United States

Department of

Agriculture

Forest Service

Pacific Northwest

Research Station

General Technical

Report

PNW-GTR-289

PPPRUNEUsersGuide

January 1992

NatalieA. Bolon, Roger D. Fight and James M. Cahill

This file was created by scanning the printed publication. Text errors identified 

by the software have been corrected; however, some errors may remain. 
Authors

The PP PRUNEsoftwareis inthe public domain andthe recipient may neither assert

any proprietaryrights thereto nor representthem to anyoneas other than Governmentproducedprograms.

The PP PRUNEsoftware is provided‘asis”withoutwarranty of any kind, including but

not limitedto the implied warranties of merchantability and fitness for a particular

purpose.The user assumes all responsibilityfor the accuracy and suitabilityof these

programsfor a specificapplication.

Inno event will the PacificNorthwestResearchStation be liable for any damages,

includinglost profis, lost savings, or other incidentalor consequentialdamages, arising

from the use or inabilityto usethis program.

The useof trade, firm, or corporationnames inthis publication isfor the information

and convenienceof the reader. Such usedoes not constitute an official endorsement

or approvalby the U.S. Departmentof Agriculture of any product or service to the

exclusionof others that may be suitable.

PP PRUNEis distributedby the ForestResourcesSystemsInstitute(FORS), a nonprofit organizationfor forestry computer support. A fee is chargedto cover the costs of

disks, postage, handling, andtelephone support to answer questions from users. For

information on orderinga machine-readablecopy, write or call:

The Forest ResourcesSystems Institute

122HeltonCourt

Florence, Alabama 35630

(205) 767-0250

NATALIEA. BOLON is a research forester, ROGER D. FIGHT is a principal economist, JAMES M. CAHILLwas a researchforester, ForestrySciences Laboratory,

P.O.Box 3890, Portland, Oregon97208. (JamesM.Cahill currently is with Bonneville

Power Administration, Portland, Oregon.)
Abstract Bolon,NatalieA.; Fight, Roger D.; Cahill, James M. 1992. PP PRUNEusersguide.

Gen.Tech. Rep. PNW-GTR-289.Portland, OR: U.S. Departmentof Agriculture,

Forest Service, Pacific Northwest ResearchStation. 18p.

The PP PRUNEprogramallows usersto conduct a financial analysis of pruning

ponderosapine (Pinus ponderosa Dougl. ex Laws.). The increase in product value and

rateof return from pruning the butt 16.5-foot logcan beestimated. Lumber recovery 

information is based on actual millexperience with pruned and unpruned logs. Users

supply lumber prices by grade, the cast of pruning, and tree descriptions from growth

and yield information. The programestimatesthe difference invaluefor trees and

standswith and without pruningandthe difference inpresent net worth from adding

pruningto a given regime.The Lotus 1-2-3spreadsheet programwas used to develop

PP PRUNE. Users need a basic knowledge of spreadsheetsto use this program.

Keywords: Ponderosa pine, pruning, forest product value, product recovery, simulation. 
Contents 1

1

2

4

5

6

6

8

8

9

10

15

16

17

Introduction

Useof PP PRUNE

SpreadsheetLayout

Discussion

Interpretation

MetricEquivalents

LiteratureCited

Appendix A: Instructions

Part 1: InstructionsFoundinProgram

Part2: Steps

Appendix 6: Regime and Price Input and Output

Appendix C: Calculations

Appendix D: Macro Features

Appendix E: RecoveryData
Introduction As the harvest of ponderosapine (Pinus ponderosa Dougl. ex Laws.) resourcesshifts

from old-growthto second-growthforests, lumber recovery will decrease inthe traditional and high-valuedlumber productsof the Select and Shop grades (Cahill, 1991).

Anticipatedharvestcycles do not allow enoughgrowthof clear wood after naturalbranch

deathand dislodgementto yield significant amounts of clear wood products.Product

recovery from young-growth pinewill consist mainly of the lower valued Common and

Dimension lumber grades. Pruningoften is mentionedas a forest-managementtoolto

achieve recovery intraditionaltypes of clear wood productsfrom young-growthstands,

yet it has not beenseriously implementedinthe Pacific Northwest.

The effects on tree growthfrom pruningyoung-growthstands of ponderosapine have

beendocumentedbyBarrett (1 968) and (1959). Lumber grade recovery studies

(Bowman 1983; Cahill, 1991) and evaluations of the financial returnto pruningponderosa pine (Davis 1958,Shaw andStaebler 1950) also have beenconducted.These

studies commonly show increasesinthe higher valued lumber grades for the pruned

trees. Pruningrecovery studies andfinancial evduationsfor other tree species, particularly Douglas-fir(Pseudotsuga rnenziesii (Mirb.) Francovar. rnenziesii) are numerous

(Anderson 1951,Brown 1962,Cahill and others 1988,Childs andWright 1956,Dimock

and Haskell 1962,DobieandWright 1978, Helmers 1946,Sutton 1984). Fight and

others (1987) evaluatedthe financial returnfrom pruningyoung-growth Douglas-fir

throughthe use of a pruningspreadsheetandfound many situations where pruning

would befeasible.

The literature clearly shows that pruning isthe only way to ensure the growth of significant volumes of clear wood in intensively managedstands. What silviculturistsand

forest managersneedto know is whether the increaseinvalue from pruned logs is

sufficientto justify investmentsin pruning.

