Permanent-Plot Procedures 

for Silvicultural and Yield 

Research

Robert O. Curtis and David D. Marshall

United States 

Department of 

Agriculture

Forest Service

Pacific Northwest 

Research Station

General Technical 

Report

PNW-GTR-634 

April 2005
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 (USDA) prohibits discrimination in all its programs and 

activities on the basis of race, color, national origin, gender, religion, age, disability, political 

beliefs, sexual orientation, or marital or family status. (Not all prohibited bases apply to all 

programs.) Persons with disabilities who require alternative means for communication of 

program information (Braille, large print, audiotape, etc.) should contact USDA’s TARGET 

Center at (202) 720-2600 (voice and TDD).

To file a complaint of discrimination, write USDA, Director, Office of Civil Rights, Room 326-

W, Whitten Building, 14th and Independence Avenue, SW, Washington, DC 20250-9410 or 

call (202) 720-5964 (voice and TDD). USDA is an equal opportunity provider and employer.

USDA is committed to making its information materials accessible to all USDA customers 

and employees.

Authors

Robert O. Curtis is an emeritus scientist and David D. Marshall is a research 

forester, Forestry Sciences Laboratory, 3625 93rd Avenue, SW, Olympia, WA 

98512-9193.
Abstract

Curtis, Robert O.; Marshall, David D. 2005. Permanent-plot procedures for 

silvicultural and yield research. Gen. Tech. Rep. PNW-GTR-634. Portland, OR: 

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research 

Station. 86 p.

This paper reviews purposes and procedures for establishing and maintaining permanent plots for silvicultural and yield research, sampling and plot design, common 

errors, and procedures for measuring and recording data. It is a revision and update 

of a 1983 publication. Although some details are specific to coastal Pacific Northwest conditions, most of the material is widely applicable.

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

plot design, growth and yield.
Contents

 1 Introduction

 1 Background

 3 Purpose

 4 Data Sources

 5 Plot Classification

 6 Some Sampling Considerations

 9 Plot Installation

 9 Plot Configuration

 12 Plot Size

 18 Plot Buffers

 20 Surveying and Marking Plots

 22 Plot Protection

 22 Plot Measurement

 22 Record of Initial Conditions

 23 Tree Numbering

 28 Determination of Breast Height

 30 Stand Age

 31 Tree Dimensions

 43 Site Index Estimates

 44 Stem Maps

 45 Regeneration and Understory Vegetation

 46 Snags and Coarse Woody Debris 

 47 Photographs

 48 Remeasurement Schedule

 49 Control of Treatments

 49 Thinning or Other Partial Cuts

 49 Fertilization

 50 Timing of Measurements in Relation to Treatment

 50 Main Plot

 52 Buffer

 52 Operations Log

 53 Data Recording

 53 Preliminary Data Editing

 54 Data Management

 56 Metric Equivalents

 57 Literature Cited

 67 Appendix A: Checklist of Needed Plot and Tree Measurement 

 Information

 77 Appendix B: Field Tree Measurement Procedures

 80 Appendix C: Sampling and Plot Measurement Scheme for a 

 Large-Scale Management Experiment

 83 Appendix D: Checklist of Items Likely To Be Needed

85 Appendix E: Plot Dimensions
1

Permanent-Plot Procedures for Silvicultural and Yield Research

Introduction

Rational forest management requires estimates of expected development of 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 observations 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, however, may be considerably different from 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 alternative regimes. These require estimates of the behavior of managed stands, including response to such management 

measures as early spacing control, thinning, fertilization, control of competing 

vegetation, and use of genetically selected planting stock. They may also involve 

estimates of biomass production and carbon sequestration, development of structural features related to wildlife habitat, and visual effects. Such estimates are 

provided by silvicultural experiments designed to determine the relations between 

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

and stand simulators that attempt to combine these relations into generally applicable systems for estimating behavior and production of future stands.

Background

From about 1920 to the 1940s, 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 standardized. 

During the subsequent two decades, relatively little new work was done on yield 

tables, but many silvicultural field experiments were established.

Since the 1960s, 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 the need for silvicultural guides and yield estimates applicable to young stands and to increasingly 

intensive management. The former distinction between yield research and silvicultural research is no longer clear, and today’s yield tables are in the form of various 

types of simulation models that use the results of silvicultural research to estimate 

growth rates and yields for a range of possible management regimes. 

Estimates of growth rates and treatment responses are often 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 
2

GENERAL TECHNICAL REPORT PNW-GTR-634

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 roughly the 1980s, there had 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 database 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 and comparable reliability in data collected by 

different individuals and organizations.

Certain defects that are repeatedly encountered severely limit or destroy the 

usefulness of much data obtained at high cost in time and money:

• Documentation has often been inadequate. Records of procedures, stand 

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

• Plots have often been excessively small, installed without buffers between 

adjacent treatments, or both.

• Treatments have sometimes been assigned subjectively rather than randomly, possibly biasing analyses.

• Height measurements have frequently been inadequate in number, distribution, or accuracy, and have sometimes been omitted altogether.

• Measurements have often been omitted for trees below some arbitrary 

"merchantable" size, which results in truncated diameter distributions and 

statistics that cannot be compared with other data.

• Estimates of tree and stand ages have often been inaccurate. Sampling has 

often been inadequate, definitions are ambiguous or inconsistent, and procedures have not been documented.

• Initial stand conditions, prior to treatment, were often not recorded.

• Plot areas may be unreliable because of poor plot surveys and poor records.

• Changes have sometimes been made in treatments, plot sizes, or measurement procedures for reasons of immediate expediency in fieldwork, without 

adequate documentation or consideration of effects on later analyses.

• Data codes and measurement standards have often been 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.

Standardization 

of plot data would 

facilitate estimation 

of regional growth 

rates for silvicultural 

treatments.
3

Permanent-Plot Procedures for Silvicultural and Yield Research

Purpose

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. Some design references specific to forestry applications include Andrew 

1986, Jeffers 1972, and Stafford 1985. Important considerations in laying out plots 

within an experimental design are uniformity in initial conditions, randomization, 

and replication. Uniformity among plots allows for more efficient measurement 

of treatment differences. Random assignment of treatments to plots (including 

the control) ensures that the estimate of experimental error is valid and that differences measured are due to treatments and not to other factors. Replication (at a 

single location or at different locations) provides an estimate of the variation within 

the experiment (experimental error) to determine if differences are significant or 

important and expand the applicability or scope of inference beyond a single case 

study.

Procedures for establishing and maintaining such research plots have been 

discussed in a number of past publications, including Curtis 1983; Decourt 1973; 

Forest Productivity Council of British Columbia 1999; 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 

widely available (for example, Bluhm and others 2003, Maguire and others 1992). 

These contain much valuable information; however, some procedures discussed are 

now out of date, and many of these 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 to provide some standardization and compatibility between data sets. It may give field personnel insight into the 

reasons behind procedures and offer possible alternatives.

Portions of the discussion may appear to be mere repetition of the obvious. 

But experience 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.
4

GENERAL TECHNICAL REPORT PNW-GTR-634

The discussion is generally in terms of fixed-area remeasured plots and evenaged 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 and simulation programs; however, many of the same 

ideas and principles apply to studies using variable-radius plots and to other stand 

conditions. Although aimed at research applications, they may also suggest possible 

modifications in inventory, stand examination, and monitoring procedures to make 

these procedures more compatible with information developed from research.

Necessarily, recommendations often represent informed opinion and the 

authors’ best judgments rather than established fact.

Data Sources

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 

relation, 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 can provide a 

representative sample of the existing forest. They are usually the best data source 

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 or existing stand conditions for specific areas (commonly their 

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

the regression relations used in stand simulation.

When estimating treatment effects, comparing potential treatment regimes, and 

making long-term estimates for future managed stands, one is often 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 often prevents satisfactory evaluation 

of treatment response.
5

Permanent-Plot Procedures for Silvicultural and Yield Research

For these and similar reasons, most silvicultural research is based on plots that 

are independent of management inventories. Yield research and modeling has often 

been based on such data, but may use some combination of inventory data and 

independently established silvicultural research plots (Kohl et al. 1995).

Plot Classification

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

groups:

• Temporary (single-measurement) plots.

• Temporary plots, with supplementary growth information.

• Permanent (remeasured) plots.

Temporary plots—The normal yield tables of the 1930s 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 considered here. They do 

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

tables and growth and yield simulators.

Temporary plots, with supplementary growth information—Additional measurements obtained from increment cores and stem analyses can provide information 

on past 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), Hann and Larsen (1990), 

Hann and Wang (1990), Myers (1966, 1971), Vuokila (1965), and Wycoff (1990).

Although information may be obtained quickly by such methods, attaining 

precision comparable to that of permanent plot methods is difficult, 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 that 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 

pre-existing 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 
6

GENERAL TECHNICAL REPORT PNW-GTR-634

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, and short-term growth observations are very susceptible to the effects of 

weather fluctuations.

It is possible, however, to construct growth and yield models from this type of 

data, and such data are often useful as a means of supplementing existing permanent plot data (Stage 1977).

Permanent (remeasured) plots—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 that is unpopular with many administrators. But, permanent plots can provide data of superior accuracy and information obtainable in no other way (Curtis and Hyink 1985).

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 subjectively selected 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 can provide a 

complete history of stand development and stand treatment, response to treatment, 

actual stand damage and mortality, and understory development—information not 

obtainable from other types of plots. When observations are continued over many 

years, variations in growth caused by short-term climatic fluctuations may balance 

out. And, for demonstration purposes, the on-the-ground examples and historical 

record of treatment and response 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.

Some Sampling Considerations

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 

Permanent plots are 

expensive and a longterm commitment but 

can provide accurate 

information obtainable 

in no other way.
7

Permanent-Plot Procedures for Silvicultural and Yield Research

climatic agents are often excluded on grounds that, under management, such stands 

or conditions will be terminated. Alternatively, some studies may be specifically 

directed at evaluating the effects of such agents.

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 or specific physical area means or totals. 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 or 

totals for some category of stands or some physical area, but to estimate coefficients 

of functions relating growth and stand development to current stand values and 

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

on certain small areas or not at all. 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 portions of the existing forest that meet stated specifications of age, site, species composition, health, density or treatment category, and relative uniformity in 

stand and site conditions. Plot location within suitable areas has often been done 

subjectively, with the observer attempting to select a plot location representing 

either an average condition for the stand or the observer’s conception of conditions 

likely under future management. A 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 plot(s) within them by some random or systematic sampling procedure.

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, site productivity, and some measure of density. A statistically desirable selection would insure that the plots include a wide range of densities for each age and site productivity class. As sample selection proceeds, the distribution of age, site productivity class, and density can be indicated in a three-way 

table and an effort made to fill all cells as equally as feasible. In subsequent regression analyses, a sample so selected will provide a better assessment of effects of the 

predictor variables, and better predictions near the margins of the range of data. 

Stands to be used for 

developing regression 

equations should be 

selected to include a 

wide range of values 

for predictor variables.
8

GENERAL TECHNICAL REPORT PNW-GTR-634

In silvicultural experiments, treatments are usually replicated at a given location or locations 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.

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

variation in weather 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.

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

growth, mortality, and treatment response made in a single short growth period. Although little can be done to allow for possible long-term trends, data that represent 

It is risky to base 

estimates of 

expected growth on 

measurements in a 

single, short period.
9

Permanent-Plot Procedures for Silvicultural and Yield Research

a series of periods rather than a single short growth period will be less influenced 

by short-term weather fluctuations. This is one major value of long-term permanentplot observations and of the accumulation over time of compatible data collected by 

consistent procedures.

Plot Installation

Well-designed permanent plots maintained and repeatedly remeasured over time 

become more valuable with increasing length of record. They are often found 

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.

Plot Configuration

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

ground, and is usually the experimental unit to which treatments are applied. 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.

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 and marking of 

the perimeter becomes difficult for larger plots; especially on steep slopes, if there 

are large numbers of trees, or trees and vegetation interfering with visibility. 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 

Procedures and data 

should be complete 

and general, as data 

are often analyzed by 

different people than 

the originators, for 

different objectives 

than originally 

intended, and by 

using new analytic 

procedures.
10

GENERAL TECHNICAL REPORT PNW-GTR-634

and tape or laser rangefinder 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. Rectangles may also be advantageous in riparian studies. 

Fieldwork is simplified and mistakes are reduced if a standard plot shape and 

layout procedure are adopted and used whenever the situation permits.

Figure 1—Typical layout of a square plot.

Fieldwork is simplified 

and mistakes are 

reduced if a standard 

plot shape and layout 

procedure are used.
11

Permanent-Plot Procedures for Silvicultural and Yield Research

Plot radii or plot sides must be specified as horizontal dimensions, and field plot 

layout procedures must provide for slope corrections (automatic with some laser 

instruments).

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. A more common situation is that in which spacing of an 

existing plantation is not sufficiently regular to allow positioning the plot with sides 

midway between rows, but is 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.

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

points are not a suitable sampling unit for research purposes, as 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 or clustered arrangement of 5 to 10 

or more points within a stand can be used, however. Variable-radius plots are more 

consistent with commonly used inventory procedures than are fixed-area plots, and 

they have the well-known advantage for some purposes that sampling proportional 

to basal area concentrates the measurements on the trees of larger size and value 

and (usually) higher growth rates. In mixed-species stands, they also select species 

in proportion to the basal area they represent.

Variable-radius plot (point) clusters and fixed-area plot clusters are best suited 

to studies that sample pre-existing stand conditions, studies where treatments are 

to be applied to relatively large areas, and to monitoring silvicultural treatments, 

rather than to the type of silvicultural experiments most common in the past in 

which treatments are applied to small areas.

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 radius of the fixed-area plot 
12

GENERAL TECHNICAL REPORT PNW-GTR-634

should equal the limiting distance as determined for that specified limiting diameter (Bell and Dilworth 1997, table 16). For example, if using a 20 basal area factor 

(BAF) angle gauge to select trees larger than 8.0 in and a fixed plot for trees 8.0 in 

and smaller, the radius of the fixed plot would be 15.56 ft (1/57.3 acre), which is the 

limiting distance for an 8.0-in tree, the largest to be measured on the fixed plot.

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

as they increase in size (“ongrowth” trees, also referred to as ingrowth) complicates 

computations and introduces irregularities in growth estimates for successive periods (Gregoire 1993 [which contains an extensive list of references], Martin 1982, 

Myers and Beers 1968). Such trees are often missed in subsequent plot remeasurements, and this is a frequent source of error. (Similar problems occur with nested 

fixed-area plots, which are often used to avoid measuring very large numbers of 

small trees.)

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

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, and to inconsistencies in 

tree numbering. 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.

