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A StudyofContributing actorsSa eed R. Mehmood and Daowei ZhanOver the past few decades, he number of nonindustrial private forest landowners in theUnited Stateshas been ncreasingwhile the averagesize of parcelshas been decreasing.Thistrend is often referred o as orest parcelization.Thisarticle reviews he causes fparcelizationsuggestedn the existing iterature and attempts o provide some empirical evidenceconcern-ingtheir validity. Death,urbanization, ncome, egulatory uncertainty,and inancial assistancefor landowners are found to have significant mpacts on the change n averageparcel size nthe United States.

ent, these wo conceptsare closely e-lated. For example,as the number oflandownersncreases,andowners' tti-tude and objectivesbecomemore di-verse.Some andowners may converttheir forestlands o other uses,whichleads o forest ragmentation.Keywords:ragmentation;onindustrial rivateorest andowners;arcelization;olicy Hypothesized Causesof ParcelizationIn the literature, the causes of

parcelization (and fragmentation, asthe distinction '!Vasnot made until re-cently) can be divided into two groups:supply and demand. On the supplyside, the drivers are death, taxes, anduncertainty (DeCoster 1998). The ef-fect of death on parcelization is oftentwofold: (1) When the original ownerdies, the land may be divided amongthe heirs and (2) part or all of the landmay be sold to pay estate and inheri-tance taxes. Forestlands also are subjectto property taxes, and if the tax rate ex-ceedsor approaches he appreciation inforest value, the landowner may find itmore profitable to put part or all of theland to a higher-valued use (Argow1996). Increased uncertainty aboutowning forestland becauseof environ-mental regulation is another importantfactor. Insecurity abo~t property rightshas been linked to decreasesn produc-tivity (Zhang 1997, 1999) and loss in

ship of parcels f less han 100 acres. fpresent trends continue, by the year2010 about 95 percent of the nation'sprivate forest ownership will be inparcels of less than 100 acres (De-Coster 1998). This generalshift froma few landownerswith large holdingsto many landowners with smallerholdings is known as parcelization,and t can havea significant mpact ontimber supplies. ncreasesn harvest-ing and transaction costs,and the di-versity of landownerobjectives nd at-titudes toward forest management, llcontribute to this impact.This article explores he magnitudeand importance of factors nfluencingforest parcelization in the UnitedStates.The terms parcelization andfragmentation often have been usedinterchangeably. But fragmentationstems from the concept of "islandbiogeography" firSt introduced byMacArthur and Wilson in 1967(Luloff et al. 2000). It refers o foresthabitats becoming isolated islandsacross he landscape. lthough differ-

n estimated 393 million acresof forests n the United States- J..are privately owned. About 59percent of all private ownersare ndi-viduals who are known as nonindus-trial private forest (NIPF) landowners(Birch 1996). NIPF lands currentlysupply about half the country's ound-wood timber supply,and this numberis expected o rise o about 60 percentby the year 2030 (Harrell 1989). Be-causeimber supply rom public forestshas dropped significantly and demandis rising, NIPF landsareunder ncreas-mg pressure.

Studieshave ound that timber sup-ply has a positive relationship withholding size (e.g., Binkley 1981;Greeneand Blamer 1986;Romm et at.1987). However, the averageparcelsizehasbeensteadilydeclining and thenumber of forest andownershasbeenincreasingsince the early 1900s (De-Coster 1998). In more recent years,forest ownership has grown 1.6 timesfaster than the population, and mostof this increase asbeen n the owner-Right: By he year2010.nearly 95 percentofprivateorestownership ill be n parcelsof ess han100 cres.

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To obtain a measure or parcelization,we calculated he changeof averageNIPFparcel size between 1978and 1994. For each state, andownerswereaggregated into six parcel size classes: 1-9, 10-49, 50-99, 100-499,500-999, and more than 1,000 acres. Medians or these classes were 5,30, 75, 300, 750, and 1,000 acres, respectively.Using hese mediansandthe numberof landowners n each size class, the weighted parcel size av-erage was calculatedas follows.

