United States 

Department of 

Agriculture 

Forest Service 

Intermountain 

Forest and Range 

Evperiment Station 

Ogden, UT 84401 

General Technical 

Report INT-129 

August 1982 

Handbook for 

Inventorying Surface 

Fuels and Biomass in 

the Interior West 

James K. ~rown, Rick D. Oberheu, 

and Cameron M. Johnston 
THE AUTHORS CONTENTS 

JAMES K. BROWN received his bachelor's degree from 

the University of Minnesota in 1960, his master's from 

Yale University in 1961, and his Ph.D. from the University 

of Michigan in 1968, all in forestry. From 1961 to 1965, he 

did research on field measurement of fuel properties and 

fire-danger rating systems while with the Lake States 

Forest Experiment Station. In 1965, he transferred to the 

Northern Forest Fire Laboratory, Missoula, Mont., where 

he conducted research on the physical properties, inventory, and prediction of fuels. He currently is leader of a 

fire effects and use project in Missoula. 

RICK D. OBERHEU received his bachelor's degree in 

forestry from the University of Montana in 1973. In 1974, 

he joined the Northern Forest Fire Laboratory, where he 

worked extensively with fuel and vegetation inventory on 

a fire effects and use project. He currently is a fuels 

management specialist on the Wallowa-Whitman National 

Forest. 

CAMERON M. JOHNSTON attended the University of 

Montana from 1965 to 1969. He worked as an engineering 

data processor for the USDA Forest Service Northern 

Region from 1969 to 1972. In 1972, he became the computer programmer for the fuel science research work unit 

at the Northern Forest Fire Laboratory. In 1978, he 

became the computer specialist for the Division of Aviation and Fire Management for the Northern Region. He 

currently is a programer analyst with the Fire Effects 

and Use R and D Program at the Northern Forest Fire 

Laboratory. 

RESEARCH SUMMARY 

Comprehensive procedures for inventorying weight per 

unit area of living and dead surface vegetation are presented to facilitate estimation of biomass and appraisal 

of fuels. The authors show how to conduct fieldwork and 

estimate weight per unit area of downed woody material, 

forest floor litter and duff, herbaceous vegetation, shrubs, 

and small conifers. Weights by species are determined for 

shrubs and small conifers. Coverage of shrubs and 

herbaceous vegetation are estimated. The several sampling methods involve the counting and measuring diameters of downed woody pieces that intersect vertical 

sampling planes, comparing quantities of litter and herbaceous vegetation against standard plots that are 

clipped and weighed, tallying shrub stems by basal 

diameter classes, tallying conifers by height classes, and 

measuring duff depth. The procedures apply most 

accurately in the Interior West; however, techniques for 

herbaceous vegetation, litter, and downed woody material 

apply anywhere. A computer program and card punching 

instructions are included for processing inventory data. 

Page 

INTRODUCTION ................................. 1 

CHOICE OF TECHNIQUES. ........................ 2 

StandingTrees ................................ 2 

Shrubs ....................................... 2 

Herbaceous Vegetation ......................... 3 

Litter and Duff ................................. 3 

Downed Woody Material. ........................ 4 

PROCEDURES .................................. 4 

Number of Sample Points. ....................... 5 

Fieldwork.. ................................... 5 

Field Equipment .............................. .13 

Calculations .................................. 14 

PUBLICATIONS CITED ........................... .19 

APPENDIX I 

Applicability of Techniques ...................... 21 

APPENDIX II 

Sampling Procedures ........................... 21 

APPENDIX Ill 

Computer Instructions ......................... .22 

APPENDIX IV 

Fieldwork Hints. .............................. .48 

I 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 which may be suitable. I 

Approved for publication by Intermountain Station 

February 1981 
Un~ted States 

Department of 

Agriculture 

Forest Service 

Intermountain 

Forest and Range 

Experiment Station 

Ogden, UT 84401 

General Technical 

Report INT-129 

August 1982 

Handbook for 

Inventorying Surface 

Fuels and Biomass in 

the Interior West 

James Km Brown, Rick Dm Oberheu, 

and Cameron M. Johnston 

INTRODUCTION 

This publication describes procedures for inventorying 

weight of forest floor duff, forest floor litter, herbaceous 

vegetation, shrubs, small conifers, and downed woody 

material (fig. 1). The procedures furnish estimates for live 

and dead vegetation by diameter classes. The inventory 

methods have application to several facets of forest and 

range management and to research investigations. 

The procedures were initially developed to provide estimates of fuel loading (weight per unit area) as part of an 

effort to appraise fire behavior potential for planning fire 

strategies in wilderness areas (Habeck and Mutch 1973; 

Aldrich and Mutch 1972). Although the methodology 

emphasizes forest fuels, estimates of aboveground 

biomass of herbaceous vegetation, shrubs, and small 

conifers may be useful for purposes other than fuel 

Figure 1.-Vegetative components included in procedures for estimating biomass and 

fuel loading. 
appraisal. The procedures were used by numerous field 

crews for several years. This experience aided 

considerably in developing the step-by-step procedures 

reported here. 

The inventory procedures are useful for determining 

biomass of any vegetation up to about 10 ft (3 m) in 

height. The entire set of procedures or a part of them can 

be applied to estimate all or any one of the vegetative 

components. 

The procedures apply most accurately in the Interior 

West. The techniques for estimating biomass of herbaceous vegetation, litter, and downed woody material, however, apply anywhere. The shrub techniques apply most 

accurately to shrubs in the Northern Rocky Mountains. 

Considering sampling efficiency as attainment of desired 

precision by the most practical means, the most efficient 

methods of sampling vegetation vary by plant species and 

purpose. Different techniques are required to most eificiently sample all vegetation. Thus, the single set of procedures assembled here may not be the most efficient for 

some situations. Nevertheless, the procedures are appropriate for sampling each category of vegetation and can 

be widely applied with a minimum of training and experience. Further discussion on applicability of techniques is 

in appendix I. 

The inventory procedures specify sampling of branch 

and stemwood under 3 inches in diameter by diameter 

classes of 0 to 0.25 inches (0 to 0.6 cm), 0.26 to 1.0 inches 

(0.6 to 2.5 cm), and 1.0 to 3.0 inches (2.5 to 7.6 cm). The 

size classes correspond in increasing size to I-, lo-, and 

100-hour average moisture timelag classes for many 

woody materials (Fosberg 1970). The size classes are 

used as moisture timelag standards in the U.S. National 

Fire-Danger Rating System (Deeming and others 1977;. A 

moisture timelag is the amount of time for a substance to 

lose or gain approximately two-thirds of the moisture 

above or below its equilibrium moisture content. Appraisal 

of forest fuels is greatly facilitated when data on biomass 

are assimilated by these size classes. 

Fuel depth was originally included in the procedures 

but was removed because interpretation of fuel depth was 

complex and required trained people to evaluate the 

reasonableness of depth observations. Although Albini 

(1975) developed an algorithm that was largely successful 

in processing fuel depth data for input to Rothermel's 

(1972) fire spread model, spurious depth measurements 

coupled with the fact that fire behavior predictions were 

highly sensitive to depth, continued to cause erratic 

predictions. In predicting fire behavior using Rot hermel's 

model, depth together with loading is required to determine fuel bulk density. Recent research (Brown 1981) 

indicates that characterization of bulk density for understory vegetation and fuel groups may eliminate the need 

for measurement of fuel depth in inventorying fuel for 

practical applications. 

To assure reasonable fire behavior predictions, inventoried fuel loadings should be interpreted by fire behavior 

modeling specialists for proper input to Rot hermel's 

model. Estimates of certain fuel components such as 

downed woody material and duff can be used without 

interpretation in operating Albini's (1 976) burnout model. 

This model is incorporated in a computer program called 

HAZARD, which appraises slash fuels (Puckett and others 

1979). As the technology in fire behavior modeling grows, 

other direct applications of fuel inventory may arise. 

CHOICE OF TECHNIQUES 

An efficient inventory of all fuel and understory 

vegetation requires several techniques because of the 

varied physical attributes of vegetation. Forest vegetation 

is comprised of living and dead plants, both standing and 

downed. Plants range in size from small grasses and 

forbs to large shrubs and trees. Pieces of vegetation considered as fuel particles range in size from small leaves, 

needles, and twigs to large branches and tree boles. 

Vegetation and fuels having similar physical characteristics, which can be appropriately sampled using the 

same technique, can be grouped as follows: 

1. Standing trees 

2. Shrubs 

3. Herbaceous vegetation (grasses and forbs) 

4. Forest floor litter (01 horizon) 

5. Forest floor duff (02 horizon) 

6. Downed woody material. 

The inventory procedures assembled here are made up 

of different techniques for each category of vegetation. 

Before presenting the procedures, methods of sampling 

and reasons why certain techniques were chosen are discussed for each category of vegetation. 

Standing Trees 

A method for estimating biomass of conifers less than 

10 ft (3 m) in height was included in the procedures presented here because small trees can contribute significantly to propagation of both surface and crown fires. The 

method requires measurement of number of trees per 

acre by species and height. Biomass of foliage and 

branchwood by size class is calculated from weight and 

height relationships developed by Brown (1978). 

Biomass of trees over 2 inches (5 cm) d.b.h. can be estimated from biomass tables or from tree volume estimates 

converted to weight using wood densities (USDA 1974). To 

determine volumes from tree volume tables, estimates of 

the number of trees per acre or basal area per acre by 

d.b.h. and species required to access the tables can be 

determined from commonly used plot and plotless sampling met hods. Procedures for inventorying trees greater 

than 10 ft (3 m) in height are not included here because 

they are commonly understood and used in forestry. If 

desired, they can be readily applied along with the procedures for surface vegetation. 

Shrubs 

Shrub biomass can be estimated nondestructively by 

one of two basic methods. One approach relates biomass 

to stem diameters as described by Telfer (1969) for shrubs 

in eastern Canada, and Brown (1976) for shrubs in the 

Northern Rocky Mountains. High correlations between 

stem diameters and weights of various shrub parts have 

been reported (Lyon 1970; Buckman 1966; Whittaker 1965). 

This approach requires a tally of number of stems by 

stem diameter on plots of known size. Another method 

relies on the relationships between biomass, canopy area, 
and canopy volume as described for semidesert shrubs in 

New Mexico (Ludwig and others 1975), sagebrush 

(Artemisia tridentata) (Rittenhouse and Sneva 1977), and 

low shrubs in California (Bently and others 1970). This 

method requires measurements of crown diameters and 

shrub height. 

The method involving measurement of stem diameters 

has the advantage of applying easily to tall shrubs 

compared to the method of measuring crown dimensions. 

Measurement of stem diameters probably permits the 

most accurate estimation of biomass because stem 

diameters should relate more directly to biomass than 

does space occupied by shrubs. A disadvantage of 

measuring stem diameters is that fieldwork can involve 

considerable time, especially for small shrubs comprised 

of many stems such as grouse whortleberry (Vaccinium 

scoparium). The fieldwork can be minimized by recording 

diameters by size classes. The met hod requiring measurement of crown dimensions is rapid and well suited to 

small- and medium-size shrubs. The method involving 

measurement of stem diameters was incorporated in 

these procedures because it applies to shrubs of all sizes, 

and relationships for estimating biomass of leaves and 

stemwood by diameter class were available for 25 species 

(Brown 1976). 

Herbaceous Vegetation 

An extensive body of literature exists on estimating 

weight and production of range vegetation. Techniques 

for estimating weight basically fall into three categories: 

(1) clipping and weighing, (2) estimation, and (3) a 

combination of weighing and estimation. 

To aid in extensive surveys, a quick, easy-to-use 

method is needed for estimating weight. Studies in 

pasture grasses (Pasto and others 1957) and annual range 

species (Reppert and others 1962) gave reasonably high 

correlations between weight per unit area, and ground 

cover and height. Similar investigation of grasses, forbs, 

and small woody plants in forest areas showed that as 

more plant sizes and shapes are included in plots, poorer 

accuracy can be expected (Brown and Marsden 1976). 

Unless relationships of suitable accuracy are known for 

specific sites, some clipping and weighing is desirable for 

estimating herbaceous vegetation. 

The weight-estimate method has been widely used and 

tested in the southern and western United States in a 

variety of vegetation including large and small grasses 

and understory vegetation. It requires an estimate of 

actual weights and can be effectively used with double 

sampling on clipped and weighed plots. Trained observers 

can estimate within 10 percent of actual weights (Hughes 

1959). When used with double sampling, variance of estimates can be reduced (Francis and others 1979). This 

method, coupled with double sampling, has proved very 

useful in estimating forest floor litter and herbaceous 

fuels for research purposes. 

Another similar technique, the relative-weight estimate 

method (Hutchins and Schmautz 1969) has been useful in 

estimating fuels. This method is based on the assumption 

that it is easier to compare weights than estimate 

weights. It involves identifying a base plot having the 

most weight from a set of four or five plots. The weight 

on the other plots is estimated as a fraction of the base 

plot. The base plot is then clipped and weighted and 

weights on other plots calculated as a fraction of the 

base plot. 

The relative weight-estimate method was incorporated 

in these procedues because it is easy to use, requires a 

minimum of training, and is based on some clipping and 

weighing. The advantages and disadvantages of this 

method include: 

Advantages 

1. Requires little training or experience to learn the 

method; remembering weight images is minimal. 

2. Checking weight estimates against actual weights is 

unnecessary. 

3. Estimates are not affected by changes in light and 

moisture content as can happen with the weight-estimate 

technique. 

4. Quantities of vegetation can be rated on a relative 

basis more easily than they can be actually estimated. 

Disadvantages 

1. The set of plots must all be readily visible to the 

observer to permit accurate comparisons. 

2. Clipping and bagging on one out of every four or five 

plots is necessary. 

3. Accuracy of the method has had little study. 

4. Probably not as accurate as weight-estimate method 

used by trained and experienced observers. 

Litter and Duff 

Sampling the forest floor litter separately from the duff 

is desirable because the litter is usually much less dense 

than the duff and frequently burns independently of the 

duff. The most accurate method of estimating forest floor 

weights is by collecting and weighing samples. This 

necessitates a cumbersome field procedure involving 

transport of soil containers and eventual ovendrying. 

Attempts to correlate stand characteristics and forest 

floor weights and depths have not always been successful. For example, forest floor weights in red pine 

plantations (Dieterich 1963) and ponderosa pine stands 

(Ffolliott and others 1968) were highly correlated with tree 

basal area. On the other hand, relationships between 

forest floor weights and basal area, site index, and stand 

age were insignificant in natural stands of red pine and 

jack pine (Brown 1966), and poorly correlated in eastern 

white pine (Mader and Lull 1968). In an extensive study of 

southwestern ponderosa pine and mixed conifers, Sackett 

(1979) found a lack of reliable relationships for predicting 

forest floor quantities from basal area or duff depth. 

Factors such as fire history, decay rates, and storms can 

strongly influence forest floor quantities. Thus, high 

correlations between forest floor quantities and basal 

area, site index, and stand age appear to have a limited 

basis-low correlations should not be surprisi,ng. The 

relationship between depth and weight of duff can be 

used to estimate weight recognizing that accuracy can be 

low. Measurement of duff depth was adopted for these 

procedures because: 

1. Collecting and weighting duff would be impractical 

for large inventories. 