The objectiveof the PP PRUNE programandthis users guide isto provideand document a toolto aid forest managers intheir decisionmaking process.The PP PRUNE

spreadsheet is a programthat can be usedto do afinancial analysisfor pruning ponderosa pine. It should bewidely applicableto interior Northwest ponderosapine regions.

The program is based on only one study, however, and further documentation of lumber

recovery studies from prunedpine logs is needed. The PP PRUNEprogramestimates

the increasein product value from pruning16.5-foot butt logs. It is basedon lumber

volume and grade recovery information reported by Cahill (l991) and from a younggrowth pine recovery study by Willits. 1

The analysis requires pine lumber prices by

grade, the cost of pruningper log, andtree descriptions. The tree descriptions are

supplied by the user from sources of growth and yield information,such as Prognosis

(Wykoff and others 1982).The Lotus 1-2-3spreadsheet programwas usedto develop

PP PRUNE. We suggest that the user follow along with the program on the computer

screen while reading this manual.

Use of PP PRUNE The PP PRUNE program projects the difference invaluefor trees and standswith and

without pruning. The present net worth of this difference takes into account the cost of

pruning and the mortality of prunedtrees (success rate) and represents the financial

returnof addingpruningto a given regime. The rate of return to pruningcanalso be

1

Unpublisheddata. Onfile with: S. Willits,researchforest products

technologist, USDA ForestService, Pacific Northwest Research

Station, P.O. Box 3890 , Portland,OR 97208.

1
estimatedfor each regime.Settingthe cost equalto zero gives the maximum amount

that can be spent on pruningwithout reducingthe rateof returnon the investmentbelow

the specified rate.

Userswill find this guide and programmore usefulthan any specific analysis we might

publish, becausethe programallows usersto analyzethe regimes most relevantto their

situation. The combinations of prices, regimes, and other assumptions in an analysiswill

differ for each user. 

Appendix A specifiesthe stepsfor operatingPP PRUNE.Once users input current and

future priceassumptionsand generate new equations, specific regimes or tree descriptions can be analyzed.The PP PRUNEprogram predicts averagelog values and is

designedto analyze one regime (tree description) at a time. The data are entered and

the spreadsheetisthen calculated. Detailed results for each regime can beseen onthe

same screen as where the regime data were input. The whole screen, with both input 

and output, is identified with a range name and can easily be printed(see appendix A,

part 1).Comparisonsfor regimes can then be made, but for several analyses this might

becumbersome.

Analyzinga set of regimesunder fixed prices will probably bethe most commonevaluation done, so PP PRUNE has a macrofeaturethat allowsthe results for each regime

runto be saved (seeappendix D). After the resultsfor each regimeare calculated,the

user cancopy them into a summary table with the macro. Graphs then can be usedto

compareseveralregime runs. An exampleof analyzing several runs includes a regime

with four different rotation ages. Four separate analyses with the sametree description

at time of pruningbut different descriptions at time of harvest (age, diameter, and height)

are runand stored inthe summary table. Graphs for the regime include the resultsfor

specific variables under allfour harvest ages (see'Interpretation," below).An example

of a generic pruninganalysiswith results is included(columnIinthe program). By using

the same regimes and priceassumptionsasthose shown inthe program, the user can

duplicate these regime runs and compare results.

An explanationof how the spreadsheet is laid out and a descriptionof the various

sectionsfollows. After reading this guide and the appendices, the user will understand 

the input needed and the resultsgenerated, and be able to runthe program. The 

spreadsheet has been"protected" sothat only the entries needed for the programto

executeare allowed. Itis also set for manualrecalculation;that is, the spreadsheet will

not automatically updateafter each entry is made. The programinstructions tell the user

how and when to calculate the spreadsheet (see appendix A). This methodsaves

computer operating time and allows the program to runfaster.

Spreadsheet Layout Figure 1 shows the general layout of the PP PRUNE spreadsheet program. In Lotus

1-2-3,the entire PP PRUNEworksheet covers columns A to BT and rows 1 to 240. It

consists of 10blocksthat make up six main areas; the areas and a brief description of

each block follow:

1. Regimedata input and output: three blocks. Block 1a is regime input. Block 1b is

individualregimeoutput. Block 1cis a summary resultstable for various regime runs. 

2. Priceinput and output:two blocks. Block 2a is lumber grade and residue priceinput.

Block 2b contains tables of product values ($/CCF) from equationsfor a range of

diameters and clear wood percentagesthat are derived from the user's price input.

2

Discussion

3.

4.

5.

6.

Instructions:one block.This block holds instructionsfor running the program (see

appendixA).

Computations:two blocks. Block 4a hastree profile equations used to calculatethe

diameter insidebark (d.i.b.) and percentageof clear wood. Block 4b stores the regressionoutput for the productvalue equations that use the calculated d.i.b. and

the percentageof clear wood.

Recoverydata: one block. Block 5 stores the ponderosapine recovery data. These 

data are usedto determinethe value of each log given the input pricesfor lumber, 

chips, and sawdust. Regression analysis is usedto predict average logvaluesfor

the pruned and unpruned logs. 

Macro features: one block. Block 6 contains the series of commands that allow the

user to usetwo sets of prices and storethe results.

Further details of PPPRUNEare illustratedinthree sections. Brief narratives of these

sectionsfollow with fulldescriptions inthe appendix noted: 

1. Regime and price input and output. The general information needed to run the program and the output generated are illustratedin appendix B.