Weighted size average= C5*n1) + C30*n2) + C75*n3) + C300*n4)+ C750*ns)+ C1000*n6)]/Nwhere n1, n2, ... n6 are the number of landowners in each size group, and Nis the total number of NIPF landowners in the state. The dependent variablewas then obtained by subtracting the 1994 value from that of 1978. Thisprocedure ensures that most dependent variables are positive Casaverageparcel size decreased in most of the states) and thus avoids possible con-fusion in explaining the results.

properties are nonexistent. Perhaps heavailability of data in the future will fa-cilitate further research. In the mean-time, our study used a proxy to repre-sent taxes. In addition, the 1978 dataon NIPF landowners are not as strongas those of 1994; for some states, the1978 survey used a smaller sample size,resulting in relatively weaker data com-pared to 1994 (Birch 1996).

forestlandvalue (Zhang, n press),butnever o parcelization.However,someNIPF ownersareweary of current andanticipated land-use regulations(LouisianaSAF Policy and LegislativeCommittee 1996; Rose and Coate2000). This increased nsecurity maymake nvestment n forestland appearunattractive, hus contributing to frag-mentation.On the demand side are lifestyleand urbanization.To live in or aroundthe woods appears o be a growinglifestyle trend (DeCoster 1998), andthis encourageshe saleof forests o beused or residentialpurposes. arlowetal. (1998) and Befort et al. (1988) havedocumented he effectsof urbanizationon land-usepatterns,and other studieshave also ound the impactsof urban-ization to be significant (e.g.,DeForestet al. 1991; Shands1991; Harris andDeForest1993).Despite ts importance, he issueofparcelization has never been exploredempirically.Our study s a first attemptto empirically investigate he signifi-cance nd magnitudeof all these ausesidentified in the literature. However,our efforts were marred with difficul-ties from the lack of appropriatedata.For example,although nheritanceandproperty taxes avebeen dentified asadriving force behind fragmentationand parcelization, state-level nheri-tance and property tax data for forest

values for 1978 and 1994. The result-ing number for each state servesas ourdependent variable (see Calculation ofthe Dependent Variable").

Most of the independent variablesare measured as changes as well, ob-tained simply by subtracting the 1978value from that of 1994. The first in-dependent variable measures thechange n death rate per thousand peo-ple in each state. Becausean increase ndeath rate raises the likelihood ofparcelization, we expect this variable tohave a positive relationship withchange in averageparcel size.

The second variable captures theimpact of taxes on parcelization. It ismeasured as the collection of estateand inheritance taxes per NIPF acre ina state. The data for this variable con-tains taxes collected on all types ofproperties and assets, not just forestproperties. Becausedata on estate andinheritance taxes collected from forestproperties are not available, we use hisvariable to capture possible impacts ofboth estate and inheritance taxesState-level property tax data on forestparcels are also nonexistent. At the be-ginning of this study, we consideredusing the change in property tax ratefor farmland, but later decided againsit because axation on farmland is sig-nificantly different from that onforestland. Estate taxes also have anobvious connection to death. Al-though we include a separate variableto capture the impacts of death, thetax variable may capture some of theimpacts as well. We expect the tax vari-able to have a positive sign.

The third variable represents thechange in the percent of urban popu-lation. This variable is included tocapture the impacts of the generaltrend of urbanization and possiblechange in lifestyle in the nation. Be-cause urbanization is likely to increaseboth fragmentation and parcelization(Befort et al. 1988), we expect thisvariable to be positive.

The income variable represents thechange in median family income (inreal 1989 dollars) betWeen 1969 and1989. A higher income makes lifestylechanges affordable, enabling people topurchase bigger houses away fromcities. This may eventually contribute

Empirical ModelWe assumed a linear relationshipbetween the change in average parcelsize n each state (except Alaska, whichwas excluded from our data set) and agroup of variables representing thecauses of parcelization. The indepen-dent variables include the five causesofparcelization and fragmentation docu-mented in the literature: death, taxes,income, uncertainty, and urbanization.In addition, we decided to test the sig-nificance of two other factors, timbermarket and state support of NIPFlandowners. These two factors, al-though not identified in the literature,may have significant impacts onparcelization.Our data set features 49 observa-tions spanning the years 1978 to 1994.For the dependent variable, theweighted averageof parcel size s calcu-lated for each state. Then, the changein average parcel size is calculated byobtaining the difference between the

