ROBERT O. CURTIS is a mensurationist at the Pacific Northwest Forest and

Range Experiment Station, Forestry Sciences Laboratory, 3628 93rd Avenue, S.W.,

Olympia, Washington 98502.

This paper is based in part on a draft prepared in 1976 by the Growth Processor

Committee, Timber Management Research, Forest Service, U.S. Department of

Agriculture, Albert R. Stage, Chairman. Other contributors to the original draft were

Martin Dale, Benee Swindel, and David Bruce. Additional useful ideas and helpful

criticism were later provided by Donald L. Reukema at the Forestry Sciences

Laboratory, Olympia, Washington.

Author
1

Curtis, Robert O. Procedures for establishing and maintaining permanent

plots for silvicultural and yield research. Gen. Tech. Rep. PNW-155.

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Forest and Range Experiment Station; 1983. 56 p.

This paper reviews procedures for establishing and maintaining permanent plots for

silvicultural and yield research; discusses purposes, sampling, and plot design; points

out common errors; and makes recommendations for research plot designs and

procedures for measuring and recording data.

Keywords: Plot analysis, permanent sample plots, tree measurement, sample plot

design.

2 Introduction

2 Background

3 Purpose

4 Data Sources

5 Plot Classification

5 Temporary Plots

5 Temporary Plots, With Supplementary Growth Information

5 Permanent (Remeasured) Plots

6 Some Sampling Considerations

8 Plot Installation

8 Plot Configuration

12 Plot Size

17 Plot Buffers

17 Surveying and Marking Plots

18 Plot Protection

18 Plot Measurement

19 Record of Initial Conditions

19 Tree Numbering

21 Determination of Breast Height

22 Determination of Stand Age

24 Tree Dimensions

34 Site Index Estimates

35 Stem Maps

35 Photographs

36 Remeasurement Schedule

36 Control of Treatments

38 Timing of Measurements in Relation to Treatment

39 Data Management

41 Literature Cited

46 Appendix

46 Checklist of Needed Plot and Tree Measurement Information

47 Standard USDA Forest Service Species Codes for Western Species

48 PDMS Tree Classification Codes

50 Field Tree Measurement Forms and Height Measurement Procedures

53 Equipment Checklist for Field Plot Work

54 Plot Dimensions and Conversion Tables

Abstract

Contents
2

Rational forest management requires information on production and patterns of

development of forest stands under current and future stand conditions and management regimes, as a basis for managerial choices, economic decisions, and field

application of chosen regimes. This information comes from observation of forest

stand development and from silvicultural experiments.

Estimates of present stand volumes and growth rates usually come from forest

inventories. The planned forest of the future will, however, often be quite difterentfrom

the present forest. Present average growth rates do not tell us what we can expect

from the future forest, nor do they provide guides to desirable management regimes

or a basis for choice among possible management regimes. These require estimates

of the behavior of managed stands, including response to such management measures as spacing control, thinning, and fertilization. Such estimates are provided by

silvicultural experiments designed to determine the relationships between growth,

stand conditions, and stand treatments; and by various types of yield tables and stand

simulators which attempt to combine these relationships into generally applicable

systems for estimating behavior and production of future stands.

From about 1920 to the 1940’s, normal yield tables were developed for many major

species. Procedures for constructing normal yield tables from temporary plot

measurements in well-stocked wild stands were worked out and fairly well standardized. During the next two decades, relatively little new work was done on yield tables,

but many silvicultural field experiments were established.

Since the early 1960’s, there has been renewed interest and activity in yield research.

This was stimulated by the advent of the computer, the availability of increasing

amounts. of data from thinning and fertilization experiments, and an urgent need for

silvicultural guides and yield estimates applicable to the growing area of young stands

and to increasingly intensive management. The former distinction between yield

research and silvicultural research is no longer clear, and the new yield tables are

various types of simulation models that estimate growth rates and yields for a range of

possible management regimes, using the results of silvicultural research.

Estimates of growth rates and treatment responses are wanted for stand conditions

and stand treatments that do not yet exist on large operationally developed forest

areas. These estimates must therefore be based on silvicultural experiments and

small experimentally treated areas. Most of the present information on thinning and

fertilization has been so developed. There have been many studies showing response

at particular locations, usually reported as case studies. But until recently, there have

been relatively few attempts to combine such information into regionally applicable

quantitative generalizations.

Such generalized estimates are badly needed. Few individuals or organizations

possess a data base adequate for the purpose, and there is much to be gained by

pooling data in cooperative efforts among research workers and research organizations. This requires compatibility of and comparable reliability in data collected by

different individuals and organizations.

Introduction

Background
3

Certain defects that are repeatedly encountered severely limit or destroy the usefulness

of much data obtained at high cost in time and money.

1. Documentation is often inadequate. Records of procedures, stand measurements,

and stand treatments are incomplete, poorly organized, or contradictory.

2. Plots are often excessively small or are installed without buffers between adjacent

treatments, or both.

3. Height measurements are frequently inadequate in number, distribution, or accuracy,

and have sometimes been omitted altogether.

4. Measurements are often omitted for trees below some arbitrary “merchantable” size,

which results in truncated diameter distributions and statistics that cannot be compared

with other data.

5. Estimates of tree and stand ages are often inaccurate. Sampling is frequently inadequate, definitions are ambiguous or inconsistent, and procedures have not been documented.

6. Initial stand conditions, prior to treatment, are often not recorded.

7. Plot areas are often unreliable because of poor plot surveys and poor records.

8. Changes are sometimes made in treatments, plot sizes, or measurement procedures for reasons of immediate expediency in fieldwork, without consideration of effects on later analyses.

9. Data codes and measurement standards are often inconsistent or incompatible. This

prevents use of a common set of computer programs or pooling of data among organizations or individuals, without costly and time-consuming conversions and loss of information.

This paper discusses items that should be considered by anyone planning or undertaking establishment and measurement of field plots in silvicultural experimentation, or for

construction of yield tables. It is concerned primarily with design and measurement of

individual plots. The larger questions of experimental design in general, and of overall

sampling design, are touched on only as they relate to plot procedure.

Procedures for establishing and maintaining such research plots have been discussed

in a number of past publications, including Decourt (1973), Forestry Commission (1979),

Hummel and others (1959), Robertson and Mulloy (1944, 1946), Synnott (1979), and

USDA Forest Service (1935). There are also various in-house manuals that are not

generally available. These contain much information of value; however, some

procedures discussed are now out of date, and many manuals are oriented specifically

to the needs and procedures of individual organizations and projects.

Installation and maintenance of permanent plots are not simple tasks. This paper is not

intended to be a complete, detailed manual of field procedure. Rather, it is intended as

an aid for those preparing procedural specifications. It should help them to avoid repetition of past mistakes by calling attention to decisions needed in the planning stage of a

research study. It should help them to provide some standardization and compatibility

between data sets. It may give field personnel insight into the reasons behind procedures, and possible alternatives.

Purpose
4

Portions of the discussion may appear to be mere repetition of the obvious. Experience, however, shows that many obvious points become obvious only in the analysis

stage, when it is too late to correct mistakes made in establishing and measuring

plots.

The discussion is generally in terms of fixed area remeasured plots and even-aged

stands with one principal species. Historically, these are the plot type and stand

condition most often used in silvicultural experiments and in construction of managed

stand yield tables; however, many of the same ideas and principles apply to studies

using point sampling and to other stand conditions. Although aimed at research

applications, they may also suggest possible modifications in inventory and stand

examination procedures to make them more compatible with information developed

from research.

Necessarily, recommendations made in this paper often represent informed opinion

and the author’s best judgment rather than established fact.

Approaches to silvicultural and yield estimation problems are influenced by (1) specific

objectives, (2) nature of the forest (even aged vs. uneven aged, pure vs. mixed

species), (3) data already available, and (4) feasibility of acquiring new data.

Data may come from research plots installed to secure information on a particular

relationship, from research plots designed to sample specified stand conditions over a

region, from existing research plots originally installed for these or other purposes,

from management inventories, or from some combination of these.

Inventory data are often available in large quantity, and they provide a representative

sample of the existing forest. They are usually the best basis for short-term projections; they have not generally proved satisfactory for other purposes, for several

reasons.

The small plots used in many inventories are subject to unknown edge effects. Usual

procedures provide only rough estimates of such attributes as age and height for the

individual plot and frequently omit or inadequately sample stems below some arbitrary

and fairly large diameter. Such data are well suited to estimation of stratum means

(their designed objective) but are poorly suited to estimation of treatment responses

or the regression relationships used in stand simulation.

When estimating treatment effects, comparing potential treatment regimes, and

making long-term estimates for future managed stands, one is commonly dealing with

conditions that as yet exist only on small areas and very restricted experimental

installations. These are not sampled adequately, if at all, by management inventories.

If sampled, the uncontrolled variation present usually prevents satisfactory eiraluation

of treatment response.

For these and similar reasons, most silvicultural research and much yield research

are based on plots established independent of management inventories.

Data Sources
5

Field plots used in silvicultural and yield research can be classified into three groups:

1. Temporary (single-measurement) plots.

2. Temporary plots, with supplementary growth information.

3. Permanent (remeasured) plots.

The normal yield tables of the 1930’s were generally based on temporary plots. Ages,

diameters, and heights were measured, but no direct information was obtained on

current growth rates and mortality rates.

Such plots still have their uses, but they will not be further considered here. They do

not provide the information on growth and mortality required for most modern yield

tables.

Additional measurements obtained from increment cores and stem analyses can

provide information on growth rates of trees on temporary plots. This information can

be extrapolated for short periods to provide the periodic growth values or estimates of

current growth rates needed for some types of analyses. This is a common procedure

in inventories in which such procedures provide some growth information at less cost

and without the delay involved when permanent plots are used. Similar methods can

be used to obtain growth data for construction of yield tables and stand simulators, by

procedures such as those discussed by Curtis (1967b), Myers (1966, 1971), and

Vuokila (1965).

Although information may be obtained quickly by such methods, precision comparable to that of permanent plot methods is not cheap, if attainable at all. The accurate

determination of diameter growth required in research studies is not easy. Except in

young stands of species with annual internodes which can be directly measured from

the ground, height growth estimates can be obtained only by laborious and destructive stem analyses; or by assuming (perhaps incorrectly) that preexisting site index

curves are a correct representation of height growth. Information on mortality is

obtainable only in the form of subjective estimates of year of death of dead trees on

the plot. Stand treatment information is usually confined to measurement of visible

stumps and rough estimates of date of cutting. No information can be obtained for

stand conditions and treatments not present in the existing forest.

It is possible, however, to construct yield estimates from this type of data, and such

data are often useful as a means of supplementing existing permanent plot data.

Much past and present research uses “permanent” plots, which are established and

measured at the start of an investigation and subsequently remeasured at intervals

over a period of a few to many years. Such plots are expensive and represent a

long-term commitment of resources which is unpopular with many administrators.

Permanent plots can provide data of superior accuracy and information obtainable in

no other way, however.

Plot Classification

Temporary Plots

Temporary Plots,

With Supplementary

Growth Information

Permanent

(Remeasured) Plots
6

For the period of observation, permanent plots provide points in a real growth series,

as opposed to artificial growth series constructed from single measurements of

stands thought to represent successive stages in development. Over an extended

period of years, the record of actual development of individual stands provides a

standard against which estimates can be compared. Characteristics and development

of individual trees can be followed over time. Such plots provide a complete history of

stand development and stand treatment, response to treatment, and actual stand

damage and mortalityinformation not obtainable from other types of plots. When

observations are continued over many years, variations in growth caused by

short-term climatic fluctuations should be compensating. And, for demonstration

purposes, the on-the-ground examples and historical record of treatment and response which they provide are more convincing to field foresters than any amount of

statistical analyses and projections of temporary plot values.

This paper is primarily concerned with permanent plots, although many of the principles and recommendations given also apply to temporary plots with supplementary

growth information.

A first step in any sampling scheme is to define the population about which inferences

are to be made, in terms of such associated characteristics as physical location, site

quality, stand origin, age class, species composition, management treatment, and

freedom from destructive agents. For many research studies, there is no need to

sample conditions that will be excluded from the forest under anticipated future

management. Thus, silvicultural experiments and yield studies rarely include very old

and decadent age classes. Stands severely injured by disease, insects, or climatic

agents are usually excluded on grounds that, under management, such stands will be

terminated.

Sample selection is relatively straightforward in management inventories, where the

population consists of all presently existing stands and the primary objective is to

estimate stratum means. It is less straightforward in silvicultural studies intended to

develop estimates of growth of future managed stands. In the latter case, one often

seeks inferences about some largely hypothetical population of future managed

stands, which may differ considerably from the present forest. The primary objective is

often not to determine means of volume or basal area for some category of stands,

but to estimate coefficients of functions relating growth to current stand values and

possible treatments. The conditions of most interest for this purpose may exist only on

certain small areas. Some conditions and treatments must be created on newly

established experimental plots. Some combinations of stand condition and treatment

can be produced only by an extended period of management; these cannot be

sampled directly, and estimates must be based on extrapolations from the most nearly

analogous conditions available.

