research article the cost of managing forest carbon under...

Research ArticleThe Cost of Managing Forest Carbon underREDD+ Initiatives A Case of Kolo Hills Forests in KondoaDistrict Dodoma Tanzania

Kabura John1 Dos Santos A Silayo2 and Arild Vatn3

1 Forest Industries Training Institute Ministry of Natural Resources and Tourism PO Box 1925 Moshi Kilimanjaro Tanzania2Department of Forest Engineering Sokoine University of Agriculture PO Box 3012 Morogoro Tanzania3 Department of International Environment and Development Studies Norwegian University of Life Sciences (NMBU)PO Box 5003 1432 As Norway

Correspondence should be addressed to Dos Santos A Silayo dsilayoyahoocouk

Received 7 February 2014 Revised 15 July 2014 Accepted 15 July 2014 Published 20 August 2014

Academic Editor Sunil Nautiyal

Copyright copy 2014 Kabura John et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Countries considering participating in a REDD+ mechanism need information on what it would cost them to reduce emissionsfrom deforestation and forest degradationThis study was conducted to estimate the cost of managing forest carbon under REDD+initiatives in Kolo Hills Forest Kondoa Tanzania Socioeconomic and biophysical information was collected through structuredquestionnaires focus group discussions and forest inventory respectively Results show that the community participated inmanaging the forest by undertaking a range of activities such as tree planting patrolling and fire protection The estimated totalcost was USD 41834938 while the average cost was USD 7906haThe average carbon stored was 1975 tC haminus1 which is equivalentto 7248 tCO

2

haminus1 Costs incurred by managing the forest in relation to tCO2

stored were USD 10485 tCO2

eminus1haminus1 The projectwas found to be economically feasible at 5 10 15 and 20discount rates withNPVs of USD 10710233183 USD 3398625586USD 10312945 and USD 124590511 respectively The internal rate of return was 2121 which is much higher than the WorldBank rate of 158 and the Tanzania rate of 148 We therefore conclude that the decision to undertake this REDD+ project wasworthwhile and should be favoured against the ldquodo nothingrdquo alternative

1 Introduction

Forests are the largest terrestrial reservoir for atmosphericcarbon dioxide [1] Tropical forests for example were esti-mated to store more than 320 billion tons of carbon [2]Tanzania has about 334 million hectares of forests andwoodlands [3] Out of this total area almost two thirdsconsist of woodlands on unreserved land which lack propermanagement [4] A forest resource on the unreserved landis under enormous pressure from expansion of agriculturalactivities livestock grazing fires and other human activitiesAbout 13 million hectares of the total forest areas in Tanzaniahave been gazetted as forest reserves of which 16 million hais under natural forests for water catchment and 80000 haare under industrial forest plantation [4] In the tropical

region where also Tanzania lies deforestation and forestdegradation have been occurring on a large scale playinga critical role in the carbon cycle with implications forclimate and biological diversity [5] Deforestation is theconversion of forested areas to nonforest land use suchas arable land urban use logged area or wasteland [6]Deforestation can result from deliberate removal of forestcover for agriculture or urban development or it can be anunintentional consequence of uncontrolled grazing (whichcan prevent the natural regeneration of young trees) Thecombined effect of grazing and fires can be a major causeof deforestation in dry areas Degradation on the other handinvolves reduced forest quality density and structure of thetrees the ecological services supplying the biomass of plantsand animals the species diversity and the genetic diversity

Hindawi Publishing CorporationInternational Journal of Forestry ResearchVolume 2014 Article ID 920964 12 pageshttpdxdoiorg1011552014920964

2 International Journal of Forestry Research

Globally CO2

emissions from deforestation and otherland use changes were 09 plusmn 05GtC on average during2003ndash2012 accounting for about 8 of all emissions fromhuman activity (fossil fuel cement and land use change)[7] Reducing forest loss is therefore of utmost impor-tance for climate change mitigation and this is reflectedin the commitment to include reduced emissions fromdeforestation and forest degradation plus sustainable for-est management enhancement of carbon stock and con-servation (REDD+) in the post-2012 agreements of theUnited Nation Framework Convention on Climate Change[8]