Plot Size

Plot size is influenced by intended purpose, by stand conditions and variability, 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 or totals of 

certain variables (for example, volume) for given strata or physical areas, based on 

plots falling in those strata or areas. Increased plot numbers can compensate for increased variability associated with smaller plots, and estimated means are unbiased 

regardless of plot size if properly installed. Some recent inventories use plot clusters with a greater aggregate area than the single plots often used in the past, and 

include measurements of many associated quantities in addition to timber (Max et 

al. 1996). Remeasurement data from a subset of such plots may be more compatible 

with typical research data and objectives than are data from many past inventories.
13

Permanent-Plot Procedures for Silvicultural and Yield Research

In discussing research plot size, it is useful to distinguish two categories 

of studies: (1) those in which the individual, relatively small plot is the basic 

experimental and analysis unit and (2) large-scale experiments in which the basic 

unit is a treatment unit of considerable size.

Small-plot experiments—Most past silvicultural research has used individual, 

relatively small plots, both because of cost considerations and because it is much 

easier to secure comparability in initial conditions and in treatment applications on 

small plots than on large areas.

Many research studies use regression equations to estimate individual tree or 

plot growth as functions of current stand values on 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 such 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 or randomly located, 

observed growth on the plot will represent in part an effect of adjacent, unmeasured, differing stand conditions. High-density plots may grow well because they 

are using adjacent growing space. Low-density plots may grow relatively poorly 

because of the competition of adjacent dense groups of trees.

Small plots may give inaccurate and often biased estimates of mortality and 

damage. In many studies, plots that lose a substantial part of their stocking 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 can 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 so 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 and damage, but estimates that are biased by the plot selection process. 

Estimates of some other stand attributes are likewise very sensitive to plot size 

(Gray 2003).

Plot size can also affect estimates of top height and corresponding estimates 

of site index (Garcia 1998, Magnussen 1999).

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 
14

GENERAL TECHNICAL REPORT PNW-GTR-634

also bias estimates of coefficients in equations expressing increment-stand density 

relationships (Hynynen and Ojansuu 2003, Jaakola 1967) if plot size is too small 

relative to the pattern of variation in within-stand density, so that increment is 

materially influenced by edge effects. Such effects will generally be more serious in 

mechanically located plots (as in inventories) than in research plots established in 

selected stand conditions, which are usually chosen for homogeneity and provided 

with suitable buffers to reduce possible edge effects.

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, 

Marckworth and others 1950, Osborne and Schumacher 1935, USDA Forest Service 

1935—still an excellent reference on many aspects of plot installation and measurement). Because much of this work was in untreated stands, presumably a somewhat 

smaller 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. Hummel and others (1959) recommended plot sizes 

of 0.3 to 0.5 acre (0.12 to 0.20 ha) for pure conifers and 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 small-diameter 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.

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 
15

Permanent-Plot Procedures for Silvicultural and Yield Research

1976, Clutter and Jones 1980, Hamilton 1976, McEwen 1979). In 1969, the University of Washington Regional Forest Nutrition Program (RFNRP) adopted a minimum 

plot size of not less than 0.1 acre (0.04 ha) (Hazard and Peterson 1984). 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.1

 Some studies in the Pacific Northwest have used quite small plots—sometimes 

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. Unsatisfactory experience with the 0.1-acre 

plots used in the RFNRP led the Stand Management Cooperative to adopt a basic 

plot size of 0.5 acre, plus a 30.5-ft buffer.2

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 RFNRP 

and British Columbia Forest Service studies cited are clearly undesirable as sources 

of growth and yield data, and even these have severe limitations in the study of 

diameter distributions, mortality, and damage. But, desirable plot size depends on 

the research objective as well as the nature of the stands involved.

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 

2 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 relation 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, it is most convenient to use a single plot size determined by 

the most extreme treatment within an installation.

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

single species and, in many cases cited, to plantations. Mixed-species stands and 

uneven-aged stands will be inherently more variable and will require larger plots—

1 Forest Productivity Committee. 1974. Field manual, balanced installation field 

programme. 63 p. + appendices. Unpublished report. On file with: British Columbia 

Ministry of Forests, P.O. Box 9049, Prov. Government, Victoria, BC V8W 9E2. 

2 Rinehart, M.L. 1986. Stand Management Cooperative—standardized field manual. 

Seattle, WA. 34 p. + appendices. Unpublished report. On file with: University of 

Washington, College of Forest Resources, Box 352100, Seattle, WA 98195-2100.

Desirable plot size 

depends on the 

research objective as 

well as the nature of 

the stands involved.
16

GENERAL TECHNICAL REPORT PNW-GTR-634

Figure 2—Plot sizes required to include 50 trees in Douglas-fir stands of given quadratic mean 

diameter and density expressed as percentage of normal (with normal defined as number of trees 

relative to that in table 25 of McArdle and others [1961]) in English (A) and metric (B) units. 
17

Permanent-Plot Procedures for Silvicultural and Yield Research

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.) The 

same is true of studies that attempt to measure mortality and impacts of wind, disease, and insects.

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, and pruning studies. Fully satisfactory and generally 

accepted techniques for expanding such results to a unit area basis are not now available, however.

Recommendation: Experimental designs that involve a large number of treatments assigned to plots within a single homogeneous stand condition—forcing 

use of very small plots because of the limited size of suitable areas—are not 

generally feasible for silvicultural and yield research and should be avoided.

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 to meet the following criteria:

• 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).

• Growth of trees on most of the plot area is little affected by surrounding, 

possibly unlike, stand conditions.

• Sufficient stems are included to provide a reasonably smooth diameter distribution.

• "Catastrophic" mortality can be distinguished from "regular" mortality composed of suppression losses plus occasional death of scattered larger trees.

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.
18

GENERAL TECHNICAL REPORT PNW-GTR-634

Experiments using relatively large treatment areas—Historically, most (though 

not all) past silvicultural and yield research has used the individual, relatively small 

plot as the experimental and analysis unit, and the preceding discussion relates 

primarily to such studies. In recent years, there has been an increasing number of 

large-scale experiments in which the experimental unit (treatment unit) is much 

larger—often on the order of 20 to 60 acres or so (Monserud 2002). These have 

been undertaken because of the increased interest in the relations between silvicultural treatments and silvicultural regimes on the one hand, and visual effects, 

wildlife effects, harvesting and management costs, mortality, and other response 

variables that cannot be effectively evaluated on the traditional small plots. They 

also permit comparisons among treatments or regimes involving uneven-age management or mixed-species management that cannot be satisfactorily represented by 

individual small plots. Compared to typical small-plot experiments, such experiments have the advantage that responses will be closely comparable to those obtainable in operational applications of similar treatments or silvicultural regimes. They 

have the disadvantage that the degree of homogeneity obtainable in initial site and 

stand conditions is necessarily less than in small-plot experiments, and the power of 

statistical tests is therefore likely to be less.

In such experiments, the relevant descriptive and response variables are the 

means of a series of small plots that sample conditions within the larger treatment 

unit. Plot distribution within the unit may be either random or systematic, but a 

systematic distribution is usually used because it simplifies plot location and later 

relocation. Size of such plots is largely a matter of convenience, provided that the 

number of plots within the treatment unit is adequate to provide estimates of unit 

stand conditions, stand increment, and mortality of satisfactory precision. When 

multiple plots are combined in the analysis, the irregularities introduced by ingrowth on either variable-radius or nested fixed-area plots tend to average out and 

can often be ignored. 

Appendix C describes (in somewhat abbreviated form) sampling procedures 

now in use in such a large silvicultural experiment (Curtis and others 2004) for 

measurement of overstory and regeneration, and limited understory measurements 

that provide some information at low cost. We do not claim that these are necessarily “best” procedures, but they may be helpful as guides to be modified as needed.

Plot Buffers

In experiments in which the individual, relatively small plot is the basic analysis 

unit (as opposed to unit values determined as means of multiple plots within a unit), 

plots should be surrounded by a buffer strip of comparable initial conditions that 
19

Permanent-Plot Procedures for Silvicultural and Yield Research

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 in some species. 

Root systems of trees on the plot will exploit water and nutrients available adjacent 

to the plot, and vice versa. Therefore, growth on the plot 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 (requiring a 

further increase in buffer width), 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.

Recommendation: 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 (which can be 

calculated from expected diameter at breast height [d.b.h.]) of dominant trees 

at the end of the planned period of observation. The Forestry Commission 

(1979) recommendation of 33 ft (10 m) seems reasonable as a general guide 

for stands of moderate diameter.

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. 
20

GENERAL TECHNICAL REPORT PNW-GTR-634

Surveying and Marking Plots 

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 should be prepared that is adequate for later 

relocation of the plots by someone unfamiliar with them. Declination used should 

be recorded. The map should include approximate location in relation to the public 

lands survey system and the latitude and longitude. Plot corners or centers and the 

starting point along the access route should also be identified by global positioning 

system (GPS) coordinates, when feasible. If overstory trees or topography make 

accurate GPS coordinates unobtainable, a GPS reading may be obtained at a nearby 

point, with an azimuth and distance to the point of interest, allowing computation of 

coordinates.

Plot centers and corners must be marked by stakes of some permanent material, such as metal, polyvinyl chloride (PVC) pipe, or substantial stakes of preservative-treated wood. Some have used short lengths of steel rebar inside PVC pipe, 

which can still be relocated with metal detectors if buried by harvesting operations. 

Stakes should be marked in a way that positively identifies the plot and the particular corner and should be witnessed by appropriate paint blazes, and tags on several 

adjacent trees. Tags should be positioned well below stump height so that they will 

not be destroyed if the trees are cut. Tags should be attached by plastic “barlock” 

connectors (thin-barked trees), staples (thick-barked trees), or long protruding nails 

so that tags will not soon be overgrown (fig. 3). Distance and azimuth from stake 

to witness trees should be recorded. Azimuths and horizontal distances between 

corners or centers must be carefully measured and recorded. The sketch map should 

show all azimuths and distances needed to relocate plot centers and corners.

Large plots, elaborate installations, or difficult terrain may warrant highly precise surveys. In most situations, satisfactory results can be obtained by careful work 

with staff compass and tape or (better) by the recently introduced staff-mounted 

laser instruments. Lasers can penetrate considerable foliage when used with a 

suitable reflector, and markedly improve both accuracy and speed of the distance 

measurements in steep terrain. To insure against blunders, boundaries should be 

run twice in opposite directions, or error of closure calculated and found to be acceptable. All dimensions and areas should be expressed on a horizontal basis.

Plot locations should 

be referenced to 

some easily 

relocatable point 

and well documented 

with a map and 

GPS coordinates.
21

Permanent-Plot Procedures for Silvicultural and Yield Research

A commercially available aid (Haglof DME 2013) useful in establishing small 

circular plots (about 0.2 acre or less) consists of a staff-mounted transponder at plot 

center and a receiver that provides the user with the slope distance from the transponder, thereby eliminating the need for tape measurement (although correction 

for slope is still needed). 

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.

Figure 3—Method of witnessing plot center or corner stakes.

3 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.
22

GENERAL TECHNICAL REPORT PNW-GTR-634

Plot Protection

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, and the installation should be entered in the manager’s geographic 

information system (GIS) database. 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. Plot boundaries should 

be painted or otherwise marked, and exterior boundaries should be conspicuously 

signed (with contact information) so that management personnel will recognize the 

area as a research installation when encountered in the field and know the office to 

contact for information. 

Common hazards include road construction, thinning and harvest operations, 

aerial application of fertilizers or herbicides, vandalism, and land ownership changes. Any of these can quickly destroy the usefulness of a research installation. In 

the absence of strong overall direction, local land managers often do not realize the 

value of existing research installations, and may give their protection lower priority 

than facilitation of their immediate administrative operations.

Plot Measurement

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 such time as the entire system of records is converted 

to metric.

Record of Initial Conditions

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

known, should be recorded at the time of the initial measurement according to 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; percentage of slope, stand origin (natural, 

planted, seeded, planted with natural fill-in); seed source and stock type for planted 

stands (if known); forest type; age at time of first measurement (even-aged stands); 

known past treatments (site preparation, vegetation control, thinning, fertilization, 

etc.) or injury; estimated site index (specify system); soils classification and habitat 
23

Permanent-Plot Procedures for Silvicultural and Yield Research

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.) It is helpful to have 

a standard form to be completed for all new studies, to insure that important items 

are not missed.

There should be a complete record of stand conditions at the time of plot establishment and immediately before any treatment. All stems removed from a plot 

should be recorded by species and 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 that have had cutting prior to plot establishment, date of cut 

should be ascertained, and the numbers and dimensions of trees removed from the 

plot should be estimated by stump measurements or otherwise insofar as possible.

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.

Tree Numbering 

Each live tree of measurable size within the plot should be assigned a unique 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).

For some objectives, removal of potential ingrowth trees at the time of study 

establishment simplifies later measurements. But, ingrowth is a part of normal stand 

development, accepted as such in most studies and often of interest in itself. In most 

studies, ingrowth should be identified and tagged as it appears. In those cases where 

there are very large numbers of potential ingrowth trees, it may be necessary to 

resort to subsampling (discussed in a later section).

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. Although initially time consuming, this insures that numbers will be 

in sequence—thereby simplifying relocation of trees and handling of records at 
24

GENERAL TECHNICAL REPORT PNW-GTR-634

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 one 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 or 112, numbers 1121 

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

Alternatively, if a tree was initially assigned the number 112, nearby ingrowth trees 

can be numbered as 112.1, 112.2, ... etc. This system can be used when the number 

of very small trees makes initial tagging of all trees impractical.

The method used for numbering or tagging trees will depend in part on size 

and characteristics of the trees. A number of methods have been used:

(a) The most common method in the past has been the use of metal tags attached 

with aluminum nails at breast height (b.h.) (fig. 4a). This is convenient for 

large thick-barked trees. Nails should be driven no farther than necessary to 

stay in place, slanting slightly upward and with the tag placed at the nail head 

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. If nails are used, they must be pulled as 

needed at each measurement to prevent overgrowth of the tags. (Except, on 

very thick-barked trees where the nails do not penetrate the wood, they will 

gradually move outward along with the bark plate). 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. Major disadvantages of nailed tags are the risk of future damage to saws and mill equipment if tags are not removed prior to cutting (aluminum rather than steel nails 

may reduce but do not eliminate the problem) and the continuing need for 

periodic nail-pulling to prevent overgrowth of tags. 

(b) One alternative is painted numbers (fig. 4b), with a supplementary paint mark 

at the b.h. measurement point. This prevents damage to saws, but painting 

is not feasible during wet weather, and there will be a need for repainting at 

subsequent measurements for numbers to remain legible. Rough-barked trees 

will require smoothing of bark before painting; this must be done above or 

below, not at the b.h. point.