Yield studies often use regression analyses of unreplicated plots, established in the

portions of the existing forest that meet stated specifications of age, species composition, health, density or treatment category, and relative uniformity in stand and site

conditions. Plot location within suitable areas is often done subjectively; the observer

attempts to select a plot representing either an average condition for the stand or the

observer’s conception of conditions likely under future management. An alternative,

more objective, and statistically more defensible approach in such studies is to select

and delineate stands that meet the required specifications and then to locate the

plots) within them by some random or systematic sampling procedure.

Some Sampling

Considerations
7

Such stands should be deliberately selected to obtain as wide a distribution of the

predictor variables as possible, consistent with study objectives and expected application of the model. As an example, many predictors of growth are regression models

that involve age and some measure of density. A statistically desirable selection would

insure that the plots include a wide range of densities for each age class. As sample

selection proceeds, the distribution of age and density can be indicated in a two-way

table and an effort made to fill all cells as equally as feasible. Such a selected sample

yields a rectangular distribution of age and density; in subsequent regression analyses, it will provide a better assessment of effects of the predictor variables, and better

predictions near the margins of the range of data.

In silvicultural experiments, treatments are usually replicated at a given location in

accordance with some specified experimental design. This provides an estimate of

experimental error and allows statistical analysis of results at that location. Often, the

experimenter’s primary interest is in defining some specific relationship, such as

response to fertilizer dosage or to density level. To minimize the experimental error,

the experimenter will then impose stringent requirements on initial homogeneity and

comparability of plots within that installation. Meeting this requirement of close

comparability of initial conditions among plots generally requires that the plots be

subjectively located, with subsequent random assignment of treatments.

Many yield studies use regression analyses of plots selected in chosen strata of the

existing population, supplemented with plots from silvicultural experiments. The latter

furnish information on conditions and treatments not available in the existing forest

and may provide guides to the form and nature of certain relationships. Considerations of time, cost, and availability of data often force the analyst to use data that are

not completely comparable or compatible in method of plot selection and standards of

measurement, and treatments may or may not be replicated at a particular location.

Stringent stand uniformity requirements and close control of treatments, which are

necessary for identification and measurement of treatment effects in silvicultural

experiments, may lead to estimates that require adjustment for operational use

(Bruce 1977).

Valid conclusions applicable on a regional basis also require that additional installations be distributed over a range of site conditions, initial stand conditions, and

geographic locations that include various unmeasured and possibly unrecognized

factors affecting growth.

Most silvicultural experiments and yield studies recognize the need for replication at a

given location if conclusions are to be drawn for that location and the need to sample

the range of stand and site conditions if conclusions are to be drawn on a regional

basis. The need to include a range over time is less generally recognized, however.

Growth of forests varies from year to year and decade to decade because of variation

in climatic conditions and sporadic occurrence of widespread stand injuries and cone

crops. In some instances, these fluctuations can be extreme (Keen 1937, Reukema

1964). Mortality tends to be clustered in both time and space because it is associated

with climatic extremes and with the occurrence of windstorms and insect and disease

outbreaks.
8

It is therefore risky to base estimates of expected growth on observations of growth,

mortality, and treatment response made in a single short time period. Although little

can be done to allow for possible long-term trends, short-term variations will average

out when the basic data represent a series of time periods rather than a single short

period. This is one major value of long-term permanent plot observations and of the

accumulation over time of compatible data collected by consistent procedures.

Well-designed permanent plots maintained and repeatedly remeasured over time

become more valuable with increasing length of record. Many times they are valuable

for purposes other than the study for which they were installed, and for purposes not

anticipated by the person who installed them.

Long-term permanent plot data are often analyzed by someone other than the original

investigator. Analytical techniques and objectives change over time, and there can be

no certainty that the computational procedures and analyses foreseen at the time the

plots were established will be those judged most suitable at the time of later analyses.

Therefore, procedures and data should be as complete and general as possible.

Shortcuts that will later limit analyses to specific summarization and analysis procedures should be avoided. Experience shows that such shortcuts usually result in later

costs and loss of information far more important than small immediate savings in field

time. It should be anticipated that details of site classification, volume computation,

and similar procedures will change, and the data should be adequate to permit

summarization and analysis by any generally applicable procedure.

The plot is the basic unit of observation. It is usually a single area delineated on the

ground. It may consist of a cluster of subplots (or points, if variable radius plots are

used) arranged randomly or systematically within the treatment area or stand, with

cluster totals treated as the basic values for analysis. In clumped or irregular stands,

such clustered subplots may be preferable to single larger plots and more consistent

with later management application of results.

Plot Installation

Plot Configuration
9

Fixed area plots can be any shape but are usually circles or squares, which minimize

perimeter per unit area and, hence, edge effects and required area of buffer. Circles

are convenient for very small plots, but accurate location of the perimeter becomes

difficult for larger plots. The straight borders of squares and rectangles lend themselves to accurate location and marking of corners and borders: Corners of squares

are easily located with compass and tape by measuring diagonals from an initial plot

center (fig. 1); subsequent measurement of boundaries provides a check on errors.

Rectangles are sometimes advantageous where there is a pronounced site gradient

(as on steep slopes) and the long axis of the rectangle can be oriented at right angles

to the gradient to reduce variation within the plot. Fieldwork is simplified and blunders

are reduced if a standard plot shape and layout procedure are adopted and used

whenever the situation permits.

RECOMMENDATION: The square plot is generally the most useful and convenient

for research studies.

Some special considerations arise in regularly spaced plantations, which sometimes

influence positioning, orientation, and exact size of plots.

In some research plantations established with very close control of spacing, it is feasible

to use a square or rectangular plot positioned so that its sides lie midway between rows,

thereby insuring that plot area is identical with the growing space available to the trees on

the plot. This is desirable when feasible and will produce plots with areas that differ slightly

from the simple fractional acres or fractional hectares generally used (fig. 2).

A more common situation is that in which an existing plantation has spacing not

sufficiently regular to allow positioning the plot with sides midway between rows, but

still sufficiently regular that position and orientation of the plot can result in a plot area

that differs appreciably from the total growing space available to the trees on the plot.

This in turn will bias all growth computations. One means of reducing such bias is to

orient the plot so that its sides intersect the planting rows at an angle of 20° to 30°

(fig. 3).

Variable radius plots (points) may also be used for permanent plots. Single points are

not a usable sampling unit for research purposes, since they include too few trees to

provide satisfactory estimates either of growth rate or of the stand attributes used as

predictors of growth. A systematic arrangement of 5 to 10 points within a stand can be

used, however.1

 Variable radius plots are more consistent with commonly used

inventory procedures than are fixed area plots, and they have the well-known advantage that sampling proportional to basal area concentrates the measurements on the

trees of larger size and (usually) higher growth rates.

Because variable radius plots include few trees from the smaller diameter classes

and information is generally also needed for these, it is usually necessary to combine

the variable radius plot with a concentric fixed area plot on which all trees below a

specified limiting diameter are recorded. The fixed area plot size should equal the

size of the variable radius plot for the specified limiting diameter.

The fact that trees initially outside the variable radius plot grow “onto” the plot as they

increase in size (“ongrowth” trees) complicates computations and introduces irregularities in growth estimates for successive periods, which are not present with fixed

area plots (Martin 1982, Myers and Beers 1968).

1 Hann, David. Development of growth and yield information for the mixed conifer

zone of southwest Oregon. Study plan on file at Oregon State University, Corvallis,

Oregon. 1981.
10
11

Figure 2.-Position of plot borders in a

plantation. Correct position (solid line) gives

unbiased estimates of growth per unit area.

Incorrect position (dashed line) gives biased

estimates of growth per unit area.

Figure 3.-Orienting plot at an angle to rows in

plantation reduces bias in estimates of

growth per unit area associated with position

of plot borders.
12

Such a cluster of points usually extends over more physical area than atypical fixed

area plot serving a similar purpose. This may be an advantage or a disadvantage,

depending on the nature and purpose of the study. It may be difficult to provide the

buffers and replication needed when several treatments are to be applied within a

limited area in a silvicultural experiment. Over an extended observation period, an

initially reasonable spacing of points can lead to variable plots that overlap or extend

into adjacent dissimilar treated areas. Because the point cluster extends over a

greater area, however, it may be more representative of conditions existing on a stand

basis and may be more consistent with data arising from typical stand examination

procedures.

Variable radius plot (point) clusters are best suited to studies that sample preexisting

stand conditions, or where treatments are applied to relatively large areas, rather than

to typical silvicultural treatment experiments.

Plot size is influenced by intended purpose, by stand conditions, by expected duration

of the study, and by cost considerations.

The criteria for suitable plot size in a research study are not the same as in an inventory. Frequently, an inventory aims to determine average values of certain variables

(such as volume) for given strata, as means of plots falling in those strata. Within

limits, increased plot numbers can compensate for increased variability associated

with smaller plots, and estimated means are unbiased regardless of plot size.

Many research studies, however, use regression equations to estimate individual tree

or plot growth as functions of current stand values of individual plots. Very small plots

will produce highly variable estimates and can lead to biased estimates of regression

coefficients as a result of edge effects and bias in subjective location of plots.

Variability increases with decreasing plot size, and plots that are excessively small

relative to the pattern of within-stand variation will produce a considerable range of

values for variables such as density and volume (Smith, 1975). If field plots are then

subjectively located for apparent uniformity and full stocking (a common procedure in

field experiments), the resulting values may be higher than are realistically attainable

on a stand basis. If plots are systematically located, observed growth on the plot will

represent in part an effect of adjacent, unmeasured, differing stand conditions. High

density plots will grow well because they are using adjacent growing space. Low

density plots will grow relatively poorly because of the competition of adjacent dense

groups of trees.

Plot Size
13

Small plots are also likely to bias mortality estimates. In many studies, plots which lose

a substantial part of their stocking to mortality between two successive measurements

are assumed to represent instances of “catastrophic mortality” and are discarded. On

small plots, however, death of even a few trees in a given period will result in large

negative increments. The analyst cannot tell whether this represents merely a few trees

whose loss is insignificant in overall stand development, or a major disaster; the

variation introduced can totally obscure any relationship between growth response and

stand treatment. The plot must therefore be discarded. The result is not merely highly

variable estimates of mortality, but estimates of mortality and of the relation of mortality

to stand conditions and treatment which are biased by the plot selection process.

Excessively small plots can be expected to give erratic values for stand statistics and

poor correlations of increment with site and stand attributes; they may also give biased

estimates of the increment-stand density relationship (Jaakola 1967). Such effects will

generally be more serious in mechanically located plots without buffers (as in inventories) than in research plots established in selected stand conditions (usually chosen for

homogeneity) and provided with suitable buffers, so that edge effects are reduced.

Although the effects of plot size on yield analyses have not been thoroughly investigated,

a number of rules of thumb for desirable size of fixed area plots are given in the literature.

Early U.S. investigators commonly recommended plot sizes that would include at least

100 stems exclusive of understory at the end of the experiment (Bruce 1926; Osborne

and Schumacher 1935; USDA Forest Service 1935-still an excellent reference on many

aspects of plot installation and measurement; Marckworth and others 1950). Since

much of this work was in untreated stands, presumably a somewhat lesser number

would be acceptable in the more uniform stand conditions expected in plantations and

consistently thinned stands.

Fabricius and others (1936) recommended plots of at least 0.6 acre (0.25 ha), larger in

irregular stands. Robertson and Mulloy (1944, 1946) recommended 0.5- to 1.0- acre

(0.2- to 0.4-ha) plots. Jeffers (1959) recommended 0.25 to 1.2 acres (0.1 to 0.5 ha) for

even-aged pure stands, depending on spacing. Hummel and others (1959) recommended plot sizes of 0.3 to 0.5 acre (0.12 to 0.20 ha) for pure conifers, 0.5 to 1.0 acre

(0.2 to 0.4 ha) for mixed stands. The Forestry Commission (1979) recommended plot

sizes of 0.25 to 0.5 acre (0.1 to 0.2 ha) for general use, with a minimum of 0.2 acre

(0.08 ha) for single plots in conifer plantations, 0.3 acre (0.125 ha) for hardwoods, and

0.1 acre (0.04 ha) in replicated treatment experiments (excluding buffers).

Vuokila (1965) compared coefficients of variation for alternate plot sizes and recommended a size in hectares equal to 0.01 x (dominant height in meters), which corresponds to a plot size in acres of 0.0075 x (dominant height in feet). Decourt (1973)

recommended the same standard, with the restrictions that minimum plot size should

not be less than 0.25 acre (0.1 ha) and that the plot should contain 100 to 200 stems.

Hegyi (1973) made a somewhat similar analysis of plot size in three untreated jack pine

(Pinus banksiana Lamb.) stands. His coefficient of variation curves suggest minimums

of 50. to 75 stems per plot and areas of about 0.1 acre (0.05 ha) for these smalldiameter stands. Note that these comparisons of coefficients of variation all deal with

live stand volumes and basal areas, rather than with increment rates-which are frequently the values of primary interest.
14

Plot sizes in the general range of 0.25 to 0.5 acre (0.1 to 0.2 ha) have been used in

several U.S. and foreign thinning and fertilization studies (Carbonnier and Fries 1976,

Clutter and Jones 1980, Hamilton 1976, McEwen 1979).