2. Computations.This section of the program provides users with a detaileddescrip

tion of the necessary computationsmade inthe PPPRUNEspreadsheet to producethe results.See appendix C.

a. Logdiameters.The tree profile equations usedto estimate logdiametersat the

time of pruningand at the time of harvest are discussed.

b. Productvalue calculations. Useof the recovery data andthe product value calculations madeby the program are reviewed (also see appendix E).

3. Macro features. The macro features allow the user to analyze pruningunder both

current and future price assumptions. Several PP PRUNE regime results also can

bestoredfor further analysis. See appendix D.

The operational costs of pruningcandiffer depending onthe methodsand equipment

used, number of trees pruned,wage rate, height the trees are prunedto, the terrain,

proportionof live to dead branches and so forth. The cost of pruningto a height of 18

feet is likelyto be inthe range of $2 to $5 per tree. This cost can be specifiedinthe

spreadsheet, but additional costs, such as recordkeeping, are not included inthe

calculations.By settingthe cost to zero, the user can look at the break-evencost

(PNW1or PNW2variables), or what one could affordto pay for pruningandjust break

even (doingthis type of analysis causes the IRR variable to display ERR becausethe

internal rateof return is meaninglesswhen the cost is zero). In a reasonably competitive 

stumpage market, buyers can be expected to pay a premium for pruned logs that

reflectsthe increaseinvalue resulting from recovery of clear wood products. Convincingfuture buyers of the quality of pruned logs may requirerecords showing tree or

stand descriptions, as well as proof of the size of trees at time of pruning, sothat the

amount of clear wood can beestimated.

4
Interpretation

In determiningthe growth andyield of a regime, it is helpfulto track the prunedtrees in

the stand; that way the average diameters and other regime input are limitedtothose

trees. Whole stand averageswould cause any thinning effects to be apparent inthe

inchesper decade of growth and inthe returnto pruningas well (becausethis depends

onthe volume of the log). When pruning, it is importantto pick those trees that will

become croptrees; therefore, at the time of pruningnot every treewill be pruned.

Prognosis(Wykoffand others 1982) is ableto generate tree listsfrom which the tallest

trees, assumedto becomecroptrees, can be chosenfor pruning.

To determinethe agewhen a stand might be pruned, userscan establish a rule of

thumb, such as removingone-third of the livecrown, or refer to Barrett’s(1968) study

onthe effects of pruning ponderosapine. Barrelt determinedthat various levels of

crown removal can result in certainpercentagesof diameter-growthloss. Users must

decidewhat levelof diameter-growth loss is acceptableto them givenvarious stand

crown ratios. If 5 percent or less diameter loss is chosen,then only specific levels of live

crown can be removedfrom trees of a certaincrown ratio. A treewith 80percent live

crown,for example, can endure 40 percent live crown removalwith only a 5-percent

loss indiameter growth. If 5 percent is the maximumgrowth loss permitted,the earliest

the tree can be pruned upto 18feet iswhen it reaches a total height of 35feet. This 

informationcan be used in conjunctionwith stand growth and yield datato determine

the age and diameter that this height occurs. 

The PP PRUNE program also can be usedto conduct a sensitivity analysis on lumber

prices. Haynes and Fight (in press) give projections of lumber pricesto 2040. Users

may havetheir own insight as to what future prices will be, but caution must be exercised in makingprice assumptions. Clear wood products from pruned young-growth logs

may have a different appearance than clear wood products from old growth. The pruned

young-growthclear wood products should be a close substitute for clear wood products 

from old growth; however, there could be market resistanceto clear wood products from

prunedyoung growth. But historicalevidence indicates that as any high-quality resource

becomesscarcer and more expensive, people become more creative in using substitutes. As old-growthclear wood becomes more expensive, the market resistanceto

young-growthclear wood likely will diminish.

One final noteof caution:The predictedlumber grade recovery for prunedlogs outside

the rangeof diametersat time of pruningandtime of harvestsampled inthe product

recovery study should be examinedcarefully (see appendix E).

It is assumedthat the reader has referredto and readthe appendiceswhile following

along inthe spreadsheet. Once specific regime results have beenproduced, ideasfor

what to do with them may be useful. As the proportionof clear wood on a log is an

important determinant of the value of a pruned log (appendix E), users might liketo

know what kindof growth a particular regime is producingon the logsOver time. Graphingthe inches per decade (output variable in columnAG inthe program) Over several

rotationor harvest ages (columnJ) shows this. To find out how this translates to the

percentageof clear wood on a log, graphthe percentageof clear wood (column R) over

the years since pruning in column AI. This and other graphs can be seen inthe spreadsheet by using the graph macro provided (see appendix D). If the user is interested in

the undiscounted futurevalue of the logs, graphs usingthe future value of the unpruned

logandthe pruned log (columnsZandAA) Over theyears since pruningcan be created

to see the differenceinvalue betweenthe two. Present net worth, the break-evencost

5
pruning,the internal rate of return, current or future returns per acre, and soforth are

other variablesthat can be usedto creategraphs to understandthe regimes and results

of the user’s financial analysis. Refer to appendix D for the available graphs provided

from the programexample regimes. Results graphed inthis way makeit easier to

answer such questions as,"Is it financially worthwhile to prune, and if so, what age is

optimum andwhen isthe best timeto harvest?”

