Georeferenced database of tree volume and biomass allometric ...

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Georeferenced database of tree volume and biomass allometric equations for North America UN-REDD PROGRAMME July, 2013 Rome, Italy

UN-REDD Programme MRV Report 12 2013

TheUNREDDProgramme,implementedbyFAO, UNDPandUNEP,hastwocomponents:(i)assistingdevelopingcountriesprepareand implement national REDD strategies and mechanisms; (ii) supporting the development of normative solutions and standardized approachesbasedonsoundscienceforaREDDinstrumentlinkedwiththeUNFCCC.Theprogrammehelpsempowercountriestomanage theirREDDprocessesandwillfacilitateaccesstofinancialandtechnicalassistancetailoredtothespecificneedsofthecountries. The application of UNDP, UNEP and FAO rightsbased and participatory approaches will also help ensure the rights of indigenous and forestdwellingpeopleareprotectedandtheactiveinvolvementoflocalcommunitiesandrelevantstakeholdersandinstitutionsinthe designandimplementationofREDDplans. The programme is implemented through the UN Joint Programmes modalities, enabling rapid initiation of programme implementation andchannelingoffundsforREDDefforts,buildingontheincountrypresenceofUNagenciesasacrucialsupportstructureforcountries. The UNREDD Programme encourage coordinated and collaborative UN support to countries, thus maximizing efficiencies and effectivenessoftheorganizations’collectiveinput,consistentwiththe“OneUN”approachadvocatedbyUNmembers.

Contacts: MatieuHenry UNREDDProgramme Food&AgricultureOrganizationoftheUnitedNations(FAO) Email:[email protected] Recommendedcitation Birigazzi,L.,Fernandez,J.,BaldassoM.,Trotta,C.,SaintAndré,L.,Sola,G.,Henry,M.(2013)Georeferenceddatabaseoftreevolumeand biomassallometricequationsforNorthAmerica,UNREDDProgramme,Rome,Italy. Disclaimer The designations employed and the presentation of material in this information product do not imply the expression of any opinion whatsoeveronthepartoftheFoodandAgricultureOrganizationoftheUnitedNations(FAO)concerningthelegalordevelopmentstatus ofanycountry,territory,city orareaor ofitsauthorities,orconcerningthedelimitationofitsfrontiersorboundaries.The mentionof specific companies or products of manufacturers, whether or not these have been patented, does not imply that these have been endorsed or recommended by FAO in preference to others of a similar nature that are not mentioned. The views expressed in this informationproductarethoseoftheauthor(s)anddonotnecessarilyreflecttheviewsorpoliciesofFAO. FAO encourages the use, reproduction and dissemination of material in this information product. Except where otherwise indicated, material may be copied, downloaded and printed for private study, research and teaching purposes, or for use in noncommercial products or services, provided that appropriate acknowledgement of FAO as the source and copyright holder is given and that FAO’s endorsementofusers’views,productsorservicesisnotimpliedinanyway. Theconclusionsgiveninthisinformationproductareconsideredappropriateatthetimeofitspreparation.Theymaybemodifiedinthe lightoffurtherknowledgegainedatsubsequentstagesoftheproject.

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Contents 1.

Introduction..................................................................................................................................................6

2.

Objectivesofthereport................................................................................................................................7

3.

TheCompilationofthedata.........................................................................................................................7 3.1.Reviewofavailableallometricequations.....................................................................................................7 3.2.Dataclassificationandgeoreferencing........................................................................................................8 3.3.Tutorialfordatainsertion..........................................................................................................................9

4.

DatabaseDescriptionandStructure...........................................................................................................10

5.

TreeallometricequationsinNorthAmerica...............................................................................................11 5.1Historicaltrend.......................................................................................................................................................11 5.2GeographicalDistributionoftheEquations...........................................................................................................12 5.3TreeSpeciestowhichequationsRefer...................................................................................................................13 5.4TreeCompartmentsconsideredbytheequations..................................................................................................16

6.

Studycase:assessingstembiomassofPiceaGlauca..................................................................................18

7.

