment The following equipment is needed (see also the equipment listed in

Section V.A, page 31, for the establishment of the photo plot):

Study Location and Documentation Data form (see Appendix A)
Cover Data form (see Illustration 13)

Permanent yellow or orange spray paint

Tally counter (optional)

One stake: 3/4- or 1-inch angle iron not less than 16 inches long
3-foot long, 3/16th-inch diameter sharpened pin

Compass

Steel post and driver

5. Training A minimum amount of training is needed for this method. Examiners

must be able to identify the plant species, be familiar with the ground-level cover



ATTRIBUTES

composition. This is because the numbers derived for frequency sampling are
unique to the choice of sample size, shape, number, and placement. For variables
of cover and weight, accuracy is mostly what is affected by these choices and the
variable can be conceived independently of the sampling protocol.”

B. Cover

1. Description Cover is an important vegetation and hydrologic characteristic. It
can be used in various ways to determine the contribution of each species to a
plant community. Cover is also important in determining the proper hydrologic
function of a site. This characteristic is very sensitive to biotic and edaphic forces.
For watershed stability, some have tried to use a standard soil cover, but research
has shown each edaphic site has its own potential cover.

Cover is generally referred to as the percentage of ground surface covered by
vegetation. However, numerous definitions exist. It can be expressed in absolute
terms (square meters/hectares) but is most often expressed as a percentage. The
objective being measured will determine the definition and type of cover measured.

a Vegetation cover is the total cover of vegetation on a site.

b Foliar cover is the area of ground covered by the vertical projection of the aerial
portions of the plants. Small openings in the canopy and intraspecific overlap
are excluded (Figure 6).

c Canopy cover is the area of ground covered by the vertical projection of the
outermost perimeter of the natural spread of foliage of plants. Small openings
within the canopy are included. It may exceed 100% (Figure 7).

Figure 6. Foliar cover. Figure 7. Canopy cover.

d Basal cover is the area of ground surface occupied by the basal portion of the
plants.

e Ground cover is the cover of plants, litter, rocks, and gravel on a site.



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Mustration 12



Nie, Norman H., C. Hadlai Hull, Jean G. Jenkins, Karin Steinbrenner, and Dale H. Bent.
1975. Statistical package for the social sciences, SPSS. 2nd Ed. McGraw-Hill Book Co.,
New York, NY. 675 p.

Nudds, Thomas D. 1977. Quantifying the vegetative structure of wildlife cover. Wildlife
Society Bulletin 5:113-117.

Odum, Eugene P. 1971. Fundamentals of ecology. 3rd Ed. W.B. Saunders Co., Philadelphia,
PA. 547 p.

Oosting, Henry J. 1956. The study of plant communities - an introduction to plant ecology.
2nd Ed. W.H. Freeman and Co., San Francisco, CA. 440 p.

Parker, Kenneth. 1954. Application of ecology in the determination of range condition and
trend. J. Range Manage. 7:14-24.

Payne, G.F. 1974. Cover-weight relationships. J. Range Manage. 27:403-404.

Pechanec, J.F. and G.D. Pickford. 1937. A weight-estimate method for the determination of
range or pasture production. J. Amer. Soc. Agron. 29:894-904.

Pechanec, J.F. and George Stewart. 1949. Grazing spring-fall sheep ranges of southern
Idaho. U.S. Dept. of Agr., Circular No. 808. 34 p.

Phillips, E.A. 1959. Methods of vegetation study. Holt, Rinehart, and Winston, Inc., New
York, NY. 107 p.

Pieper, Rex D. 1973. Measurement techniques for herbaceous and shrubby vegetation.
Dept. of Animal and Range Sciences, New Mexico State Univ., Las Cruces, NM. 149 p.

Pierce, W.R. and L.E. Eddleman. 1970. A field stereographic technique for range analysis. J.
Range Manage. 23:218-220.

Pitt, Michael D. and Harold F. Heady. 1979. The effects of grazing intensity on annual
vegetation. J. Range Manage. 32:109-114.

Reppert, Jack N. and Richard E. Francis. 1973. Interpretation of trend in range condition
from 3-step data. U.S. Dept. of Agr., For. Ser., Rocky Mtn. For. and Range Exp. Sta., Ft.
Collins, CO., Research Paper RM-103. 15 p.

Richardson, Arlo E. 1981. Report on the feasibility of using phenoclimatography models to
predict range development and production on BLM winter ranges. BLM Contract No.
UT-910-CTO-003. 73 p.

Richardson, Arlo E. and Stephen G. Leonard. 1981. Climatic modeling of winter rangelands
in Utah. In: Ext. Abstract 15th Conf. on Agr. and For. Meteorology and 5th Conf. on
biometeorology, Anaheim, CA. p. 182-185.

Riser, Paul G. 1984, Methods for Inventory and Monitoring of Vegetation, Litter, and Soil
Surface Condition. Developing Strategies for Rangeland Monitoring. National Research
Council National Academy of Sciences.



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STUDY DESIGN AND ANALYSIS

s= | (X) - X)2 + (X)- XP +... + (XK, - XP

The following shows how to calculate the standard deviation for the density of
sideoats grama occurring in two sample designs. In this example there are 2, 10,
and 21 sideoats grama plants in three separate quadrats in the first design and 9,
10, and 14 sideoats grama plants in the second set of three plots. The average
number of plants in both sets of plots is 11 (2+10+21= 33/3= 11 and 94+10+14=
33/3=11). The standard deviation is calculated as follows:

or S= XK-X) (X- xX)?

n-l n
where:
S = standard deviation
X = number of plants
X = the mean or average number of plants per quadrat
n = the number of samples (quadrats in this example)
Squared
Number of plants Deviation Deviation
(X- X) (x- x)
2 2-11=-9 81
10 10-11=-1 1
21 21-11=10 100
X=33/3=11 182
Xz
Se APE XP _ (2 - 22 = (oT = 954
n-\ 3-1 2
Squared
Number of plants Deviation Deviation
(x= X) (X= X}
9 9-11=-2 4
10 10-11=-l 1
14 14-ll= 3 2
X = 33/3 =11 14

— |O(K- Xp 1400 © 140 _ _
S= = = = = 2.65
n-l 3-1 2 v7

The coefficient of variation for the first set of quadrats is 9.54/11 or .86,
whereas the second set of quadrats has a coefficient of variation of 2.65/11]= .24.
Since the second sampling design has the lowest coefficient of variation, it is the
most efficient design.

This example, with only three quadrats in each sampling design, is given solely to show how

to calculate standard deviations and coefficients of variation. When comparing actual
study designs, ensure that the sample standard deviation is a good estimate of the popula-
tion standard deviation. One way of ensuring this is to construct sequent! scinpling
graphs of the standard deviation of each design (see Sequential Sampling below).



METHODS—Photographs

Rangeland Monitoring

Photo Plot Frame—5- x 5-foot

3/4 Light tubing--*”

Telescoping legs --~
(see detail)

| 18" DETAIL

Illustration 2 | 35 |



APPENDIX B

3. Label 3 A placard on which identifying characteristics can be entered can be
developed to meet local field needs. The placard can be constructed of heavy
white cardboard on which such things as Date, “T” (township), “R” (range), Sec-
tion Number, etc., are preprinted. A heavy mylar film can be placed over the
preprinted placard. The specific identifying information can be handprinted on
the mylar with a heavy grease pencil or other readily removable, highly visible,
marking material. After taking the desired photographs, the mylar can be wiped
clean and the placard reused for other photographs. A more permanent placard
can be constructed of plywood and painted enamel white. The grease pencil
markings can be wiped from the enameled surface and the placard reused for other
photographs. Caution must be exercised in the placement of the placard to
prevent glare from the mylar or enameled surface.

NOTE - Labels can be placed flat on the ground immediately adjacent to photo plots for
close-up photographs.

- Labels can be placed in an upright position in the foreground of general view
photographs.



D. Daubenmire Method

1. General Description The Daubenmire method consists of systematically
placing a 20- x 50-cm quadrat frame along a tape on permanently located transects
(see Figure 4 on page 13). The following vegetation attributes are monitored using
the Daubenmire method:

¢ Canopy cover
¢ Frequency
* Composition by canopy cover

It is important to establish a photo plot (see Section V.A) and take both close-up
and general view photographs. This allows the portrayal of resource values and
conditions and furnishes visual evidence of vegetation and soil changes over time.

2. Areas of Use This method is applicable to a wide, variety of vegetation types as
long as the plants do not exceed waist height.

3. Advantages and Limitations This method is relatively simple and rapid to
use, A limitation is that there can be large changes in canopy cover of herbaceous
species between years because of climatic conditions, with no relationship to the
effects of management. In general, quadrats are not recommended for estimating
cover (Floyd and Anderson 1987; Kennedy and Addision 1987). This method
cannot be used to calculate rooted frequency.

4. Equipment The following equipment is needed (see also the equipment listed
in Section V.A, page 31, for the establishment of the photo plot):

Study Location and Documentation Data form Appendix A)

Daubenmire forms (see Illustration 9 and 10)

Hammer

Permanent yellow or orange spray paint

Two stakes: 3/4 - or l-inch angle iron not less than 16 inches long

Tape: 100- or 200-foot, delineated in tenths and hundreds, or a metric tape of
the desired length.

Steel pins (reinforcement bar) for marking zero, mid, and end points of the transect
Frame to delineate the 20- x 50-cm quadrats (see Illustration 11)

Compass

Steel post and driver

5. Training The accuracy of data depends on the training and ability of the
examiners. Examiners must be able to identify the plant species. They must
receive adequate and consistent training in laying out transects and making
canopy coverage estimates using the frame.

6. Establishing Studies Careful establishment of studies is a critical element in
obtaining meaningful data (see Section II).

a Site Selection The most important factor in obtaining usable data is selecting

representative areas (critical or key areas) in which to run the study (see Section
ILD). Study sites should be located within a single plant community within a

_Ka



10.

Internet ftp (file transfer protocol) site: odin.mda.uth.tmc.edu. Documentation is
included with the program. The program calculates sample sizes needed for all of
the types of significance testing but does not calculate those required for estimat-
ing a single population average, total, or proportion. PC-SIZE: CONSULTANT is
a shareware program that will calculate sample sizes for estimating an average (but
not a proportion) and for all the types of significance tests. It was developed in
1990 by Gerard E. Dallal, who also developed the commercial program DESIGN
discussed above. PC-SIZE: CONSULTANT appears to contain all of the algo-
rithms included in DESIGN but at a fraction of the cost (the author asks for a fee
of $15.00 if the user finds the program to be useful). The program is available via
the World Wide Web at the following address:

http://www.coast.net/SimTel/SimTel/

Once at the homepage, change to the directory msdos/statstic/ and download the
file st-size.zip. Unzip the file using the shareware program PKUNZIP. Executable
files and documentation are included.

Alternatively, tables can be used to calculate sample size. For detecting change in
averages, proportions, or totals between two time periods, the tables found in
Cohen (1988) are highly recommended.

Graphical Display of Data The use of graphs, both to initially explore the
quality of the monitoring data collected and to display the results of the data
analysis, is important to designing and implementing monitoring studies. See the
Interagency Technical Reference, Planning for Monitoring, for descriptions of these
graphs, along with examples.

a Graphs to Examine Study Data Prior to Analysis The best of these graphs
plot each data point. These graphs can help determine whether the data meet
the assumptions of parametric statistics, or whether the data set contains outli-
ers (data with values much lower or much higher than most of the rest of the
data—as might occur if one made a mistake in measuring or recording), Normal
probability plots and box plots are two of the most useful types for this purpose.
Graphs can also assist in determining appropriate quadrat size. For more
information, see the Interagency Technical Reference, Planning for Monitoring.

b Graphs to Display the Results of Data Analysis Rather than displaying
each data point, these graphs display summary statistics (i.e., averages, totals, or
proportions). When these summary statistics are graphed, error bars must be
used to display the precision of estimates. Because it is the true parameter
(average, median, total, or proportion) that is of interest, confidence intervals
should be used as error bars. Types of graphs include:

¢ Bar charts with confidence intervals.
© Graphs of summary statistics plotted as points, with error bars.