In 1969, the University of Washington Regional Forest Nutrition Program adopted a

minimum plot size of not less than 0.1 acre (0.05 ha), to contain at least 50 stems,

plus buffer.2

 The British Columbia Forest Productivity Committee specified a minimum

of 0.12 to 0.25 acre (0.05 to 0.1 ha) according to number of stems, but not less than

60 stems, plus buffer.3

Recent studies in the Pacific Northwest have frequently used quite small plotssometimes as small as one-twentieth acre (0.02 ha)-because of difficulty in finding

fully comparable stand conditions over an area large enough to allow replication of a

series of treatments at a single location.

Our experience (Curtis and others 1981) leads to the conclusion that the very small

plot sizes used in some thinning and fertilization experiments are undesirable, and

sometimes unusable, as a basis for increment regressions and for estimates of

mortality and diameter distributions.

Note that all the rules of thumb given above lead to plot sizes considerably larger than

those used in many inventories, even though stands are selected for uniformity. Plots

smaller than those used in the University of Washington and British Columbia Forest

Service studies cited are clearly undesirable as sources of growth and yield data, and

even these have severe limitations for study of diameter distributions and mortality.

2 University of Washington. Forest fertilization research in the

Douglas-fir region of the Pacific Northwest: research proposal and

project description. College of Forest Resources, Seattle. 1969.

3 British Columbia Forest Service, Forest Productivity Committee. Field

manual, balanced installation field programme. Victoria, B.C. 1974.
15

Consistency among plot sizes in different stand conditions may be obtained by

relating a standard number of stems to average diameter or to stand height. Figure 4

gives an example of such a guide, indicating the plot sizes required to include 50

stems in Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) stands of a given

average diameter and percentage of normal stand density. (Many thinned stands, for

example, would fall between the 50- and 75-percent curves indicated in early

thinnings, and near the 75-percent curve at older ages.) Similar guides can also be

derived from the relation of number of trees and dominant height, or from the crown

area-diameter relationship of open-grown trees. Such guides should be qualified by a

minimum number of trees acceptable in the most open stands (minimum of 50

suggested). Generally, a single plot size determined by the most extreme treatment

should be used for all plots within an installation.

The preceding discussion applies to relatively uniform even-aged stands of a single

species; in many cases cited, to plantations. Mixed species stands and uneven-aged

stands will be inherently more variable and will require larger plots-sometimes much

larger-to characterize stand structure and growth. (For example,. Synnott (1979)

recommends 2.47-acre (1 .0-ha) plots for mixed tropical forest.)

Although the above discussion applies directly only to fixed area plots, similar considerations apply to variable radius plots. The basal area factor, number of points, and

limiting diameter and radius of the concentric fixed area plot should be chosen to

include a sufficient number of trees to provide a reasonably smooth diameter distribution and the ability to distinguish “catastrophic” from “regular” mortality. The decision

on arrangement and spacing of points should take into account future growth, so that

with increase in tree size the variable radius plots will not overlap each other or

adjacent dissimilar treatments or conditions, within the anticipated life of the study.

Plots composed of single trees or small groups of trees have their uses for such

purposes as determining presence or absence of response, relation of response to

individual tree characteristics, pruning studies. Fully satisfactory and generally

accepted techniques for expanding such results to a unit area basis are not now

available, however.

RECOMMENDATIONS: Experimental designs that require large numbers of plots

within a single homogeneous stand condition-forcing use of small plots because of

the limited size of suitable areas-are not generally feasible for silvicultural and yield

research and should be avoided.
16

Although no fixed universal standards can be given, required size of plot (or plot

cluster) will increase with (1) average tree size and (2) within-stand heterogeneity. Plot

size should be selected in relation to the stand conditions expected at the end of the

planned period of observation, rather than to initial conditions only. Plot size should be

large enough in relation to stem size, number of stems, and pattern of stem distribution that:

(1) the plot can be regarded as representative of a condition that exists, or could exist,

on a stand basis (that is, minor shifts in plot location would not materially alter the plot

statistics);

(2) growth of trees on most of the plot area is little affected by surrounding, possibly

unlike, stand conditions;

(3) sufficient stems are included to provide a reasonably smooth diameter distribution;

and

(4) “catastrophic” mortality can be distinguished from “regular” mortality composed of

suppression losses plus occasional death of scattered larger trees.
17

Research plots should be surrounded by a buffer strip of comparable initial conditions,

which receives identical treatment. This insures that growth of the plot is not influenced

by adjacent, unlike stand conditions and treatments. It also provides for the possibility of

future destructive sampling of individual trees for such purposes as determination of

past height growth patterns and wood quality studies, without destruction of the plot

proper.

Adjacent stand density differences have an effect on microclimate on the plot. It is well

known that root systems extend for considerable distances and that root grafting and

physiological linkage with nearby trees are common. Root systems of onplot trees will

exploit water and nutrients available adjacent to the plot, and vice versa. Therefore,

onplot growth is likely to be influenced by adjacent changes in site conditions and stand

density. Adjacent fertilizer treatments may affect growth of unfertilized plots through root

systems that extend across plot boundaries, through downslope movement of soil

water, and through litter fall from fertilized trees onto unfertilized areas.

Failure to provide adequate buffers will tend to produce underestimates of differences

in response to treatment. Provision of adequate buffers is most critical on small plots,

because small plots have a greater proportion of edge to total area than do large plots.

A frequently quoted rule of thumb is that width of buffer should equal stand height

(Fabricius and others 1936, USDA Forest Service 1935). In the tall stands of the Pacific

Northwest, however, this rule often gives values that seem unreasonable and impractical in application. Buffer size is sometimes specified as a proportion of plot area, but

any single fixed proportion will give unreasonable values when applied to extremes of

plot size.

If future destructive sampling of individual trees in the buffer is anticipated, width of the

buffer may need to be increased to allow for this and to insure that the sample trees

can be considered representative of conditions on the measured plot proper.

An additional isolation strip outside the treated buffer may be needed if there is an

adjacent drastically different stand condition (for example, a clearcut), an abrupt site

change, or concern over possible movement of fertilizer.

RECOMMENDATIONS: A rule that is probably adequate for most situations, provided

adjacent conditions are not drastically different, is that width of the buffer should be at

least equal to the expected crown width of dominant trees at the end of the planned

period of observation. The Forestry Commission (1979) recommendation of 33 feet (10

m) seems reasonable as a general guide.

Much time is lost relocating inadequately monumented plots. Lost corners and carelessly surveyed plots are frequent sources of error in plot areas and in corresponding

values of stand statistics.

The plot center or a plot corner should be referenced to some easily relocatable point

along a road or other access route, by compass bearing and measured distances.

Other plots in the installation should be referenced to this by bearings and distances,

and a careful sketch map prepared adequate for relocation of the plots by someone

unfamiliar with them. The map should include approximate location in relation to the

public lands survey system.

Plot Buffers

Surveying and Marking

Plots
18

Plot centers and corners must be marked by stakes of some permanent material,

such as metal, or substantial stakes of preservative-treated wood. Stakes should be

marked in a way that positively identifies the plot and the particular corner and should

be witnessed by appropriate paint blazes or scribe marks on adjacent trees. Declination used should be recorded. Bearings and horizontal distances between corners or

centers must be carefully measured and recorded. The sketch map should show all

bearings and distances needed to relocate plot centers and corners.

Large plots, elaborate installations, or difficult terrain may warrant use of transit

surveys, including computation of error of closure to a preassigned standard. Smaller

plots and simpler situations can be adequately handled with staff compass and tape,

provided care is used. To insure against blunders, boundaries should be run twice in

opposite directions, or error of closure calculated. Errors should not exceed one-half

degree in angles and 1:100 in horizontal distances, or 1 percent error of closure.

Plot borders should be marked with paint blazes or signs (except where public

attention is undesirable) or standard scribe marks on adjacent trees facing the plot

border. In dense stands they should be carefully delimited with string before the trees

are initially tagged and measured.

A standard record form should be used and checked to insure that all specified items

are recorded.

There must be an agreement with the organization administratively responsible for the

area to protect the installation from disturbance for the planned period of observation.

The land manager must be informed of the exact location and nature of research

plots. Organizations should have a standard procedure for insuring that managers

have an up-to-date record of research installations on their lands, and that these are

not disrupted by forest operations without prior consultation and agreement with the

research organization.

Common hazards include road construction, thinning operations, and aerial application of fertilizers or herbicides. Any of these can quickly destroy the usefulness of a

research installation.

All measurements and records on a given installation should be either in metric or in

English units. The two should not be mixed. Tapes and instruments graduated in both

systems invite errors and should be avoided where possible. In general, metric units

are preferable for new installations. Measurement of old installations should continue

in English units until the entire system of records is converted to metric.

Plot Protection

Plot Measurement
19

General characteristics and past history of the site and stand, so far as these are

known, should be recorded at the time of the initial measurement using a standard

procedure and specifications. This includes such items as location (public land

survey, map coordinates, political subdivision); ownership; administrative responsibility for the area; elevation; aspect; slope percent; stand origin (natural, planted,

seeded, planted with natural fill-in); forest type; age at time of first measurement

(even-aged stands); known past treatment or injury; estimated site index (specify

system); soils classification and habitat type, when available. Quantitative items such

as elevation, aspect, and age should be recorded as numerical values rather than

classes, to provide flexibility in later use. For example, the practice of recording

aspect as cardinal direction only-instead of azimuth-prevents use of the trigonometric

functions in later analyses to describe the location of maximum and minimum growth.

There must be a complete record of stand conditions at the time of plot establishment

and immediately before any treatment. All stems removed should be recorded by

species and diameter at breast height (d.b.h.) and any treatment should be completely described. If d.b.h. is not directly available for cut trees, it should be estimated

from measured stump diameters and stump heights (Alemdag and Honer 1973, Beck

and others 1966, Chambers 1978, Curtis and Arney 1977, McClure 1968). When

plots are established in stands which have had cutting prior to plot establishment,

date of cut should be ascertained and the dimensions of trees removed from the plot

should be estimated by stump measurements or otherwise.

Although diameters can be estimated from stump measurements with reasonable

accuracy under favorable conditions, the procedure becomes unreliable when trees

are small, if stumps are not recent, or if portions of the plot are covered with slash or

brush or have been disturbed by logging equipment. Direct measurement before

trees are cut is preferable.

Each five tree of measurable size within the plot should be assigned a permanent

identification number. This is necessary for later separation and summarization of the

components of forest growth; namely, survivor growth, mortality, cut, and ingrowth

(Beers 1962).

Live trees that are below minimum measurable size at the time of initial plot establishment but appear likely to grow to measurable size later may also be assigned numbers and tagged at the time of establishment, even though d.b.h. is not measured.

Though initially time consuming, this insures that numbers will be in sequencethereby simplifying relocation of trees and handling of record sheets at subsequent

measurements. This practice is desirable in plantations and similar situations where

the number of such stems is limited and most will later reach measurable size.

As an alternative procedure for insuring that ingrowth trees will be numbered in

sequence with adjacent trees, tree numbers assigned at time of plot establishment

can be multiples of 10. When an ingrowth tree is later found, it is then assigned the

number of the nearest initially numbered tree, plus 1, 2 . . . 9 as the case may be. For

example, if a tree was initially assigned the number 1120, numbers 1121 through

1129 are then available for subsequent assignment to nearby ingrowth trees. This

system can be used when the number of very small trees makes initial tagging of all

trees impractical.

Tree Numbering

Record of Initial

Conditions
20

Figure 5.-Plot divided into sectors; arrows show

sequence of tree tagging and measurement. Tags

should be positioned to face direction of travel.

Subdivision lines are best oriented in the direction

most nearly parallel to the contour, to minimize effort

in traveling between trees and to facilitate use of

sectors in distributing site trees across any site

gradient.

The method used for numbering trees will depend in part on size and characteristics

of the trees. Metal tags attached with aluminum nails at breast height (b.h.) are

convenient for large thick-barked trees (nails should be driven no farther than necessary to stay in place, with the tag placed at the nailhead so that it does not quickly

become overgrown). On small trees and thin-barked species, nails may cause

swellings that interfere with measurement; where this is a problem, either tags can be

attached at a lower or higher point (with b.h. a fixed distance from the nail, preferably

indicated by a paint mark), or painted numbers can be used instead. For very small

trees, tags can be wired to a branch near b.h. If nails are used, they must be pulled as

needed at each meaurement to prevent bark overgrowing the tags. Nails should be

removed and the tag nailed to a root or below stump height before trees are cut. This

prevents damage to saws and allows identification of cut trees.

If painted numbers are used, these will require repainting as needed at subsequent

measurements to remain legible.

If tags are used when plots are established, the field crew should be provided with

sets of tags prenumbered in sequence. They should also have a label maker and

metal label tape to supply tags needed if the sequence provided is exceeded (duplication of tag numbers on the same plot must be avoided).