2. The literature on duff bulk density seemed substantial enough to use in estimating weight from depth. 
3. Depth is easily measured and can be a useful measurement itself for planning and evaluating prescribed 

fires conducted for fuel reduction and site preparation. 

The bulk densities in table 1 served as a basis for 

establishing the following bulk densities that are used in 

the computer program to calculate duff loadings from 

duff depth: 

Cover type Bulk density 

L blf t3 

1. Ponderosa pine 5 

2. Lodgepole pine 8 

Douglas-fir 

Shrubfields 

Grand fir 

3. Others 10 

Because the bulk densities used to calculate duff 

weights are approximations, the weights are approximations and must be interpreted accordingly. If desired, 

bulk densities other than those above can be used to 

calculate duff loadings as described in the section on 

calculations. 

Litter depth was not adopted as a basis for estimating 

litter weight because the literature on bulk density of litter 

was scant. More important, perhaps, is that considerable 

judgment is required to identify the top of litter. This 

problem is serious because the litter layer is often very 

thin and large errors in depth measurement could result. 

The relative weight-estimate technique was chosen for 

litter because it applies readily to litter and was also 

being used for herbaceous vegetation. 

Downed Woody Material 

Downed woody material is the dead twigs, branches, 

stems, and boles of trees and shrubs that have fallen and 

lie on or above the ground. Loadings of downed woody 

material vary considerably among stands due primarily to 

site productivity and stand history (Brown and See 1981). 

Table 1 .-Bulk densities of forest floor duff summarized from literature 

Collecting and weighing downed woody material is 

impractical in most forest stands. The planar intersect 

technique (Brown 19746; Brown and Roussopoulos 1974) 

adopted here is nondestructive and avoids the time-consuming and costly task of collecting and weighing large 

quantities of downed woody material. It has the same 

theoretical basis as the line intersect technique (Van 

Wagner 1968). The planar intersect technique involves 

counting intersections of woody pieces with vertical 

sampling planes that resemble guillotines dropped 

through the downed debris. Volume is estimated; then 

weight is calculated from volume by applying estimates 

of specific gravity of woody material. 

PROCEDURES 

The procedures in this section are an assembly of 

sampling techniques that provide estimates of the 

following variables: 

1. Biomass and fuel loading on an ovendry basis of: 

a. Downed woody material 

b. Forest floor litter and duff 

c. Herbaceous vegetation 

d. Shrubs 

e. Conifers less than 10 ft (2 m) in height. 

2. Depth of duff and height of shrubs and small trees. 

3. Percentage cover of herbaceous vegetation and 

shrubs. 

4. Percentage of dead in herbaceous vegetation and 

shrubs. 

5. Percentage cover of forest floor litter. 

6. Number of small trees per acre by species. 

7. Stand age. 

In addition, provision is made for recording and summarizing slope, elevation, aspect, cover type, and habitat 

ty PeThe field procedures involve counting shrub and small 

tree stems and intersected pieces of downed woody 

Forest type 

Forest 

Location floor layer 

Bulk density 

Mean Standard Source 

deviation 

Ponderosa pine 

Ponderosa pine 

Mixed conifers 

Eastern white pine 

Lodgepole pine 

Fir - hemlock 

Fir - hemlock 

White spruce, balsam, poplar 

White pine 

White pinelhemlock 

Red pine 

Jack pine 

Mont. 

Ariz. 

Wash. 

Wash. 

Mass. 

Wyo. 

Wash. 

Wash. 

Ontario 

Wisc. 

N.Y. 

Minn. 

Mich. 

F, H 

F 

H 

Basalt (F,H) 

other soil (F,H) 

Basalt (F,H) 

other soil (F,H) 

F 

H 

F. H 

Mull (F,H) 

Mull (F,H) 

Mull (F,H) 

Mull (F,H) 

Greasy Mor (F,H) 

F, H 

F. H 

2.10 Brown (1970) 

0.15 Ffolliott and others (1968) 

.44 

Wooldridge (1968) 

Wooldridge (1968) 

Mader and Lull (1968) 

1.9 Brown (1974a) 

Williams and Dyrness (1967) 

Mader (1953) 

Mader (1953) 

Mader (1 953) 

Mader (1 953) 

Brown (1966) 

Brown (1966) 
material; measuring diameters, depth, and height of vegetation; ocularly estimating percentage of cover and 

percentage of dead vegetation; and extracting increment 

cores for determining tree age. All the procedures may be 

followed to furnish estimates of all vegetation, or a 

subset of the procedures may be used to furnish an estimate of any single variable such as duff depth or shrub 

biomass. For an average amount of vegetation, about 15 

minutes per sample point are required to complete 

measurements. Counting shrubs and clipping herbaceous 

vegetation and litter require the most time. 

Deciding when to sample.-The time of year when 

vegetation, especially grasses and forbs, is sampled has 

a large influence on results. Grasses and forbs may not 

be fully developed during late spring or early summer. 

Sampling at that time will result in low estimates. During 

late summer, some annuals may have cured and deteriorated to such an extent that their biomass cannot Be 

accurately estimated. The time of year when sampling is 

done must agree with the purpose of inventory. For 

appraising fuels, sampling during the normal fire season, 

such as late July and August in the western United 

States, is recommended. 

Number of Sample Points 

For any area where estimates are desired, at least 15 to 

20 sample points should be located. This sampling "intensity will often yield estimates having standard errors 

within 20 percent of the mean estimates (appendix 11). 

Areas larger than approximately 50 acres containing a 

high diveraity in amount and distribution of fuel and 

vegetation, should be sampled with more than 20 points 

to achieve standard errors within 20 percent of mean 

estimates. 

Changing the size of plots also influences the desired 

number of sample points. For sampling downed woody 

material, these procedures accommodate a variable 

length sampling plane. Choose sampling plane lengths 

from the following tabulation: 

Diameter of debris 

Downed material 0-1 inch 1-3 inches >3 inches ----- Sampling plane (ft) ----- 

Nonslash (naturally 

fallen material) 6 10-1 2 35-50 

Discontinuous 

light slash 6 10-1 2 35-50 

Continuous heavy 

slash 3 6 15-25 

If material larger than 3 inches (7.6 cm) in diameter is 

scanty or unevenly distributed, the longer sampling planes 

in the tabulation should be used. 

For fuel and vegetation other than downed woody 

material, plot sizes could be changed. If the computer 

program listed in appendix Ill is used to calculate loadings, however, it would have to be modified or its output 

corrected to adjust for different plot sizes. Variable 

sampling plane lengths are accounted for, in the program. 

The amount and distribution of vegetation, especially 

downed woody material, varies greatly among and within 

stands. Thus, these sampling recommendations should be 

considered approximate because a greater or fewer 

number of sample points may be required to furnish 

adequate precision for any given area. Sampling intensities are discussed further in appendix 11. 

Fieldwork 

Locating Sample Points 

After determining sampling area, such as a stand, 

delineate or describe its boundaries. Definition of the area 

and its boundaries should satisfy a sampling design 

based on a clear objective for the sampling. Sample 

points may be systematically or randomly located; however, systematic placement is usually the most practical. 

Two methods are: 

1. Locate plots at a fixed interval along transects that 

lace regularly across a sample area (uniform sampling 

grid). For example, on a sample area, mark off parallel 

transects that are 5 to 10 chains (100 to 200 m) apart. 

Then, along the transects, locate plots at 1- to 5-chain 

(20- to 100-m) intervals. 

2. Locate plots at a fixed interval along a transect that 

runs diagonally through the sample area. To minimize 

bias, have the transect cross areas where changes in 

fuels or biomass are suspected. Before entering the 

sample area, determine a transect azimuth and distance 

between plots. Distance between plots can be paced by 

foot or sampling rod. If variations in biomass across an 

area are obvious and significant, it may be desirable to 

divide the area into recognizable strata and sample each 

stratum separately. 

Hints for conducting fieldwork are listed in appendix IV. 

Plot Layout 

The plot layout at a sample point consists of a 

randomly positioned line transect for downed woody 

material and duff, a 11300-acre plot for trees, two 

Ih-milacre plots for shrubs, and four 0.98 by 1.97-ft (30 by 

60-cm) plots for herbaceous material and litter (fig. 2). 

Downed woody material, litter, herbaceous vegetation, 

shrubs, and small trees are measured on plots laid out 

parallel to the slope. Thus, calculations of loading on a 

horizontal acre basis require slope correction. Duff depth 

is measured vertically so that slope adjustment is unnecessary for calculating loading. 

Step I: Mark the sampling point Nith a chaining pin (No. 

9 wire or similar item). Avoid disturbing material 

around the point so that measurements can be 

accurately made. 

Step 2: Randomly determine direction of the sampling 

plane in one of two ways: 

(1) Toss a die to indicate one of six 30" angles 

between 0" and 150". The 0" heading is the 

direction of travel. Turn a fixed direction, such as 

clockwise, to position the sampling plane. 

(2) Orient the sampling plane in the direction 

indicated by the second hand of a watch at a 

given instant. To avoid bias in placement of the 

sampling plane, do not look at the fuel or ground 

while turning the interval. 

Step 3: Denote position of sampling plane by placing a 

6.8-ft inventory rod (diameter of 11300-acre plot) 

out from the chaining pin parallel to the ground 

in the direction determined in step 2 (fig. 2). A 
50-foot tape is used along this same line to measure large pieces. The tape and rod fix the position of vertical sampling planes. 

Small Trees 

Figure 3.-Positioning sample frames for 

the relative estimate technique on the surface of the forest floor. 

Vegetation 

category 

Downed 

woody 

material 

Litter 

Duff 

Herbaceous 

plants 

Shrubs 

Small 

conifers 

Step 4: Next, locate four relative estimate subplots and 

two %-milacre shrub plots on the ground as 

shown in figure 2. Mark the two shrub plots with 

chaining pins or similar devices. They are located 

90" to the sampling plane. Place the relative 

estimate frames parallel to the slope, and maintain this position when collecting samples (fig. 3). 

Similarly, count shrub stems from plots 

delineated parallel to the slope. 

Figure 2.-Plot layout at a sample point. 

Table 2.-Vegetation to be sampled by different biomass techniques 

Vegetation to be sampled by each technique is 

summarized in table 2. Some vegetation could be sampled 

by more than one technique. To avoid double sampling of 

any component, definitions of vegetation to be sampled 

by each technique must be consistently and closely 

followed. 

Technique Sampled vegetation 

Planar Twigs, branches, stems, and tree boles in and above the litter 

Intersect 

Relative- Litter is the 01 horizon or "L" layer of the floor and includes freshly fallen leaves, needles, bark 

weight flakes, cone scales, fruits, dead matted grass, and a variety of miscellaneous vegetative parts. 

Include cones that are more than one-half in or above the litter. If they are more than one-half below 

the litter, treat as duff. Omit sampling downed woody material as part of the litter because it is 

sampled by the planar intersect method. 

Depth Duff is the 02 horizon or fermentation ahd humus layers of the forest floor. It lies below the litter and 

measure- above mineral soil 

ment 

Relative- All live and dead grasses, sedges, and forbs. Dead grasses and forbs detached and fallen from their 

weight growing point should be considered litter. Some small woody plants such as bunchberry (Cornus 

estimate canadensis), twinflower (Linnea borealis), prince's pine (Chimaphila umbellata), and kinnikinnick 

(Arctostaphylos uva-ursi), should be sampled as herbs because the shrub method is inapplicable. If 

desired, small woody plants can be sampled separately using an extra form. 

Stem counts All woody shrubs except those included in the herbaceous sample. Include common juniper 

(Juniperus communis) as a shrub. 

Tree counts All conifers except common juniper. Small deciduous trees such as aspen, cottonwood, and birch 

can be handled as tall shrubs. 
Measurements 

After the subplots and line transects have been established on the ground, begin recording general information 

at the top of the inventory form (fig. 4). 

INVENTORY FORM 

CREW : 

DATE I I I STAND NO.^ I I PLOT NO. 1 I I TERRAINSLOPE I I 1 ASPECT 1 I I 

ELEV. II I STAND AGE I COVER TYPE I I H. T. I I PLANER SLOPE I 

TRANSECT LENGTHS NO. INTERSECTIONS <3 IN TRAN. LENGTH 

0-1 IN I I 1-3 IN I 1 A 0-flN I I I I f-1IN 1 I I 1-31N I I 231N I I I 

DIAMETER INTERSECTIONS 3 IN I 

SOUND )11~1~~11~11~11)11~11(11~11~1

DUFF HERBS L l TTER 

DEPTH (IN) %STAND % DEAD % COV. BASE WT. % STAND BASE WT. 

111 11 Ill 11.1 I I ILI Ill I Ibl, 

SHRUBS I 

% COV. % DEAD AVE. HT. ( IN) 

I I 11111 I PERCENT CODES 

IPI I I NO. STEMS BY D IAMETER CLASS (CM) I 

- 111 I I I, .I I, .I I I 

I -. Ill I I I I I I I 

* Ill I I I I I I I I, 

1 SMALL TREE COUNT I 

'SP . NO. HT. SP. NO. HT. SP. NO. HT. SP. NO. HT. SP. NO. HT. 

I I I I I I I I I I I I I I i 

Figure 4.-Ground fuel and vegetation inventory form. 
General Information: 

STAND ~0.1 I I I 1 I PLOT NO. I I I j Id TERRAIN SLOPE lsld ASPECT 121 1 141 STAN0 AGE 1 lSld COVER TYPE blFl I H. T. ]21b101 PLANER SLOPE (3151 

Step 1: 

Step 2: 

Step 3: 

Step 4: 

Step 5: 

Step 6: 

Step 7: 

Date can be recorded as month and year, or day 

and month. 

Identify stands and plots by consecutive 

number. Stand numbers can be placed on a 

field map for referencing locations (e.g., stand 

No. 1, plots numbered 1-10; stand No. 2, plots 

numbered 1 1-20). 

Determine topographic slope in percent. A 

Relaskop, Abney, or a clinometer is useful for 

measuring slope. 

Using a compass, record aspect of the area 

near the sample point in degrees. 

Determine elevation by an altimeter or from 

reading a contour map. If an altimeter is used, 

calibrate it daily to a known elevation. 

Determine stand age by extracting increment 

cores from three or four dominant or codominant trees in the stand. Take the cores at d.b.h. 

on the uphill side of the tree. Average the ages 

and enter the average on the form. Age needs 

to be recorded on only one plot per stand. 

Cover type is used to determine duff loading. 

For proper duff calculations, record the cover 

type that most resembles one of the following 

species categories (left justify the codes, see 

data form insert): 

Cover type is most like: Code 

1. Long-needled pine (except ponderosa pine) PP 

2. Intermediate-needled conifer (except lodge- LP 

pole pine) and other conifers that typically DF 

occur in mixed pine-fir types (except 

Douglas-f ir) 

3. Predominantly short-needled conifers Any other 

(except true fir, spruce, and hemlock) code 

Step 8: Record habitat type using a 3-digit code. The 

habitat type system developed by Pfister and 

others (1977) is appropriate here. 

Step 9: Estimate or measure the slope of the planar 

intersect sampling plane by sighting along the 

transect pole or tape previously positioned on 

the ground. Record this as a percentage. 