* Box plots with “notches” for error bars.

STUDY DESIGN AND ANALYSIS



Hironaka, M. 1985. Frequency approaches to monitor rangeland vegetation. Symp. on use
of frequency and for rangeland monitoring. William C. Krueger, Chairman. Proc., 38th
Annual Meeting, Soc. for Range Manag. Feb. 1985. Salt Lake City, UT. Soc. for Range
Manage. 84-86,

Hyder, D.N., C.E. Conrad, P.T. Tueller, L.D. Calvin, C.E. Poulton, and RA. Sneva. 1963.
Frequency sampling of sagebrush-bunchgrass vegetation. Ecology 44:740-746.

Hyder, D.N., R.E. Bement, E.E. Remmenga, and C. Terwilliger, Jr. 1965. Frequency sampling
of blue grama range. J. Range Manage. 18:94-98.

Hyder, D.N., R.E. Bement, and C. Terwilliger. 1966. Vegetation-soils and vegetation-
grazing relations from frequency data. J. Range Manage. 19:1]-17.

Jardine, J.T. and Forsling, C.L. 1922. Range and cattle management during drought. USDA
Bul. 1031, 84 p.

Jasmer, Gerald E. and Jerry Holechek. 1984. Determining Grazing Intensity on Rangelands.
Journal of Soil and Water Conservation. 39(1):32-35.

Jones, M.B. and R.A. Evans. 1959. Modification of the step-point method for evaluating
species yield changes in fertilizer trials on annual grasslands. Agron. J. 51:467-470.

Kennedy, K.A. and P.A. Addison. 1987. Some considerations for the use of visual estimates
of plant cover in biomonitoring. J. Ecology 75: 151-157.

Kinsinger, Floyd E., Richard E. Eckert, and Pat 0. Currie. 1960. A comparison of the line-
interception, variable-plot, and loop methods as used to measure shrub-crown cover. J.
Range Manage. 13:17-21.

Krebs, CJ. 1989. Ecological methodology. Harper & Row, New York, NY.

Lapin, Lawrence L. 1993. Statistics for Modern Business Decisions. 6th Ed. Dryden Press,
Orlando, FL. 1265p.

Laycock, W.A. 1987. Setting Objectives and Picking Appropriate Methods for Monitoring
Vegetation on Rangelands. Rangeland Monitoring Workshop Proceedings. U.S.
Department of Interior. Bureau of Land Management. Golden, CO.

Levy, E.B. and E.A. Madden. 1933. The Point Method for Pasture Analysis. New Zealand
J. Agric. 46: 267-279.

Lillesand, Thomas M. and Ralph Kiefer. 1979. Remote sensing and image interpretation.
John Wiley and Sons, New York, NY. 612 p.

Lucas, H.A. and G.A.F. Seber. 1977. Estimating coverage and particle density using the
line intercept method. Biometricka 64:61 8-622.

Lund, H. Gyde and Elise McNutt. 1979. Integrating inventories: an annotated bibliography.
USS. Dept. of the Interior, BLM Tech Note No. 333. 183 p.



METHODS—Cover Board

g Study Documentation Document pertinent information concerning the study
on the Study Location and Documentation Data form (see beginning of Section
III and Appendix A).

7. Taking Photographs The directions for establishing photo plots and for taking

8.

9.

10.

11.

close-up and general view photographs are given in Section V.A.

Sampling Process In addition to collecting the specific studies data, general
observations should be made of the study sites (see Section II.F).

Position the cover board in the appropriate locations 15 feet from the observation
point. Record the cover class from the modified Daubenmire cover classes (see
Table 2) for each segment of the cover board (see Illustration 20). Depending on
the objectives, vegetative cover can be recorded by species or simply for the total
of all species. Cover can also be recorded as a straight percentage.

Table 2

Cover Class Range of Coverage Midpoint of Range
0% 0%
<1% 0.5%
1 to 5% 3.0%
5 to 25% 15.0%
25 to 50% 37.5%
50 to 75% 62.5%
75 to 95% 85.0%
95 to 100% 97.50%

AURWNHYO

. Calculations for Vertical Canopy Cover Calculate the average “cover

score” by layer. The midpoint of each cover class is used to calculate the average
cover for each layer or for the entire transect when using cover classes. If actual
percentage estimates are made, calculate an average cover value by averaging cover
for each layer. For a total cover average, the calculation involves summing the
cover values for all layers and dividing by the number of layers.

Data Analysis For trend analysis, permanent sampling units are suggested. If
permanent transects are monitored, use the appropriate paired analysis technique. If
the transects are not permanently marked, use the appropriate nonpaired test.

When comparing more than two sampling periods, use repeated measures ANOVA.

References

Nudds, Thomas D. 1977. Quantifying the vegetative structure of wildlife cover.
Wildlife Society Bulletin 5:113-117.

Spalinger, D.E. 1980. Vegetation Changes on Eight Selected Deer Ranges in Nevada
Over a 15-Year Period. Nevada State Office Bureau of Land Management.

USDI, Bureau of Land Management. 1987. Riparian Inventory and Monitoring,
Montana BLM Riparian Tech. Bull. No.1.



METHODS—Frequency

11.

(3) Total frequency for all transects Calculate the percent frequency of a
plant species by plot size for the total of all transects by adding the occur-
rences of a species by plot size on all transects, dividing the total by the
total number of quadrats sampled for the study, and multiplying the value
by 100. Record the percent frequency in the appropriate plot size on a
separate form.

10. Data Analysis To determine if the change between sampling periods is signifi-

cant, a Chi Square contingency table analysis should be used (see the Interagency
Technical Reference, Planning for Monitoring). Frequency must be analyzed sepa-
rately for each species. Chi Square analysis of variance can also be used to detect
changes in cover classes between sampling periods.

References

Bonham, C.D. 1989. Measurements for Terrestrial Vegetation, John Wiley and
Sons, 338 p.

Despain, D.W., P.R. Ogden, and E.L. Smith. 1991. Plant frequency sampling for
monitoring rangelands. Some methods for monitoring rangelands and other

natural area vegetation. Extension Report 9043. University of Arizona, Tucson,
AZ.

Eckert, Richard E., Jr. and John S. Spencer. 1986. Vegetation response on allot-

ments grazed under rest rotation management. Soc. for Range Manage. 39 (2):
166-173.

Francis, Richard E., Richard S, Driscoll, and Jack N. Reppert. 1972. Loop-fre-
quency as related to plant cover, herbage production, and plant density. U.S.
Dept. of Agr., For. Ser., Rocky Mtn. For. and Range Exp. Sta., Ft. Collins, CO.
Research Paper MA-94. 15 p.

Hironaka, M. 1985. Frequency approaches to monitor rangeland vegetation.
Symp. on use of frequency and for rangeland monitoring. William C. Krueger,
Chairman. Proc., 38th Annual Meeting, Soc. for Range Manag. Feb. 1985. Salt
Lake City, UT. Soc. for Range Manage. 84-86.

Hyder, D.N., CE. Conrad, P.T. Tueller, L.D. Calvin, CE. Poulton, and FA. Sneva.
1963. Frequency sampling of sagebrush-bunchgrass vegetation. Ecology
44:740-746.

Hyder, D.N., R.E. Bement, E.E. Remmenga, and C. Terwilliger, Jr. 1965. Frequency
sampling of blue grama range. J. Range Manage. 18:94-98.

Hyder, D.N., R.E. Bement, and C. Terwilliger. 1966. Vegetation-soils and vegeta-
tion-grazing relations from frequency data. J. Range Manage. 19:11-17.

Nevada Range Studies Task Group. 1984. Nevada Rangeland Monitoring Hand-
book. Bureau of Land Management Nevada State Office, Reno, NV. 50 p.



Examples of Sighting Devices

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METHODS—Point Intercept

Examples of Pin Frames

Illustration 16



METHODS—Comparative Yield

each quadrat is determined without regard to species. Be sure to save all
clipped material. The reference quadrats can be used as part of these
clipped quadrats, The more quadrats clipped, the better the calibration.
Each distinct sampling period should have a separate calibration. Bags can
be weighed in the field to determine green weight and then saved and
dried to determine dry weight (see Section V.J.9.b.(6)). These weights are
then used to determine average weight per reference.

9. Calculations The number of quadrats tallied for each ranking is totaled
(Illustration 7, column 2) and multiplied by the ranking (column 1).

Rank x Tally = Weighted ranking

These weighted rankings (column 3) are summed and divided by the number of
total quadrats. This indicates the average ranking for the site.

Total rank = Average ranking for the site
Total number of quadrats sampled

The average yield may be estimated with a ratio estimate (described below) or a
least-squares regression technique. The ratio estimate is good for quick field
calculations, but the least-squares regression should be used for final data analysis.

To use the ratio estimate technique, calculate the average rank and average clipped
weight of the harvested quadrats by dividing the total of the clipped rankings and the
total clipped weight by the number of harvested (clipped) quadrats (column 4 and 5).

S = Average rank of clipped quadrats
Total number of clipped quadrats

Total clipped weight = Average weight of clipped quadrats
Total number of clipped quadrats

The average clipped weight is then divided by the average rank to determine the
average rank interval.

Average weight of clipped quadrats = Average rank interval (ARI)
Average rank of clipped quadrats

The average ranking for the site—which is based on the estimated, not clipped,
quadrats—is then multiplied by the average rank interval to estimate the average
yield per quadrat for the site.

Average ranking for the site x Average rank interval = Average yield/Quadrat.

The average yield in grams per quadrat obtained above can be converted to either
pounds/acre or kilograms/hectare.

Use the following table to convert grams to pounds per acre if the total area
sampled is a multiple of 9.6 ft2.



Page of /_
Comparative Yield
Study Number . Date ] Examiner . Pasture
y Silver Creek #4 SfI/ IS | Welly Pip 3
Allotment Name & Number Number of Quadrats Quadrat Size
Silver Creek 2/703 25 YOx 40

Study Location 2 miles EasT of Red Wel/ om NORTH Side of road.

Sampled Quadrats Harvested Quadrat
Rank (1) Tally (2) Rank x Tally (3) Clip Rank (4) Clip Weight (5)
0) 2) 2) } 10
5 (2) 2) 2 27
1 3 3 3 46
1.5 4 6 4 62
2 s 10 fs) 8&3
2.5 4 10
3 2 6
| 35 3 10.5
4 2 8
45 ! v5
5 ° U 5
Total 25 63 is 228
Average 2.52 3 45.6
Notes
122 Illustration 24



ATT

2. Advantages and Limitations

a Quadrats, point sampling, and step point methods can all be used to calculate
composition.

b The repeatability of determining composition depends on the attribute col-
lected and the method used.

c Sensitivity to change is dependent on the attribute used to calculate composition.
For instance, if plant biomass is used to calculate composition, the values can
vary with climatic conditions and the timing of climatic events (precipitation,
frost-free period, etc.). Composition based on basal cover, on the other hand,
would be relatively stable.

d Composition allows the comparison of vegetation communities at various
locations within the same ecological sites.



APPENDIX B

1,

b The next characters are the township number (3, 16, etc.) followed by the
range number (7, 32, etc.) and the section number (8, 21, etc.).

c The next three characters are used to identify the subdivisions within a section
(down to 10 acres) in which a study is located. These subdivisions have letter
designations as follows:

bla
a a
—s- d A
c | d
8
Cc D

d The last character(s) is (are) simply a series number (1, 2,3,... 10, 11, etc.)
assigned to a study based on the number of studies located within the smallest
subdivision.

e For example, Studies 1 and 2 located in the SE1/4NE1/4NW1/4 of Section 8,
T3S, R21E would be numbered (D-3-21)8Bad-1 and (D-3-21)8Bad-2.

f Depending on the local situation, this scheme can be modified by adding
characters to the code where there are fractional townships or ranges, where
there are more than 99 sections/tracts within a township, and/or where there is
more than one public land survey principal meridian and baseline within the
area of jurisdiction.