Studycase:NationalbiomassandcarbonestimationinMexicousingbiomassallometricequations......19

8.

GapsinassessingvolumeandbiomassinNorthAmerica..........................................................................31

9.

Recommendations......................................................................................................................................32

10.

References..................................................................................................................................................33

11.

Appendices..................................................................................................................................................37

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ListofFigures Figure1.Treecomponentsclassificationusedinthepresentwork(Henry,etal.,2011).......................................8 Figure2.Numberofpublishedarticlesperyear...................................................................................................11 Figure3.Numberofequationspercountry..........................................................................................................12 Figure4.Numberofequationsperecologicalzoneclassification.FAOecologicalzoneclassification................12 Figure 5. Geographical distribution of the sample plots in North America. The red dots represent the sites whereequationsweredeveloped...........................................................................................................13 Figure6.Numberofequationsperfamily............................................................................................................14 Figure7.Numberofequationspergenus.............................................................................................................14 Figure8.Numberofequationspermainspecies..................................................................................................15 Figure9.Numberofstudiedspeciespercountry.................................................................................................15 Figure10.Numberofstudiedplantfamiliespercountry.....................................................................................16 Figure11.Numberofequationspertreecomponents.........................................................................................17 Figure12.PlotoffourequationspredictingstembiomassforPiceaglaucafortemperatecontinentalforest...18 Figure 13.Graphical representation of the procedure to conduct the Monte Carlo uncertainty estimation for totalAGBcarbonatthenational–level...................................................................................................22 Figure14.Graphicalrepresentationoftheuncertaintyrangeforcarbonstockchangexforagivenstratum.....23 Figure15.Decisiontree1.SpeciesspecificallometricequationsareprioritizedwithinDBHapplicabilityranges forthemodels..........................................................................................................................................25 Figure 16. Decision tree 2. Species, genus and foresttype models are selected, in that order, within DBH applicabilityrangesdefinedinthemodels..............................................................................................26 Figure17.Decisiontree3......................................................................................................................................27 Figure18.Applicationofbiomassallometricequationforthethreedecisiontreesemployed...........................29

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ListofTables Table 1. Area by forest stratum for INEGI (2007) and grouped by de Jong et al. (2009) for the 19902006 NationalGHGInventory...........................................................................................................................19 Table2.CharacteristicsofthedecisiontreesemployedfortheestimationofbiomasscarboninMexico..........24 Table 3. National biomass carbon estimation using different decision trees for selecting biomass allometric models......................................................................................................................................................29 Table4.Percentage(%)ofavailablemetadataassociatedtobiomassallometricmodelsinMexico(n=339).....30

ListofAppendices Appendix1.ListoftheAcronymusedinthedatabase.........................................................................................37 Appendix2.Listofdataneededtoinsertanewallometricequationintothedatabase.....................................38 Appendix3.AdditionalallometricequationstoDeJongetal.’s(2009a)originalcompilation............................47 Appendix4.Referencesusedtocompiletheallometricequationdatabase.......................................................5