Individual trees should 

be tagged by means 

that will not harm the 

tree and will persist 

through time.
25

Permanent-Plot Procedures for Silvicultural and Yield Research

B

C

A

D

Figure 4—Methods of attaching tree tags: (a) nails, (b) painted numbers after smoothing bark, (c) plastic barlocks stapled to tree, (d) tags 

stapled directly to thick bark plates.

(c) An alternative that eliminates damage to saws and frequent need to pull 

nails to avoid overgrown tags, and can be used in any weather, is the use of 

plastic barlocks stapled to the tree (fig. 4c) by using a squeeze-type stapler 

and 9/16-in staples. Use a single staple applied horizontally for best results. 

This works well on small thin-barked trees where the staples can penetrate into the wood; the point of attachment is then soon overgrown and 

the length of the barlock is sufficient to allow considerable growth without 

overgrowing the tag. It is not satisfactory for older thick-barked trees unless 

one gouges the bark sufficiently to allow stapling into wood. Barlocks used 

should be resistant to ultraviolet light. Unfortunately, they may sometimes 

attract attention and may be ripped off by vandals or large wildlife.
26

GENERAL TECHNICAL REPORT PNW-GTR-634

(d) Another alternative applicable to older thick-barked trees is to staple the 

metal tag directly to bark plates (fig. 4d). Although we have used this method for only a limited time, it appears to be fairly long-lasting and avoids the 

overgrowth and saw damage problems.

(e) For very small trees, tags can be attached to a branch near b.h. with wire 

or barlocks. (Tags should never be wired around the stem; this can cause 

deformities or death of the tree.) Seedlings can be identified with tags attached to wire pins adjacent to the seedling. When regeneration is sampled 

with very small subplots, planted seedlings can be identified by distance 

and azimuth from the subplot center marker.

For some specialized purposes, UPC (bar code) tags are an alternative to the 

usual metal tags.

Research is currently in progress at the University of Washington on embedded 

machine-readable chips for permanent tree identification, analogous to procedures 

now used with livestock. These are not currently available, but if successful and 

available at reasonable cost, they would eliminate the problems of saw damage, tag 

overgrowth, and tag removal by vandals.

 Opinion: The most generally satisfactory methods are barlocks (fig. 4c) 

for thin-barked trees, and direct stapling of tags to bark plates (fig. 4d) for 

thick-barked trees.

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, or write-on aluminum labels, to supply tags as needed if the sequence provided is exceeded. (Duplication of tag numbers on the same plot must be avoided). 

Likewise, remeasurement crews should make new tags as needed to replace lost 

tags and for tagging ingrowth. 

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

height-sample trees. 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), which will facilitate later relocation of trees. It may sometimes 

be desirable to divide the plot into numbered subplots so that trees can later be 

sorted by subplots as an aid to relocation. 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 crew as they 

travel across the plot in a systematic sequence. If on remeasurement a tree is found 

to be out of sequence, the number of the nearest properly tagged tree should be 

recorded.
27

Permanent-Plot Procedures for Silvicultural and Yield Research

A consistent procedure must 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 ft to facilitate numbering and later remeasurements. 

Removal of live limbs should normally be avoided except as necessary to allow 

access to the tag and d.b.h. measurement point. Any such pruning should be done 

with handsaws or loppers, to avoid stem injuries.

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

trees (ingrowth, previously missed trees, trees with lost tags). Lost tags can often 

be recovered from the duff; if not, the tree number may be identifiable from its 

position and the same number then replaced. New numbers should be assigned to 

any ingrowth or previously missed trees (by using the xxx.x or similar convention 

Figure 5—Plot divided into sectors: arrows show sequence of tree 

tagging and measurement. Tags should be positioned to face the 

crew as they travel through the plot. 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 

subdivisions in distributing site trees across any site gradient.
28

GENERAL TECHNICAL REPORT PNW-GTR-634

that maintains the number sequence to facilitate relocation). 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, heights, and other characteristics of these trees. 

Note that when tagging such new trees in the field, one should never transfer 

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

though convenient in the field, causes endless confusion. Tags should be made as 

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

Determination of Breast Height

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. There are, however, some unresolved inconsistencies 

in definition of b.h. that require a choice.

In the United States, b.h. has in the past been defined both as 4.5 ft above mean 

ground level (common practice in many past research studies) and as 4.5 ft 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 in the past in collecting the data used to construct existing volume and 

taper equations and 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 ft 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 m; however, the 

international standard is 1.3 m, and this will probably eventually become standard 

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

1982).

Recommendation: When new plots are installed, it is best to establish and 

mark (by tag or paint) the 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. 

When tagging new 

trees, never reuse an 

old number from dead 

or harvested trees.
29

Permanent-Plot Procedures for Silvicultural and Yield Research

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

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

• 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.

• If a tree forks below b.h., treat it as two trees, with the tag and diameter 

measurement located at (1) 2.0 ft (0.6 m) above fork at the initial measurement or (2) 4.5 ft (1.3 m) above ground, whichever is higher.

• 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.

Figure 6—Measurement points for measuring diameter at breast height (d.b.h.) of trees in various 

situations.
30

GENERAL TECHNICAL REPORT PNW-GTR-634

Stand Age

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 determinations to corresponding total age from seed. The 

record may show age as total age from seed, years from planting date + stock type 

(if known), or age at b.h. but must clearly specify which and should indicate the 

basis for conversion from actual measurements to the ages given and the best available estimate of conversions from age at b.h. to total age or vice versa. In young 

plantations of conifers with clearly defined internodes, age at b.h. can be readily 

determined by counting internodes from tip to b.h. point.

A stand age at b.h. based on borings or internode counts 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 site quality, 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 per 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.
31

Permanent-Plot Procedures for Silvicultural and Yield Research

Tree Dimensions

Standard procedure at each scheduled plot measurement must provide for:

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

• Classification of measured stems by crown class, tree status, condition, and 

nature of any injury or death, in accordance with a standard coding system. 

The system must also recognize the categories: survivors, ingrowth, mortality, cut, intentionally killed trees, previously missed trees, and understory, 

as applicable. Understory stems (those clearly of an age class younger than 

the main stand) should be recognized as a separate crown class or cohort, 

when present.

• Measurement of heights of a sample of trees sufficient to provide a reliable 

height-diameter curve and estimates of stand average height, top or dominant height, and site index. 

• Measurement of heights to live crown (and crown width, if measured) on the 

same trees at successive measurements is highly desirable.

• 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 

format (fig. 7) or recording device display containing the previous measurements on 

each tree. New and old measurements should be checked for reasonable agreement, 

and major discrepancies should be checked by remeasurement of the tree. (Electronic recording devices can be programmed to “beep” when a measurement differs by 

Figure 7—A plot measurement field form or recorder screen.
32

GENERAL TECHNICAL REPORT PNW-GTR-634

more than a specified amount from the previous measurement). 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, 

as 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 (usually indicated by tag position, or by a paint mark) at each plot 

remeasurement, normally to the nearest 0.1 in or 1.0 mm. Except in stands with 

many very small stems (where a “go-no-go” gauge or fork caliper is useful), this is 

best done with a diameter tape.

When a tree that died since the previous measurement is encountered, its diameter is recorded, together with a mortality code indicating that it was found dead at 

this measurement and the cause of death (if evident). It will save time in future remeasurements if such trees are blazed or painted and the tag removed and nailed at 

a point below any possible stump height (to avoid damage to equipment in the event 

of any salvage). Nailing the tag below stump height makes the tree easily identifiable as previously recorded mortality with a known approximate year of death. 

It was 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 in or 

1.5 in or 2.5 cm. 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 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. 
33

Permanent-Plot Procedures for Silvicultural and Yield Research

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. Because 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 bigger than the larger d.b.h. 

limit is found, numbered, tagged, 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. 

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 for the larger trees. 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.

Height measurements—Stand height is (with age, number of trees, and quadratic 

mean diameter [Curtis and Marshall 2000]) 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, accurate estimates of bole biomass, 

estimation of site index, and characterization of stand conditions and stand development. Crown length (or equivalently, height to live crown or crown ratio) is now 

used in many tree and stand simulators, and it is therefore highly desirable that 

this also be measured. Because measurement of heights is time consuming and 

frequently inaccurate, height and crown length 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 rather than merchantable height 

need be measured. Merchantable heights, if wanted, are better determined from 

Because measurement 

of heights is time 

consuming and 

frequently inaccurate, 

height and crown 

length sampling and 

measurement are the 

weakest points in 

much existing data.
34

GENERAL TECHNICAL REPORT PNW-GTR-634

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.

It is often impractical to measure heights of all trees on the plot, and one must 

then 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:

• Each plot or plot cluster should be sampled independently. Samples generally cannot be combined across plots or treatments without biasing analyses.

• 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 or coded as unsuitable for developing height-diameter curves or 

for site index estimates. Sample trees should be reasonably well distributed 

across the plot area.

• The sample should include trees from the full range of diameters present, 

and should specifically include the largest and smallest diameter classes. 

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 

dominants and codominants only.

• Large d.b.h. classes should generally be sampled more heavily than small 

d.b.h. classes, because they contribute more to volume, volume growth, and 

value. The small trees must also be sampled in a manner adequate to characterize that portion of the height-diameter curve and provide information 

on vertical structure of the stand.

• When designated site trees are used, 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, curves for intermediate dates can often 

be obtained by interpolation or by fitting a system of height-diameter-age curves. 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.
35

Permanent-Plot Procedures for Silvicultural and Yield Research

• Normally, except where new trees are needed to 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 height trees with paint for easy subsequent recognition. 

Height trees lost through cutting or mortality 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.

The Stand Management Cooperative (Maguire and others 1992) and the 

Hardwood Silviculture Cooperative (Bluhm and others 2003) currently require 40 

height-sample trees for each single-species, homogeneous research plot. A general 

rule of thumb would be for two-thirds of the trees to be distributed across the d.b.h. 

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

classes. This should be considered a minimum number of acceptable height-sample 

trees for a single-species, homogeneous plot with well-established crown differentiation. If plots at a given location receiving the same treatment are similar in structure and productivity, height-sample trees may be pooled for a common height-diameter curve. In this case fewer trees per plot could be sampled as long as the total 

sample is at least 40 and the trees are distributed across the plots and the range of 

diameters. More trees will be required in plots with a wide range in diameters and 

in mixed-species stands. Some types of studies, such as genetics trials, will require 

heights of all trees. The recent introduction of much-improved height measurement 

instruments (discussed below) has greatly improved the ease and accuracy of height 

measurements, and larger samples than commonly used in the past are now feasible. On small plots with relatively few trees, measurement of heights of all trees is 

desirable.

Height estimates should be compared with previous measurements (ocularly, or 

automatically by electronic recorder) 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, and corrections made accordingly. 

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 is present, a decision must be made on sampling the 

associated species. Options are:

Data should be 

compared to previous 

data before leaving 

the field to help 

identify errors and 

make corrections.
36

GENERAL TECHNICAL REPORT PNW-GTR-634

• 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 errors that may arise from 

use of heights of the primary species for the secondary species.

• If the secondary species is few in number 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.

• If the secondary species represents a substantial portion of both plot volume 

and numbers of trees or is otherwise important to study objectives, then a 

height sample should be drawn and measured the same as for the primary 

species.

Similar considerations apply in situations where two clearly distinguishable and 

important cohorts (age classes) are present.

A number of instruments are available for height measurements (Williams and 

others 1994, Wing and others 2004). Choice of instruments and procedures for 

measurement of heights is influenced by expected tree size, terrain, and brush and 

understory conditions.

In very young stands, height poles are fast and accurate. Commercially available telescoping poles provide measurements to 30 to 40 ft (9 to 12 m) in height, 

depending on the model. Sectional poles have been constructed that can be used 

(with considerable difficulty) for heights up to 50 to 60 ft (15 to 18 m) 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, and at a point higher than the base of the tree if such is available.

The most common procedure in the past has been to measure slope distance 

from observer to the tree with tape, and angles to tip and base of tree with a handheld clinometer. Then (1) calculate corresponding horizontal distance by using 

slope correction factors given in table 3 in appendix E or equivalently as (slope 

distance) x (cosine of angle in degrees), and (2) calculate tree height as:

H = [(horizontal distance) × (slope to tip in percent)] – [(horizontal 

distance) × (slope to base in percent)]

where slope to base is negative if below horizontal, positive if above.
37

Permanent-Plot Procedures for Silvicultural and Yield Research

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

heavy brush. Special circular slide rules were used in the past to simplify field 

computation of heights, but these have been replaced by the programmable 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 by 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 have been marketed but are not generally satisfactory. 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 

often cumbersome and difficult to use with poor lighting and visibility.

A useful procedure, requiring only a height pole and a clinometer, that 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). This procedure does not require measurement of distance to the tree and 

allows for greater ease of movement by the observer to get the best view of the 

point on the tree to be measured. 

Tall trees (over 100 ft or 30 m) tax the accuracy of simple clinometers. Sighting 

angles over 45° should be avoided. Precision of handheld 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, as 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- or staff-mounted optical instrument such as the Bitterlich Telerelaskop will improve accuracy. 

A useful procedure for 

estimating tree height 

requires only a height 

pole and a clinometer.
38

GENERAL TECHNICAL REPORT PNW-GTR-634

Figure 8—Estimation of tree height with clinometer and tape measurement of slope distance.

 is angle in degrees.

H is total tree height.

HLC is height to live crown.

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

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 for H, but with 3 replacing 2.
39

Permanent-Plot Procedures for Silvicultural and Yield Research

Figure 9—Estimation of tree height by the pole and clinometer method.  is angle in degrees. 

Because tan  = 0.01 slope  in percent, substituting 0.01 slope  in the equation causes the 

0.01 factors to cancel out. Thus the equation can use either tangent of the angle (in degrees) or 

percentage of slope.

H is total tree height,

HLC is height to base of live crown, 

h is height of lower aim point (usually breast height),

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.
40

GENERAL TECHNICAL REPORT PNW-GTR-634

The introduction of instruments such as the “Impulse “(Laser Technology Inc.) 

and ”Forest Ace” (Measurement Devices Ltd.) laser instruments (fig. 10) (Wing and 

others 2004) for measuring heights and distances has greatly improved the speed 

and precision of height and distance measurements. When used in conjunction with 

a reflecting prism placed at the base of the tree at a known height such as b.h., these 

can provide readings through a considerable amount of foliage and give horizontal 

distances and heights without tape measurement of distances or manual slope corrections. The principle is the same as the old tape and clinometer method (fig. 8) 

but the computations are done automatically, the optical sight improves accuracy 

of angle determinations, and distance measurements are faster and more accurate 

than tape measurements. Another instrument serving the same purpose and having similar advantages for moderate-size trees is the Haglof “VERTEX III,” which 

uses sound and a transponder attached to the tree bole (note: heavy rain or a nearby 

stream can affect signal transmission).