B. Identifying Photographs In most cases, the number that has been assigned
to a study is the number used to identify the photographs associated with that study.
Following is a description of three labels that can be used to include the study number
in the photographs:

Label 1 The Photo Identification Label included as Appendix C can be copied
and used to identify photographs. This label provides space for documenting the
date, number, and location (Resource Area, allotment, and pasture) of a study. A
large black felt-tip marking pen should be used to print the information on the label.

Label 2 A slotted sign board with a black felt background and movable white
plastic letters can be used as a photo identification label. Room permitting, the
user may include any information desired on such a label. A 9- x 12-inch board
with slots running lengthwise at a spacing of 1/4-inch and 1-1/2-inch white letters
makes a highly visible label for most photographs.



INTRODUCTION

selecting key species to ensure that data needs of the various resources are met.
In addition, interested publics should be invited to participate, as appropriate, in
selecting these species (see Section II.G).

b Considerations in Selecting Key Species The following points should be
considered in selecting key species:

¢ Changes in density, frequency, reproduction, etc., of key species on key areas
are assumed to reflect changes in these species on the entire stratum.

¢ The forage value of key species may be of secondary or no importance. For
example, watershed protection may require selection of plants as key species
which protect the watershed but are not the best forage species. In some
cases, threatened, endangered, or sensitive species that have no particular
forage value may be selected as key species.

¢ Any foraging use of the key species on key areas is assumed to reflect forag-
ing use of that species on the entire stratum.

© Depending on the selected management strategy and/or periods of use, key
species may be foraged during the growing period, after maturity, or both.

¢ In areas of yearlong grazing use and in areas where there is more than one
use period, several key species may be selected to sample. For example, on
an area with both spring and summer grazing use, a cool season plant may be
the key species during the spring, while a warm season plant may be the key
species during the summer.

© Selection of several key species may be desirable when adjustments in livestock
grazing use are anticipated. This is especially true if more than one plant species
contributes a major portion of the forage base of the animals using the area
(Smith 1965).

c Key Species on Depleted Rangelands The key species selected should be
present on each key area on which monitoring studies are conducted; however,
on depleted rangelands these species may be sparse or absent. In this situation
it may be necessary to conduct monitoring studies on other species. Data
gathered on non-key species must be interpreted on the basis of effects on the
establishment and subsequent response of the key species. It should also be
verified that the site is ecologically capable of producing the key species.

General Observ. AtiONS General observations can be important when con-
ducting evaluations of grazing allotments, wildlife habitat areas, wild horse and burro
herd management areas, watershed areas, or other designated management areas.

Such factors as rodent use, insect infestations, animal concentrations, fire, vandalism,
and other uses of the sites can have considerable impact on vegetation and soil re-
sources. This information is recorded on the reverse side of the study method forms or
on separate pages, as necessary.



OSSARY

resource value ratings. Trends in resource value ratings for several uses on the same site at
a given time may be in different directions, and there is no necessary correlation between
trends in resource value ratings and the trend in ecological status.

U

understory: plants growing beneath the canopy of other plants; usually refers to grasses,
forbs, and low shrubs under a tree or shrub canopy.

unsuitable rangeland: rangeland which has no potential value for, or which should not be
used for, a specific use because of permanent physical or biological restrictions. When
unsuitable rangeland is identified, the identification must specify what use or uses are
unsuitable (e.g., “unsuitable for cattle grazing”).

useable forage: that portion of forage that can be grazed without damage to the basic
resources; may vary with season of use, species, and associated species.

utilization: the proportion or degree of the current year’s forage production by weight that
is consumed or destroyed by animals (including insects). The term may refer either to a
single plant species, a group of species, or the vegetation community as a whole.
Utilization is synonymous with use.

Vv

vegetation: plants in general, or the sum total of the plant life above and below ground in
an area,

vegetation hit: a point on vegetation, either basal or canopy, where the tip of the pin or the
crosshairs in a sighting device intersect a leaf, stem, or other portion of the plant. Lichens
and mosses must exceed 1/16 of an inch in thickness to qualify as a vegetation hit. Li-
chens and mosses less than 1/16-inch in thickness growing on rock are considered as rock;
if they are growing on bare ground, they are considered as persistent litter.

vegetation type: a kind of existing plant community with distinguishable characteristics
described in terms of the present vegetation that dominates the aspect or physiognomy of
the area.

vigor: relates to the relative robustness of a plant in comparison to other individuals of the
same species. It is reflected primarily by the size of a plant and its parts in relation to its
age and the environment in which it is growing.

W

warm season species: plants whose major growth occurs during the spring, summer, or fall
and that are usually dormant in winter.

wet meadow: a meadow where the surface remains wet or moist throughout the summer,
usually characterized by sedges and rushes.

137



Robel, R.J., JIN. Briggs, A.D. Dayton, and L.C. Hulbert. 1970. Relationships Between
Visual Obstruction Measurements and Weight of Grassland Vegetation, J. Range
Manage. 23:295.

Robel, R.J. 1970. Possible Role of Behavior in Regulating Greater Prairie Chickens’ Populations,
J. Wildlife Manage. Vol 34:306-312.

Rossiter, R.C. 1966. Ecology of the Mediterranean annual-type pasture. Advances in
Agronomy 18:1-56.

Salzer, D. 1994. An introduction to sampling and sampling design for vegetation
monitoring. Unpublished papers prepared for Bureau of Land Management Training
Course 1730-5, BLM Training Center, Phoenix, AZ.

Sampson, Arthur W. 1952. Range management - principles and practices. John Wiley and
Sons, New York, NY. 570 p.

Schaeffer, R.L., W. Mendenhall, and L. Ott. 1979. Elementary survey sampling. Duxbury
Press, North Scituate, MA.

Schmutz, Ervin M. 1978. Let’s put manage in range management. Rangeman’s Journal
5:185-188.

Schultz, Arnold M., Robert P. Gibbens, and Leonard DeBano. 1961. Artificial populations
for teaching and testing range techniques. J. Range Manage. 14:236-242.

Schwartz, Chas. C., Edward C. Thor, and Gary H. Elsner. 1976. Wildlands planning glossary.
US. Dept. of Agr., For. Ser., Pacific Southwest For. and Range Exp. Sta., Berkeley,
Calif, Gen. Tech. Rept. PSW-13. 252 p.

Seher, J. Scott and Paul T. Tueller. 1973. Color aerial photos for marshland. Photogrammetric
Engineering 39:489-499.

Smith, A.D. 1944. A study of the reliability of range vegetation estimates. Ecology
25:441-448.

. 1965. Determining common use grazing capacities by application of the key
species concept. J. Range Manage. 18:196-201.

Smith, J.G. 1959. Additional modifications of the point frame. J. Range Manage.
12:204-205.

Smith, Stuart D. 1982. Evaluation of the frequency plot method as an improved technique
for measuring successional trend. M.S. Thesis. Univ. of Idaho, Moscow, ID. 95 p.

Snedecor, George W. and William C. Cochran. 1974. Statistical methods. Iowa State
University Press, Ames, IA. 573 p.

Snyder, W.D. 1991. Wheat stubble as nesting cover for ring necked pheasants in northern
Colorado. Wildlife Soc. Bulletin vol 19:4.

re



Page—/_of 4

Study Location & Documentation Data

Study Method Daubenmire Trend py a _o@

Allotment Name & Number Quaking Aspen -//037 Pasture Sheep Creek

District Howe Resource Area Lost (Tour fain

Ecological Seriayey .y5-/9"Worthern Plains \PlantCommunity pare 2 — 46SP- POES

Date Established Established by (Name) Map Reference
7/24/24 Chariie Wagon Graystone 72min. /apo.

Elevation Slope Exposure Aerial Photo Reference
4200 Flat Kast BLM -2YCN-AZTIA-~ Y/22f7F

Township Range Section 1/4 1/4 14
3s 27W 8 NW SE WW Scale:_2 inches

Location equals one mile

Key Species

1 AGSP 2 PONE 3 3

Distance and bearing between reference post or reference point and the transect
location stake, beginning of transect, or plot

The transect (ocation stake (g (0074, south (180) of the
reference post. feeference post is Zmiles west of Redtop Reservein

Distance and bearing between location stake and bearing stake (a2 feet at 195°

Transect Bearing Vertical Distance Between Ground & Aligned Tape
3 frches

Length of Transect JOO Feet Plot/Frame Size 20x50 cn - 6 cover classes

i Eeaty 2 ft. beginnig at the [-foot mark on Ha f |
Samplin Interval vey, tL Legene 8 ine Foams ah coery Total Number of Samples 50
|_ 20 pe Sige ©, ‘ae »

Notes (Description of study location, diagram of transect/plot layout, description of photo points, etc. If more
space is needed, use reverse side or another page.)
The twve photo plots are located at G7 and 53 feet along rhe ape .
Close-up photos are taken from fhe northeast siae of the photo plots .

Note: Depending on the study method, fill in the blocks that apply when a study is established. This
documentation enables the examiners to conduct follow-up studies in a consistant manner to provide
comparable data for analysis, interpretation, and evaluation.



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illustration 4



INTRODUCTION

represent the “pulse” of the rangeland. Proper selection of key areas requires
appropriate stratification. Statistical inference can only be applied to the stratifica-
tion unit.

a Selecting Key Areas The most important factors to consider when selecting
key areas are the management objectives found in land use plans, coordinated
resource management plans, and/or activity plans. An interdisciplinary team
should be used to select these areas. In addition, permittees, lessees, and other
interested publics should be invited to participate, as appropriate, in selecting
key areas. Poor information resulting from improper selection of key areas leads
to misguided decisions and improper management.

b Criteria for Selecting Key Areas The following are some criteria that should
be considered in selecting key areas. A key area:

¢ Should be representative of the stratum in which it is located.
¢ Should be located within a single ecological site and plant community.
¢ Should contain the key species where the key species concept is used.

© Should be capable of and likely to show a response to management actions.
This response should be indicative of the response that is occurring on the
stratum.

c Number of Key Areas The number of key areas selected to represent a stratum
ideally depends on the size of the stratum and on data needs. However, the
number of areas may ultimately be limited by funding and personnel constraints.

d Objectives Objectives should be developed so that they are specific to the key
area. Monitoring studies can then be designed to determine if these objectives are
being met.

e Mapping Key Areas Key areas should be accurately delineated on aerial
photos and/or maps. Mapping of key areas will provide a permanent record of
their location.

E. Key Species Key species are generally an important component of a plant
community. Key species serve as indicators of change and may or may not be forage
species. More than one key species may be selected for a stratum, depending on
objectives and data needs. In some cases, problem plants (poisonous, etc.) may be
selected as key species. Key species may change from season to season.

The process used to select key species should be documented. Documentation should
include the management objectives, the criteria used for selecting species, and the kinds
of comparisons or interpretations expected to be made from them.

a Selecting Key Species Selection of key species should be tied directly to
objectives in land-use plans, coordinated resource management plans, and
activity plans. This selection depends upon the plant species in the present
plant community, the present ecological status, and the potential natural com-
munities for the specific sites. An interdisciplinary team should be used in



ececeee

One transect location stake: 3/4 - or 1-inch angle iron not less than 16 inches
long

Hammer

Tally counter (optional)

Compass

Steel post and driver

Tape: 50-, 100-, or 200-foot delineated in tenths and hundreds or a metric tape
of the desired length.

. Training A minimum amount of training is needed for this method. Examiners
must be able to identify the plant species and be able to tell whether or not a
species occurs, according to study specifications, within a quadrat. Examiners
must be familiar with the cover categories and how to collect cover data using the
tines on the quadrat frame.