Step 10: Record the transect lengths. (Refer to the 

discussion on sampling plane lengths.) Note on 

the inventory form that sampling plane lengths 

for 0- to 1-inch (0- to 2.5-cm) and 1- to 3-inch 

(2.5- to 7.6-cm) material require a decimal place. 

TRANSECT LENGTHS I NO. INTERSECTIONS < 3 IN I TRAN. LENGTH 

0-1 IN 1-3 IN 11 l~d 0- f IN I 13131 f - 1 IN 1 151 1-3 IN 1 >3 IN 1 131s 

Step 1: Count the number of 0- to 0.25-inch (0- to 0.6-cm) 

and 0.25- to 1-inch (0.6- to 2.5-cm) particles 

intersected by the sampling plane. This technique 

involves counting intersections of woody pieces 

with vertical sampling planes that resemble 

guillotines dropped through the downed debris. 

The vertical plane is a plot. Consequently, in 

counting particle intersections, it is very 

important to visualize the plane passing through 

one edge of the plot rod and terminating along 

an imaginary fixed line on the ground. Once 

visualized on the ground, the position of the line 

should not be changed while counting particles 

(fig. 5). 

Figure 5.-The sampling plane is exactly 

defined by one edge of the plot rod. 

The intersections can be counted one size class 

at a time or "dot tallied," which takes slightly 

longer than counting. The actual diameter of the 

particle at the point of intersection determines its 

size class. A golno-go gage with openings of 0.25 

inch (0.6 cm), 1 inch (2.5 cm), and 3 inches (7.6 

cm) works well for training the eye to recognize 

size classes. Count the 0- to I-inch (0- to 2.5-cm) 

intersections on the 6.8-ft (2.07-m) transect (or 

whatever length is chosen). See tally rules for 

qualifying particles. 

Downed Woody Material: 

Less than 3-inch diameters.-This material should be 

measured first to avoid disturbing it and causing 

inaccurate estimates. 
Step 2: Count the number of 1- to 3-inch (2.5- to 7.6-cm) 

particles. Proceed as in step 1, but use a longer 

sampling plane, such as 10 ft (3 m). The 50-foot 

tape can be used to mark the transect. Count the 

number of intersections of woody pieces between 

1 and 3 inches (2.5 and 7.6 cm) in diameter. Refer 

to tally rules for qualifying particles. 

Three-inch and greater diameters.-Measure or estimate 

the diameters of all pieces 3 inches (7.6 cm) and larger at 

the point of intersection with the sampling plane. Record 

true piece diameters to nearest whole inch regardless of 

angle of intersection. Record sound pieces and rotten 

pieces separately. For example, the data form insert 

shows that 5- and 6-inch sound pieces were intersected 

and that 4-, lo-, and 6-inch rotten pieces were intersected. 

Consider pieces rotten when the piece at the intersection is obviously punky or can be easily kicked apart. 

A ruler laid perpendicular across a large piece of fuel 

works satisfactorily for measuring diameters (fig. 6). Be 

sure to avoid parallax in reading the ruler. See tally rules 

for qualifying particles. 

Figure 6.-Diameters of large fuels can be 

estimated using a ruler laid perpendicularly 

across the pieces. 

Tally rules.-These rules apply to pieces of all diameters: 

1. Particles qualifying for tally include downed, dead, 

woody material (twigs, stems, branches, and bolewood) 

from trees and shrubs. Dead branches attached to boles 

of standing trees are omitted because they are not 

downed vegetation. Consider a particle downed when it 

has fallen to the ground or has been severed from its 

original growing point. Dead woody stems and branches 

still attached to standing shrubs and trees are not 

counted. 

2. Twigs, and branches lying in the litter layer and 

above are counted. But they are not counted when the 

intersection between the central axis of the particle and 

the sampling plane lies in the duff (fig. 7). 

Does Not Qualify Qualifies 

Planar Intersect: intersections qualify only in litter. 

Figure 7.-Regardless of size, pieces are 

tallied only when intersection lies in and 

above the litter. 

3. If the sampling plane intersects the end of a piece, 

tally only if the central axis is crossed (fig. 8). If the plane 

exactly intersects the central axis, tally every other such 

piece. 

YES / 

Sampling Planer 6' 

Figure 8.-An intersection at the end of a 

branch or log must include the central axis 

to be tallied. 
4. Do not tally any particle having a central axis that 

coincides perfectly with the sampling plane. (This should 

rarely happen.) 

5. If the sampling plane intersects a curved piece more 

than once, tally each intersection (fig. 9). 

Carefully expose a profile of the forest floor for the 

measurement (fig. 10). A knife or hatchet helps but is not 

essential. Avoid compacting or loosening the duff where 

the depth is measured. Measure duff depth after sampling 

the downed woody material to avoid disturbing the 

downed woody material along the sampling plane. 

Figure 9.-Count both intersections for a 

curved piece. 

6. Tally wood slivers and chunks left after logging. 

Visually mold these pieces into cylinders for determining 

size class or recording diameters (fig. 6). 

7. Tally uprooted stumps and roots not encased in dirt. 

For tallying, consider uprooted stumps as tree boles or 

individual roots, depending on where the sampling planes 

intersect the stumps. Do not tally undisturbed stumps. 

8. For rotten logs that have fallen apart, visually 

construct a cylinder containing the rotten material and 

estimate its diameter. The cylinder will probably be 

smaller in diameter than the original log. 

9. Be sure to look up from the ground when sampling 

because downed material can be tallied up to any height. 

A practical upper cutoff is about 6 ft. In deep slash, 

however, it may be necessary to tally above 6 ft. 

Duff Depth: 

Step 1: Measure depth of duff to the nearest 0.1 inch, 

using a ruler held vertically at two points along 

the sampling plane: (1) 1 ft (0.3 m) from the 

sample point; and (2) a fixed distance of 3 to 5 ft 

(1 to 1.5 m) from the first measurement. 

w DEPTH (IN) 

Duff is the fermentation and humus layers on the forest 

floor. It does not include the freshly cast material in the 

litter layer. The top of the duff is where needles, leaves, 

and other castoff vegetative material have noticeably 

begun to decompose. Often the color of duff differs from 

the litter above. Individual particles usually will be bound 

by fungal mycelium. When moss is present, the top of the 

duff is just below the green portion of the moss. The 

bottom of the duff is mineral soil. 

Figure 10.-Measure duff depth along an 

exposed profile of the forest floor from the 

top of the mineral soil to the bottom of the 

01 horizon. 

When stumps, logs, and trees occur at the point of 

measurement, offset 1 ft (0.3 m) perpendicular to the right 

side of the sampling plane. Measure through rotten logs 

whose central axis is in the duff layer (fig. 11). 

Yes= center of log is duff layer or below. 

NO= center of log is above duff layer. 

x = center of log 

Figure 11.-Duff depth is measured through 

a rotten log when its central axis lies in or 

below the duff. 
Herbaceous Vegetation and Litter: 

Step 1: 

Step 2: 

Step 3: 

Step 4: 

View all four subplots and judge which one has 

the greatest weight of herbaceous plants, both 

live and dead. See table 2 for discussion of 

plants to be sampled here. The subplot picked 

with the greatest weight is the standard subplot 

and is recorded as an 8. 

Rate the amount of herbaceous plants on the 

remaining three subplots as a percentage of that 

on the standard subplot using the following 

codes established for these procedures: 

Percent 

0-5 

6-20 

21 -40 

41 -60 

61 -80 

81 -95 

96-1 00 

Code 

1 

2 

3 

4 

5 

6 

7 

For each individual subplot, ocularly estimate the 

percentage of herbaceous vegetation that is 

dead. Use the established percentage code. 

Ocularly estimate, in percentage, cover of herbaceous vegetation on subplots 1 and 2. (Percentage of cover is the percentage of subplot area 

covered by a vertical projection of herbaceous 

material.) Record cover using the established 

codes. 

View the right half of all four subplots and judge 

which one has the greatest quantity of litter. 

Occasional probing of the litter may help in 

judging quantities. Be sure to examine only 

material qualifying as litter. See table 2 for 

material to be included as litter. Record the 

standard litter subplot with an 8. 

Rate the quantity of litter on the remaining three 

subplots as a percent of that on the standard 

subplot. Be sure to view only the right half of 

each subplot. Use the established codes. 

Step 5: Clip the herbaceous vegetation from the herb 

standard subplot and place in a paper bag. 

Collect litter from the litter standard subplot 

(right half only) and place in a paper bag. Label 

bags with date, stand number, plot number, and 

litter or herb. 

- . . . - . . 

The samples should be ovendried at 95" C for a 

period of 24 hours. Record the ovendry weights, 

labeled as base weights on the inventory form, to 

the nearest 0.01 gram. Gunnysacks work well for 

transporting and storing samples. Airtight 

containers, such as plastic sacks, may promote 

decay. 

%STAND 

11294 

1183 

Shrubs: 

BASEWT. 

1 ~qm, 

Step 1: Shrubs are tallied on the two %-milacre subplots 

(fig. 2). Using a 1.86-ft (57-cm) rod (radius of 

lh-milacre plot), swing around the subplot center 

parallel to the ground and note the species that 

occur. Within each subplot, ocularly estimate 

percent cover of all shrubs together, both live and 

dead, according to the established percentage 

classes. 

Step 2: Ocularly estimate the percentage of shrub biomass that is dead according to the established 

percentage classes. 

Step 3: Measure the height of shrubs within each subplot 

from the forest floor to what appears as the 

average top. Record to the nearest whole inch. 

Step 4: On each subplot, count the number of stems by 

species and the following basal diameter 

classes: 

0 to 0.2 inch (0 to 0.5 cm) 

0.2 to 0.4 inch (0.5 to 1.0 cm) 

0.4 to 0.6 inch (1.0 to 1.5 cm) 

0.6 to 0.8 inch (1.5 to 2.0 cm) 

0.8 to 1.2 inches (2.0 to 3.0 cm) 

1.2 to 2.0 inches (3.0 to 5.0 cm) 

Over 2.0 inches (5.0 cm) 

SHRUBS 

Determine basal diameters above the root crown 

or above the swelling of the root crown, which is 

usually within 1 or 2 inches above the top of the 

litter. A golno-go gage is helpful for checking 

%COV. %DEAD 

112 

4 1 11 

1-2 

3 

AVE.HT.(IN) 

1219 1112 
diameters (fig. 12). The basal diameter classes 

are identified on the data form in centimeter 

units because they can be visualized more easily 

than inches for estimating shrub diameters. 

Figure 12.-A golno-go gage used for tallying the number of shrub stems by basal diameter classes. 

Record species using the abbreviations in the following tabulation. If a sampled species is not in 

the list, record it as a low, medium, or high shrub, 

depending on the group it most resembles. 

Whenever LOW or MED abbreviations are used, 

left justify them (see insert of inventory form). 

Shrubs Abbreviation 

Low shrubs: 

Snowberry (Symphoricarpos albus) SYAL 

Blue huckleberry (Vaccinium globulare) VAGL 

Grouse whortleberry (Vaccinium scoparium) VASC 

Wild rose (Rosa spp.) ROSA 

Gooseberry (Ribes spp.) RlLA 

White spirea (Spirea betulifolia) SPBE 

Oregon grape (Berberis repens) BERE 

Thim bleberry (Rubus parviflorus) RUPA 

Red raspberry (Rubus idaeus) RUlD 

Combined species LOW 

Medium shrubs: 

Ninebark (Physocarpus malvaceus) PHMA 

Smooth menziesia (Menziesia ferruginea) M EFE 

Utah honeysuckle (Lonicera utahensis) LOUT 

Oceanspray (Holodiscus discolor) HOD1 

Evergreen ceanothus (Ceanothus velutinus) CEVE 

Moc korange (Philadelphus le wisii) PH LE 

Russet buffaloberry (Shepherdia canadensis) SHCA 

Big sagebrush (Artemisia tridentata) ARTR 

Common juniper (Juniperus communis) JUCO 

Combined species MED 

High shrubs: 

Serviceberry (Amelanchier alnifolia) AMAL 

Mountain maple (Acer glabrum) ACGL 

Mountain ash (Sorbus scopulina) SOSC 

Mountain alder (Alnus sinuata) ALSl 

Redosier dogwood (Cornus stolonifera) COST 

Willow (Salix spp.) SASC 

Chokecherry (Prunus virginiana) PRVl 

Combined species HIGH 

Small trees 

5MAI L TREE COUNT 1 

Delineate the plot by swinging the 6.8-ft rod about the 

sample point pin and parallel to the slope. Within the 

11300-acre plot, count the number of trees less than 10 ft 

(3 m) in height by species. ~ecord the number of trees 

within each species and average their height to the 

nearest 0.5 ft. To avoid the potential of a substantial bias, 

however, do not average heights differing by more than 

5 ft. If trees of the same species differ by more than 5 ft 

in height, record them separately on the data form. If 

more than five species are identified, consolidate similar 

species. Tally only individual trees that have survived one 

growing season, are free to grow, have good coloration, 

and have root systems in mineral soil. 

Use the following tree codes (single letter codes are left 

justified; see insert of inventory form): 
Species 

Subalpine fir (Abies lasiocarpa) 

Douglas-fir (Pseudotsuga menziesi~) 

Western redcedar (Thuja plicata) 

Grand fir (Abies grandis) 

Juniper (Juniperus scopularum) 

Western larch (Larix occidentalis) 

Lodgepole pine (Pinus contorta) 

Ponderosa pine (Pinus ponderosa) 

Western white pine (Pinus monticola) 

Whitebark or limber pine (Pinus albicaulis/ 

Pinus flexilis) 

Engel man n spruce (Picea engelmannil) 

Western hemlock (Tsuga heterophylla) 

Mountain hemlock (Tsuga mertensiana) 

Pacific yew (Taxus brevifolia) 

Field Equipment 

Item 

6.8-ft plot rod marked in I-ft intervals (fiberglass rod, 

bamboo, or aluminum tubing works well) 

1-ft ruler or steel pocket tape 

Golno-go gage (can be cut from 1116-118-inch sheet 

aluminum) or small caliper 

1.86-ft plot rod marked in I-inch increments (wood dowel 

works well) 

Five chaining pins 

Four 0.98- by 1.97-ft (inside measurement) subplot 

frames, four pieces of %-inch square aluminum rod, 

loosely riveted at three corners, allows frame to be 

placed through and under vegetation. A solid frame is 

difficult to place without bias. 

Hand compass 

Relaskop, Abney, or clinometer 

Altimeter 

Increment borer 

50-ft tape (reel up cloth works best) 

Gaming die or watch with second hand 

Paper bags (size 10 or 12) and rubber bands 

Grass clippers 

Clipboard, forms, maps, and pencils 

Pack, map tube 

Code 

AF 

DF 

C 

GF 

J 

L 

LP 

PP 

WP 

Use 

Plot and transect layout, measure small tree and shrub 

heights 

Measure duff depth and diameter of intersected pieces 

Determine lh-, I-, and 3-inch diameters of downed 

woody pieces and 0.2-, 0.4-, 0.6-, 0.8-, 1.2-, and 2-inch basal 

stem diameters of shrubs 

Shrub plot layout; measure height of small trees and 

shrubs 

Mark plot locations 

Sample herbaceous vegetation and litter 

Measure aspect. Locate sample points 

Measure slope 

Measure elevation 

Determine tree age 

Delineate sampling plane 

Orient sampling plane 

Collect herb and litter samples 

Clip subplots 

Record data 

Carry equipment. Map tube keeps small rods and subplot 

frames together. 

