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document Historic, archived Do not assume content reflects current scientific knowledge, policies, or practices. C I USDA United states Estimating Total Forest Departmentof Agriculture Biomass Maine, 1995 in ForestService Northeastern Research Station Resource Bulletin NE-142 Eric H. Wharton Douglas M. Griffith Piscataquis Washington 'Andro- ISagadahoc The Authors ERIC H. WHARTON and DOUGLAS M. GRIFFITH are foresters with the Forest Inventory and Analysis unit of the USDA Forest Service's Northeastern Research Station at Radnor, Pennsylvania. Manuscript received for publication 18 August 1997 Acknowledgments We thank members ofthe field crews who collected the data used in this study; the Maine Department of Conservation, Bureau of Forestry, for its assistance; Beverly Grant, who compiled the tables and performed statistical verification; and Vickie Sharon and Lynda Hines, who was responsible for administrative and secretarial services. Published by: For additional copies: USDA FOREST SERVICE USDA Forest Service 5 RADNOR CORP CTR SUITE 200 Publication Distribution RADNOR, PA 19087-4585 359 Main Road Delaware, OH 43015 July 1998 have not always kept pace. Many methods for measuring biomass have been explored duringthe Abstract past couple ofdecades, butthere is little consistency annong them. The relationshipsthat Traditional measures ofvolume inadequately have been developed between commontree describe forest resources. The 1995 Inventoryof measurements and the weightof individualtree Maine's forest lands included estimates oftotal components, determined largely by regression forest biomass based on an evaluation of available equations, include many data-gathering and biomass-estimation techniquesfound inthe analytical techniques. The resulting concern over literature. When applied to the forest resource their applicability iscompounded bythe factthat inventory of Maine, these regression equations many ofthe regression equations now being used yielded an estimateof morethan 900 million dry are designedfor afew common species. tons of biomasson timberland, and nearly 928 million dry tons of biomasson all forest land. About Since It appears likelythat research on 45 percent ofthe biomasswas in growing stock, the environmental interactions, sometimeson a global remaining 55 percent was in the branches, foliage, scale, will not only continue but increase in and stumps of growing-stocktrees; cull trees, complexity, and because social and economic salvable dead trees; seedlings and saplings; and factors andtheir interaction have increased pressure shrubs. on ourforest resources, it was necessaryto evaluatethe accumulated procedures forestimating biomass as one meansto more adequately assess Maine's forest resources. Background Keays (1971a, b, c, d, e) published the earliest Since 1928, the USDA Forest Service has synthesis of literature available on biomass measured the Nation's forest resources, supplying estimation. Other reviews ofthe North American information about their nature and condition. In the literature were conducted byYoung (1976) and past, forest inventoriesfocused on volume Hitchcock and McDonnell (1979). Pelz (1987) estimation: cubic feet for growing stock and board reviewed European literature, and there have been feet forsawtimber (these and otherterms are regional reviews forthe Southern (Baldwin 1987) defined in Appendix F). Volume statistics have and Northeastern (Tritton and Hornbeck 1982) proven useful to resource planners and managers United States. The regression equationsthey for quantifying thetimber supply and fortracking describe were evaluated and incorporated intothe changes in thetimber resource overtime. But resource inventory process for Maine. conventional methods for measuring timbervolume do not adequately define conditionsofthe entire forest and, therefore, have limited applicabilitytothe Procedures for Estimating Green Weigiit kinds of assessments required bytoday's resource planners, managers, and researchers. Many factorscontributeto the variation ofweight in trees; certainly moisturecontent is a critical one. In We now recognizethat ourforests are not only a the past, green weight was commonly used bythe source ofwood fortraditionaltimberproducts but Forest Serviceto measure biomass supplies, at also ofwood fiberfor new industrial products and least in the Northeast, simply because green weight nonindustrial products such as fuelwood. In most closely approximatesthe condition ofstanding addition, the nation'sforest resource plays an trees. And because it reflects the economic cost of important part with respect to wildlife habitat, plant removing wood fromthe forest, this measure is diversity, nutrient recycling, and