Originalscientificpaper

Croat. j. for. eng. 37(2016)1 37

Effect of Forest Structure on Operational

Efficiency of a Bundle-Harvester System in Early Thinnings

Dan Bergström, Fulvio Di Fulvio, Yrjö Nuutinen

Abstract

The objective of the study was to improve knowledge on effects of harvested tree size and den-sity of undergrowth on the operational efficiency of a bundle-harvester that produces 2.6 m long bundles, with ca. 60–70 cm diameter, in early fuel wood thinnings. In total 26 time study plots were marked out in 30 to 35 year old Scots pine dominated stands with initial density of 2800–9300 trees/ha and stem size range of 15–43 dm3. Ten of the units, randomly chosen, were precleared of undergrowth trees (≤2.5 cm at breast height diameter) prior to harvesting.There were no significant differences between treatments (preclearing vs. no preclearing) in properties or operational efficiency of the harvested and remaining stands. The average height of cut trees and volume of cut stems were 7.4 m and 16.2 dm3, respectively, and on average, 3554 trees/ha were removed. The bundles had a mean fresh mass of 439 kg and the mass was correlated to the proportion of birch trees cut. The productivity was, on average, 3.1 OD t/PM0H (6.6 fresh t/PM0H; 15.1 bundles/PM0H, where PM0H is productive machine hours, without delays) and was modeled with the harvested stem volume (dm3) as a single independent variable. The study provides complementary knowledge to earlier studies of the system’s performance, especially for harvesting stems <30 dm3. Its productivity was limited by the cutting efficiency and could probably be significantly increased by using a felling and bunching head that could cut and accumulate trees during continuous boom movements. Thus, it would be informative to evaluate such a system in various early thinning stand conditions, including assessments of its manoeuvrability in more difficult terrain.

Keywords: pre-commercial thinning, productivity, Scots pine, bioenergy

masscanalsobedeliveredunprocessedorcomminut-ed to terminals for reloading, intermediate storage and/orcomminutionbeforefurthertransportation(Konsetal.2015).Thisisapotentiallyimportantdifference,ashighpayloadsduringterrainandroadtransportationarecrucialforproducinganddeliveringforestfuelswithhighcostefficiency.Comminutionat roadsidelandingsincreasespayloadsforbulkymaterialslikelogging residues from clear cuts and small-diameter wholetreesfromearlythinnings,butitacceleratesdeg-radation, so comminuted material must be delivered to industrialsitesquickly toavoidsignificantbiomasslosses(cf.Jirjis1995).Anotherdrawbackisthatspe-ciallydesignedtrucksforcomminutedmaterialsmustbeusedratherthanstandardtimbertrucksinthesup-

1. IntroductionSmall-diametertreesinyoungdenseforestsareal-

readyharvestedintheNordiccountriestoproducefuelsforheatandpowergeneration,andharvestsareexpectedtoincreaseasdemandforhighqualityresid-ual biomasses for biorefining rises (Bergström andMatisons2014).InSweden,potentialannualextractionsof such trees amount to ca. 6.5x106 m3;fivetimesmorethancurrentharvests(Routaetal.2013).Correspond-ing quantities for Finland are 7.7x106 m3, which would give33%morethancurrently(Routaetal.2013).Smallheatingplantsoftenrequiredeliveriesofcomminutedfuels, while large-scale heat and combined heat and powerplantscannormallycomminutematerialon-site,andthusalsoreceiveunprocessedtreeparts.Thebio-

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38 Croat. j. for. eng. 37(2016)1

plychain.Further,comminutionismorecostlyatland-ingsthanatterminalsorindustrialsitesastheopera-tionalefficiencyisaffectedbythescaleofmachinery(cf.Kärhä2011).Alternatively,thebiomasscouldbecompressedandbundledintoca2.5–3.5mlongbun-dleswithdensitiesof270–780kg/m3 in the stand, or at roadside,beforefurtherhandlingandtransport(Nor-dfjellandLiss2000,PetterssonandNordfjell2007,Jo-hanssonetal.2006,KärhäandVartiamäki2006,JylhäandLaitila2007).Suchsystemshavebeenstudied,andresultsindicatethattheymayhavesufficientadvan-tagesthroughoutthesupplychain,ifconvenientbun-dlesfortransportonconventionaltimbertruckscanbeproduced(Johanssonetal.2006,Jylhä2011,Kärhäetal.2011,BergströmandDiFulvio2014a).Thebundlesareeasytohandlewhentheyarereloaded,drywellduringstorageandcanbeeffectivelycomminutedus-ing large-scalesystems.However,currentbundlingmachineryiscostlyandnewsystemswithhighercostefficiencyarerequired.BergströmandDiFulvio(2014a)haveshownthatwithfurtherdevelopmentbundle-harvestingsystemsforyoungdensethinningscouldbeupto15%morecostefficient(whenincludingtrans-portationinanalysis)thanconventionaltree-parthan-dlingsystems.Intestsofaprototypewhole-treebundle-harvester

forsmall-diametertreesinFinland,reportedbyJylhäandLaitila(2007),bundlingproductivitywaslimitedbecausesimultaneousharvestingandbundlingphas-esaccountedforonly8–18%ofthemonitoredeffectiveworkingtime.Thecitedauthorsconcludedthatthestudiedsystemwasnotcompetitivewithconvention-alharvestingsystemsbuthadgreatpotentialforfu-turedevelopment.Nuutinenetal.(2011)foundthatasecondprototypeofthemachinehad38–77%higherproductivitythanthefirst,duetoahighercutting-accumulationcapacityandbetterbundlinghydrau-lics,which increasedpossibilities for simultaneouscuttingandbundling.Athirdversionofthebundle-harvestersystemwas