Sampling can be completed without a compass, slope instrument, or altimeter. If only a portion of the vegetation is to 

be sampled, other equipment may be unnecessary. 
Cakdations in appendix Ill. An example of the program output is 

shown in figure 13. Loadings are calculated for land 

The calculations of fuel loadings, biomass, and other projected to a horizonal plane. The data can be readily inventoried properties are straightforward but detailed. To analyzed using a desk calculator. The following facilitate analysis, a computer program that calculates discussion explains how average biomass and fuel 

means, standard deviations, and standard errors as a per- loadings can be calculated. 

centage of means for the sampled properties is displayed 

PATTEE CANYON POSTFIRE 1900 PAGE 1 

HABITAT TYPE CODE 260 

01.25 T 

,2501 I 

LITTER 1 

DEAD HERBS I 

I~-----.~~-~~-o.I~~------~~.-~-~~.~---~~-.--o~~.~~-.~~o~.I.--~.---.-w I 

FINES I 2308, 2076, 11.2 I ,257 I 

1-3 I 2678 6 2016 I ,300 I 

LESS THAN 3 I 4986 54570 13.7 I 0559 I 

.-.----~--~~----I~~g--.~---.--.----.-~---w~--....~--...-.~.-o-.o--~.- I 

3+ TOTAL I 

SOtiND 3-6 I 

SObhD 6-10 T 

SOUND 10-20 I 

SOUIVC) 204- I 

3+ SOUND TOTAL 1 

RUTTEN 3-6 I 

HOTTEb 6-10 I 

ROTTEh 10-20 I 

RGTTEW 20+ 1 

3+ ROTTEb! TOTAL I 

--o---.-------.-I-----------.--.-----------.-.--.---.--..~-----.----- I 

DUFF I 12875 e I 1,443 I 

DEAD SHRUB I 64 171, 23e5 I ,007 I 

DEADFbEL LOAD I 36444, 52161, 17.9 I Qe085 I 

LIVE HERBS I 1132. 957. 10.6 I ,127 I 

LIVE SHRUB I 1363, 3971, 25,7 I ,153 I 

TREE NEEDLES I 0 2, 4Be1 I ,000 I 

O-.25 I 0 1. 48e1 I ,000 I 

e25 + I 0. 2, 1 X e000 I 

TOTAL TREE I 1 4 48.1 I ,000 I 

*********t DEPTH (INCHES) ********** 

Figure 13.-Output summary from computer program FUELS which analyzes the inventoried data in figure 4. 
PATTEE CANYON FOSTFIRE 1980 PAGE 2 

* TOPOGRAPHIC CONnITIQNS ********** 

I AVESAGE MINIMUM MAXIPiUR STD-DEV I 

------------x------------------------------------- I 

SLOPE I 20.5 7.0 53.0 12,32 I 

ASPECT I 171.0 I 

ELEVATIQN I 4448. 3920 . 5250, 395.3 I 

* SMALL TREES ********** 

SPECIES TREES/ACHE AVGeHTqFT. 

LP 122. . 56 

TOTAL 122. 

Figure 13. - (con.) 
Downed Woody Material 

Besides the inventoried data on number of intersections and piece diameters, calculations of loading require 

estimates of specific gravity, average diameters of 

particle size and classes, and nonhorizontal correction 

factors. Precision of the calculated loadings depends on 

determination of these constants. Detailed instructions 

for computing loading are described by Brown (1974b). 

When inventorying large areas that hold many species, 

it is practical to use values based on a composite of 

species for specific gravity, average particle diameters, 

and nonhorizonal correction factors. The following 

formulas for calculating loading assume fixed values for 

these variables: 

1. O- to 0.25-inch (O- to 0.6-cm) 

class: w = 190.7ncl(NI) (1) 

2. 0.25- to l-inch (0.6- to 2.5-cm) 

class: W = 3,650 ncl(N I) (2) 

3. 1- to 3-inch (2.5- to 7.6-cm) 

class: W = 29,040 ncl(NI) (3) 

4. 3 + -inch (7.6 + -cm) sound: - 

w = 9,312 d2cl(~l) (4) 

5. 3 + -inch (7.6 + -cm) rotten: 

w = 6,984 d2cl(NI) (5) 

where: 

Gj = average loading, ovendry basis, lblacre 

n = total number intersections by particle class per 

stand 

d2 = sum of diameters (inches squared for all 

intersected pieces per stand, inches2 

c = planar slope correction factor 

N = number of sample points 

I = length of sampling plane. 

The slope correction factor is 

When n, d2, and c are totaled saparately for a stand, a 

bias that is probably small could result. Summing (n) (c) 

or d2 (c) over all plots would eliminate the biases. 

Litter and Herbaceous Vegetation 

Litter loading is calculated as: 

N 

i'i = 24.78 Z ciwi(l + P2 + P, + P,),IN (7) 

i = 1 

where: 

c = topographic slope correction 

w = weight on standard plot, grams 

P = fraction of weight on standard plot for individual 

subplots 

i = index for sample points. 

Herbaceous vegetation loading is calculated as: 

N 

ii = 12.39 t ciwi(l + P2 + P, + P,),IN (8) 

i=l 

To calculate the amount of dead herbaceous 

vegetation, the fraction of weight on the standard plot is 

multiplied by the fraction dead: 

N 

= 12.39 1 ciwi(D, + P2D2 + P,D, + P,D,),IN (9) 

i = 1 

where: 

D = fraction of dead on individual subplots. 

Use the midpoints of the established percentage 

classes for fractions in the calculations. 

The slope correction may be handled differently 

depending on the amount of slope and its variability. If 

slope is less than about 40 percent, the correction is 8 

percent and, for practical purposes, could be ignored. 

If the slope in a stand is steep and uniform, the slope 

correction factor can be multiplied times the average 

stand loading rather than times the loading at each 

sample point. This also applies to calculation of shrub 

loadings. 

Shrubs 

Shrub loading is calculated by summing the weights of 

individual stems by species: 

N,2,7 

w = 8.8185 t c~(s~w~)~~/(~N) [I O) 

ijk 

where: 

s = number of stems per basal diameter class 

w = weight per stem of foliage and wood by basal 

diameter class (table 3), grams 

j = index for shrub subplots 

k = index for basal diameter classes. 

Dead shrub weight is calculated by multiplying the fraction dead on each subplot by estimated weight per subplot. Thus, 

w,7 

Gj = 8.8185 t c~D~~(s,w,)~~/(~N) (11) 

ijk 

where: 

D = fraction of dead shrubs per subplot. 

Weight per stem is summarized in table 3 based on 

data by Brown (1976). Brown also presents relationships 

for estimating foliage and stemwood separately. 

Duff 

Duff loading is calculated as: 

GV = 3,630 Bd 

where: 

B = bulk density, lblft3 

d = average duff depth for a stand, inches. 

Bulk densities can be obtained from table 1, the 

condensation of table 1 in the text, or from other sources. 

Small Trees 

Small tree loadings can be computed by summing the 

weights of individual sample trees. The simplest approach 

is to first construct a table showing the total number of 

sample trees per stand by species and l-ft height increments. Loading for each species can then be calculated 

by: 
10 

ii = 300 NhwhlN (1 3) 

i = 1 

where: 

N, = total number sampled trees by height class per 

stand 

W, = weight per tree by height class, pounds 

i = index for height classes. 

Weights per tree as determined by Brown (1978) are 

summarized in table 4. The 300 in equation (13) expands 

11300-acre plot estimates to a per-acre basis. If other plot 

sizes are used, the 300 should be replaced with appropriate expansion factors. 

The procedures in this publication permit estimation of 

total biomass and fuel loading of forest floor and understory vegetation. The estimates are appropriate for 

intensive land management and studies involving biomass 

and forest fuels. 

Table 3.-Total aboveground weight of shrubs by basal diameter classes 

Species 

-- pp 

Stem basal diameters (cm) 

0 -0.5 0.5-1 .O 1.0-1.5 1.5-2.0 2-3 3-5 5-6 

Low shrubs 

Snowberry 

Blue huckleberry 

Grouse whortleberry 

Wild rose 

Gooseberry 

White spirea 

Oregon grape 

Thimbleberry 

Red raspberry 

Combined species 

Medium shrubs 

Ninebark 

Smooth menziesia 

Utah honeysuckle 

Oceanspray 

Evergreen ceanothus 

Mock orange 

Russet buffaloberry 

Big sagebrush 

Common juniper 

Combined species 

High shrubs 

Serviceberry 

Mountain maple 

Mountain ash 

Mountain alder 

Redosier dogwood 

Willow 

Chokecherry 

Combined species 
Table 4.-Weight per tree of aboveground foliage, bark, and wood by 1-ft tree height increments 

Height 

Species 1 2 3 4 5 6 7 8 9 10 
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field data on fuel depths. USDA For. Sew. Gen. Tech. 

Rep. INT-23, 25 p. Intermt. For. and Range Exp. Stn., 

Ogden, Utah. 

Albini, Frank A. 1976. Computer-based models of wildland 

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Intermt. For. and Range Exp. Stn., Ogden, Utah. 

Aldrich, David F., and Robert W. Mutch. 1972. Wilderness 

fires allowed to burn more naturally. U.S. Dep. Agric. 

Fire Control Notes 33(1):3-5. 

Avery, T. Eugene. 1967. Forest measurements. p. 121-143. 

McGraw-Hill, New York. 

Bentley, J. R., D. W. Seegrist, and D. A. Blakeman. 1970. 

A technique for sampling low shrub vegetation by 

crown volume classes. USDA For. Sew. Res. Note 

PSW-215, 11 p. Pac. Southwest For. and Range Exp. 

Stn., Berkeley, Calif. 

Brown, James K. 1966. Forest floor fuels in red and jack 

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Cent. For. Exp. Stn., St. Paul, Minn. 

Brown, James K. 1970. Physical fuel properties of ponderosa pine forest floors and cheatgrass. USDA For. 

Serv. Res. Pap. INT-74, 16 p. Intermt. For. and Range 

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Brown, James K. 1974a. Reducing fire potential in lodgepole pine by increasing timber utilization. USDA For. 

Sew. Res. Note INT-181, 6 p. Intermt. For. and Range 

Exp. Stn., Ogden, Utah. 

Brown, James K. 1974b. Handbook for inventorying 

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Ogden, Utah. 

Brown, James K. 1976. Estimating shrub biomass from 

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Brown, James K. 1978. Weight and density of crowns of 

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Brown, James K. 1981. Bulk densities of nonuniform 

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Brown, James K., and Peter J. Roussopoulos. 1974. Eliminating biases in the planar intersect method for estimating volumes of small fuels. For. Sci. 20(4):350-356. 

Brown, James K., and Thomas See. 1981. Downed dead 

woody fuel and biomass in the northern Rocky 

Mountains. USDA For. Serv. Gen. Tech. Rep. INT-117, 

48 p. Intermt. For. and Range Exp. Stn., Ogden, Utah. 

Buckman, R. E. 1966. Estimation of cubic volume of 

shrubs (Corylus spp.). Ecology 47:858-860. 

Deeming, John E., Robert E. Burgan, and Jack D. Cohen. 

1977. The National Fire-Danger Rating System-1 978. 

USDA For. Serv. Gen. Tech. Rep. INT-39, 63 p. Intermt. 

For. and Range Exp. Stn., Ogden, Utah. 

Dieterich, J. H. 1963. Litter fuels in red pine plantations. 

USDA For. Sew. Res. Note LS-14, 3 p. 

Ffolliott, Peter F., Warren P. Clary, and James R. Davis. 

1968. Some characteristics of the forest floor under 

ponderosa pine in Arizona. USDA For. Sew. Res. Note 

RM-127, 4 p. Rocky Mt. For. and Range Exp. Stn., Fort 

Collins, Colo. 

Fosberg, M. A. 1970. Drying rates of heartwood below 

fiber saturation. For. Sci. 16:57-63. 

Francis, R. C., G. M. Van Dyne, and B. K. Williams. 1979. 

An evaluation of weight estimation double sampling as 

a method of botanical analysis. J. Environ. Manage. 

8:55-72. 

Habeck, James R., and Robert W. Mutch. 1973. Firedependent forests in the northern Rocky Mountains. 

Quat. Res. 3:408-424. 

Hughes, Ralph H. 1959. The weight-estimate method in 

herbage production determination. In Techniques and 

Methods of Measuring Understory Vegetation, Proc. p. 

17-19. For. Serv., South. and Southeast. For. Exp. Stns. 

Hutchings, Selar S., and Jack E. Schmautz. 1969. A field 

test of the relative-weig ht estimate method for 

determining herbage production. J. Range Manage. 

22(6):408-411. 

Ludwig, John A., James F. Reynolds, and Paul D. 

Whitson. 1975. Size-biomass relationships of several 

Chichuahuan Desert shrubs. Am. Midland Nat. 

94(2):451-461. 

Lyon, L. Jack. 1970. Length- and weight-diameter relations 

of sewiceberry twigs. J. Wildl. Manage. 34:456-460. 

Mader, Donald L. 1953. Physical and chemical characteristics of the major types of forest humus found in the 

United States and Canada. Soil Sci. Soc. Proc. (1953), p. 

155-1 58. 

Mader, Donald L., and Howard W. Lull. 1968. Depth, 

weight, and water storage of the forest floor in white 

pine stands in Massachusetts. USDA For. Sew. Res. 

Pap. NE-109, 35 p. Northeast. For. Exp. Stn., Broomall, 

Pa. 

Pasto, J. K., J. R. Allison, and J. B. Washko. 1957. 

Ground cover and height of sward as a means of 

estimating pasture production. Agron. J. 49:407-409. 

Pfister, Robert D., Bernard L. Kovalchik, Stephen F. Arno, 

and others. 1977. Forest habitat types of Montana. 

USDA For. Sew. Gen. Tech. Rep. INT-34, 174 p. Intermt. 

For. and Range Exp. Stn., Ogden, Utah. 

Puckett, John V., Cameron M. Johnston, Frank A. Albini, 

and others. 1979. User's guide to debris prediction and 

hazard appraisal. USDA For. Serv., Northern Region, 

Missoula, Mont. 

Reppert, J. N., M. J. Morris, and C. A. Graham. 1962. 

Estimation of herbage on California annual-type range. 

J. Range. Manage. 15:318-323. 

Rittenhouse, L. R., and F. A. Sneva. 1977. A technique 

for estimating big sagebrush production. J. Range. 

Manage. 30(1):60-68. 

Rothermel, Richard C. 1972. A mathematical model for 

predicting fire spread in wildland fuels. USDA For. Sew. 

Res. Pap. INT-115, 40 p. Intermt. For. and Range Exp. 

Stn., Ogden, Utah. 

Sackett, Stephen S. 1979. Natural fuel loadings in ponderosa pine and mixed conifer forests of the 

Southwest. USDA For. Sew. Res. Pap. RM-213, 10 p. 

Rocky Mt. For. and Range Exp. Stn., Fort Collins, Colo. 
Telfer, E. S. 1969. Weight-diameter relationships for 22 

woody plant species. Can. J. Bot. 47:1851-1855. 

U.S. Department of Agriculture, Forest Service. 1974. 

Wood handbook: wood as an engineering material. U.S. 