These or similar instruments have become indispensable to anyone needing 

to measure large numbers of heights. Whichever instrument is used, the observer 

should have a good view of the sighting point on the tree, and measured angles 

should generally be kept below 45°.

Recommendations: Height poles are fast and accurate for short trees. For 

trees too tall for easy use of height poles, the new laser or sonic instruments 

are far superior to the older methods in speed and accuracy. However, if such 

instruments are not readily available, the older tape and clinometer and pole 

and clinometer methods are still useful and will give results of 

acceptable accuracy for trees of moderate height.

Figure 10—Recently introduced laser instruments greatly 

improve speed and accuracy of height measurements and, with 

compass and staff attachments, are suitable for rapid surveys of 

moderate precision.

New instruments have 

greatly improved the 

speed and precision 

of height and distance 

measurements.
41

Permanent-Plot Procedures for Silvicultural and Yield Research

Crown measurements—Crown dimensions were only rarely measured in older 

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

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

Height-to-live-crown (HLC) is the most easily determined crown dimension. In 

combination with total height, this gives crown length and live crown ratio (crown 

length/total height). These are associated with tree competitive status and potential 

response to treatment and have been useful predictors of growth in growth and 

yield models (Hahn and Leary 1979, Hann and others 1997, Holdaway and others 

1979, Krumland and Wensel 1980, Stage 1973). Hence, measurements of height to 

live crown should be made for all 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. Different 

observers will not be entirely consistent in judging the location of the base of live 

crown, and therefore measurements of height to live crown are inherently less precise than those for total tree height.

A suggested definition for conifers 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. Some hardwoods typically have highly irregular crowns, and in 

such cases, “lowest live branch” may be the only feasible definition. In some species, the lower crown may droop far below the base of the lowest live branch, and 

an additional height to live foliage may be useful.

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

and response to treatment. These are best made as an average of measurements 

along the long and short axes.

If stands are not excessively dense, crown widths can be readily measured on 

large-scale aerial photographs. Ground measurements require vertical projection 

of crown margins, which can be done with such simple instruments as the Suunto 

clinometer, a pole with rod level, by ocular estimation (small trees); or with any of a 

variety of instruments constructed especially for the purpose.

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

crowns extending nearly to the ground and in very open stands, but become difficult and inaccurate with increasing height and stand density. Ground measurement 

of crown widths is considerably more difficult and time consuming than measurement of height to live crown.
42

GENERAL TECHNICAL REPORT PNW-GTR-634

Recommendations: Height to live crown should be routinely measured on 

all new research installations and on 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 measurement—There may be need to 

measure upper-stem diameters on a sample of trees for either of two reasons:

• 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.

• 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 to assume that treatment effects on form, beyond those incorporated 

in standard volume and taper equations including height, diameter, and—sometimes—crown ratio as predictors, can be ignored. Hence, upper-stem measurements 

specifically for this purpose are probably not needed. This is a convenient assumption rather than a 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, Chambers and Foltz 1980); more complete 

information is given by stem taper curves.

Suitable taper curves are often available from other sources (Hann 1994). 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 Wheeler pentaprism caliper (Wheeler 

1962) the Bitterlich relaskop, the Bitterlich tele-relaskop, and some of the new 

laser instruments (Garrett and others 1997, Parker 1997, Parker and Matney 1999, 

Williams and others 1999.) The old Barr and Stroud dendrometer was precise, but 

is no longer manufactured.
43

Permanent-Plot Procedures for Silvicultural and Yield Research

Some taper equations allow for calibration by using one or more upper-stem 

diameters (Flewelling 1993, Kozak 1998). In contrast, direct estimation of tree 

volume requires measurements of stump height, d.b.h., total height, and diameters 

inside bark at a series of relative height intervals such as 0.05, 0.10, 0.20, 0.30, 0.40, 

0.50, 0.60, 0.70, 0.80, 0.90, and 0.95 of total height (or alternatively, at fixed height 

intervals) and total height. Diameter inside bark can be directly measured for upperstem positions on felled trees but must be estimated for measurements on standing 

trees (Mesavage 1969). Height to base of live crown is a highly desirable additional 

measurement, and some studies require stem diameter at this point (which is related 

to leaf area). Detailed procedures and various taper and volume equations are given 

by Bitterlich (1981), Bruce (1972), Bruce and others (1968), Cao and others (1980), 

Flewelling and Raynes (1993), Gray (1956), Grosenbaugh (1963), Kozak (1988), 

Martin (1981), Max and Burkhart (1976), and Walters and Hann (1986).

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.

Site Index Estimates

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 (see Hann 1995 for a list of available site equations for the Pacific Northwest and California). 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 from 

site index estimates. If all site trees were not measured, 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 
44

GENERAL TECHNICAL REPORT PNW-GTR-634

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 (authors’ opinion), and more are highly 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 meet the specifications for qualified site trees. Age of site trees should 

be determined by boring at b.h., when feasible. Ages and heights of individual trees 

should be retained in the record, to allow for possible future recomputation with 

alternative procedures.

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 differs among stands. As young stands develop, later 

estimates of site index will more accurately represent the growth potential of the 

site. Site index estimates and the population of qualified site trees often change over 

time, and the record should be updated as this occurs.

Recommendation: 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, such as the 40 largest per acre (100 

largest per hectare). 

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 may be located 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. The preferred method is to divide the plot into 1/40-acre 

(0.01 ha) subplots and select site trees as the largest otherwise suitable tree within 

each subplot (Forest Productivity Council of British Columbia 1998). 

Stem Maps 

Consideration should be given to stem mapping selected installations expected to be 

major sources of long-term growth data. Stem maps can provide:

• Easy relocation of missing trees and of sample trees drawn from the 

plot record.

• Description of spatial distribution of stems.

• Description of spatial distribution of mortality and injury.

Site index estimates 

and the population 

of qualified site trees 

often change over time, 

and the record should 

be updated as this 

occurs.
45

Permanent-Plot Procedures for Silvicultural and Yield Research

• Information needed for development of distance-dependent simulation 

models, which use measures of inter-tree competition based on individual 

tree dimensions and inter-tree 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.

A common procedure uses angles and distances from plot center or plot corners, a procedure that has been greatly improved in speed and accuracy by the 

new staff-mounted laser instruments with compass attachment (Moeur 1993). An 

alternative procedure that takes advantage of the newer distance-measurement 

instruments uses triangulation of distances measured to each tree from two known 

points such as plot corners (Quigley and Slater 1994). An older procedure suitable 

for small plots determines coordinates by reference to two tapes stretched at right 

angles and using right-angle prisms (Reed and others 1989). Digitized aerial photography is highly efficient for 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.

Regeneration and Understory Vegetation

Much past work has been concerned primarily with development of the trees 

composing the present or expected future merchantable volume of a stand, and has 

often paid relatively little attention to development of understory trees and secondary vegetation. Planned regeneration has generally been measured and documented; 

not so the establishment of tree species in the understory that do not constitute part 

of the planned future crop. And, establishment and development of nontree species in the understory have generally been ignored unless they constitute a threat to 

planned regeneration. Although often described in very general terms, quantitative 

information has generally been lacking.

With the current emphasis on wildlife habitat, biodiversity, stand structures, 

and silvicultural systems that are alternatives to the long-established clearcutting 

system, and recognition that competing vegetation can have major influences on 

crop-tree growth, there is a new interest in characterizing the composition and 

growth of the understory that develops under various stand treatment regimes. And, 

its composition is often the basis for classification of plant communities that are 

related to other ecological and management concerns.

There is a new 

interest in 

characterizing 

the composition 

and growth of the 

understory that 

develops under 

various stand 

treatment regimes. 
46

GENERAL TECHNICAL REPORT PNW-GTR-634

Regeneration—Information is commonly wanted on the number, species, dimensions, spatial distribution, and survival of tree regeneration. By definition, this 

refers to trees smaller than the minimum diameter (or height) included in the main 

plot measurements discussed earlier. When the experimental units are relatively 

small plots, this will require subsampling by subplots or by transects within the 

main plot. When the experimental units are relatively large treatment areas, they 

can be sampled either by a grid of small plots independent of the plots used to characterize the treatment area, or (more efficiently) by a series of small subplots superimposed on the larger plots used for the main tree measurements. 

One often wishes to trace the development and survival of planted trees, as 

opposed to natural seedlings. For this purpose, planted trees must be identified so 

that development and survival of individual seedlings can be followed through time. 

This can be done either by tagging planted seedlings or by recording azimuth and 

distance of each seedling from the center or corner of the regeneration subplot.

Secondary species—A complete inventory and description of all the secondary 

(nontree) species on an area is an extremely time-consuming, laborious, and expensive undertaking. And, it requires a degree of botanical expertise usually lacking in 

field crews. From a silvicultural standpoint, one does not usually need a complete 

enumeration and description (although these might be required for modeling or 

computing abundance and diversity indices for ecological studies). Primary interest is usually in those species that are serious competitors of tree species and in 

those that are of value for wildlife or for specialized products such as floral greens. 

The number of species that are of major importance from these standpoints within 

a given area is usually fairly small. It may often be sufficient to describe conditions 

in terms of percentage of cover and average height of a small number of species or 

species groups. Frequently, ocular estimates of these values on small subplots or 

transects, made at successive measurements, will suffice to identify trends in understory development under different stand treatment regimes.

Snags and Coarse Woody Debris

The number, size, and condition of snags and the amount, dimensions, and condition of down material are frequently of interest from the standpoints of wildlife 

habitat, carbon sequestration, and fuel loading. Therefore, consideration should be 

given to securing and maintaining a record of snags and down material. 

Tagged trees that have been found dead can be reexamined at subsequent 

measurements to determine rate of deterioration. Snags existing at the time of plot 

establishment can be tagged, recorded as snags, and reexamined at subsequent 

measurements. The number of snags on small plots is often small and highly 

The number, size, and 

condition of snags 

and the amount, 

dimensions, and 

condition of down 

material are frequently 

of interest from the 

standpoints of wildlife 

habitat, carbon 

sequestration, and 

fuel loading.
47

Permanent-Plot Procedures for Silvicultural and Yield Research

variable, and estimates based on individual small plots therefore have inherently 

high variance. In large-scale experiments where relatively large treatment units are 

sampled by a series of small plots, it may be desirable to overlay a larger plot size 

for snags.

Quantity and dimensions of down material present at each measurement can be 

estimated on the basis of subplot or transect samples. On very small plots, complete 

enumeration and measurement of all qualifying pieces is possible. With larger plots 

or large treatment units, this becomes impractical and sampling is necessary. A 

variety of methods have been used (Stahl and others 2001). The most widely used 

technique is line intersect sampling. In simplest form this consists of recording 

piece diameter at the point of intersection of the piece with one or more randomly 

oriented lines. Elaborations can provide estimates by piece size and decay class. 

Excellent discussions of field techniques are given by Iles (2003, chapter 10—

very readable), Marshall and others (2000), and Waddell (2002).

Several generally similar but not identical systems exist for describing characteristics of snags and down material (Bull and others 1997, Cline and others 1980, 

Maser and others 1979).

Photographs 

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 (Hall 2002). So far as is feasible with changing stand conditions, photos should 

be taken in the same direction from the same points at successive dates. Vegetation 

development will often make this unfeasible, in which case, one should seek nearby 

points that illustrate representative conditions. Photopoints can be identified either 

by distinctively marked stakes or by distance and bearing from plot corners or plot 

centers, and should be documented and permanently stored with other information 

about the plot. A person or some object of easily recognized dimensions should be 

included in photos to provide a size scale meaningful to the viewer.

Photos are worthless unless they are carefully and completely identified by 

study, installation, plot, location, 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 

A systematic 

procedure must be 

used for identifying 

and filing photographs 

to insure that the 

needed information 

is recorded.
48

GENERAL TECHNICAL REPORT PNW-GTR-634

with other records for a particular study, installation, and plot; and that negatives 

and transparencies are protected from damage.

Remeasurement Schedule

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, 

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 

difficulty of accurately measuring small growth changes.5 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 carried out.

Research studies most commonly 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 at all 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. If measurements must be done 

outside the dormant season, these should be on as nearly as possible the same date 

on each occasion.

5 A first remeasurement soon after establishment will, however, serve to correct 

measurement and recording errors made at the time of measurement.
49

Permanent-Plot Procedures for Silvicultural and Yield Research

Control of Treatments

Thinning or Other Partial Cuts

Type, severity, and frequency of thinning or other operations in silvicultural 

research studies are normally specified in the study plan. Procedures for applying 

and controlling operations on the ground to meet these specifications and needs for 

pretreatment information will vary with study objectives and the required degree of 

control over silvicultural operations.

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 some time before study installation, 

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 measured and stand statistics 

calculated before the marking is done, as 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 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 a suitable tree nearest 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 otherwise 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 
50

GENERAL TECHNICAL REPORT PNW-GTR-634

to fertilizer dosage and is often the only way to apply fertilizer to small areas with 

adjacent unfertilized plots. 

Plots are sometimes installed in operationally fertilized areas 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 that 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 to aerial applications difficult, inaccurate, and often impossible; hence the researcher’s preference for uniform ground application in fertilizer 

studies (Bruce 1977).

Timing of Measurements in Relation to Treatment 

Main Plot

A complete stand measurement is needed whenever a thinning, harvest, 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. Pretreatment statistics may or may not 

be used as a basis for controlling the silvicultural operation, but they are always 

needed in analyses to describe the initial conditions. Associated control plots are 

sometimes used but often are not sufficiently comparable to provide satisfactory 

information. Posttreatment stump measurements, although possible, are often inaccurate and are an undesirable substitute for adequate pretreatment measurements.

When possible, a pretreatment measurement and the actual treatment should 

be done during the same dormant season. At a minimum, diameters of all trees 

should be measured before a thinning or harvest operation. A posttreatment remeasurement is then needed as soon as possible after completion of the operation, 

to identify trees cut, destroyed, or damaged during the thinning or partial harvest 

operation. 

Pretreatment statistics 

are helpful to describe 

initial conditions even 

when control plots are 

used.
51

Permanent-Plot Procedures for Silvicultural and Yield Research

When a thinning or other partial cut 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. Preliminary tally followed by postcut measurements. A preliminary dot 

tally (by 1-in or 1-cm classes) can be made to guide treatment and provide 

precut stand statistics, followed by numbering, tagging, and complete measurement of leave trees after treatment.

2. Pre-identify leave trees. If leave or cut trees can be identified before measurements are made, it may suffice to measure and record other (cut) trees 

by 1-in or 2-cm classes only. If numbers are assigned to the leave trees, they 

can be recorded in the order encountered, which provides an indication of 

spatial position. All designated leave trees must be measured to 0.1 in or 

0.1 cm, numbered, and tagged or painted. A postthinning check is made to 

identify trees destroyed, missed, or damaged.

3. 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 in or 0.1 cm). 