launchedin2013,withreportedincreasesinefficiency(time/bundle)of111–133%comparedtothepreviousversion (»Fixteri II«),providingproductivitiesof9.7–13.8m3solid /PM0Hwhen thinning Scots pinedominated stands, removing stems with average vol-umesof27–84dm3 (NuutinenandBjörheden2015).The solidvolumesof theproducedbundles rangefrom 0.3 to 0.5 m3(JylhäandLaitila2007)andtheiruseincreasesforwardersandtruckspayloadsbyca50%,respectively,incomparisontohandlingloosemateri-als(Laitilaetal.2009).However,thesystem’sproduc-tivityhasnotbeenextensivelystudiedinstandswithan average harvested tree volume <30 dm3, in which

theremaybesignificantproportionsofdisturbingun-dergrowthtreesthatmayreducecuttingproductivi-ties(cf.Kärhä2006,2015a,2015b,Jonsson2015),andhencecostefficiency.

1.1 ObjectivesTheobjectiveofthestudypresentedherewasto

evaluateeffectsofharvestedtreesizeanddensityofundergrowthontheoperationalefficiencyofthethirdversionoftheFixteribundle-harvesterinearlyfuelwood thinnings.

2. Material and methods

2.1 TreatmentsAstandcontainingpatchesdominatedbybroad-

leaves and conifers of various characteristics was se-lected.Thestandareawasdividedintotimestudyplots,aimingtoisolatehomogeneousareasintermofdendrometricalfeatures(speciescomposition,sizeoftreestoberemoved,density,etc.).Eachtimestudyplotwas20mwide(thedistancereachableduringharvest-ingwitha11mcranefromastriproad)and40–60mlong.Intotal26timestudyplotsweremarkedoutforcuttingandbundlingwork,eachwithanaverageareaof 1215 m2 (SD 227), covering a total area of 3.2 ha.

2.2 Study siteThestudysitewaslocatedinHolmsund(N63°43’,

E20°25’),nearthecoastofnorthernSweden,ina30–35yearoldstandcontainingmostlyScotspine (Pinus sylvestrisL.),Norwayspruce(Picea abies(L.)Karst.)andbirch(Betulaspp.).Somegreyalder(Alnus incana (L.) Moench.) and lodgepole pine (Pinus contorta Douglas)werealsopresentinsomepatches.Theforesthadnotbeenpreviouslyprecommerciallythinnedandsomepartscontainedconsiderableamountsofundergrowth,mainlyconsistingofbirchesandNor-wayspruce(Table1).Thegroundgenerallyhadgoodbearing capacity, the surfacehadnoobstacles, theslopewasslightanditwasclassifiedas2.1.1accordingtoBerg´s(1992)terrainclassificationsystem.

2.2.1 Time study plot preparationPrior to thinning, strip road center lines were

markedoutineachtimestudyplot.Twopermanent100 m2transects(5mwideand20mlong)werelaidoutat25mspacingperpendiculartothestriproadineachtimestudyplotforinventoriesofdendrometricfeaturesbeforepre-clearingandthinningworkandafterthinningwork(Table1).Intotal397treesweresampled and their height and diameter at stumpheight(15cmabovegroundlevel)weremeasured.

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Croat. j. for. eng. 37(2016)1 39

Trees≤2.5cmindiameteratbreastheight(DBH) were onlycountedandregistered.Afterinventory,tenofthe26timestudyplotswere

pre-cleared,bycuttingundergrowthtreesof≤2.5cm(DBH) with a cleaning saw and leaving them on the ground before thinning.

2.3 Machine systemThemachine system studiedwas a harwarder

equippedwithafellingcraneandabundlingunitcapableofbuckingthecuttreesandbundlingtheminto2.6mlongcylinderswithca.60–70cmdiameters(Fig.1).Thebasemachinewasan8wheeledLogman811FCharwarder(LogmanOy)with125kWenginepower,15tmass,2.8mwidthand65cmgroundclear-ance.Itwasequippedwithan11mreachLogfitFT100crane(LogfitAB)integratedonarotatingcabinwithendlessturning.ThecranewasequippedwithaNi-

sula280E+(NisulaForestOy)accumulatingfellingheadwithamassof330kgandmaximumcuttingdiameter of 28 cm.

The bundling unit was a Fixteri FX15a machine (massca.6500kg,width240cm,length410cm,height280cm;www.fixteri.fi).Ithastwofeedrollers,acut-to-lengthguillotineandacompressionandbundlingcompartment. The bundling chamber has a fixedlengthof2.6m,threesetsofchainsusedforcompres-sionandaverticallyslidingframe.Ononesideofthecompressionchamber,tworollsofplasticnet(4000mlong)aremounted.Ontheoppositesideofthecham-ber, there are two mobile arms for integrating scaling anddropping-offofbundles.

2.3.1 Work sequenceWholetreesarecut,accumulatedandfedtothe

bundlingunitforprocessing(Fig.2).Oncethecom-partmentcontainssufficientmaterialforproducingabundle(ca.450–500kgoffreshmass),thebunchoftreesislifteduptoacompactionchamber,whereitiscompressedbyrevolvingchainsandtiedupusingaplasticnet.Atthesametime,thelowercompartmentcan be fed with other trees. Once the bundle reaches sufficientdensity,itisautomaticallyunloadedfromthecompactionchambertotwosidearms.Thebundleisautomaticallyscaledand informationontimeofproductionandmassisrecordedonthebasemachine.Thebundleisthendroppedonthegroundfromthearmsandanewbundlingcyclestarts.Thebundlingprocessisautomatedwithpossibilitiesfortheoperatortocontroltheprocess.Thefelling,feeding,droppingandweighingworkcanbeperformedsimultaneouslywiththebundlingprocess.