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1. Introduction Since2000theinterestinforestbiomasshasbeengrowing(ZianisandMencuccini,2004,Henry,et al.,2011,Parresol,1999).Estimationofabovegroundtreebiomassismainlyconductedtosupport sustainablemanagementofforestresources.Whiletreevolumeequationsweremainlydeveloped for timber management (Lanly and Lepitre,1970) and biomass equations forfuel wood production (Millington, et al., 1994) the climate change crisis highlights the need to better assess the contributionofterrestrialecosystemstotheglobalcarboncycle. Better understanding tree growth is crucial to accurately quantify ecosystems’ contribution to the global carbon cycle and to elaborate effective climate change strategies for mitigation and adaptation (Bombelli, et al.,2009). Vegetation biomass, in particular, is an important ecological variable for understanding the evolution and potential future changes of the climate system. Vegetation is storing a large amount of carbon (550±100 Pg) on the order of the amount in the atmosphere(800Pg)(Houghton,2007).Changesintheamountofvegetationbiomassalreadyaffect theglobalatmospherebybeinganetsourceofcarbon,andhavingthepotentialeithertosequester carboninthefutureortobecomeanevenlargersource(GTOS,2008,IPCC,2007). ReducingEmissionsfromDeforestationandforestDegradation(REDD)mayplayanimportantrole for climate change mitigation and, moreover, an accurate estimate of emission factors is also fundamental to develop and verify environmental policies and strategies. The Conference of the Parties held in Copenhagen in 2009, under the UN framework convention on climate change (UNFCCC), requests developing country Parties to establish robust and transparent monitoring systemsforforestandcarbonstock(UNFCCC,2009). Severalmethodshavebeenusedandtestedtoestimatetreebiomassandcarbonstocks(Valentini,et al.,2000,Luyssaert,etal.,2007,Asner,etal.,2012,Kindermann,etal.,2008).Themostcommonmethod toassessforestbiomassisbasedontheapplicationoftreeallometricequationstotheforestinventory data.Treeallometricequationsrelatedifficulttomeasuretreeparameters(suchasvolumeorbiomass) toeasytomeasuredendrometricvariables(suchasdiameteratbreastheightortreeheight)(Picard,et al.,2012).Differentmethodsexistfordevelopingtreeallometricequationsdependingontheobjective (commercialvolume,bioenergy,biomassorcarbon),foresttype(monospecificorplurispecificforest), treesize,accessibilityofthetree,forestrylaw,technical,financialandhumancapacities.Inconsequence, the quality of the estimates varies between allometric equations and depends on the method for destructive and semidestructive measurements, individual tree assessment, and adjustment method and model selection. The inappropriate use of tree allometric equations can also introduce significant biasanderrors.Thereforeitisimportanttocollectnotonlythemereformulasbutalso,ifavailable,all therelatedstatistical,geographical,ecologicalparametersoftheequation.Unfortunately,treeallometric equationsareoftennoteasilyavailableand,especiallyindevelopingcountries,quiterare. Inordertoidentifythegapsandtomakeavailabletheequationsdevelopedsofar,comprehensive collectionsoftreebiomassregressionsforNorthAmericanspecieswerecompiledinthelastyears.A diameterbased database of allometric equations for USA and Canada was developed in 2003 (Jenkins,etal.,2003),whileacollectionofequationsforMexicowaspublishedin2009(deJong,et al.,2009a)andthenupdated(Rojasetal.2009)andpublishedonlinein2012(CONAFOR,2012). As an identical forest classification was developed using the land cover classification system (Di GregorioandJansen,2005)forthethreecountries,itappearsthatamorelargescaledatabase,such asthepresentwork,willfacilitatedataexchangeandassessmentofforestcarbonstocksatregional scale. Furthermore, geo referencing the data allows unambiguously identifying the equation ecological zones, improving estimates of the equations geographic distribution and identifying the potentialgaps.

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2. Objectivesofthereport Theobjectivesofthisreportareto(1)provideanoverviewofthecurrentstatusoftreevolumeand biomassallometricequationsinNorthAmerica,(2)identifythegapsandfutureneeds,(3)provide recommendations for volume, biomass and carbon stock assessment, and (4) provide examples of howtousethedatabaseandselecttheappropriateequation.Thereportanalysesthevarioustree allometricequationsandidentifytheirpotentialforassessingnationalvolume,biomassandcarbon stocksandthevalidityandsuitabilityforuseinspeciesthatarefoundunderthecountry’sclimatic characteristics.

