research article volume and aboveground biomass models for...

Research ArticleVolume and Aboveground Biomass Models forDry Miombo Woodland in Tanzania

Ezekiel Edward Mwakalukwa12 Henrik Meilby1 and Thorsten Treue1

1 Department of Food and Resource Economics Faculty of Science University of Copenhagen Rolighedsvej 231958 Frederiksberg C Denmark

2Department of Forest Biology Faculty of Forestry and Nature Conservation Sokoine University of Agriculture PO Box 3010Chuo Kikuu Morogoro Tanzania

Correspondence should be addressed to Ezekiel Edward Mwakalukwa ezedwayahoocom

Received 7 March 2014 Accepted 14 April 2014 Published 22 May 2014

Academic Editor Guy R Larocque

Copyright copy 2014 Ezekiel Edward Mwakalukwa et al This is an open access article distributed under the Creative CommonsAttribution License which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

Tools to accurately estimate tree volume and biomass are scarce for most forest types in East Africa including Tanzania Basedon a sample of 142 trees and 57 shrubs from a 6065 ha area of dry miombo woodland in Iringa rural district in Tanzaniaregression models were developed for volume and biomass of three important species Brachystegia spiciformis Benth (119899 = 40)Combretum molle G Don (119899 = 41) and Dalbergia arbutifolia Baker (119899 = 37) separately and for broader samples of trees (28species 119899 = 72) shrubs (16 species 119899 = 32) and trees and shrubs combined (44 species 119899 = 104) Applied independent variableswere log-transformed diameter height andwood basic density and in each case a range of differentmodels were testedThe generaltendency among the final models is that the fit improved when height and wood basic density were included Also the precisionand accuracy of the predictions tended to increase from general to species-specific models Except for a few volume and biomassmodels developed for shrubs all models had 1198772 values of 96ndash99 Thus the models appear robust and should be applicable toforests with similar site conditions species and diameter ranges

1 Introduction

Standing volume and aboveground biomass (AGB) are thetwo main measures of forest stocking that are typicallyconsidered within the framework of sustainable forest man-agement and for carbon accounting purposes [1 2] Accurateestimation of tree volume and forest biomass is not onlycrucial for assessing expected yields from commercial andsubsistence harvesting It is also important for carbon storageassessment in relation to global climate change mitigationmeasures [3 4] For this purpose forest biomass can beapplied to estimate carbon stocks and carbon fluxes whenmeasured repeatedly thus providingmeans for estimating theamount of carbon dioxide released into or removed from theatmosphere

However direct measurement of volume and AGB istime consuming costly and usually destructive by natureTherefore the general practice is to estimate volume andAGB

from tree dendrometric characteristics such as diameter andheight using established general or site-specific allometricequations [1 3 5 6] The selection of an appropriate allomet-ric equation is a key element in the accurate estimation offorest yield and stand productivity as well as carbon stocksand changes in stocks [7 8] Unfortunately such equationsoften produce biased results when applied outside the forestarea or region where they were developed If high accuracyis required for quantification and verification of a particularforestrsquos carbon storage or for other management purposesit is therefore recommended to develop local biomass andvolume equations or at least to harvest and measure a fewtrees representing the range of tree sizes typically found inthe forest and use these to check the validity of the appliedequation under local conditions [1 9 10]

In eastern central and southern Africa where miombowoodland is the principal vegetation type only few studiesof this nature have been conducted and tools for accurate

Hindawi Publishing CorporationInternational Journal of Forestry ResearchVolume 2014 Article ID 531256 11 pageshttpdxdoiorg1011552014531256

2 International Journal of Forestry Research

estimation of forest volume and biomass and for carbonaccounting purposes are generally lacking [10ndash12] In Tanza-nia two studies have developed biomass models using datafrom a relatively dry miombo woodland site at KitulanghaloForest Reserve in Morogoro Region eastern Tanzania whichreceives an annual rainfall of about 900mm yearminus1 [13 14]These studies were conducted on the basis of a very limitedsample size (lt30 trees) covering a narrow diameter range(11ndash50 cm) Recent work by Mugasha et al [15] covers awider range of sites (four dry and one wet miombo sites)Yet it only includes a few more trees per site in the threerelatively dry miombo woodland sites 40 trees in ManyaraRegion northeastern Tanzania (854mm yearminus1) 40 trees inKatavi Region western Tanzania (881mm yearminus1) and 40trees in Tabora Region western central Tanzania (771mmyearminus1) In addition the number of species used in devel-oping site-specific models was very low for example 10species for the Manyara site but the general countrywidemodel had adequate species richness (gt45 different species)Having included trees from wet miombo sites which havedifferent growth habits compared to those found in typicaldry miombo areas and considering the large site differencesacross miombo woodlands with respect to climate soilaltitude land form species composition and historical landuse there appears to be a strong need for developing modelsfor sites that receive very little precipitation such as the areasin Iringa Region south central Tanzania (617mm yearminus1) toincrease the accuracy of predicted stand volume biomassand carbon stock in such site types

Miombo woodlands consist of open light stands of adeciduous or semideciduous nature with up to three vege-tation strata upper canopy trees secondary layer (includingthe shrub layer lt8m tall) and herbaceous layer whichconsists chiefly of grasses up to 2m tall [16] The uppercanopy trees can reach heights of 14ndash20m while trees of thesecondary layer may reach 8ndash12m Understory shrubs aremultistemmeddue to fire or stem cutting and tend to cover upto 70 of the ground This vegetation is an important sourceof fuel wood for the majority of people living in miomboareas and due to the large areas that it covers the carbonstocks and sequestration potential of the woodland are high[17 18] Unfortunately previous studies in the miombo didnot include biomass models for understory species (shrubs)[13ndash15]

Although with some limitations due to the large numberof species in tropical forests species-specific volume andbiomass models are often preferred for accurate estimationof forest volume and biomass and for carbon accountingpurposes [19 20] This type of models has been developedfor a wide range of plantation species and in temperateregions where the number of relevant tree species is lowerHowever most types of tropical vegetation are characterizedby dominant species so it has been suggested to develop adatabase of allometric equations for selected dominant treespecies which are particularly important for volume andbiomass estimates as they contribute a large proportion ofthe biomass compared to other species [21] In Tanzaniaspecies-specific volume functions have been prepared for

a few dominantmiombo species in Tabora in thewestern partof the country [22 23] and elsewhere [24]These studies werehowever also based on a very small sample size (lt27) and anarrow diameter range (lt43 cm)

Wood density is a key variable in the estimation oftree biomass [25 26] However none of the above studieshave reported biomass models which take into account thecontribution ofwood basic density in explaining the variationin treeshrub biomass Inclusion of wood density in biomassmodelling has been shown to improve the performance of themodels significantly [25 26]

Accordingly the objectives of this study were to (1)develop volume and AGB allometric equations for threedominant species (Brachystegia spiciformis Benth Combre-tum molle G Don and Dalbergia arbutifolia Baker) and(2) develop general equations for three life form groupstrees shrubs and woody species in general (trees andshrubs combined) The new models will not only helpincrease our knowledge on total aboveground productivity ofmiombo woodlands but also support planning assessmentand development of management strategies for sustainableutilization of the woodlands Furthermore the local biomassmodels developed in this paper will not only add to existingknowledge about the miombo but also support the nationof Tanzania in accurate estimation and reporting of currentforest biomass stocks and their changes over time

2 Materials and Methods

21 Study Site Gangalamtumba Village Land Forest Reserve(GVLFR) is located in central-southern Tanzania (7∘351015840 S35∘351015840 E) about 30 km northwest of Iringa Municipality theadministrative capital of Iringa Region (Figure 1) The area ofthe forest is 6065 hectares and it is managed by the Mfyomevillage which is located in the ward of Kiwele The forestcan be described as dry miombo woodland and the terrainis relatively flat and located 850ndash1300 metres above sealevel The average annual rainfall is (mean plusmn standard error)617 plusmn 17mm (range 448ndash1085mm) and the mean annualtemperature is 198∘CThe soil texture ranges from sandy soilsat low elevations to sandy clay loams at higher elevationswith pH from 57 to 87 GVLFR is a production forest whichallows some commercial forest activities including charcoalproduction firewood collection and livestock grazingmainlyduring the dry season

22 Field Sampling The survey was conducted in August2009 and September-October 2010 and involved harvestingof 142 individual trees (28 species) and 57 individual shrubs(16 species) from a 30mwide boundary zone of 35 permanentcircular sample plots with a radius of 50m (07854 ha)that were distributed across the entire area of the GVLFR(Figure 1) Plots were located along transect lines and thedistance between plots was about 2 km The centre pointsof the plots are identical to those used in a survey thatwas previously conducted in the forest [27] The minimumand maximum sizes of sample treesshrubs were 14 cm and620 cm in diameter at breast height (Dbh) respectively For

International Journal of Forestry Research 3

0 25 5To Iringa

To DodomaIkengeza

Itagutwa

Airport

Mfyome

Kiwele

Luganga

PlotsVillagesDirt roads

Forest roadsGangalamtumba forest reserve

N

Iringa Region

Tanzania

10

(km)

Figure 1 Map of the study area and its location in Iringa RegionTanzania

each tree or shrub felled the following measurements weremade stump diameter 20 cm above ground Dbh crownradius in four directions (north south west and east) heightto first branch and total height Diameter was measured tothe nearest 01 cm using a diameter tape height wasmeasuredusing a Suunto clinometer and crownwidth wasmeasured tothe nearest 001m by tape measure Species were identifiedby a local botanist using vernacular names in the Hehelanguage Scientific identificationwas done by a botanist fromthe herbarium centre at the Silviculture Research Station inLushoto which is part of Tanzania Forest Research Institute(TAFORI) In cases where it proved difficult to identify aspecies in the field voucher specimens were collected andsent to the herbarium in Lushoto for identification

Based on their estimated relative basal area 44 species(both trees and shrubs) were selected as a representativesample of themost common speciesThis selectionwasmeantto cover the widest possible range of diameter classes asrecommended by for example Brown [1] and Husch et al[3] Furthermore to distribute the sample across the forestat least 3 trees and 2 shrubs were felled within each of the 35plots To support data quality checking and error correction asketch of the crown structure of each treeshrubwas preparedin the field and used for marking points of cross-cuttingGenerally the choice of upper diameter limit depends on theutilisation of the wood In this region an important use ofthe wood is for charcoal production and few tree species areused for timber productionThe typical top diameter appliedby charcoal makers in the area appears to be 5 cm and wetherefore prepared models for total volume and biomass andfor commercial volume of stems with diameter ge5 cm

In the field small branches with diameter less than 5 cmwere first removed tied into bundles (piles) and weighed(fresh weight) Subsamples of these piles were selected andbrought to the laboratory for dry weight determination Foreach treeshrub five disks with a thickness of about 2-3 cmwere sampled from the remaining part of the treeshrub(ge5 cm diameter) These were used for basic density esti-mation and their greenfresh weight was measured in thefield Selection of the five disks was based on importancesampling for example [5 28] implying that the selectionof tree sections in which the disks were to be extracteddepended on the estimated proportion of volume in eachsection (probability of selection proportional to volume)This method has been found to yield relatively good resultswith minimal errors and bias compared to the conventionalmethod of sectional weight measurements in the field whichis often costly in terms of labour and time [5]

23 Laboratory Analyses In the laboratory all subsamplesfor twigsbranches lt5 cm (crown wood) and disks extractedfrom stem and branch sections were oven dried at 103 plusmn 2∘Cto constant weight Dried samples were weighed and thebiomass ratio for each pile of twigsbranches was computedas the ratio of oven-dry weight to green weight [5 13] Greenvolume of the sample disks was obtained after soaking thedisks in water for at least four days until they were saturatedUsing the water displacement method the volume of eachdisk was determined [1 29] Basic density (g cmminus3) for eachdisk was determined as the ratio of dry weight (g) to greenvolume (cm3)

24 Data Preparation For each tree the stump volume wascalculated using the cylinder formula and the volume of stemsections and branches with diameter ge5 cm was calculatedusingNewtonrsquos formulaThe volume of twigsbrancheslt5 cmin diameter was estimated using their estimated biomass andthe estimated basic density [30] Commercial volume ge5 cmwas estimated as the sumof stump volume and the volumes ofstem and branch sections to 5 cm top diameter Total volumewas calculated by adding the estimated volume of brancheslt5 cm to the commercial volume This dataset was used fordeveloping volume models for each group of species (1) Bspiciformis (2) C molle (3) D arbutifolia (4) shrubssmalltrees (5) trees and (6) all species (trees and shrubs)

