3

United States

7) Department of

Argriculture

Southern Forest

Forest Service Research Note

Experiment Station

SO-286

December, 1982

Estimating Dbh from Stump Diameter for 15 Southern Species

Carl V. Bylin

SUMMARY Data Set

Regression equations for predicting dbh from

tree stump diameter inside and outside bark are

presented for 15 southern species. Equations were

verified on independent test subsets using the F

distribution statistic with a significance level of

.05.

Addltional keywords: Dbh, stump diameter.

INTRODUCTION

Data used in this study were gathered In Louisiana (1973) as part of a wood utilization study. The

number of samples ranged from 436 for loblolly

pine to 14 for yellow-poplar. A species test subset

was extracted from every species data set which

contained more than 30 sample trees. The majority

of the trees were sawtimber size with mean dbh of

12.7 inches for softwoods and 14.4 inches for hardwoods. The mean stump height was 0.8 feet for

softwoods and 1.0 feet for hardwoods (table 1).

The Southern Forest Renewable Resources Unit

needed an accurate prediction of diameter breast

height (dbh) from stump dimensions to estimate

the dbh of removals. From the existing information

on dbh, volume of the removals could be calculated

using existing volume equations or volume tables.

Dbh estimation has several other applications

such as: (1) predicting removals from a large

forested area, (2) predicting total volume of timber

resulting from trespass cutting, (3) aiding in the

calculation of basal area distribution, and (4)

calculating growth on cut as part of a forest inventory.

Although, previous studies predicting dbh from

stump dimensions are numerous, none of the

studies were done in the Midsouth region of the

U.S.A. Only McClure’s (1968) report included

species of interest to the Midsouth, but his study

was conducted in the Southeast. Charts and

graphs dominated the earlier studies (Hough 1930,

Rapraeger 1941, and Endicott 1859), while regression techniques are used frequently today (Myers

1963, McClure 1968, and Raile 1977).

Simple linear regression equations were

developed to predict dbh from stump diameter inside bark or outside bark. Raile’s and McClure’s

models, which are more complex (both used

variable stump height), were tested on slash pine

and sweetgum data sets. Examination of the Rz’s

and standard errors indicated that simple linear

regression equations predicted dbh with accuracy

comparable to Raile’s and McClure’s models.

Analyses of the distribution of residuals for all

three models also indicated the adequacy of simple linear model.

Equations predicting dbh from stump diameter

outside bark were slightly more accurate than

those equations using stump diameter inside bark

(table 2). Dbh was predicted better for the softwoods than for hardwoods.

METHODS

RESULTS

Southern Forest Experiment Station/T-10210 U.S. Postal Services Bldg., 701 Loyoia Avenue, New Orieans, La. 70113

Forest Service, U.S. Department of Agriculture.

Serving Alabama, Arkansas, Louisiana, Mississippi, E. Oklahoma, Tennessee, E. Texas, Puerto Rico, U.S. Virgin islands

1
.

Table 1 .-Meen, range’, and number of samples for selected parameters in the data sets

Mean

,Specles No. samples

Range Mean Range Inside bark Outside bark

range range

Slash Pine 134 9.8 3.4-17.2 .7 0.4-l .2 3.8-27.2 4.8-29.1

Shortleaf Pine 198 12.8 4.5-23.5 .7 0.2-l .2 4.4-24.0 5.3-28.1

Longleaf Pine 4 2 13.3 7.5-19.4 .7 0.5-l .3 7.1-20.3 8.5-23.4

Loblolly Pine 438 13.5 3.0-27.0 .8 0.1-1.5 3.3-28.8 4.2-31.3

All Pines 914 12.7 3.0-27.0 .8 0.1-1.5 3.3-32.5 4.2-35.4

Hickory 3 8 15.0 8.7-24.2 1.1 0.5-l .5 7.9-28.7 9.0-28.2

Whlte Oak 7 2 13.9 8.3-23.3 1.1 0.1-2.1 7.4-28.1 7.9-27.5

Water Oak 8 2 18.8 8.8-38.9 1.1 0.5-1.8 8.3-41.8 9.0-43.2

Post Oak 8 8 11.8 4.1-22.8 .9 0.5-l-5 4.9-27.4 8.0-29.0

Cherrybark Oak 2 8 15.0 7.3-28.5 1.1 0.5-1.5 8.7-32.1 9.4-34.3

S. Red Oak 8 9 11.8 4.4-22.0 1.0 0.4-2.9 4.7-25.9 5.2-27.4

Sweetgum 119 12.7 4.0-41.4 1.0 0.3-l .5 4.9-27.4 5.3-28.5

Black Tupelo 2 1 13.2 8.8-20.2 1.1 0.3-l .5 8.7-28.4 9.8-27.3

Yellow-poplar 1 4 17.3 15.3-22.5 1.0 0.5-1.5 18.2-23.4 17.8-25.2

Sugarberry 2 1 15.8 8.4-28.2 1.4 1 .O-2.5 12.9-32.1 13.7-33.7

Beech 1 5 18.4 8.9-21.9 1.2 0.7-1.5 10.5-25.9 10.9-27.0

Other Hardwood 111 14.4 4.4-29.8 1.0 0.3-I .5 5.2-34.9 5.8-38.5

All Hardwood 819 13.8 4.0-41.4 1.0 0.1-2.9 4.7-43.4 5.2-45.3

Dbh Stump helghi Stump diameter

(Inches) (feet) (Inches)

‘Due to the selectlon of test subsets, ranges for all-pines and all-hardwoods data sets may differ from species

ranges.