Dep. Agric. Handb. 72, rev. U.S. Gov. Print. Off., 

Washington, D.C. 

Van Wagner, C. E. 1968. The line intersect method in 

forest fuel sampling. For. Sci. 14(1):20-26. 

Whittaker, R. H. 1965. Branch dimensions and estimation 

of branch production. Ecology 46:365-370. 

Williams, Carroll B., and C. T. Dyrness. 1967. Some 

characteristics of forest floors and soils under true firhemlock stands in the Cascade Range. USDA For. Serv. 

Res. Pap. PNW-37, 19 p. Pac. Northwest For. and Range 

Exp. Stn., Portland, Oreg. 

Wooldridge, David D. 1968. Chemical and physical properties of forest litter layers in central Washingtqn. In Tree 

Growth and Forest Soils, Proc. Third North Am. For. 

Soils Conf. [N.C. State Univ., Aug. 19681. p. 327-337. 
APPENDIX I 

APPLICABILITY OF TECHNIQUES 

Some techniques can be applied more widely than 

others without any known loss of accuracy. Limitations in 

applying the techniques can be inferred from knowing the 

sources of data underlying their development. Applicability of the techniques is as follows: 

1. Downed woody material - Average diameters of size 

classes less than 3 inches (7.6 cm) are based on an 

average of major western tree species. The estimates of 

this material are robust and should be reasonably accurate in coniferous forests. More precision can be obtained 

using the procedures in Brown (1974b). No limitations are 

built into the technique for material greater than 3 inches 

(7.6 cm) in diameter. 

2. Litter and herbaceous vegetation - The relative 

estimate technique has no geographic restrictions. 

3. Duff - Estimates of depth apply without geographic 

limitations. However, the duff bulk densities used to 

determine loading are based on a small amount of data 

from western coniferous forests. Although the loading 

estimates are probably applicable throughout coniferous 

forests in the United States and perhaps elsewhere, they 

should be viewed as crude approximations. 

4. Shrubs - Biomass estimates are based on data from 

shrubs in western Montana and northern Idaho. The 

weight relationships for low, medium, and high shrubs 

may be used to estimate biomass of any species. 

Accuracy of these relationships outside of the Northern 

Rocky Mountains is unknown. 

5. Small trees - Estimates of biomass for trees less 

than 10 ft (3 m) in height are based on data from western 

Montana and northern Idaho for Engelmann spruce, 

western hemlock, western white pine, whitebark pine, 

ponderosa pine, lodgepole pine, grand fir, western 

redcedar, western larch, Douglas-f ir, and subalpine fir 

(Brown 1978). Equating a species not listed to one of the 

above may provide reasonable estimates of biomass; 

however, accuracy of this substitution is unknown. 

APPENDIX II 

SAMPLING PROCEDURES 

Use of these procedures in the Selway-Bitterroot 

Wilderness (Habeck and Mutch 1973) provided a basis for 

determining desirable sampling intensities as shown by 

the coefficients of variation in table 5. Number of sample 

points can be calculated for any chosen percent error 

(Avery 1967) from: 

where: 

cv = (standard deviationlmean) 100 

Percent error = (standard error of mean1mean)lOO. 

Figure 14 shows sampling intensities for herbs and fine 

fuels, cv = 80; litter, cv = 100; and shrubs, cv = 140. 

Fine fuels consist of litter, herbs, and 0- to %-inch (0- to 

0.6-cm) downed woody material. The sampling intensities 

for fines agree with those in Brown (1974b) for 0- to 1-inch 

(0- to 2.5-cm) downed woody material. Generally, for a 

given level of precision, estimates for combined vegetative categories require fewer sample points than for individual vegetative categories. 

A scattergram of mean estimates and percent errors 

showed a lack of correlation. Thus, figure 14 should apply 

to loadings ranging from light to heavy. Cover types 

appeared to slightly influence coefficients of variation 

(table 5). For example, for a given percent error, fewer 

sample points are required to estimate litter in ponderosa 

pine and Douglas-fir than in the grand fir and spruce-fir 

types. This seems reasonable because litter is more uniform in ponderosa pine and Douglas-fir stands. For the 

most part, however, differences among cover types in 

table 5 provided little guidance on sampling intensities. 

Advance knowledge about the uniformity of fuels should 

be more useful in deciding upon sampling intensities than 

cover type. 

Coefficients of variation for shrubs varied considerably 

from stand to stand. High coefficients of variation were 

due to occasional plots falling in clumps of large-sized 

shrubs. The number of plots required to achieve a given 

percent error might easily be twofold to fourfold more or 

less than suggested in figure 14. 

Table 5.-Average coefficients of variation from stands sampled with 10 sample points in the Selway-Bitterrott Wilderness 

Herbaceous Number of 

Cover type Litter vegetation Fines Shrubs Duff stands 

Ponderosa pine 93 79 73 116 104 12 

Douglas-fir 91 86 72 137 79 19 

Grand fir 131 75 74 160 74 19 

Engelmann sprucesubalpine fir 122 8 1 102 168 96 13 

Average 109 80 80 145 88 - 
l---=- - SHRUBS 

LITTER --- HERBS, FINES 

PERCENT ERROR 

Figure 14.-Number of sample points 

related to percentage of error based on data 

from the Selway-Bitterroot Wilderness, 

Idaho. 

Quantity of downed woody material larger than 3 

inches (7.6 cm) in diameter can vary considerably with 

stands. As number of pieces per acre increases, 

variability among sample points tends to decrease and 

sampling effort can be reduced to achieve a given sampling precision. For large diameter pieces, the sampling 

plane should be long enough so that on the average, at 

least one intersection occurs with three-fourths or more of 

the planes. A large sampling variance results when many 

zeros are recorded for intersections. In areas where very 

little downed material exists, sampling planes should 

actually be one to several hundred feet long to provide 

respectable precision. As an average for coniferous cover 

types, use of 35- to 50-ft (10.8- to 15.2-m) sampling planes 

should require sampling intensities similar to litter 

(fig. 14). 

APPENDIX Ill 

COMPUTER INSTRUCTIONS 

This appendix explains how to set up and operate a 

computer program for calculating results from the inventory data. It includes a listing of the computer program 

and instructions for punching and verifying data. 

ADP Program Writeup 

Description 

SYSTEM 

PROGRAM 

LANGUAGE 

MACHINE 

USAGE 

STAND BIOMASS 

FUELS 

ASCII FORTRAN V 

PERKIN ELMER 3200 

BATCH 

Purpose 

This program performs calculations of the sampling 

results shown in figure 13. The program produces weight 

in pounds per acre and kilograms per square meter of 

forest floor duff, forest floor litter, herbaceous vegetation, 

shrubs, small conifers, and downed woody material. Also, 

estimates for live and dead vegetation by diameter size 

classes are furnished. This information has application in 

research investigations and intensive forest management. 

Input 

The program accepts data from the inventory form in 

figure 4. The input data must follow the sequence of the 

data form. The record order of Card 1 through Card 6 for 

each plot is required. The data must be on an input 

medium which will allow REWIND, i.e., a magnetic tape or 

disk file. The present program reads the parameter card 

from the card reader designated LU 60. The input data file 

is read from LU 5. 

The first parameter card is a title card for the run. The 

second parameter card defines one of the three output 

options available. The options are: 

1. Individual stands 

2. Sorted by cover type 

3. Sorted by habitat type. 

All the acceptable cover type, habitat type, tree and 

shrub species codes are found in the text. 

Output 

The program will produce two pages of output (fig. 13) 

for each stand of input. Also, two pages of output will be 

produced for each cover type or habitat type. 

Method 

The program contains a set of constants tied to the 

sampling techniques described in the text: XLOAD, 

ZLOAD, YLOAD(l), YLOAD(2). They convert all units to 

tons per acre and also account for the nonhorizontal 

particle correction, particle density, and the 218 portion 

of the planar intersect formula. YLlT and YGFS convert 

the plot weights to the proper weight units. If any variation of the sampling technique is used, these constants 

will require recalculation. 

Runstream 

As stated earlier, the inventory data must be a file on 

disk, tape, or other medium that allows REWIND. The 

parameter cards are read from the card reader. The 

formats are: 

CARD 1 TITLE CARD 

cc Description 

1-60 Free field to identify run 

CARD 2 TYPE OF RUM 

cc Description 

1-19 Sort desired on date, legal options are: 

CC 

1 5 10 15 

STAND SEPARATELY 

COVER TYPE 

HABITAT TYPE 
FUNCTION * PROGRAM I NAME 

D- DUPLICATE S- SKIP V- VERIFY NUMBER PROGRAM DATE 

P- PUNCH 1 

L-LEFTJUSTIFY EYEPARED 6 

of - 

CARD FIELD COLUMNS NO. FUNC. 

'FROM ( TO COLS. * REMARKS r 

STAND NO. 1 44P 

PLOT NO. 5 8 4 P 

TERRAIN SLOPE 9102P 

ASPECT 11 13 3 P 

ELEVATION 14 17 4 P 

STAND AGE 18 20 3 P 

COVER TYPE 21 23 3 L ALPHA 

HABITAT TYPE 24 26 3 P 

PLANER SLOPE 27 28 2 P 

TRANSECT LENGTH (0-1 ) 29 30 2 P 

TRANSECT LENGTH (1 -3) 31 33 3 P 

NO INTERSECTS 0-1/4 in. 34 36 3 P 

NO INTERSECTS 1/4-1 in. 37 38 2 P 

NO INTERSECTS 1-3 in. 39 40 , 2 P 

TRANSECT LENGTH >3 in. 41 43 3 P 

DIA. >3 in. SOUND 44 73 30 P 10 3-DIGIT NOS. r 

SKIP 74 79 6 

CARD NO. 80 PUNCH "1" 

.A 
CARD PUNCHING AND VERIFYING INSTRUCTIONS L 

FUNCTION * PROGRAM 

NAME 

L 

D- DUPLICATE S- SKIP V- VERIFY PROGRAM 

NUMBER 

'P,R,EPARED 

DATE 

I 

P- PUNCH PAG LO^ E 6 

CARD FIELD 

STAND NO. 

PLOT NO. 

DIA. >3 in. ROTTEN 

DUFF DEPTH 

HERBS % STANDARD I 

HERBS % DEAD 

HERBS COVER 

HERB BASE WEIGHT 

LITTER % STANDARD 

LITTER BASE WEIGHT 

SHRUBS % COVER I 

SHRUBS % DEAD I 

SHRUBS AVERAGE HEIGHT 

SKIP 

CARD NO. 

I 

L 

REWRKS 

103-digitnos. 

23-digitnos. 

41-digitnos. 

41-digitnos. 

21-digitnos. 

41-digitnos. 

21-digitnos. 

21-digitnos. 

23-digitnos. 

PUNCH "2" 

JUSTIFY 

NO. 

COLS. 

44D 

84D 

30 

6 

4 

4 

2 

5 

4 

5 

2 

2 

6 

FUNC. * 

P 

P 

P 

P 

P 

P 

P 

P 

P 

P 

P 

L-LEFT 

COLUMNS 

FROM 

1 

5 

& 

9 

39 

45 

49 

53 

55 

60 

64 

69 

71 

73 

79 

TO 

38 

44 

48 

52 

54 

59 

63 

68 

70 

72 

78 

80 
CARD PUNCHING AND VERIFYING INSTRUCTIONS 

FUNCTION * PROGRAM 1 NAME 

D- DUPLICATE S- SKIP V- VERI 

P- PUNCH L- LEFT - 

CARD FIELD COLUMNS 

FROMI TO 

STAND NO. 111 4 

PLOT NO. 5 8 

SUB-PLOT 9 

SPECIES I 10 1 13 

NO STEMS 0-0: 5 1 14 1 16 

NO STEMS 0.5-5+ 117 128 

SPECIES 

NO. STEMS 0-0.5 

NO. STEMS 0.5-5+ 137 1 48 

SUB-PLOT 

I PROGRAM 

NUMBER 

I DATE 

b 

U ST I FY PREPARED PAGE 

BY 30f 6 

COLS. No IFU*NC.I REMARKS 

1 P If no stems recorded do not 

h ~~PCP4 L ALPHA 

12 1 P ( 6 2-digit nos. 

4 L ALPHA 

4 L ALPHA 

NO. STEMS 0-0.5 54 56 3 P 

NO. STEMS 0.5-5+ 57 68 12 P 6 2-digit nos. 

SKIP 69 79 11 I 

CARD NO. 80 PUNCH "3" 

I 

, 

1 
CARD PUNCHING AND VERIFYING INSTRUCTIONS 

FUNCTION * PROGRAM I NAME t 

D- DUPLICATE S- SKIP V- VERIFY PROGRAM DATE 

NUMBER I 

P- PUNCH L-LEFTJUSTIFY REPARED PAGE 40f 6 

CARD FIELD COLUMNS NO. FUNC. 

'FROMI TO ' COLS. * REMARKS 1 

I STAND NO. 1 4 4 D 

PLOT NO. 5 84D 

SUB-PLOT 9 1 P 

SPECIES 10 13 4 L ALPHA I 

NO STEMS 0-0.5 14 16 3 P I 

NO STEMS 0.5-5+ 17 28 12 P 62-digitnos. 

SUB- PLOT 29 1 P 

SPEC1 ES 30 33 4 L ALPHA 

NO STEMS 0-0.5 34 36 3 P 

NO STEMS 0.5-5+ 37 48 12 P 62-digitnos. 

SUB-PLOT 49 1 P L 

SPECIES 50 53 4 L ALPHA 

NO STEMS 0-0.5 54 56 3 P 

NO STEMS 0.5-5+ 57 68 12 P 62-digitnos. 

SKIP 69 79 11 . 

CARD NO. 80 1 PUNCH "4" 

I 

/ 
I CARD PUNCHING AND VERIFYING INSTRUCTIONS 

FUNCTION * PROGRAM 

NAME 

D- DUPLICATE S- SKIP V- VERIFY PROGRAM 

NUMBER 

ZRyEPARED 

DATE 

PAGE LO^ ~i P- PUNCH 

CARD FIELD 

STAND NO. 

PLOT NO. 

SUB-PLOT 

SPEC1 ES 

NO. STEMS 0-0.5 

NO. STEMS 0.5-5+ 

SUB- PLOT 

SPECIES 

NO. STEMS 0-0.5 

NO. STEMS 0.5-5+ 

SUB-PLOT 

SPECIES 

NO. STEMS 0-0.5 

NO. STEMS 0.5-9 

SKIP 

CARD NO. 

REMARKS 

ALPHA 

6 2-digit nos. 

ALPHA 

6 2-digit nos. 

ALPHA 

62-digitnos. 

PUNCH "5" 

NO. 

COLS. 

44D 

4 

1 

4 

3 

12 

1 

4 

3 

12 

1 

4 

3 

12 

11 

1 

FUNC. * 

D 

P 

L 

P 

P 

P 

L 

P 

P 

P 

L 

P 

P 

L-LEFTJUSTIFY 

COLUMNS 

'FROMI 

1 

5 

10 

14 

17 

30 

34 

37 

50 

54 

57 

69 

TO 

8 

9 

13 

16 

28 

29 

33 

36 

48 

49 

53 

56 

68 

79 

80 
I CARD PUNCHING AND VERIFYING INSTRUCTIONS 

D- DUPLICATE S- SKIP V- VERIFY NUMBER PROGRAM 

P- PUNCH L- LEFT JUST l FY of L -- 

CARD FIELD 1 COLU,MNS NOFROM TO COLS. 