Biomass (kg) was calculated as the product of density(kgmminus3) and volume (m3) for stem and branch sections[5 28] For twigs and leaves biomass was estimated as theproduct of estimated biomass ratio (dry to green weight ofsubsamples) and total green weight (kg) of the pile measuredin the field The total aboveground biomass for each treewas obtained as the sum of stump biomass biomass of stemand branch sections and biomass of twigs and leaves Theresulting dataset was used for developing biomass models foreach of the six species groups mentioned above

25 Statistical Analysis Like in other studies [3 13 31] severallinear models with different transformations were testedduring the development of volume and biomass models


Table 1 Volume and biomass equationsdagger for estimating total aboveground and stem (ge5 cm) volume and biomass of three dominant speciesin the Gangalamtumba Village Land Forest Reserve All parameter estimates are significantly different from zero (119875 lt 0001)

Species Component Equationdagger Regression parameters Dbh range (cm) Adj 1198772 RMSE Avg error ()119886 119887 119888

Brachystegiaspiciformis(119873 = 40)

Total volume(df = 37) 3 minus93188

(0166)19663(0088)

09118(0174) 12ndash543 0997 0142 199

(df = 38) 4 minus85018(0077)

24142(0027) mdash 12ndash543 0995 0185 349

Stem volume(df = 31) 3 minus117673

(0379)20335(0141)

16858(0314) 5ndash543 0990 0209 minus002

(df = 32) 4 minus98909(0203)

27460(0066) mdash 5ndash543 0981 0286 214

Total biomass(df = 37) 3 minus26071

(0149)20638(0078)

07847(0155) 12ndash543 0998 0127 160

(df = 38) 4 minus19040(0068)

24492(0024) mdash 12ndash543 0996 0162 267

(df = 38) 6 minus93309(0108)

09827(0008) mdash 12ndash543 0998 0127 166

Stem biomass(df = 31) 3 minus50668

(0343)21424(0128)

15563(0284) 5ndash543 0992 0189 minus057

(df = 32) 4 minus33345(0185)

28002(0061) mdash 5ndash543 0985 0262 117

Combretummolle(119873 = 41)


(0165)19212(0099)

07712(0183) 22ndash265 0987 0171 290

(df = 39) 4 minus85247(0130)

22972(0051) mdash 22ndash265 0981 0204 424


(0223)20420(0126)

10908(0193) 5ndash265 0977 0146 464

(df = 31) 4 minus98028(0277)

26237(0102) mdash 5ndash265 0954 0206 498


(0165)19685(0099)

07545(0183) 22ndash265 0987 0170 288

(df = 39) 4 minus19395(0129)

23364(0050) mdash 22ndash265 0982 0203 420

(df = 39) 6 minus88347(0230)

09371(0168) mdash 22ndash265 0987 0170 298


(0230)21112(0130)

10410(0199) 5ndash265 0976 0151 441

(df = 31) 4 minus32047(0275)

26663(0101) mdash 5ndash265 0956 0205 466

Dalbergiaarbutifolia(119873 = 37)


(0191)19701(0059)

08854(0152) 18ndash215 0991 0144 204

(df = 35) 4 minus83253(0120)

22413(0051) mdash 18ndash215 0982 0200 390


(0761)20113(0246)

27732(0455) 5ndash215 0871 0355 1297

(df = 30) 4 minus105743(0793)

27785(0313) mdash 5ndash215 0715 0528 3287


(0199)19900(0062)

09035(0159) 18ndash215 0990 0150 122

(df = 35) 4 minus17001(0124)

22667(0052) mdash 18ndash215 0981 0206 300


Table 1 Continued


(df = 35) 6 minus93782(0213)

09823(0016) mdash 18ndash215 0990 0148 137


(0776)20138(0250)

28503(0464) 5ndash215 0869 0362 1153

(df = 30) 4 minus39094(0812)

28023(0321) mdash 5ndash215 0708 0541 3054

(df = 30) 6 minus145150(1467)

12961(0108) mdash 5ndash215 0823 0421 1700

Note numbers in brackets indicate standard errors of the parameter estimates Height (range) B spiciformis 2ndash172m C molle 26ndash94m and D arbutifolia26ndash88m df is degrees of freedom RMSE is the standard error of the residuals Adj 1198772 is the adjusted coefficient of determination Avg is Average daggerEquation(3) ln(119884) = 119886 + 119887 ln(Dbh) + 119888 ln(ht) Equation (4) ln(119884) = 119886 + 119887 ln(Dbh) Equation (6) ln(119884) = 119886 + 119887 ln(wdDbh2ht) 119884 is volume (m3) or biomass (kg) Dbhis diameter at breast height (cm) ht is total height (m) and wd is wood density (kgmminus3)

The following general model formulations with logarithmictransformation of dependent and independent variables weretested

(1) ln(119884) = 119886 + 119887 times ln(Dbh) + 119888 times ln(Dbh2) + 119889 times ln(ht) +119890 times ln(ht2)

(2) ln(119884) = 119886 + 119887 times ln(Dbh2 ht)(3) ln(119884) = 119886 + 119887 times ln(Dbh) + 119888 times ln(ht)(4) ln(119884) = 119886 + 119887 times ln(Dbh)

For species-specific volume and biomassmodels we usedordinary least squares estimation assuming that errors werenormally and independently distributed whereas modelsfor groups of species (ie trees shrubs and both groupscombined) were prepared using the following mixed linearmodel formulation

(5) ln (119884)119894119895= 119891(Dbh

119894119895 ht119894119895) + V119894+ 120576119894119895

In all models 119884 is volume (m3 treeminus1) or biomass(kg treeminus1) Dbh is diameter at breast height (cm) and htis total height of the treeshrub (m) 119886 119887 119888 119889 and 119890 aremodel parameters and ln is the natural logarithm In model5 119894 is species 119895 is tree number 119891(Dbh

119894119895 ht119894119895) is one of the

model formulations 1ndash4 V119894sim 119873(0 120590

2

spe) is a random specieseffect and 120576

119894119895119904 are random errors 120576

119894119895sim 119873(0 120590

2) Thus for

species groups the between-species variation was modelledas a random effect

Furthermore to test the contribution of wood basicdensity in explaining the variation of biomass the loga-rithmic version of the following power model 119884 = 120572 times(119908119889 times Dbh2 times ht)119887 was tested

(6) ln(119884) = 119886 + 119887 times ln(119908119889 times Dbh2 times ht) where 119908119889 is thewood basic density

Prior to the regression analysis dependent variables(volume and biomass) were plotted against each of theexplanatory variables to examine the range and shape ofthe functional relationship and to assess the heterogeneityof the variance Relationships were tested after transformingthe variables We selected our final models based on high

adjusted 1198772 low residual standard error (RMSE) and graph-ical analysis of the residuals To assess the quality of the finalmodels we applied the approach also used by Chave et al[25] and Djomo et al [31] where the average percentageerror between predicted and measured values is comparedbetween the different equations after back-transforming totheir original scale and correcting for logarithmic bias Thepercentage error was calculated as

100 times119884predicted minus 119884measured

119884measured (1)

where 119884 is the biomass or volume of the tree The correctionfactor (CF) used for correcting for logarithmic bias was theone proposed by Sprugel [32] CF = exp(RMSE22) whichwas applied to the predicted values of volume and biomass

Finally the average percentage error of the models pre-pared in this study was compared with that of ten previ-ously published models when applied to the datasets fromGVLFR Correction for logarithmic bias was made in caseswhere dependent variables had been log-transformed Allanalyses weremade in Excel spreadsheets andR version 2130(httpwwwr-projectorg)

3 Results

31 Volume and Biomass Models Selected models for totaland stem volume and biomass of the three most dominantspecies are presented in Table 1 Similarly Table 2 showsmodels for total and stem volume and biomass for thethree species groups shrubs trees and all species (trees andshrubs) The general tendency among the final models isthat the fit improved when height and wood basic densitywere included in the model as indicated by the high adj1198772 low residual standard error and low average percentage

error However the improvement of the fit achieved byincluding wood density was in most cases negligible and theperformances of models 3 and 6 are therefore similar Asillustrated in Figure 2 the observations of total volume andbiomass were nicely distributed around the values predictedby model 4 for shrubs trees and trees and shrubs combinedand with only few outliers ending up outside (below) the


Table 2 Volume and biomass equations for estimating total aboveground and stem (ge5 cm) volume and biomass of shrubs trees and woodyplants in general (shrubs and trees) in Gangalamtumba Village Land Forest Reserve A few estimates are not significantly different from zero(119875 gt 005) These are marked ldquonsrdquo

Category Component Equationdagger Regression parameters Dbh range (cm) 1198772LR RMSE 120590spe Avg error ()119886 119887 119888

Shrubs(119873 = 32)16 species


(0237)22340(0099)

00507ns(0206) 18ndash215 0979 0251 000 1848

(df = 28) 4 minus82844(0152)

22517(2252) mdash 18ndash215 0979 0247 000 1857


(0673)17917(0316)

28547(0453) 5ndash215 0865 0533 000 3034

(df = 24) 4 minus108001(0710)

26587(0299) mdash 5ndash215 0792 0482 0636 5779


(0252)22145(0106)

01591ns(0219) 18ndash215 0977 0267 000 2190

(df = 28) 4 minus17179(0163)

22697(0073) mdash 18ndash215 0977 0265 000 2243

(df = 28) 6 minus86142(0427)

09417(0034) mdash 18ndash215 0968 0266 0184 1893


(0639)19676(0257)

26083(0428) 5ndash215 0916 0390 0276 2950

(df = 24) 4 minus43236(0705)

26903(0296) mdash 5ndash215 0799 0470 0676 5602

Trees(119873 = 72)28 species


(0075)18067(0040)

11940(0076) 14ndash62 0997 0129 000 166

(df = 70) 4 minus84800(0099)

23351(0033) mdash 14ndash62 0986 0219 0179 646


(0166)19316(0079)

15360(0119) 5ndash62 0994 0162 000 455

(df = 35) 4 minus109307(0273)

30134(0093) mdash 5ndash62 0975 0317 0119 1310


(0123)17586(0057)

12934(0115) 14ndash62 0992 0118 0278 247

(df = 70) 4 minus20667(0124)

23561(0036) mdash 14ndash62 0979 0213 0392 996

(df = 70) 6 minus91880(0101)

09668(0007) mdash 14ndash62 0996 0131 0052 132


(0326)21420(0158)

17090(0269) 5ndash62 0965 0294 0221 630

(df = 38) 4 minus44622(0365)

29972(0120) mdash 5ndash62 0928 0387 0375 1060

Combined(119873 = 104)44 species


(0104)19637(0053)

07737(0103) 14ndash62 0989 0193 0131 654

(df = 101) 4 minus84554(0084)

23236(0031) mdash 14ndash62 0983 0248 0140 989


(0244)21378(0127)

17695(0203) 5ndash62 0977 0271 0153 1850

(df = 43) 4 minus111929(0339)

30514(0115) mdash 5ndash62 0935 0413 0327 4922


(0131)19041(0064)

09377(0128) 14ndash62 0983 0182 0317 896

(df = 101) 4 minus19564(0102)

23260(0035) mdash 14ndash62 0974 0242 0327 1260


Table 2 Continued


(df = 101) 6 minus88819(0139)

09497(0010) mdash 14ndash62 0988 0187 0162 640


(0279)20894(0146)

19457(0238) 5ndash62 0970 0290 0230 1370

(df = 43) 4 minus48335(0349)

30979(0117) mdash 5ndash62 0924 0383 0488 4310

(df = 43) 6 minus135156(0455)

12284(0032) mdash 5ndash62 0971 0314 0153 2510

Note numbers in brackets indicate standard errors of the estimates Height range shrubs 25ndash8m trees 25ndash182m and combined 25ndash182m df is degrees offreedom RMSE is standard error of the residuals 120590spe is the standard deviation of the species random effect (between-species variation) 1198772LR is the likelihoodratio based coefficient of determination and Avg is Average daggerEquation (3) ln(119884) = 119886+119887 ln(Dbh)+119888 ln(ht) Equation (4) ln(119884) = 119886+119887 ln(Dbh) Equation (6)ln(119884) = 119886 + 119887 ln(wdDbh2ht) Y is volume (m3) or biomass (kg) Dbh is diameter at breast height (cm) ht is total height (m) and wd is wood density (kgmminus3)