It is sometimes desirable to use a distinctive paint marking on site trees or height

sample trees (discussed on p. 28). It is often convenient to divide the plot into strips or

sectors with string to insure that no trees are missed and that tags are arranged in a

systematic manner (fig. 5). For reasons discussed later, it may be desirable to divide

the plot into numbered subplots so that trees can later be sorted by subplots when

wanted. Relocation of trees during plot remeasurements will be facilitated if all numbers are placed on the same side of the trees, within strips or subdivisions of the plot,

arranged so that tags face the direction of travel across the plot in a systematic

sequence.
21

A consistent procedure should be used with “line trees” in determining whether or not to

consider them on the plot and tag them. The decision is best based on location of the

center of the tree at stump height. Trees exactly on line by this standard can be classified as “in” or “out” according to the direction of lean, if any. Borderline cases can be

classified as “in” or “out” alternately or by coin toss. “Out” trees should be identified by

paint blaze or standard scribe mark facing the plot, to prevent later confusion.

Depending on stand conditions and stage of development, dead limbs may be pruned

to a height of 6 or 7 feet to facilitate numbering and later remeasurements.

At each remeasurement, a search should be made for additional unnumbered trees

and new numbers assigned to any found. If this is neglected, impossibly large “ingrowth” trees will later appear in the record. Such impossible “ingrowth” introduces

abrupt changes in calculated periodic growth values, and the missing values must then

be supplied by borings or by estimating past unmeasured diameters of these trees.

Note that when tagging such new trees in the field, one should not transfer to them

numbers previously used on trees that have died or been cut. This practice, though

convenient in the field, causes endless confusion. A label maker should be carried and

tags made as needed for newly assigned numbers. The number of the nearest previously numbered tree should be noted on the field sheet as an aid to later relocation.

For consistency in successive d.b.h. measurements on the same tree, all measurements must be made at the same point on the tree bole. The system used must include

a mark at the b.h. point on all numbered trees. This mark may be a painted band or the

location of the tag nail. There are, however, some unresolved inconsistencies in

definition of b.h. which require a choice.

In the United States, breast height has been defined both as 4.5 feet above mean

ground level (common practice in many past research studies) and as 4.5 feet above

ground level on the high side (common inventory practice). The former definition

sometimes gives unreasonably low points for large trees on steep slopes; the latter

definition gives a point that, for trees on steep slopes, rises as the tree increases in size

(Bruce 1980). A further source of uncertainty is that in many cases the standard used in

collecting the data used to construct existing volume tables is unknown.

On gentle slopes, the difference between the two procedures is slight.

A second inconsistency arises in the shift from English to metric measurements.

Traditionally, b.h. has been defined in the United States as 4.5 feet above ground,

however “ground” is defined. Some people in the United States and other Englishspeaking countries have used the equivalent metric value of 1.37 meters; however, the

international standard is 1.3 meters and this will probably eventually become standard

in the United States, as it is now in Canada (Bruce 1976, Demaerschalk and Kozak

1982).

RECOMMENDATIONS: When new plots are installed, it is bestto establish and

markthe b.h. point measured from ground level on the high side, thereby at least

partially avoiding the unreasonable heights that sometimes arise from use of average

ground level on steep slopes. All subsequent measurements should be made at this

same marked point on the tree. In new studies, measured in metric units from the start,

b.h. height should be the international standard 1.3 meters.

Determination of Breast

Height
22

A consistent procedure should be used for forked trees and trees with abnormal

swellings at the b.h. point. Suggested conventions are (fig. 6):

1. If a tree forks above b. h., treat it as a single tree, with the tag and diameter measurement below the swelling caused by the fork but as close to normal b.h. height as

feasible.

2. If a tree forks below b.h., treat it as two trees, with the tag and diameter measurement located at (1) 2.0 feet (0.6 m) above fork at the initial measurement or (2) 4.5

feet (1.3 m) above ground, whichever is higher.

3. If the tree has an abnormal swelling at the normal b.h. point, tag and measure it

immediately above the irregularity at the point where it ceases to affect stem form.

Stand age must be determined for all even-aged stands. This is best done at the time

of first plot measurement.

Tree ages are normally determined by boring at b.h., by counting rings on stumps, or

from known planting dates. Some estimate of intervening years is necessary to

convert age to corresponding total age from seed. The record may show age as either

total age from seed or age at b.h. but must clearly specify which and should indicate

the basis for conversion from actual measurements to the ages given.

A stand age based on borings at b.h. is highly desirable in plantations as well as in

natural stands, even though year of planting may be known. Time required to grow to

the b.h. point varies with weather, site preparation, brush control, and other factors

and is often considerably shorter in plantations than in natural stands. Hence, inconsistencies in method of determining age can introduce apparent differences among

stands that have little meaning for long-term development. Use of measured age at

b.h. in site estimation and growth relationships avoids at least part of this variation.

Stand age is meaningful only for even-aged stands. It should be defined as average

age of dominant or crop trees or of trees selected by some nearly equivalent numerical rule, such as the 40 largest per acre (100/ha). Occasional large residuals, lower

crown classes, and trees unlikely to reach rotation age should be excluded. The

sample should normally include designated site trees, if any, plus additional trees

selected from the stand tally on the basis of dominant or crop tree classification or the

40 largest trees per acre.

The sample should be large enough to determine the mean age of dominant (crop)

trees on the plot to a prespecified standard of precision. Staebler (1954) suggests a

standard error of the mean of 1.0 year or less, after elimination of obvious outliers.

Individual tree ages used in calculating the plot mean should be retained in the record,

with identifying tree numbers. The plot age carried in the record should be the mean

calculated to the nearest year, not a broad age class category.

In mixed species stands, sufficient samples of each major species should be taken to

determine whether or not age differences exist among species.

Determination of Stand

Age
23
24

Standard procedure at each scheduled plot measurement must provide for:

1. D.b.h. measurement of all trees above the lower limit of measurement.

2. Classification of measured stems by crown class, tree status, condition, cause of

injury or death, in accordance with a standard coding system. This must recognize the

categories:

a. Survivors.

b. Ingrowth.

c. Mortality.

d. Cut.

e. Intentionally killed trees.

Where variable radius plots are used, there will be the additional category “ongrowth”.

In even-aged stands, understory stems (those clearly of a younger age class than the

main stand) should be recognized as a separate crown class.

3. Measurement of heights of a sample of trees sufficient to provide a reliable heightdiameter curve and estimates of stand average height, top or dominant height, and

site index. (Measurement of heights to live crown is a highly desirable addition.)

4. An estimate of tree form. This is most commonly made indirectly by means of

standard volume tables or taper functions based on diameter and height but may be

done by direct measurement of a sample of trees.

When plots are remeasured, it is advantageous to use a standard tally sheet (fig. 7) or

recording device containing the previous measurements on each tree. New and old

measurements should be checked for reasonable agreement, and major discrepancies checked by remeasurement of the tree. This will frequently avoid gross blunders

and recording errors, which are easily corrected in the field but which become a major

nuisance if not caught until the compilation stage.

The initial measurement is particularly prone to blunders and recording errors, since

no check is available. One method of avoiding troublesome errors in the initial measurement is to make two successive measurements at the time of plot establishment,

exchanging the measurement and tally roles among the crew. Measurements that do

not agree within reasonable limits are repeated and corrected on the spot. The time

required for such a second measurement, although considerable, is usually a relatively small fraction of the total time required for initial plot installation and measurement.

Diameter measurements.-D.b.h. of each tagged tree should be measured at the

marked b.h. point at each plot remeasurement, normally to the nearest 0.1 inch or 1.0

millimeter. Except in stands with many very small stems, this is best done with a

diameter tape.

When a tree that died since the last measurement is encountered, its diameter is

recorded, together with a mortality code indicating that it was found dead at this

measurement. It will save time in future remeasurements if such trees are blazed and

the tag nails driven into the wood so that the tag does not fall off as the bark decays,

making the trees easily identifiable as previously recorded mortality.

Tree Dimensions
25
26

It has been a common practice in the past to measure only trees above an arbitrary

d.b.h. limit, more or less corresponding to some merchantability standard. This was

usually done to simplify fieldwork, but it has been the source of numerous difficulties

in analysis. Such truncation of diameters distorts the statistics of stand average

diameter and number of trees, hampers or prevents fitting of diameter distribution

functions, and often makes different data sets completely incompatible. It should be

avoided.

In principle, it is desirable to tally all stems taller than b.h.; however, very small stems

are difficult to tag and measure and may be numerous. As a practical matter, it is

usually necessary to adopt some lower limit of measurement such as 0.5 inch or 1.5

inches or 2.5 centimeters. Higher limits should not be used. Where it is not feasible to

measure all trees on the plot above such a limit, a subsampling scheme can be

adopted.

When fixed area plots are established in very young stands and are to be observed

over an extended time period, a plot size adequate for the initial condition is much too

small for the stand condition expected at the end of the observation period. Conversely, a plot size suitable for the final stand condition may initially involve tagging

and measuring a prohibitive number of small stems.

A procedure sometimes used in this situation is to tag and measure all stems on

subplots within the main plot, but only stems over a specified larger d.b.h. (no larger

than absolutely necessary) on the remainder of the plot. The sample of small trees

must be large enough to provide stable estimates and must be representative of trees

on the main plot area. Since small stems are frequently clumped, several systematically located subplots within the main plot may be preferable to the single concentric

plot often used. A common mistake is insufficient sampling of the small stems.

Particular care must be taken that the ingrowth over the larger d.b.h, limit is tagged,

numbered, and measured at each remeasurement.

Note that increment values for each successive period will be based on a slightly

different tree sample (because of ingrowth into the main plot), that this design complicates computation of plot summaries, and that it involves a continuing need to search

for and tag numerous new ingrowth stems at each subsequent measurement. Therefore, such subsampling should be used only when absolutely necessary.

When variable radius plot (point) sampling is used, the tree population must be

subdivided by a limiting d.b.h., below which trees are recorded on a circular fixed area

plot and above which trees are recorded if their diameter subtends an angle larger

than the critical angle for the basal area factor selected for the larger trees. Size of the

fixed area plot for small trees should match the size of the variable radius plot at the

limiting d.b.h. A suitable choice of limiting d.b.h. and associated size of the fixed area

plot can reduce the problem of measuring very large numbers of small trees, while

including enough such trees to define the diameter distribution.
27

Height measurements.-Stand height is (with age, number of trees, and average

diameter) one of the basic descriptors of a stand. It is essential to most analyses of

growth and yield. Heights are necessary for computation of volume and volume

increment, for estimation of site index, and for characterization of stand conditions

and stand development. Because measurement of heights is time consuming and

frequently inaccurate, height sampling and measurement are the weakest points in

much existing data.

For species in which the limit of merchantability is generally determined by bole

diameter, as in most conifers, only total height need be measured. Merchantable

heights, if wanted, are better determined from taper curves. In species where the limit

of merchantability is frequently determined by “breakup” of the main stem rather than

by diameter (for example, many hardwoods), it may be desirable to measure merchantable height in addition to (but not instead of) total height.

In most situations, it is impractical to measure heights of all trees on the plot, and one

must resort to subsampling. A suitable sample of trees should be measured for

heights when the plot is established and at each remeasurement.4

 This requires (1)

adequate sample size, (2) efficient distribution of the sample, and (3) careful height

measurement. Measurement of only a few heights at a given date, insufficient for

construction of a height-diameter or volume-diameter curve, serves no useful purpose.

RECOMMENDATIONS:

1. Each plot or cluster of subplots should be sampled independently. Samples

generally cannot be combined across plots without biasing analyses.

2. Height sample trees are best drawn initially from the plot tally, rather than selected

visually. After the initial sample is drawn, trees with broken tops, pronounced lean

(over 10°), severe malformations, or disease should be rejected. Sample trees should

be reasonably well distributed across the plot area.

3. The sample should include trees from the full range of diameters present. A

common and serious mistake is omission of small d.b.h. classes, which leaves the

curve shape undefined; the sample should not be confined to only dominants and

codominants.

4. Large d.b.h. classes should be sampled more heavily than small d.b.h. classes,

since they contribute more to volume, volume growth, and value.

5. When designated site trees are used (discussed on p. 34), these should routinely

be included in the height sample, with additional sample trees selected as needed to

provide a satisfactory distribution across the range of diameters.

4

 Given several well-distributed height samples, satisfactory curves for intermediate

dates can often be obtained by interpolation or by fitting a system of height-diameter-age

curves (Curtis 1967a). This, however, is computationally bothersome, may obscure real

differences in growth among periods, and is usually a makeshift solution made

necessary by past omissions. It is better to avoid the need.
28

6. Normally, except where new trees are needed replace trees lost by cutting, mortality, or severe top breakage, the same height sample trees should be used at each

successive measurement. This provides better estimates of height increment than

independent sampling at each measurement (even though it may perpetuate peculiarities of the initial sample). It may be convenient to mark trees with paint for easy

subsequent recognition. Lost trees should be replaced by other trees of similar

diameter and crown position. Over long periods or in plots established at an early

stage of stand development, it will become necessary to delete some trees and add

others to maintain a satisfactory distribution across the range of diameters.

A rule of thumb used at the Forestry Sciences Laboratory in Olympia, Washington,

calls for height measurement of at least 15 trees per plot, with two-thirds distributed

across the d.b.h. classes larger than average stand d.b.h., and one-third distributed

across the smaller d.b.h. classes. This is a minimum applicable to relatively small

homogeneous plots of a single species with well-established crown differentiation.