Metric Equivalents 1 inch = 2.54 centimeters

1foot = 0.305 meter

1 cubic foot = 0.028cubic meter

1 acre = 0.4047 hectare

Literature Cited Anderson, E.A. 1951. Healingtime for prunedDouglas-fir.Tech. Rep. 1907. Madison,

WI: U.S.Departmentof Agriculture, Forest Service, Forest Products Laboratory. 5 p.

Barrett, James W. 1988. Pruningof ponderosa pine..effect on growth. Res. Pap. PNW68. Portland,OR: U.S.Departmentof Agriculture, Forest Service, Pacific Northwest

Forest and Range ExperimentStation. 9 p.

Bowman, H.F. 1983. The financial returnof pruning ponderosa pine. In: Management

of the eastsidepinetype in northeasternCalifornia. SAF 83-06. [Locationof publisher

unknown]: Northern California Society of American Foresters:[pages unknown].

Brown,G.S. 1962. The importance of stand density in pruning prescriptions. Empire ForestryReview. 41(13): 246-257. .

Cahill, James M.; Snellgrove, Thomas A.; Fahey,Thomas D. 1988. Lumber and

veneer recovery from pruned Douglas-fir.Forest ProductsJournal. 38(9):27-32.

Cahill, James M. 1991. Lumber recoveryfrom pruned young-growth ponderosa 

pine. ForestProductsJournal. 41 (11/12):67-73.

Childs, T.W.; Wright, E. 1956. Pruning and occurrenceof heart rot inyoung Douglasfir. Res. Note 132. Portland, OR: U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Forest and RangeExperimentStation. 15 p.

Czaplewski, Raymond L.; Brown,Amy S.; Guenther, Dale G. 1989. Estimating

merchantabletree volume in OregonandWashingtonusingstem profile models. Res.

Pap. RM-286.FortCollins, CO: U.S.Departmentof Agriculture, Forest Service,

Rocky Mountain Forest and RangeExperimentStation. 15p.

Davis,G. 1958. Profitsfrom pruningponderosa pine in relationto pruningdiameter.

Journal of Forestry. [Volumeand issue unknown]: 905-908.

Dimock, EdwardJ.; Haskell, Henry H. 1962.Veneer gradeyield from pruned

Douglas-fir. Res. Pap. 48. Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific NorthwestForest and RangeExperimentStation. 15p.

Dobie, J.; Wright, D.M. 1978. Economics of thinning and pruning: a case study.

Forestry Chronicle. 54(1): 34-38.

Fight, Roger D.; Cahill, James M.; Snellgrove,Thomas A.; Fahey, Thomas D.

1987. PRUNE-SIMuser’s guide. Gen. Tech. Rep. PNW-209. Portland,OR: U.S.

Department of Agricutture, ForestService, Pacific Northwest ResearchStation. 21 p.

6
Gordon, D.T. 1959.Ten-year observations on pruned ponderosa and Jeffrey pine. Res.

Note 153. [Berkeley, CA]: U.S. Department of Agriculture, Forest Service, Pacific 

Southwest Forest and Range ExperimentStation. 4 p.

grades of Douglas-fir,coast hem-fir, inland hem-fir, and ponderosa pine lumber. Res. 

Pap. Portland,OR: U.S. Departmentof Agricutture, Forest Service, PacificNorthwest

ResearchStation.

Haynes, RichardW.; Fight, Roger D .[Inpress]. Priceprojectionsfor selected

Helmers, A.E. 1946. Effectof pruningon growth of western white pine. Journal of

Forestry.44(9): 673-676.

Shaw, Elmer W.; Staebler, George R. 1950. Financialaspects of pruning. Portland,

OR: US. Departmentof Agriculture, Forest Service, Pacific Northwest Forest and

Range ExperimentStation. 45 p.

Sutton, W.R.J. 1984. New Zealand experiencewith radiata pine.The H.R. MacMillan

LectureshipinForestry.Vancower, BC: University of BritishColumbia. 21 p.

Warren, Debra D. 1990-91. Production, prices, employment, and trade in Northwest

forest industries. Resour. Bull.Portland, OR: US. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station. [Published quarterly]. 

Western Wood ProductsAssociation. 1981. Westernlumber grading rules. Portland,

OR. 222 p.

Wykoff, William R.; Crookston, NicholasL.;Stage, Albert R. 1982. User’s guide to

the stand prognosis model. Gen. Tech. Rep. INT-133.Ogden, UT: U.S. Department

of Agriculture,Forest Service, IntermountainForest and Range Experiment Station. 

112p.

7
Appendix A:

Instructions

Part 1:Instructions

Foundin Program

Thefollowing is a copy of the instructionsfound inthe PP PRUNEprogram startingat

cell I118.

INSTRUCTIONS

See USER'S GUIDE for details. Usethe 'HOME" key to returnto cell A1.

STEP 1-Startingat cell E27enter prices besideeach of the grades (columnsE and F,

rows 27-48).

STEP 2-Once prices have beenentered, press 'Alt" and "C", for current price results

AND/OR "Alt F"for future prices.The $/CCF regression equations will use

your prices to generate results.Tables usingthe new equationsfor each setof

prices arefound directly belowwherethe prices are input (cellsA53 andA66).

EACH time you re-enter current or future prices, you must reruneither "Alt C" or "Alt F". This is not necessary if you are runningsensitivity analyses on regimedatawith fixed

prices.

STEP 3-Enter a summary table analysis headingone screento the right of HOME, at

cell M2 (anexample has beenprovidedthat can be erased, if you like).