In Tanzania forest deforestation and degradation ratesare higher around 403000 ha annually equivalent to 116 ofthe forest estate hence the country is an important sourceof greenhouse gases (GHGs) emissions [3 9] REDD+ is aconcept that has been gaining momentum in climate changepolicy negotiations at both the international and nationallevels Hence a number of government funds have been estab-lished to support REDD+ activities such as the AustralianForest and Climate Initiative the GermanClimate ProtectionProgram and the Norwegian governmentrsquos fund Also anumber of developing countries announced initiatives toaddress emissions fromdeforestation and degradation At thesame time conservation organizations project developersand governments were beginning to implement voluntarymarket-based REDD+ pilot activities on the ground in devel-oping countries Currently sixteen (16) countries includingTanzania were receiving funding for piloting the REDD+under the UN-REDD program The programrsquos policy boardapproved a total of US$593 million for national programmesin these 16 partner countries These funds help to supportthe development and implementation of national REDD+strategies in the respective countries [10] Also there were 28UN-REDD program countries not receiving direct supportto national programmes but engage with the program in anumber of ways including observers to the programrsquos policyboard and through participation in regional workshops andknowledge sharing facilitated by the programrsquos interactiveonline workspace [10]

In Tanzania there are eight (8) REDD+ pilot projectsbeing implemented in different ecosystems by nongovern-mental organizations (NGOs) in collaboration with centrallocal government academic institutions and private sectorsin implementing the projects [11] Among those projectswas advancing REDD+ in Kolo Hills Forest (ARKFor)under AfricanWildlife Foundation (AWF) [11]The potentialof REDD+ pilot projects as part of a post-2012 climatechange regime remains uncertain in part due to lack ofdetailed information on the likely costs associated withforest carbon projects and REDD+ programmes in particular[12]

Angelsen et al [13] argue that there is no doubt thatREDD+ payments can do many activities that lead todeforestation and degradation less attractive However coun-tries considering participating in a REDD+ mechanismneed information on what it would cost them to reduceemissions from deforestation and forest degradation [14]Therefore as Tanzania prepares to embark on REDD+

it needs information on the future costs and benefits ofthese programmes This is because it will remain difficult todevelop REDD+ policy for initiating future REDD+ activitieswithout empirical evidences of the costs and benefits ofdeforestation and degradation and the avoidance of suchactivities Meanwhile several studies for example Wertz-Kanounnikoff [15] and Lubowski [16] have developed someeconomic models and estimated several costs associated toREDD+ at global level The costs include the opportunitycosts the transaction costs and the management costsamong others But according to Pagiola and Bosquets [14]these estimates provide very little guidance in this regard asin addition to the inevitable crude approximations that mustbe made in any such large-scale exercise conditions withinany given country (such as Tanzania) will differ substantiallyfrom any international and indeed any non-Annex 1 countryconditions AlsoWertz-Kanounnikoff [15] argued that infor-mation on the transaction costs of REDD+ schemes remainslimited

This study was delimited in identifying and estimatingtransaction costs associated with establishment and imple-menting of advancing REDD+ in Kolo Hill pilot projectUnderstanding and minimizing the transaction costs arecritical for reducing tropical forest losses [17] The resultswill help in identifying costs per specific areas in the courseof implementing REDD+ project and will help in assessingthe economic viability of the project This due to the factthat more attention to transaction costs would benefit theinstitutional design of a new global program intended tocombat tropical deforestation in developing countries andprovide information on how emission reductions mightpotentially be able to ldquosellrdquo to a REDD+ mechanism at agiven price It will also serve as a source of informationto policy makers and planners for initiating cost-effectivefuture REDD+ activities Therefore the aim of this study wasto identify and estimate the transaction cost associated inmanaging forest carbon under REDD+ initiatives at Kolo hillsforests Specifically it was based on identifying routine andnonroutine activities in establishing and running the projectThereafter we estimated their associated transaction costsincurred in setting up and running the project Finally weestimated carbon stock in Kolo Hill forest under REDD+project