TreesShrubs

00001

0001

001

01

1

10

00001

0001

001

01

1

10Shrubs and trees All three models

Obs shrubsObs treesModel shrubs

Model treesModel both

1 10 10000001

0001

001

01

1

10

00001

0001

001

01

1

10

1 10 100 1 10 100 1 10 100

Tota

l vol

ume (

m3)

Diameter at breast height (cm) Diameter at breast height (cm) Diameter at breast height (cm) Diameter at breast height (cm)

(a)



Shrubs

1 10 10001

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000Trees

1 10 100

Shrubs and trees

1 10 100

All three models

1 10 100

Tota

l bio

mas

s (kg)


(b)

Figure 2 Model 4 for total volume (a) and biomass (b) of the three species groups shrubs trees and shrubs and trees First three columnscircles indicate observed values unbroken lines show expected values and dashed lines are 95 prediction intervals fourth column all threemodels (see legend)

95 prediction intervals Furthermore the graphs in Figure 2illustrate that the differences between values predicted bymodels for the three life form groups are limited

32 Model Performance To some extent the overall perfor-mance of the volume and biomass models can be judged

from the RMSE and 1198772 values reported in Tables 1 and 2In addition to these measures both tables report the averagepercentage error after correction for logarithmic bias Asexpected species-specific models (Table 1) turned out tohave lower average percentage error compared to modelsdeveloped for the broader species groups (trees shrubs and


trees and shrubs combined) see Table 2 When comparisonwas made between the average percentage error obtained byusing species-specificmodels for volume and biomass predic-tion in the individual species datasets and the correspondingvalues obtained for the general mixed species-group models(models prepared for trees applied to B spiciformis and Cmolle and models prepared for shrubs applied to D arbuti-folia) it emerged that the individual species-specific modelsproduced considerably lower average percentage errors thanthe mixed species-group models (results not shown) Asimilar patternwas observedwhenmodels calibrated for treesand shrubs were applied to datasets including either treesor shrubs alone For both volume and biomass it emergedthat model 4 which includes only one independent variable(Dbh) was characterised by larger average percentage errorsthanmodel 3 which includes two independent variables (Dbhand ht) Also inclusion of wood basic density in the models(model 6) tended to improve the fit significantly as indicatedby the high adj 1198772 and low residual standard error

4 Discussion

The new volume and biomass models for individual speciesand for broader species groups (shrubs trees and both)provide a comprehensive range of tools for estimation ofstanding volume aboveground biomass and carbon stockof dry miombo vegetation in Tanzania Since the number ofsample trees and shrubs for the general model is relativelylarge and includes a large number of species (44 differentspecies) compared to site-specific models reported elsewhere[13ndash15] the newly developed models are likely to be quiterobust and can presumably be applied in areas with similarsite conditions with only a limited increase of bias comparedto locally calibrated models

Not surprisingly the species-specific volume and biomassmodels were superior to models prepared for species groupsin terms of average percentage error Similarly modelsprepared for individual species groups (trees and shrubsseparately) were superior to models prepared for the com-bined dataset including both trees and shrubs Thus theprecision and accuracy of the predictions tends to increasefromgeneral (all species trees and shrubs) to species-specific(single species) models

To assess the increase in accuracy achieved in GVLFRby the new models 10 different previously published volumeand biomass models for miombo woodlands were testedon the datasets prepared in this study The models includefive volume functions and five biomass functions and thecalculated average percentage error obtained for each com-bination of model and dataset is shown in Table 3 Ineach case model predictions were corrected for logarithmicbias except for models 8 9 and 16 for which no residualstandard deviation (RMSE) was provided and models 1213 14 and 15 which are power models When comparingthe average percentage errors obtained for our models withthose of the existing models it turned out that both ourspecies-specific models (Table 1) and species-group models(Table 2) yielded relatively low average percentage errors

compared to the existing models However based on theaverage percentage errors it also appeared that models 8 910 and 11 produced the most accurate estimates of volumefor shrubs and similarly that models 9 and 10 yielded thelowest average percentage errors for volume in the combineddataset (trees and shrubs) Except for models prepared forthe shrub species group (Table 2) which are characterised byrelatively high average percentage errors models prepared inthis study produced better estimates of biomass with loweraverage percentage errors than the existing models In partthis is a consequence of calibrating and testing our modelson the same dataset but it may also be related to the factthat the diameter ranges of the datasets applied in this studyare considerably broader than those of the datasets used forcalibrating the existing models from the literature Mugashaet al [15] observed a similar pattern of improved accuracyand precision of the predictionswhen comparing site-specificmodels to a general model However as shown in Table 3models 14 and 15 (biomass) seem to work very well onthe shrub dataset and the C molle (tree) and D arbutifolia(shrub) datasets as they are characterised by relatively lowaverage percentage errors

Considering the high species diversity found in themiombo woodlands the variation of species compositionfrom site to site and the impact of site conditions on theshape of trees the use of mixed-species regression modelscalibrated on data from sites with similar site conditionsand species composition is a logical choice By contrastgeneral allometric equations developed in other regions withdifferent species composition should be used with cautionand only if local mixed-species models are not availableLocally abundant species would usually not be representedin the databases used for development of such generalallometric models and they therefore may not accuratelyreflect the true biomass of trees in a given forest area [1 31 33]Therefore the use of site-specific models is recommendedto ensure that high precision is achieved in quantification ofwoodland resources [15]

The large percentage errors observed for the shrub datasetare presumably caused by the large variation of physicalshapes characterising this category of woody plants Thedataset included 16 different shrub species and some of themare characterised by very special stem and crown shapes andvery low (or high) wood basic densities This could explainthe large variation observed in the volume and biomass forstems

The value of species-specific models as a way to minimisevariation and increase the accuracy of models should notgo unmentioned However as explained the high diver-sity of species in miombo woodlands and in most othertropical forest types combined with frequent challenges ofcorrect botanical identification enhances the cost of prepar-ing species-specific models with a view to improve theaccuracy of standing volumes and biomass estimates at theforest level Mixed-species models are therefore still usefulbut they should be applied with due consideration of theimproved quality of volumebiomass estimates that can beobtained by the application of species-specific models


Table3Av

erageerrorinpercento

fmeasuredvalues

asob

served

forp

reviou

slypu

blish

edvolumeandbiom

asse

quations

form

iombo

woo

dlands

whenappliedto

species-specificand

mixed-speciesdatasetsprepared

inthisstu

dyM

odelsd

evelo

pedin

thisstu

dyareincludedforcom

paris

onSym

bols119884isvolume(m

3 )or

biom

ass(kg)Dbh

isdiam

eteratbreastheight

(cm)

htistotalh

eight(m)BA

isbasalarea(

cm2 )and119873

issamples

ize

Mod

eldagger

Source

Nam

eofspecies

Averagee

rror

inpercentfor

thed

atasetsp

reparedin

thisstu

dyB

spiciform

isC

molle

Darbutifolia

Shrubs

Trees

Com

bined

Mod

el(3)=

totalvolum

eTh

isstu

dy19

9290

204

1848

166

654

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(7)log10119884=minus385+249log 10Dbh

Abbo

tetal[24]

Brachyste

giaboehmii

minus1073

2176

1201

2998

844

1534

119873=27D

bh8ndash4

0cm

(8)log10119884(litres)=minus12875+28436log 10Dbh

Temu[22]

Brachyste

giaspiciform

isminus603

1712

012

282

1048

745

119873=un

know

nDbh

5ndash4

3cm

(9)119884=0092Dbh

259

Malim

bwiand

Temu[23]

Pterocarpu

sangolensis

minus2116

445

minus686

minus111minus445

minus364

119873=25D

bh6ndash6

1cm

(10)

log 10119884=minus422+276log 10Dbh

Abbo

tetal[24]

Mixed

species(17

spp)

minus1536

877

minus57

minus266

106

minus020

119873=51D

bh5ndash4

0(11)119884=00001Dbh

2032 ht0

66Malim

bwietal[13]

Mixed

species(13

spp)

minus2091

minus19

4minus110

minus74

5minus1282minus1126

119873=17D

bh8ndash4

3cm

Mod

el(3)=

totalbiomass

Thisstu

dy16

0288

122

2190

247

896

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(12)119884=006Dbh

2012 ht0

71Malim

bwietal[13]

Mixed

species(13

spp)

minus3856

minus2344

minus3061minus2051minus807

minus1168

119873=17D

bh8ndash4

3cm

(13)119884=00263Dbh

1505ht

1762

Cham

sham

aetal[14

]Mixed

species(20

spp)

minus2817

minus3317

minus3628


119873=30D

bh11ndash

50cm

(14)119884=01027Dbh

24798

Mugasha

etal[15]

Mixed

species(49

spp)

minus2421

452

minus681

885

2119

1739

119873=167D

bh11ndash

110cm

(15)119884=00763Dbh

22046ht

04918

Mugasha

etal[15]

Mixed

species(49

spp)

minus2038

minus12

7minus1109

minus335

1557

975

119873=167D

bh11ndash

110cm

(16)

log 10119884=minus0535+log 10BA

Brow

n[1]

Mixed

species(no

tind

icated)minus5002

minus3029

minus3591minus1927minus1904minus1926

119873=191D

bh3ndash30c

mdaggerFo

reachmod

elther

ange

ofdiam

etersinthem

aterialformingtheb

asisforthe

mod

elisspecified


5 Conclusion

This study for the first time provides a comprehensive poolof different allometric equations for estimating total andstem volume and biomass for (i) selected individual speciesand (ii) for mixed-species groups found in the dry miombowoodlands of Tanzania Sincemost of themodels have higher1198772 lower RMSE and lower average percentage error than

the existing equations these new models should be usefulfor providing reliable estimates of volume and biomass forforests with similar species composition and site conditions(soil and climate) Furthermore the new models can beapplied at all levels from the species-specific individual-treelevel to the stand level Modelling the volume and biomassof shrubs turned out to be challenging possibly due to thelarge variation of wood density and shape of stem and crowncharacterising this group Further research on measures thatcould be used to improve volume and biomass estimates forshrubs would therefore be useful

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

Special thanks are due to the people of Mfyome villagefor their invaluable assistance during the field work MzeeIddi Kaheya Damian Chotamasege Augustino MkwamaIbrahim Mbilinyi Liberatus Simime Mawazo NyangwaThomas Kivamba and Lutengano Anangisye The authorsgratefully acknowledge the help and contributions of Good-luck Moshi their driver Venancia Mlelwa John Shesigheand Tulamwona Ernest at Sokoine University of Agriculturewho did most of the laboratory work Nassoro H Magogoat Tanzania Forest Research Institutersquos herbarium in Lushotowho did the botanical identification work and Klaus Donsat Forest amp Landscape who prepared the map of the studysite in Figure 1 Finally the Danish Ministry of ForeignAffairs (Danida) supported the work financially throughthe ENRECA project ldquoParticipatory Forest Management forRural Livelihoods Forest Conservation and Good Gover-nance in Tanzaniardquo (Grant no 725)

References

[1] S Brown ldquoEstimating biomass and biomass change of tropicalforests a primerrdquo FAO Forest Paper 134 1997

[2] T J Brandeis M Delaney B R Parresol and L RoyerldquoDevelopment of equations for predicting Puerto Rican sub-tropical dry forest biomass and volumerdquo Forest Ecology andManagement vol 233 no 1 pp 133ndash142 2006

[3] B Husch T W Beers and J A Kershaw Forest MensurationJohn Wiley amp Sons Hoboken NJ USA 4th edition 2003

[4] P H Freer-Smith M S J Broadmeadow and J M LynchForestry amp Climate Change Forestry Research Farnham UK2007

[5] A de Gier ldquoA new approach to woody biomass assessmentin woodlands and shrublandsrdquo in GeoinFormatics for TropicalEcosystems P S Roy Ed pp 161ndash198 Bishen Singh MahendraPal Singh Dehradun India 2003

[6] J Navar ldquomeasurement and assessment methods of for-est aboveground biomass a literature review and the chal-lenges aheadrdquo in Biomass M Momba and F Bux Edspp 27ndash64 publisher Janeza Trdine Rijeka Croatia 2010httpwwwsciyocom

[7] M Williams C M Ryan R M Rees E Sambane J Fernandoand J Grace ldquoCarbon sequestration and biodiversity of re-growing miombo woodlands in Mozambiquerdquo Forest Ecologyand Management vol 254 no 2 pp 145ndash155 2008

[8] M De RidderW Hubau J van den Bulcke J van Acker and HBeeckman ldquoThe potential of plantations of Terminalia superbaengl amp diels for wood and biomass production (MayombeForest Democratic Republic of Congo)rdquo Annals of ForestScience vol 67 no 5 pp 501ndash512 2010