Table 2.-Coefficients, standard error, and FT of equation predicting dbh

Dbh = b, + b,*SDOB’ Dbh = b, + b,*SDIB’

Species No. samples b0 b, SE RZ 4 b, SE R’

Slash Pine 134 -.055 .808 .74 36 .518 .902 .78 .95

Shortleaf Plne 198 .178 .851 .75 .97 .798 .910 .88 98

Longleaf Pine 4 2 A69 .841 .87 .92 1.048 .921 96 .91

Loblolly Plne 438 -.255 .854 39 36 Ml .902 1.03 98

All Pines 914 -.198 .853 38 36 .a88 .902 1.01 95

Hickory 3 8 .413 ,811 1.28 .90 1.317 .840 1.31 -90

Whlte Oak 7 2 .152 .778 1.38 .a4 .810 .811 1.37 .84

Water Oak 8 2 1.148 .725 1.79 .91 1.438 .749 1.82 .91

Post Oak 8 8 - .107 .773 1.18 .93 .471 .a20 1.17 .93

Chertybark Oak 2 8 .852 .788 1.21 .9!5 .815 .8C18 1.23 .95

S3kn-l Oak 8 9 .422 .748 1.30 .88 .885 .792 1.33 .87

Sweetgum 119 -.198 .818 1.02 .94 222 .a40 1.07 93

Black Tupelo 2 1 .444 .788 96 .94 .855 .798 1.07 33

Yellow-poplar 1 4 .388 .851 .Qo .95 .449 305 .93 .9!5

Sugarberry 2 1 1.033 ,899 1.82 .81 1.305 .720 1.83 .81

Beech 1 5 1.182 .777 2.00 .71 1.108 .880 2.02 .70

Other Hardwood 111 .515 .778 1.38 33 .902 .a04 1.41 .92

All Hardwood 819 .595 .757 1.43 90 1.203 .777 1.48 .Qo

,

’ SDOB = stump diameter outside bark.

’ SvB = stump diameter lnslde bark.

darl V. Bylln Is Research Forester, Southern Forest Experiment Station, Forest Service-USDA, New Orleans, La.

2
A

.

The equations (table 2) were applied to each

species’ respective test subset. Examining the

residuals, the F-test with .05 significance level failed to reject any of the equations. Although the

F-test failed to reject water oak equations, these

equations underestimated dbh of larger diameter

trees. This possibly reflects swelling of the butt log

characteristic in this species.

The user of these coefficients and equations for

prediction of dbh Is warned to observe the limits for

individual species indicated by the range of stump

diameters (table 1). Measurement of stump

diameter should be taken around the stump height

mean. Extrapolation to larger diameters should be

verified if warranted. It should also be noted that

variability of the prediction is larger for larger

stump diameters.

LITERATURE CITED

Endicott, N. D. 1959. Stump heights. Victoria

Commonwealth Forestry, Forestry Technical

Paper No. 2(11-2).

Hough, A. F. 1930. Stump diameter-d.b.h. relationship for beech in northwestern Pennsylvania.

U.S. Department of Agriculture Forest Service,

Allegheny Forest Experiment Station, Technical

Note 1, 1 p.

McClure, Joe P. 1968. Predicting tree d.b.h. from

stump measurements in the southeast. U.S.

Department of Agriculture Forest Service,

Southeastern Forest Experiment Station,

Research Note SE-99, 4 p.

Myers, Clifford A. 1963. Estimating volumes and

diameters at breast height from stump

diameters, southwestern ponderosa pine. U.S.

Department of Agriculture Forest Service, Rocky

Mountain Forest and Range Experiment Station,

Research Note RM-9, 2 p.

Rapraeger, E. F. 1941. Determining tree d.b.h. from

stump measurements. U.S.’ Department of

Agriculture Forest Service, Northern Rocky

Forest and Range Experlment Station, Research

Note No. 18, 8 p.

Raile, Gerhard. 1977. Estimating D.B.H. from stump

dimensions. In Proceeding: 1977 Midwest Forest

MenWratlonist Meeting. U.S. Department of

Agriculture Forest Service, North Central Forest

Experiment Station. General Technical Report

NC-48. p. 30-33.

3

12ll.S. GOVERNNEWT PRINTING OEFICL: ~q83-6~q-,w~,‘~~