TAND NO. 1 

PLOT NO. 

SUB-PLOT 9 1 P 

1 SPECIES I 10 13 4 L ALPHA 

I NO. STEMS 0-0.5 1 14 

1 NO. STEMS 0.5-5+ 28 1 12 1 P 1 6 2-digit nos. 

I TREE COUNT SPECIES 1 29 30 2 L ALPHA -- 

I I NO. 31 

I I HT . 33 

I I I SPECIES 1 35 36 1 2 1 L I ALPHA 

38 2 P 

40 2 P 

42 2 L ALPHA 

44 2 P 

46 2 P 

48 2 L ALPHA 

50 2 P 

I I NO. 

I I HT. 

I I I SPEC I ES 1 41 

I I NO. 

I I SPECIES 47 

I I NO. 49 

I I SPECIES 

I I NO. 

I SKIP 

CARD NO. 80 1 PUNCH "6" 
C***********~*******************9************************************ 

C 

C INPUT CATA FRO'! (INIT TIP 

C 

C CAHL! WO. 1 

C COL-UMN \iAR TAI?I E DESCRIPTION 

C 1-4 ISTY - STAPlll KlJ 

C 5-8 JPI T - PLCIT NUP3EP 

C 9-10 TRSL - TERRAIK SLnPE IN PERCFNT 

C 11-13 ASPT - ASPFCT IT\' "EGREES 

C 14-17 FLFV - ELE\IATIOt\l TN FEET 

(3 10-30 SALE - '3TAND AGF 

C 21-23 TCVT - CCIVFR TYPE 

C 24-26 ItIRT - HAPTTAT TYPF 

C 27-28 PLSL - PLANER Si OPF IN PERCERT 

C 29-3~1 TSl 1 - TRANSECT LF.UGTH 0-1 

C 31-33 TSI 3 - TRANSECT LFidGTH 1-3 

C 34-36 XNTl - PJlJ?IRER OF TNTERSECTS Q-1/4 

C 37-38 XiJT2 - &JULnR€R OF: TI?ITERSECTS 1/4-1 

C 33-40 YMT3 - N!JPqREP OF TIVTERSECTS 1-3 

C 41-43 TSI 4 - TRANSECT LFXIGTH 1+ 

C 44-73 !-JIA(T.,I 1 - QIAPIETFR 3+ qOliK8 (10 3-DIGIT f:OS* IEeI=lqlO) 

C 

C CAR11 fl10. 3 

C COL'JKN VAHIBRl E DESCRIPTXOW 

C 9-38 UIA(I13) - PIAWETFH 3+ ROTTEPI (1Q 3-DTGIT NOS. IEeT=lqlO) 

C 39-44 nO~(1) - PIIFF [IFPTH I2 3-DIGIT NOS. IE,I=lr2) 

C 45-52 TGF(I,,I) - GRASS-FOPBY COVER AS PERCERT bF STANDARD 

C T=1 4 REPL TCATIONS 

C J=l FOR ?:, qTANOARD r J=3 FOR YQ DEAD 

C 53-54 TGFC(1) - FERrCNT ?RASS-FQRR COVEP 

C I=1.2 RFPLTCATIOMS 

C 55-59 IriGFf3 a MEIGMT OF GRASS-FOPB BASE 

C 69-63 TLTS(7) - LITTER C3VFI3 AS PERCEidT OF STAKDARD 

C X=1.4 REPLICATIONS 

C 64-68 MLTH - WEIGHT OF ! TTTEP BASE 

C 69-72 IRC ( I, ,I 1 - PEHCEI'JT '3Rl 1st-4 COVER 

C I=102 RFPL ICATIOPIS 

C J=l FOR TOTAL COVER r J=2 FOR DEAD 

C 73-7R ABRY(1I -PVERAGE PH(1St-l HEIGHT 

C I=l r 2 RFPL ICATIONS 

C 

c CARD No. 3 

C CAfiUS 3,405 

C COLUW VARIABLF 

c in-13 TSP(I) - BRU~H SPFCTFS FOR PLOT I 

C 14-2P r'IST(IqtI) - f\lilMAE'R OF CTENS 3Y DIAMETR CLASS J FOR PLOT I 

C Jz1.7 CLIISTFS 

C 30-33 ISP(1) 

C 34-4H NST ( I rJ I 

C 50-53 TSP(1) 

C 54-68 NST ( I ,I 

C ++++++++ THIS INPIJT DATA IS REPEATEO 10 TINES 

C I=l r 10 

C CAR0 6 

C COLLIMN \IARIARI E 
1: LTCEfdSC 1) PESTkICTEti QIGHTS AS STATEn IN LICENSE E-0156 

03/C 

**** SEE GOCUMENTAI 
: LICENSED RESTRICTED RIGHTS AS STATED IN LICENSE E-0156 

03/01 

***, SEE DOCUMENTAT' 
: LICEI\SED RESTKICTEG RIGHTS AS STATED IN LICENSE E-0156 

03/0 

***r SEE DOCUMENTAT 

CO9E(Y)=1,0 

cODE(9)=O0O 

ILAST=-9999 

C 

C *** HEAD IN THE TITLE CARD 

C 

REAIJ(IN,~O) (IHEAD(I)~I=1,15) 

10 FOt4flAT (lSA4 

C 

C *** READ IN THE CONTROL CARD 

C 

20 I2=12 

REAL)( IN930 ,ENO=l97) * (TCO~(I)~I=1~2)r(IPS(I)~ICLT(I)~I~1~I2)tIX 

30 FORllAT(2A5~9X912(AltA4)vA1) 

IF(ICON(1 IeEQe'STOP '1 CALL EXIT 

C 

r kt* IhTERPHET CONTROL CARD AND SET PARAMETERS 

PIC = 1 

PPS = 1 

IC1 = 1 

00 40 I=l*3 

IF(IICL(I).EfJ.ICON(l) 1 GO TO 45 

40 COrdTINUE 

GO TO 50 

45 KEY=I 

IF (KEYoLE.8) GO TO 90 

* CHECK FOR CONTINUATION AND READ THEM IN 

50 WRITE(IOt60) 

60 FORluiAT (///*52H************ ERROR * ERROR ***+******** 

1// ~OXI'CONTROL CARD IN ERROR - THE CORRECT COOES ARE STAND r HA 

2BITAT TYPE 9 COVER TYPE' // >OH  PROGRAM TERMINATED ** ** 1 

CALL EXIT * SET THE CONTROL KEY 

* SLOPE, ELEVATION, ASPECT* AND STAND AGE CLASSES 

* COVER TYPE AND HABITAT TYPE 

*** REWIND THE DATA TAPE 

170 REWIND IIP 

+** ZERO OUT ALL STORAGE ARRAYS 

CALL ZERO (20) 

IC=1 

IY = 0 
: LICENSED KESTRICTEO RIGHTS AS STATED IN LICENSE E-0156 

03/0L 

***q SEE DOCUMENTATI 

C 

C *** READ IN SOME DATA 

C 

180 REAU(IIPq190tENC)=580) * 1STNtIPLTtT~SLtASPT~F:LEVtSAGEtICVTtIHSTIPLSL~TSLlv 

1TSL3tXNI1qX~I2~YNI3tTSL4q~13IA(Itl)tI=lrlO) 

190 F~R~AT(2I4tF2~O~F3~0tF~~O~F3~UtA3~I3tF2~OtF2~ltF3~l~F3~Oq2

10t10F3.0) 

C 

C 

C *** IF THIS REAO MARKS END-OF-FILE ON ITP CALL OUTPUT 

C 

IF (TSLl*TSL3*TSLQ.GToO.O) GO TO 196 

WRITE (IOt195) ISTNtIPLTqTSLlqTSL3tTSL4 

195 FOH4AT (lHltlOX146H** ERROR ** DATA EPROR ** ERROR **q 

l//t16XqqSTAND NUMUEH qqI4c*c PLOT NUMBER 'qI4r/t18Xq'0-1 TRANSECT 

?LENGTH ='tF6olt' FT't/tlBXq'1-3 TRANSECT LENGTH ='tF69lr' FT'q/tl8 

3Xqq3+ TRANSECT LENGTH ='tF601tq FTtq/tlOXv'ALL TRAruSECT LENGTHS M 

4UST BE GREATER TWN ZERO'q//tlOXt46H********* CHECk CARD AND RESU 

5HPlIT *********I 

197 CALL EXIT 

196 IF (ASPT.GE.360.0) ASPT=ASPT-360.0 

C 

C *** PEA0 IN THE REMAINING 5 CASDS OF DATA SET 

C 

READ(IIPt200) (~IA(l~2)~I=ltlO~~(ODP(I)rI=lt2)t((IGF(I~J~~I~1~4~

1=lt2)~IGFCt~GFB~(ILTS(I~~I=lt4~tWLT@c((I~C~I~J~tI~lt2~~J~l

2H(I)~I=1~2)~(ISP(I)t~I'JST(ItJ)tJ~1~7~tI~ltlO~t~ISP~Y~I~tNST~l

lI)tI=lqL)) 

C 

200 F~RMAT(9Xq1UF3~Ot2F~~1t1OI1~F5~2t4IltF5~2t4Il~2F3~O / 

$: 8X,3(1XqA4rI3~61 

12)/8~q3(1~tA4rI3~6I2)/8Xt3(1X~A4tI3t6I2)/8X~lX~A4~I3t6I2~4(A2qI2~F 

32.1) ) 

C 

C 

C I*** SET PAHAP'IETERS RASED ON DESIRED ACTION 

C 

GO TO (210i250t260)rKEY 

C 

C * STANDS SEPEHATE 

C 

210 IF (ILASTeEQoISTN) GO TO 330 

IF (ILAST.EQo-9999) GO TO 220 

CALL OUTPUT(NCtIRN~ISPX~r\]Ai\1EtIO) 

IEN = 0 

IY = 0 

CALL ZERO (NC) 

220 ILAST=ISTN 

GO TO 330 

C 

C * COVER TYPE 

C 

250 IK=ICVT 

GO TO 270 

C 

C * HABITAT TYPE 
: LICENSEO HESTRICTEC RIGHTS AS STATED IN LICENSE E-0156 

xk=xwer 

UQ 2eo I=IC1,12 

IF (IKoEQoICLT(I)) 60 TO 290 

CCr\lTINtJE 

IF (ICloGTol.ORoI2oGEo144) GO TO 180 

12=I2+1 

ICLT(I2)=IK 

hjPS= I2 

IF (12,GT,20) GO TO 180 

IC = I2 

NC = I2 

GO TO 330 

IC=I-IClt1 

IF (ICoGTO20) GO TO 180 

CALCULATE PLANER AND TERRAIN SLOPE CONSTANTS 

CALCULATE THE LOAD IN POUNDS/ACHE FOR ALL SIZE CLASSES 

FIRST SET MULTIPLICATION CONFTANTS BASED ON COVER TYPE 

DO 333 IJJ=lq19 

JF(ISPX(1JJ)oEBoICVT) GO TO 336 

CO~\JTIF\IUE 

IJJ = 26 

CALL LOOK(IJJqAlrA2qA3) 

LOAC CASE 2: 1/4-1 

LCAU CASE 6: 1-3 

LOAD CASE 9-12: 3+ SOUND RY SIZE CLASS 

LCAU CASE 14-17: 3+ ROTTEN RY SIZE CLASS 

03/0 

***q SEE DOCUMENTAT 
LICENSED RESTRICTED RIGHTS AS STATED IN LICENSE E-0156 

LOAD CASE 13: 3+ SOUND TOTAL 

LOAD CASE 18: 3+ ROTTEN TOT4L 

K = K+1 

X(K) = XX 

CONTINUE 

IF(WLTB.EQ.O.O) GO TO 380 

XX=O Q 

00 370 I=1,4 

J=ILTS ( I) 

IF (JoLE.0) J=9 

XX=XX+COOE(J) 

CONTINUE 

X(3)=YLIT*ACRE*dLTB*XX*TSLP/4.0 

XNLT(IC)=XNLT(IC)+l.O 

GO TO 390 

X(3)=0.0 

LOAD CASE 4: DEAD GRASS-FORBS 

LOAD CASE 22: LIVE GRASS-FORDS 

)IX = 0.0 

XY = 0.0 

YY = 0.0 

YX = 0.0 

IF (WGFBoEQ.0.O) GO TO q10 

DO 400 I=1,4 

J=IGF(Iql) 

K=IGF(It2) 

IF (J.LE.0) J=9 

IF (K.LE.0) K=9 

YY=YY+CODE(K) 

YX=YX+CUDE(J) 

CON=C03E(J)*CODE(K) 

XX=XX+COBE (J) -CON 

XY=XY+CON 

CONTINUE 

X(22)=YGFS*ACRE*WGFB*XX*TSLP/4mO 

X(4)=YGFS*ACRE*WGFB*XY*TSLP/LC.O 

XNGF(IC)=xNGF(IC)+l,O 

GO TO 420 

X(4)=0.U 

K(22) = 0.0 

LOAD CASE 19: DUFF 

COW = 10.0 

IF(ICVTmEQa3HPP CON = 5.0 

IF(ICVTeEQe3HLP .ORaICVT.EQ.3HDF 1 CON = 8.0 

CEPDF=(CDp(l)+DDP(2))/2,0 

X(lS)=CON*DEPDF*ACRE/GRAM 

X(5) = X(l)+X(2)+X(3)+X(4) 

X(7) = X(5) + X(6) 

03/04/ 

***c SEE DOCUMENTATIO 
: I,ICEh:SED RESTRICTED RIGHTS AS STATE@ IN LICENSE E-0156 

IF(ARHh(l),GT,O) IBN = IBN + 1 

IF(ARRH(2)mGT,O) IeN = IRW + 1 

TIEP(2tIC) = OEP(2tIC) + (ARRH(1) + ABRH(2)) 

DEP2(2tIC)=DEp2(2tIC)+ABRH(l)*ABRH(l)+ABRH(2)*ABRH(2) 

LO 460 I=192 

IF (DMX(291C),LToABHH(I)) DMX(29IC)=ABRF(I) 

IF (dVN(291C).GTmARSH(I)) DMN(2tIC)=ABRb(I) 

460 CONTINUE 

C * PERCEbJT CASE 192: TOTALIDEAD BRUSH COVER 

00 470 I=lt2 

J=IRC(lrI) 

K=IHC(2rI) 

IF (JmEb.0) J=9 

IF (XmEGmO) K=9 

PD=(CbDE(J)+COUE(K))/2,0 

FCV(IIIC)=PCV(IIIC)+PD 

470 CON7 INUE 

C 

C * PERCEPIIT CASE 394: TOTALIBEAD GASS-FOHBS 

IF(IGFC(l)mEW,O) IGFC(1) = 9 

IF(IGFC(?)eEQ,O) IGFC(2) = 9 

COUEX = (CODE(IGFC(1)) + COOE(IGFC(2)))/ 2.0 

PCV(3tIC) = PCV(3tIC) + YX*COUEX/YoO 

PCV(4tIC)=PCV(4tIC)+YY/4m0 

C *** CALCULATE BRUSH LOADINGS BY SIZE CLASS AND SPECIES 

TOTHW=O,O 

DO 520 I=ltlO 

C * CHECK AND COMBINE SIMILAR SPECIES 

IF (ISF(I),EGo'tH GO TO 520 

IF (ISP(I),EQoQHVAME) ISP(II=NSP(19) 

DO Q00 K=l t2P 

IF (ISP(I),EQoNSP(K)) GO TO 500 

480 COOjTIhUE 

IY = IY + 1. 