Table 1 Characteristics of the 26 time study plots before pre-clearing and thinning work. DBH=diameter at breast height, OD=oven-dry, SD=standard deviation

Trees >2.5 cm DBH Trees ≤2.5 cm DBH

DBH1

DBH

basa

l2

Basa

l ar

ea

Stem

vo

lume4

Dens

ity

Heig

ht

Stem

vo

lume4

Biom

ass

volum

e5

Biom

ass5

Pine

Spru

ce

Birc

h

Dens

ity6

Pine

Spru

ce

Birc

h

Post

de

nsity

7

Stats. cm cm m2/ha dm3 trees/ha m m3/ha m3/ha OD t/ha %3 %3 %3 trees/ha %3 %3 %3 trees/ha

Mean 7.1 8.0 26.3 26.5 5406 8.2 133.9 189.2 92.3 27.4 23.5 48.4 4523 6.1 33.9 60.0 1516

Min. 5.5 6.3 17.8 15.0 2765 7.0 91.0 124.0 54.0 1.0 0.0 5.0 134 0 0 0 0

Max. 8.5 9.9 36.4 43.0 9302 9.7 206.0 302.0 148.0 95.0 75.0 89.0 11,951 55.0 100 96.0 4289

Median. 7.0 8.0 25.6 24.5 5200 8.1 131.0 173.5 91.0 17.0 16.0 60.5 3648 2.0 25.5 69.0 1165

SD 0.9 1.0 5.3 8.1 1583 0.7 28.9 48.7 24.9 25.8 21.0 28.3 3509 12.1 28.9 29.1 1517

1 Arithmetic mean; 2 Weighted by basal area; 3 In number of trees; 4 Stem volume on bark; 5 Whole tree volume/mass (incl. tops and branches); 6 All plots before pre-clearing; 7 All plots after pre-clearing of ten plots

Fig. 1 The bundle-harvester system

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40 Croat. j. for. eng. 37(2016)1

2.3.2 OperatorTheoperatorhadoneyearofexperienceinearly

thinningoperations andhadbeenworking for sixmonths with the studied machine in thinnings before ourexperiment.Beforethetimestudies,theoperatorhadahalfdaytrainingsessionatthestudysite,andwassubjectivelyjudgedtobe»moreskilledthantheaverageoperator«.

2.3.3 Thinning work methodThethinningwascarriedoutselectivelyfrombe-

lowalongstriproadsystems,withbroadleavespri-oritizedforremovalandtargetingaresidualdensityofatleast1200–1500futurecroptrees/ha(DBH>6–7cm).Trees with DBH≤2.5cmwereonlycutandaccumu-lated if they obstructed the crane fromharvestinglarger trees.

2.4 Time studyThetimestudywasconductedbetweenthe5th and

14thofMay2014,andthetotaldurationofthemoni-toredworkwas29.40PM15H(productiveworktime

includingdelaytimelessthan15min).TheworktimeconsumptionwascontinuouslyrecordedwithanAl-legroFieldPC® runningSDI software (HaglöfAB)recording0.6second(1cmin)time-steps(Table2)(cf.Nuutinen2013).Delaytimewasseparatelyrecorded.Thehighestpriorityinthetimerecordingwasgiventothecranework,i.e.ifthecraneworkandbundlingwereperformedatthesametime,thecranewaspri-oritized.Duringharvesting,thenumberoffelledtreespercranecycle(DBH>2.5cm)wasalsorecorded(theDBHthresholdwasvisuallyestimated).Atthesametime,themachinecomputercreateda

dataset for each timestudyplot, including the time (hour:minute: second)when eachbundlewas ex-pelledfromthebundleranditsfreshmassasacquiredfrom the integrated scale.

2.5 Stand quality measuresAfterthetimestudy,theDBHandspeciesofall

trees, and numbers of undergrowth trees, were re-cordedagainintheinventorytransects.ThecutareaineachtimestudyplotwasaccuratelymeasuredusingaPersonalDigitalAssistantwithanexternalGPSan-tennaat1mprecision.Theheightofallstumpslo-cated less than 1 m from the center line of each transect (i.e.alongalineperpendiculartothestriproaddirec-tion)wasalsomeasured.ThestriproadwidthwasmeasuredaccordingtoBjörhedenandFröding(1986).Thedistancebetweenstriproads(definedasthesumofthedistancesoneithersideofthestriproadfromthe road center to the furthest cut tree, along a line perpendiculartothestriproad)wasalsomeasuredwithin the transects. The stem volumes of trees with DBH≤5cmand>5cmwerecalculatedusingfunctionspresentedbyAndersson(1954)andNäslund(1947),respectively.Theoven-dry(OD) biomass content of stems, branches and needles was calculated using functionspresentedbyMarklund(1987),andforcon-version to solid volumes, basic density values forcrownbiomassobtainedbyHakkila(1978)wereused.DamagewasrecordedwhentherewasvisibleharmtosapwoodoftreeswithDBH>2.5 cm, with no restriction onwoundsize(cf.Wallentin2007),registeringwheth-erthedamagedtreewasadjacenttoastriproadorlocated inside the stand.

2.5.1 Bundle massThe fresh mass of each bundle was acquired di-

rectlyfromthemachinedatabaseandconvertedtoovendry(OD)massusingthemoisturecontent(MC) ofmaterialsampledfromeachtimestudyplot(deter-minedasdescribedbelow).Thebundles’solidvol-umes(m3)werealsocalculatedfromtheirdrymasses(inODkg)usingaveragedensitiesof450,554and

Fig. 2 Flow chart of work processes for the studied bundle-harvest-er (cf. Nuutinen et al. 2011, Nuutinen and Björheden 2015). Fell A, B indicate that the work can include accumulation of several trees

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Croat. j. for. eng. 37(2016)1 41

536kg/m3calculatedforpine(10plots),spruce(3plots)and birch (13 plots). The calculated basic density(weightedbytreespecies)was505kg/m3.