biochemical preferred bythetimber-using industry. However, interchanges so essential to our survival. merchantable-stem biomass may bethe only green- weight statistic ofvalue. Comparisonsto dryweight Overthe years, the complete-tree concept (Young can be made if needed, and yieldsof industrial 1965) has become more accepted even though forest products harvested and resulting residual methodsto measurethe content ofthe wholetree weightscan bedeveloped from them. 1 There are many regression equationstliat predict stem breaks into branches ifthis occurs beforethe thegreen weight oftrees and theircomponents. We minimum diameter is reached. were interested in how wellthese equationspredict Sincethe regional model predictstotal-stem the green weight oftrees in areasforwhich biomass, adjustments had to be madeto quantify equations had not been developed. Tritton and merchantable-stem biomass (growing-stock Hombeck (1982) indicatedthat while most biomass biomass). First, conversions were applied that equations for northeastern tree species have been relatetotal-stem biomass (the parameterpredicted developed locally and their use has been relatively bythe regional model) to aboveground tree biomass limited, some may be useful forpredicting weights of on a green-weight basisfrom regression equations treesoverextensive geographic regions. developed by Monteith (1979). Then, conversions fromthe same study were appliedthat relate Hocker and Early (1983) argued against using abovegroundtree biomass to merchantable-stem equationsto predict weights oftrees over large biomass (the parameterof interest). The regions. However, a study byJacobs and Monteith relationshipoftotal-stem and merchantable-stem to (1981) has shown thatthe weights of identical aboveground tree biomasswere averaged by northeasterntree species are similar in different evergreen and deciduous species, and by standard regionsofthe Northeast. And resultsfrom a more Forest Service stand-size classes (Table2). detailed study (Barrett and Jastrembski 1990) based on an analysisof indicatorvariables showed that In the regional model, total tree height is used as an differences in tree green weight between locations independentvariableto predict biomass. This is a may not be important enoughto preclude using limitation becausetreesoften are measured onlyto regional modelson a wide geographic scale. a certain merchantable height, as isdone by Forest Sufficient research has been conducted to assure us Inventory and Analysis. The regional equations ofthevalidity of using regional biomass equations. described are unusable unlesstotal tree height can be measured orpredicted. Regional Regression Equations We usedthe regional regression equations Table 1. Total stem-weight regression developed by Barrett and Jastremski (1990) from coefficients forselected species sources in New Hampshire, New York, Ohio, West Virginia, and Michigan. Y=bo+bi{D2H) The form ofthe regional regression equation is: Y=greenweight(inpounds) D=diameteratbreastheight(ininches) Y = bo + bi(D2H) H =totaltreeheight(infeet) wherethe dependentvariable Y istotal tree-stem Coefficients Species biomass (in green pounds), and the independent bo b^ variables D and H are, respectively, diameter at breast height (in inches) and total tree height (in Hemlock 45.05 0.1856 feet). Regression coefficients were developed for 14 species (Table 1). Specieswere segregated into Spruce 235.95 0.1378 evergreen and deciduous species. Species for Pine 116.92 0.1547 whichthere was no specific biomass regression Fir 113.77 0.1603 equation were matched withthosethat did (called Oak 51.28 0.1797 key species) based on green-weight densities Maple 56.09 0.1663 Hickory -58.58 0.2046 (Appendix A). Basswood 19.95 0.1344 The Forest Inventory and Analysis unit ofthe Forest Aspen 53.47 0.1549 Service equatesthe merchantable stem to growing Cherry -19.37 0.1753 stock, that is, thetree bole between a 1.0-foot stump Birch -47.78 0.2076 height and a specifiedtop. The growing-stocktop is Yellow-poplar -39.77 0.1439 at a minimum 4.0-inch diameteroutsidethe bark on Ash 16.81 0.1496 Beech 34.69 0.2245 the central stem, orthe point at whichthe central 2 Table 2. Total-stem biomass and merchantable-stem biomass as a percentage of aboveground tree biomass, green-weight basis Total stem Merchantable stenn Stand-size class Evergreen Deciduous Evergreen Deciduous Poletlmber 0.7617 0.8010 0.6503 0.7269 Small sawtimber 0.8032 0.7990 0.7695 0.7737 Large sawtimber< 21.0" d.b.h. 0.8194 0.7979 0.8053 0.7852 Large sawtimber> 21.0" d.b.h. 0.8235 0.7975 0.8136 0.7884 Total Tree Height coefficientswere grouped withthosethat did based on average height and bole and crown Measuring thetotal height of sampletrees has been characteristics that most closely