ICUNl(IY) = IsP(I) 

GO TO 520 

C * SPECIES IS UNIDENTIFIED, CHECK FOR SMALL OR LARGE STEM 

C 4 CALCULATE SHRUB YEIGHT 

500 KK = K 

DO 510 J=1t7 

IF (NST(1tJ)mEQ.O) GO TO 510 

XX = fiEG(JtK) * FLOAT(I~ST(I~J))* 8.8185 

IF (XXmGTo0,O) XX=XX*TSLP 

ShWT(J*KKtIC)=SHWT(JtKKtIC)+XX 

IF (XXmLE,OoO) GO TO 510 

TOTRW=TQTBW+XX 

510 CONTINUE 

520 CONTINUE 

C * LOAC CASE 20: DEAD BRUSH 

03/0& 

***r SEE DOCUMENTATI 
: LICENSED RESTRICTED RIGHTS AS STATED IN LICENSE E-0156 

X(20)=TOTUd*PD 

C * LOAD CASE 23: LIVE 4RUSt-i 

X (23 )=Tr)TDW-X (20 

C * LOAG CASE 21: TOTAL DEAD FUEL 

X(B) = >(I31 + X(18) 

X(21) = X(7) + X(8) + XU91 + x(20)/2,0 

X(24) = 0,O 

X(25) = Q,fl 

X(26) = 0,O 

DO 540 1=1,19 

00 540 J=l,Y 

IF(ISYY(J)mNE,ISPX(I)) GO TO 540 

SDLH(IIIC) = SDLH(1,IC) + YSP(J) 

XCLH(I~IC)=XDLH(IIIC)+~,O 

P!SDL(ItIC)=NSOL(I,IC)+NSTM(J) 

CALL SEED[-(ItHSP(JIrNSTM(J1 1 

540 CONTINUL 

X(27)=X(24)+X(25)+X(26) 

C * LOAD CASE 28: TOTAL FUEL LOAD 

X(2@)=X(21)+X(22)+Y(23)/2.o+Y(27) 

C *** SUM THE LQA3INGS BY SIZE CLASS 

DO 530 1=1,2e 

XX=X (I 

XL~~S(ItIC)=XLDS(ItIC)+XX 

XL02(I,IC)=XLD2(I~IC)+XX*xx 

530 CGNTIhUE 

C *** ASPECT SLOPE AND ELEVATION 

PO 550 IZ1.3 

TCOA(I,IC)=TCOA(I~IC)+TCOX(T) 

IF (IeGEo3) GO TO 550 

TC02(I~IC)=TC02(ItIC)+TCOI(I)*TCOI(I) 

IF (TCO~I(IIIC)~GT~TCOI(I)) TCON(IIIC)=TCOI(I) 

IF (TCOX(IqIC)eLTmTCOI(I)) TCOX(I,IC)=TCOI(I) 

550 CONTINUE 

C * UPDATE THE COUNTER 

XN(IC)=XN(IC)+lmO 

GO TO 180 

C *** OK SPIT OUT ALL THAT GARRAGE 

580 CALL OUTPUT(NC~IBNIISPXI~\IANE~IO) 

IBN = 0 

EbU FILE. I0 

IF(YEYeEBml) GO TO 20 

ICl=IC1+2r, 

IF (IC1.GTeNPS) GO TO 20 

12=IC1+19 

IF (12.GT.NPS) 12=NPS 

NC=I2-IC1+1 

GO TO 170 

END 

03/01 

***r SEE DOCUMENTAT: 

7C 804-00 R.4IhlPHOG ,MAIN 03/04/82 15:27:44 TABLE SPACE: 11 KB 

FFER: 20 LINES/1321 EYTES STACK SPACE: 209 hORDS 

SIOM FLOATING PT SUPPORT REQUIRED FOR EXECUTION 
: LICERSEU HESTHICTEO RIGtATS AS STATED IN LICENSE E-0156 

03/0 

***r SEE DOCUMENTAT 

SURROUTINE OUTPUT (NC r IHNr IbPXr NAFIEr I0 1 

CtiAGACTER NAME (2 128 1 *fir ICON*S 

~'JIYENSION ITO(~t2s)rISPX(19) 

COMYON /HED/ IHEAD(15)rICLT(144)rICO~J(2)rILASTrKEYrXINCrNPSrICl~ 

1TPS(144)~TCVTtIHHTrSAGEtTOU~11(1OO~r1Y 

COMYON ~L~~S(28r20)rXLL~2(28r2O)rUEP(12~2O)rPCV(4r2O)rXNDP(8r2O)rX( 

*2b 

lrADIA(2r2@)rXN~(2r2O)rDEP2(2r2O)rSHWT(7~28r2O)rXN(2O)rD~X(2r2O)r 

2Xf~LT(20)r~NGF(20)rOMN(2r2O)rNSDL(19r20)rSCLH(l9r2O)rXDLH(~9r2O)rTC 

30A(3r20)r~C0~j(2r20)~TCOX(2r2CI)rTCO2(2r2O)rSTCA(2r2O)rSTCN(2r2O)~ST 

YCX(2r2I?)r~~C2(2r20) 

PATA ITO/4H c4H O-,r4H25 r4H t 

*4H r4H 02594H-1 r4H r 4H r4H LITr4HTER r4H 9 

*4HDEAlJr4H HERt4HBS r4H r 4H t4H FINrqHES tYH t 

*4H r4H 1-314H 4H r4H LEr4YSS Tt4HHAN rYH3 r 

*4H3+ r4HTOTAtQHL r4H r UH S r 4HOUhD r 4H 3-6 r 4H 9 

4 Sr4HOUhDq4Y 6-1r4HO r4H Sr4HOUhDt4H 101r4H20 t 

4 Sr4HGUNDr4h 20+t4Y r 4H3+ S r 4HOUb!D r 4H TOT r 4HAL 9 

4 Rq4HQTTEr4HN 3-r4H6 r4ti Rr4HOTTEr4HN 6mr4H10 9 

*4H Pt4HOTTEr4Hh 10r4H-20 r4ti hr4HOTTEr4HN 20r4H+ r 

*4h3+ RrQHOTTEr4HN TOr4HTAL rQHDUFFr4H r 4H r 4H r 

*$HUEAD 9 4H SHK 9 4HUB t 4H r4HDEADr4HFUELr4H LOAr4HD r 

*4HLIvE rkH HER r4HBS r4H raH Lr4HIVE r4HSHRUr4Hh 9 

*4WTRFE r 4H NEE r 4HDLES t 44 t 4H r4a 0-0t4H25 94Y t 

*ll H r4H 02594H + r4H r4HTOTAr4HL TRr4HEE r4H 9 

*4HTOTArQHL LOr4HAD r4H / 

80 450 IC=ltNC 

IF (XN(IC)oLE.OoO) GO TO 450 

XN2=XN(IC)*2,Q 

C *** PRIitJT OUT FUEL L04GIkG SUMMARY 

C * TITLE ArJU HEADING 

IhP=XN(IC) 

CALL HEAO (IC9IO) 

hhITE (IOt10) INP 

10 FOHPiAT (/r23Yr4aH********** FUEL LOADING SUPMARY ***********I93 

17Xr'(FOP'rISr' PLOTS)'r/26Xr'Itr4Xr'L0AOING IN OVEN-DRY POUNOS/ACR 

2E'SXr'I'rllXr'I' / 13XrgSIZE CLASS I AV€RAGE'rlSXr*STD-DEV %ER 

3ROR I hG/SQ-M I' 1 

WRITE (10920) 

20 FOKHAT (10Xr16('m')r'I'r40('-'~r~I~r11~'-')c'Iv~ 

DO 90 11-=lr28 

C * AVERAGE THE LOADINGS BY SIZE CLASS 

XX=XN ( IC 

IF (ILo€Q*2OoORoILoEQ,23) XX=XN2 

IF (XX~LE~QoOoORoXLOS(IL~IC~oLEoO,O) GO TO 30 

XL~s(ILrIC)=XL~S(ILIIC)/XX 

C * STANDARD DEvIATIOF! 

KF (XXoLEaloOo~RmXLDS(1L~IC)oLEoOoO) GO TO 40 

XLD2(ILrIC)=STDV(XLD2(ILrIC)rXLDS(ILrIC)rXX) 

C * PERCEhT ERROR 

X(IL)=XLD2(ILrIC)/(SQRT(XX)*XLDS(ILIIC))*lOOoO 

GO TO 50 

30 XLDS(ILrIC)=O.O 

40 XLD2(ILtIC)=O0O 

X(IL)=O.O 

50 PFSF =(XLDS(ILrIC) / 43560,0)* 408824 

IF(ILoEQo19) wRITE(IO~~O) 

38 
LICENSED RESTRICTED RIGHTS AS STATED IN LICENSE €90156 **** SEE OOCUMENTATI 

IF (IL~EQ~~O~R.ILOEQ~S.OR~XL.EQO~~,~R.IL,EG~~~ WR1TE(10120) 

IF ((ILoGTo8oAND.ILoLTo1RoAND.ILmNEo13),0R.~ILoLEo4~~OR~~~IL~G€o 

124)oANDo(IL.LEo26))) GO TO 70 

XF(ILoEQ.6) GO TO 70 

IF(IL.EQ.20) GO TO 70 

IF(ILoEQ.22) GO TO 70 

JF(IL.EQ.23) GO TO 70 

IF(ILeEQe19) GO TO 85 

C * PRINT OUT FUEL LOADING 

WRITE(I0*60) (ITO(I~IL)~I=~~~)rXL0S~IL~IC~~XLD2(ILtZC~~X~1L~~P

60 FOR~AT(~OX~~A~~~I~~F~C)~O~~~X~F~O~O~1') 

GO TO 90 

70 MRITE(IOISO) (ITO(IIIL)~I=~~~)~XLDS(TL~IC)~XLD~(ILIPC)~X(IL)~PPSF 

8P FORMAT~lOX~~A4~'I'~IOX~F1O~O~1X~F1OoOtF7l2X'I'FlO3' 1') 

GO TO 90 

85 VRITE(IOqt?6) (ITO(IIIL)~I=~~~)~XLOS(IL~IC)~PPSF 

86 FOHMAT(10X~4A4~'I'~10X~F1000~20X~'I'~F103' I' 

90 CONTINUE 

C *** AVERAGE FUEL DEPTHS 

C * AVERAGE FUEL DEPTH 

08 120 I=1,12 

XX=XN ( IC 

IF(I.EQ.2) XX = IBN 

IF (I.LTo3o0ROI.GTolO) GO TO 95 

J=I-2 

XX=XNDP(JvIC) 

95 IF (XXoLEoO.0) GO TO 110 

DEP(I~IC)=DEP(IIIC)/XX 

GO TO 120 

110 DEP(ItIC)=O.O 

120 CONTINUE 

C * STANCARQ DEVIATION 

DO 130 1~1.2 

XN3=XN2 

IF(IoEOo2) XN3ZXBN 

DEP2(IvIC) = STDV(DEP2(ItIC)*DEP(I~IC)tXN3) 

130 CONTINUE 

C * PRINT OUT FUEL DEPTHS 

WR1TE(101140) 

140 FORMAT(/~24X,42H********** DEPTH (INCHES) *********** 1 

WRITE (109150) 

WRITE (109160) (DEP(I~IC)rDMN(I~IC),DMY(I~IC~tDEP2(IIIC~~I~1~2~ 

150 FORMAT (31Xq'I AVERAGE MINIMUM MAXIMUM STD-!lEV 1@/19Xq12(*-' 

l)*'I't37('-')~'1') 

160 FORMAT(~~XI'DUFF I'r4(F802,1X)v' I' / 22XqVSHRUf3 I't4(FBe2c 

11X)' 1') 

C '" PRINT OUT TOP0 CONDITIONS 

CALL HEAD (IC,IG) 

110 200 I=1,3 

TCOA(I~IC)=TCOA(IIIC)/X~I(IC) 

IF (IeGE.3) GO TO 200 

TC02(I~IC)=STDV(TC02(I~IC~~TCOA(I~IC~~Xf\I~IC~~ 

200 COtdTXNUE 

WRITE (101210) 

210 FGHPIAT (//,22~946H********** TOPOGRAPHIC CONDITIONS **********I 
: LICENSEE' HESTHICTED RItt4TS AS STATEP IN LICENSE Em0156 **** SEE DOCUMENTAYI 

WRITE (1091501 

WRITE (10,220) TCOA(I~IC)~TCON(ltIC)~TCOX~1~IC~~TCO2(lrIC~ 

220 FOHP'IAT(Z3X.'SLOPE 1'~3(FReltlX)~FBo29' 1') 

WRITE (10.230) TCOA(3qIC) 

230 FOSFIAT (23Xv'ASPECT I'rF8,lt29X*'I') 

WRITE (10.240) TCOA(2tIC)~TCON(2~IC)~TCOX(2~IC)~TCO2(2~IC) 

240 FORMAT (21X*@ELEVATIOfd 1'93(FOeO11X),FBelr' 1') 

IF(IYqLEo0) GO TO 1s 

IF(IYeGT.26) IY = 26 

WRITE(IOt575) (13UPI(I)~I=I,IY) 

575 FORPIAT( /lOX'THESE CODES D 

lPONU TO THE LIST OF ACCEPTABLE BRUSH SPECIES,'/ 10X,@THIS DATA WA 

3s 410T USEC IN THE CALCULATIONS. ' / lOX,13(AQqlX) / lOX913(A4rlX)) 

15 CONTINUE 

C *** PPINT OlJT THE ORUSH LOADING HEADING 

INP2=Xf\12 

hHXTE (10,330) INP2 

WVITE (10.3401 

C * CALCULATE SHRUB LOADING RY SPECIES 

DO 250 Jz9.16 

X(J)=O.G 

250 CONTINUE 

DO 300 1=1,20 

X(8)=(ioO 

DO 290 J=lr7 

IF (SHWT(JIIIIC)~EQOO~O) GOTO 270 

IF (SHWT(JIIIIC).LT.O,O) GO TO 260 

X(J)=SHWT(J,IqIC)/XN2 

Y(&)=X(H)+X(J) 

GO TO 280 

260 X(J)=SHUT(JIIIIC) 

X(fi)=X(9)+1E-20 

GC TO 280 

270 X(J)=OeO 

200 COI~TIRU~ 

IF (X(0)oEQeOeO) GO TO 300 

C * SUPl HIGH, IYEUIUM. LOW* AND UNDEFINED BRUSH 

c * WRITE OUT THE ORUSH WEIGHTS 

WRITE (13,350) (YAME(K,I)r<=lr2).(X(J)qJ=1*8) 

DO 290 J=ltt3 

IF (X(J)oLEeO*O) GO TO 290 

h=J+8 

X(K)=X(K)+X(J) 

290 COrdTINUE 

300 COI\ITIPJUL 

WRITE (IQ9340) 

KRITE (109360) (X(J)*J=gtl6) 