2.5.2 Moisture contentImmediatelyafterharvesting,a10cmthickslice

(weighingatleast500g)wascutfromhalfwayalonga randomly selectedbundle fromeachof the timestudyplotsusingachainsaw.TheMCofthesamplewasdeterminedfollowingstandardmethodCEN/TS14774-2(2004),andtheaverageMC for units domi-natedbypine,spruceandbirchwasfoundtobe53.4(SD2.5),58.7(SD1.3)and52.6%(SD3.0),respectively.

2.5.3 Fuel consumption and energy efficiencyThroughouttheentirefieldtrialperiod,fromMay

5–16,thesystemconsumed1619litersofdieselfuelduring98.5PM15H(includingmovingbetweenhar-vesting units, etc.), of which data recorded during 29.40 PM15H were used in the time study. Thus,69.1hoursofadditionaltimealsoincludedunproduc-tiveworksuchasmovingbetweenharvestingunits,etc.Thisoperationalworkwasperformedinthestudysite under the same conditions, on average, as the av-eragestandconditionsduringthetimestudy(cf.Table1).Duringthetotalrunningtime(98.5PM15H),1444bun-dleswithatotalfreshmassof305,779kgwerepro-

duced.Theenergyefficiency(MJ/ODt)andenergyreturnoverenergyinvested(EROEI) were calculated usingthetotalfuelconsumption,totalOD mass har-vested, heating values of diesel fuel and the biomass of35.3MJ/l(cf.Athanassiadis2000)and19.2MJ/kgTS (Ringman1996),respectively,andaMCof53.4%(aver-agevalueobtainedforsamplescollectedfromthetimestudyplots).

2.5.4 Other measurementsThebiomasslossesduringthebundlingprocess

weremeasuredinaseparatetest,asfollows.Thebun-dling chamber was emptied and then fed withweighed, cut tree sections until it contained enough to produceafullbundle.Thebundlewasthenweighed,andbiomasslosseswerecalculatedbysimplysub-tracting its mass from the mass of material used to createit.Intotal13bundleswereproducedusingrep-resentativesamplesoftreeswithclosetoaveragechar-acteristics for theirrespectivestands (Table1).Theaveragemassofthese13bundleswas493kg(SD 115).

2.6 Analysis and statisticsThe remaining stands properties and the time

consumed(s/tree),whenharvestingpreclearedandnotpreclearedtimestudyplots,werecomparedbyanalysisofvariance(ANOVA).Correlationanalysis

Table 2 Definitions of recorded work elements

Work element (Abbreviation) Description Priority*

Boom out (Crut)Starts when an empty crane moves towards the first tree to be harvested and stops when the tree has been reached

1

Felling (Fell)Starts when the first tree has been reached and stops when the last tree in a crane cycle has been felled (moving to successive trees is included)

1

Boom in (Crin)Starts when the last tree in the crane cycle has been felled and stops when the felling head drops the bunch of trees on the bundler feeding plate/on the ground

1

Arrangement of felled trees on the ground (Artr)

Starts when the felling head drops the bunch of trees on the ground and ends when the cross-cut tree parts are dropped on the ground/on the bundler feeding plate

1

Arrangement of bundles on the ground (Arbu)

Starts when the crane grabs a bundle and ends when the bundle is dropped on the ground 1

Moving (Move) Starts when the base machine wheels start turning and ends when the base machine stops 2

Bundling (Bundle)Starts when the crane/base machine wheels are idling and the bundling unit is feeding/compressing trees and ends when the crane/machine starts to move for felling or a bundle is dropped on the scale

3

Scaling and dropping (Drop)Starts when the crane/base machine wheels are idling and a bundle is dropped on the scale and ends when the bundle is dropped on the ground or the crane/base machine starts moving

3

Miscellaneous (Other) Other activities e.g. trees are dropped and then picked up again 4

Delays Time not related to effective work time, e.g. personal breaks, repairing 4

*The lower the number, the higher the priority

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42 Croat. j. for. eng. 37(2016)1

wasappliedtoevaluatecorrelationsbetweeninde-pendentvariablesusingPearson´scorrelationtest.Analysisofcovariance(ANCOVA)wasusedforana-lyzingthecombinedeffectsoftreatmentsandinde-pendentvariablesontheproductivity(OD t or bun-dles/PM0H).Regressionanalysiswasusedfortestingpossiblesignificantpredictorsofthebundlesmass(ODkg/bundle).95%confidenceintervals(CI) were calculated for thebiomass losses (freshkg)of thebundles.Ap-levelof≤0.05wasusedasathresholdforstatisticalsignificance.

3. Results

3.1 Harvest and thinning qualityTherewerenosignificantdifferencesinproperties

betweentimestudyplotsthatwerepreclearedandnotpreclearedpriortothinning,ineitherharvested(e.g.treevolume,treeheightanddensity)orremainingstands(e.g.basalarea,standdensity,stemvolume,height,damageandstriproadspacing).Theaveragetree and average stem volumes cut were 23.3 dm3(SD 7.7, range9–28dm3) and 16.2 dm3(SD5.0,range12–43dm3), respectively.Theaveragetreeheightandnumbersofremovedstemsforalltimestudyplotswere7.4m(SD 0.7) and3554trees/ha(SD1184),respectively.