More trees will be required in large plots and mixed species stands and in young

plantations where crown differentiation is only beginning.

Height estimates should be compared with previous measurements before the field

crew leaves the plot. If obvious discrepancies are found, the measurement should be

repeated to determine whether the present or previous measurement is in error.

Where conditions allow, height growth since the previous measurement can also be

estimated from internodal distance, as a check in doubtful cases.

If more than one species are present, a decision must be made on sampling the

associated species. Options are:

1. If the secondary species represents a minor component of the plot, and particularly

if it is not greatly different in characteristics from the primary species, then the simplest course may be to ignore height differences and sample the primary species

only-accepting any error in volume computations that arises from use of heights of the

primary species in computing volumes for the secondary species.

2. If the secondary species is small in numbers but includes a few large trees with a

substantial contribution to plot volume, the best course will be to measure heights of

all such trees and use these heights in computation of their volumes.

3. If the secondary species represents a substantial portion of both plot volume and

numbers of trees, then a height sample should be drawn and measured the same as

for the primary species.

Choice of instruments and procedures for measurement of heights is influenced by

expected tree size, terrain, and brush and understory conditions.

In young stands height poles are fast and accurate. Commercially available telescoping poles provide measurements to 30-45 feet in height, depending on the model.

Certain sectional poles can be used, with difficulty, for heights up to 50-60 feet or

more. Care must be taken that the pole is kept close to the tree and that the pole tip is

at the same distance from the observer as the tree bole. The observer should stand

as far away as possible.
29

The most common procedure has been to measure slope distance from observer to

the tree with tape, and angles to tip and base of tree with an Abney level or similar

instrument graduated in percent slope. Then (1) calculate corresponding horizontal

distance using slope correction factors given in table 4 in the appendix (=cosine of

angle in degrees), and (2) calculate tree height as:

H = (horizontal distance) (slope percent, tip)

 - (horizontal distance) (slope percent, base);

where, slope to base is negative if below horizontal, positive if above.

This procedure is adequate for moderate size trees on moderate slopes, without

heavy brush. Special circular slide rules (Haig 1925, Stage 1959) simplify field

computation of heights, but these are being replaced by the programable pocket

calculator. With such a calculator and a clinometer graduated in degrees, cumbersome tables and calculation of horizontal distance as a separate step can be eliminated, using the procedure shown in figure 8. Angles should be read to the nearest

one-fourth degree (or 1 percent).

It is often convenient to adopt a standard procedure of sighting on the b.h. mark

rather than the base of the tree (often obscured by brush), and then adding the value

of b.h. (4.5 ft or 1.3 m) to the calculated height. A flashlight is useful to provide a

sighting point in heavy brush or shade.

On steep terrain or if heavy brush is present, distance measurement by tape becomes laborious and inaccurate, resulting in poor height measurements. Procedures

not requiring tape measurement of distance are advantageous.

Several optical rangefinders are on the market. In general, the simpler types lack the

precision needed for research work. Some limit the user to a fixed distance, which is

impractical in dense stands where trees are often visible from only a few points. The

more precise instruments are expensive, and some are cumbersome and difficult to

use with poor lighting and visibility.
30

Figure 8.-Estimation of tree height using clinometer and tape measurement of slope distance.

θι; is angle in degrees.

H is total tree height.

HLC is height to live crown.

h is height to lower aim point (usually, b.h.).

ds

 is slope distance, measured parallel to line of sight from observer to center of tree at lower aim point.

Angles should be measured to nearest one-fourth degree or 1 percent. Formulas for HLC are as shown, but with θ3 replacing θ2.
31

A useful procedure, requiring only a height pole and a clinometer, which provides

satisfactory precision for moderate size trees while eliminating tape measurement of

distance, is illustrated in figure 9 (Curtis and Bruce 1968, Bell and Gourley 1980).

Tall trees (over 100 feet or 30 meters) tax the accuracy of the Abney level and similar

instruments. Sighting angles over 45° should be avoided. Precision of hand-held

instruments can often be improved by resting the instrument hand on a staff as

support. This reduces hand tremor and provides a constant instrument height for all

angles measured from a given point. It is often advisable to make two height estimates from different positions and average the results, since errors are the combined

result of errors in clinometer reading and in measurement of distance, and of any

lean in the tree. An alternative procedure, sometimes useful in improving height

growth estimates in relatively open stands in which the tree tip is easily visible, is to

record bearing and slope distance from tree to observer at the initial measurement

and then take subsequent height measurements from the same position.

A tripod-mounted optical instrument such as the Bitterlich Telerelaskop or the British

“Enbeenco” clinometer will improve accuracy.5

 Special studies requiring accurate

height values for individual trees require measurement of angles by transit. For tall

trees in stands with reasonable visibility at rod height, the transit with stadia measurement of distances may be not only the most accurate method but also relatively rapid.

Crown measurements.-Crown dimensions have only rarely been measured in the

past. Yet, crown development reflects the past history of trees and stands and is

related to competitive status and growth rate and to future growth potential.

Live crown length is the most easily determined crown dimension. It is associated

with tree competitive status and potential response to treatment and has been a

useful predictor of growth in recent yield research (Hahn and Leary 1979, Holdaway

and others 1979, Krumland and Wensel 1980, Stage 1973). In combination with total

height, live crown length is equivalent to height to live crown or live crown ratio. These

can be obtained by including measurement of height to live crown for the trees in the

height sample.

Some care is needed in defining base of live crown for consistency among different

installations and measurements made by different individuals. A suggested definition

is “lowest whorl with live branches in at least three quadrants, exclusive of epicormic

branches and whorls not continuous with the main crown.” Irregular and one-sided

crowns must be ocularly “adjusted” to estimate the corresponding position of the base

of a normally formed crown of the same volume.

Crown widths are also frequently of interest in studies of tree and stand growth and

response to treatment.

5 The use of trade, firm, or corporation names in this publication is for the information

and convenience of the reader. Such use does not constitute an official endorsement

or approval by the U.S. Department of Agriculture of any product or service to the

exclusion of others that may be suitable.
32

Figure 9.-Estimation of tree height by the pole and clinometer method. θι is angle, in either degrees or percent.

Since tanθ = 0.01 * slope θ in percent, and the factor 0.01 cancels, the computational formulas are the same for either unit.

H is total tree height.

HLC is height to base of live crown.

h is height of lower aim point (usually b.h.).

p is length of portion of pole above lower aim point. Length of pole should be at least one-fourth of total tree height, more when

feasible.

Care must be taken that base and tip of pole are against the tree bole, or beside the tree at the same distance from the observer

as the tree bole.

Measurements should be taken perpendicular to direction of any tree lean.
33

Under favorable conditions, crown widths can be measured on large-scale aerial

photographs. Ground measurements require vertical projection of crown margins and

can be made with such simple instruments as the Suunto clinometer, or with any of a

variety of instruments constructed especially for the purpose (Montana and Ezcurra

1980, Shepperd 1973).

Ground measurements of crown width are easily obtained for short trees with crowns

extending nearly to the ground but become difficult and inaccurate with increasing

height to live crown, particularly when crowns are in contact with adjacent trees. Ground

measurement of crown widths is considerably more difficult and time consuming than

measurement of height to live crown.

RECOMMENDATIONS: Height to live crown should be measured on new research

installations and at least some of the more valuable older installations.

Crown width should be measured only on selected installations where there is a clear

and specific purpose for such measurements.

Upper-stem diameters and tree form measurements.-There may be need to measure upper stem diameters on a sample of trees for either of two reasons:

1. The form estimate implicit in conventional double-entry volume equations may not

adequately account for a change after treatment; hence, estimates may be needed for

individual plots or treatments.

2. Information on stem taper and size assortments may be needed as a basis for

subdivision of tree and stand volume into size, product, or value classes.

The question of possible effects of stand treatment on standard volume equation and

taper function estimates has not been entirely resolved. Direct estimation of individual

tree and plot volumes is laborious and expensive. Most researchers have preferred-in

the absence of clear evidence that individual plot volume and taper equations are

needed-to assume that treatment effects on form beyond those incorporated in standard volume equations can be ignored; hence, that upper stem measurements specifically for this purpose are probably not needed. This is assumption rather than clearly

demonstrated fact.

There is generally a need for estimates of volume to different merchantability limits, and

by size, product, or value classes. Some information is easily obtainable from the tarif

system (Brackett 1973, Turnbull and others 1980); more complete information is given

by stem taper curves.

Suitable taper curves are often available from other sources. If not, it may be desirable

to include upper stem measurements on a sample of trees to provide the basis for

developing such curves and associated assortment tables. Needs for such information

and existing sources should be considered as part of the study planning process.

If there is need for upper stem measurements, these can be obtained either by measurement of felled trees on the plot or on the adjacent buffer strip, or by dendrometry.

Commercially produced instruments suitable for measuring upper stem diameters in

the standing tree include the Barr & Stroud dendrometer, the Wheeler penta prism

caliper (Wheeler 1962), the Bitterlich Telerelaskop, and the transit dendrometer

(Robinson 1962).
34

Required measurements are stump height; stump diameter; d.b.h.; diameters outside

bark at height intervals of 0.05, 0.10, 0.20...1.0 fractions of total height (or more or less

equivalent absolute height intervals); bark thickness at point of diameter measurement;

total height; and merchantable height, in species where this is determined by factors

other than diameter. Height to base of live crown is a desirable additional measurement.

Detailed procedures and various taper and volume equations are given by Bennett and

Swindel (1972), Bitterlich (1981), Bruce (1972), Bruce and others (1968), Cao and

others (1980), Demaerschalk and Kozak (1977), Grosenbaugh (1963), Gray (1956),

Kozak and others (1969), Martin (1981), Max and Burkhart (1979), and Ormerod

(1973).

The time and cost of such data collection and analyses are substantial and should be

carefully evaluated in relation to needs before such work is undertaken.

Even-aged stands are commonly classified by site index, the expected height of a

specified portion of the stand at a specified reference age, as an index of productivity.

Details of definition of the stand component used and the estimation techniques differ

among species and regions because of the evolution of techniques over time and the

vagaries of different authors. Normally, classification is based on the principal species

present, although approximate conversions are possible for species having similar site

requirements.

Established procedures often involve subjective choice of site trees on the basis of

crown class or other descriptive criteria. Newer procedures define site trees by position

within the diameter frequency distribution. Where a procedure is well established, plot

measurement procedures should provide for its use. Procedures continue to evolve,

however, and a procedure in general use at the start of an experiment is not necessarily

that which will be used at its conclusion.

Trees with damage affecting height and height growth should be excluded. Height

estimates for the specified stand component may be obtained as values read from the

height-diameter curve for the mean diameter of the specified component, or as a mean

of measured heights of sample trees drawn from that component. If the latter procedure

is followed, guidelines will be needed for the required number of sample trees, based on

the variability of site index estimates. In general, the required number will increase as

plot size increases and also as the difference between plot age and index age increases, but the number cannot exceed the number of qualifying trees present on the

plot and, if necessary, its buffer strip. A site index estimate should not be based on fewer

than four trees per plot, and more are desirable when allowed by plot size and component specifications. Site trees should be identified on the plot record and remeasured at

successive plot remeasurements as long as they remain qualified site trees. Age of-all

site trees should be determined by boring at b.h.

Site index estimates will improve as stand age approaches the reference age. Therefore, a new estimate should be made for each measurement date. Actual shape of the

height growth curve varies among stands. As young stands develop, later estimates of

site index will more accurately represent the growth potential of the site. Site index

estimates often change over time, and the record should be updated as this occurs.

RECOMMENDATIONS: In general, it is best to base site index estimates on a stand

component defined in terms of the d.b.h. frequency distribution rather than subjective

crown classes. The preferred basis is a specified number of the largest diameter stems

per unit area (Curtis and others 1974), such as the 40 largest per acre (100 largest per

hectare).

Site Index Estimates
35

Application of any selection rule should include a “well-distributed stems” requirement

to insure that the average represents the entire plot area and is not materially influenced by any site gradient across the plot. (For example, on steep slopes the tallest

trees are often found along the lower edge of the plot.) One means of insuring this is

to divide the plot into subplots or strips parallel to the contour and of approximately

equal area, and then apply the site tree selection rule separately within each subplot.

Consideration should be given to stem mapping selected installations expected to be

major sources of long-term growth data. Stem maps can provide:

1. Easy relocation of missing trees and of sample trees drawn from the plot record.

2. Description of spatial distribution of stems.

3. Description of spatial distribution of mortality and injury.

4. Information needed for development of distance-dependent simulation models,

which use measures of intertree competition based on individual tree dimensions and

distances.

Stem mapping can be done rapidly in stands with moderate numbers of stems, good

visibility, and easy terrain. It becomes laborious, expensive, and error prone when

there are large numbers of small stems, difficult terrain, or dense brush; it should not

be undertaken lightly under such conditions.

One procedure determines coordinates by reference to two tapes stretched at right

angles, using right-angle prisms. Other procedures use angles and distances from

plot center (best for circular plots) or aerial photography (open stands).

Stem mapping need be done only once on an installation. Once coordinates for each

tree are available, actual stem maps for the first or any subsequent measurement

can be produced by computer.