330 FORMAT (//v~OX~~H*******~~X~~AVERAGE LIVE AND DEAD SHRUB LOADINGS 

1Ih POUNDS/ACREvr2X~7H*******,/.31X~'(FOR@t15 PLOTS)@,/r21X*@I'rl 

23Xv'SIZE CLASS IN CENTIMETERS'tl2X,'I'~/.8X~'SPECIES't6Xr'I 01.5 

3 e5-1 1-1e5 1,592 2-3 3-5 5+ I TOTAL*) 

340 FORMAT (8~~13('-')~'1~~50('-')~@1'~7(@-')) 

350 FOHRPT (8X92A6r9 I'r7F7.1,' I'qF7e1) 

36'3 FOPMAT (BX~'TOTAL'.HX~'1'~7F7el~' I'~F7el) 

C *** PERCENTAGE ESTIMATES AND 3+ SOUND XND ROTTEN 

C * AVERAGE PERCENT BRUSH COvEP 

GG 370 I=1*4 
: LICENSEG RESTRICTED RIGHTS AS STATED IN LICENSE F-0156 

03/01 

***I SEE DOCUMENTAT: 

PCV(191C)=PCV(ItIC)/XR~~IC~*1~O~0 

370 CONTINUE 

C * AVERAGE 0IAMETFRS 

00 390 1=1,2 

TF (XND(1,IC)eLEeOeO) GO TO 360 

ADIA(IIIC)=ADIA(I~IC)/YNU(TI~C) 

GO TO 390 

360 ALIA(ItIC)=O.O 

390 CONTINUE 

C * PHINT OUT ESTIMATES 

X(~)=XLOS(~~IIC~/~OOO.O*~O~~~ 

X(2)=XL9S(l8~1C)/20GOeO*106eS3 

WRITE (109400) (PCV(I~IC)tI=lr4)I(X(I)~ADIA(IIIC)II=lr2) 

400 FORIUIAT (//,9X971ti***** PEHCFNTAGE ESTIMATES ** 3+ VOLU 

1lYE Ahn DIAMETER ***** / 9X01 SHRUR I HERBS I 

2 s 0 1.1 r\t 0 I ROTTEN 1'1/r9X1'1'12(' %COVER XDEAO I' 

3)12(' CU-FT AVGeDIA I')r/t9X~'I't2(16('~'~~~1'~~2(17('-~~1'1~~1/ 

~~~X~II'~~(~(F~,II~X)I'I')I~(F~~OIF~~~I' 1')) 

C *** SEEDLIPdG COUNT 

WRITE (101410) 

410 FORi'IAT(// 23X138H********** SMALL TREES ********** / 28Xv'SPE 

lCIES TREES/ACRE AVGeHTeFTe') 

TOTSED=OeO 

PO 430 I=1119 

IF (NSDL(IIIC)~EQ~O) GO TO 430 

SEED=FLOAT(NSDL(I~IC))*3OOeO/XN(IC) 

TOTSED=TOTSED+SEED 

AVHT=SDLH(ItIC)/XDLH(IqIC) 

WRITE (1014201 ISPX(I)~SEEDIAVHT 

420 FORVIPT (~~XIA~I~XIF~O~~I~X~F~O~~) 

430 CONTIWUE 

WRITE (101440) TOTSEII 

44O FORMAT (~~XI'TOTAL'~FIO~O) 

450 CONTINUE 

KLTURPj 

END 

70 RO4-00 SUBROUTINE OUTPUT 03/04/82 15:27354 TABLE SPACE: 7 KB 

FFER: , 20 LINES/1321 BYTES STACK SPACE: 185 WORDS 

SION FLOATING PT SUPPORT REQUIRED FOR EXECUTIOhi 
LICENSED HESTHICTEO RIGHTS AS STATED IN LICEQSE E-0156 

03/04 

***, SEE DOCUMENTATI 

SUBROUTINE LOOK (IqOlrD2qD3) 

C *** SET PULTIPLICi~TION CONSTANTS BASED ON COVER 

IF (1,EQ.O) GO i.0 140 

GO T0(30~14O~14I~r14Ot3Ot1~@~3Oq1~O~14Oq4Oq2O~I4fl~I4OqlOq3O~14O~4O

1140~140~140)qI 

10 D1=0,0342 

GO TO 50 

20 @1=0*0201 

GO TO 50 

30 D1=0,0122 

GO TO 50 

40 D1=OeQ149 

5G GO T~(70~140q1~0~140~~0~14Oq7Oq14O~14Oq8Oq6Oql~~~l4Oq8O~7O~l4

1140q140q140)rI 

60 02=0,344 

GO TO 90 

70 C2=0,304 

GO TO 30 

80 [?2=0,238 

90 GO T0(10091409140~140q110~14091109140~14091209110q140914091009110v 

1140~120q140r140~140)~1 

100 D3=3,12 

GO TO 130 

110 L13=2,87 

GO TO 130 

120 @3=2,17 

130 RETURh 

140 01=0,0151 

D2=0,289 

D3=2,76 

PETLiHlv 

END 

'G FiO4-00 SUEPOUTINL LOOK 03/04/82 15:27:55 TABLE SPACE: 2 KB 

'FERt 20 LIPlES/1321 BYTES STPCK SPACE: 52 WORDS 

;ION FLOATING PT SUPPORT REOllIREn FOR EXECUTION 
t LICENSED RESTRICTED RIGHTS AS STATEP IN LICENSE E-0156 

03/0 

***q SEE DOCUMENTAT 

SUBROUTINE ZERO (NC) 

C *** ZERO OUT ALL STORAGE ARRAYS 

COYMON XLOS(ZRr2@)tXL~2(28r2O)~OEP(12v2O)~PCV(4~2O)rXNOP(8r2O)~X(2 

1A)tAUIA(2r20)rXMD(2~2O)rDEP2(2~2O)~SHWT(7~28t2O)rXN(2O)vDMX(2r2O)~ 

~XNLT(~~)~XNGF(~~)~O~~N~~~~[~~~F\~SOL(~~~~

~OA(~~~~)~TCON(~~~~)~TCOX(~~~~)~TCO~(~,~O)~STCA(

YCX(2r2O)qSTC2(?q20) 

00 80 IC=l*NC 

XF\I(~C)=O.O 

XNLT(IC)=OoO 

XNGF(IC)=O.O 

DO 10 J=lq2R 

XLDS(Jq1C) = 0.0 

XLD2(JqIC) = 0.0 

10 CONTINUE 

DO 20 J=lq12 

DEP(JrIC)=O.O 

20 CONTINUE 

DO 30 J=lq8 

XNDP(JqIC)=OoO 

30 CONTINUE 

00 40 J=1q3 

TCOA(J,IC)=O.O 

40 CONTINUE 

DO 50 JZ1.2 

DEP2(JqIC) = 0.0 

ADIA(Jq1C) = 0.0 

XND(J9IC) = 0.0 

DKX(J9IC) = -loOE+20 

STCX(JQIC) = -1oOE+20 

TCOX(Jr1C) = -1eOE+2O 

DMN(JqIC1 = l,OE+20 

STCN(J9IC) = 10OE+20 

TCON(Jt1C) = loOE+20 

STCA(J9I.C) = 0.0 

STC2(JrIC) = 0.0 

TC02(J,IC) = 0.0 

50 COWTINUE 

DO 60 1~1928 

GO 60 J=lq7 

SHWT(JtIrIC)=OoO 

60 CONTINUE 

DO 70 J=lq4 

PCV(JqIC)=O.O 

70 CCNTINUE 

C)O 80 J=lq19 

SDLH(J9IC) = 0.0 

XDLH(Jt1C) = 0.0 

NSDL(JqIC)=O 

80 CONTINUE 

FETURFJ 

E i\'D 

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03/04 

***, SEE DOCUMENTATI 

FLNCTIOM STOV (XX t XMNgXN) 

IF (XNeLE.I.0) GO TO 10 

STDV=SQHT((XX-Xh*(XMN**2))/(XN-1~0)) 

GO TO 20 

10 STDV=O.U 

20 PETIJEN 

F r'dD 

'C F04-00 FUNCTION STDV 03/04/82 15:27:58 TABLE SPACE: 1 KB 

'FEk: 20 LINES/1321 BYTES STACK SPACE: 151 hORDS 

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03/0 

***' SEE DOCUMENTAT 

SbBHOUTINE HEAD (IC'IO) 

CHARACTER ICVTP*lO,ICON*S 

CJIMENSION ICVTP(2r12) 

CC?Ih~Oh/tJED/ ItiEAD(15)~ICLT(144)~ICON(2)~ILAST~KEYIXIhlC~NPS~ICl~IP 

lS(J44)tICVT~IHRTtSAGE~IOUM1(100)rIY 

DATA ICVTP/ 'POPJDEKOSA ' 9 'PINE '9 

1 'LODGEPOLE 'r 'PINE '9 

2 'DOUGLAS-FI" 'R 'v 

3 'SPRUCE' SP', 'RUCE FIR 'q 

4 'ALPINE FIR'r ' '9 

5 'Gf3ARD FIR '9 ' 'r 

h 'WESTERR RE', '8 CEDER '9 

7 'BRUSH 't ' '9 

8 'ALPINE LAR'r 'CH '9 

9 'W3ITERARK '9 'PINE 't 

$ 'GRASS '9 ' 'q 

S UhDEFINEn ' ' '/ 

DATA IPAGE/O/ 

IPAGE=IPAGE+l 

IX=IC+ICl-1 

C *** PRIVT OUT TITLE 

k~ITE(IOtl0) (IHEAD(I)tI=lrl5)tIPAGE 

IF(KEYeEQ.1) WRITE(I0~15I ICVTVIHBTISAGE 

10 FOR~4T(lW1~9X~lSA4r' PAGE ''13 /) 

15 FCR;JlAT( 1OX~'COVEH TYPE 'rA3r2Xr'HABITA 

1T TYPE '~I~*~XI'STAND AGE 'rFq.0 ) 

GO TO(4O*lSUtl70)tKEY 

C * STAKDS sEPERATELY 

40 WRITE (10950) ILAST 

50 FOHIdlAT (36X 9 'STAND pJlJPSER ' r 14) 

6C TO 210 

C * CUVEH TYPE COCES 

150 Il=ICLT(IX) 

PRITE (10,160) (ICVTP(ItIl)tI=1~2) 

160 PGRi'qAT (30x9 'COVER TYPE ' 92A10) 

GO TO 260 

C + HABITAT TYPE CODE 

170 WHITE (109180) ICLT(1)O 

180 FORFIAT (34Xq'HRHITAT TYPE CODE'qI4) 

210 PETURK 

E lLu 

7G h04-00 SUBROUTINE HEAD 03/04/82 15:27:59 TABLE SPACE: 2 KB 

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LICENSED RESTRICTED RIGHTS AS STATE') IN LICENSE E-0156 

0 3/ 0 4 

***r SEE DOCUMENTATI 
: LICENSED RESTRICTED RJGtiTS AS STATED IN LICENSE E-0156 

GO TO 200 

Ck=YN* 03'+51*XHT 

GO TO 200 

Ch=YN*oO3lll*~HT**2.0 

GO TO 200 

CK=Ybj*.4294*XVT 

GO TO 200 

Ch=YN*o04933*XHT**2.0 

GO TO 200 

CW=YN*o1128*XHT+o00813*XHT**2 

GC TO 200 

Ck=YN*eG1482*XHT**2e7168 

GO TO 200 

CW=Yrd*, 035615*XtiT**2.503 

GC TO 2UU 

RETURN 

DO 210 I= 193 

IF(XtiToLE.4.9) Z(1) = Zl(I9ISP) 

IF(XHTqGEoSe0) Z(I) = 22(19ISP) 

CONT INIJE 

X(24) = X(24) + CW * Z(1) 

X(25) = X(25) + CW * z(2) 

X(26) = X(26) + CW * Z(3) 

PETURN 

E-hrl 

03/0ri 

***r SEE DOCUMENTATI 

70 K04-00 SURPOUTINE SEEUL 03/04/82 15:28:02 TABLE SPACE: 4 KB 

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APPENDIX IV 

FIELDWORK HINTS 

1. Steep slopes and heavy brush will slow procedures 

from 5 to 10 minutes per sample point. Keep this in mind 

when laying out the day's work. 

2. In bogs or moist areas, it can be difficult to distinguish the division between duff and mineral soil. It may 

be desirable to establish a lower limit such as 12 inches. 

Below this, duff should not be measured. 

3. Before going to the field, label bags for collecting 

herbs and litter. 

4. Keep herb and litter samples in porous containers to 

prevent mildew. If the weather permits, hang samples 

where they can air-dry. 

5. Approach sample point centers cautiously to avoid 

disturbing vegetation. At each point, lay out the sampling 

plane and subplots before doing any sampling. This will 

minimize disturbance of vegetation to be sampled. 

6. In areas with abundant herbaceous vegetation, take 

larger bags for collecting samples. 

7. Fill out the forms in pencil with dark lead. Mistakes 

can be easily erased. 

8. Take care to enter data and label sacks clearly. 

Make sure all the recording is completed in the field at 

each plot while it is still fresh in your mind. 

$- US. GOVERNMENT PRINTING OFFICE: 1982-576-026115 REGION No. 8 

48 
I Brown, James K., Rick D. Oberheu, and Cameron M. Johnston. 1981. Handbook for 

I inventorying surface fuels and biomass in the Interior West.USDA For. Serv. 

Gen. Tech. Rep. INT-129,48 p. Intermt. For. and Range Exp. Stn., Ogden, Utah 1 84001. 

Presents comprehensive procedures for inventorying weight per unit area of 

living and dead surface vegetation, to facilitate estimation of biomass and 

appraisal of fuels. Provides instructions for conducting fieldwork and calculating 

estimates of downed woody material, forest floor litter and duff, herbaceous 

vegetation, shrubs, and small conifers. Procedures produce the most accurate 

estimates in the Interior West; however, techniques for herbs, litter, and downed 

woody material are applicable anywhere. Includes computer program and card 

punching instructions for processing inventory data. 

I 

I KEYWORDS: sampling, forest floor estimation, shrub estimation, grass and forb 

estimation, forest fuel estimation 
The Intermountain Station, headquarted in Ogden, 

Utah, is one of eight regional experiment stations charged 

with providing scientific knowledge to help resource 

managers meet human needs and protect forest and range 

ecosystems. 

The Intermountain Station includes the States of 

Montana, Idaho, Utah, Nevada, and western Wyoming. 

About 231 million acres, or 85 percent, of the lhd area in 

the Station territory are classified as forest and rangeland. 

These lands include grasslands, deserts, shrublands, alpine 

areas, and well-stocked forests. They supply fiber for 

forest industries; minerals for energy and industrial 

development; and water for domestic and industrial consumption. They also provide recreation opportunities for 

millions of visitors each year. 

Field programs and research work units of the Station 

are maintained in: 

Boise, Idaho 

Bozeman, Montana (in cooperation with 

Montana State University) 

Logan, Utah (in cooperation with Utah State 

University) 

Missoula, Montana (in cooperation with the 

University of Montana) 

Moscow, Idaho (in cooperation with the 

University of Idaho) 

Provo, Utah (in cooperation with Brigham 

Young University) 

Reno, Nevada (in cooperation with the University of Nevada)