The remaining stands had, on average, 1852 trees/ha (SD455,intherangeof1014–2651/ha),ofwhich39,20and41%werepine,spruceandbirch,respectively.Thenumberofbirchtreesperhawashighlycorrelatedtothenumbersofbothpinetrees(p=0.04)andspruce(p=0.01)perha,buttherewasnocorrelationbetweennumbersofpineandsprucetreesperha.Onaverage,5.5%(SD 4.2) of the remaining trees were damaged and5.7%(SD7.9)ofthestrip-roadtrees.Thestrip-roadwidth,thedistancebetweenstrip-roadsandthestumpheightwere,onaverage,4.5m(SD0.3),19.8m(SD1.3)and18.3cm(SD4.5),respectively.Thebundleshadameanfreshweightof439kg

(SD24.1,intherangeof391–493kg),andmeandrymass of 203.4 OD kg (SD 17.3).A correlation testshowed that the ODmassofthebundleswasposi-tively correlated to the proportion of birch trees(R=0.394;p=0.046)andnegativelycorrelatedtothepro-portionofsprucetrees(R=–0.409;p=0.038) used to cre-ate them. There were negative correlations between bothproportionsofbundledbirchandsprucetrees(R=–0.610;p=0.001)andproportionsofbirchandpinetrees(R=–0.548;p=0.004).Therefore,thefollowingpre-diction model, with ODt/bundleasadependentvari-ableandproportionofbirchtreesinthebundleasanindependentvariable,wasconstructed:

( ) ( )( )2tBundlemass 190.27 0.249 shareofbirch,%No.oftreescut adj. 0.12, 0.046)bundle

OD R p = + × = =

( ) ( )( )2tBundlemass 190.27 0.249 shareofbirch,%No.oftreescut adj. 0.12, 0.046)bundle

OD R p = + × = = ( ) ( )( )2tBundlemass 190.27 0.249 shareofbirch,%No.oftreescut adj. 0.12, 0.046)

bundleOD R p = + × = =

(1)

3.2 Time consumptionTheproductivemachinehourswithoutdelaysdur-

ingthetimestudyamountedto26.76PM0H,andde-laysaccountedfor9.1%ofthemonitoredtime.Preclearance(andthusthedensityofundergrowthtreesduringthinning)hadnosignificanteffectonthehar-vestingandbundlingworktimeconsumption(Table3).Thefellingcranewasidling7.4%ofthePM0 time, mainlyduetoproblemswithfeedinglargetreesanddroppingbundles.Onaverage,4.1trees/cranecyclewereharvested(SD1.0)andtherewerenodifferencesbetweentreatmentsinthisrespect(p=0.926).Onaver-age,eachcranecycletook44.6sec(SD 4.2), and 5.5 cranecycles(SD0.7)wererequiredtoproduceabun-dle.Hence,onaverage,4.1minofworktimewasre-quiredperproducedbundle(SD 0.7).

3.2.1 Bundler workThe number of cranecyclesrequiredperbundle

washighlycorrelatedtotheaverageharvestedtreesize(R=–0.775;p<0.001).Thetimerequiredtoproduceabundlewasfarfromsignificantlycorrelatedtothe

Table 3 Distribution of effective work time (s/tree) in work ele-ments (mean values for precleared and not precleared time study plots). SD=standard deviation. p-values are given for the treatment effect (preclearing vs. no preclearing)

Stats

Work element Mean, s/tree SD % p-value

Move 0.8 0.2 7.4 0.661

Fell 5.8 0.5 51.6 0.229

Crut 1.5 0.4 13.2 0.902

Crin 2.1 0.6 18.6 0.792

Artr 0.1 0.1 1.1 0.901

Arbu <0.1 0.1 0.2 0.240

Bundle 0.5 0.3 4.5 0.848

Drop 0.3 0.1 2.9 0.660

Other 0.1 0.1 0.4 0.658

Total 11.2 2.0 100 0.864

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fresh weight of the produced bundles (R=0.215; p=0.291),butclosetosignificantlycorrelatedtothenumberofcranecyclesrequiredperbundle(R=0.367; p=0.065)andstronglycorrelatedtothetimeconsump-tionofthecuttingworkperbundle(R=0.787, p=<0.001) (Fig.3).Thus,thetimeconsumptionperbundlewasmodeledasafunctionofthetimeconsumptionpercranecycle(Fig.3):

( ) ( )2Time timemin 1.95 0.136 cycle,s , adj. 0.60%, 0.001bundle crane

R p = − + = =<

( ) ( )2Time timemin 1.95 0.136 cycle,s , adj. 0.60%, 0.001bundle crane

R p = − + = =< (2)

3.3 ProductivityTheproductivityreached,onaverage,3.1ODt/PM0H

(SD0.6)(6.6fresht/PM0H,SD1.2)(Table4andFig.4).The independent variable harvested stem volume(dm3)providedthehighestpredictivepower,R2(adj) value, and hence was used as a single covariate in the ANCOVAanalysis.Allcombinationsofotherinde-

Fig. 3 Time consumption (PM0) of the bundle-harvester to produce a bundle as a function of time consumption per crane cycle work. Calculations are based on average values for 26 time study plots

Table 4 ANCOVA table and linear regression model of the bundle-harvester productivity (OD t/PM0H)

Source DF Seq. SS Adj. SS Adj. MS F p R2 R2, adj.

Stem volume, dm3 1 6.625 6.813 6.813 – <0.001 – –

Treatment 1 0.197 0.197 0.197 54.36 0.222 – –

Error 23 2.882 2.883 0.125 1.58 – – –

Total 25 9.705 – – – – 0.700 0.68

Regression terms Coeff. SE coeff. T – – – – –

Constant 1.3865 0.2410 5.75 – – <0.001 – –

Stem volume, dm3 0.10556 0.01432 7.37 – – <0.001 – –

Table 5 ANCOVA table and linear regression model of the bundle-harvester productivity (bundles/PM0H)

Source DF Seq. SS Adj. SS Adj. MS F p R2 R2, adj.