approximated a considered frequently in statewide inventory speciesforwhich therewas an equation designs. Given the high cost of obtaining tree (Appendix D). information ascurrently collected, we have found the cost of measuring totaltree height to be prohibitive. Yet thevalue of total tree height cannot be Table 3. Total tree-height regression overstated, especially considering its use as a coefficients forselected species parameter in many biomass regression equations. Most equations that predicttotal tree biomass Y=bo+bi (D) +b2(H) incorporate totaltree height. And in some instances, it can proveto be a significant predictorof Y=totaltreeheight(infeet) biomass. Because ofgreat differences in height D=diameteratbreastheight(ininches) overthe range of some species, the measureof H =merchantableheight(infeet) total tree height often is seen as essential. Coefficients Cunia and others (1984) developed a procedure for Species bo b2 predicting total tree height from diameter and merchantable-height measurements. Developed to simulate populations oftreesto test sample designs, Red maple 21.425 0.0000 1.03546 this procedure can be applied to actualtree Sugar maple 33.477 0.0000 0.85822 dimensions. Yellow birch 46.935 0.0000 0.48425 Beech 24.479 0.0000 0.93307 The form ofthe model is: White ash 30.779 0.0000 0.87421 Blackcherry 31.520 0.0000 0.78366 Y = bo + bi(D) + b2(H) Basswood 39.430 0.0000 0.66960 Yellow-poplar 39.572 0.0000 0.63497 where the dependentvariableY istotal tree height White oak 33.639 1.5880 0.29821 (in feet); the independent variables D and H are, Scarlet oak 40.751 0.0000 0.53881 respectively, diameter at breast height (d.b.h., in Chestnut oak 41.585 0.0000 0.48834 inches) and merchantable height (in feet). Northern red oak 40.805 0.0000 0.62504 Consequently, we could estimate total tree height Blackoak 29.915 0.0000 0.79821 from measurements we already had. Trembling aspen 9.760 0.0000 1.11161 Balsam fir 19.818 0.0000 0.76839 Regression coefficients for 17 species were used Red pine 17.977 0.0000 0.85621 (Table 3). Species with no specific regression White spaice 11.924 0.0000 0.93523 3 Procedures for Estimating Dry Weight Three sets of regression equations were chosen Dryweight is more consistent overtime, avoiding from the literature that covered the greatest range of seasonal variationsthat ocx^urwhen trees are species encountered in the Northeast: Young and measured in terms of green weight. Thedry-weight others (1980) developed models for species in measure also provides a more common base, Maine, Wiant and others (1977) developed models yielding an easier solutionto environmental forspecies in West Virginia, and Monteith (1979) questions such asthose relatedtothe cart)on developed models forspecies in New York. These content offorests. Scientists prefer dry weight when models predict abovegroundtree biomass. Growing accessing different biomass components because it stock biomass was estimated by subtracting the allows analysis between trees and othervegetation. portion in branches and foliage which were determined from regression equationsdeveloped by Merchantable-stem biomass is best reported in both Young (1980). green weight and dry weight. However, most other components-branches, foliage, stumps and roots, Equationsdeveloped in Mainewerethe source for culltrees, seedlings and saplings, shrubs, etc.-are all evergreen speciesfound: balsamfir, eastern best reported in dryweight since biomass studies white pine, red pine, spruce, hemlock, northern todaytend to be directed more to vegetation white-cedar, and larch; and forsome deciduous analysis and biodiversity studies. These generally species: red maple, yellow birch, and quaking require biomassto be reported in dry weight. aspen. Equations developed in West Virginia were the source primarilyforAppalachian deciduous For extensive forest surveys, the most important species: hickory, yellow-poplar, blackcherry, white parts oftotal forest biomassto report (Fig. 1) are: oak, scarlet oak, chestnut oak, northern red oak, and blackoak. Equations developed in NewYork •The biomass in the merchantable stem ofgrowing- werethe source forsugar maple, American beech, stocktrees (also called growing stock), which can be and white ash. furtherapportioned into poletimber, sawtimber, and the upperstem portion above sawtimber. The form ofthe models developed in Maine (1), West Virginia (2), and New York (3) are: •Additional sources of biomass in growing-stock trees-branches, foliage, and the stump-root LnY = bo + biLn(D) (1) system-and cull treeswhich together constitute timber. LOG10Y = LOGiobo + biLOGio(D) (2) •The biomass in nontimbertrees, e.g., salvable where Ln isthe natural logarithm, the dependent dead trees, seedlings, and saplings. variableY