A sequence of photographs showing stand development over time is useful for both

oral presentation of research results and illustration of publications. The need for

photographs should be considered and procedures specified at the time a study is

established. Usually, a sequence of photographs beginning with the initial plot measurement date should be obtained for at least a sample of plots, sufficient to illustrate

the stand conditions and treatments involved.

Photos are most useful when they show the same scene at successive points in time.

So far as is feasible with changing stand conditions, photos should be taken in the

same direction from the same points at successive dates. Photo points can be

identified either by distinctively marked stakes or by distance and bearing from plot

corners or plot center. A person or some object of easily recognized dimensions

should be included in photos to provide a size scale meaningful to the viewer.

For oral presentations, 35 mm transparencies are most useful, but they are generally

unsatisfactory for reproduction; black and white photographs in larger film sizes (for

example, 4 by 5 inches) are preferred for publication.

Photographs

Stem Maps
36

Photos are worthless unless they are carefully and completely identified by study,

installation, plot, location, direction, date, photographer, and any special points

illustrated. A systematic procedure must be used for identifying and filing photographs

to insure that the needed information is recorded; that each photo can be associated

with other records for a particular study, installation, and plot; and that negatives and

transparencies are protected from damage.

A plot remeasurement schedule should be specified and adhered to as closely as

possible. A standard planning procedure should be provided to insure that scheduled

remeasurements are not missed.

The interval between measurements depends on stand conditions and on the purpose

of the installation. In general, measurements at relatively short intervals are needed

for rapidly growing stands (young stands, good sites) or where there is major interest

in short-term changes in growth in response to treatment. Longer intervals suffice in

slower growing stands. Except where there is a specific need for measurements at

short intervals to define the shape of a response function, measurements at very short

intervals (say, under 3 years) are not generally useful because of the irregularities

introduced by year-to-year variations in growth and the measurement errors involved

in attempting to measure small changes.6

 With longer intervals and slower growing

stands, limited deviations from the planned measurement schedule may be allowable,

depending on the nature of the study; but measurements must not be missed or

postponed when an associated treatment is applied. A complete stand measurement

should be made whenever a thinning, fertilization, or other stand treatment is applied.

Research studies generally use a fixed interval for all plots in a given installation or

study. This is usually specified in calendar years but may be defined by amount of

height growth or other measure of stand development, as a means of allowing for

differences from expected growth rates and obtaining closer comparability among

installations.

Measurements should be made during the dormant season if possible. Although

fractional years arising from measurement during the growing season can be used in

analyses, they are a complication and a source of errors, which may be large for short

growth periods. Changes in bole moisture content and the attendant shrinkage and

swelling have measurable effects on diameters and estimated diameter increments;

to a considerable degree, these effects are associated with season and are reduced

by dormant season measurement.

Thinning.-Type, severity, and frequency of thinning in silvicultural research studies

are normally specified in the study plan. Procedures for applying and controlling

thinning on the ground to meet these specifications and needs for prethinning information will vary with study objectives and the required degree of control over the

thinning operations.

6 A first remeasurement soon after establishment will, however, serve

to correct measurement and recording errors made at the time of

establishment.

Control of Treatments

Remeasurement

Schedule
37

In precommercial thinning, the objective is generally some specified number of

well-spaced best trees, compatible with some target diameter for first commercial

thinning. Detailed knowledge of present stand statistics is usually not necessary to

apply the initial thinning, although knowledge of initial stand statistics may be needed

in later analyses. For subsequent thinnings, knowledge of pretreatment stand statistics and growth may or may not be necessary to carry out the thinning, depending on

study objectives and specifications.

In stands that have been previously spaced, the objective may also be to leave a

specified number of well-spaced best trees. This can often be achieved without prior

knowledge of stand statistics and growth. In some studies, however, knowledge of

individual tree growth obtained by measurement may be the primary basis for deciding which trees to remove.

If study specifications call for retention or removal of some specified fraction of

growth or growing stock, then the stand must be remeasured and stand statistics

calculated before the marking is done, since the approximate volume and size

distribution of trees are necessary as a guide to the marking operation.

The close control of residual numbers, size, and spatial distribution of trees needed in

many silvicultural studies often requires subdivision of the plot and plot record into

subplots or other subdivisions for marking purposes. Where very close control of

residual spacing is wanted, the area may be gridded with string or otherwise at the

desired spacing and the nearest suitable tree to each grid point designated as a leave

tree. More commonly, it will suffice if the required number of reasonably well-spaced

best trees is left on each subplot or other subdivision of the plot.

Fertilization.-Although operational forest fertilization is generally done by aerial

application, most research studies use carefully controlled hand application. The plot

is subdivided with string or paint into relatively small segments or squares, and

measured amounts of fertilizer are applied to each subdivision. Although this uniformity of application is not consistent with the variability encountered in operational

fertilization, it is necessary if the objective is to relate growth response to fertilizer

dosage.

Plots are sometimes installed in operationally fertilized areas for monitoring purposes,

in an attempt to estimate the gain in yield from fertilization. For meaningful results,

one or both of two procedures must be followed: (1) the fertilizer dosage actually

reaching each plot must be estimated by sampling with an adequate number of

fertilizer traps on each plot or (2) clustered subplots may be distributed within portions

of the treated area which are comparable in other respects, in a manner that insures

that the average amount of fertilizer received by the cluster will approximate the

nominal area dosage.

The gain in yield from fertilization is estimated by comparing growth on the fertilized

plots with that on comparable unfertilized plots, or with some other estimate of

expected untreated growth. Because of the relatively large treatment areas necessary

with aerial application, it is difficult to provide comparable control plots and adequate

replication. This fact, plus the high variability in actual dosage and in stand conditions

within operational areas, makes direct quantitative measurement of treatment response difficult, inaccurate, and often impossible; hence the researcher’s preference

for uniform ground application in fertilizer studies (Bruce 1977).
38

Main plot.-A complete stand measurement is needed whenever a thinning or fertilization treatment is applied to an installation. For plots that are fertilized only, a single

measurement suffices. For plots that are thinned, information is needed for the live

stand before thinning and after thinning, for trees cut, and for damage occurring during

the thinning operation. Prethinning statistics may or may not be used as a basis for

controlling the thinning operation, but they are always needed in analyses to describe

the initial conditions. Associated control plots are rarely sufficiently comparable to

provide satisfactory information. Postthinning stump measurements, though possible,

are often inaccurate and are an undesirable substitute for adequate prethinning measurements.

When possible, the prethinning measurement and the actual thinning should be done

during the same dormant season. Diameters of all trees should be measured before

thinning. A postthinning check is then made to identify trees cut, destroyed, or damaged

during the thinning operation. If there is substantial delay-one or more growing

seasons-between initial measurement and the actual thinning, a complete remeasurement of the installation is necessary after thinning; this situation should be avoided.

When thinning is done at the time of plot establishment, alternative procedures may be

used, depending on stand conditions and the expected numbers of cut and leave trees:

1. Permanently number all trees at the start. Tag or paint all trees with tree number and

a clear identification of the height at which d.b.h. is to be measured. Measure all trees

for exact d.b.h. (nearest 0.1 inch or 0.1 cm). Then make a postthinning check to identify

trees that were cut, destroyed, or damaged.

2. Temporarily tag all trees. To avoid permanent tagging of trees that are measured only

once and then cut, temporary numbered cards can be stapled to the trees. Numbers

should be in the sequence in which trees are encountered and positioned so that the top

edge of the tag denotes the height at measurement. Measure all trees and make the

postthinning check as in (1). Permanently number the leave trees with tags or paint at

the time of the postthinning check.

3. Preidentify leave trees. If leave trees can be identified before measurements are

made, it may suffice to measure and record other (cut) trees by 1-inch or 2-cm classes

only.

a. If numbers are assigned to these trees, they can be recorded in the order encountered which provides an indication of spatial position.

b. An alternative, sometimes necessary when large numbers of small trees are cut,

is a dot tally only of trees to be cut by size classes.

In either (a) or (b), all designated leave trees must be measured to 0.1 inch or 0.1 cm,

numbered, and tagged or painted. The postthinning check is made as in (1).

4. Preliminary dot tally to guide treatment.

If pretreatment stand statistics are needed to guide treatment and methods (1) or (2)

are not feasible, a dot tally of all trees by size classes may provide all that is needed.

Leave trees are then marked, numbered, and measured before thinning. A postthinning

check is made as in the other methods. (Numbering and accurate measurement of the

leave trees can be deferred until the postthinning check but may be severely hampered

by slash, and there is no opportunity to correct errors.)

Timing of Measurements

in Relation to

Treatment
39

When thinning is done at the time of plot establishment, it may be desirable to

measure heights at the time of the postthinning check, rather than at the prethinning

measurement. This avoids one-time height measurements on trees that are then

immediately cut, and confines the sample to trees likely to be present at the next

measurement. If, however, prethinning heights or volumes are needed as a basis for

controlling treatment, heights must be measured before thinning. Substitutes for

anytrees cut can be remeasured atthe postthinning check, which is often not made

until the next growing season. In such cases, recorded height should be the height at

the end of the previous growing season.

On previously measured plots, trees having prior height measurements should be

remeasured at the time of the prethinning measurement. If any of these trees are cut

or if additional trees are needed to maintain a desirable distribution of the height

sample, the additional trees should be added at the time of the postthinning check.

Growth estimates for the subsequent period can then be based on the same sample

trees.

Buffer strip.-Although all residual trees on the main plot must be assigned permanent numbers, tagged, and measured at the time of plot establishment, the procedure

to be followed with trees on the buffer strip may vary with the nature of the study and

the treatments applied.

There is normally no need to tag or measure trees on the buffer strip surrounding an

untreated control plot or any plot that is not thinned. There may or may not be need to

measure buffer strip trees on plots to be thinned, as a basis for controlling thinning. If

needed, a dot tally by diameter classes usually suffices.

Studies of individual tree competition that require information on diameter and

location of competing trees may require numbering, measurement, and stem mapping of trees in the buffer strip, in the same manner as on the main plot. This situation

arises when very small plots are used for such studies, in which it is not possible to

designate a central subplot that is not influenced by trees in the buffer strip.

In many instances plot procedures, measurement standards, data recording codes

and formats, and computational procedures have been developed more or less

independently for each study by the individual or organizational unit concerned. These

have been shaped by the investigator’s immediate interests, experience, and limitations, and are often inadequately documented.

There is an urgent need to draw together accumulated data from different sources, to

develop generally applicable estimates of treatment responses and potential yields.

There is also a need to secure new data to supplement those now existing and to

extend work to other species little studied as yet. The magnitude and costs of the plot

establishment, plot measurement, and data management tasks lead to the conclusion

that cooperative efforts involving several organizations are necessary. Cooperation

and exchange of data are severely hampered by the general absence of uniform

procedures for collecting, coding, recording, and summarizing data.

It is often a major task merely to discover what information exists. Much information is

lost in attempting to reconcile inconsistent measurements and coding systems.

Individual data sets frequently require their own tailormade computer programs.

Conversion to a common format and codes, essential for analysis by a single set of

programs, is costly and prone to error.

Data Management
40

Standardization is clearly needed. It is probably impractical to write detailed specifications for nationwide use. Research workers and cooperating organizations concerned

with particular species or types of major importance should jointly prepare and adopt

specifications for collecting and recording permanent plot data. These should provide

for a minimum set of required measurements and information codes and a common

basic record format.

The elements involved are:

1. Establishment and maintenance of an index of plot data relevant to specified

objectives which can be continuously updated. This would provide specified information on the nature of the installation and treatment and status of existing data.

2. Agreement on and specifications forthe basic design standards and measurements

to be made on all permanent plots.

3. Adoption of a standard data format and coding system. It is impossible to anticipate

the special interests and objectives of individual studies and investigators, and these

should therefore be designed so that the user has latitude to subdivide codes or add

additional special purpose codes, while retaining certain mandatory lower category

codes common to all data in the system and necessary for compatibility with the

associated computational package.

4. A package of computer programs designed to operate on data in the standard

format and codes. These should include programs for:

a. Maintaining and updating index information describing plot status.

b. Editing and correcting plot and tree data.

c. Updating plot and tree records.

d. Calculating standard summaries of plot and tree data.

Portions of such systems already exist in some organizations, although most either

are not publicly available or are incomplete or inadequately documented.

Western Forestry and Conservation Association (1977) gave a list of recommended .

items to be included in plot records. Arney and Curtis (1977) gave specifications for a

plot index system and a detailed tree record format and coding system used in a large

regional yield study in Douglas-fir. These codes and formats are being revised at the

Forestry Sciences Laboratory, Olympia, Washington, and an associated package of

computer programs is in preparation.7

This system is now in trial use in one large study in coastal Douglas-fir in Oregon and

another in the hemlock-spruce type in Alaska. In its present form, the system is

applicable only to fixed-area plots. Current expectations are that the specifications,

programs, and documentation will be available by 1984.

Some examples of codes and types of information are given in “PDMS Tree Classification Codes” in the appendix. These are subject to change, and there is no implication intended that others should adopt these as given. They do, however, illustrate the

types of information that must be provided in such a system.