Stem volume, dm3 1 138.598 142.074 142.074 78.55 <0.001 – –

Treatment 1 3.560 3.560 3.560 1.97 0.174 – –

Error 23 41.602 41.602 1.804 – – – –

Total 25 183.760 – – – – 0.77 0.75

Regression term Coeff. SE Coeff T – – – – –

Constant 7.3805 0.9154 8.06 – – <0.001 – –

Stem volume, dm3 0.48205 0.05439 8.86 – – <0.001 – –

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pendentvariablesgavelessgoodpredictionsand/orwerebiasedbymulticollinearity(Tables4and5).Onaverage,15.1bundles/PM0Hwereproduced

(SD2.7,intherangeof10.8–20.3;Fig.4).Thestemvol-umeprovidedslightlybetterproductivitypredictions,R2(adj.) valuesof0.75vs.0.68,intermsofbundles/PM0Hthan in terms of ODmass(cf.Tables4and5).

3.3.1 Energy efficiency and biomass lossesDuringthetotalfieldtrialperiod(98.5PM15H),the

systemconsumed15.87MWhofdieselfuelandpro-duced1392MWhofbiofuel,correspondingtoanaver-ageenergyefficiencyof401MJ/ODt (PM15time)(441MJ/ODtinPM0time)andanEROEIof80.6(inPM15time)(88.7inPM0 time). On average, a bundle hadafreshweightof454kg,correspondingto0.96MWh,andfuelconsumptionaveraged15.1l/PM0H(16.4 l per hour ofmachinework timeduring thewholetrialperiod(approximatestoPM15 time)).Thetreesectionslost,onaverage,37kg(SD29)

massduringthebundlingprocess,asmeasuredintheseparatetest,7.1%oftheirmeanmass(±3.0%;intherangeof4.1–10.1%).Byvisualinspection,thismassconsistedmainlyoffinebranchesandneedles.

4. DiscussionUnexpectedly, thedensityofundergrowthtrees

didnotsignificantlyaffecttheefficiencyofthecuttingwork,asfoundinpreviousstudies(e.g.Kärhä2006,Jonsson2015).Apossiblecontributoryfactorexplain-ingtheresultsinthepresentstudyisrelatedtothe

nature of the undergrowth, as the studywas per-formedinthebeginningofMay,whenbroadleaveshavejuststartedtosproutandthusmighthaveonlyslightlyreducedvisibility.Accordingly,Jonsson(2015)foundthatdefoliatedundergrowthreducesvisibilitymuchlessthanfullyleafedtrees.Furthermore,theop-erator used techniqueswith efficient cranemove-ments,similartothoseappliedinboom-corridorthin-ningasdescribedinBergströmetal. (2007),whichcouldhaveminimizedtheeffectsofundergrowth.Theundergrowthdidnotaffectthequalityofthethinningworkeither,whichisconsistentwiththehypothesisthattheundergrowthdidnotsignificantlyimpairvis-ibilityoftheoperator.However,fewoftheharvestedunits inourstudyhaddensespruceundergrowth,whichmaybesignificantassprucehasgreaterbranch-inessthanpineandbirch(cf.Kärhä2006),andthusmayhavestrongereffects.Inconventionalpulpwoodandenergywoodthinning,onlytree-sizesaboveca7–9cmDBH are extracted as commercial assortments, meaningthatundergrowthtreesaredefinedastreesbelowca.7–9cmDBH.Inthatsense,comparingthecuttingefficiencyinpreclearedstandsnotpreclearedstandswouldlikelygivehighereffectsthanfoundinthisstudy.Thus,itislikelythattheeffectsofunder-growth clearanceup to ca. 8 cmDBH would have given significantdifferences inworkefficiencybe-tween the treatments. However, such comparisonwould be irrelevant since we studied whole tree bio-massthinning,whichhereisdefinedasutilizationofalltrees,includingtheirtopsandbranches,above2.5cmDBH.Theproductivityrecordedinthepresentstudy

Fig. 4 Productivity (to left, OD t/PM0H and to right, bundles/PM0H) of the bundle-harvester system as a function of average size of harvested tree

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was 23% and 9% lower than values recorded byNuutinenandBjörheden(2015),forharvestingtreesof 27 dm3 and 44 dm3,respectively,whenthesamebundle-harvestersystemwasusedforthinningpinedominatedstandsduringwinter(Fig.4).However,thecitedauthorsonlyusedfreshmassesintheirproduc-tion estimates, without measuring the MC, and for conversiontosolidvolumes,theyusedadensityof855kg/m3solid, thus forcomparisontovaluespre-sented here, a MC of 53.4% was assumed for their bio-mass.Furthermore,theuncertainties(deviationsofaverage values) of the data are not stated in the cited study,therefore,nodefinitiveconclusionsregardingsimilarities or differences in productivity can bedrawn,butasindicatedbythetrendsshowninFig.5,the results seem to be consistent.TheresultspresentedhereandbyNuutinenand

Björheden(2015)showthatthecuttingefficiencyisthelimitingfactorforthesystem.Thebundle-harvestersystemmonitoredinbothstudieswasequippedwithaNisula280E+accumulatingfellingheadthatcutstreeswithsheares/knives.Thistypeofheadisrobustandrequireslesshydraulicpressurethanheadswithsaws,butthecuttingefficiencyisgenerallylimitedbytheneedtokeeptheheadstillwhilecuttingatree,regardlessofthetreesizecut.However,theBrackeC16cansweepshortdistances(ca1–2m)duringcut-ting(www.brackeforest.com),andthuscuttreesdur-ingacontinuousmovement.Thistechniquecanpro-vide improvements in productivity that arenegativelyrelatedtothesizeofcuttreesandpositive-lyrelatedtothedegreeofcontinuouscranemovementused,asshownbye.g.Bergströmetal.(2007),Berg-ström(2009)andSängstuvalletal.(2012).BergströmandDiFulvio(2014a)modeledoperationsofanopti-mizedbundle-harvesterbasedontheBrackeC16ac-cumulating felling and bunching head, with no idle timebetweenthecraneandbundlingwork,andob-tainedsimulatedproductivities(assumingthesameconversion rate as used above) of 15 and 21 m3/PM0Hfor harvesting trees of 27 dm3 and 44 dm3,respective-ly.Thesevaluesareinaverage55%and76%higher,fortreesofcorrespondingsizes,thanthoserecordedinthepresentstudyandbyNuutinenandBjörheden(2015).Themodelingindicatesthatthereissignificantpotential to increaseproductivity ifefficientfellingand bunching technologies are integrated with bun-dlingsystems.BergströmandDiFulvio(2014a)alsoconsidered