[9] S Brown ldquoMeasuring monitoring and verification of carbonbenefits for forest-based projectsrdquo Philosophical Transactions ofthe Royal Society A vol 360 no 1797 pp 1669ndash1683 2002

[10] M Henry N Picard C Trotta et al ldquoEstimating tree biomassof sub-Saharan African forests a review of available allometricequationsrdquo Silva Fennica vol 45 no 3 pp 477ndash569 2011

[11] O Hofstad ldquoReview of biomass and volume functions forindividual trees and shrubs in Southeast Africardquo Journal ofTropical Forest Science vol 17 no 1 pp 151ndash162 2005

[12] C M Ryan M Williams and J Grace ldquoAbove- and below-ground carbon stocks in a miombo woodland landscape ofmozambiquerdquo Biotropica vol 43 no 4 pp 423ndash432 2011

[13] R E Malimbwi B Solberg and E Luoga ldquoEstimation ofbiomass and volume in miombo woodland at KitulangaloForest Reserve Tanzaniardquo Journal of Tropical Forest Science vol7 no 2 pp 230ndash242 1994

[14] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal no 200 pp 59ndash69 2004

[15] W A Mugasha T Eid O M Bollandsas et al ldquoAllometricmodels for prediction of above- and below ground biomass oftrees in themiombowoodlands of Tanzaniardquo Forest Ecology andManagement vol 310 pp 87ndash101 2013

[16] N Calender ldquoMiombo woodlandmdashdistribution ecology andpatterns of land userdquo Working Paper 16 Swedish University ofagricultural Sciences Uppsala Sweden 1981

[17] E N Chidumayo ldquoEstimating fuelwood production and yieldin regrowth dry miombo woodland in Zambiardquo Forest Ecologyand Management vol 24 no 1 pp 59ndash66 1988

[18] D D Shirima P K T Munishi S L Lewis et al ldquoCarbonstorage structure and composition of miombo woodlands inTanzaniarsquos Eastern Arc Mountainsrdquo African Journal of Ecologyvol 49 no 3 pp 332ndash342 2011

[19] Q M Ketterings R Coe M Van Noordwijk Y Ambagaursquoand C A Palm ldquoReducing uncertainty in the use of allometricbiomass equations for predicting above-ground tree biomass inmixed secondary forestsrdquo Forest Ecology and Management vol146 no 1ndash3 pp 199ndash209 2001

[20] H K Gibbs S Brown J O Niles and J A Foley ldquoMonitoringand estimating tropical forest carbon stocks making REDD arealityrdquo Environmental Research Letters vol 2 no 4 Article ID045023 2007


[21] M A Pinard and F E Putz ldquoRetaining forest biomass byreducing logging damagerdquoBiotropica vol 28 pp 278ndash295 1996

[22] A B Temu ldquoDouble sampling with aerial photographs inestimating wood volume in miombo woodlandsrdquo Division ofForestry University of Dar-es-Salaam Morogoro Tanzania vol22 pp 1ndash17 1981

[23] R E Malimbwi and A B Temu ldquoVolume functions forPterocarpus angolensis and Julbernadia globiflorardquo Journal ofTanzania Association of Foresters vol 1 pp 49ndash53 1984

[24] P Abbot J Lowore andMWerren ldquoModels for the estimationof single tree volume in four Miombo woodland typesrdquo ForestEcology and Management vol 97 pp 25ndash37 1997

[25] J Chave C Andalo S Brown et al ldquoTree allometry andimproved estimation of carbon stocks and balance in tropicalforestsrdquo Oecologia vol 145 no 1 pp 87ndash99 2005

[26] M Henry A Besnard W A Asante et al ldquoWood densityphytomass variations within and among trees and allometricequations in a tropical rainforest of Africardquo Forest Ecology andManagement vol 260 no 8 pp 1375ndash1388 2010

[27] LIFE and SUA ldquoParticipatory Forest Management inceptionreportrdquo Sokoine University of Agriculture (SUA) Facultyof Forestry and Nature Conservation (FFNC) University ofCopenhagen Forest amp Landscape Denmark (FLD) CambridgeUniversity Cambridge UK University of Manchester Manch-ester UK 2007

[28] H T Valentine LM Tritton andGM Furnival ldquoSubsamplingtrees for biomass volume or mineral contentrdquo Forest Sciencevol 30 no 3 pp 673ndash681 1984

[29] P O Olesen ldquoThe water displacement method A fast andaccurate method of determining the green volume of woodsamplesrdquo Forest Tree Improvement vol 3 pp 1ndash23 1971

[30] E E Mwakalukwa H Meilby and T Treue ldquoWood basic den-sities of dry miombo woodland trees and shrubs in TanzaniardquoIn press

[31] A N Djomo A Ibrahima J Saborowski and G GravenhorstldquoAllometric equations for biomass estimations in Cameroonand pan moist tropical equations including biomass data fromAfricardquo Forest Ecology and Management vol 260 no 10 pp1873ndash1885 2010

[32] D G Sprugel ldquoCorrecting for bias in log- transformed allomet-ric equationsrdquo Ecology vol 64 no 1 pp 209ndash210 1983

[33] J Navar ldquoBiomass component equations for Latin Americanspecies and groups of speciesrdquo Annals of Forest Science vol 66no 2 p 208 2009

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of



EcosystemsJournal of


MeteorologyAdvances in

EcologyInternational Journal of


Marine BiologyJournal of


Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in


Environmental Chemistry

Atmospheric SciencesInternational Journal of



Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics


Geological ResearchJournal of

EarthquakesJournal of


BiodiversityInternational Journal of


ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


ClimatologyJournal of


estimation of forest volume and biomass and for carbonaccounting purposes are generally lacking [10ndash12] In Tanza-nia two studies have developed biomass models using datafrom a relatively dry miombo woodland site at KitulanghaloForest Reserve in Morogoro Region eastern Tanzania whichreceives an annual rainfall of about 900mm yearminus1 [13 14]These studies were conducted on the basis of a very limitedsample size (lt30 trees) covering a narrow diameter range(11ndash50 cm) Recent work by Mugasha et al [15] covers awider range of sites (four dry and one wet miombo sites)Yet it only includes a few more trees per site in the threerelatively dry miombo woodland sites 40 trees in ManyaraRegion northeastern Tanzania (854mm yearminus1) 40 trees inKatavi Region western Tanzania (881mm yearminus1) and 40trees in Tabora Region western central Tanzania (771mmyearminus1) In addition the number of species used in devel-oping site-specific models was very low for example 10species for the Manyara site but the general countrywidemodel had adequate species richness (gt45 different species)Having included trees from wet miombo sites which havedifferent growth habits compared to those found in typicaldry miombo areas and considering the large site differencesacross miombo woodlands with respect to climate soilaltitude land form species composition and historical landuse there appears to be a strong need for developing modelsfor sites that receive very little precipitation such as the areasin Iringa Region south central Tanzania (617mm yearminus1) toincrease the accuracy of predicted stand volume biomassand carbon stock in such site types

Miombo woodlands consist of open light stands of adeciduous or semideciduous nature with up to three vege-tation strata upper canopy trees secondary layer (includingthe shrub layer lt8m tall) and herbaceous layer whichconsists chiefly of grasses up to 2m tall [16] The uppercanopy trees can reach heights of 14ndash20m while trees of thesecondary layer may reach 8ndash12m Understory shrubs aremultistemmeddue to fire or stem cutting and tend to cover upto 70 of the ground This vegetation is an important sourceof fuel wood for the majority of people living in miomboareas and due to the large areas that it covers the carbonstocks and sequestration potential of the woodland are high[17 18] Unfortunately previous studies in the miombo didnot include biomass models for understory species (shrubs)[13ndash15]

Although with some limitations due to the large numberof species in tropical forests species-specific volume andbiomass models are often preferred for accurate estimationof forest volume and biomass and for carbon accountingpurposes [19 20] This type of models has been developedfor a wide range of plantation species and in temperateregions where the number of relevant tree species is lowerHowever most types of tropical vegetation are characterizedby dominant species so it has been suggested to develop adatabase of allometric equations for selected dominant treespecies which are particularly important for volume andbiomass estimates as they contribute a large proportion ofthe biomass compared to other species [21] In Tanzaniaspecies-specific volume functions have been prepared for

a few dominantmiombo species in Tabora in thewestern partof the country [22 23] and elsewhere [24]These studies werehowever also based on a very small sample size (lt27) and anarrow diameter range (lt43 cm)

Wood density is a key variable in the estimation oftree biomass [25 26] However none of the above studieshave reported biomass models which take into account thecontribution ofwood basic density in explaining the variationin treeshrub biomass Inclusion of wood density in biomassmodelling has been shown to improve the performance of themodels significantly [25 26]

Accordingly the objectives of this study were to (1)develop volume and AGB allometric equations for threedominant species (Brachystegia spiciformis Benth Combre-tum molle G Don and Dalbergia arbutifolia Baker) and(2) develop general equations for three life form groupstrees shrubs and woody species in general (trees andshrubs combined) The new models will not only helpincrease our knowledge on total aboveground productivity ofmiombo woodlands but also support planning assessmentand development of management strategies for sustainableutilization of the woodlands Furthermore the local biomassmodels developed in this paper will not only add to existingknowledge about the miombo but also support the nationof Tanzania in accurate estimation and reporting of currentforest biomass stocks and their changes over time

2 Materials and Methods

21 Study Site Gangalamtumba Village Land Forest Reserve(GVLFR) is located in central-southern Tanzania (7∘351015840 S35∘351015840 E) about 30 km northwest of Iringa Municipality theadministrative capital of Iringa Region (Figure 1) The area ofthe forest is 6065 hectares and it is managed by the Mfyomevillage which is located in the ward of Kiwele The forestcan be described as dry miombo woodland and the terrainis relatively flat and located 850ndash1300 metres above sealevel The average annual rainfall is (mean plusmn standard error)617 plusmn 17mm (range 448ndash1085mm) and the mean annualtemperature is 198∘CThe soil texture ranges from sandy soilsat low elevations to sandy clay loams at higher elevationswith pH from 57 to 87 GVLFR is a production forest whichallows some commercial forest activities including charcoalproduction firewood collection and livestock grazingmainlyduring the dry season

22 Field Sampling The survey was conducted in August2009 and September-October 2010 and involved harvestingof 142 individual trees (28 species) and 57 individual shrubs(16 species) from a 30mwide boundary zone of 35 permanentcircular sample plots with a radius of 50m (07854 ha)that were distributed across the entire area of the GVLFR(Figure 1) Plots were located along transect lines and thedistance between plots was about 2 km The centre pointsof the plots are identical to those used in a survey thatwas previously conducted in the forest [27] The minimumand maximum sizes of sample treesshrubs were 14 cm and620 cm in diameter at breast height (Dbh) respectively For


0 25 5To Iringa

To DodomaIkengeza

Itagutwa

Airport

Mfyome

Kiwele

Luganga



N

Iringa Region

Tanzania

10

(km)














(0166)19663(0088)

09118(0174) 12ndash543 0997 0142 199

(df = 38) 4 minus85018(0077)

24142(0027) mdash 12ndash543 0995 0185 349


(0379)20335(0141)

16858(0314) 5ndash543 0990 0209 minus002

(df = 32) 4 minus98909(0203)

27460(0066) mdash 5ndash543 0981 0286 214


(0149)20638(0078)

07847(0155) 12ndash543 0998 0127 160

(df = 38) 4 minus19040(0068)

24492(0024) mdash 12ndash543 0996 0162 267

(df = 38) 6 minus93309(0108)

09827(0008) mdash 12ndash543 0998 0127 166


(0343)21424(0128)

15563(0284) 5ndash543 0992 0189 minus057

(df = 32) 4 minus33345(0185)

28002(0061) mdash 5ndash543 0985 0262 117



(0165)19212(0099)

07712(0183) 22ndash265 0987 0171 290

(df = 39) 4 minus85247(0130)

22972(0051) mdash 22ndash265 0981 0204 424


(0223)20420(0126)

10908(0193) 5ndash265 0977 0146 464

(df = 31) 4 minus98028(0277)

26237(0102) mdash 5ndash265 0954 0206 498


(0165)19685(0099)

07545(0183) 22ndash265 0987 0170 288

(df = 39) 4 minus19395(0129)

23364(0050) mdash 22ndash265 0982 0203 420

(df = 39) 6 minus88347(0230)