3. TheCompilationofthedata 3.1Reviewofavailableallometricequations Thefirstphasefocusesoncollectionandreviewofselectedliteratureconcerningvolume,biomass andcarbonstocksinNorthAmerica. Theequationsselectedweremainlydiameterbasedwithotherpossiblecovariablessuchasheight, age, etc. No other selection criteria (such as R2values, species, ages, sizes, site conditions, or samplingmethods)wereusedapriori. TheliteraturesurveywasconductedonInternetandinspecializedlibrariesanditismainlybasedon thecontributionsofJenkinsetal.(2003)anddeJongetal.(2009a).Onlineliteratureresearchwas conducted for sources that reported biomass and volume equations. A survey of online libraries (Springerlink,GoogleScholaretc.)andjournalssuchasCanadianJournalofForestResearch,Forest EcologyandManagement,ForestScience,EcologicalMonographs,JournalofEnvironmentalScience andManagement,Oecologia. Itisworthrememberingthatthedatacompilationisnotexhaustiveandmayhavenotconsideredall thedata.However,itisafirstregionaldatabasethatwillbeprogressivelycompleted. Duringthedatacollection,boththehardandsoftcopiesofallthedocumentscitedinthedatabase werecollectedinordertomakethemavailableforfurtherstudies.WithparticularregardtoMexico, theresearchwasalsoconductedattheFAOFRA(ForestResourcesAssessments)Library.TheFAO FRAlibrarycomprisesacollectionofFAOworkingpapers,projectfielddocuments,countryreports, volumetablesandforestinventoriesfromtheearly50stothelate90s,anditwasaprecioussource of data and information which would otherwise be difficult to obtain. Other worldwide reviewed libraries were, among others, the University of Idaho Library, Fort Hays State University Library, DavidLubinMemorialLibrary. For U.S.A and Canada the thorough work of Jenkins at al. (2003) was a valuable source of information,aswellaspreviousregressioncompilationssuchastheonefromTrittonandHornbeck (1982), TerMikaelian and Korzukhin (1997) and Means et al (1994). For Mexico, the mentioned nationalallometricequationdatabaseforaerialtreebiomass,developedbydeJongetal.(2009a), wasused. Tomaketheconsultationofbibliographyandreferenceseasierandtoexporttheminexceldatabase weusedaRISformatreferencemanagementsoftware(Thomson,2005).

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3.2Dataclassificationandgeoreferencing Oncethedocumentswerecollected,thedataweregeoreferencedandorganizedinordertomake themconsistentwiththetemplatedatabasethatwaselaborated. Aproblematicpointwasrelatedtothetreecompartmentspredictedbytheequation.Infact,there isnotauniquewaytodefinethevegetationcomponents(Finerootslargeroots,bigbranchessmall branchesetc.)aswellasthereisnotastandardandcommondefinitionforabovegroundbiomassor growingstock(itmayormaynotincludethestump,thebark,thetopetc.).Therefore,inorderto standardize the data and make them easier to use, 11 different tree compartments have been selected (Figure 1), thoroughly checking the original sources before entering the equations in the databaseandcarefullyconvertingtheircomponentsystemintoours.

Crownarea(m2)

Treeheight(m)

Bg B

Logheight(m)

Circumferenceordiameter (cm)at1.3m Basalcircumferenceor diameter(cm)

S Rm

Logvolume(m3)

T

Treevolume(m3)

Crownheight(m)

Bd

Bt

B Branchvolume(m3)

F

L

Leafvolume(m3)

Crowndiameter(m)

Basalarea(m2)

Bark

Bd

Deadbranches

Bg

Grossbranches:D>7cm

Bt

Thinbranches:D1 modelsareavailableatanylevel.Onlymodelsbuiltwith>30sampledtreesareconsideredforthedecisiontree. IfthemodelsdonothaveanR2associated,becauseitisnotreportedbytheauthoroifthemetadatahasnot yetbeencompiled,thenthemodelisnotaccountedforinthedecisiontree.Itisbasicallyexcludedfromthe analysis.Ifthishappens,theselectionprocessistakentoahigherlevel(genusorforesttypeequations)fora particulartree.

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Figure 17. Decision tree 3. A preliminary assessment is undertaken to determine whether equations at different levels are applicable for a particular tree in the inventory (e.g. a species and genuslevel equation couldbeusedtoestimatethebiomassofa20cmDBHPinuspatula).Oncetheappropriatelevel(s)arechosen (boxes arranged vertically after start) the decision tree shown after “A” is followed. This is done within the models’ DBH applicability ranges. If no models are applicable within their applicability ranges all levels are considered outside their applicability range and “A” is followed (See **). If the models do not have an MSE associated,because it is not reported by the author o if the metadata has not yet been compiled, then the modelisnotaccountedforinthedecisiontree.Itisbasicallyexcludedfromtheanalysis.