newcuttingtechnologiesespeciallydesignedforcon-tinuouscuttingandaccumulationinboom-corridorscombinedwithoptimizedbundlingsystems(i.e.withno idle time between cutting and bundling). Such

bundle-harvestersystemscouldsignificantlyreducecostsinstandswheretheaveragesizeofcuttreesis<30 dm3.Theyalsoshowthataconventionalbundle-harvestersystem,suchastheFixterisystemequippedwith(forinstance)aBrackeC16head,islesscostlywhencuttingtreesfromca.30toca70dm3.

It should be noted that biomass losses during the bundlingprocessleadtoproportionallossesinpro-ductivity,andareprobablycorrelatedtothesizesofcuttrees,andratiosofconiferstobroadleaves.How-ever,inastudyofatest-benchforcompression-pro-cessingofbunchedsmall-diameterconifertrees,Berg-ström et al. (2010) found that processing freshbunches resulted in mass losses of about 10% to 15% (fortreesof5–8and12–15cmDBH,respectively),with35–50%reductionsinashcontentsand80–160%in-creasesinbulkandnetenergydensity.Inthepresentstudymasslossesof4–10%wererecorded,consistingmainlyofnutrient-richfractions(accordingtovisualobservations), indicating that the ash content in stands, wheremostlyconifersarecut,couldbedecreasedbyuptoca35%.Whether the losses due to bundling should be

minimizedorsetatcertainlevelsisaquestionofpri-oritizingproductivityornutrientremovalandfuelquality.Thisquestionishighlyrelevantwhenconsid-ering stands that are sensitive to nutrient removal as the studied bundle-harvester cut and bundle the whole tree above ground. For instance, in Finland the whole-treeharvestingguidelinesforearlythinningsreportthatca.30%ofthebiomasscutafterwhole-treeharvestingshouldbeleftatthefellingsite(cf.Kärhä2015a),e.g.bypreclearingtreesbelow7–9cmDBH andbydelimbingthetreescutbyharvester.Instudiesof theBrackeMAMAprototypeheaddesignedforcompression-processing, Bergström andDi Fulvio(2014b)foundthatbiomasslossesduringprocessingreducedharvestingyieldsby10–23%.Thus,bundlingusingtheFixteriFX15systemseemstoresultinrela-tivelylowbiomasslossesandtobeless»aggressive«than the feed-roller-based compression-processingtechniques studied byBergström et al. (2010) andBergströmandDiFulvio(2014b).However,themag-nitudeoflossesduetocompression/bundlingshouldbecontrolled,regardlessofthetechnologyandsystemused,tooptimizethebalancebetweenproductivityand losses in accordance with stand conditions and economic goals. The additional tests of biomass losses duringprocessingofbundlesdidnotcoverallpossibletypesoftreemixturesthatcanoccurinthinnings,buttheresultsindicatepossiblelossesforpine-dominatedstands.Lossesarelikelytobesimilarforspruce-dom-inated stands and lower for birch-dominated stands,

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but differences in losses between seasons are alsolikely,because(forinstance)branchesaremorebrittlewhenfrozen.Thestudyprovidespredictivemodels forearly

thinnings from below in dense stands, in which trees with9–28dm3stemvolumesarecut,andproductiondata in both fresh and ODmassespereffectivehourofwork,derivedusingmoisturecontentsofrepresen-tativesamples.Theproductivitypredictionmodelsarehighlysignificantandprovidehighprecisionesti-mates.Theoverallproductivityforthewholetrialtimeisverysimilartovaluesobtainedfromthetimestudy,corroborating the robustness of the models obtained fromthetimestudyplots.However,usersshouldbeawareofthelimitednumbersofoperatorsandstandtypesthatthemodelsarebasedupon.Theoperation-al fuelconsumptionduringthefieldtrialperiodisconsistent with earlier measurements under some-whatdifferentconditions(Jylhä2011),indicatingthatthesystemconsumesca.16ldiesel/PM15H.However,effectsonfuelconsumptionofvariationsinsizesofcuttrees(andhenceproductivity)werenotmeasureddueto limitations in resources.Theconditionsatthestudysitearerepresentativeof

largetractsofforestinSweden,especiallyinnorthernparts(cf.Fernandez-Lacruzetal.2015).Tocoverforestsmorerepresentativeofsouthernparts,spruce-dominat-edstandswithhighproportionsofsuppressedbirchtreesandspruceundergrowthshouldbeincludedin

furtherstudies.Thestudywasconductedinforestsiteswithgoodbearingcapacity,lowroughnessandlimitedslopes.Duetothesystem’shighmass,itcouldpoten-tiallybelimitedbydifficultsoilconditions,thusfurtherstudiesarealsoneededtoassesseffectsofsoilproper-tiesonitsoperationalefficiency.Themachine’scenterofgravitywasnotmeasured,butitislikelytobehigh-er than for a standard harvester, due to the addition of the bundling unit. This might also somewhat restrict themachine’soperationalmaneuverabilityonslopes,and warrants investigation.Theoperator’seffectwaskeptconstantduringthe