09371(0168) mdash 22ndash265 0987 0170 298


(0230)21112(0130)

10410(0199) 5ndash265 0976 0151 441

(df = 31) 4 minus32047(0275)

26663(0101) mdash 5ndash265 0956 0205 466



(0191)19701(0059)

08854(0152) 18ndash215 0991 0144 204

(df = 35) 4 minus83253(0120)

22413(0051) mdash 18ndash215 0982 0200 390


(0761)20113(0246)

27732(0455) 5ndash215 0871 0355 1297

(df = 30) 4 minus105743(0793)

27785(0313) mdash 5ndash215 0715 0528 3287


(0199)19900(0062)

09035(0159) 18ndash215 0990 0150 122

(df = 35) 4 minus17001(0124)

22667(0052) mdash 18ndash215 0981 0206 300


Table 1 Continued


(df = 35) 6 minus93782(0213)

09823(0016) mdash 18ndash215 0990 0148 137


(0776)20138(0250)

28503(0464) 5ndash215 0869 0362 1153

(df = 30) 4 minus39094(0812)

28023(0321) mdash 5ndash215 0708 0541 3054

(df = 30) 6 minus145150(1467)

12961(0108) mdash 5ndash215 0823 0421 1700






(5) ln (119884)119894119895= 119891(Dbh

119894119895 ht119894119895) + V119894+ 120576119894119895


119894119895 ht119894119895) is one of the


2



119894119895sim 119873(0 120590

2) Thus for







119884measured (1)



3 Results








(0237)22340(0099)

00507ns(0206) 18ndash215 0979 0251 000 1848

(df = 28) 4 minus82844(0152)

22517(2252) mdash 18ndash215 0979 0247 000 1857


(0673)17917(0316)

28547(0453) 5ndash215 0865 0533 000 3034

(df = 24) 4 minus108001(0710)

26587(0299) mdash 5ndash215 0792 0482 0636 5779


(0252)22145(0106)

01591ns(0219) 18ndash215 0977 0267 000 2190

(df = 28) 4 minus17179(0163)

22697(0073) mdash 18ndash215 0977 0265 000 2243

(df = 28) 6 minus86142(0427)

09417(0034) mdash 18ndash215 0968 0266 0184 1893


(0639)19676(0257)

26083(0428) 5ndash215 0916 0390 0276 2950

(df = 24) 4 minus43236(0705)

26903(0296) mdash 5ndash215 0799 0470 0676 5602



(0075)18067(0040)

11940(0076) 14ndash62 0997 0129 000 166

(df = 70) 4 minus84800(0099)

23351(0033) mdash 14ndash62 0986 0219 0179 646


(0166)19316(0079)

15360(0119) 5ndash62 0994 0162 000 455

(df = 35) 4 minus109307(0273)

30134(0093) mdash 5ndash62 0975 0317 0119 1310


(0123)17586(0057)

12934(0115) 14ndash62 0992 0118 0278 247

(df = 70) 4 minus20667(0124)

23561(0036) mdash 14ndash62 0979 0213 0392 996

(df = 70) 6 minus91880(0101)

09668(0007) mdash 14ndash62 0996 0131 0052 132


(0326)21420(0158)

17090(0269) 5ndash62 0965 0294 0221 630

(df = 38) 4 minus44622(0365)

29972(0120) mdash 5ndash62 0928 0387 0375 1060



(0104)19637(0053)

07737(0103) 14ndash62 0989 0193 0131 654

(df = 101) 4 minus84554(0084)

23236(0031) mdash 14ndash62 0983 0248 0140 989


(0244)21378(0127)

17695(0203) 5ndash62 0977 0271 0153 1850

(df = 43) 4 minus111929(0339)

30514(0115) mdash 5ndash62 0935 0413 0327 4922


(0131)19041(0064)

09377(0128) 14ndash62 0983 0182 0317 896

(df = 101) 4 minus19564(0102)

23260(0035) mdash 14ndash62 0974 0242 0327 1260


Table 2 Continued


(df = 101) 6 minus88819(0139)

09497(0010) mdash 14ndash62 0988 0187 0162 640


(0279)20894(0146)

19457(0238) 5ndash62 0970 0290 0230 1370

(df = 43) 4 minus48335(0349)

30979(0117) mdash 5ndash62 0924 0383 0488 4310

(df = 43) 6 minus135156(0455)

12284(0032) mdash 5ndash62 0971 0314 0153 2510


TreesShrubs

00001

0001

001

01

1

10

00001

0001

001

01

1




1 10 10000001

0001

001

01

1

10

00001

0001

001

01

1

10

1 10 100 1 10 100 1 10 100

Tota

l vol

ume (

m3)


(a)



Shrubs

1 10 10001

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000Trees

1 10 100

Shrubs and trees

1 10 100

All three models

1 10 100

Tota

l bio

mas

s (kg)


(b)







4 Discussion









Table3Av


fmeasuredvalues

asob

served

forp

reviou

slypu

blish

edvolumeandbiom

asse

quations

form

iombo

woo

dlands

whenappliedto

species-specificand


inthisstu

dyM

odelsd

evelo

pedin

thisstu

dyareincludedforcom

paris

onSym


3 )or

biom

ass(kg)Dbh

isdiam

eteratbreastheight

(cm)

htistotalh

eight(m)BA

isbasalarea(

cm2 )and119873

issamples

ize

Mod

eldagger

Source

Nam

eofspecies

Averagee

rror

inpercentfor

thed

atasetsp

reparedin

thisstu

dyB

spiciform

isC

molle

Darbutifolia

Shrubs

Trees

Com

bined

Mod

el(3)=

totalvolum

eTh

isstu

dy19

9290

204

1848

166

654

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(7)log10119884=minus385+249log 10Dbh

Abbo

tetal[24]

Brachyste

giaboehmii

minus1073

2176

1201

2998

844

1534

119873=27D

bh8ndash4

0cm


Temu[22]

Brachyste

giaspiciform

isminus603

1712

012

282

1048

745

119873=un

know

nDbh

5ndash4

3cm

(9)119884=0092Dbh

259

Malim

bwiand

Temu[23]

Pterocarpu

sangolensis

minus2116

445

minus686

minus111minus445

minus364

119873=25D

bh6ndash6

1cm

(10)


Abbo

tetal[24]

Mixed

species(17

spp)

minus1536

877

minus57

minus266

106

minus020

119873=51D

bh5ndash4

0(11)119884=00001Dbh

2032 ht0

66Malim

bwietal[13]

Mixed

species(13

spp)

minus2091

minus19

4minus110

minus74

5minus1282minus1126

119873=17D

bh8ndash4

3cm

Mod

el(3)=

totalbiomass

Thisstu

dy16

0288

122

2190

247

896

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(12)119884=006Dbh

2012 ht0

71Malim

bwietal[13]

Mixed

species(13

spp)

minus3856

minus2344


minus1168

119873=17D

bh8ndash4

3cm

(13)119884=00263Dbh

1505ht

1762

Cham

sham

aetal[14

]Mixed

species(20

spp)

minus2817

minus3317

minus3628


119873=30D

bh11ndash

50cm

(14)119884=01027Dbh

24798

Mugasha

etal[15]

Mixed

species(49

spp)

minus2421

452

minus681

885

2119

1739

119873=167D

bh11ndash

110cm

(15)119884=00763Dbh

22046ht

04918

Mugasha

etal[15]

Mixed

species(49

spp)

minus2038

minus12

7minus1109

minus335

1557

975

119873=167D

bh11ndash

110cm

(16)


Brow

n[1]

Mixed

species(no

tind

icated)minus5002

minus3029


119873=191D

bh3ndash30c

mdaggerFo

reachmod

elther

ange

ofdiam

etersinthem

aterialformingtheb

asisforthe

mod

elisspecified


5 Conclusion





Acknowledgments


References







































Journal of












Volume 2014

Advances in









Geophysics















0 25 5To Iringa

To DodomaIkengeza

Itagutwa

Airport

Mfyome

Kiwele

Luganga



N

Iringa Region

Tanzania

10

(km)














(0166)19663(0088)

09118(0174) 12ndash543 0997 0142 199

(df = 38) 4 minus85018(0077)

24142(0027) mdash 12ndash543 0995 0185 349


(0379)20335(0141)

16858(0314) 5ndash543 0990 0209 minus002

(df = 32) 4 minus98909(0203)

27460(0066) mdash 5ndash543 0981 0286 214


(0149)20638(0078)

07847(0155) 12ndash543 0998 0127 160

(df = 38) 4 minus19040(0068)

24492(0024) mdash 12ndash543 0996 0162 267

(df = 38) 6 minus93309(0108)

09827(0008) mdash 12ndash543 0998 0127 166


(0343)21424(0128)

15563(0284) 5ndash543 0992 0189 minus057

(df = 32) 4 minus33345(0185)

28002(0061) mdash 5ndash543 0985 0262 117



(0165)19212(0099)

07712(0183) 22ndash265 0987 0171 290

(df = 39) 4 minus85247(0130)

22972(0051) mdash 22ndash265 0981 0204 424


(0223)20420(0126)

10908(0193) 5ndash265 0977 0146 464

(df = 31) 4 minus98028(0277)

26237(0102) mdash 5ndash265 0954 0206 498


(0165)19685(0099)

07545(0183) 22ndash265 0987 0170 288

(df = 39) 4 minus19395(0129)

23364(0050) mdash 22ndash265 0982 0203 420

(df = 39) 6 minus88347(0230)

09371(0168) mdash 22ndash265 0987 0170 298


(0230)21112(0130)

10410(0199) 5ndash265 0976 0151 441

(df = 31) 4 minus32047(0275)

26663(0101) mdash 5ndash265 0956 0205 466



(0191)19701(0059)

08854(0152) 18ndash215 0991 0144 204

(df = 35) 4 minus83253(0120)

22413(0051) mdash 18ndash215 0982 0200 390


(0761)20113(0246)

27732(0455) 5ndash215 0871 0355 1297

(df = 30) 4 minus105743(0793)

27785(0313) mdash 5ndash215 0715 0528 3287


(0199)19900(0062)

09035(0159) 18ndash215 0990 0150 122

(df = 35) 4 minus17001(0124)

22667(0052) mdash 18ndash215 0981 0206 300


Table 1 Continued


(df = 35) 6 minus93782(0213)

09823(0016) mdash 18ndash215 0990 0148 137


(0776)20138(0250)

28503(0464) 5ndash215 0869 0362 1153

(df = 30) 4 minus39094(0812)

28023(0321) mdash 5ndash215 0708 0541 3054

(df = 30) 6 minus145150(1467)

12961(0108) mdash 5ndash215 0823 0421 1700






(5) ln (119884)119894119895= 119891(Dbh

119894119895 ht119894119895) + V119894+ 120576119894119895


119894119895 ht119894119895) is one of the


2



119894119895sim 119873(0 120590

2) Thus for







119884measured (1)



3 Results








(0237)22340(0099)

00507ns(0206) 18ndash215 0979 0251 000 1848

(df = 28) 4 minus82844(0152)

22517(2252) mdash 18ndash215 0979 0247 000 1857


(0673)17917(0316)

28547(0453) 5ndash215 0865 0533 000 3034

(df = 24) 4 minus108001(0710)

26587(0299) mdash 5ndash215 0792 0482 0636 5779


(0252)22145(0106)

01591ns(0219) 18ndash215 0977 0267 000 2190

(df = 28) 4 minus17179(0163)

22697(0073) mdash 18ndash215 0977 0265 000 2243

(df = 28) 6 minus86142(0427)

09417(0034) mdash 18ndash215 0968 0266 0184 1893


(0639)19676(0257)

26083(0428) 5ndash215 0916 0390 0276 2950

(df = 24) 4 minus43236(0705)

26903(0296) mdash 5ndash215 0799 0470 0676 5602



(0075)18067(0040)

11940(0076) 14ndash62 0997 0129 000 166

(df = 70) 4 minus84800(0099)

23351(0033) mdash 14ndash62 0986 0219 0179 646


(0166)19316(0079)

15360(0119) 5ndash62 0994 0162 000 455

(df = 35) 4 minus109307(0273)

30134(0093) mdash 5ndash62 0975 0317 0119 1310


(0123)17586(0057)

12934(0115) 14ndash62 0992 0118 0278 247

(df = 70) 4 minus20667(0124)

23561(0036) mdash 14ndash62 0979 0213 0392 996

(df = 70) 6 minus91880(0101)

09668(0007) mdash 14ndash62 0996 0131 0052 132


(0326)21420(0158)