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Mainfindings Wefoundthatuncertaintyandtotalbiomasscarbonestimatedvariedaccordingtothedecisiontree employed(Table3).Differencesintheuncertaintyestimateswereduetotheapplicationofdifferent biomass models since the application of forest stratification, wood density values and carbon fractionswasthesameforalldecisiontrees. We also observed that uncertainty did not decrease with an increased use of species or genus specific models (Figure 18). Uncertainty was also not correlated to the number of equations employed in each decision tree (decision trees 1, 2 and 3 used 64, 29 and 114 equations, respectively,fromthe339equationpool;thefirstdecisiontreewith64equationsyieldedthelowest uncertainty). This may provide an argument for creating generic or forest type models instead of investinginspeciesorgenuslevelequations,however,modelerrorshouldbeassesspriortothis. For example, decision tree 3 was more efficient in selecting species or genuslevel equations but onlypresentedanaverageduncertainty. Despite the similarity of Decision trees 1 and 2, their uncertainties were very different which may suggestthatanyadditionalcriteriainDecisiontree1mayhavecontributedtoaloweruncertainty.In this regard, using geographic coordinates to assign biomass allometric equation may have cause estimation errors at the small scale (i.e. stands may vary considerably in structure and biomass content within meters) but at larger scales the criterion could be useful to avoid using equations builtindifferentgeoclimaticconditionstowherethetreethatisbeingestimatedislocated. Decision trees 2 and 3 used a minimum criteria of 30 trees used for constructing the biomass models.BothpresentedhigheruncertaintiesthanDecisiontree1,butitwouldberiskytoconclude thatthiscriterionaccountedforanincreaseduncertaintyintheestimates. Generally,itappearsthatdecisiontreesbuiltusingthecriteriaappliedhere(Table3)willprovidea good selection of equations if metadata is available (i.e. uncertainty was fairly constant in all decisiontreesintherange13,+19%.Metadataisimportantaskeyinformationtoselectequations. Table4showsmetadataavailablefortheequationsforMexico. Given thatwefound noapparent correlationbetweenthenumberofmodelsusedanduncertainty,itisadvisabletoemployasmany andbettermodelsaspossibletoreducebias. Finally,ifthemodelsanddataareavailabletocountrieswerecommendthatthisprocessisrepeated and several decision trees are tested prior to selecting one. Mexico is currently improving the information(metadata)thatgoesintoinformingthedecisiontrees,collectingwooddensityvalues and creating better models at the foresttype level, since these are most frequently used in the estimation.

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Table 3. National biomass carbon estimation using different decision trees for selecting biomass allometricmodels. Estimatedbiomasscarbonatnationallevel (10^3millionsoftonsofC)

Decisiontree1

Decisiontree2

Decisiontree3

1.68

1.44

1.33

Lognormal

Lognormal

Lognormal

Uncertaintylowerend

13%

16%

14%

Uncertaintyhigherend

+14%

+19%

+16%

pvalueassociatedtotheAICcriterioninthe MonteCarloanalysis.Thepvalueindicates theprobabilitythatthePDFand,hence,the percentilesestimatedtobuildtheuncertainty rangecomefromaknowndistributionthat wasfitusinggoodnessoffittestsandthe maximumlikelihoodcriterion.

0.27

0.20

0.85

Probabilitydensityfunction

Figure 18. Application of biomass allometric equation by level for the three decision trees employed. Uncertaintyestimatesare11,+12;16,+19;and14,+16,fordecisiontrees1,2and3,respectively.

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Table 4. Percentage (%) of available metadata associated to biomass allometric models in Mexico (n=339).