2 Material and Methods

21 Location of the Study Area This study was conductedin Mnenia forest a part of the ARKFor pilot project com-monly known as Isabe and Salanga forest reserve and thesurrounding village of Mnenia in Kondoa district (Figure 1)The Mnenia forest in which the study conducted composedof five (5) hills namely Singe Chemchemi Kwachondo Rest-house and Malawi The forest is located 30 km east-southof Kondoa district The Kolo hills forest is estimated to be18000 ha The village and the forest are located in Kondoadistrict Dodoma at S 4∘54101584098310158401015840 andE 35∘47101584093710158401015840Thereforethe average altitude of an area ranges from 1650 to 2000Mabove sea level

International Journal of Forestry Research 3

Kondoa

Kondoa

MpwapwaDodoma

Kongwa

Bumbuta

To Kondoa

Mnenia Ward

Mnenia

Kwachondo

Singe Hill

To Pahi

N

(km)

Hill

TanzaniaLake Victoria

Lake

Nya

sa

Lake

Tan

gnyi

ka

DistrictGoima

144000

144000 146000 148000 150000 152000

9488000

9488000

9484000

9484000

9480000

9480000

9476000

9476000

146000 148000 150000 152000

Forest

420

Study sitesSettlement

Mnenia Forest

Mnenia villageRoad

Rural

Busi

Kwadelo

Jangalo

PahiHaubi

KikoreKisese

KikdoMasange

MneniaSoeraThawi

Changaa KoloKalamba

DalaiMondoKondoaMjini

Ovada

Lalta

Suruke

Kingale

Sanzawa

Mpendo

Farkwa

Makorongo

Gwandi

Paranga

Chemba

ChandamaMriloKwamtoro

Figure 1 Map of Kondoa district showing the study area


22 Sampling Procedures

221 Sampling for Socioeconomic Survey The sampling unitof the study was households However in this study ahousehold is defined as a group of people who eat in acommon pot and usually share a dwelling house and maycultivate the same land (Poate and Daplyn 1988 as cited by[18]) The Mnenia village was selected purposefully basedon the accessibility potentiality and proximity to the forestreserve Further it was under the REDD+ pilot project andsampled by the CCIAM-SUA project The households wereobtained from the village registersMoreover the respondentswere selected by matching their numbers in the register withthe first three numbers in the table of random numbersTherefore five percent (5) of households in the villagewas sampled randomly resulting into 35 households Accord-ing to Boyd et al [19] a recommended and reasonablerepresentative sample size of particular populations underthe study should be at least 5 Further other peoplewere selected purposefully village chairman members ofvillage natural resource committees and project coordina-tor of advancing REDD+ in Kolo Hills forest (ARKHFor)at Kondoa this is because we are better informed aboutthe specific costs of managing the forest under REDD+initiative

222 Sampling for Biophysical Survey Forest inventory wasconducted in Mnenia forest which is part of the Kolo Hillforest reserve This part of the forest falls under five hillsthat are Singe Chemchemi Kwachondo Rest-house andMalawi which covers an area of 5500 ha However the aimof selecting this portion of the project was based on limitedtime and resources to cover thewhole project area of 18000 haduring forest inventory The information obtained from theforest was extrapolated to cover the whole area due to thefact that the ARKFor project covers the same ecosystemTheMnenia forest was under joint forest management strategyintroduced by the project in the area hence informationon forest carbon stock in relation to the cost accrued bystakeholders assumed to be similar in other forest blocks ofthe project Consequently in order to cover the whole areaof the forest systematic sampling design was adopted Thenumber of sample plots was determined using the followingformula 119873 = (TA lowast SiPs lowast 100) where N is the numberof sample plots TA is the total area of the forest Si is thesampling intensity and Ps is the plot size In addition to thatthe sampling intensity of 005 was adopted a total of 39circular plots (007 ha) was laid out on 8 transects Furtherthe distance and distribution of plots between transects were250m and 200m between plots Furthermore GPS was usedto locate and mark each plot during the inventoryThereforethis is because the data obtained can be used in ground-truthing (remote sensing) and develop location mapping ofthe forest