17090(0269) 5ndash62 0965 0294 0221 630

(df = 38) 4 minus44622(0365)

29972(0120) mdash 5ndash62 0928 0387 0375 1060



(0104)19637(0053)

07737(0103) 14ndash62 0989 0193 0131 654

(df = 101) 4 minus84554(0084)

23236(0031) mdash 14ndash62 0983 0248 0140 989


(0244)21378(0127)

17695(0203) 5ndash62 0977 0271 0153 1850

(df = 43) 4 minus111929(0339)

30514(0115) mdash 5ndash62 0935 0413 0327 4922


(0131)19041(0064)

09377(0128) 14ndash62 0983 0182 0317 896

(df = 101) 4 minus19564(0102)

23260(0035) mdash 14ndash62 0974 0242 0327 1260


Table 2 Continued


(df = 101) 6 minus88819(0139)

09497(0010) mdash 14ndash62 0988 0187 0162 640


(0279)20894(0146)

19457(0238) 5ndash62 0970 0290 0230 1370

(df = 43) 4 minus48335(0349)

30979(0117) mdash 5ndash62 0924 0383 0488 4310

(df = 43) 6 minus135156(0455)

12284(0032) mdash 5ndash62 0971 0314 0153 2510


TreesShrubs

00001

0001

001

01

1

10

00001

0001

001

01

1




1 10 10000001

0001

001

01

1

10

00001

0001

001

01

1

10

1 10 100 1 10 100 1 10 100

Tota

l vol

ume (

m3)


(a)



Shrubs

1 10 10001

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000Trees

1 10 100

Shrubs and trees

1 10 100

All three models

1 10 100

Tota

l bio

mas

s (kg)


(b)







4 Discussion









Table3Av


fmeasuredvalues

asob

served

forp

reviou

slypu

blish

edvolumeandbiom

asse

quations

form

iombo

woo

dlands

whenappliedto

species-specificand


inthisstu

dyM

odelsd

evelo

pedin

thisstu

dyareincludedforcom

paris

onSym


3 )or

biom

ass(kg)Dbh

isdiam

eteratbreastheight

(cm)

htistotalh

eight(m)BA

isbasalarea(

cm2 )and119873

issamples

ize

Mod

eldagger

Source

Nam

eofspecies

Averagee

rror

inpercentfor

thed

atasetsp

reparedin

thisstu

dyB

spiciform

isC

molle

Darbutifolia

Shrubs

Trees

Com

bined

Mod

el(3)=

totalvolum

eTh

isstu

dy19

9290

204

1848

166

654

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(7)log10119884=minus385+249log 10Dbh

Abbo

tetal[24]

Brachyste

giaboehmii

minus1073

2176

1201

2998

844

1534

119873=27D

bh8ndash4

0cm


Temu[22]

Brachyste

giaspiciform

isminus603

1712

012

282

1048

745

119873=un

know

nDbh

5ndash4

3cm

(9)119884=0092Dbh

259

Malim

bwiand

Temu[23]

Pterocarpu

sangolensis

minus2116

445

minus686

minus111minus445

minus364

119873=25D

bh6ndash6

1cm

(10)


Abbo

tetal[24]

Mixed

species(17

spp)

minus1536

877

minus57

minus266

106

minus020

119873=51D

bh5ndash4

0(11)119884=00001Dbh

2032 ht0

66Malim

bwietal[13]

Mixed

species(13

spp)

minus2091

minus19

4minus110

minus74

5minus1282minus1126

119873=17D

bh8ndash4

3cm

Mod

el(3)=

totalbiomass

Thisstu

dy16

0288

122

2190

247

896

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(12)119884=006Dbh

2012 ht0

71Malim

bwietal[13]

Mixed

species(13

spp)

minus3856

minus2344


minus1168

119873=17D

bh8ndash4

3cm

(13)119884=00263Dbh

1505ht

1762

Cham

sham

aetal[14

]Mixed

species(20

spp)

minus2817

minus3317

minus3628


119873=30D

bh11ndash

50cm

(14)119884=01027Dbh

24798

Mugasha

etal[15]

Mixed

species(49

spp)

minus2421

452

minus681

885

2119

1739

119873=167D

bh11ndash

110cm

(15)119884=00763Dbh

22046ht

04918

Mugasha

etal[15]

Mixed

species(49

spp)

minus2038

minus12

7minus1109

minus335

1557

975

119873=167D

bh11ndash

110cm

(16)


Brow

n[1]

Mixed

species(no

tind

icated)minus5002

minus3029


119873=191D

bh3ndash30c

mdaggerFo

reachmod

elther

ange

ofdiam

etersinthem

aterialformingtheb

asisforthe

mod

elisspecified


5 Conclusion





Acknowledgments


References







































Journal of












Volume 2014

Advances in









Geophysics



















(0166)19663(0088)

09118(0174) 12ndash543 0997 0142 199

(df = 38) 4 minus85018(0077)

24142(0027) mdash 12ndash543 0995 0185 349


(0379)20335(0141)

16858(0314) 5ndash543 0990 0209 minus002

(df = 32) 4 minus98909(0203)

27460(0066) mdash 5ndash543 0981 0286 214


(0149)20638(0078)

07847(0155) 12ndash543 0998 0127 160

(df = 38) 4 minus19040(0068)

24492(0024) mdash 12ndash543 0996 0162 267

(df = 38) 6 minus93309(0108)

09827(0008) mdash 12ndash543 0998 0127 166


(0343)21424(0128)

15563(0284) 5ndash543 0992 0189 minus057

(df = 32) 4 minus33345(0185)

28002(0061) mdash 5ndash543 0985 0262 117



(0165)19212(0099)

07712(0183) 22ndash265 0987 0171 290

(df = 39) 4 minus85247(0130)

22972(0051) mdash 22ndash265 0981 0204 424


(0223)20420(0126)

10908(0193) 5ndash265 0977 0146 464

(df = 31) 4 minus98028(0277)

26237(0102) mdash 5ndash265 0954 0206 498


(0165)19685(0099)

07545(0183) 22ndash265 0987 0170 288

(df = 39) 4 minus19395(0129)

23364(0050) mdash 22ndash265 0982 0203 420

(df = 39) 6 minus88347(0230)

09371(0168) mdash 22ndash265 0987 0170 298


(0230)21112(0130)

10410(0199) 5ndash265 0976 0151 441

(df = 31) 4 minus32047(0275)

26663(0101) mdash 5ndash265 0956 0205 466



(0191)19701(0059)

08854(0152) 18ndash215 0991 0144 204

(df = 35) 4 minus83253(0120)

22413(0051) mdash 18ndash215 0982 0200 390


(0761)20113(0246)

27732(0455) 5ndash215 0871 0355 1297

(df = 30) 4 minus105743(0793)

27785(0313) mdash 5ndash215 0715 0528 3287


(0199)19900(0062)

09035(0159) 18ndash215 0990 0150 122

(df = 35) 4 minus17001(0124)

22667(0052) mdash 18ndash215 0981 0206 300


Table 1 Continued


(df = 35) 6 minus93782(0213)

09823(0016) mdash 18ndash215 0990 0148 137


(0776)20138(0250)

28503(0464) 5ndash215 0869 0362 1153

(df = 30) 4 minus39094(0812)

28023(0321) mdash 5ndash215 0708 0541 3054

(df = 30) 6 minus145150(1467)

12961(0108) mdash 5ndash215 0823 0421 1700






(5) ln (119884)119894119895= 119891(Dbh

119894119895 ht119894119895) + V119894+ 120576119894119895


119894119895 ht119894119895) is one of the


2



119894119895sim 119873(0 120590

2) Thus for







119884measured (1)



3 Results








(0237)22340(0099)

00507ns(0206) 18ndash215 0979 0251 000 1848

(df = 28) 4 minus82844(0152)

22517(2252) mdash 18ndash215 0979 0247 000 1857


(0673)17917(0316)

28547(0453) 5ndash215 0865 0533 000 3034

(df = 24) 4 minus108001(0710)

26587(0299) mdash 5ndash215 0792 0482 0636 5779


(0252)22145(0106)

01591ns(0219) 18ndash215 0977 0267 000 2190

(df = 28) 4 minus17179(0163)

22697(0073) mdash 18ndash215 0977 0265 000 2243

(df = 28) 6 minus86142(0427)

09417(0034) mdash 18ndash215 0968 0266 0184 1893


(0639)19676(0257)

26083(0428) 5ndash215 0916 0390 0276 2950

(df = 24) 4 minus43236(0705)

26903(0296) mdash 5ndash215 0799 0470 0676 5602



(0075)18067(0040)

11940(0076) 14ndash62 0997 0129 000 166

(df = 70) 4 minus84800(0099)

23351(0033) mdash 14ndash62 0986 0219 0179 646


(0166)19316(0079)

15360(0119) 5ndash62 0994 0162 000 455

(df = 35) 4 minus109307(0273)

30134(0093) mdash 5ndash62 0975 0317 0119 1310


(0123)17586(0057)

12934(0115) 14ndash62 0992 0118 0278 247

(df = 70) 4 minus20667(0124)

23561(0036) mdash 14ndash62 0979 0213 0392 996

(df = 70) 6 minus91880(0101)

09668(0007) mdash 14ndash62 0996 0131 0052 132


(0326)21420(0158)

17090(0269) 5ndash62 0965 0294 0221 630

(df = 38) 4 minus44622(0365)

29972(0120) mdash 5ndash62 0928 0387 0375 1060



(0104)19637(0053)

07737(0103) 14ndash62 0989 0193 0131 654

(df = 101) 4 minus84554(0084)

23236(0031) mdash 14ndash62 0983 0248 0140 989


(0244)21378(0127)

17695(0203) 5ndash62 0977 0271 0153 1850

(df = 43) 4 minus111929(0339)

30514(0115) mdash 5ndash62 0935 0413 0327 4922


(0131)19041(0064)

09377(0128) 14ndash62 0983 0182 0317 896

(df = 101) 4 minus19564(0102)

23260(0035) mdash 14ndash62 0974 0242 0327 1260


Table 2 Continued


(df = 101) 6 minus88819(0139)

09497(0010) mdash 14ndash62 0988 0187 0162 640


(0279)20894(0146)

19457(0238) 5ndash62 0970 0290 0230 1370

(df = 43) 4 minus48335(0349)

30979(0117) mdash 5ndash62 0924 0383 0488 4310

(df = 43) 6 minus135156(0455)

12284(0032) mdash 5ndash62 0971 0314 0153 2510


TreesShrubs

00001

0001

001

01

1

10

00001

0001

001

01

1




1 10 10000001

0001

001

01

1

10

00001

0001

001

01

1

10

1 10 100 1 10 100 1 10 100

Tota

l vol

ume (

m3)


(a)



Shrubs

1 10 10001

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000Trees

1 10 100

Shrubs and trees

1 10 100

All three models

1 10 100

Tota

l bio

mas

s (kg)


(b)







4 Discussion









Table3Av


fmeasuredvalues

asob

served

forp

reviou

slypu

blish

edvolumeandbiom

asse

quations

form

iombo

woo

dlands

whenappliedto

species-specificand


inthisstu

dyM

odelsd

evelo

pedin

thisstu

dyareincludedforcom

paris

onSym


3 )or

biom

ass(kg)Dbh

isdiam

eteratbreastheight

(cm)

htistotalh

eight(m)BA

isbasalarea(

cm2 )and119873

issamples

ize

Mod

eldagger

Source

Nam

eofspecies

Averagee

rror

inpercentfor

thed

atasetsp

reparedin

thisstu

dyB

spiciform

isC

molle

Darbutifolia

Shrubs

Trees

Com

bined

Mod

el(3)=

totalvolum

eTh

isstu

dy19

9290

204

1848

166

654

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(7)log10119884=minus385+249log 10Dbh

Abbo

tetal[24]

Brachyste

giaboehmii

minus1073

2176

1201

2998

844

1534

119873=27D

bh8ndash4

0cm


Temu[22]

Brachyste

giaspiciform

isminus603

1712

012

282

1048

745

119873=un

know

nDbh

5ndash4

3cm

(9)119884=0092Dbh

259

Malim

bwiand

Temu[23]

Pterocarpu

sangolensis

minus2116

445

minus686

minus111minus445

minus364

119873=25D

bh6ndash6

1cm

(10)


Abbo

tetal[24]

Mixed

species(17

spp)

minus1536

877

minus57

minus266

106

minus020

119873=51D

bh5ndash4

0(11)119884=00001Dbh

2032 ht0

66Malim

bwietal[13]