. Establishing Studies Careful establishment of studies is a critical element in
obtaining meaningful data (see Section III).

a

Site Selection The most important factor in obtaining usable data is selecting
representative areas (critical or key areas) in which to run the study (see Sec-
tions II.D). Study sites should be located within a single plant community
within a single ecological site. Transects and sampling points need to be randomly
located within the critical or key areas (see Section III).

Pilot Studies Collect data on several pilot studies to determine the number of
samples (transects or observation points) and the number and size of quadrats
needed to collect a statistically valid sample (see Section III.B.8).

Selecting Quadrat Size The selection of quadrat size is important and de-
pends on the characteristics of the vegetation to be sampled (see Section III.B.6).

(1) Asa rule of thumb, it is expected that all frequency percentages for impor-
tant species should fall between 10 and 90 percent or, if possible, between
20 and 80 percent. This will provide the greatest possible chance for
detecting an important trend for a species when the study is read again.
Use a frame size that will produce frequencies falling in this range for the
greatest number of species possible.

(2) To build a sample frame, see Illustration 6, which shows an example of a
frequency frame.

(3) Use the same size quadrat throughout a study and for rereading the study.
If frequencies for a specific species approach the extremes of either 0 or
100 percent, it may be necessary to use a different sized quadrat for that
species. The nested plot concept would be suitable in this instance.

d Nested Plot Technique The use of one size plot is usually not adequate to

collect frequency data on all the important species within a community. For
each species occurring on a site, there is a limited range of plot sizes capable of
producing frequency percentages between 20 and 80 percent. A plot size
appropriate for one species may not be appropriate for another. The nested plot



METHODS—Comparative Yield

ie}

(2)

(3)

@)

(2)

(3)

(4)

Five reference quadrats are subjectively located. References ] and 5 are
located first. The first quadrat (reference 1) is placed in a low-yielding area
which represents the low-yielding situations commonly encountered on the
site (avoid bare or nearly bare quadrats). Reference 5 is determined by
placing a quadrat on a high-yielding area, excluding unusually dense
patches of vegetation which would have a rare chance of being sampled.
The examiner should make a mental note of the amount of production in
each of the reference quadrats. These references are then clipped and
weighed. If the clipped weight in reference 5 is more than five times the
weight found in reference 1, then two new sites should be selected as
references ] and 5. In establishing the initial reference quadrats, the
weight in reference 5 is usually too high and the weight in reference 1 is
too low. Make sure reference 5 does not represent a rare situation. When
references 1 and 5 have been selected, reference 3 is located by placing a
frame in an area considered to have a yield halfway between references 1
and 5. References 2 and 4 are located the same way by selecting the mid-
point yield between references ] and 3 and references 3 and 5, respectively.

All five reference quadrats are clipped and weighed to compare the refer-
ence quadrats to a linear distribution of quadrat weights. This process is
repeated by clipping additional quadrats until the weights of the five
reference quadrats are approximately linear and observers are confident in
their ability to rank quadrats relative to one of the five references. If the
rankings are not linear, the precision of the method will be reduced. If
more than five percent of the quadrats have no production, then a larger
quadrat frame should be used.

In areas with less than 500 Ib/ac, small quadrats are difficult to evaluate. In
these situations, larger quadrats should be used or three reference quadrats
should be established instead of five.

b Collecting the Data

Start a transect by randomly locating the first quadrat along the transect
bearing.

Read additional quadrats at specified intervals. To change the length of the
transect, increase the number of paces between quadrats.

For each quadrat, compare the total yield in the quadrat to the references
and record the appropriate rank by dot count tally. It is appropriate to
assign intermediate ranks if the yield is at the midpoint between two
references. For example, if a quadrat has a yield between references | and 2,
assign a rank of 1.5. If a quadrat yield greatly exceeds the yield of refer-
ence 5, then a higher rank may be estimated. For example, if a quadrat is
50% greater than reference 5, a rank of 7 could be recorded. If more than
five percent of the quadrats are ranked above 5, the references were not
properly selected.

To calibrate the ranks, several quadrats representing each reference should
be clipped and weighed independently of the transect. The total yield in



STUDY DESIGN AND ANALYS|

8. Pilot Studies The purposes of pilot studies are to select the optimum size and/
or shape of the sampling unit for the study and to determine how much variability
exists in the population being sampled. The latter information is necessary to
determine the sample size necessary to meet specific management and monitoring
objectives.

a Initial Considerations Before beginning the actual pilot study, subjectively
experiment with different sizes and shapes of sampling units. For example, if
estimating density, subjectively place quadrats! of a certain size and shape in
areas with large numbers of the target plant species. Then see how many plants
fall into the quadrat and ascertain if this is too many to count. See what kind of
problems there might be with edge effect: when individuals fall on or near one
of the long edges of the quadrat, will it be difficult for examiners to make
consistent calls as to whether these individuals are in or out of the quadrat??

See if there is a tendency to get more plants in rectangular quadrats when they
are run one way as opposed to another. If so, then the quadrats should be run in
the direction that hits the most plants. Otherwise it is likely that some quadrats
will have few to no plants in them, while others will have many; this is highly
undesirable. The goal should be to end up with similar numbers of plants in
each of the quadrats, while still sampling at random.

If transects or lines are the sampling units, subjectively lay out lines of different
lengths and in different directions. See if the lines cross most of the variability
likely to be encountered with respect to the target plant species. If not, they
may need to be longer. Don’t make the lines so long, however, that it will be
difficult to measure them, especially if there are a lot of lines involved. As with
rectangular quadrats, it is desirable to have each of the lines encountering
similar numbers and/or cover values of the target species, while still sampling at
random.

b Efficiency of Sample Design Pilot sampling allows the examiner to compare
the efficiency of various sampling designs. By dividing the sample standard
deviation by the sample average, the coefficient of variation is obtained.
Comparing coefficients of variation allows one to determine which of two or
more sampling designs is most efficient (the lower the coefficient of variation,
the greater the efficiency of the sampling design).

Conduct a pilot study by randomly positioning a number of sampling units of
different sizes and shapes within the area to be sampled and then choosing the
size and shape that yields the smallest coefficient of variation.

L

Note that it is not necessary to construct an actual frame for the quadrats used. It is sufficient to delineate
quadrats using a combination of tape measures and meter (or yard) sticks. For example, a 5m x 0.25 m
quadrat can be constructed by selecting a 5 m interval along a meter tape, placing two 1-meter sticks perpen-
dicular to the tape at both ends of the interval (with their zero points at the tape), and laying another tape or
rope across these two sticks at their 0.25 m points, This then circumscribes a quadrat of the desired size and
shape.

Often, problems with edge effect can be largely overcome by making a rule that any plants that fall on the left
or top edges of the quadrat are counted, whereas any plants that fall on the right or bottom edges of the
quadrat are not counted.



STUDY DESIGN AND ANALYSIS

Because the quadrats are being placed with their long side parallel to
the x-axis, the coordinates are ordered first by the x-axis and next by
the y-axis. Thus the new order is as follows:

X-axis y-axis
1. 16.0m 28.0 m
2. 48.0 m 8.0m
3. 48.0 m 27.0m
4, 64.0m 34.0 m

In each column defined by an x-coordinate, sampling starts from the
bottom of the macroplot and moves to the top. This systematic
approach ensures that quadrats are not walked on until after they have
been read.

c Linear This study design samples a study site in a straight line. Because it
samples such a small segment of the sample area, this technique is not
recommended except for long, narrow study sites such as riparian areas.

Randomly select the beginning point of the transect within the study site and
mark it with a stake to permanently locate the transect (figure 4}. Randomly
determine the transect bearing and select a prominent distant landmark such as
a peak, rocky point, etc., that can be used as the transect bearing point. Vegeta-
tion attribute readings are taken at a specified interval (paced or measured)
along the transect bearing. If the examiner is unable to collect an adequate
sample with this transect before leaving the study site, additional transects can
be run from the transect location stake at different bearings.

B. Statistical Considerations

1. Target Population Study sites are selected (subjectively) that hopefully reflect
what is happening on a larger area. These may be areas that are considered to be
representative of a larger area such as a pasture (see Section II.D.2 for more discus-
sion of key areas) or critical areas such as sites where endangered species occur.
Monitoring studies are then located in these areas. Since these study sites are
subjectively selected, no valid statistical projections to an entire allotment are
possible. Therefore, careful consideration and good professional judgement must
be used in selecting these sites to ensure the validity of any conclusions reached.

a Although it would be convenient to make inferences from sampling study sites
regarding the larger areas they are chosen to represent, there is no way this can be
done in the statistical sense because the study sites have been chosen subjectively.

b For this reason it is important to develop objectives that are specific to these
study sites. It is equally important to make it clear what actions will be taken
based on what happens on the study sites.

¢ Itis also important to base objectives and management actions on each study site
separately. Values from study sites from different strata should never be averaged.



I. INTRODUCTION

Identifying the appropriate sampling technique first requires the identification of the proper
vegetation characteristic or attribute to measure. To do this the examiner must consider
objectives, life form (grass, forb, shrub, or tree), distribution patterns of individuals of a
species, distribution patterns between species (community mosaic pattern), efficiency of data
collection from an economic standpoint, and accuracy and precision of the data.

Permittees, lessees, other rangeland users, and interested publics should be consulted and
encouraged to participate in the collection and analysis of monitoring data. Those individuals
or groups interested in helping to collect data should be trained in the technique used in the
specific management unit.

This document deals with the collection of vegetation data. The interpretation of that data
will be addressed in other documents. This document does not address interpreting vegeta-
tion data for adjusting livestock numbers or making other management decisions.

A. Terms and Concepts The following terms require an expanded discussion
beyond the scope of the Glossary of Terms:

1. Inventory Inventory is the systematic acquisition and analysis of information
needed to describe, characterize, or quantify vegetation. As might be expected,
data for many different vegetation attributes can be collected. Inventories can be
used not only for mapping and describing ecological sites, but also for determining
ecological status, assessing the distribution and abundance of species, and establish-
ing baseline data for monitoring studies.

2. Population A population (used here in the statistical, not the biological, sense)
is a complete collection of objects (usually called units) about which one wishes to
make statistical inferences. Population units can be individual plants, points, plots,
quadrats, or transects.

3. Sampling Unit A sampling unit is one of a set of objects in a sample that is
drawn to make inferences about a population of those same objects. A collection
of sampling units is a sample. Sampling units can be individual plants, points,
plots, quadrats, or transects.

4, Sample A sample is a set of units selected from a population used to estimate
something about the population (statisticians call this making inference about the
population). In order to properly make inferences about the population, the units
must be selected using some random procedure (see Interagency Technical Refer-
ence, Planning for Monitoring). The units selected are called sampling units.

5. Sampling Sampling is a means by which inferences about a plant community
can be made based on information from an examination of a small proportion of
that community. The most complete way to determine the characteristics of a
population is to conduct a complete enumeration or census. In a census, each
individual unit in the population is sampled to provide the data for the aggregate.
This process is both time-consuming and costly. It may also result in inaccurate



a
N. Other Methods

1. Weight Estimate and Ocular Reconnaissance Methods Both of these
methods were commonly used to determine forage production prior to the imple-
mentation of the Ecological Site Inventory Method. They both involved determin-
ing the production on all species, which could then be used to calculate species
composition and total production. Although they are no longer widely used
techniques, written description for completing each can be found in BLM’s Range-
land Inventory and Monitoring Supplemental Studies, Technical Reference 4400-5.

2. Community Structure Analysis Method This technique is used by very
few field offices. It will be moved to BLM’s Technical Reference 4400-5 in a

future revision.

3. Photo Plot Method This technique requires many quadrats for each study site
in order to provide statistically reliable data. Since this technique is very time
consuming, it is no longer used in most field offices. It will be moved to BLM’s
Technical Reference 4400-5 in a future revision.