23 Data Collection A cross-sectional design was employedin this study However the design allows collection ofinformation at one point in time [20] In addition to that it

involves two sets of data that are socioeconomic (identifica-tion of activities and transaction cost estimation) and carbonstock estimation Consequently in order to obtain all infor-mation required for the study both primary and secondarydata were collected Hence the study was conducted in threephases In phase one reconnaissance survey was conductedto provide a general picture of the research area through arapid assessment Nonetheless during this survey the studyvillage was selected the questionnaires were pretested theforest for inventory activities was identified and training tofield team was done Further for phase two the collectionof socioeconomic information in the selected village wasdone Lastly in phase three the collection of the vegetationinformation on the identified forest was done

231 Primary Data

(1) Socioeconomic Data A Socioeconomic survey using astructured questionnaire was conducted to collect informa-tion with regard to socioeconomic aspects of the commu-nities surrounding the Mnenia forest This involved solicitroutine nonroutine activities conducted by stakeholders andcost accrued in managing the forest However among allof the data collected were time and resources used by localpeople in the REDD+ project set-up and costs involved ininstitutional basis for making REDD+ (cost for defining landrights and establishing new village committees and costsof start-up information program eg number of meetingand people involved) Subsequently conservation institutionssuch as AWF and district forest office were also contactedfor additional information Therefore the socioeconomicinformation was collected through structured questionnaires(open and close ended) Further focus group discussion andparticipant observation were used in collecting data Accord-ing to Kajembe [18] as cited by Haule [21] focus on groupdiscussion and participant observation were used in orderto triangulate information given through questionnaires tocross check respondentrsquos answers and to obtain informationthat may not be covered by the questionnaire

(2) Forest Carbon Stock Data Forest inventory was conductedas to collect information on biophysical data of the Mneniaforest However circular sample plots with 2m 5m 10m and15m radius were adopted during the study because they areeasy to lay out and counting errors during inventory of bordertrees are minimised URT [22] reported that the edge effect isreduced in circular plots as compared to other plot shapesA circular plot when subdivided ensures that small trees aremeasured in small plots and large trees (which constitutemost of the biomass per unit area) are measured in largeplots and therefore normality of forests can be measuredThetropical natural forests are characterized by having negativeexponential diameter distribution such that there are severalsmall size trees and the number of trees decreases withincreasing tree sizes [22] During the inventory the plots werelocated systematically running from the forest border withthe first starting point selected randomly In addition to thatthe plots were measured using a measuring tape and all plotcoordinates of each transect were Geo-referenced using a


GPS and the direction of the transect line determined usingcompass to allow transect to be relocated in the future In eachplot along the transect line the data recordedwere diameter atbreast height (DBH) of all trees with DBH greater than 5 cmA treewas defined as any standingwoody plantwith a straightstem of at least 3m and with a diameter greater than 5 cmand below 4 cm was counted as regenerates In addition tothat species names (vernacular and botanical) of all measuredtrees were recorded in each plot Further local people assistedin identifying the tree species in local names and translatedinto botanical names using a checklist and literatures

232 Secondary Data Collection There was one categoryof data collected during the research as the secondaryinformation This information was on cost categories insocioeconomic data However secondary data included otherresearch findings and experience from different case studiesrelated to the transaction cost analysis and carbon stockestimation Hence data on transaction cost category werecollected from pilot project coordinating office in Kondoaand AWF headquarter in Arusha by using existing annualreports and relevant records for two years (January 2010 toDecember 2011) Further data were obtained from differentpublications journals and visiting websites to form anoverview and identify information gaps