Mixed

species(13

spp)

minus2091

minus19

4minus110

minus74

5minus1282minus1126

119873=17D

bh8ndash4

3cm

Mod

el(3)=

totalbiomass

Thisstu

dy16

0288

122

2190

247

896

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(12)119884=006Dbh

2012 ht0

71Malim

bwietal[13]

Mixed

species(13

spp)

minus3856

minus2344


minus1168

119873=17D

bh8ndash4

3cm

(13)119884=00263Dbh

1505ht

1762

Cham

sham

aetal[14

]Mixed

species(20

spp)

minus2817

minus3317

minus3628


119873=30D

bh11ndash

50cm

(14)119884=01027Dbh

24798

Mugasha

etal[15]

Mixed

species(49

spp)

minus2421

452

minus681

885

2119

1739

119873=167D

bh11ndash

110cm

(15)119884=00763Dbh

22046ht

04918

Mugasha

etal[15]

Mixed

species(49

spp)

minus2038

minus12

7minus1109

minus335

1557

975

119873=167D

bh11ndash

110cm

(16)


Brow

n[1]

Mixed

species(no

tind

icated)minus5002

minus3029


119873=191D

bh3ndash30c

mdaggerFo

reachmod

elther

ange

ofdiam

etersinthem

aterialformingtheb

asisforthe

mod

elisspecified


5 Conclusion





Acknowledgments


References







































Journal of












Volume 2014

Advances in









Geophysics















Table 1 Continued


(df = 35) 6 minus93782(0213)

09823(0016) mdash 18ndash215 0990 0148 137


(0776)20138(0250)

28503(0464) 5ndash215 0869 0362 1153

(df = 30) 4 minus39094(0812)

28023(0321) mdash 5ndash215 0708 0541 3054

(df = 30) 6 minus145150(1467)

12961(0108) mdash 5ndash215 0823 0421 1700






(5) ln (119884)119894119895= 119891(Dbh

119894119895 ht119894119895) + V119894+ 120576119894119895


119894119895 ht119894119895) is one of the


2



119894119895sim 119873(0 120590

2) Thus for







119884measured (1)



3 Results








(0237)22340(0099)

00507ns(0206) 18ndash215 0979 0251 000 1848

(df = 28) 4 minus82844(0152)

22517(2252) mdash 18ndash215 0979 0247 000 1857


(0673)17917(0316)

28547(0453) 5ndash215 0865 0533 000 3034

(df = 24) 4 minus108001(0710)

26587(0299) mdash 5ndash215 0792 0482 0636 5779


(0252)22145(0106)

01591ns(0219) 18ndash215 0977 0267 000 2190

(df = 28) 4 minus17179(0163)

22697(0073) mdash 18ndash215 0977 0265 000 2243

(df = 28) 6 minus86142(0427)

09417(0034) mdash 18ndash215 0968 0266 0184 1893


(0639)19676(0257)

26083(0428) 5ndash215 0916 0390 0276 2950

(df = 24) 4 minus43236(0705)

26903(0296) mdash 5ndash215 0799 0470 0676 5602



(0075)18067(0040)

11940(0076) 14ndash62 0997 0129 000 166

(df = 70) 4 minus84800(0099)

23351(0033) mdash 14ndash62 0986 0219 0179 646


(0166)19316(0079)

15360(0119) 5ndash62 0994 0162 000 455

(df = 35) 4 minus109307(0273)

30134(0093) mdash 5ndash62 0975 0317 0119 1310


(0123)17586(0057)

12934(0115) 14ndash62 0992 0118 0278 247

(df = 70) 4 minus20667(0124)

23561(0036) mdash 14ndash62 0979 0213 0392 996

(df = 70) 6 minus91880(0101)

09668(0007) mdash 14ndash62 0996 0131 0052 132


(0326)21420(0158)

17090(0269) 5ndash62 0965 0294 0221 630

(df = 38) 4 minus44622(0365)

29972(0120) mdash 5ndash62 0928 0387 0375 1060



(0104)19637(0053)

07737(0103) 14ndash62 0989 0193 0131 654

(df = 101) 4 minus84554(0084)

23236(0031) mdash 14ndash62 0983 0248 0140 989


(0244)21378(0127)

17695(0203) 5ndash62 0977 0271 0153 1850

(df = 43) 4 minus111929(0339)

30514(0115) mdash 5ndash62 0935 0413 0327 4922


(0131)19041(0064)

09377(0128) 14ndash62 0983 0182 0317 896

(df = 101) 4 minus19564(0102)

23260(0035) mdash 14ndash62 0974 0242 0327 1260


Table 2 Continued


(df = 101) 6 minus88819(0139)

09497(0010) mdash 14ndash62 0988 0187 0162 640


(0279)20894(0146)

19457(0238) 5ndash62 0970 0290 0230 1370

(df = 43) 4 minus48335(0349)

30979(0117) mdash 5ndash62 0924 0383 0488 4310

(df = 43) 6 minus135156(0455)

12284(0032) mdash 5ndash62 0971 0314 0153 2510


TreesShrubs

00001

0001

001

01

1

10

00001

0001

001

01

1




1 10 10000001

0001

001

01

1

10

00001

0001

001

01

1

10

1 10 100 1 10 100 1 10 100

Tota

l vol

ume (

m3)


(a)



Shrubs

1 10 10001

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000Trees

1 10 100

Shrubs and trees

1 10 100

All three models

1 10 100

Tota

l bio

mas

s (kg)


(b)







4 Discussion









Table3Av


fmeasuredvalues

asob

served

forp

reviou

slypu

blish

edvolumeandbiom

asse

quations

form

iombo

woo

dlands

whenappliedto

species-specificand


inthisstu

dyM

odelsd

evelo

pedin

thisstu

dyareincludedforcom

paris

onSym


3 )or

biom

ass(kg)Dbh

isdiam

eteratbreastheight

(cm)

htistotalh

eight(m)BA

isbasalarea(

cm2 )and119873

issamples

ize

Mod

eldagger

Source

Nam

eofspecies

Averagee

rror

inpercentfor

thed

atasetsp

reparedin

thisstu

dyB

spiciform

isC

molle

Darbutifolia

Shrubs

Trees

Com

bined

Mod

el(3)=

totalvolum

eTh

isstu

dy19

9290

204

1848

166

654

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(7)log10119884=minus385+249log 10Dbh

Abbo

tetal[24]

Brachyste

giaboehmii

minus1073

2176

1201

2998

844

1534

119873=27D

bh8ndash4

0cm


Temu[22]

Brachyste

giaspiciform

isminus603

1712

012

282

1048

745

119873=un

know

nDbh

5ndash4

3cm

(9)119884=0092Dbh

259

Malim

bwiand

Temu[23]

Pterocarpu

sangolensis

minus2116

445

minus686

minus111minus445

minus364

119873=25D

bh6ndash6

1cm

(10)


Abbo

tetal[24]

Mixed

species(17

spp)

minus1536

877

minus57

minus266

106

minus020

119873=51D

bh5ndash4

0(11)119884=00001Dbh

2032 ht0

66Malim

bwietal[13]

Mixed

species(13

spp)

minus2091

minus19

4minus110

minus74

5minus1282minus1126

119873=17D

bh8ndash4

3cm

Mod

el(3)=

totalbiomass

Thisstu

dy16

0288

122

2190

247

896

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(12)119884=006Dbh

2012 ht0

71Malim

bwietal[13]

Mixed

species(13

spp)

minus3856

minus2344


minus1168

119873=17D

bh8ndash4

3cm

(13)119884=00263Dbh

1505ht

1762

Cham

sham

aetal[14

]Mixed

species(20

spp)

minus2817

minus3317

minus3628


119873=30D

bh11ndash

50cm

(14)119884=01027Dbh

24798

Mugasha

etal[15]

Mixed

species(49

spp)

minus2421

452

minus681

885

2119

1739

119873=167D

bh11ndash

110cm

(15)119884=00763Dbh

22046ht

04918

Mugasha

etal[15]

Mixed

species(49

spp)

minus2038

minus12

7minus1109

minus335

1557

975

119873=167D

bh11ndash

110cm

(16)


Brow

n[1]

Mixed

species(no

tind

icated)minus5002

minus3029


119873=191D

bh3ndash30c

mdaggerFo

reachmod

elther

ange

ofdiam

etersinthem

aterialformingtheb

asisforthe

mod

elisspecified


5 Conclusion





Acknowledgments


References







































Journal of












Volume 2014

Advances in









Geophysics



















(0237)22340(0099)

00507ns(0206) 18ndash215 0979 0251 000 1848

(df = 28) 4 minus82844(0152)

22517(2252) mdash 18ndash215 0979 0247 000 1857


(0673)17917(0316)

28547(0453) 5ndash215 0865 0533 000 3034

(df = 24) 4 minus108001(0710)

26587(0299) mdash 5ndash215 0792 0482 0636 5779


(0252)22145(0106)

01591ns(0219) 18ndash215 0977 0267 000 2190

(df = 28) 4 minus17179(0163)

22697(0073) mdash 18ndash215 0977 0265 000 2243

(df = 28) 6 minus86142(0427)

09417(0034) mdash 18ndash215 0968 0266 0184 1893


(0639)19676(0257)

26083(0428) 5ndash215 0916 0390 0276 2950

(df = 24) 4 minus43236(0705)

26903(0296) mdash 5ndash215 0799 0470 0676 5602



(0075)18067(0040)

11940(0076) 14ndash62 0997 0129 000 166

(df = 70) 4 minus84800(0099)

23351(0033) mdash 14ndash62 0986 0219 0179 646


(0166)19316(0079)

15360(0119) 5ndash62 0994 0162 000 455

(df = 35) 4 minus109307(0273)

30134(0093) mdash 5ndash62 0975 0317 0119 1310


(0123)17586(0057)

12934(0115) 14ndash62 0992 0118 0278 247

(df = 70) 4 minus20667(0124)

23561(0036) mdash 14ndash62 0979 0213 0392 996

(df = 70) 6 minus91880(0101)

09668(0007) mdash 14ndash62 0996 0131 0052 132


(0326)21420(0158)

17090(0269) 5ndash62 0965 0294 0221 630

(df = 38) 4 minus44622(0365)

29972(0120) mdash 5ndash62 0928 0387 0375 1060



(0104)19637(0053)

07737(0103) 14ndash62 0989 0193 0131 654

(df = 101) 4 minus84554(0084)

23236(0031) mdash 14ndash62 0983 0248 0140 989


(0244)21378(0127)

17695(0203) 5ndash62 0977 0271 0153 1850

(df = 43) 4 minus111929(0339)

30514(0115) mdash 5ndash62 0935 0413 0327 4922


(0131)19041(0064)

09377(0128) 14ndash62 0983 0182 0317 896

(df = 101) 4 minus19564(0102)

23260(0035) mdash 14ndash62 0974 0242 0327 1260


Table 2 Continued


(df = 101) 6 minus88819(0139)

09497(0010) mdash 14ndash62 0988 0187 0162 640


(0279)20894(0146)

19457(0238) 5ndash62 0970 0290 0230 1370

(df = 43) 4 minus48335(0349)

30979(0117) mdash 5ndash62 0924 0383 0488 4310

(df = 43) 6 minus135156(0455)

12284(0032) mdash 5ndash62 0971 0314 0153 2510


TreesShrubs

00001

0001

001

01

1

10

00001

0001

001

01

1




1 10 10000001

0001

001

01

1

10

00001

0001

001

01

1

10

1 10 100 1 10 100 1 10 100

Tota

l vol

ume (

m3)


(a)



Shrubs

1 10 10001

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000Trees

1 10 100

Shrubs and trees

1 10 100

All three models

1 10 100

Tota

l bio

mas

s (kg)


(b)







4 Discussion









Table3Av


fmeasuredvalues

asob

served

forp

reviou

slypu

blish

edvolumeandbiom

asse

quations

form

iombo

woo

dlands

whenappliedto

species-specificand


inthisstu

dyM

odelsd

evelo

pedin

thisstu

dyareincludedforcom

paris

onSym


3 )or

biom

ass(kg)Dbh

isdiam

eteratbreastheight

(cm)

htistotalh

eight(m)BA

isbasalarea(

cm2 )and119873

issamples

ize

Mod

eldagger

Source

Nam

eofspecies

Averagee

rror

inpercentfor

thed

atasetsp

reparedin

thisstu

dyB

spiciform

isC

molle

Darbutifolia

Shrubs

Trees

Com

bined

Mod

el(3)=

totalvolum

eTh

isstu

dy19

9290

204

1848

166

654

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(7)log10119884=minus385+249log 10Dbh