trials,althoughthetimestudycoveredallweekdaysanddaylighthours.Inordertoobtainmorecompre-hensiveresults,reflectingvariationsinoperatorskills,usingseveraldriverswouldbeadvantageous,asop-eratorsstronglyaffecttheperformanceofharvestersinthinning(cf.Väätäinenetal.2005,Lindroos2010).How-Väätäinenetal.2005,Lindroos2010).How-Lindroos2010).How-ever,themainaimsofthestudyweretostudytheef-fectsofundergrowthdensityonproductivity,aswellasproductivitylevelsper se.Thus,thestudydesignin-cludedcompromisesintendedtomeetthesetwinaims,andkeepingtheoperatorconstantreducesbothcostsandmanagementcomplexities.Duringthewholetrialperiod,betweenthetimestudiesanotheroperatoralsodrovethemachine.Themeanproductivityduringthisperiodwas14.7bundles/PM15Hor 3.1OD t/PM15H

Fig. 5 Productivity as a function of harvested whole tree size (stem+branch volume) recorded in the present study and accord-ing to findings by Nuutinen and Björheden (2015)

Fig. 6 Time consumption to produce a bundle as a function of the bundles mass. The dotted line indicates the maximum capacity of 1.2 min/bundle, reached for bundles with masses between 400 and 500 kg in the study. Values of time consumption lower than ca. 7 min are considered as PM0 time, i.e. work with no delays

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(verysimilartoPM0Hvaluessincedelayswereminor),inlinewiththetimestudy,whichindicatesthatdiffer-encesinproductivitylevelsbetweenoperatorswereminor.However,thecuttingworkwiththeheadusedhereisrelativelyslowandstraightforward.Thus,ifafellingandbunchingheadaffordinghighercuttingef-ficiency(andhencemorecomplexmovements)wasused,therewouldprobablybegreaterdifferencesintheefficiencybetweenoperators.Insuchcasescranema-noeuvrabilitycanbesupportedtoahigherextentbysharedcontrol/semi-automation(cf.Jundénetal.2012).Theaveragemassofbundlesproducedinthetime

studywas439kg,andtheirmasseswerecorrelatedtotheproportionsofbirchtreesintheinitialstands,asbirchwoodisgenerallydenserthanpineandsprucewood.ThedottedlineinFig.6indicatestheminimumbundling time thatwasapproximately reached forbundleswithafreshweightbetween400to500kg,showingthatthemaximumcapacityofthesystemwasca.1.2minperbundle.Thiswouldcorrespondtoacranecycletimeof23.2sec,accordingtothefunction inFig.3,andprovideproductivityof20fresht/PM0H.AssumingthatthefactorforconversiontoPM15His1.3,theproductivitywouldbeca.100%higherwhenharvesting trees with an average volume of 23 dm3 thanreportedbyBergströmandDiFulvio(2014a).Duringthetimestudies,itwasnotedthatsomeextra

»planningtime«occurredduringunloading/droppingofbundles,astheoperatorhadtocheckthattherewasenoughspaceintheplaceallocatedforunloadinginorder to avoid damaging the remaining trees and en-surethatbundleswerelocatedoff-road,whichishigh-lyimportantforefficientforwardingwork.Forexam-ple,sometimesdroppedbundlesfellintothestriproadarea and had to be relocated before forwarding, since theallocatedforwardercraneworkareaisintheop-positedirectiontothedrivingdirection.

5. ConclusionsTheefficiencyofthestudiedbundle-harvesterwas

notaffectedbythedensityofundergrowthtrees,buthighlycorrelatedwiththesizeofharvestedtrees.Thestudyprovidesinformationaboutthesystem’sperfor-mancethatcomplementsearlierfindings,especiallywhenhandlingrelativelysmalltrees,andtherecordedproductivityisconsistentwithpreviousreports.Thesystem’s timeconsumptionperbundlewasnotaf-fectedbyeithertreesizeorthemixtureoftreespeciesharvested,butthemassofthebundleswaspositivelycorrelatedwiththeproportionofbirchtreescut.Thebundlingunitmaximumefficiencywasnotreachedduring the trial, but estimates indicate that it could be

significantly(perhapsupto100%)higher.However,toreachsuchefficiency,thesystemwouldhavetobeequippedwithafellingandbunchingheadthatcancut trees during continuous boom movements. In the nearfutureitshouldbeequippedwithaheadwithhighercuttingefficiency,e.g.theBrackeC16head,anditsproductivity,manoeuvrabilityandqualityofbun-dles should be further investigated in various forest conditions.

AcknowledgementsThe research leading to these results has received

fundingfromtheEuropeanUnionSeventhFrame-workProgramme(FP7/2012-2015)[grantagreementno.311881]andtheSKMprojectwasfunded,inter alia, bytheSwedishEnergyAgency.

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Received:May29,2015Accepted:November30,2015

Authors’address:

Researcher,Assoc.prof.DanBergström,D.Tech.*e-mail:dan.bergstrom@slu.seDepartmentofForestBiomaterialsandTechnologySwedishUniversityofAgriculturalSciencesSE-90183UmeåSWEDEN

Researcher,FulvioDiFulvio,PhD.e-mail:fulvio.di.fulvio@slu.se;difulvi@iiasa.ac.atDepartmentofForestBiomaterialsandTechnologySwedishUniversityofAgriculturalSciencesSE-90183UmeåSWEDEN

andInternationalInstituteforAppliedSystemsAnalysisEcosystemsServicesforAppliedSystemsAnalysisA-2361,LaxemburgAUSTRIA

Researcher,YrjöNuutinen,PhD.e-mail:yrjo.nuutinen@luke.fiNaturalResourcesInstituteFinlandFI-80101JoensuuFINLAND

*Correspondingauthor