7 Curtis, Robert O.; Clendenen, Gary W. Plot data management system

(PDMS). Study plan on file at the Forestry Sciences Laboratory, Olympia,

Washington. 1981.
41

Alemdag, I. S.; Honer, T. G. Relationships between breast-height and stump diameters for eleven tree species from eastern and central Canada. Inf. Rep.

FMR-X-49. Ottawa, ON: Forest Management Institute, Canadian Forestry Service,

Department of the Environment; 1973. 14 p. plus tables.

Arney, James D.; Curtis, Robert O. Code legend for standardized permanent plot

records. In: Reimer, D. R., chairman. Standards of measure and data sharing:

report of the Committee of Standards of Measure and Data Sharing (COSMADS).

Portland, OR: Western Forestry and Conservation Association; 1977. 18 p.

Beck, James A., Jr.; Teeguarden, Dennis E.; Hall, Dale O. Stump diameter-d.b.h.

relationships for young-growth mixed conifer species. Calif. For. and For. Prod. 44.

Berkeley, CA: University of California, School of Forestry; 1966. 6 p.

Beers, Thomas W. Components of forest growth. J. For. 60(4): 245-248;1962.

Bell, John F.; Gourley, Robert. Assessing the accuracy of a sectional pole, Haga

altimeter, and alti-level for determining total height of young coniferous stands.

South. J. Appl. For. 4(3):136-138; 1980.

Bennett, F. A.; Swindel, B. F. Taper curves for planted slash pine. Res. Note SE-179.

Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest

Experiment Station; 1972. 4 p.

Bitterlich, Walter. Telerelaskop techniques. In: Proceedings 17th world congress of

the International Union of Forestry Research Organizations, Div. 4; [Date of meeting unknown]; Japan. [Place of publication unknown]: [Publisher name unknown];

1981: 155-162.

Brackett, Michael. Notes on tarif tree volume computation. Resour. Manage. Rep. 24.

Olympia, WA: State of Washington, Department of Natural Resources; 1973. 26 p.

Bruce, David. Metrication-what’s next? J. For. 74(11): 737-738; 1976.

Bruce, David. Yield differences between research plots and managed forests. J. For.

75(1): 14-17; 1977.

Bruce, David. Where is the ground? In: Growth of single trees and development of

stands: Proceedings, joint meeting of working parties S4.01-02 and S4.02-03,

International Union of Forestry Research Organizations; 1979 September 14-15;

Vienna. [Place of publication unknown]: [Publisher name unknown]; 1980: 49-50.

Bruce, David; Curtis, Robert O.; Vancoevering, Caryanne. Development of a system

of taper and volume tables for red alder. For. Sci. 14(3): 339-350; 1968.

Bruce, Donald. A method of preparing timber-yield tables. J. Agric. Res. 32(6):

543-557; 1926.

Bruce, Donald. Some transformations of the Behre equation of tree form. For. Sci.

18(2): 164-166; 1972.

Cao, Quang V.; Burkhart, Harold E.; Max, Timothy A. Evaluation of two methods for

cubic-volume prediction of loblolly pine to any merchantable limit. For. Sci. 26(1):

71-80; 1980.

Literature Cited
42

Carbonnier, Charles; Fries, Joran. Permanent plots in Swedish growth and yield

research. In: Fries, J., ed. Permanent plots in forestry growth and yield research.

Subject Group S4.01. Research Notes 43. Stockholm: International Union of

Forestry Research Organizations, Royal College of Forestry, Department of Forest

Yield Research; 1976: 50-56.

Chambers, Charles J., Jr. Predicting dbh from stump dib and stump height for second

growth Douglas-fir. DNR Note 25. Olympia, WA: State of Washington, Department

of Natural Resources; 1978. 2 p.

Clutter, Jerome L.; Jones, Earle P., Jr. Prediction of growth afterthinning in old-field

slash pine plantations. Res. Pap. SE-217. Asheville, NC: U.S. Department of

Agriculture, Forest Service, Southeastern Forest Experiment Station; 1980.14 p.

Curtis, Robert O. Height-diameter and height-diameter-age equations for

second-growth Douglas-fir. For. Sci. 13(4): 365-375; 1967a.

Curtis, Robert O. A method of estimation of gross yield of Douglas-fir. For. Sci.

Monogr. 13; 1967b. 24 p.

Curtis, Robert O.; Arney, James D. Estimating d.b.h. from stump diameters in

second-growth Douglas-fir. Res. Note PNW-297. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment

Station; 1977. 7 p.

Curtis, Robert O.; Bruce, David. Tree heights without a tape. J. For. 66(1):

60-61;1968.

Curtis, Robert O.; Clendenen, Gary W.; DeMars, Donald J. A new stand simulator for

coast Douglas-fir: DFSIM user’s guide. Gen. Tech. Rep. PNW-128. Portland, OR:

U.S. Department of Agriculture, Forest Service, Pacific Northwest Forest and

Range Experiment Station; 1981. 79 p.

Curtis, Robert O.; DeMars, Donald J.; Herman, Francis R. Which dependent variable

in site index-height-age regressions? For. Sci. 20(1): 74-87; 1974.

Decourt, N. Protocole d’installation et de mesure des placettes de production semipermanentes: Procedures for installation and measurement of semi-permanent

yield plots. [Place of publication unknown], France: Centre National de Recherches

Forestieres (INRA); 1973. 25 p.

Demaerschalk, J. P.; Kozak, A. The whole-bole system: a conditioned dual-equation

system for precise prediction of tree profiles. Can. J. For. Res. 7(4): 488-497;1977.

Demaerschalk, Julien P.; Kozak, Antal. Dbh measurements and conversions in the

metric system. For. Chron. 58(4): 173-175; 1982.

Fabricius, L.; Oudin, A.; Guillebaud, W. H. Outlines for permanent sample plot investigations. [Place of publication unknown]: International Union of Forest Research

Organizations; 1936. 33 p.

Forestry Commission. Sample plot code. London: (British) Forestry Commission;

1979. Unpaged.

Gray, H. R. The form and taper of forest-tree stems. Inst. Pap. 32. Oxford: Oxford

University, Imperial Forestry Institute; 1956. 79 p.
43

Grosenbaugh, L. R. Optical dendrometers for out-of-reach diameters; a conspectus and

some new theory. For. Sci. Monogr. 4;1963. 47 p.

Hahn, Jerold H.; Leary, Rolfe A. Potential diameter growth functions. In: A generalized

forest growth projection system aplied to the Lake States region. Gen. Tech. Rep.

NC-49. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central

Forest Experiment Station; 1979: 22-26.

Haig, I. T. Short cuts in measuring tree heights. J. For. 23(11): 941-944; 1925.

Hamilton, G. J. Permanent sample plots in Britain. In: Fries, J., ed. Permanent plots in

forestry growth and yield research. Subject Group S4.01. Research Notes 43.

Stockholm: International Union of Forestry Research Organizations, Royal College of

Forestry, Department of Forest Yield Research; 1976: 75-81.

Hegyi, F. Optimum plot dimensions for experimental designs in jack pine stands. Sault

Ste. Marie, ON: Canadian Forestry Service, Department of the Environment, Great

Lakes Forest Research Centre; 1973. 13 p.

Holdaway, Margaret R.; Leary, Rolfe A.; Thompson, Jerrilyn LaVarre. Estimating mean

stand crown ratio from stand variables. In: A generalized forest growth projection

system applied to the Lake States region. Gen Tech. Rep. NC-49. St. Paul, MN: U.S.

Department of Agriculture, Forest Service, North Central Forest Experiment Station;

1979: 27-30.

Hummel, F. C.; Locke, G. M. L.; Jeffers, J. N. R.; Christie, J. M. Code of sample plot

procedure. For. Comm. (G. B.) Bull. 31; 1959. 113 p.

Jaakola, Sipi. On the use of variable size plots for increment research. In: Proceedings

14th world congress of the International Union of Forestry Research Organizations.

Div. 6, Sect. 25; [Date of meeting unknown]. [Place of publication unknown]: [Publisher

name unknown]; 1967: 370-378.

Jeffers, J. N. R. Experimental design and analysis in forestry research. [Place of publication unknown]; International Union of Forest Research Organizations; 1959. 172 p.

Keen, F, P. Climatic cycles in eastern Oregon as indicated by tree rings. Mon. Weather

Rev. 65(5): 175-188; 1937.

Kozak, A.; Munro, D. D.; Smith, J. H. G. Taper functions and their application in forest

inventory. For. Chron. 45(4): 458-463; 1969.

Krumland, Bruce; Wensel, Lee C. Concepts, design, and uses of coastal growth models.

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New Zealand: New Zealand Forest Service, Forest Research Institute; 1979: 253-301.
44

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Service, Canada Department of Mines and Resources, Ottawa; 1946. 69 p.

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Experiment Station; 1954. 14 p.
45

Stage, Albert R. A cruising computer for variable plots, tree heights, and slope corrections. J. For. 57(11): 835-836; 1959.

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60(12): 877-878; 1962.
46

Appendix

Checklist of Needed Plot and Tree Measurement

Information

The following list is taken from the current version of the

Plot Data Management System (PDMS). This is still

under development and is subject to change; readers

may not wish to follow the details. It does, however,

indicate items that should be recorded in some comparable manner.

Header (index) information.-

Installation number

Plot number

Status: active, abandoned, destroyed

Plot age b.h., at first measurement

Site index

Site index system used

Plot area

Plot shape

Stem mapped: yes or no

Stand origin: natural, planted, seeded (if known, note

spacing, seed source, etc., under general comments)

Primary species

Secondary species

Location: forty, section, township, range,

State

Elevation

 Aspect, azimuth (N=360)

Slope percent

Slope position

Local name of installation

Measurement units: English vs. metric

Organization responsible

Project identification

Date of first measurement: month, day, year

Date of last measurement: month, day, year

Date of first thinning, if any: month, day, year

Date of last thinning, if any: month, day, year

Date of first fertilization, of any: month, day, year

Date of last fertilization, if any: month, day, year

Fertilization treatments: (enter successively for repeated

treatments)

Method of fertilizer application (hand, fixed wing, helicopter)

Nutrient element, application rate per unit area

Physical soil description (if available)

Analytical soil characteristics (if available)

Area environmental characteristics (if available)

General comments: (Provides for descriptive notations

on any special characteristics of the area, plot, or

treatment history not adequately described by the

above)
47

Individual tree records.-

Installation number

Plot number

Tree number

Species Age b.h. as of first plot measurement (sample

trees only)

Stem map coordinates (stem-mapped plots only)

Number of measurements on plot

Tree measurement information to be recorded for each

successive measurement:

D.b.h.

Height (height sample trees only)

Height to live crown (height sample trees only, optional)

Crown class code

Tree status code

Tree damage, location (optional)

Tree damage, cause, general (optional)

Tree damage, cause, specific (optional)

See “PDMS Tree Classification

Codes,” page 48, for code

definitions as used in the 1982

version of PDMS.

Standard USDA Forest Service Species Codes for

Western Species1

1 Unclassified Softwoods 93 Engel mann Spruce 201 Big cone Douglas-fir 542 Oregon Ash

4 Unclassified Hardwoods 94 White Spruce 202 Inland Douglas-fir 631 Tan Oak

11 Pacific Silver Fir 95 Black Spruce 204 Eastslope Rocky Mtn 740 Cottonwood Species

15 White Fir 96 Blue Spruce Douglas-fir 741 Balsam Poplar

17 Grand Fir 98 Sitka Spruce 205 Coastal Douglas-fir 746 Quaking Aspen

18 Corkbark Fir 101 Whitebark Pine 211 Coast Redwood 747 Black Cottonwood

19 Subalpine Fir 102 Bristlecone Pine 212 Giant Sequoia 760 Cherry Species

20 California Red Fir 103 Knobcone Pine 231 Pacific Yew 800 Oak Species

21 Shasta Red Fir 104 Foxtail Pine 242 Western Red Cedar 803 Arizona White Oak

22 Noble Fir 106 Pinyon Pine 251 California Torreya 805 Canyon Live Oak

41 Port-Orford Cedar 108 Lodgepole Pine 263 Western Hemlock 807 Blue Oak

42 Alaska Yellow Cedar 109 Coulter Pine 264 Mountain Hemlock 810 Emory Oak

51 Arizona Cypress 112 Apache Pine 310 Maple Species 814 Gambel Oak

60 Juniper Species 113 Limber Pine 312 Big Leaf Maple 815 Oregon White Oak

62 California Juniper 114 Mexican White Pine 313 Box Elder 818 California Black Oak

63 Alligator Juniper 116 Jeff rey Pine 350 Alder Species 821 California White Oak

64 Western Juniper 117 Sugar Pine 351 Red Alder 829 Mexican Blue Oak

65 Utah Juniper 118 Chihuahua Pine 361 Pacific Madrona 839 Interior Live Oak

66 Rocky Mtn Juniper 119 Western White Pine 376 W. Paper Birch 920 Willow Species

71 Tamarack 120 Bishop Pine 377 Alaska Paper Birch 981 Oregon Myrtle

72 Subalpine Larch 122 Ponderosa Pine 378 NW Paper Birch 999 Noncommercial Species Not

73 Western Larch 124 Monterey Pine 431 Golden Chinkapin Coded in other Specific Codes

81 Incense Cedar 127 Digger Pine 492 Pacific Dogwood Such as Vine Maple, Cascara,

92 Brewer Spruce 540 Ash Species Etc.

1

 Quoted from Forest Survey Handbook. Forest Service Handbook

SH 4813.1. March 1967.
48

PDMS Tree Classification

Codes

The following system of tree classification codes is that

used in the 1982 version of the PDMS system.