Allmodels

Specieslevel

Genuslevel

Foresttypelevel

Numberofmodels

339

273

50

16

r2

35

37

22

43

Meansquareerror

8

7

8

31

Rootmeansquareerror

1

1

4

0

Standarderror

14

13

14

25

Meanbiomass

0

0

0

0

Biomassvariance

1

1

0

0

Numberoftrees

36

36

28

62

Carbonfraction

2

1

10

0

Minimumwooddensity

0

0

0

0

Maximumwooddensity

0

0

0

0

Meanwooddensity

3

4

0

0

MinimumDBH

60

60

58

62

MaximumDBH

58

58

56

62

MeanDBH

8

7

8

12

Minimumrainfall

47

52

32

18

Maximumrainfall

11

11

12

0

Meanrainfall

11

11

14

6

Minimumtemperature

7

6

12

0

Maximumtemperature

7

6

12

0

Meantemperature

22

25

10

12

Maximumelevation

22

25

16

0

Minimumelevation

18

19

18

0

Meanelevation

5

6

2

0

Climatetype

48

53

30

25

Soiltype

34

37

30

6

Managementtype

0

0

2

0

Naturaldisturbances

2

2

6

0

State

64

66

68

18

Geographiccoordinates

35

34

46

18

Yearpublished

80

77

96

81

*Shadedlinesarecriteriausedinthedecisiontrees.

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8. GapsinassessingvolumeandbiomassinNorthAmerica The database is only a first attempt to create a comprehensive collection of tree allometric equationsforNorthAmerica.Somelacksareinevitable.Thedatabase,however,isdesignedtoallow aconstantupdatingofthedataandexistinggapscanbeaddressedinthefuture. Relying on the data collected as far, the present study shows that for Mexico there is a smaller number of available equations (only 319 compared with the 1809 of USA or 467 of Canada). It appearsthatthreeofthe14ecologicalzonesoccurringinnorthAmerica(FAO,2006)havemorethan 80% of the total equations. Important and widespread biomes, such as boreal coniferous forest, tropicalrainforest,tropicaldryforestareparticularlyunderrepresented. Thedistributionofequationspertreespeciesisnothomogenous,withamarkedpreferenceforthe moreeconomicallyimportantfamily,suchasPinaceaeandFagaceae.Thedatasuggestthatonlythe 14%ofthetreespeciesofNorthAmericahavebeenstudied. Concerningthetreecomponentmorethan40%oftheequationsreferstothetreestem,whereas theequationsforabovegroundbiomassrepresentonlythe14%andforundergroundbiomassand rootslessthan3%.Undergroundbiomassisequallyimportantfortheestimateofcarbonstock,and especiallyindryregion.

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9. Recommendations ItwouldbeimportanttoupdatethedatabasebyconductingaliteraturereviewforUSAandCanada for the period after 2003. For Mexico it is necessary to deepen the literature analysis, especially includinginthedatabasetheregressionsfortreeabovegroundcomponents. The equations collected so far should be subjected to a quality control in order to check their consistenceandtheintervalsofcalibration(Henry,etal.,2011). Further studies should also go in the direction to fill the existing gaps in the allometric equations inventory: 1) to improve the geographical distribution of the sample plots, including the under represented biomes, such as boreal coniferous forest, tropical rainforest, tropical dry forest and subtropicaldryforests;2)todevelopequationsfornewtreespeciesthatareprioritizedaccordingto theircontributiontototalvolume/biomass/carbon;3)toincreasetheproductionofnewallometric equationforMexico;4)tostimulateallometryresearchfortreeabovegroundcomponents. In order to improve the quality of biomass assessment and to develop new and more accurate models, it is also necessary to develop a comprehensive wood density and raw data database at regionalscale,collectingalltheavailablemeasuredtreebiomassvaluesforNorthAmerica.

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10.