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ment, thereby increasing fragmenta-tion. We thereforeexpect his variableto havea negative ign.Mean

elasticity

Explanatory variable

Figure 1.Representation f elasticities orsignificant explanatoryvariables.of stringent land-use regulations. Theinsignificance of the forest industriesvariable implies that the hypothesis ofa negative relationship between astrong timber market and parcelizationcannot be accepted. The dummy vari-able representing the presence of cost-share programs is also significant, im-plying that cost-share programs mayrestrict parcelization or fragmentationor that they at least may slow down theprocess.This may have important pol-icy implications.To represent the impacts of the sig-nificant explanatory variables, elastici-ties at the mean of variables are calcu-lated and presented n figure 1. Becauseelasticities are free from units, the im-pacts of different variables can be com-pared to one another effectively. Theincome variable comes out to be themost elastic, with a value of 1.54. Fi-nancial assistance programs are nextwith an elasticity of -0.54. The envi-ronmental voting index and urbaniza-tion have modest elasticities of Q.47and 0.32, respectively, and the deathrate has an elasticity of 0.03. Compar-ing these values, we can conclude thatthe income variable has about threetimes as much impact as do financialassistance programs and uncertainty,and almost five times as much impactas does urbanization.

to fragmentation, so we expect the in-come variable to have a positive sign.

The impact of uncertainty is cap-tured by a variable that represents thechange in the environmental votingscoresassigned o each state's epresen-tatives to the federal legislatures by theLeague of Conservation Voters (LCY).The scoring is between 0 and 100, with100 being the most "environmentfriendly" voting record. Because a leg-islator's voting behavior represents, atleast n part, his or her constituents' in-terests, the higher the score the moresympathetic the constituents are to en-vironmental causes. Because this mayincrease the likelihood of stringent en-vironmental regulations in these partic-ular states, landowners in these statesmay perceive land-use investments asrisky. Therefore, as a state's environ-mental friendliness increases, risk anduncertainty associatedwith forestry op-erations may also increase, which inturn may encourage some landownersto sell all or part of their land and in-vest in other assets. The variable istherefore expected to be positive.A variable that repr:esents thechange in the contribution of forestindustries in gross state products isalso included in the model. If the for-estry sector is not important to astate's economy, the number of forestindustries in the state will be small,making the timber market less active.The absence of a well-developed mar-keting channel may provide an incen-tive for landowners to use their landfor purposes other than forestry. A re-duction in the contribution of the for-estry sector is expected to reduce aver-age parcel size.The final variable in the model is abinary dummy (meaning the variablecan only take the value of 0 or 1) thatrepresents the presence of a cost-shareprogram in a state. Financial supportfor landowners could have some posi-tive effect on forest management (Blissand Martin 1990; Lee et al. 1992;Zhang and Flick, in press) and mightprevent delays n reforestation (Bullardand Straka 1988) as it enhances forestlandowners' financial returns. An ab-senceof funds may give landowners anincentive to put the land to higher-val-ued uses such as commercial develop-

ResultsThe model is estimated by the ordi-nary least square (OLS) method (see"The RegressionMo.del," p. 34). The ftest on the model is significant at the 1percent level. The r-squared value forthe model is 0.58, which means thatthe explanatory variables explain about58 percent of the variations in the de-pendent variable. All of the indepen-dent variables show the expected rela-tionship with the dependent variable.Urban population, income, environ-mental voting index, and the cost-shareprogram variables are positive and sig-nificant at the 5 percent level. Thedeath rate variable is also positive as ex-pected, and significant at the 10 per-cent level. The variables representingtaxes and the forest industries are notsignificant.The significance of the death ratevariable is consistent with the litera-ture in that death is one of the majordriving forces behind fragmentationand parcelization (DeCoster 1998).Barring large measurement errors, theinsignificance of the tax variable im-plies that estate and inheritance taxesdo not have a significant impact onparcelization. However, this resultshould be considered with cautionsince we used a proxy that is not spe-cific to forest properties. The signifi-cance of the change in the percent ofurban population is also consistentwith the claims in the literature thaturbanization inspires changes n land-use patterns (Befort et al. 1988). Esti-mates for the income variable, on theother hand, imply that an increase infamily income contributes to par-celization. A higher income increasespurchasing power, which enables peo-ple to afford lifestyle changes. Hence,this variable captures the impacts ofchanges n lifestyle trends and, to someextent, urbanization.The environmental voting indexvariable comes out as significant, im-plying that landowners in states withenvironmentally friendly constituentsmay perceive investment in forestlandas more risky becauseof the likelihood

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to meet the nation's wood fiber de-mands, we must find a way to makeforestry-relatedegulation essonerousand to attract and retain these and-owners.Forest ragmentationand parceliza-tion are mportant issuesn the nation'sforest policy. Considering currenttrends, heir importance s likely to in-tensify (DeCoster 1998). However, nsharp contrast to their importance,studieson these ssues re are.Furtherresearchon the processof parceliza-tion-its causes nd consequences-will help policymakersunderstand heprocess o they can alleviate he prob-lems associated ith it.