isdry weight (in pounds), and the independentvariable D isd.b.h. (in inches); and •Other kinds of nontree-related forest biomass, for example, shrubs. Y = bo-hbi(D) + b2(D2) (3) Biomass of Growing Steele wherethe dependentvariableY isdry weight (in kilograms), and the independentvariables D and Growing-stocktrees are live, predominantly sound are, respectively, d.b.h. and d.b.h. squared (both in trees from which it is possibleto harvest commercial millimeters). timber products. When measuring the volume of growing-stocktrees, it is customary to deductthe Regression coefficientsfor 21 species were volumeof rotten cull when reporting board-foot developed (Table 4). Specieswere segregated into volume, andto also deductthe volume of sound cull evergreen and deciduous species. Species for (gradedeductionsthat are still solid wood) when whichthere was no specific biomass regression reporting cubic-footvolume. Rotten cull affectstree equation were matched withthosethat did (called weight, but sound cull does not, so onlythe key species) based on dry-weight densities percentage of rotten cull in a tree is deducted when (Appendix B). reporting tree quantities in terms ofweight. 4 Forest Biomass Biomassof Timber Figure 1. Relationship of total forest biomass components 5 Table 4. Aboveground tree-weight regression been synthesized from the literature and presented coefficients for selected species in tabularformat bythe Forest Service (1984). However, they were developed mostly for LnY=bo+biLn{D) (1) southeastern tree species. LOGioY=LOGiobo+biLOGio(D) (2) Branchbiomass-V^ederived biomass in branches Y=bo+bi(D) +b2(D2) (3) from regression equations developed by Young (1980). By dividing the weight of branches by Y=dryweight(inpoundsorkilograms) abovegroundtree biomass, the proportion of branch D =d.b.h. (in inchesormillimeters) biomass can be determined using averages by evergreen and deciduous species and by stand-size Coefficients Equation class (Table 5). Resulting branch percentages are Species number applied to estimates of aboveground biomass as outlined inthe previous section. Balsamfir 0.5958 2.4017 Foliagebiomass-Th\s component of forest biomass REaesdteprinnewhitepine 00..74105870 22..34846950 hastaken on more importance recently. It has been Spruce 0.8079 2.3316 used as a data input for determining hydrocarbon Hemlock 0.6803 2.3617 emissions and is a critical component of research on N.white-cedar 1.1182 1.9269 carbon sinks and sequestering. Foliage biomass Larch 0.8162 2.2453 can be estimated through thetechnique as outlined Redmaple 0.9392 2.3804 Sugarmaple 5.2480 0.3661 0.0076 forbranches. Average proportions are presented in Yellowbirch 1.1297 2.3376 Table 5. Hickory 1.9338 2.6209 Americanbeech 5.3373 -0.3257 0.0072 Sfump/roof£)/omass-lnformation on stumps and Whiteash 3.2031 -0.2337 0.0061 roots currently seems of littlevalue but might Yellow-poplar 1.5779 2.5153 become more important. This component can be Blackcherry 2.5883 2.4253 Aspen 0.4689 2.6087 estimated bythe technique as described for Whiteoak 1.2892 2.7010 branches. Although root estimates may be poordue Scarletoak 2.6574 2.4395 to incomplete recovery during the development of Chestnutoak 2.1202 2.5344 estimation procedures. Average proportions are Northernredoak 1.6891 2.6598 Blackoak 2.1457 2.5050 presented in Table 5. Cullfrees-These aretrees with morethan 67 percent oftheirvolume deducted due to rot or poor Biomass ofTimber form. As with othertimbertrees, only rotten cull is deducted to determine net weight. Cull trees pose The biomassof growing stock can be extendedto no special problem otherthan thatthe regression include portions of the entire growing-stocktree- equations may not fittrees of poorform. Some of branches, foliage, stumps, and roots. Also included thesetrees may be wolftrees whose biomasscould were cull trees, which along with the biomass of be underestimated because regression equations individual components of growing-stocktrees usually are developed fordominant and codominant comprisethe biomass oftimber. trees. Until regression equations aredeveloped for rough, poorly formed, and similarkinds oftrees, the Bark also could be included but little research has biomass equations now available must suffice. been conducted on the amount of bark biomass contained in standing trees, eitheron a green- or Forest Biomass dry-weight basis. Forthose interested in estimates ofbark biomass, onetechnique isto divide When other kinds of nontimberand nontree estimates of whole-tree wood biomass by estimates biomass, e.g., salvable dead trees, small trees, and of whole-tree wood and bark biomass. Comparative shrubs, are added to the biomass oftimber, we regression equations useful forthis purpose have approach total forest biomass. 6