Note that although the system provides for six digits of

information, including very detailed information on tree

condition and cause of damage, only the first two digits

are necessary for operation of summary programs and

are mandatory for all tree measurements.

This system may not meet all needs, but it does illustrate

characteristics needed in any system. It is sufficiently

general that with minor modifications it should meet

most needs.

For all classifications, programs will assign code “0” if no

other entry is present.

1. Crown class

0 No estimate

1 Dominant

2 Codominant

3 Intermediate

4 Suppressed

5 Understory

6 Overstory

7 Off-plot tree

Codes 5, 6, and 7 are necessary for operation of PDMS

and must be entered when applicable. Code 7 has

priority over all other crown class designations (that is, if

both 7 and another code apply, record 7). Code 5 is a

tree in an even-aged stand which is clearly of a younger

age class than the main canopy. Code 6 is a tree in an

even-aged stand that is recognized as substantially older

than the average age of the main canopy. Code 7 is a

site tree or buffer strip tree located off the plot proper;

these trees may be measured for site estimates or

included in stem maps but are excluded from plot

summaries.

2. Tree status

0 Live

1 Live cut

2 Dead

3 Ingrowth

4 New tree (that is, a tree missed in previous

measurement)

5 Dead cut, salvable

6 Live tree with measured height, not suitable for

height-diameter curves or site estimates

7 Both site and crop tree

8 Site tree

9 Crop tree

Codes 1 through 6 are essential to PDMS and must be

entered when applicable. Codes 7, 8, and 9 are not

essential to the system but should be recorded when

applicable and override code 0. Codes 1 through 6 have

priority over codes 7, 8, and 9. (Dead or cut trees are

identified as site or crop trees by a summary program

check on classification at the previous measurement.)

Codes 7, 8, and 9 are treated as code 0 by PDMS in

summary computations. Programs will treat a code 5

tree as code 2 and include it in mortality if the tree was

alive at the immediately preceding measurement; if

coded 2 at the immediately preceding measurement, the

tree will be excluded from mortality totals for the current

measurement.

3. Location and nature of damage or cause of death

(code only the most serious damage)

0 No damage or no information

1 Damage present, location and nature unspecified

2 Tip

3 Foliage

4 Limbs

5 Bole, other than 2 or 6

6 Basal

7 Roots

8 Leaning or bent tree

9 Down tree

These codes and those for severity and cause of

damage (classifications 4, 5, and 6 below) are not

essential to operation of standard PDMS programs. It is

desirable to include the classifications for location and

severity (3 and 4) at least for the conditions that render a

tree unsuitable for use as a height-diameter sample or

as a site tree. Otherwise, one may use all, some, or

none of those codes as desired.
49

4. Severity of damage

0 Unspecified

1 Minor

2 Moderate

3 Severe

Where more than one type or location, of damage is

present, rate “severity” as the combined effect of all

damage-minor if damage is noticeable but judged

unlikely to have a significant long-term effect; moderate

if the tree is judged likely to survive but with substantially

reduced growth rate or value; severe if the tree is judged

likely to die or become unmerchantable.

5. Cause and nature of 6. Cause and nature of

damage-general damage-specific

0 Unknown or 0 Unknown or

unspecified unspecified

1 Human activities 0 Unknown or

unspecified

1 Logging

2 Foliage sprays

3 Bole treatments

4 Root and soil

treatments

5 Pruning2

6-9 User defined

2 Crown diseases and 0 Unknown or

abnormalities unspecified

1 Unhealthy

appearance

2 Foliage diseases

3 Mistletoe

4-9 User defined

3 Bole diseases and 0 Unknown or

abnormalities unspecified

1 Bole rots

2 Multiple stems and

forks

3 Stem cankers and

mistletoe

4 Sweep and crook

5 Dead or broken top

6 Epicormic branching

7 Fluting

 8-9 User defined

4 Root diseases 0 Unknown or

unspecified

1-9 User defined

5 Insects 0 Unknown or

unspecified

1 Defoliators

2 Bark beetles

3 Sucking insects

4-9 User defined

6 Mammals and birds 0 Unknown or

unspecified

1 Deer, elk

2 Bear

3 Livestock

4 Porcupine

5 Mountain beaver

6 Other small mamr

7 Birds

8-9 User defined

7 Fire 0 Unspecified

1-9 User defined

8 Weather 0 Unspecified

1 Wind

2 Snow, ice

3 Freeze

4 Drought

5-9 User defined

9 Miscellaneous 0 Unspecified

1-9 User defined

2

 Note: Code 5 is recorded at initial measurement of any pruned tree. If subsequently

coded as damaged by other causes, it is still identifiable by a summary program

check for code 5 at previous measurements.
50

Plot measurement record form.-A standard form, which can also serve as a data

entry document, should be used for field measurements. For remeasurements, the

information needed for tree identification plus previous measurement values needed

to provide a check against measurement errors must be entered before fieldwork.

Several organizations are now using computer-produced forms for this information.

Figure 7 is based on one of these forms, modified to conform to the standards and

coding system used in the 1982 version of PDMS. (Although this particular variation

has not yet been implemented at the Forestry Sciences Laboratory at Olympia, an

earlier version has been in use for several years.)

The successive fields represent:

TREE #: tree identification number, preprinted for all trees recorded at the previous

measurement. Final digit is “0” for trees present at initial measurement (can be left

blank on field form, if preferred); subsequent ingrowth trees are assigned a number

determined as that of the nearest initial tree + a nonzero integer from 1 to 9.

SP: tree species, coded by standard USDA Forest Service three-digit species code

(see p. 47). Preprinted.

AGE BH: tree age at breast height, as of the year of plot establishment. Preprinted if

determined at the date of a previous measurement.

DIAMETER:

“74”- previous measurement, 1974 in this case. 1974 diameters preprinted on forms.

“76”- previous measurement, 1976 in this case. Preprinted. Blank columns: used for

entry of new field measurements of d.b.h. as illustrated. Enter measurements to 0.1

unit (inches or centimeters). Enter year of measurement in column heading.

H: total height of height sample trees. When heights are determined by one of the

clinometer methods, this value is transcribed from the height measurement field sheet

(fig. 10), after completion of field measurement and before data are entered into the

computer system. If heights are measured with a height pole, heights are entered

directly on this form. Last column to be used only if height is measured to nearest 0.1

unit.

CC: crown class.

“76”- value recorded at previous measurement, 1976 in this case. Preprinted. Blank

column-used for entry of new field measurement, as shown.

STAT: tree status (see tree classification codes, p. 48).

“76”- status code from previous measurement, 1976 in this case. Blank column-used

for entry of new field measurement as illustrated. Enter year in heading.

DAMAGE: Damage classification codes (see p. 48-49).

“76” -severity code from previous measurement, 1976 in this case. Preprinted. Blank

columns-used for entry of new field observations. “Loc” = location; “Sev” = severity;

“Cause” = cause, general; “Spec” = cause, specific.

Field Tree Measurement

Forms and Height

Measurement

Procedures
51

HLC: height to base of live crown. When determined by one of the clinometer methods, this value is transcribed from the height measurement field sheet (fig. 10), after

field measurements are completed and before data are entered into the computer

system. It can be entered directly when measured with a height pole.

Last column to be used only if measured to 0.1 unit.

Tree coordinates: X and Y coordinates of tree. Preprinted if plot has previously been

stem mapped. Left blank and available for “Notes” if plot is not stem mapped.

NOTES: Blank space for any miscellaneous information not covered by specified

items, or for reference to explanatory notes elsewhere, if any.

Height measurement form and measurement procedures.-Sample tree height

measurements are normally obtained as a separate operation after measurement of

diameters of all trees on the plot. The diameter record is used as the basis for

selecting or modifying the sample of trees to be measured for heights.

A form for recording height measurements in the field is given in figure 10. The form

is designed for use of either of two common height measurement procedures described in figures 8 and 9. (If heights are measured with a height pole, values are

entered directly on the plot measurement form (fig. 7).)

Numbered columns on the form (fig. 10) represent the following:

1. Tree identification number for each tree in the height sample.

2. D.b.h. of each tree.

3. Recorded height (H) at last measurement, if any.

4. Recorded heightto live crown (HLC) at last measurement, if any. (Note: i , 2, 3,

and 4 may be either preprinted on the form or transcribed from a

computer-generated list of trees measured for heights at the last measurement.

This initial list must then be modified by any deletions and additions needed to

obtain a satisfactory height sample for the current measurement.)

5. Slope distance from instrument to tree.

6. Angle to tip of tree.

7. Blank column, provided to allow for measurements to some other point, if

wanted; for example, if height of the nth node from tip is wanted to provide an

estimate of height growth in the last n years.

8. Angle to base of live crown.

9. Angle to tip of measurement pole (when using pole and clinometer method).

10. Length of portion of pole used in item 9.

11. Angle to lower aim point.

12. Height of lower aim point above ground.

13. Blank column provided for miscellaneous notes.

14. Total height of tree calculated from the above values.

15. Height to base of live crown calculated from the above values.
52
53

Values of H and HLC should be calculated in the field and compared with previous values

(if any) recorded in columns 3 and 4. If differences appear unreasonable for the time

involved and apparent lengths of leader and internodes, the heights in question should be

remeasured to be sure that current measurements and calculation are correct. Any

abnormal leader and internode lengths or other characteristics that would account for an

apparently inconsistent previous value should be noted, as an aid to later data editing.

After field measurements are complete, the calculations in columns 14 and 15 should be

checked for arithmetical errors and the values of H and HCL transcribed to the plot

measurement record form. This serves as the data entry document.

Equipment Checklist for

Field Plot Work

Modify this checklist as needed for specific jobs:

Tatum holder

Pocket calculator (preferably programable)

Extra battery pack for above

Field tally sheets (or recording device), with previous

measurements, if any

Coordinate paper or standard form for sketch maps

Protractor Engineer’s pocket scale

Copy of study plan or establishment report

Manual or specifications with applicable measurement

instructions and recording codes

Maps

 Aerial photos

Pocket stereoscope

String, large cones (for delimiting plot boundaries and

strips within plot)

Paint gun or pressurized paint cans; tube paint for marking boundaries, numbering trees, marking b.h. point

Lumber crayons, yellow

Lumber crayon holders

Nails, aluminum (for tags)

Prenumbered metal tags, in sequence (if tagging new

plot)

Label maker with metal tape

Claw hammer

Aluminum wire (for tagging small trees, corner stakes)

Flagging, assorted colors

Bark scribe

Hatchet

Machete

Small maul (for driving stakes)

Stakes (metal or other permanent material, for marking

plot corners and centers)

Pruning saw

Staple gun, staples, cards (if there may be a need to tag

trees temporarily)

Pocket compass

Staff compass with staff

Steel tape, 150 ft or 60 m, with reel (for laying out plot

boundaries and measuring base lines)

Tape repair sleeves or spare tape

Pocket cloth tape, 75 ft or 30 m

Range poles

Height pole

Clinometers of type appropriate for expected tree size

Tripod if required by above

Diameter tapes

Increment borers (two sizes) with extra bits Increment

core holders (plastic drinking straws or the equivalent)

Bark gage

Hand lens

Flashlight with extra batteries

Transit with tripod (initial plot layout)

Stakes, tacks (initial plot layout)

Plumb bobs (initial plot layout)

First aid kit

Packs for carrying equipment
54

Plot Dimensions and Conversion Tables (Tables 1-4)

Table 1-Dimensions of square plots of specified area

Table 2-Dimensions of circular plots of specified area
55

Table 3-Multipliers to convert slope distance to horizontal distance and horizontal distance to slope distance 1
56

Table 4-English and metric equivalents
57

Curtis, Robert O. Procedures for establishing and maintaining

permanent plots for silvicultural and yield research. Gen. Tech.

Rep. PNW-155. Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Forest and Range Experiment

Station; 1983. 56 p.

This paper reviews procedures for establishing and maintaining

permanent plots for silvicultural and yield research; discusses

purposes, sampling, and plot design; points out common errors; and

makes recommendations for research plot designs and procedures

for measuring and recording data.

Keywords: Plot analysis, permanent sample plots, tree measurement, sample plot design.
58

The Forest Service of the U.S. Department of Agriculture

is dedicated to the principle of multiple use management

of the Nation’s forest resources for sustained yields of

wood, water, forage, wildlife, and recreation. Through

forestry research, cooperation with the States and

private forest owners, and management of the National

Forests and National Grasslands, it strives - as directed

by Congress - to provide increasingly greater service to

a growing Nation.

The U.S. Department of Agriculture is an Equal Opportunity Employer. Applicants for all Department programs

will be given equal consideration without regard to age,

race, color, sex, religion, or national origin.

Pacific Northwest Forest and Range

Experiment Station

809 N.E. Sixth Avenue

P.O. Box 3890

Portland, Oregon 9708