Abbo

tetal[24]

Brachyste

giaboehmii

minus1073

2176

1201

2998

844

1534

119873=27D

bh8ndash4

0cm


Temu[22]

Brachyste

giaspiciform

isminus603

1712

012

282

1048

745

119873=un

know

nDbh

5ndash4

3cm

(9)119884=0092Dbh

259

Malim

bwiand

Temu[23]

Pterocarpu

sangolensis

minus2116

445

minus686

minus111minus445

minus364

119873=25D

bh6ndash6

1cm

(10)


Abbo

tetal[24]

Mixed

species(17

spp)

minus1536

877

minus57

minus266

106

minus020

119873=51D

bh5ndash4

0(11)119884=00001Dbh

2032 ht0

66Malim

bwietal[13]

Mixed

species(13

spp)

minus2091

minus19

4minus110

minus74

5minus1282minus1126

119873=17D

bh8ndash4

3cm

Mod

el(3)=

totalbiomass

Thisstu

dy16

0288

122

2190

247

896

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(12)119884=006Dbh

2012 ht0

71Malim

bwietal[13]

Mixed

species(13

spp)

minus3856

minus2344


minus1168

119873=17D

bh8ndash4

3cm

(13)119884=00263Dbh

1505ht

1762

Cham

sham

aetal[14

]Mixed

species(20

spp)

minus2817

minus3317

minus3628


119873=30D

bh11ndash

50cm

(14)119884=01027Dbh

24798

Mugasha

etal[15]

Mixed

species(49

spp)

minus2421

452

minus681

885

2119

1739

119873=167D

bh11ndash

110cm

(15)119884=00763Dbh

22046ht

04918

Mugasha

etal[15]

Mixed

species(49

spp)

minus2038

minus12

7minus1109

minus335

1557

975

119873=167D

bh11ndash

110cm

(16)


Brow

n[1]

Mixed

species(no

tind

icated)minus5002

minus3029


119873=191D

bh3ndash30c

mdaggerFo

reachmod

elther

ange

ofdiam

etersinthem

aterialformingtheb

asisforthe

mod

elisspecified


5 Conclusion





Acknowledgments


References







































Journal of












Volume 2014

Advances in









Geophysics















Table 2 Continued


(df = 101) 6 minus88819(0139)

09497(0010) mdash 14ndash62 0988 0187 0162 640


(0279)20894(0146)

19457(0238) 5ndash62 0970 0290 0230 1370

(df = 43) 4 minus48335(0349)

30979(0117) mdash 5ndash62 0924 0383 0488 4310

(df = 43) 6 minus135156(0455)

12284(0032) mdash 5ndash62 0971 0314 0153 2510


TreesShrubs

00001

0001

001

01

1

10

00001

0001

001

01

1




1 10 10000001

0001

001

01

1

10

00001

0001

001

01

1

10

1 10 100 1 10 100 1 10 100

Tota

l vol

ume (

m3)


(a)



Shrubs

1 10 10001

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000

01

1

10

100

1000

10000Trees

1 10 100

Shrubs and trees

1 10 100

All three models

1 10 100

Tota

l bio

mas

s (kg)


(b)







4 Discussion









Table3Av


fmeasuredvalues

asob

served

forp

reviou

slypu

blish

edvolumeandbiom

asse

quations

form

iombo

woo

dlands

whenappliedto

species-specificand


inthisstu

dyM

odelsd

evelo

pedin

thisstu

dyareincludedforcom

paris

onSym


3 )or

biom

ass(kg)Dbh

isdiam

eteratbreastheight

(cm)

htistotalh

eight(m)BA

isbasalarea(

cm2 )and119873

issamples

ize

Mod

eldagger

Source

Nam

eofspecies

Averagee

rror

inpercentfor

thed

atasetsp

reparedin

thisstu

dyB

spiciform

isC

molle

Darbutifolia

Shrubs

Trees

Com

bined

Mod

el(3)=

totalvolum

eTh

isstu

dy19

9290

204

1848

166

654

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(7)log10119884=minus385+249log 10Dbh

Abbo

tetal[24]

Brachyste

giaboehmii

minus1073

2176

1201

2998

844

1534

119873=27D

bh8ndash4

0cm


Temu[22]

Brachyste

giaspiciform

isminus603

1712

012

282

1048

745

119873=un

know

nDbh

5ndash4

3cm

(9)119884=0092Dbh

259

Malim

bwiand

Temu[23]

Pterocarpu

sangolensis

minus2116

445

minus686

minus111minus445

minus364

119873=25D

bh6ndash6

1cm

(10)


Abbo

tetal[24]

Mixed

species(17

spp)

minus1536

877

minus57

minus266

106

minus020

119873=51D

bh5ndash4

0(11)119884=00001Dbh

2032 ht0

66Malim

bwietal[13]

Mixed

species(13

spp)

minus2091

minus19

4minus110

minus74

5minus1282minus1126

119873=17D

bh8ndash4

3cm

Mod

el(3)=

totalbiomass

Thisstu

dy16

0288

122

2190

247

896

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(12)119884=006Dbh

2012 ht0

71Malim

bwietal[13]

Mixed

species(13

spp)

minus3856

minus2344


minus1168

119873=17D

bh8ndash4

3cm

(13)119884=00263Dbh

1505ht

1762

Cham

sham

aetal[14

]Mixed

species(20

spp)

minus2817

minus3317

minus3628


119873=30D

bh11ndash

50cm

(14)119884=01027Dbh

24798

Mugasha

etal[15]

Mixed

species(49

spp)

minus2421

452

minus681

885

2119

1739

119873=167D

bh11ndash

110cm

(15)119884=00763Dbh

22046ht

04918

Mugasha

etal[15]

Mixed

species(49

spp)

minus2038

minus12

7minus1109

minus335

1557

975

119873=167D

bh11ndash

110cm

(16)


Brow

n[1]

Mixed

species(no

tind

icated)minus5002

minus3029


119873=191D

bh3ndash30c

mdaggerFo

reachmod

elther

ange

ofdiam

etersinthem

aterialformingtheb

asisforthe

mod

elisspecified


5 Conclusion





Acknowledgments


References







































Journal of












Volume 2014

Advances in









Geophysics
















4 Discussion









Table3Av


fmeasuredvalues

asob

served

forp

reviou

slypu

blish

edvolumeandbiom

asse

quations

form

iombo

woo

dlands

whenappliedto

species-specificand


inthisstu

dyM

odelsd

evelo

pedin

thisstu

dyareincludedforcom

paris

onSym


3 )or

biom

ass(kg)Dbh

isdiam

eteratbreastheight

(cm)

htistotalh

eight(m)BA

isbasalarea(

cm2 )and119873

issamples

ize

Mod

eldagger

Source

Nam

eofspecies

Averagee

rror

inpercentfor

thed

atasetsp

reparedin

thisstu

dyB

spiciform

isC

molle

Darbutifolia

Shrubs

Trees

Com

bined

Mod

el(3)=

totalvolum

eTh

isstu

dy19

9290

204

1848

166

654

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(7)log10119884=minus385+249log 10Dbh

Abbo

tetal[24]

Brachyste

giaboehmii

minus1073

2176

1201

2998

844

1534

119873=27D

bh8ndash4

0cm


Temu[22]

Brachyste

giaspiciform

isminus603

1712

012

282

1048

745

119873=un

know

nDbh

5ndash4

3cm

(9)119884=0092Dbh

259

Malim

bwiand

Temu[23]

Pterocarpu

sangolensis

minus2116

445

minus686

minus111minus445

minus364

119873=25D

bh6ndash6

1cm

(10)


Abbo

tetal[24]

Mixed

species(17

spp)

minus1536

877

minus57

minus266

106

minus020

119873=51D

bh5ndash4

0(11)119884=00001Dbh

2032 ht0

66Malim

bwietal[13]

Mixed

species(13

spp)

minus2091

minus19

4minus110

minus74

5minus1282minus1126

119873=17D

bh8ndash4

3cm

Mod

el(3)=

totalbiomass

Thisstu

dy16

0288

122

2190

247

896

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(12)119884=006Dbh

2012 ht0

71Malim

bwietal[13]

Mixed

species(13

spp)

minus3856

minus2344


minus1168

119873=17D

bh8ndash4

3cm

(13)119884=00263Dbh

1505ht

1762

Cham

sham

aetal[14

]Mixed

species(20

spp)

minus2817

minus3317

minus3628


119873=30D

bh11ndash

50cm

(14)119884=01027Dbh

24798

Mugasha

etal[15]

Mixed

species(49

spp)

minus2421

452

minus681

885

2119

1739

119873=167D

bh11ndash

110cm

(15)119884=00763Dbh

22046ht

04918

Mugasha

etal[15]

Mixed

species(49

spp)

minus2038

minus12

7minus1109

minus335

1557

975

119873=167D

bh11ndash

110cm

(16)


Brow

n[1]

Mixed

species(no

tind

icated)minus5002

minus3029


119873=191D

bh3ndash30c

mdaggerFo

reachmod

elther

ange

ofdiam

etersinthem

aterialformingtheb

asisforthe

mod

elisspecified


5 Conclusion





Acknowledgments


References







































Journal of












Volume 2014

Advances in









Geophysics















Table3Av


fmeasuredvalues

asob

served

forp

reviou

slypu

blish

edvolumeandbiom

asse

quations

form

iombo

woo

dlands

whenappliedto

species-specificand


inthisstu

dyM

odelsd

evelo

pedin

thisstu

dyareincludedforcom

paris

onSym


3 )or

biom

ass(kg)Dbh

isdiam

eteratbreastheight

(cm)

htistotalh

eight(m)BA

isbasalarea(

cm2 )and119873

issamples

ize

Mod

eldagger

Source

Nam

eofspecies

Averagee

rror

inpercentfor

thed

atasetsp

reparedin

thisstu

dyB

spiciform

isC

molle

Darbutifolia

Shrubs

Trees

Com

bined

Mod

el(3)=

totalvolum

eTh

isstu

dy19

9290

204

1848

166

654

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(7)log10119884=minus385+249log 10Dbh

Abbo

tetal[24]

Brachyste

giaboehmii

minus1073

2176

1201

2998

844

1534

119873=27D

bh8ndash4

0cm


Temu[22]

Brachyste

giaspiciform

isminus603

1712

012

282

1048

745

119873=un

know

nDbh

5ndash4

3cm

(9)119884=0092Dbh

259

Malim

bwiand

Temu[23]

Pterocarpu

sangolensis

minus2116

445

minus686

minus111minus445

minus364

119873=25D

bh6ndash6

1cm

(10)


Abbo

tetal[24]

Mixed

species(17

spp)

minus1536

877

minus57

minus266

106

minus020

119873=51D

bh5ndash4

0(11)119884=00001Dbh

2032 ht0

66Malim

bwietal[13]

Mixed

species(13

spp)

minus2091

minus19

4minus110

minus74

5minus1282minus1126

119873=17D

bh8ndash4

3cm

Mod

el(3)=

totalbiomass

Thisstu

dy16

0288

122

2190

247

896

ln(119884)=119886+119887ln(Dbh)+119888ln(ht)

(12)119884=006Dbh

2012 ht0

71Malim

bwietal[13]

Mixed

species(13

spp)

minus3856

minus2344


minus1168

119873=17D

bh8ndash4

3cm

(13)119884=00263Dbh

1505ht

1762

Cham

sham

aetal[14

]Mixed

species(20

spp)

minus2817

minus3317

minus3628


119873=30D

bh11ndash

50cm

(14)119884=01027Dbh

24798

Mugasha

etal[15]

Mixed

species(49

spp)

minus2421

452

minus681

885

2119

1739

119873=167D

bh11ndash

110cm

(15)119884=00763Dbh

22046ht

04918

Mugasha

etal[15]

Mixed

species(49

spp)

minus2038

minus12

7minus1109

minus335

1557

975

119873=167D

bh11ndash

110cm

(16)


Brow

n[1]

Mixed

species(no

tind

icated)minus5002

minus3029


119873=191D

bh3ndash30c

mdaggerFo

reachmod

elther

ange

ofdiam

etersinthem

aterialformingtheb

asisforthe

mod

elisspecified


5 Conclusion





Acknowledgments


References







































Journal of












Volume 2014

Advances in









Geophysics















5 Conclusion





Acknowledgments


References







































Journal of












Volume 2014

Advances in









Geophysics
































Journal of












Volume 2014

Advances in









Geophysics














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