METHODS—Double Weight Sampling

Pechanec, JR. and G.D. Pickford. 1937. A weight-estimate method for the deter-
mination of range or pasture production. J. Amer. Soc. Agron. 29:894-904.

Riser, Paul G. 1984. Methods for Inventory and Monitoring of Vegetation, Litter,
and Soil Surface Condition. Developing Strategies for Rangeland Monitoring.
National Research Council National Academy of Sciences.

USDA, Soil Conservation Service. 1976. National Range Handbook. 154 p.

USDI, Bureau of Land Management. 1984 (rev. 1990). National Range Handbook
4410-1. Washington, D. C.

Van Dyne, George M., W.G. Vogel, and H.G. Fisser. 1963. Influence of small plot
size and shape on range herbage production estimates. Ecology 44:746-759.



Hanley, Thomas A. 1978. A comparison of the line-interception and quadrat
estimation methods of determining shrub canopy coverage. J. Range Manage.
31:60-62.

Kinsinger, Floyd E., Richard E. Eckert, and Pat 0. Currie. 1960. A comparison of
the line-interception, variable-plot, and loop methods as used to measure
shrub-crown cover. J. Range Manage. 13:17-21.

USDI, Bureau of Land Management. 1985. Rangeland monitoring - Trend studies
TR4400-4.

METHODS—tine Intercept



Y DESIGN AND ANALYSIS -

C. Other Important Considerations

1. Sampling All Species Although the key species concept is important in ana-
lyzing and evaluating management actions, other species should also be considered
for sampling. Whenever possible, all species should be sampled, especially on the
initial sampling. It is also important to record sampling data by individual species
rather than by genera, form class, or other grouping. These data can be lumped
later during the analysis if appropriate. Both of these approaches will provide
greater flexibility in data analysis if objectives or key species change in the future.

2. Plant Species Identification The plant species must be properly identified in
order for the data to be useful in grazing allotment, wildlife habitat area, herd
management area, watershed area, or other designated management area evalua-
tions. In some cases, it may be helpful to include pressed plant specimens, photo-
graphs, or other aids used for species identification in the study file. If data are
collected prior to positive species identification, examiners should collect plant
specimens for later verification.

3. Training The purpose of training is to provide resource specialists with the
necessary skills for implementing studies and collecting reliable, unbiased, and
consistent data. Examiners should understand data collection, documentation,
analysis, interpretation, and evaluation procedures, including the need for
uniformity, accuracy, and reliable monitoring data.

Training should occur in the field by qualified personnel to ensure that examiners are
familiar with the equipment and supplies and that detailed procedural instructions
are thoroughly demonstrated and understood.

As a follow-up to the training, data collected should be examined early in the
study effort to ensure that the data are properly collected and recorded.

Periodic review and/or recalibration during the field season may be necessary for
maintaining consistency among examiners because of progressive phenological
changes. Review and recalibration during each field season are especially important
where data collection methods require estimates rather than direct measurements.



Floyd, D.A. and J.E. Anderson. 1983. A new point interception frame for estimating cover
of vegetation. Idaho National Engineering Laboratory Radioecology and Ecology Pro-
grams 1983 Progress Report, pp. 107-113.

. 1987. A comparison of three methods for estimating plant cover. Journal of
Ecology 75: 229-245.

Francis, Richard E., Richard S. Driscoll, and Jack N. Reppert. 1972. Loop-frequency as
related to plant cover, herbage production, and plant density. U.S. Dept. of Agr., For.
Ser., Rocky Mtn. For. and Range Exp. Sta., Ft. Collins, CO. Research Paper MA-94. 15 p.

Freese, Frank. 1962. Elementary forest sampling. U.S. Dept. of Agr., For. Ser., Agr. Hand-
book No. 232. 91 p.

—. 1967. Elementary statistical methods for foresters. U.S. Dept. of Agr., For. Ser.,
Agr. Handbook No. 317. 87 p.

Goldstein, R. 1989. Power and sample size via MS/PC-DOS computers. American
Statistician 43:253-260.

Goodall, D.W. 1952. Some considerations in the use of point quadrats for the analysis of
vegetation. Aust. J. Sci. Res., Series B 5:1-41.

Greig-Smith, P. 1983. Quantitative plant ecology. 3rd Ed. University of California Press,
Berkeley and Los Angeles, CA.

Hanley, Thomas A. 1978. A comparison of the line-interception and quadrat estimation
methods of determining shrub canopy coverage. J. Range Manage. 31:60-62.

Hansen, Herbert C. 1962. Dictionary of ecology. Bonanza Books, Crown Publishers, Inc.,
New York. 382 p.

Harniss, Roy 0. and Robert B. Murray. 1976. Reducing bias in dry leaf weight estimates of
big sagebrush. Jr. Range Manage. 29:430-432.

Hart, R.H. 1980. Determining a proper stocking rate for a grazing system. In: Proceedings,
Grazing Management Systems for South West Rangelands Symposium, Range
Improvement Task Force, New Mexico State Univ., Las Cruces, NM, pp.49-64.

Heady, Harold F. 1961. Continuous vs. specialized grazing systems: a review and application
to the California annual type. J. Range Manage. 14:182-193.

Heintz, T.W., J.K. Lewis, and S.S. Waller. 1979. Low-level aerial photography as a management
and research tool for range inventory. J. Range Manage. 32:247-249.

Hewitt, George B., Ellis W. Huddleston, Robert J. Lavigne, Darrell N. Ueckert, and J. Gordon
Watts. 1974. Rangeland entomology. Society for Range Management, Range Science
Series No. 2. 127 p.

141



STUDY DESIGN AND ANALYSIS

A. Planning the Study Proper planning is by far the most important part of a
monitoring study. Much wasted time and effort can be avoided by proper planning.
A few important considerations are discussed below. The reader should refer to the
Technical Reference, Planning for Monitoring, for a more complete discussion of these
important steps.

1. Identify Objectives Based on land use and activity plans, identify objectives
appropriate for the area to be monitored. The intent is to evaluate the effects of
management actions on achieving objectives by sampling specific vegetation
attributes.

2. Design the Study The number of quadrats, points, or transects (sample size)
needed depends on the objectives and the efficiency of the sampling design. It should
be known before beginning the study how the data will be analyzed. The frequency of
data collection (e.g., every year, every other year, etc.) and data sheet design should be
determined before studies are implemented. The sample data sheets included
with each method (following the narrative) are only examples of data forms. Field
offices have the option to modify these forms or develop their own.

All of the methods described in this document can be established using the following
techniques:

a Baseline A baseline is established by stretching a tape measure of any desired
length between two stakes (figure 1). For an extremely long baseline, interme-
diate stakes can be used to ensure proper alignment. It is recommended that
metric measurement be used. Individual transects are then run perpendicular
to the baseline at random locations along the tape. The location of quadrats
along these transects can be either measured or paced. Transects can all be run
in the same direction, in which case the baseline forms one of the outer bound-
aries of the sampled area, or in two directions, in which case the baseline runs
through the center of the sampled area. If transects are run in two directions,
the direction for each individual transect should be determined randomly.
(Directions for randomly selecting the location of transects to be run off of a
baseline using a random numbers table are given in Appendix D). Quadrats or
observation points are spaced at specified distances along the transect. This
study design is intended to randomly sample a specified area. The area to be
sampled can be expanded as necessary by lengthening the baseline and/or
increasing the length between quadrats or sampling points.

This design may need to be modified for riparian areas or other areas where the
area to be sampled is long and narrow. For these areas, a single linear transect
may be more appropriate.

b Macroplot The concept with this type of design is to allow every area within
the study site or sample area to have an equal chance to be sampled. A
macroplot is a large square or rectangular study site. The size of the macroplot
will depend on the size of the study site. The macroplot should encompass
most of the study site. From the standpoint of statistical inference, it is best,
once the macroplot boundaries have been determined, to redefine the study site
to equal the macroplot. Examples of macroplot sizes are 50 m x 100 m, 100 m
x 100 m, and 100 m x 200 m, but much larger macroplots can be used to cover
larger study sites. Macroplot size and shape should be tailored to each situation.



REFERENCES
VII. REFERENCES

Barrett, James P. and Mary E. Nutt. 1979. Survey sampling in the environmental sciences: a
computer approach. COMPress, Inc., Wentworth, NH. 319 p.

Biswell, H.H. 1956. Ecology of California grasslands. J. Range Manage. 9:19-24.

Blaisdell, James P. 1958. Seasonal development and yield of native plants on the upper
Snake River plains and their relation to certain climatic factors. U.S. Dept. of Agr., For.
Ser., Tech. Bul. No. 1190. 68 p.

Bonham, C.D. 1989. Measurements for Terrestrial Vegetation, John Wiley and Sons, 338 p.

Brown, Dorothy. 1954. Methods of surveying and measuring vegetation. Commonwealth
Bureau of Pastures and Field Crops. Bulletin No. 42. Commonw. Agr. Bur., Farmham
Royal, Bucks, England. 223 p.

Brown, B.W., C. Brauner, A. Chan, D. Gutierrez, J. Herson, J. Lovato, and J. Polsley. 1993.
STPLAN, Version 4.0. University of Texas, M.D. Anderson Cancer Center, Department
of Biomathematics, Houston, TX.

Brun, Jorge M. and Thadis W. Box. 1963. Comparison of line intercepts and random point
frames for sampling desert shrub vegetation. J. Range Management. 16:21-25.

Buckner, D.L. 1985. Point-intercept sampling in revegetation studies; maximizing objectivity
and repeatability. Proceedings of the American Society of Surface Mining and Reclamation.
1985 Annual Meeting, Denver, CO.

Call, Mayo W. 1981. Terrestrial wildlife inventories - some methods and concepts. U.S.
Dept. of the Interior, BLM Tech. Note No. 349. 17] p.

Canfield, R.H. 1941. Application of the line interception method in sampling range
vegetation. J. Forestry 39:388-394.

—. 1944. Measurement of grazing use by the line intercept Method. Jour. For.
42(3):192-194.

Chambers Jeanne C., Ray W. Brown. 1983. Methods for Vegetation and Analysis on
Revegetated Mined Lands. USDA, Forest Service General Technical Note INT-151. 57 p.

Clark, Ronnie. 1980. Erosion condition classification system. U.S. Dept. of the Interior,
BLM Tech. Note No. 346. 47 p.

Cochran, William G. 1977. Sampling Techniques. John Wiley & Sons, Inc. New York, NY.

Cohen, J. 1988. Statistical power analysis for the behavioral sciences. Lawrence Erlbaum
Associates, Hillsdale, NJ.

Cook, C. Wayne and James Stubbendieck. 1986. Range Research: Basic Problems and
Techniques. Society for Range Management. Denver, CO.



ATTRIBUTES

or comparing seedlings to mature plants. Density on rhizomatous or stolonifer-
ous plants is determined by counting the number of stems instead of the num-
ber of individuals. Seedling density is directly related to environmental condi-
tions and can often be interpreted erroneously as a positive or negative trend
measurement. Because of these limitations, density has generally been used
with shrubs and not herbaceous vegetation. Seedlings and mature plants should
be recorded separately.

If the individuals can be identified, density measurements are repeatable over
time because there is small observer error. The type of vegetation and distribu-
tion will dictate the technique used to obtain the density measurements. In
homogenous plant communities, which are rare, square quadrats have been
recommended, while heterogenous communities should be sampled with
rectangular or line strip quadrats. Plotless methods have also been developed
for widely dispersed plants.

D. Production

1. Description Many believe that the relative production of different species in a
plant community is the best measure of these species’ roles in the ecosystem.