Then make a postthinning check to identify trees that were cut, destroyed, 

missed, or damaged. 

4. 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.

If pretreatment stand statistics are needed to guide treatment and methods, a 

dot tally of all trees by size classes may provide all that is needed. Leave (or cut) 

trees are then selected, marked, and tallied before the cut. In some operational-scale 

studies, precut marking of individual trees may not be feasible; tree selection is then 

done by the operator, subject to periodic check for compliance with specifications. 

Numbering, tagging, and accurate measurement of the leave trees can be deferred 

until after the thinning or harvest operation.

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, confines the sample to trees likely to be present at the next measurement, and provides better visibility of tree tops. If, however, prethinning heights 
52

GENERAL TECHNICAL REPORT PNW-GTR-634

(especially for small trees that may be removed in thinning) or volumes are needed 

as a basis for controlling treatment, heights must be measured before thinning. 

Substitutes for any trees cut can be remeasured at the postthinning check, which is 

often not made until the next growing season. In such cases, recorded height should 

be the estimated 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, 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

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 may differ according to the nature of the study and 

the treatments applied.

There is normally no need to tag or measure trees on the buffer surrounding 

an untreated control plot or any plot that is not thinned. There may or may not be a 

need to measure buffer 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.

Operations Log

There should be a systematic procedure for recording the date and nature of any 

measurements made or treatments applied. It should be standard practice for the 

field crew leader to prepare a file memorandum or report recording what was done, 

when it was done, who did it, costs in person-hours or dollars, and any incidental 

observations made while on the plot(s).

Any damage or untoward events affecting the plot or overall study should be recorded when discovered and fully described in the record. This includes such things 

as major wind, snow, or ice damage; major insect or disease injury; and human 

There should be a 

systematic procedure 

for recording the date 

and nature of any 

measurements made 

or treatments applied.
53

Permanent-Plot Procedures for Silvicultural and Yield Research

activities not planned as part of the study (road relocations, failure to protect plots 

from operations on adjacent land, vandalism, trespass, ownership change).

Data Recording

Obtaining quality data requires well-trained crews following established procedures 

for handling data in the field and office, using well-maintained equipment appropriate for the job. Recording of measurements in the field should be done neatly (if 

written) and carefully with the recorder orally confirming observations made by 

the measurer. If available, relevant prior measurement data should be easily available for the recorder to compare for reasonableness in order to catch current or past 

measurement errors. For each current measurement made that has a past measurement available, the recorder should check whether the increase in diameter or height 

is reasonable and if the height increase is consistent with internodal length (if 

visible).

Figure 7 is an example of a field sheet that can be produced by computer with 

the relevant prior measurements, and printed or copied on waterproof paper. Although paper field sheets are still useful for small-scale and specialized tasks, they 

are being replaced by electronic data recorders. A screen set-up similar to figure 7 

can be used with these.

Small, field-rugged computers are now commonly used for data collection. 

Electronic data recorders eliminate manual data transfer (keypunching) from field 

sheets to computer, a time-consuming and error-prone task. They can also allow for 

the automation of onsite editing and data-checking tasks, such as checking that all 

required fields have been entered with an appropriate code and that measurements 

fall within reasonable limits. Until recently, the software required for data entry 

required custom programming. Now most computers have spreadsheet applications 

available that are adequate for many small jobs. For more complex data collection 

efforts, programs like DataPlus (Field Data Solutions, Inc.) can be used to create 

custom data entry applications quickly and with no programming experience.

Preliminary Data Editing

As soon as possible after the measurements are completed (and the data entered, 

if field sheets were used) there should be a preliminary data edit designed to catch 

gross errors while they can still be readily corrected. These edit checks may start 

by simply computing the minimum and maximum values of the various measurements (for example, d.b.h and height) to identify unreasonable values. A simple 

tally of numbers of trees by species or other codes can identify unknown codes. 

Computing the number of live and dead trees and comparing this with the number 

If done as soon 

as possible after 

the measurements 

are completed, a 

preliminary data edit 

can catch gross errors 

while they can still be 

readily corrected.
54

GENERAL TECHNICAL REPORT PNW-GTR-634

of live trees at the prior measurement provides a quick check that all trees have 

been accounted for. In addition to these tallies, simple graphical checks, such as 

scatter plots of heights over diameter, or more elaborate plots of the change in individual tree measurements (for example, diameter, height, and height to live crown) 

over their current measurement can reveal potential errors and outliers in tree 

measurements (see Karsh and Lavigne 1993 for more elaborate editing guidelines). 

Such procedures can be done in spreadsheets or with more sophisticated statistical 

software packages and can often catch gross errors that would waste much time and 

effort if left until the analysis stage.

Data Management

In the past, plot procedures, measurements standards, data recording codes and 

formats, and computational procedures have often been developed more or less 

independently for each study by the individual researcher or organizational unit 

involved. These have been shaped by the investigator’s immediate needs and interests, experience, and limitations, and are often inadequately documented.

Good-quality data often have a life that goes beyond a specific research project 

or even beyond the career of the researcher responsible for collecting them. Old 

data sets can often provide answers to new research questions without a new data 

collection effort. In addition, some research requires drawing together individual 

data sets from different sources to develop regional or more generally applicable 

estimates of treatment responses and potential yields. In some cases, there is a 

need to secure new data to supplement those now existing and to extend work to 

less studied species or conditions. The magnitude of work and costs involved in the 

establishment, maintenance, and measurements of research plots and management 

of the data produced has led to more extensive use of cooperative data collection 

efforts, now facilitated by computer technology. In the past, cooperation and exchange of data has often been severely hampered by the general absence of uniform 

procedures for collecting, coding, recording, documenting, and summarizing data.

It is often a major task merely to discover what information exists. Once data 

are located, much information is then lost in attempting to reconcile inconsistent 

measurements and coding systems. Individual data sets frequently require their 

own tailor-made computer programs. Conversion to a common format and codes, 

essential for analysis by a single set of programs, is costly and prone to error.

Standardization is clearly important. It is impractical to expect that detailed 

specifications could be written that would meet the data collection needs of all 

organizations and all research objectives. However, research workers and cooperating organizations concerned with particular species or types of major importance 

Standardizing data 

standards, codes, and 

documentation for a 

minimum variable set 

facilitates use of data 

beyond the original 

planned use.
55

Permanent-Plot Procedures for Silvicultural and Yield Research

should jointly prepare and adopt specifications for collecting and recording permanent plot data. These should provide for a minimum set of required measurements, 

standards, information codes, and documentation.

The elements involved are:

• An individual(s) in each organization responsible for permanent plots. They 

should establish and maintain a database of plot data relevant to specified 

objectives that can be continually updated. This would provide specified 

information on the nature of the installation, treatments applied, and the 

status of existing data.

• Agreement on minimum specifications for the basic design standards and 

measurements to be made on all permanent plots. This manual and field 

manuals from regional cooperatives should provide a basis for this process.

• Individual organizations should maintain up-to-date documentation on the 

data format and coding system used. Standard data formats and coding system would be desirable. However, many organizations have existing legacies and it is impossible to anticipate the special interests and objectives of 

individual studies. For cooperative data collection efforts, data formats and 

codes should be designed so that the user has latitude to subdivide codes 

or add additional special-purpose codes, while retaining certain mandatory 

categories and codes common to all data in the system and necessary for 

compatibility with associated computational programs.

Examples of codes and the types of information typically needed are given in 

“Tree Classification Codes” in Appendix A. The Silviculture and Modeling Team 

at the Pacific Northwest Research Station’s Olympia Forestry Sciences Laboratory 

currently uses these codes. Although there is no implication intended that others 

should adopt these as given, they do illustrate the types of information that must be 

provided in such a system. 

Each organization will likely use its own computer programs designed to operate on their data sets for the format and specific codes used. For cooperative studies, 

common applications should be available. These should be well documented and 

perform the following tasks:

• Maintaining and updating information describing installation and plot status.

• Updating plot and tree data.

• Editing and correcting new plot and tree data.

• Calculating standard summaries of plot and tree data.

Efforts to encourage standardization and develop data management systems are 

not new. The Western Forestry and Conservation Association (1977) gave a list of 
56

GENERAL TECHNICAL REPORT PNW-GTR-634

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 have since evolved considerably and have been incorporated in many systems 

(for example, Sweet and Byrne 1990), often in the context of commercially available relational database programs. Such systems or portions of them exist in some 

organizations, including regional research cooperatives and some industrial organizations. Most are either not publicly available or are incomplete or inadequately 

documented.

A critical component to data management is data storage. Although data sets 

need to be accessible and updateable, they also need to be protected. Paper records 

(documentation, maps, and field sheets) should be stored in a fireproof cabinet. 

Computer files and programs should be backed up and archived offsite on a durable 

medium and in a format that is likely to be readable in the future despite changes in 

software and operating systems. A scheme to periodically verify and refresh electronic data storage systems will be required.

Maintenance and operation of a data management system are not simple tasks 

that can be delegated to anyone with some acquaintance with computers and data 

processing. It requires both abilities in programming and operation of database programs, and a considerable knowledge of related aspects of forest mensuration and 

silviculture. Without the latter, nonsense may not be recognized until it is too late to 

do anything about it.

Metric Equivalents

When you know: Multiply by: To find:

Inches (in) 25.4 Millimeters (mm)

Inches (in) 2.54 Centimeters (cm)

Feet (ft) .3048 Meters (m)

Square feet (ft2) .0929 Square meters (m2)

Cubic feet (ft3) .028 Cubic meters (m3)

Acres (ac) .4047 Hectares (ha)

Milacres .0004047 Hectares (ha)

Square feet per acre (ft2/ac) .2296 Square meters per hectare (m2/ha)

Cubic feet per acre (ft3/ac) .06997 Cubic meters per hectare (m3/ha)

Miles per hour (mph) 1.609 Kilometers per hour (kph)

Fluid ounces (oz) .0296 Liters (L)

Gallons (gal) 3.78 Liters (L)

Tons .907 Megagrams (Mg)

Degrees Fahrenheit (°F) (°F – 32) × 0.556 Degrees Celsius (°C)

A critical component 

to data management is 

data storage.
57

Permanent-Plot Procedures for Silvicultural and Yield Research

Literature Cited

Alemdag, I.S.; Honor, T.G. 1973. 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. 14 p. plus tables.

Andrew, I. 1986. Simple experimental designs for forestry field trials. Rev. FRI 

Bull. 71. Rotorua, New Zealand: Forest Research Institute. 45 p.

Arney, J.D.; Curtis, R.O. 1977. 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. 

18 p.

Beck, J.A., Jr.; Teeguarden, D.E.; Hall, D.O. 1966. Stump diameter-d.b.h. 

relationships for young-growth mixed conifer species. California Forestry and 

Forest Products. No. 44. Berkeley, CA: University of California, School of 

Forestry. 6 p.

Beers, T.W. 1962. Components of forest growth. Journal of Forestry. 

60(4): 245–248.

Bell, J.F.; Dilworth, J.R. 1997. Log scaling and timber cruising. Corvallis, OR: 

John Bell and Associates. 439 p.

Bell, J.F.; Gourley, R. 1980. Assessing the accuracy of a sectional pole, Haga 

altimeter, and alti-level for determining total height of young coniferous stands. 

Southern Journal of Applied Forestry. 4(3): 136–138.

Bitterlich, W. 1981. Telerelaskop techniques. In: Proceedings, 17th world congress 

of the International Union of Forestry Research Organizations, Division 4; Japan. 

[Place of publication unknown]: [Publisher unknown]: 155–162.

Bluhm, A.A.; Bower, A.L.; Buermeyer, K.; Ahrens, G.R.; Hibbs, D. 2003.

Hardwood silviculture cooperative red alder stand management study field 

manual. Corvallis, OR: Hardwood Silviculture Cooperative, Forest Science 

Department, Oregon State University. 93 p.

Brackett, M. 1973. Notes on tarif tree volume computation. Res. Manage. 

Rep. 24. Olympia, WA: Washington Department of Natural Resources. 26 p.

Bruce, D. 1926. A method of preparing timber-yield tables. Journal of Agriculture 

Research. 32(6): 543–557.
58

GENERAL TECHNICAL REPORT PNW-GTR-634

Bruce, D. 1972. Some transformations of the Behre equation of tree form. Forest 

Science. 18(2): 164–166.

Bruce, D. 1976. Metrication—What’s next? Journal of Forestry. 74(11): 737–738.

Bruce, D. 1977. Yield differences between research plots and managed forests. 

Journal of Forestry. 75(1): 14–17.

Bruce, D. 1980. 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; Vienna. [Place of 

publication unknown]: [Publisher unknown]: 49–50.

Bruce, D.; Curtis, R.O.; Vancoevering, C. 1968. Development of a system of 

taper and volume tables for red alder. Forest Science. 14(3): 339–350.

Bull, E.L.; Parks, C.G.; Torgersen, T.R. 1997. Trees and logs important to 

wildlife in the interior Columbia River basin. Gen. Tech. Rep. PNW-GTR-391. 

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

Research Station. 55 p.

Cao, Q.V.; Burkhart, H.E.; Max, T.A. 1980. Evaluation of two methods for cubicvolume prediction of loblolly pine to any merchantable limit. Forest Science. 

26(1): 71–80.

Carbonnier, C.; Fries, J. 1976. Permanent plots in Swedish growth and yield 

research. In: Fries, J., ed. Permanent plots in forestry growth and yield research. 

Subject Group S4.01. Res. Note 43. Stockholm: International Union of Forestry 

Research Organizations, Royal College of Forestry, Department of Forest Yield 

Research: 50–56.

Chambers, C.J., Jr. 1978. Predicting dbh from stump dib and stump height 

for second growth Douglas-fir. DNR Note 25. Olympia, WA: Washington 

Department of Natural Resources. 2 p.

Chambers, C.J.; Foltz, B.W. 1980. Comprehensive tree-volume tarif tables. 

3rd ed. Olympia, WA: Washington Department of Natural Resources. 13 p. 

plus tables. 

Cline, S.P.; Berg, A.B.; Wight, H.M. 1980. Snag characteristics and dynamics in 

Douglas-fir forests, western Oregon. Journal of Wildlife Management. 

44(4): 773–786.

Clutter, J.L.; Jones, E.P., Jr. 1980. Prediction of growth after thinning in old-field 

slash pine plantations. Res. Pap. SE-RP-217. Asheville, NC: U.S. Department of 

Agriculture, Forest Service, Southeastern Forest Experiment Station. 14 p.
59

Permanent-Plot Procedures for Silvicultural and Yield Research

Curtis, R.O. 1967a. Height-diameter and height-diameter-age equations for 

second-growth Douglas-fir. Forest Science. 13(4): 365–375.

Curtis, R.O. 1967b. A method of estimation of gross yield of Douglas-fir. Forest 

Science Monograph 13. 24 p.