A.C. NELSON. 1991. Timberland downrown? Sourb-em foresr resources along rbe urban-rural continuum.In Proceedingsof a symposium on ecological and classi-fication: Application to identify the productive potentialof southern forests, eds. D.L. Mengel and D.T. Tew.Asheville, NC: USDA Forest Service.

GREENE, J.L., and K.A. BLATNER. 1986. Identifyingwoodland owner characteristics associared with tim-ber managemenr. Forest Science32(1):135-46.

HARRELL, J.B. 1989. Federal and state cost-share pro-grams for forest farmers. Forest Farmer Nov.-Dec.:20-27.

HARRIs, T., and C. DEFoREST. 1993. Policy implicationsof timberland loss, fragmenrarion, and urbanizationin Georgia and the Southeast. In Proceedings of the1993 Southern Forest Economics Workshop, ed. D.N.Wear. Durham, NC: Duke University.

LEE, KJ., F. KAISER,and R. AuG. 1992. Substitution ofpublic for private funding in planting sourbern pine.Southern Journal of Applied Forestry 16(4):204-208.

loUISIANA SAP POLICYAND LEGISLATIVECOMMITTEE.1996. Privare forest practice regulation: Questions insearch of reasonable rules. Journal of Forestry 94(5):10-13.

LUWFF, AE., J.C. FINLEY, and J. MELBYE. 2000. Socialissuesand impacts associated with land parcelization.Paper presented at rbe Fragmentation 2000 Confer-ence, September 17-20, Annapolis, MD.

ROMM,J., R. TUAWN, andC. WASHBURN.1987. Relat-ing forestry investment to rbe characteristics of non-industrial private forestland ownets in Norrbern Cal-ifornia. Forest Science33(1): 197-209.

ROSE, R., and J. COATE. 2000. Reforesration rules inOregon: Lessons learned from strict enforcement.Journal of Forestry 98(5):24-28.

SHANDS, WE. 1991. Problems and prospects at theurban-forest interface. Journal of Forestry89(6):23-26.

ZHANG, D. 1997. The in/luenceofrbe form of tenure onreforestarion in Btitish Columbia. Forest Ecology andManagement 98:239-50.

-. 1999. Endangered species nd timber harvesting:The case of the red-cockaded w/!odpecker. Workingpaper. Auburn Univetsity, School of Forestry andWildlife Sciences.

-. In press. Faustmann in an uncertain policy en-vironment. Forest olicy nd Economics.

ZHANG, D., and W FLICK. In press. Sticks, carrots, andreforestationnvestment.Land conomics.

SayeedR. Mehmood is research ssociateand Daowei Zhang (zhangdl@auburn.edu) is associate rofesso1; chool of For-estryand Wildlife Sciences, uburn Uni-versity, I 36849.

Conclusions nd DiscussionThe resultsof this study show thatdeath, urbanization, income, regula-tory uncertainty, and financial assis-tance or landowners re ound to havesignificant impacts on the change naverage arcelsize n the United States.These esultsmay have mportant pol-icy implications. First, not much canbe done from a policy standpointabout rising ncome and increasing r-banization, and only careful planningat the local level may help slow downthe parcelization rocess.Second, financial assistancepro-grams,such as cost-sharing, lso seemto havea significant mpact on parcel-ization; cost-share rogramscould beused as a policy tool to slow downparcelization.This variablealsohas hesecond-largest elasticity. Cost-shareprograms,although controversial,mayhave wo impacts: (1) They may causelandownerswho did not originally in-tend to actively manage heir land todo so, and (2) by increasing he returnof forestry nvestment, heseprogramsmay help retain some and for forestrythat may otherwise have been ost toother uses.Finally, regulatoryuncertainty asso-ciated with owning forestlandalsohasa significant mpact. Owning a pieceofforest is a substantial nvestment. Be-cause f restrictionson forest manage-ment brought about by regulations,forestry may becomea less-attractiveinvestment. This is especially rue forlandowners who intend to managetheir land for wood products. f we are

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34 Reprinted from Western ournal of Forestry,Vol. 99, No.4, April 2001. Not for further reproduction.