STEP 4-Inthe HOMEscreen (A5), fill inthe regimedata. Calculatethe spreadsheet

now by pressing"F9".Resultsare shown at A8. To store your input and

resultsinthe summary resultstable (startingin column I,directly abovethese

instructions), press 'Alt A". Upto 100results can bestored.

The LotusWorksheetTitles or Window options can be usedto scrollthroughthe table.

It is highly recommendedthat you add labelsto the summary table asyou go. This

keepsthe data separatedfor easier viewing. Headingsor labels must be entered only in

column I.

Note: ****PLEASE DO NOTINSERTROWSANYWHEREINTHISSPREADSHEET!****

The following options also areavailable:

"Alt G" presentsexample graphs, includingthe Current & Future$/CCF andfour

example regimesgraphs. Press"enter"after each graph is shown to choose

againfromthe graph menu (see appendix D of the user's guide). Erasingthe

example regimeresultsfrom the summary table will invalidatethese graphs.

NamedPrint Rangesfor the "PRICES", "CCFTABLE", & "RESULTS@A8"exist. To use

these, press "/" select "PRINT", "PRINTER", "CLEAR", and "RANGE".Now

choose "RANGE" andtype inthe name of the range youwish to print.Select

"GO".

8
Part 2: Steps The followingis a list of PP PRUNEoperatingsteps:

1.

2.

3.

4.

5.

6.

7.

8.

9.

Input current andfuture prices (columnsEandF,rows 27 through 48).

Press"AltC" and/or "AltF" to updatethe productvalue equationswith the user's

prices.

Input cost and interest rates (columnsA, B, and C; row 5).

Inputregimedata; that is, age, diameter and height at time of pruningand at harvest (columnsA through F, row 7).

Input number of trees to be pruned(cellG7) andthe success rate (proportionof

pruned trees survivingto harvest, cell H7).

Calculatespreadsheet by pressing"F9".

Press"Alt A" to store

Look at individual regimeresults in cells A8 to H20. Look at stored results of several

regimeanalyses incolumn I.

Graph results by using Lotus graphing procedures and the output variables of interest (see 'Interpretation," intext).

9
AppendixB :

Regime and Price

Input and Output

Figure2 shows the regime input neededandthe sectionfor individualregime results. 

Regime input is in rows 4 through7. Individualregime results are inrows8through 20.

Figure3shows the price input and resultant product value output when using a rangeof

diametersandclear wood percentages.The lumber grade priceinput isinrows 21 through

49. The tables usingthese pricesfollow this section in rows50 through77. Figure4

shows a summary table of several regimesthat can later be usedfor further analysis.

Variable Definitions All variables inthe spreadsheethave hidden definitionsthat appear when the cursor is

onthe cell. If,for example,the cursor is movedto column C and row 7 (cellC7), the

variable name HT1 is highlightedandthe hiddendefinition, “HT1-Total height at time of

pruning,”will show abovethe spreadsheetonthe commandline. Most input and output

variables from the list describedbelow also can befound inthe summary results table.

To compact the output into a summary resultstable, several of the variable labels had

to be compressed. If a shorter abbreviationis used inthe summary resultstable, itwill

be shown in parenthesesafter the term usedinthe input or individual output section in

the following definitions.

Inputvariables-Four types of input are needed inthe program.

Cost andinterest rates--Theestimated cost and interest ratesto be used inthe

analysis must beenteredby the user.The specific informationinthe cells is:

A5 = COST, the cost of pruningper log;

B5 = RATE 1,the interestrate usedinthe analysis; and

C5 = RATE 2, the second interest rate usedinthe analysis.

Tree descriptions-Thetree descriptions are containedin cells A7 through F7. Users

must get this informationfrom yieldtables suchas Prognosis( Wkyoff and others 1982).

The specific informationin each cell is:

A7 =AGE1 (Al), age at time of pruning;

87 = DBH1 (Dl), diameter at breast height at time of pruning;

C7 = HT1 (Hl), total height at time of pruning;

D7 = AGE2 ( A2) , age at time of harvest;

E7 = DBH2 (D2) diameter at breast height at time of harvest; and

F7 = HT2 (H2), height at time of harvest.

Numberoftrees andsuccess-

_Anestimateof the number of trees to be prunedand

the proportion surviving to age of harvest must be made by the user. The specific informationinthe cells is:

G7 = TREES (TRES) ,the number of prunedtrees per acre; and

H7= SUCCESS (SUCC), the proportionof prunedtrees assumedto be present at the

time of harvest (in decimal form).

Lumberprices- _Users must supply lumber and residueprices (columnsEand F, rows

27 through 48). Lumber pricesare enteredin dollars per thousand boardfeet ($/MBF)

1

Prioesused in the programdiffer slightly becausethey were based on aprelimineryproducerprice index for 1989.

10
Figure 2_ An exampletrom thespreadsheet of the individual regime input andoutputsections. Lettersand numbers refer to columns and rows in the

spreadsheet.

by lumber grade (fig. 3) .Haynesand Fight1 (in press) give detailed descriptions of the

ponderosa pine lumber grades as well as future price projectionsout to 2040. Priceinformation also is available inWarren (1990-91).The residueprices can be enteredin

dollars per cubic foot ($/CF) of solidwood equivalent or be determinedfromthe conversiontable provided(cellG36) .Conversionsto $/CF are suppliedfor the following prices:

dollars per bonedry unit ($/BDU), dollars per metric ton ($/MT), and dollars per short

ton ($/Short ton). These residueprices, regardless of how initiallyentered, must come

from the user's professionaljudgment as they differ widely with locationand are not

readily available.