Curtis, R.O. 1983. 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. 56 p.

Curtis, R.O.; Arney, J.D. 1977. 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. 7 p.

Curtis, R.O.; Bruce, D. 1968. Tree heights without a tape. Journal of Forestry. 

66(1): 60–61.

Curtis, R.O.; Hyink, D.M. 1985. Data for growth and yield models. In: Van 

Hooser, D.D.; Van Pelt, N., comps. Proceedings—growth and yield and other 

mensurational tricks: a regional technical conference. Gen. Tech. Rep. INT-193. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain 

Research Station: 1–5.

Curtis, R.O.; Marshall, D.D. 2000. Why quadratic mean diameter? Western 

Journal of Applied Forestry. 15(3): 137–139.

Curtis, R.O.; Marshall, D.D.; DeBell, D.S., eds. 2004. Silvicultural options for 

young-growth Douglas-fir forests: the Capitol Forest Study. Gen. Tech. Rep. 

PNW-GTR-598. Portland, OR: U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Research Station. 110 p. 

Decourt, N. 1973. Protocole d’installation et de mesure des placettes de production 

semi-permanentes [Procedures for installation and measurement of semipermanent yield plots]. [City of publication unknown], France: Centre National 

de Recherches Forestieres (INRA). 25 p.

Demaerschalk, J.P.; Kozak, A. 1982. Dbh measurements and conversions in the 

metric system. Forest Chronicles. 58(4): 173-175.

Fabricius, L.; Oudin, A.; Guillebaud, W.H. 1936. Outlines for permanent sample 

plot investigations. [Place of publication unknown]: International Union of Forest 

Research Organizations. 33 p.
60

GENERAL TECHNICAL REPORT PNW-GTR-634

Flewelling, J.W. 1993. Variable-shape stem-profile predictions for western 

hemlock. Part II. Predictions from DBH, total height, and upper stem 

measurements. Canadian Journal of Forest Research. 23: 537–544.

Flewelling, J.W.; Raynes, L.M. 1993. Variable-shape stem-profile predictions 

for western hemlock. Part I. Predictions from DBH and total height. Canadian 

Journal of Forest Research. 23: 520–536.

Forest Productivity Council of British Columbia. 1998. Definition and 

estimation of top height for site index. Available online at http://www.for.

gov.bc.ca/hre/fpc/standards/topheight/index.htm. (Feb. 14, 2005).

Forest Productivity Council of British Columbia. 1999. Minimum standards 

for establishment and remeasurement of permanent sample plots in British 

Columbia. Rev. Victoria, BC: British Columbia Ministry of Forests. 28 p. 

Forestry Commission. 1979. Sample plot code. London: (British) Forestry 

Commission. Unpaged.

Garcia, O. 1998. Estimating top height with variable plot sizes. Canadian Journal 

of Forest Research. 28: 1509–1517.

Garrett, S.; Kempf, J.J.; Copstead, R.L. 1997. Instruments for measuring stem 

diameters. San Dimas, CA: San Dimas Technology and Development Center. 

13 p. 

Gray, H. 2003. Monitoring stand structure in mature coastal Douglas-fir forests: 

effect of plot size. Forest Ecology and Management. 175: 1–16.

Gray, H.R. 1956. The form and taper of forest-tree stems. Inst. Pap. 32. Oxford, 

United Kingdom: Oxford University, Imperial Forestry Institute. 79 p.

Gregoire, T.G. 1993. Estimation of forest growth from successive surveys. Forest 

Ecology and Management. 56: 267–278.

Grosenbaugh, L.R. 1963. Optical dendrometers for out-of-reach diameters: 

a conspectus and some new theory. Forest Science Monograph 4. 47 p.

Hahn, J.H.; Leary, R.A. 1979. Potential diameter growth functions. 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: 22–26.

Hall, F.C. 2002. Photo point monitoring handbook: Part A—Field procedures. 

Gen. Tech. Rep. PNW-GTR-526. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station. 48 p.
61

Permanent-Plot Procedures for Silvicultural and Yield Research

Hamilton, G.J. 1976. Permanent sample plots in Britain. In: Fries, J., ed. 

Permanent plots in forestry growth and yield research. Subject Group S4.01. Res. 

Notes 43. Stockholm: International Union of Forestry Research Organizations, 

Royal College of Forestry, Department of Forest Yield Research: 75–81.

Hann, D.W. 1994. A key to the literature presenting tree volume and taper 

equations for species in the Pacific Northwest and California. Res. Contrib. 6. 

Corvallis, OR: Forest Research Laboratory, Oregon State University. 58 p.

Hann, D.W. 1995. A key to the literature presenting site-index and dominantheight-growth curves for species in the Pacific Northwest and California. Res. 

Contrib. 7. Corvallis, OR: Forest Research Laboratory, Oregon State University. 

26 p.

Hann, D.W.; Hester, A.S.; Olsen, C.L. 1997. ORGANON user’s manual, version 

6.0. Corvallis, OR: Department of Forest Resources, Oregon State University. 

167 p.

Hann, D.W.; Larsen, D.R. 1990. Diameter growth equations for fourteen tree 

species in southwest Oregon. Res. Bull. 9. Corvallis, OR: Forest Research 

Laboratory, Oregon State University. 18 p.

Hann, D.W.; Wang, C. 1990. Mortality equations for individual trees in the 

mixed-conifer zone of southwest Oregon. Res. Bull. 67. Corvallis, OR: College 

of Forestry, Forest Research Laboratory, Oregon State University 17 p.

Hazard, J.W.; Peterson, C.E. 1984. Objectives and analytical methods of the 

regional forest nutrition research project. Inst. For. Resour. Contrib. 53. Seattle, 

WA: College of Forest Resources, University of Washington. 23 p.

Hegyi, F. 1973. 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. 13 p.

Henderson, J.A.; Peter, D.H.; Lesher, R.D.; Shaw, D.C. 1989. Forested plant 

associations of the Olympic National Forest. R6 Ecol. Tech. Pap. 001-88. 

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

Region. 502 p.

Holdaway, M.R.; Leary, R.A.; Thompson, J.L. 1979. 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: 27–30.
62

GENERAL TECHNICAL REPORT PNW-GTR-634

Hummel, F.C.; Locke, G.M.L.; Jeffers, J.N.R.; Christie, J.M. 1959. Code of 

sample plot procedure. Bull. 31. London: Forestry Commission. 113 p.

Hynynen, J.; Ojansuu, R. 2003. Impact of plot size on the effect of competition in 

individual-tree competition measures for growth and yield simulators. Canadian 

Journal of Forest Research. 33: 455–465.

Iles, K. 2003. A sampler of inventory topics. Nanaimo, BC: Kim Iles and 

Associates, Ltd. 869 p.

Jaakola, S. 1967. 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. [Place of publication unknown]: 

[Publisher unknown]: 370–378.

Jeffers, J.N.R. 1972. Experimental design and analysis in forestry research. [Place 

of publication unknown]: International Union of Forest Research Organizations. 

172 p.

Karsh, M.B.; Lavigne, M.B. 1993. Guidelines for editing permanent sample plot 

data. Information Report N-X-287. St. John’s, Newfoundland: Forestry Canada, 

Newfoundland and Labrador Region. 13 p.

Keen, F.P. 1937. Climatic cycles in eastern Oregon as indicated by tree rings. 

Monthly Weather Review. 65(5): 175–188.

Kohl, M.; Scott, C.T.; Zingg, A. 1995. Evaluation of permanent sample surveys 

for growth and yield studies: a Swiss example. Forest Ecology and Management. 

71: 187–194.

Kozak, A. 1988. A variable-exponent taper equation. Canadian Journal of Forest 

Research. 18: 1363–1368.

Kozak, A. 1998. Effects of upper stem measurements on predictive ability of 

a variable-exponent taper equation. Canadian Journal of Forest Research. 

28: 1078–1083.

Krumland, B.; Wensel, L.C. 1980. Concepts, design, and uses of coastal growth 

models. Res. Note 14. Berkeley, CA: University of California, College of Natural 

Resources. 7 p.

Magnussen, S. 1999. Effect of plot size on top height in Douglas-fir. Western 

Journal of Applied Forestry. 14(1): 17–27.
63

Permanent-Plot Procedures for Silvicultural and Yield Research

Maguire, D.; Chappell, N.; Bennett, W. [and others]. 1992. Stand management 

cooperative field procedures manual: Douglas-fir version. Seattle, WA: 

Stand Management Cooperative, College of Forest Resources, University of 

Washington. 74 p. 

Marckworth, G.O.; McKay, D.; Gross, W.C. 1950. Techniques for establishing 

permanent growth plots in the Douglas-fir region. In: Reports of the West Coast 

Forestry Procedures Committee on various recommended forest practices and 

techniques. Rep. No. VIII. Portland, OR: Western Forestry and Conservation 

Association: 59–67.

Marshall, P.L.; Davis, G.; LeMay, V.M. 2000. Using line intersect sampling 

for coarse woody debris. For. Res. Tech. Rep. TR-003. Nanaimo, BC: British 

Columbia Forest Service, Vancouver Forest Region. 34 p.

Martin, A.J. 1981. Taper and volume equations for selected Appalachian 

hardwood species. Res. Pap. NE-490. Broomall, PA: U.S. Department of 

Agriculture, Forest Service, Northeastern Forest Experiment Station. 22 p.

Martin, G.L. 1982. A method for estimating ingrowth on permanent horizontal 

sample points. Forest Science. 28(1): 110–114. 

Maser, C.; Anderson, R.G.; Cromack, K.; Williams, J.T.; Martin, R.E. 

1979. Dead and down woody material. In: Thomas, J.W., ed. Wildlife habitats 

in managed forests in the Blue Mountains of Oregon and Washington. Agric. 

Handb. 553. Washington, DC: U.S. Department of Agriculture, Forest Service: 

78–95.

Max, T.A.; Burkhart, H.E. 1976. Segmented polynomial regression applied to 

taper equations. Forest Science. 22(3): 283–289.

Max, T.A.; Schreuder, H.T.; Hazard, J.W.; Oswald, D.D.; Teply, J.; Alegria, 

J. 1996. The Pacific Northwest Region vegetation and inventory monitoring 

system. Res. Pap. PNW-RP-493. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station. 22 p.

McArdle, R.E.; Meyer, W.H.; Bruce, D. 1961. The yield of Douglas-fir in the 

Pacific Northwest. Tech. Bull. 201. Rev. Washington, DC: U.S. Department of 

Agriculture. 24 p.

McClure, J.P. 1968. Predicting tree d.b.h. from stump measurements in the 

Southeast. Res. Note SE-99. Asheville, NC: U.S. Department of Agriculture, 

Forest Service, Southeastern Forest Experiment Station. 4 p.
64

GENERAL TECHNICAL REPORT PNW-GTR-634

McEwen, A.D. 1979. Yield research plots of the Forest Research Institute. 

In: Elliot, D.A., ed. Mensuration for management planning of exotic forest 

plantations. Symp. 20. Rotorua, New Zealand: New Zealand Forest Service, 

Forest Research Institute: 253–301.

Mesavage, C. 1969. Converting dendrometer estimates of outside-bark stem 

diameters to wood diameters on major southern pines. Res. Note SO-93. New 

Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest 

and Range Experiment Station. 4 p.

Moeur, M. 1993. Characterizing spatial patterns of trees using stem-mapped data. 

Forest Science. 39(4): 756–775.

Monserud, R.A. 2002. Large-scale management experiments in the moist 

maritime forests of the Pacific Northwest. Landscape and Urban Planning. 59: 

159–180.

Myers, C.A. 1966. Yield tables for managed stands with special reference to the 

Black Hills. Res. Pap. RM-21. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Forest and Range Experiment Station. 20 p.

Myers, C.A. 1971. Field and computer procedures for managed-stand yield tables. 

Res. Pap. RM-79. Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment Station. 24 p.

Myers, C.C.; Beers, T.W. 1968. Point sampling for forest growth estimation. 

Journal of Forestry. 66(12): 927–929.

Osborne, J.G.; Schumacher, F.X. 1935. The construction of normal-yield and 

stand tables for even-aged timber stands. Journal of Agricultural Research. 

51(6): 547–564.

Parker, R.C. 1997. Nondestructive sampling applications of the Tele-Relaskop in 

forest inventory. Southern Journal of Applied Forestry. 21(2): 75–83.

Parker, R.C.; Matney, T.G. 1999. Comparison of optical dendrometers for 

prediction of standing tree volume. Southern Journal of Applied Forestry. 

23(2): 100–107.

Quigley, M.F.; Slater, H.H. 1994. Mapping forest plots: a fast triangulation 

method for one person working alone. Southern Journal of Applied Forestry. 

18(3): 133–136.

Reed, D.D.; Liechty, H.O.; Burtons, A.J. 1989. A simple procedure for mapping 

tree locations in forest stands. Forest Science. 35(3): 657–662.
65

Permanent-Plot Procedures for Silvicultural and Yield Research

Reukema, D.L. 1964. Some effects of freeze injury on development of Douglas-fir. 

Northwest Science. 38(1): 14–17.

Robertson, W.M.; Mulloy, G.A. 1944. Sample plot manual. Misc. Ser. 4. Ottawa, 

ON: Dominion Forest Service, Canadian Department of Mines and Resources. 

60 p. plus tables.

Robertson, W.M.; Mulloy, G.A. 1946. Sample plot methods. Ottawa, ON: 

Dominion Forest Service, Canadian Department of Mines and Resources. 69 p.

Smith, J.H.G. 1975. Use of small plots can overestimate upper limits to basal area 

and biomass. Canadian Journal of Forest Resources. 5(3): 503–505.

Staebler, G.R. 1954. Standard computations for permanent sample plots. Portland, 

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

and Range Experiment Station. 14 p.

Stafford, S.G. 1985. A statistics primer for foresters. Journal of Forestry. 

83(3): 148–157.

Stage, A.R. 1973. Prognosis model for stand development. Res. Pap. INT-137. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain 

Forest and Range Experiment Station. 32 p.

Stage, A.R. 1977. Forest inventory data and construction of growth models. Zurich: 

Berichte Eidgenössische Anstalt für das Forstliche Versuchswesen. 171: 23–27.

Stahl, G.; Ringvall, A.; Fridman, J. 2001. Assessment of coarse woody debris—

a methodological overview. Ecological Bulletin. 49: 57–70.

Sweet, M.D.; Byrne, J.C. 1990. A standardized data structure for describing 

and exchanging data from remeasured growth and yield plots. Gen. Tech. Rep. 

INT-GTR-271. Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Research Station. 43 p.

Synnott, T.J. 1979. A manual of permanent plot procedures for tropical rain 

forests. Trop. For. Pap. 14. Oxford, United Kingdom: University of Oxford, 

Commonwealth Forestry Institute. 67 p.