The terminology associated with vegetation biomass is normally related to
production.

a Gross primary production is the total amount of organic material produced,
both above ground and below ground.

b Biomass is the total weight of living organisms in the ecosystem, including
plants and animals.

c Standing crop is the amount of plant biomass present above ground at any given
point.

d Peak standing crop is the greatest amount of plant biomass above ground
present during a given year.

e Total forage is the total herbaceous and woody palatable plant biomass available
to herbivores,

f Allocated forage is the difference of desired amount of residual material subtracted
from the total forage.

g Browse is the portion of woody plant biomass accessible to herbivores.
2. Advantages and Limitations
a Biomass and gross primary production are rarely used in rangeland trend studies

because it is impractical to obtain the measurements below ground. In addition,
the animal portion of biomass is rarely obtainable.





being sampled. As a general rule of thumb long, thin quadrats are better
(often very much better) than circles, squares, or shorter and wider quad-
rats (Krebs 1989). How narrow the quadrats can be depends upon consid-
eration of measurement errors due to edge effect, but these problems can
be largely overcome by incorporating rules for determining whether a plant
falls inside or outside a quadrat (discussed in more detail under Sampling
Process below).

(a) Subjectively place quadrats’ of a certain size and shape in areas with
large numbers of the target plant species. See how many plants fall into
the quadrat and ask if this is too many to count. See what kind of
problems there might be with edge effect: when individuals fall on or
near one of the long edges of the quadrat, will it be difficult for examin-
ers to make consistent calls as to whether these individuals are in or out
of the quadrat? See if there is a tendency to get more plants in rectan-
gular quadrats when they are run one way as opposed to another.

(b) Determine the standard deviations of those quadrat sizes and shapes
deemed to be practical from the subjective examination described
above (see Section III.B.8.b).

(c) Choose the quadrat size and shape with the smallest standard deviation.

(2) Direction of quadrats Determine if there is an environmental gradient
affecting the density of the target species in the key area. Examples of
such gradients are elevation and moisture. If there is a gradient, the study
should be set up so that the long side of each quadrat is placed perpendicu-
lar to this gradient. This ensures that there is more variability within each
quadrat than there is between quadrats.

Subjectively placing quadrats in different directions as described under
6.b.(1)(a) above can assist in making this determination. For example, if
quadrats laid out with the long side going north-south tend to have no or
fewer plants of the key species than quadrats with the long side going east-
west, the east-west position should be selected.

c Study Layout Data can be collected using the baseline, macroplot or linear
study designs described in Section III.A.2 beginning on page 8. The macroplot
technique is the recommended procedure.

d Reference Post or Point Permanently mark the location of each study with a
reference post and a study location stake (see beginning of Section III).

=

7 Note that it is not necessary to construct an actual frame for the quadrats used. It is sufficient to delineate

quadrats using a combination of tape measures and meter (or yard) sticks, For example, a 5m x 0.25 m
quadrat can be constructed by selecting a S m interval along a meter tape, placing two 1-meter sticks perpen-
dicular to the tape at both ends of the interval (with their zero points at the tape), and laying another tape or
rope across these two sticks at their 0.25 m points. This then circumscribes a quadrat of the desired size and

shape. Alternately place a meter stick perpendicular to the tape at one end of the interval. The meter stick is
then moved slowly up the interval and all plants of the species occurring within the first 0.25 m of the meter
stick recorded until the end of the interval is reached.





Cover Board Method
Density Board

Page —_of ___

Study Number Date

Examiner

Allotment Name & Number

Pasture

Density Board Location -

Percent Cover
Plot 1 Plot 2 Plot 3

Plot 4

Avg. Cover

Total Average Cover-

Illustration 18



Baseline End Point Stake ——>@

Photo plots may be

permanently located
anywhere along the
baseline tape.

OOoogonuoooon go

OoOogodagaunurunu ono

Transect 3

OOoOoo0odod0g00

Transect 2

OOo0d080od000

Baseline Beginning Point Stake ——>o

Figure 1. Study layout for the baseline technique.

STUDY DESIGN AND ANALYSIS

Study Layout

i<t—— 100-Meter Baseline Tape

OOOO0d0odoo 00
OOOO0COOOHOD 0

Transect 1

OO0oodoodHf OOo 0

X <t+ Study Location Stake



METHODS—Density

* Tapes: 50-, 100-, 150-, or 200-meter delineated in centimeters. (Tapes in
English measurements can be substituted but metric tapes are preferred.) At
least three tapes are required (one, to be used for constructing quadrats, need
only be as long as the long side of the quadrat; a rope of the desired length can
be substituted for this tape); four are better.

Meter sticks (or yard sticks if using English measurements). Two are required.
Four stakes: 3/4- or 1-inch angle iron not less than 16 inches long

Hammer

Permanent yellow or orange spray paint

Tally counter (optional)

Compass

Steel post and driver

eoceeeee

5. Training As with any monitoring method, adequate training is essential to
minimize nonsampling errors.

a Examiners must be able to identify the target plant species.

b For sod-forming grasses and other species for which individual plants might be
hard to distinguish, written guidelines should be provided on what constitutes
an individual unit to be counted.® This will help to ensure consistency among
examiners. To assess consistency prior to the study, several examiners should be
asked to independently count these units in the same set of quadrats and the
results compared. If relatively consistent results cannot be achieved a different
species should be chosen for estimation or a different method selected.

6. Establishing Studies Careful establishment of studies is a critical element in
obtaining meaningful data.

a Site Selection The most important factor in obtaining usable data is selecting
representative areas (critical or key areas) in which to run the study (see Section
ILD). Study sites should be located within a single plant community within a
single ecological site. Transects and sampling points need to be randomly
located within the critical or key areas (see Section III).

b Pilot Studies Collect data on several pilot studies to determine the number of
samples (transects or observation points) and the number and size of quadrats
needed to collect a statistically valid sample (see Section III.B.8).

(1) Quadrat size and shape It is vital to choose the quadrat size and shape
that will give the highest statistical precision for the area and key species

® Determination of what constitutes a unit to be counted is somewhat arbitrary. For rhizomatous grasses such as
western wheatgrass (Pascopyrum smithii), each culm group can be visualized as an actual or potential plant
unit, as can rooted stoloniferous units of such species as vine mesquite (Panicum obtusum). Mat or sod-
forming plants such as blue grama (Boutelowa gracilis) or alkali sacaton (Sporobolus airoides) usually start
growth as small, distinct clumps, but may spread to plants a meter or more in diameter. As this occurs they
tend to fragment into more-or-less separate units, and it is these separate units that should be counted as
actual or potential individuals. For rhizomatous or mat-forming forbs, flowering stems may be the units
counted. The examiner should ensure, however, that a change in the unit chosen is of biological significance,
i.e, reflects a real change in the vegetation community. If it has no such significance, then another unit or a
different species should be chosen. (Alternatively, an attribute other than density can be selected for monitoring.)



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Illustration 21



METHODS—Comparative Yield a -

L. Comparative Yield Method
1.

General Description This method is used to estimate total standing crop or
production of a site. The total production in a sample quadrat is compared to one
of five reference quadrats; relative ranks are recorded rather than estimating the
weight directly.

It is important to establish a photo plot (see Section V.A) and take both close-up
and general view photographs. This allows the portrayal of resource values and
conditions and furnishes visual evidence of vegetation and soil changes over time.

. Areas of Use This method works best for herbaceous vegetation but can also be

used successfully with small shrubs and half-shrubs. As with most production
estimates, the comparative yield method can be used to compare relative produc-
tion between different sites.

: Advantages and Limitations The advantage of the comparative yield

method is that a large sample can be obtained quickly. Total production is evalu-
ated, so clipping calibration on a species basis is not needed. The process of develop-
ing reference quadrats for ranking purposes reduces both sampling and training time.
This technique can be done in conjunction with the frequency, canopy cover, or dry
weight rank methods. Identification of individual species is not required.

Large shrub communities are not well suited for this technique. If used in con-
junction with other techniques (frequency and dry weight rank), the quadrat size
may need to be different. This technique can detect only large changes in
production,

. Equipment The following equipment is needed (see also the equipment listed in

Section V.A, page 31, for the establishment of the photo plot):

Study Location and Documentation Data form (see Appendix A)
Comparative Yield form (Illustration 24)

Five sampling quadrat frames

Clippers

Paper bags

Kilogram and gram spring-loaded scale with clip

One stake: 3/4- or 1-inch angle iron not less than 16 inches long
Tally counter (optional)

Hammer

Permanent yellow or orange spray paint

Compass

Steel post and driver

. Training Examiners must calibrate their estimates when sampling situations

change (i.e., different sites, time of day, or season).

. Establishing Studies Careful establishment of studies is a critical element in

obtaining meaningful data. Depending on the objectives, comparative yield data
can be collected on permanent transects or in a random or systematic design.



METHODS—Daubenmire

Rangeland Monitoring
Daubenmire Frame

Six Cover Class Frame

50cm

20.cm The frame is made of 3/8-inch

iron rod. The inside dimensions

of the frame are 20 x 50
centimeters. The frame should
have sharpened legs 3 centimenters
long welded to each corner to

help hold the frame in place.

The six cover class frame is
divided into fourths by painting
alternate sections of the frame
different colors as illustrated.
Use orange and white or red
and white paint.

In one corner of the frame,
delineate two sides of an area
71 millimeters square as
illustrated. This area represents
5% of the quadrat area.

The painted design provides
visual reference areas equal to
5, 25, 50, 75, 95, and 100% of
the plot area.

|

71cm

| 74.0m

BOXXX

Mlustration 11 | 63 |



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illustration 12



STUDY DESIGN AND ANALYSIS

d From a sampling perspective, it is the study site that constitutes the target
population. The collection of all possible sampling units that could be placed in
the study site is the target population.

2. Random Sampling Critical to valid monitoring study design is that the sample
be drawn randomly from the population of interest. There are several methods of
random sampling, many of which are discussed briefly below, but the important
point is that all of the statistical analysis techniques available are based on knowing
the probability of selecting a particular sampling unit. If some type of random
selection of sampling units is not incorporated into the study design, the probabil-
ity of selection cannot be determined and no statistical inferences can be made
about the population. (Directions for randomly selecting the location of transects
to be run off of a baseline using random number tables are given in Appendix D).

3. Systematic Sampling Systematic sampling is very common in sampling
vegetation. The placement of quadrats along a transect is an example of systematic
sampling. To illustrate, let's say we decide to place ten 1-square-meter quadrats at
5-meter (or 5-pace) intervals along a 50-meter transect. We randomly select a
number between 0 and 4 to represent the starting point for the first quadrat along
the transect and place the remaining 9 quadrats at S-meter intervals from this
starting point. Thus, if 10 observations are to be made at 5-meter intervals and the
randomly selected number between 0 and 4 is 2, then the first observation is made
at 2 meters and the remaining observations will be placed at 7, 12, 17, 22, 27, 32,
37, 42, and 47 meters along the transect. The selection of the starting point for
systematic sampling must be random.

Strictly speaking, systematic sampling is analogous to simple random sampling
only when the population being sampled is in random order (for example, see
Williams 1978). Many natural populations exhibit an aggregated (also called
clumped) spatial distribution pattern. This means that nearby units tend to be
similar to (correlated with) each other. If in a systematic sample, the sampling
units are spaced far enough apart to reduce this correlation, the systematic sample
will tend to furnish a better average and smaller standard error than is the case
with a random sample, because with a completely random sample one is more
likely to end up with at least some sampling units close together (see Milne 1959
and the discussion of sampling an ordered population in Scheaffer et al. 1979).

4. Sampling vs. Nonsampling Errors In any monitoring study, it pays to keep
the error rate as low as possible. Errors can be separated into sampling errors and
nonsampling errors.

a Sampling Errors Sampling errors arise from chance variation; they do not
result from “mistakes” such as misidentifying a species. They occur when the
sample does not reflect the true population. The magnitude of sampling errors
can be measured.

b Nonsampling Errors Nonsampling errors are “mistakes” that cannot be
measured.