Future prices of pinelumber will be important in determiningthefinancial returnsfrom

pruningyoung pinestands, becausethe returnfrom pruningwill not be captured until

the stand is harvested.This returnwill dependonthe difference in price betweenclear

grades and lower grade products.Various studies of supply and demandfor timber and

historical trends can help project prices, butthefuture is really unknown. Becausewe

do not know what future prices will be, we suggest looking at the financial returnfrom

pruningfor a rangeof future prices.

Output variables-

_Locationsand descriptions for the individual regimeoutput variables

follow (see fig. 2):

A10 = Loglength, lengthof butt logwith trim.

C10 = dib, calculatedsmall-end diameter inside bark in inchesfor the butt log.

E10 = CfVol,the predictedcubic-footvolumefor the average butt loginthe regime.

G10 = % Clear ( %C) the calculated , percentageof clear wood inthe pruned butt log.

C13,E13 = Value unprunedlog, undiscountedvalue in $/CCF for the average unpruned

butt log at harvest, under current andfuture prices, respectively.

D13,F13 = Value unprunedlog (VUL), undiscountedvalue in $/logfor the average

unpruned butt log at harvest, under current andfuture prices, respectively.

11


C14,E14 = Value pruned log, undiscounted value in$/CCF for the average prunedbutt

logat harvest, under current andfuture prices, respectively.

D14,F14 = Value prunedlog (VPL), undiscountedvalue in$/log for the average pruned

butt log at harvest, under current and future prices, respectively.

C15,E15 = Increase inValue, the undiscounted differenceinvalue ($/CCF)between

unprunedand pruned logs, under current and future prices,respectively.

D15,F15 = IncreaseinValue, the undiscounteddifferenceinvalue ($/log) between

unprunedand pruned logs, under current and future prices, respectively.

D16,F16= IRR, the internalrate of returnfor pruningthe butt log, using$/log under

current andfuture prices, respectively.This will be computedonly if a cost

of pruningis entered.

and pruned logs ($/log), usinginterest rate 1 under current andfuture

prices, respectively.

and pruned logs ($/log), using interest rate 2 under current andfuture

prices, respectively.

C18,E18= PNWof butt log (PNW1),discounteddifferenceinvalue between unpruned

D18,F18 = PNWof butt log (PNW2), discounteddifferenceinvalue between unpruned

C19,E19 = PNWper acre (PA1), PNW for the butt logon a per acre basis, using

interest rate 1 under current andfuture prices, respectively.

D19,F19 = PNWper acre (PA2), PNWfor the butt logon a per acre basis, using

interest rate2 under current andfuture prices, respectively.

The summary results table (fig. 4) also includes a variablefor user convenience in

describingthe regime:

AG4 = IN/DEC, average inchesof growthper decade.

A l 4 = YRS SINCE PRUNING,difference inyears betweenthe age at the time of

pruningand at harvest.

14
AppendixC:

LogDiameters

Calculations

Product Value

Calculations

Figure1(block 4a) shows the sectionof the spreadsheet containingthe equations

needed to computethe insidebark diameters of the 16.5-footbutt log. Thesevalues

are usedin equations predictingvolume for the log, both at the time of pruningandat

harvest. The percentageof clear volume (% Clear or % C) is calculatedas the difference between the volume of the logat harvest and the volume of the log at thetime of

pruning.

A tree profile equation was usedto predict d.i.b. at any point onthe stem. A correction

factor for initialoverestimationsof the inside bark diameters was then appliedas in

Czaplewski and others (1989).The independent variables neededto makediameter

predictionsare diameter at breast height (d.b.h.) andtotal height, bothat the time of

pruning (cells B7and C7)and at the time of harvest (cells E7 and F7).Stump height is

set at1foot with a log length of 16.5 feet. To meet user specifications, these variables

can bechanged manually in cellsAK8 throughAL8 andAM8 throughAN8 for the

pruned butt log at time of harvest and the knotty core at time of pruning, respectively.

We recommend, however, that these variables not bechanged, becausethe recovery

data are basedontrees prunedto 17.5feet, which allowsfor a 1-foot stump and a 16-

foot log plus one-halffoot for trim.

The recovery data are used along with lumber pricesand logdescriptionsto determine

the regressioncoefficientsneededfor predictingthe value of butt logs in a regime (see

appendixE). Productvalue per hundredcubic feet ($/CCF) of logvolume is calculated

by computing the total value of products (lumber, chips, and sawdust) manufactured

from each log inthe data set. The $/CCF value, under both current andfuture price

input, isthen usedas the dependent variable in regressionprocedures. Independent

variables are logdiameter and percentageof clear wood. The storedregressionoutput

is showninblock 4b of figure 1,The modelforms for the value of unprunedand pruned 

logs are in appendix E. The equationsalso are shownwiththe product value output

tables inthe spreadsheet (cell A50).

The resultantequation coefficientsare usedwith the small end d.i.b., as calculated

from the user’s input tree description, to determinethe value for unprunedbutt logs.

The valuefor pruned butt logs, giventhe user’s tree description, usesthe calculated

percentageof clear wood (%C),as well asthe interactionbetween%Candthe calculatedd.i.b. These equationsallow the product valuetables (cellA50) and individual

regimeresults (cellA8) to be calculated.The generic product valuetables use a range

of diameters and clear wood percentagesand give users a feel for the rangeof data

the pruningmodelis basedon, as well as a toolto gaugethe range of returns their own 

regimesmay produce.