U.S. Department of Agriculture, Forest Service. 1935. Sample plots in 

silvicultural research. Circ. 333. Washington, DC. 88 p.

Vuokila, Y. 1965. Functions for variable density yield tables of pine based on 

temporary sample plots. Helsinki, Finland: Communicationes Instituti Forestalls 

Fenniae 60.4. 86 p.
66

GENERAL TECHNICAL REPORT PNW-GTR-634

Waddell, K. 2002. Sampling coarse woody debris for multiple attributes in 

extensive forest inventories. Ecological Indicators. 1: 139–153.

Walters, D.K.; Hann, D.W. 1986. Taper equations for six conifer species in 

southwest Oregon. Res. Bull. 56. Corvallis, OR: Forest Research Laboratory, 

Oregon State University. 41 p.

Western Forestry and Conservation Association. 1977. A set of recommended 

parameters and measurement instructions for field records of permanent growth 

plots. 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. 7 p.

Wheeler, P.R. 1962. Penta prism caliper for upper-stem diameter measurements. 

Journal of Forestry. 60(12): 877–878.

Williams, M.S.; Bechtold, W.A.; LaBau, V.J. 1994. Five instruments for 

measuring tree height: an evaluation. Southern Journal of Applied Forestry. 

18(2): 76–82.

Williams, M.S.; Cormier, K.L.; Briggs, R.G.; Martinez, D.L. 1999. Evaluation 

of the Barr & Stroud FP15 and Criterion 400 laser dendrometers for measuring 

upper stem diameters and heights. Forest Science. 45(1): 53–61.

Wing, M.G.; Solmie, D.; Kellogg, L. 2004. Comparing digital range finders for 

forestry applications. Journal of Forestry. 102(4): 16–20.

Wycoff, W.R. 1990. A basal area increment model for individual conifers in the 

Northern Rocky Mountains. Forest Science. 36(4): 1077–1104.
67

Permanent-Plot Procedures for Silvicultural and Yield Research

Appendix A: Checklist of Needed Plot and 

Tree Measurement Information

Plot description

The following indicates plot description items that should be recorded in some 

standard format:

• Installation number

• Plot number

• Location: forty, section, township, range, state, GPS coordinates 

• Local name of installation

• Organization responsible

• Contact person

• Status: active, abandoned, destroyed

• Plot age b.h. (or from seed—specify), at first measurement

• Site index

• Site index system used

• Plot area

• Plot shape

• Stem mapped: yes or no

• Primary species

• Secondary species

• Elevation

• Aspect, azimuth (N = 360)

• Slope percent

• Slope position

• Measurement units: English or metric

• Stand origin: natural, planted, seeded (if known, note spacing, seed source, 

site preparation, etc. under general comments)

• Project identification

• Date of first measurement: month, day, year

 (repeat for each successive measurement)

• Date of first thinning, if any: month, day, year

 (repeat for each successive thinning)

Date of first fertilization, if any: month, day, year

 (repeat for each successive fertilization)

• Fertilization treatments: (enter successively for repeated treatments)

• Method of fertilizer application (hand, fixed-wing aircraft, helicopter)

• Nutrient element, application rate per unit area
68

GENERAL TECHNICAL REPORT PNW-GTR-634

• Physical soil description (if available)

• Analytical soil characteristics (if available)

• Area environmental characteristics (if available)

• Vegetation control, if any

• General comments: descriptive notations on any special characteristics of 

the area, plot, or treatment history not adequately described.

Tree Description Record

Installation number

Plot number

Tree number

Species

Age b.h. as of this plot measurement (ring counts made at this measurement)

Stem map coordinates (stem-mapped plots only)

Tree measurement information to be recorded for each successive measurement:

• Diameter b.h.

• Height (height-sample trees only)

• Height to live crown (height-sample trees only)

• Crown width (height-sample trees only, optional)

• Crown class code

• Tree class code

• Tree damage, nature/cause

• Tree damage, severity

Current Forest Service species codes for both tree species and secondary 

vegetation consist of four alpha characters, of which the first two are the first two 

letters of the genus and the second two are the first two letters of the species name. 

In cases where this leads to duplication, a fifth numerical character is added. Thus, 

the species code for Douglas-fir (Pseudotsuga menziesii) becomes PSME. A list of 

species codes for the coastal Douglas-fir region is given in table 164 of Henderson 

and others (1989). A more complete and up-to-date nationwide list is given in the 

national plants database (http://plants.usda.gov).

Tree Classification Codes

The following system of tree classification codes is currently used in silvicultural 

studies at the Olympia Forestry Sciences Laboratory, and will serve to illustrate the 

types of information needed. This illustrates characteristics needed in any system. 

With modifications or additions it should meet most needs. Thus, some users may 

want additional codes relating to fire (such as percentage of crown scorch, height of 

bole charring) or to other specific diseases and pests.
69

Permanent-Plot Procedures for Silvicultural and Yield Research

Species

Code Common name Scientific name

ABAM Pacific silver fir Abies amabilis Dougl. ex Forbes

ABGR Grand fir Abies grandis (Dougl. ex D. Don) Lindl.

ABLA2 Subalpine fir Abies lasiocarpa (Hook.) Nutt.

ACCI Vine maple Acer circinatum Pursh

ACMA Bigleaf maple Acer macrophyllum Pursh

ARME Pacific madrone Arbutus menziesii Pursh

ALRU Red alder Alnus rubra Bong.

CHNO Alaska yellow-cedar Chamaecyparis nootkatensis (D. Don) Spach

PICO Lodgepole pine Pinus contorta Dougl. ex Loud.

PIMO Western white pine Pinus monticola Dougl. ex D. Don

PISI Sitka spruce Picea sitchensis (Bong.) Carr.

PREM Bitter cherry Prunus emarginata Dougl. ex Eaton

PSME Douglas-fir Pseudotsuga menziesii (Mirb.) Franco

RHPU Cascara Rhamnus purshiana DC.

SASP Willow species Salix species

THPL Western redcedar Thuja plicata Donn ex D. Don

TSHE Western hemlock Tsuga heterophylla (Raf.) Sarg.

UNCLH Unclassified hardwood (species unidentified)

UNCLS Unclassified softwood (species unidentified)

For species not listed above, use the first two letters of the genus and first two 

letters of the species scientific names for the code.

Tree Class

Code Tree class (all trees)

10 Live tree (leave tree)

11 Ingrowth tree

12 New tree, missed at previous measurement(s)

13 Live tree not suitable for height/diameter curves or height growth

21 Standing dead (snag)

22 Down dead

23 Dead cut tree

24 Presumed dead; could not relocate

30 Live cut tree (marked to be cut)

31 Live tree cut, not planned at time of treatment

40 Off-plot tree
70

GENERAL TECHNICAL REPORT PNW-GTR-634

Crown Class

Code Crown class (live trees only)

1 Dominant

2 Codominant

3 Intermediate

4 Suppressed

5 Understory

6 Overstory (usually from an older age class; sometimes called 

 superdominant)

7 Open grown

8 Shrub (single stem origin)

9 Shrub clump (multiple stem origin)

Dead Tree Class

Code Snags

1 Bark present; limbs and branches present; top usually pointed; 

sapwood intact, sound, incipient decay, hard, original color; 

heartwood sound, hard, original color.

2 Bark beginning to slough; few limbs and no fine branches 

remaining; top may be out; sapwood sloughing, advanced 

decay, fibrous, firm to soft; heartwood sound at base, incipient 

decay in outer edge of upper bole, hard.

3 Bark sloughing; limb stubs only; top broken; sapwood sloughing, 

fibrous, soft; heartwood incipient decay at base, advanced decay 

throughout upper bole, fibrous, hard to firm.

4 Bark sloughing; few to no branch stubs; top broken; sapwood 

sloughing, cubical, soft; heartwood advanced decay at base, 

sloughing from upper bole, fibrous to cubical, soft.

5 Bark mostly gone; no branches or stubs; top broken; sapwood 

gone; heartwood sloughing, cubical, soft, or fibrous, very soft, 

conifers frequently encased in hardened shell.

Code Down dead

1 Bark intact and tight; branches, twigs, and fines present; shape 

round; wood hard; log elevated above ground on support points.

2 Bark mostly present but may be loose; branches present but twigs 

and fines generally absent; shape round; wood hard to partly soft; 

log elevated above ground but slightly sagging.
71

Permanent-Plot Procedures for Silvicultural and Yield Research

3 Bark loose and missing in places; twigs and fines absent; wood hard and 

in large pieces with some decay; shape round to oval; all of log on ground.

4 Bark generally absent; small branches, twigs, and fines absent; wood 

soft and in blocky pieces; shape round to oval; all of log on ground.

5 Bark entirely absent; branches, twigs, and fines absent; wood soft 

and powdery; shape oval; all of log always on ground.

Damage Codes

Damage is coded as a five-character code as follows: XXSSR where XX is 

two-character damage code, SS is two-character (or digit) severity code, and 

R is one-character recency code. Up to three sets of codes can be used. If damage 

does not fit one of the defined severity codes, then do not code the damage.

Code Logging damage

LB Live branch breakage (felling damage to major branches)

 Code Severity

 1 One to five major branches broken

 2 More than five major branches broken

RD Root damage (usually caused by skidding)

 Code Severity

 1 Support roots damaged on one side of tree

 2 Support roots damaged on two sides of tree

 3 Support roots damaged on three sides of tree

 4 Support roots damaged on four sides of tree

SB Basal bark removal—debarking within first 1.3 m above ground on 

bole, usually caused by skidding, and can extend into bole section 

above 1.3 m. Used only for wounds occurring within the first 1.3 m. If 

wound does not extend into the lower 1.3 m, then code as upper bole 

damage, UB. Basal bark removal severity is divided into two single 

numeric fields, one for the width dimension (circumference class), and 

one for the vertical dimension (length class); both fields must be completed for basal bark removal.

Code Circumference class (width dimension)

 1 Bark missing on <10 percent of circumference 

 2 Bark missing on 10 to 25 percent of circumference

 3 Bark missing on 26 to 50 percent of circumference

 4 Bark missing on 51 to 75 percent of circumference
72

GENERAL TECHNICAL REPORT PNW-GTR-634

 5 Bark missing on 76 to 95 percent of circumference

 6 Bark missing on more than 95 percent of circumference

Code Length class (vertical dimension)

 1 <0.5 m (<1.5 ft)

 2 0.5 to 0.9 m (1.5 to 2.9 ft)

 3 1.0 to 1.4 m (3.0 to 4.4 ft)

 4 1.5 to 1.9 m (4.5 to 6.0 ft)

 5 2.0 m + (6.0 ft +)

UB Upper bole damage—usually felling damage to bole above 1.3 m. 

Not used for wounds extending into the lower 1.3 m of the bole. 

For wounds extending into the lower 1.3 m of the bole, use basal 

bark removal damage code, SB.

Code Severity

 1 2 to 3 m vertical stripe, one side only

 2 3+ m vertical stripe, one side only

 3 Vertical stripe(s) on two or more sides

LT Broken top caused by logging

 Code Severity

 1 Leader or tip missing (top one to three internodes missing)

 2 25 percent or less of crown missing, but more than three 

 internodes missing

 3 26 to 50 percent of crown missing

 4 More than 50 percent of crown missing

 5 Leader or stem broken, but still attached and alive

LL Excessive lean (includes bent; excludes down) caused by logging

LR Uprooted, down but alive caused by logging

LM Recently dead, caused by logging

Code Crown appearance, disease, and insects

AP Aphids

CH Chlorotic (yellowish needles, may be a symptom of root rot)

DI Diseased/sick/dying (declining vigor, short, sparse needles 

 sometimes accompanied by chlorotic appearance)

LA Leaf abnormalities (rusts, blisters, curling)

LE Leaf-eating insects

MI Mistletoe 
73

Permanent-Plot Procedures for Silvicultural and Yield Research

RU Blister rust (on white pine)

TA Limb and twig abnormalities (galls, cankers, lesions, witches’ brooms, 

etc.; not blister rust)

Code Stem diseases and insects

BE Bark beetles

SD Decay

SC Cankers, galls, and lesions

SR Rusts

WB Wood borers (primarily in hardwoods)

Code Animal damage

AD Animal damage (other than listed below)

AR Antler rub

BD Bear bark removal 

BR Deer or elk browse 

BV Beaver

PD Porcupine 

SH Sapsucker or woodpecker feeding holes (typically ring(s) 

 of small-diameter, pencil-sized holes around stem)

WC Woodpecker cavities (usually found in dead portions, but 

 occasionally found in live stems)

Code Weather

DE Desiccation

LG Lightning

SS Sunscald

TD Tip dieback (frost damage)

UR Uprooted, down (alive)

WS Wind, snow, ice

Code Stem physical defects (stem form)

BS Basal scar (origin unknown)

BT Broken top 

 Code Severity

 1 Leader or tip missing (top one to three internodes missing)

 2 25 percent or less of crown missing, but more than three 

 internodes missing

 3 26 to 50 percent of crown missing
74

GENERAL TECHNICAL REPORT PNW-GTR-634

 4 More than 50 percent of crown missing

 5 Leader or stem broken, but still attached and alive

CK Cracks

CR Crook

DT Dead top

 Code Severity

 1 Leader or tip dead (top one to three internodes dead)

 2 25 percent or less of crown dead, but more than three 

 internodes dead

 3 26 to 50 percent of crown dead

 4 More than 50 percent of crown dead

 5 Leader or stem broken, but still attached and dead

EB Epicormic branching 

EL Excessively limby (wolf tree or grouse ladder)

FT Forked top or stem

 Code Severity

 1 Leader or tip forked (within top one to three internodes)

 2 Within crown, but below top three internodes

 3 Above b.h. but below crown

 4 At or below b.h.

FU Fluting

MT Multiple top or stem (more than two above b.h.)

 Code Severity

 1 Leader or tip forked (within top one to three internodes)

 2 Within crown, but below top three internodes

 3 Above b.h. but below crown

 4 At or below b.h.

RB Ramicorn branch(es)

SI Sinuosity

SG Stems grown together (cannot measure separately)

SW Sweep

SP Sprout (origin of stem)

WP Whip

XL Excessive lean (includes bent, excludes down)
75

Permanent-Plot Procedures for Silvicultural and Yield Research

Code Damage—Other (use for all damage not already defined above) 

M Damage likely to reduce monetary value or vigor substantially

S Damage likely to render tree monetarily worthless or likely to 

 eventually result in tree death

N Minimal or no economic damage

Code Damage Recency

N New; since last measurement

O Old; before last measurement

Code Mortality (since prior measurement)

RD Root disease

WS Wind, snow, ice

Blank Unknown or other

Comment Codes

Code Meaning

01 See field sheets

02 No tag

03 Tag hung on branch

04 Tag on barlock circling stem

05 Tag too high

06 Tag too low

07 Height measurement verified

08 Diameter measurement verified

09 Previous height changed

10 Previous d.b.h. changed

11 Change in terminal

12 Replacement tree

13 Cut tree

14 On skid road/landing

15 Height not measured

16 Verified cut

17 Marked as cut tree but not cut

18 Height to live crown measurement verified

19 Uneven crown—average height to live crown

20 <15 cm recent colluvium

21 15 to 50 cm recent colluvium

22 50 to 100 cm recent colluvium
76

GENERAL TECHNICAL REPORT PNW-GTR-634

23 >100 cm recent colluvium

24 High d.b.h.

25 Low d.b.h.

26 Broken below b.h.

27 Origin from rooted branch

28 Moved diameter to b.h. location

29 Pruned
77

Permanent-Plot Procedures for Silvicultural and Yield Research

Appendix B: Field Tree Measurement Procedures

Plot measurement record

A standard form, which can also serve as a data entry document, (or an equivalent 

recorder screen) 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.