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METHODS—Density

e Study Identification Number macroplots for proper identification to ensure
that the data collected can be positively associated with specific sites on the
ground (see Appendix B).

f Study Documentation Document pertinent information concerning the study
on the Study Location and Documentation Data form (see beginning of Section
IM and Appendix A).

. Taking Photographs The directions for establishing photo plots and for taking
close-up and general view photographs are given in Section V.A.

. Sampling Process In addition to collecting the specific studies data, general
observations should be made of the study sites (see Section II.F).

a Selecting Random Pairs of Coordinates Using the technique described in
Section III.A.2.b.(2) on page 10 and Appendix D, select coordinates to mark the
points at which quadrats will be positioned.

b Sampling Assuming that the x-axis is on the “bottom” and the y-axis is at the
“left,” each pair of coordinates represents the lower left corner of each quadrat.
Thus, if one random set of coordinates is 0,0, the quadrat is positioned with its
lower left corner at the origin.

(1) Place the quadrats at each of the random pairs of coordinates and continue
reading them until the number of quadrats previously determined to be
required has been read.

Make a quadrat of the desired size and shape by running a tape in the
direction of the long side of each quadrat from the appropriate axis and
using two 1-meter sticks and another tape or rope. In the example in
Section JII.A.2.b.(2)(e) on page 11, it has been decided that the quadrats
should be placed with their long sides parallel to the x-axis and that the
quadrats should be 1 mx 16 m. Based on the random coordinates chosen,
the first quadrat is to be placed at the 28 m point on the y-axis and the 16
m point on the x-axis. A tape is run parallel to the x-axis beginning at the
28 m point on the y-axis. At the 16 m mark on this tape, a meter stick is
positioned perpendicular to the tape with its 0 point at the tape. Another
meter stick is similarly placed at the 32 m mark. Another tape or a rope of
16 m in length is placed across the two 1-meter sticks at their 1 m points.
The number of plants is counted in this quadrat and sampling continues. If
the short side of each quadrat exceeds 1.0 m, more than one 1-meter stick or
additional tapes or ropes may need to be used.

(2) Count the number of individuals (or other counting unit) of the key
species in each quadrat and record this on the Density form (Illustration 21).



STUDY DESIGN AND ANALYSIS

Wiegert (1962), summarized in Krebs (1989:67-72), gives a quantitative
method for determining optimal quadrat size and/or shape. The method con-
siders the costs involved in locating and measuring quadrats and the standard
deviation (or its square, the variance) that results from samples of that size and
shape. Refer to Krebs’ book for details (and an example).

Sequential Sampling The estimate of the standard deviation derived through
pilot sampling is one of the values used to calculate sample size, whether one
uses the formulas given in the Interagency Technical Reference, Planning for
Monitoring, or uses a computer program.

When conducting the pilot sampling, employ sequential sampling. Sequential
sampling helps determine whether the examiner has taken a large enough pilot
sample to properly evaluate different sampling designs and/or to use the stan-
dard deviation from the pilot sample to calculate sample size. The process is
accomplished as follows:

Gather pilot sampling data using some arbitrarily selected sample size. Calculate
the average and standard deviation for the first two quadrats, calculate it again
after putting in the next quadrat value, and continue these iterative calculations
after the addition of each quadrat value to the sample. This will generate a
running average and standard deviation. Look at the four columns of numbers on
the right of Figure 5 for an example of how to carry out this procedure.

Plot on graph paper (or use a computer program) the sample size versus the
average and standard deviation. Look for curves smoothing out. In the ex-
ample shown in Figure 5, the curves smooth out after n = 30-35. The decision
to stop sampling is a subjective one. There are no hard and fast rules.

A computer is valuable for creating sequential sampling graphs. Spreadsheet
programs such as Lotus 1-2-3 allow for entering the data in a form that can later
be analyzed while at the same time creating a sequential sampling graph of the
running average and standard deviation. This further allows the examiner to
look at several random sequences of the data before deciding on the number of
sampling units to measure.

Use the sequential sampling method to determine what sample size not to use
(don’t use a sample size below the point where the running average and
standard deviation have not stabilized). Plug the final average and standard
deviation information into the appropriate sample size equation to actually
determine the necessary sample size.



METHOD: equency

Rangeland Monitoring

Frequency Frame

The frame is made of 3/8-inch
iron rod and 1-inch angle iron
or 1 1/4-inch x 3/16-inch flat iron.

Quadrat size should be based on local conditions
determined from the pilot study.

QUADRAT
Number Size Area
1 75x75 com 56.25 sqcm
2 15.0x 15.0 cm 225.00 sq cm
3 30.0 x 30.0 cm 900.00 sq cm
4 40.0 x 40.0 cm 1600.00 sq. cm
5 50.0 x 50.0 cm 2500.00 sq cm
6 20.0 x 50.0 cm 1000.00 sq cm

Prong - 1-inch long
1/8-inch wide

The ends of the tines

(both front and rear)

can be tapered to points as
illustrated. These points can
be used to collect additional
cover data.

| 43 Illustration 6



METHODS—Cover Board

Examples of Cover Boards

hinged inside

y
Z
2 vem OZ:

V N V V wing nuts
> removable ‘———_ 2-0" —— >|
30.48m spikes

Profile Board Density Board

Illustration 20 | 93 |



V. METHODS

A. Photographs

1. General Description Photographs and videotapes can be valuable sources of
information in portraying resource values and conditions. Therefore pictures
should be taken of all study areas. Both photographs and videos can be taken at
photo plots or photo points. The difference between photo plots and photo points
is that, with photo points, closeup photographs of a permanently marked plot on
the ground are not taken. Use close-up and/or general view pictures with all of
the study methods. Comparing pictures of the same site taken over a period of
years furnishes visual evidence of vegetation and soil changes. In some situations,
photo points could be the primary monitoring tool. All pictures should be in
color, regardless of whether they are the primary or secondary monitoring tool.

2. Equipment The following equipment is suggested for the establishment of
photo plots:

© Study Location and Documentation Data form (see Appendix A)

¢ Photo Identification Label (see Appendix C)

¢ Frame to delineate the 3- x 3-foot, 5- x 5-foot, or ]- x 1- meter photo plots
(see Illustrations 1 and 2)

¢ Four rods to divide the 3- x 3- foot and 1- x 1-meter photo plot into nine square

segments

Stakes of 3/4 - or 1- inch angle iron not less than 16 inches long

Hammer

35-mm camera with a 28-mm wide-angle lens and film

Small step ladder (for 5- x 5-foot photo plots)

Felt tip pen with waterproof ink

3. Study Identification Number studies for proper identification to ensure that
the data collected can be positively associated with specific studies on the ground
(see Appendix B).

4, Close-up Pictures Close-up pictures show the soil surface characteristics and
the amount of ground surface covered by vegetation and litter. Close-up pictures
are generally taken of permanently located photo plots.

a The location of photo plots is determined at the time the studies are estab-
lished. Document the location of photo plots on the Study Location and
Documentation Data form to expedite relocation (see Appendix A).

b Generally a 3- X 3-foot square frame is used for photo plots; however, a differ-
ent size and shape frame may be used. Where new studies are being estab-
lished, a 1-meter x 1-meter photo plot is recommended. Frames can be made
of PVC pipe, steel rods, or any similar material. Illustration 1 shows a diagram
of a typical photo plot frame constructed of steel rod.





VI. GLOSSARY OF TERMS

A

actual use: a report of the actual livestock grazing use certified to be accurate by the per-
mittee or lessee. Actual use may be expressed in terms of animal unit months or animal
months.

allotment: an area of land designated and managed for grazing by livestock. Such an area
may include intermingled private, state, or federal lands used for grazing in conjunction
with the public lands.

allotment management plan (AMP): a documented program which applies to livestock
grazing on the public lands, prepared by consulting, cooperating, and coordinating with
the permittee(s), lessee(s), or other interested publics.

analysis: (1) a detailed examination of anything complex in order to understand its nature
or determine its essential features; or (2) a separating or breaking up of any whole into its
component parts for the purpose of examining their nature, function, relationship, etc. A
rangeland analysis includes an examination of both biotic (plants, animals, etc.) and abiotic
(soils, topography, etc.) attributes of the rangeland.

annual plant: a plant that completes its life cycle and dies in 1 year or less.

animal month: a month’s tenure upon the rangeland by one animal. Animal month is not
synonymous with animal unit month.

animal unit: considered to be one mature cow of approximately 1,000 pounds, either dry or
with calf up to six months of age, or their equivalent, based on a standardized amount of
forage consumed.

animal unit month (AUM): the amount of dry forage required by one animal unit for one
month, based on a forage allowance of 26 pounds per day.

apparent trend: an assessment, using professional judgement, based on a one-time observa-
tion. It includes consideration of such factors as plant vigor, abundance of seedlings and
young plants, accumulation or lack of plant residues on the soil surface, and soil surface
characteristics (i.e., crusting, gravel pavement, pedicled plants, and sheet or rill erosion.

available forage: that portion of the forage production that is accessible for use by a speci-
fied kind or class of grazing animal.

B

basal cover (area): the cross-sectional area of the stem or stems of a plant, or all plants in a
stand. Herbaceous and small woody plants are measured at or near the ground level;
larger woody plants are measured at breast or other designated height.

biomass: the total amount of living plants and animals above and below ground in an area
at a given time.

__ KE



STUDY DESIGN AND ANALYSIS

Examples of nonsampling errors include the following:

¢ Using biased selection rules, such as selecting “representative samples” by
subjectively locating sampling units or substituting sampling units that are
“easier” to measure.

¢ Using sampling units in which it is impossible to accurately count or estimate
the attribute in question.

* Sloppy field work.
¢ Transcription and recording errors.

¢ Incorrect or inconsistent species identification.
To minimize nonsampling errors:

¢ Design studies to minimize nonsampling errors. For example, if canopy cover
estimates are needed, point intercept or line intercept techniques result in
smaller nonsampling errors than the use of quadrats (Floyd and Anderson
1987; Kennedy and Addison 1987; Buckner 1985). For density data, select a
quadrat size that doesn’t contain too many individual plants, stems, etc., to
count accurately.

* When different personnel are used, conduct rigorous training and testing to
ensure consistency in measurement and estimation.

© Design field forms that are easy to use and not confusing to data transcribers.
Double (or triple) check all data entered into computer programs to ensure
the numbers are correct.

5. Confidence Interval In rangeland monitoring, the true population total (or
any other true population parameter) will never be known. The best way to judge
how well a sample estimates the true population total is by calculating a confidence
interval. The confidence interval is a range of values that is expected to include the
true population size (or any other parameter of interest, often an average) a given
percentage of the time (Krebs 1989). For instructions in calculating confidence
intervals, see the Interagency Technical Reference, Planning for Monitoring.

6. Quadrat Size and Shape Quadrat size and shape can have a major influence
on the precision of the estimate.

a Frequency Frequency is most typically measured in square quadrats. Because
only presence or absence is measured, square quadrats are fine for this purpose.
Of most concern in frequency measurement is the size of the quadrat. Good
sensitivity to change is obtained for frequency values between 20 percent and
80 percent (Despain et al. 1991). Frequency values between 10 percent and 90
percent are still useful, but values outside this range should be used only to
indicate species presence, not to detect change (Despain et al. 1991). Because
frequency values are measured separately for each species, what constitutes an
optimum size quadrat for one species may be less than optimum or even inappro-
priate for another. This problem is partially resolved by using nested plot quad-
rats of different sizes (refer to Frequency Method, Section V.B).



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K. Harvest Method

1. General Description The concept of this method is to determine the amount
of current-year above-ground vegetation production on a defined area. The
following vegetation attributes are monitored:

¢ Peak standing crop, which is the above-ground annual production of each plant
species

* Species composition by weight

It is important to establish a photo plot (see Section V.A) and take both close-up

and general view photographs. This allows the portrayal of resource values and

conditions and furnishes visual evidence of vegetation and soil changes over time.
2. Areas of Use This method can be used in a wide variety of vegetation types. It

is best suited for grasslands and desert shrubs. It is not well suited to large shrub

and tree communities.