15
Appendix D:

Macro Features

For ease in use, the spreadsheet containsfour macrosthat executethe calculations and

give resultsasfound infigures 2,3, and 4. These macros can be runfrom anywhere in

the spreadsheet andwill returnthe user to the same screenfrom which the macrowas

evoked. For ease in runningthe program, brief instructionsfor operatingthe program

havebeen includedinthe spreadsheet (cell I112), and a copy also can befound in

appendix A, part 1.

Lumber prices are enteredin cell locationsE27through E48for current prices and F27

through F48for future prices. Once entered, the macros can be executedto calculate

new product value equations basedon these prices. For equations usingcurrent prices,

holddownthe "Alt" key and press "c", and for those usingfutureprices, hold"Alt" while

pressing"f". The new regressioncoefficientsare calculatedand reported in block 4b as

shown infigure 1.These coefficientsare usedto generateestimatesfor the product

value ($/CCF)tables startingat cell A50 andfor the $/CCF values found inthe individual

regime resultssection (cellsA8 through H20).

Oncethe product value ($/CCF) informationhas been generated, the tree descriptions

(regimes) canbe entered (cellsA4 through H7).After this is completed, the spreadsheet

is calculated. Lotus 1-2-3 does this for the userthroughthe F9function key. The individual results section has now been updated.To store these results intothe summary

resultstable so that more runs can bemade, hold downthe "Alt" key and press "a".

Oncethis is completed,the user will find an abbreviatedversionof the individualresults,

as well as the user's input, copiedunder the last linefound inthe summary resultstable

(locatedin cells I5 throughAH105).This is a convenient way to summarize and store

resultsfrom a series of analyses. To break upthe results, users may want to include

data headings inthe summary resultssection beforeeach runor set of runs is entered

and copiedover. The headingmust be enteredincolumn I to avoidbeingoverwritten

whenthe "Alt A" macro is executed.

These resultscan begraphedtofacilitate comparisonof alternativeregimesor assump

tions. A macroshowing examples of possiblegraphs can be evokedby holding"Alt "and

pressing "g". The graphs availablethroughthis macro includethe productvalue tables

for current and future prices (cellA50) as well asfour graphs from the example regime

analyses providedwith the program (locatedinthe summary results table at cell I5).

After selecting a graphto view, press "enter" to make another choice. To exit this macro,

choosethe quit option, andthe screenwill returnto where the user was whenthe macro

was first executed.

The user can makegraphs similar,to those shown (see"Interpretation"intext) by followingthe Lotus 1-2-3manual proceduresfor graphing. An example of creatinga new graph

would beto first clear oldsettingsby pressing"/","GRAPH", "RESET", then "GRAPH".

Now use "X"to specrfy a rangefor the X-axis, and "A"through "F" for the Y-axis ranges

(up to six linesof data can be shownonthe graph). Use the "."(period) to anchor the

cursor and set the range. The "OPTIONS" command letsthe user addtitles and other

labelsto the graph andspecify formats. Use "Alt G" to see graphing examples.

The product value graphs will be updatedeachtime new prices are input andvalue

equations generated;the regimeexamplegraphs are fixed, however. If the regime

examplesprovidedwith the programare erased, the graphs may no longer be

that is, if users erasethe examples from the summary resultstable andthenfill that

spacewith their own analyses, graph variable ranges will needto be updated if users

wish to makesimilar graphs withtheir own results.

16
Appendix E:

RecoveryData

Lumber recovery datafrom a recent study formthe basisfor estimatinglogvaluesfor

prunedand unpruned young-growthponderosapineinthe PP PRUNE spreadsheet. A

brief description of the study, including basic stand information, range of data, types of

products produced, and analyses conducted, are presentedbelow. A completedescription of the study is available (Cahill 1991).

PrunedSample Pruned trees were selectedfrom the PringleFallsExperimentalForest incentral

Oregon. Stand age at thetime of pruning (1941) was 55 years; Meyer site index was 78

at 100years. Trees included in the study were harvestedin 1988;thus 47 years of 

growthhadoccurredsince pruning. Pruned trees were selectedby the amount of growth

that occurred since pruning, andto representthe rangeof sizes prunedin 1941.Tree

d.b.h. at the time of pruningrangedfrom 6 to 18 inches; d.b.h. at the time of harvest

ranged from 13 to 25 inches.A total of 98 pruned16.5-foot logs were selected.

Logdiameters andthe diameter of the knotty corewere measured to the nearest onetenth of an inch. The coreof knotty, unpruned wood was identifiedby countingannual

rings back to the year of pruning.The proportionof clear wood (% Clear) formed after

pruningwas estimatedasthe ratioof clear woodto total logvolume:

x 100 total cubic logvolume - volume of knotty core % Clear = total cubic logvolume

This estimate of clear shell includes an unknown amount of massed pitch, occluded 

bark, and distorted graindeveloped duringthe healingof branch stubs. 

Unpruned Control

Sample

Sixty unprunedlogs, also 16.5 feet long, were selectedfrom the PringleFallsExperimental Forest. Thesewerefrom the samestand as the prunedtrees. The sample of

unprunedlogswas broadened to includean additional 78young-growthbutt logs. These logs were sampledfrom several young stands inthe Cascade Rangeof central

and southernOregon; they were processed inthe same mill and at the sametime as

 the logsfrom PringleFalls.We decidedto combinethe two sources of unpruned logs

after statisticalanalyses indicatednosignificant differences inlumber volume or lumber

grade recovery. 