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Appendices Appendix1.ListoftheAcronymusedinthedatabase. Acronym

Description

Unit

Population

2

BA

Basalarea:StemcrosssectionalareaatDBH(1m30height)

cm

TREE

BA0

Stemcrosssectionalareaatthesoil

cm2

TREE

BD

Basaldiameter

cm

TREE

C

Circumferenceat1.3m

cm

TREE

C10

Circumferenceat10cmheight

cm

TREE

C180


cm

TREE

C20


cm

TREE

C30


cm

TREE

C50


cm

TREE

2

Ca

Canopyarea

m

TREE

CA

Crownarea

cm2

TREE

Cb

Basalcircumference

cm

TREE

Cb5

Circonferenceat5cmfromsoil

cm

TREE

CD

Crowndiameter

Cm

TREE

CH

Crownheight

cm

TREE

CR

Crownradius

cm

TREE

CV

Canopyvolume

cm3

TREE

D20

Diameterat20cmheight

cm

TREE

D30

Diameterat30cmheight

cm

TREE

DBH

Diameteratbreastheight

cm

TREE

H

Height

cm

TREE

Hd

Standdominantheight

cm

STAND

Hme

Merchantableheight

cm

TREE

Ht

Heightofthetrunk

cm

TREE

M_DBH

AverageofDBH

cm

STAND 1

N

Numberoftrees

Tree*ha

R

treering

nr

TREE

SUMD10

Sumofthediametersat10cmfromthesoil

Cm

STAND

Yr

Year

yr

TREE

Vs

Stemvolume

dm3

TREE

WD

Wooddensity

g*cm3

TREE

Age

Ageofthetrees

yr

STAND

STAND

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Appendix2.Listofdataneededtoinsertanewallometricequationintothedatabase. N. 1

2

FIELD

DESCRITPION

EXAMPLES

Notes

ID

Identificationnumberoftheallometricequation.

1188

a.c.

EachequationhasitsownIDreference,twodifferentequationscannothavethesameID.

Lianas:woodyclimbingplantsmainlyoftropicalforests;

Tree

a.

Forest

Forest

a.

Plantation Hedgerow Homegarden Treeoutsideforest

Population

Mangroves:evergreentreesorshrubsoftropicalforests,havingproprootsandstemsandforming densethicketsalongtidalshores; Sprout:isashootwhichgrowsfromabudatthebaseofatreeorfromashruborfromitsroots; Stand:contiguousareathatcontainsanumberoftrees; Tree:woodyplanthavingamaintrunkandusuallyadistinctcrown. 3

Ecosystem

4

Continent

Nameofthecontinentwheretheequationwasdeveloped

Africa

a.

5

Country

NameofthecountryusingtheGAULnomenclature(GlobalAdministrativeUnitLayers,FAO).

BurkinaFaso

a.

Write“None”whentheallometricequationdoesnotrefertoanycountry.

Identificationnumberofthelocation.

6772

6

ID_Location

a.c.

Inthesamearticleforthesamelocationtheycouldbemorethanoneequation.

38

7

8

Group_Location

Location

Identificationnumberofthegrouplocations.

24

Whenanallometricequationisvalidforagroupoflocations.

Write“None”whentheallometricequationdoesnotrefertoanygrouplocation.

AlwaysprovideaseparatelistwiththeGroup_Locationsyouusedinthedatabase,eachonewiththe correspondingID.

LocationcorrespondstothenameoftheplacewheretheequationwasdevelopedItcanbeaprecise location(city,village..)orageographicalarea.

Laba

c.

a.

Searchalocationaspreciselyaspossible. Write“None”whentheallometricequationdoesnotrefertoanylocation. 9

10

Latitude

Longitude

Decimaldegrees

41.899566

Write“None”whentheallometricequationdoesnotrefertoanylatitude.

Decimaldegrees

12.515275

Write“None”whentheallometricequationdoesnotrefertoanylongitude.

b.

b.

11

Biome_FAO

GlobalEcologicalZones

Tropicaldryforest

b.

12

Biome_UDVARDY


Tropicaldryforests/ Woodlands

b.

13

Biome_WWF


Tropical&Subtropical Grasslands,Savannas& Shrublands

b.

14

Division_BAILEY


SAVANNADIVISION

b.