3. Advantages and Limitations

a The harvest method measures the attribute historically used to determine the
capabilities of an ecosystem.

b It provides the basic data currently used for determining ecological status.

c Seasonal and annual fluctuations in climate can influence plant biomass.

d Measurements can be time-consuming.

e Current year’s growth can be hard to separate from previous years’ growth.

f Accurate measurements require collecting production data at peak production
periods which, are usually short, or using utilization and phenology adjustment
factors.

g Green weights require conversion to air-dry weights.

h In most areas, the variability in production between quadrats requires the
sampling of large numbers of quadrats in order to detect reasonable levels of

change.

4, Equipment The following equipment is needed (see also the equipment listed in
Section V.A, page 31, for the establishment of the photo plot):

Study Location and Documentation Data form (see Appendix A)
Production form (Illustration 22, page 109)

Sampling frames or hoops

One stake: 3/4- or 1-inch angle iron not less than 16 inches long
Herbage Yield Tables for Trees by Height, DBH, or Canopy



METHODS—Harvest

7. Taking Photographs The directions for establishing photo plots and for taking
close-up and general view photographs are given in Section V.A.

a

e

a

8. Sampling Process In addition to collecting the specific studies data, general
observations should be made of the study sites (see Section II.F).

Determine the transect bearing and select a prominent distant landmark such as
a peak, rocky point, etc., that can be used as the transect bearing point.

Randomly select the starting point along the transect bearing. Take the speci-
fied number of paces and read the first quadrat.

Record weights by clipping and weighing all vegetative material for each species
occurring in the quadrat. Samples should be bagged and saved for determining
air-dry weights. Samples from subsequent quadrats should be kept separate.
The following information should be record on each bag: Date, Transect
Number, Quadrat Number, and Species.

When harvesting plants, include all parts of all plants within the quadrat. Ex-
clude all parts of herbaceous plants and shrubs outside the vertical projection of
the quadrat, even though the base is within the quadrat (see Illustration 23).

Continue the transect by establishing additional quadrats at specified intervals.
To change the length of the transect, adjust the number of paces between
quadrats.

Oven-dry samples at 60°C for 24 hours to determine air-dry weight.

9. Calculations The weights collected for each species per quadrat placement are
recorded on the Production form (see Illustration 22).

The green weight for each species is totaled for the entire transect and shown in
column 5.

Column 6 is the total dry weight for each species. This column is totaled at the
bottom of the form for the composition totals.

Percent composition (Column 11) is calculated by dividing the total dry weight
of each species by the composition totals.

Columns 4, 7, 8, 9,and 10 are used only for double sampling.

If plant biomass is collected in grams, it can be easily converted to pounds per
acres if the total area sampled is a multiple of 9.6 ft?.



INTRODUCTION

values when individual sampling units are difficult to identify. Therefore, the best
way to collect vegetation data is to sample a small subset of the population. If the
population is uniform, sampling can be conducted anywhere in the population.
However, most vegetation populations are not uniform. It is important that data
be collected so that the sample represents the entire population. Sample design is
an important consideration in collecting representative data. (See Section III.)

6. Shrub Characterization Shrub characterization is addressed here since it is
not covered in most of the techniques in this technical reference. Shrub character-
ization is the collection of data on the shrub and tree component of a vegetation
community. Attributes that could be important for shrub characterization are
height, volume, foliage density, crown diameter, form class, age class, and total
number of plants by species (density). Another important feature of shrub charac-
terization is the collection of data on a vertical as well as a horizontal plane.
Canopy layering is also important. The occurrence of individual species and the
extent of canopy cover of each species is recorded in layers. The number of layers
chosen should represent the herbaceous layer, the shrub layer, and the tree layer,
though additional layers can be added if needed.

7. Trend Trend refers to the direction of change. Vegetation data are collected at
different points in time on the same site and the results are then compared to detect
a change. Trend is described as moving “towards meeting objectives,” “away from
meeting objectives,” “not apparent,” or “static.” Trend data are important in deter-
mining the effectiveness of on-the-ground management actions. Trend data indicate
whether the rangeland is moving towards or away from specific objectives. The
trend of a rangeland area may be judged by noting changes in vegetation attributes
such as species composition, density, cover, production, and frequency. Trend data,
along with actual use, authorized use, estimated use, utilization, climate, and other
relevant data, are considered in evaluating activity plans.

8. Vegetation Attributes Vegetation attributes are quantitative features or charac-
teristics of vegetation that describe how many, how much, or what kind of plant
species are present. The most commonly used attributes are:

Frequency Production
Cover Structure
Density Species Composition

B. Techniques Not Addressed the following are not included in this document:

¢ Riparian Monitoring

¢ Monitoring Using Aerial Photography

* Special Status Plant Monitoring

© Weight Estimate and Ocular Reconnaissance Methods
¢ Soil Vegetation Inventory Method

¢ Community Structure Analysis Method

© Photo Plot Method



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METHODS—Photographs

Rangeland Monitoring

Permanent Photo Plot Location

(3- x 3-foot, 5- x 5-foot, or 1- x 1-meter outline)

Camera Point—Permanent Stake angle tron
(locate on north side of plot) [
e

_-lL-- eee 4
angle iron
stake Paint the stakes with bright-colored permanent spray paint

(yellow or orange) to aid in relocation. Repaint these stakes
when subsequent photographs are taken.

| 36 | Illustration 3





M. Visual Obstruction Method - Robel Pole

1. General Description This method is used for determining standing plant
biomass on an area. It has primarily been used to determine the quality of nesting
cover for birds on the Great Plains and is commonly referred to as the Robel Pole
Method. This method is applicable to other ecosystems throughout the western
U.S. where height and vertical obstruction of cover are important. The following
vegetation attributes are monitored using this method:

© Vertical cover
¢ Production
¢ Structure

It is important to establish a photo plot (see Section V.A) and take both close-up
and general view photographs. This allows the portrayal of resource values and
conditions and furnishes visual evidence of vegetation and soil changes over time.

2. Areas of Use The Robel Pole Method is most effective in upland and riparian
areas where perennial grasses, forbs, and shrubs less than 4 feet tall are the pre-
dominant species.

3. Advantages and Disadvantages Robel Pole measurements are simple,
quick, and accurate. This method can be used to monitor height and density of
standing vegetation over large areas quickly. Statistical reliability improves because
numerous measurements can be taken in a relatively short time. Limitations of the
method may stem from infrequent application in a variety of rangeland ecosys-
tems. While the Robel Pole Method has been used with great success on the Great
Plains, there needs to be more research in a variety of plant communities.

4. Equipment The following equipment is needed (see also the equipment listed in
Section V.A, page 31, for the establishment of the photo plot):

Study Location and Documentation Data form (see Appendix A)
Robel Pole form (Illustration 25)

Cover classes for the area or plant community

Robel pole (Illustration 26)

One stake: 3/4- or 1-inch angle iron not less than 16 inches long
Hammer

Permanent yellow or orange spray paint

Compass

Steel post and driver

coerce eee ee

5. Training The accuracy of the data depends on the training and ability of the
examiners. They must receive adequate and consistent training in laying out
transects, determining cover classes, and reading the Robel pole.

6. Establishing Studies Careful establishment of studies is a critical element in
obtaining meaningful data. Select study sites that are representative of much
larger areas in terms of similar cover levels.



METHODS—Density _ a a

Count only those plants that are rooted in the quadrat. Often it is desir-
able to make separate counts for different size or age classes of the key
species. This is particularly true for seedlings, many of which may not
survive to the next sampling period.

(a) To eliminate measurement error due to edge effects, it is helpful to
have rules for determining whether an individual plant that falls
exactly on the edge of a quadrat is considered inside or outside the
quadrat.

(b) A good rule to follow is to count those individuals falling on the left
and top edges of the quadrat as being inside the quadrat and those
individuals falling on the right and bottom edges of the quadrat as
being outside the quadrat. Make sure that all observers follow the
same set of rules.

9. Calculations Make the calculations and record the results on the Density form
(see Illustration 21).

a Average Density per Quadrat Calculate the estimated average density per
quadrat for each size/age class by dividing the total number of plants counted in
the sample for each size/age class by the number of quadrats in the sample. If
more than one key species is counted, this process is done separately for each
species. For example, a sample of 40 quadrats yields a total of 177 individual
mature plants of key species Y. The estimated average density of mature plants
per quadrat is therefore 177/40 = 4.4 plants/quadrat.

b Total Density of Macroplot Calculate the estimated total density of the
macroplot by multiplying the average density per quadrat by the total number
of possible quadrats in the macroplot. If more than one key species is counted,
this process is done separately for each key species. Say the macroplot in the
example given in 9.a above is 40 m x 80 m and the quadrat size is 1.0 mx 16 m.
There are 200 possible nonoverlapping quadrat placements in a macroplot of
this size (40/1 = 40 along one axis and 80/16 = 5 along the other; 40 x 5 = 200
possible quadrats). The estimate of the total density of the macroplot is there-
fore 4.4 mature plants/quadrat x 200 quadrats = 880 mature plants.

10. Data Analysis and Interpretation Data analysis is straightforward. Confi-
dence intervals should be constructed around each of the estimates of average
density per quadrat (hereafter referred to simply as “average”) and total macroplot
density for each year. The averages of two years should be compared by using a t
test (for independent samples). Averages of three or more years can be compared
by an analysis of variance. See the Interagency Technical Reference, Planning for
Monitoring, for information on carrying out these procedures.

11. References
Krebs, CJ. 1989. Ecological methodology. Harper & Row, New York. This book

discusses the superiority of long, thin quadrats over circular and square quadrats,
as well as the potential problems of edge effect.



METHODS—Frequency

concept is a simple approach to collecting data on two or more different sized
plots at one time. Several different sized plots are placed inside each other in a
smallest to largest sequence (see Illustration 7).

e Number of Studies Establish at least one frequency study on each study site;
establish more if needed (see Sections II.D and III.B).

f Study Layout Frequency data can be collected using either the baseline,
macroplot, or linear study designs described in Section IIJ.A.2 beginning on
page 8. The baseline technique is the one most often used.

Align a tape (100-, or 200-foot, or metric equivalent) in a straight line by
stretching it between the baseline beginning stake and the baseline end point
stake (see Figure 4 on page 13.) A pin may also be driven into the ground at
the midpoint of the transect. Do not allow vegetation to deflect the alignment
of the tape. A spring and pulley may be useful to help maintain a straight line.

With the baseline technique, any number of transects can be run perpendicu-
larly to the baseline, depending on the intensity of the sample needed (see
Figure 1 on page 9). Each transect originates at a randomly selected mark along
the baseline. The randomization is restricted so that half of the transects are
randomized on each side of the halfway mark. (Directions for randomly select-
ing the location of transects to be run off of a baseline using random number
tables are given in Appendix D.)

The starting point for each transect off the base line and the distance between
each quadrat should not be any closer than the width of the quadrat being used
to avoid the possibility that any two quadrats might overlap.

g Reference Post or Point Permanently mark the location of each study with a
reference post and study location stake (see beginning of Section III).

h Study Identification Number studies for proper identification to ensure that
the data collected can be positively associated with specific studies on the
ground (see Appendix B).

i Study Documentation Document pertinent information concerning the study
on the Study Location and Documentation Data form (see beginning of Section III
and Appendix A).

. Taking Photographs The directions for establishing photo plots and for taking
close-up and general view photographs are given in Section V.A.

. Sampling Process In addition to collecting the specific study data, general
observations should be made of the study sites (see Section II.F).

a Running the Transect Study data are collected along several transects. The
location of each transect (distance along the baseline) and the direction (to left
or right from the baseline) are randomly determined for each study site. A
quadrat is read at the specified interval until all quadrats have been read. The
interval between quadrats can be either paced or measured. To widen the area