Table 1 showsthe range in% Clear, range inradialgrowth, andthe number of pruned

and unpruned logs by logdiameter for the logs included inthis study. Usersof the PP

PRUNEspreadsheet programshould take careful noteof this table and determine if

regimesunder evaluationfall inthe category of predictionor extrapolation.

Processing

Analysis

The logswere processed ina millequippedwith a double-cut band saw,twin-band

resaw, edger, andtrimsaws. Eachpiece of lumber was identifiedwith the log it originatedfrom. The mill produced4/4and 5/4 lumber inthe Select, Moulding,Shop, and

Commongrades. All lumber, except the Shop, was kiln-dried, surfaced, andgraded;

Shop lumberwas dried butwas gradedinthe rough-dry condition. Grading was supervised by inspectorsfrom the WesternWood ProductsAssociation (WWPA) according

to WWPA grading rules (WWPA 1981).

Regressionanalysiswas usedto determineappropriate modelforms for the prunedand

unprunedlogs inthe data set. Average log value per hundredcubic feet of logvolume

(QCCF) was usedasthe dependent variable. Logvalue is defined as the value of lumber, chips, andsawdust producedfromthe individual logsinthe sample. Logdiameter

was used as the independentvariablefor the unprunedlogs;log diameter, % Clear, and

17
Table 1-Range in% Clear, range in radial growth, and the number of pruned

and unprunedlogsby log diameter

the interactionbelweendiameter and % Clear were usedas independentvariables for

the prunedlogs. The analysis indicatedthefollowingmodelsconsistently "best "at representingthe data:

Unpruned:

Pruned:

$/CCF = B0 + B1(1/dib)

$/CCF = B0 + B1(% Clear) + B2 (% Clear/dib)

where:

dib is small-end diameter of the log;

$/CCF is product value per hundredcubic feet of logvolume;

% Clear isthe proportionthat is clear wood; and

B0 ,B1, B2 ,are regressioncoefficients.

The generaltrends were consistent with other recovery studies on prunedand unpruned

logs. Inthe unpruneddata, averagelogvalue increasedas diameter increasedbecause

more lumber per unit of logvolume is recovered in largelogsversus small logs, andthe

opportunity to recover morevaluableitems (wideCommons, Clears, and Shops) increases with logsize. Trends for the pruned logsshowed similar trends with diameter

but also indicatedthat logvalue increasedas the proportionof clear wood increased.

The recovery informationfor each log inthis study (lumber volumes by lumber grade

and chip and sawdust volume) is includedinthe spreadsheet program. After users input 

lumber, chip, and sawdust prices relevant to them, new coefficients are estimated with 

the model forms shown above. These coefficientsare usedto estimate averagelog

values inthe economic analyses of pruning. It should be notedthat the recoveryinformationfrom this study is somewhat biasedagainst pruningfor two reasons: First, the

pruningconductedat PringleFallswas done at age 55; in general it is perceivedthat

pruningwould becarriedout earlier instand growth. Second, the sawmill was oriented

towards productionratherthan recovery of the maximum amount of clear wood. Mills

handling large numbers of pruned logs inthe future would likely try to maximizethe

recovery from the clear shell portionof the log.

18

* U.S. GOVERNMENT PRINTING OFFICE:1992 - 691000/60019
Bolon, Natalle A.;FIght,Roger D.;Cahlll,James M.1992.PP PRUNE users

guide. Gen. Tech. Rep. PNW-GTR-289.Portland,OR: U.S. Departmentof

Agriculture, ForestService, Pacific Northwest ResearchStation. 18 p.

The PP PRUNE program allows usersto conduct a financial analysis of pruning

ponderosa pine (Pinus ponderosa Dougl. ex Laws.). The increase in productvalue

and rate of returnfrom pruning the butt 16.5-foot log can be estimated. Lumber

recovery informationis based on actual mill experiencewith pruned and unpruned

logs. Users supply lumber prices by grade, the cost of pruning, andtree descriptions from growth andyield information. The program estimates the difference in

value for trees and standswith andwithout pruningandthe differencein present

net worth from adding pruningto a given regime. The Lotus 1-2-3spreadsheet

programwas usedto develop PP PRUNE. Users needa basic knowledgeof

spreadsheetsto usethis program.

Keywords: Ponderosapine, pruning, forest product value, product recovery,

~ simulation.

The ForestServiceof the U.S. Department of

Agriculture is dedicatedto the principleof multiple

use managementof the Nation’sforest resources

for sustainedyields of wood, water, forage, wildlife,

and recreation.Through forestry research,

owners, and management of the National Forests

and NationalGrasslands,it strives_as directed by Congress_to provideincreasinglygreater service

to a growingNation.

The U.S. Departmentof Agriculture is an Equal OpportunityEmployer.Applicantsfor all Department

programswill begivenequal consideration without

regardto age, race, color, sex, religion,or national

origin.

Pacific Northwest ResearchStation

333 S.W. FirstAvenue

cooperationwith the States and privateforest

P.O. Box

Portland,Oregon 97208-3890
U.S.Department of Agriculture

Pacific Northwest ResearchStation

333 S.W. First Avenue

P.O. Box 3890

Portland, Oregon 97208

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