Figure 7 is a computer-produced form (or equivalent recorder screen) with the 

following fields:

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.

Species: tree species, 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.

Tree class: codes representing live, ingrowth, etc., this measurement.

Crown class: this measurement.

DBH: (1) previous measurement (1998 in this case), to nearest 0.1 inch.

 (2) this measurement, to nearest 0.1 in.

Height: (1) previous measurement (1998 in this case), to nearest foot.

 (2) this measurement (1998 in this case), to nearest foot. Entered 

 directly if measured by height pole or laser; if by clinometer 

 and tape or clinometer and pole methods, transcribed from the 

 height measurement field sheet (fig. 11) before leaving the area.

HLC: height to live crown. 

 (1) previous measurement (1998 in this case) to nearest foot.

 (2) New measurement (2004) to nearest foot. Entered directly if 

 measured by height pole or laser; if by clinometer and tape or 

 clinometer and pole methods, transcribed from the height 

 measurement field sheet (fig. 11) before leaving the area.

Damage: kind, severity, and recency as determined at current measurement 

and recorded with the appropriate codes.

Dead class: dead trees only, condition code.

Cause: current measurement, appropriate code.

Coordinates: tree coordinates on stem-mapped plots.

Notes: comments.

Other items can be added as needed for a particular study.
78

GENERAL TECHNICAL REPORT PNW-GTR-634

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. 

If heights are measured with a height pole or laser, values are entered directly 

on the plot measurement form (fig. 7). If heights are measured with tape and 

clinometer or tape and pole methods, the field form shown in fig. 11 can be used. 

Columns on the form represent the following:

• Tree identification number for each tree in the height sample.

• D.b.h. of each tree.

• Recorded height (H) at last measurement, if any.

• Recorded height to live crown (HLC) at last measurement, if any. 

(Note: First four items 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.)

• Slope distance from instrument to tree.

• Angle to tip of tree.

Installation__________ Location___________ Date____________

Plot____________ Study_____________ Measured by___________

Subplot_________ English___ /metric___ Recorded by___________

Tree # DBH Previous 

19__

Slope

Dist

ds

∠

tip

θ2

∠

HLC

θ3

∠

pole

θ4

Pole

lgth

p

∠

base

θ1

Add

h

Calc 

H

Calc 

HLC

Notes

H HLC

Calculation checked by___________ on _____________

Transcribed to permanent record by____________ on_____________

Figure 11—A field form for height measurement, for use with either tape and clinometer or pole and clinometer methods.
79

Permanent-Plot Procedures for Silvicultural and Yield Research

• A blank column may be inserted 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.

• Angle to base of live crown.

• Angle to tip of measurement pole (if using tape and clinometer method).

• Length of measurement pole used.

• Angle to lower aim point.

• Height of lower aim point above ground.

• Blank column provided for miscellaneous notes.

• Total height of tree calculated from above values.

• Height to base of live crown calculated from above values.

Heights should be calculated in the field and checked for reasonableness against 

the previous measurement (if any).
80

GENERAL TECHNICAL REPORT PNW-GTR-634

Appendix C: Sampling and Plot Measurement Scheme 

for a Large-Scale Management Experiment

A number of large-scale management experiments have been initiated in the Northwest in the past decade (Monserud 2002) to evaluate silvicultural regimes that attempt to integrate production of timber, wildlife, biodiversity, and scenic values. The 

regimes cannot be realistically evaluated on the small plots that have been common 

in silvicultural research. Therefore the experimental units become treatment areas 

on the order of 20 to 60+ acres. This necessarily introduces considerably more uncontrolled variation than in typical small-plot experiments, but provides results that 

are operationally realistic and allows evaluation of scenic and wildlife effects that 

are not possible on individual small plots. 

The meaningful analysis unit is the treatment unit. The primary values being 

compared are mean values for the units estimated from a series of small permanent 

plots within each unit. From this standpoint, size of the individual plot is not critical 

provided the number of such plots is sufficient to provide good estimates of mean 

unit characteristics, including both stand condition and growth rates.

In this section we describe one scheme now in use for sampling treatment units 

in such an experiment (Curtis and others 2004). We do not present this as the only 

or the best method, but it may be helpful for others with similar problems.

Each treatment unit is sampled with a series of small plots arranged on a systematic grid, with spacing selected to yield some desired number of such plots 

within each treatment. 

The individual tree measurement plot is a 1/5-acre circular plot, with center 

marked by a white polyvinyl chloride (PVC) pipe driven in the ground and referenced by azimuth and distance to three tagged witness trees (fig. 12). 

Prior to the initial stand treatment, all trees 9.6 in and larger are measured on the 

1/5-acre plot (fig. 12). Trees 5.6 in and larger are measured on a 1/10-acre concentric 

plot. Trees 1.6 to 5.5 in are measured on a 0.025-acre concentric plot. Pretreatment 

d.b.h. measurements are recorded to nearest inch or centimeter (fig. 13). This provides the stand table that serves as the basis for preparing treatment specifications. 

Height measurements on a sample of trees may or may not be wanted as a basis for 

preliminary volume computations.

After the initial stand treatment, all trees are tagged, detailed individual tree 

measurements are made, and descriptive information is recorded as shown in figure 

7 or an equivalent form. 

Four supplementary subplot centers are located at the intersection of the 1/5-acre 

plot boundary and N-S and E-W lines through the plot center. These are marked 

with PVC pipe of smaller diameter, and serve as centers of two types of subplot:
81

Permanent-Plot Procedures for Silvicultural and Yield Research

Figure 12—Permanent plot design, with associated subplots.

Figure 13—A field form for pretreatment tree measurements with the plot design of figure 12.

Installation__________ Treatment__________ Plot No.____________

Location: Legal Description__________________ GPS______________

Crew______________________ Date__________

Reference trees: R1: species_________ DBH_____ Azimuth_____ Distance

R2: species_________ DBH_____ Azimuth_____ Distance

R3: species_________ DBH_____ Azimuth_____ Distance

Grid azimuth________________ Distance between plots______________

Trees 1.6–5.5 in d.b.h. on 0.025 acre, plot radius 18.6 ft No pretreatment measures on control (untreated) plots

Trees 5.6–9.5 in d.b.h. on 0.10 acre, plot radius 37.2 ft

Trees 1.6–5.5 in d.b.h. on 0.20 acre, plot radius 52.7 ft

Species DBH HT Species DBH HT Species DBH HT
82

GENERAL TECHNICAL REPORT PNW-GTR-634

Figure 14—A field form for recording regeneration and understory with the plot design of figure 12.

• Trees >1 ft in height and ≤ 1.5 in d.b.h. are recorded (but not tagged) on 

0.004 acre. Planted trees, if any, are identified by distance and azimuth 

from the subplot center.

• An ocular estimate of percentage of cover and average height of each major 

nontree species present is made on a concentric 0.025-acre circular plot.

Data sheets for recording subplot data are illustrated in figures 13 and 14. A 

supplementary record, not shown, identifies each planted seedling on the subplot by 

species, height, and azimuth and distance from the subplot stake. This makes it possible to follow mortality and growth of individual seedlings until they reach a size 

suitable for permanent tagging.

This scheme provides comparable estimates of unit means at successive remeasurements at minimal cost. It can be supplemented as needed by subdivision and 

classification by quadrants within the plots, by transects measuring such things as 

regeneration development in openings of different sizes, by more elaborate enumeration of minor shrub and herbaceous species present, or additional measurements of 

such things as coarse woody debris.

REGENERATION AND UNDERSTORY INVENTORY

Installation__________________ Plot__________ Subplot____________

Measured by______________________ Date__________

Established regeneration, 4-mil-acre subplot radius (7.45 ft)

Established acceptable stems (H >1 and DBH <1.6 in) Species DBH Height Origin (P or N)

Largest stem 

Second largest

Additional planted

PSME TSHE THPL ALRU

Number on plot

Ground vegetation, 1/40-acre subplot (radius 18.6 ft)

Plant group Shrubs Ferns Herbs/Forbs Grasses Mosses

Percentage cover

Common name Scientific name Code Percentage cover Average height (ft)
83

Permanent-Plot Procedures for Silvicultural and Yield Research

Appendix D: Checklist of Items Likely To Be Needed

Copy of study plan, any establishment report

Manual or specifications with applicable measurement instructions and 

 recording codes

Maps

Aerial photos

GPS equipment

Tatum holder

Pocket calculator 

Field tally sheets or recording device, containing previous measurements, if any

Coordinate paper or standard form for sketch maps

Protractor

Engineer’s pocket scale

Pocket stereoscope

String, large cones (for delimiting plot boundaries and strips within plot)

Paint gun, pressurized paint cans or tube paint for marking boundaries, 

 numbering trees, marking b.h. point

Lumber crayons, yellow

Lumber crayon holders

Nails, aluminum (for tags)

Plastic barlocks

Staple gun, staples (9/16 in), cards (if there may be a need to tag trees temporarily)

Prenumbered metal tags, in sequence (if tagging new plot)

Label maker with metal tape, or write-on metal tags

Claw hammer

Wire (for tagging small trees, corner stakes)

Side-cutting pliers

Flagging, assorted colors

Bark scribe

Hatchet

Machete or brush axe

Small maul (for driving stakes)

Stakes (metal, plastic, or other permanent material) for plot corners and centers

Pruning saws, with sheath

Pocket compass

Staff compass with staff

Fiberglass tape, 100 to 150 ft or 60 m, with reel (for laying out plot boundaries 

 and measuring base lines)
84

GENERAL TECHNICAL REPORT PNW-GTR-634

Spare tape

Pocket cloth tape, 75 ft or 30 m

Range poles

Height pole, rod level

Clinometers of type appropriate for expected tree size

Laser, with staff mount and extra batteries

Prism reflector for use with laser

Diameter tapes, with spares

Increment borers with extra bits

Increment core holders (plastic drinking straws or the equivalent)

Bark gauge

Signs for plot boundaries

Hand lens

Flashlight with extra batteries

Flagged pins (initial plot layout)

First-aid kit

Packs for carrying equipment

Safety goggles, hard hats, high-visibility vests, footgear as appropriate for 

 working conditions

Bow saw

Chainsaw and associated equipment (if trail and boundary clearance is needed)
85

Permanent-Plot Procedures for Silvicultural and Yield Research

Appendix E: Plot Dimensions

Commonly used plot dimensions and slope correction factors are given in tables 

1 through 3.

Table 1—Dimensions of square plots of specified area

English units Metric units

Area Side Diagonal Semidiagonal Area Side Diagonal Semidiagonal

Acres - - - - - - - - - -Feet - - - - - - - - - - Hectares - - - - - - - - - Meters - - - - - - - -

 0.001 6.60 9.33 4.67 0.001 3.16 4.47 2.24

 .01 20.87 29.52 14.76 .01 10.00 14.14 7.07

 .05 46.67 66.00 33.00 .05 22.36 31.62 15.81

 .10 66.00 93.34 46.67 .10 31.62 44.72 22.36

 .15 80.83 114.32 57.16 .15 38.73 54.77 27.39

 .20 93.34 132.00 66.00 .20 44.72 63.25 31.62

 .25 104.36 147.58 73.79 .25 50.00 70.71 35.36

 .30 114.32 161.67 80.83 .30 54.77 77.46 38.73

 .40 132.00 186.68 93.34 .40 63.25 89.44 44.72

 .50 147.58 208.71 104.36 .50 70.71 100.00 50.00

Table 2—Dimensions of circular plots 

of specified area

 English Metric

 Area Radius Area Radius

 Acres Feet Hectares Meters

 0.001 3.72 0.001 1.784

 .01 11.78 .01 5.64

 .05 26.33 .05 12.62

 .10 37.24 .10 17.84

 .15 45.60 .15 21.83

 .20 52.66 .20 25.23

 .25 58.88 .25 28.21

 .30 64.50

 .40 74.47

 .50 83.26
86

GENERAL TECHNICAL REPORT PNW-GTR-634

Table 3—Multipliers to convert slope distance to 

horizontal distance and horizontal distance to slope 

distance

 Slope cos θ 1/cos θ Slope cos θ 1/cos θ

Percent Percent

 0 1.0 1.0 62 0.850 1.177

 5 .999 1.001 64 .842 1.187

 10 .995 1.005 66 .835 1.198

 15 .989 1.011 68 .827 1.209

 20 .981 1.020 70 .819 1.221

 22 .977 1.024 72 .812 1.232

 24 .972 1.028 74 .804 1.244

 26 .968 1.033 76 .796 1.256

 28 .963 1.038 78 .788 1.268

 30 .958 1.044 80 .781 1.281

 32 .952 1.050 82 .773 1.293

 34 .947 1.056 84 .766 1.306

 36 .941 1.063 86 .758 1.319

 38 .935 1.070 88 .751 1.332

 40 .928 1.077 90 .743 1.345

 42 .922 1.085 92 .736 1.359

 44 .915 1.092 94 .729 1.372

 46 .908 1.101 96 .721 1.386

 48 .902 1.109 98 .714 1.400

 50 .894 1.118 100 .707 1.414

 52 .887 1.127

 54 .880 1.136

 56 .872 1.146

 58 .865 1.156

 60 .857 1.166

Note: d = horizontal distance

ds = slope distance

 θ = slope angle in degrees

d = ds × cos θ

ds = d / cos θ
Pacific Northwest Research Station

Web site http://www.fs.fed.us/pnw

Telephone (503) 808-2592

Publication requests (503) 808-2138

FAX (503) 808-2130

E-mail pnw_pnwpubs@fs.fed.us

Mailing address Publications Distribution

 Pacific Northwest Research Station

 P.O. Box 3890

 Portland, OR 97208-3890
U.S. Department of Agriculture

Pacific Northwest Research Station

333 SW First Avenue

P.O. Box 3890

Portland, OR 97208-3890

Official Business

Penalty for Private Use, $300