15

Biome_HOLDRIDGE


Tropicaldryforest

b.

|39

16

X

Independentvariable(seebelow).

BA

a.

e.g.: BA(basalarea,thecrosssectionalareaofthestematbreastheight),Bd(diameteratsoil),Bd5 (diameterat5cmfromsoil),C(circumferenceatbreastheight),Cb(circumferenceatsoil),Cd5 (circumferenceat5cmfromsoil),D10(diameterat10cmofheightfromthesoil),DBH(diameterof thestematbreastheight),H(height),wd(wooddensity).Lookattheendofthetutorialforan exhaustivelistoftheacronymstobeused. 17

Unit_X

Unitmeasure(mm,cm,cm2,cm3,dm,gcm3,m,m2...).Alwayskeeptheunitofmeasurement reportedbytheauthor.

cm

a.

18

Z

Independentvariable.

DBH

cm

H

m

Cannotbethereasecondvariable. Write“None”whenyouhavenotthisdata. 19

Unit_Z

Unitmeasure Write“None”whenyouhavenotthisdata.

20

W

Independentvariable. Write“None”whenyouhavenotthisdata.

21

Unit_W

Unitmeasure. Write“None”whenyouhavenotthisdata.

22

U


23

Unit_U

Unitmeasure Write“None”whenyouhavenotthisdata.

24

V


25

Unit_V

Unitmeasure. Write“None”whenyouhavenotthisdata.

40|

26

Min_X

ItistheminimumXvalue.

10cm

40cm

3,6m

7,8m

biomass

a.

Log10

a.

Write“None”whenyouhavenotthisdata. 27

Max_X

ItisthemaximumXvalue. Write“None”whenyouhavenotthisdata.

28

Min_Z

ItistheminimumZvalue. Write“None”whenyouhavenotthisdata.

29

Max_Z

ItisthemaximumZvalue. Write“None”whenyouhavenotthisdata.

30

Output

Itisthedependentvariable:Y Itcanexpress: Biomass Volume

31

Output_TR

TheoutputoftheequationcanbeexpressedintheLog(Y)orinthearithmeticvalueofY,inwhichcase youdon’tspecifyanything. Whentheresultoftheequationisalogarithmyouhavetospecifyifitisanaturallogarithm(Log)ora logarithmtobaseb=10,thecommonlogarithm(Log10). Write“None”if“Y”doesnotrefertoanylog.

32

Unit_Y

UnitmeasureofY(e.g.cm3,dm3,m3,m3/ha,g,kg,Mg,kg/ha,Mg/ha...).

kg

a.

33

Age

Ageofthepopulationconsideredintheexperiment(years).

20

Itcanbeaprecisenumber(e.g.20)orarange(e.g.2040)oradefinition(eg.young...). Write“None”whenyouhavenotthisdata.

|41

34

Veg_Component

35

B

Theyarethevegetationcomponentsoftheplantsconsideredintheequation(seebelow). e.g.: Branchbiomass Branchbiomasswithouttwigs Biomassofroots(RC+RF+RS) Biomassofdeadbranches Biomassofstembark Biomassofsmallroots Biomassoffineroots Crownbiomass(BR+FL) Proproots Stemvolume Stemwoodbiomass Stumpbiomass Totalabovegroundbiomass Totalfoliagebiomass Totalstembiomass(SW+SB) Totaltreebiomass(AB+RT) Totalabovegroundbiomasswithoutleaves Totalabovegroundwoodybiomass Bark

Totalstembiomass(SW+SB)

a.

TRUE

a.

a.

a.

a.

Write“TRUE“ifbarkisconsideredintheoutput; Write“FALSE“ifthiscomponentisnotconsidered. 36

Bd

Deadbranches Write“TRUE“ifdeadbranchesareconsideredintheoutput; Write“FALSE“ifthiscomponentisnotconsidered.

37

Bg

Grossbranches:D>7cm Write“TRUE“ifgrossbranchesareconsideredintheoutput; Write“FALSE“ifthiscomponentisnotconsidered.

38

Bt

Thinbranches:D