24 Data Processing and Analysis

241 Socioeconomic Data Data from the questionnaires wasanalysed using the SPSS computer program The data thatwere analysedwere household characteristics such as age sexand occupation of the respondents The collected data wasfirst coded into meaningful computer language to assist inthe analysis Hence the analysis which included the deter-mination of descriptive statistics (such as central tendencyand dispersion of responses) was summarised and presentedas percentage means and frequency tables Data on routineand nonroutine activities of the local community were listedcoded and analysed through multiple response domain andpresented in frequency tables In addition to that data oncost (resources) from the local level and reports for ARKForproject were listed coded and analysed usingMicrosoftExcelspreadsheet to generate information on the total cost accruedby the local community and an NGO (AWF) It was assumedthat paying per day for local community was equivalent to$33 when an exchange rate of $1 was equal to 1500Tsh thatdepends on the prevailing average farm labours in the studysite

242 Above Ground Forest Carbon Stock of ARKFor ProjectData collected from the forest was analysed using theMicrosoft Excel spreadsheet so as to obtain above ground car-bon stock in terms of tons of biomass and carbon per hectareA locally available allometric equation developed by Cham-sahama et al [23] used to estimate forest biomass becausethe equation used to estimate carbon in Miombo woodlandThe allometric equation that was used was Biomass =00625119863

2553 where biomass is tree biomass (kgha) and 119863

is tree diameter at breast height (cm) Therefore the use oflocal allometric equations for areas with similar vegetationtype is recommended in the literature [24] In addition tothat the allometric equation has 1198772 of 097 making it reliablefor the estimation of biomass Further this equation includestrees from 1 cm diameter at breast height (dbh) and it hasthe advantage of requiring only Dbh as a variable Further-more forest average biomasses were obtained by dividingthe obtained biomass per plot by area (ha) of each cyclebiomass (kgha) is biomass (kg)area (ha) Then the averageabove ground biomass (AGB) values across all measuredplots was calculated using the following formulae AGB =sum119901

pl=1(Bpl)Npl where Bpl is the total biomass of all plots andNpl is the total number of plots in the study forest In additionto that the average biomass per hectare (Kgha) obtained wasconverted to carbon using a biomass-carbon ratio of 049[25 26] It involves multiplying average biomass estimated tobe obtained from hectare by 049 to obtain carbon stock perha (Kgha) Therefore the average carbon stock estimated tobe obtained per hectare was converted into tonne per ha bythe following formulae tC = C(kgha)1000Kg where tCis the tonne of carbon and C (Kgha) is the carbon (Kg) perhectare Lastly the cost per tonne of carbon dioxide stored perha in the forest was obtained by using the following formulaCost per tonne of CO

2

= ATCtCO2

where ATC is theaverage total cost andAtCO

2

is the average total carbon storedin the forest It was assumed that the average conversionfactor of 366 is equal to 1tCO

2

stored in the forest

243 Cost Benefit Analysis (CBA) CBA is the most widelyused approach in project appraising and it was the one usedin Mnenia forest project a part of the ARKFor pilot projectThe aim of doing CBA in this study was to determine whethermanaging Mnenia forest was economically profitable byusing Net Present Value (NPV) as a decision criterion Theformula we used for NPV was

NPV =119899

sum

119905=1

119861119905 minus 119862119905

(1 + 119903)119905

(1)

whereNPV isNet PresentValue119861119905 is project benefit in year 119905119862119905 is project costs in year 119905 119903 is Discount rate and 119899 is numberof years in the planning horizon According to this criterionan investment is profitable only if the NPV is greater thanzero In this evaluation two alternatives were considered withproject alternative and without project alternative the latterbeing the do nothing alternative According to Kessy et al[27] with suchmutually exclusive alternatives NPV is the bestcriterion compared to internal rate of return and benefitcostratio because the last two criteria may be misleading as theydo not show the monetary magnitude of the return

(1) Costs Benefit and Emission Baseline Components Thecosts considered in this analysis were based on the amountincurred by stakeholders and projection in setting up andrunning the project for 40 years Further other costs werebased on estimated amount of carbon credit emitted byconsidering the baseline deformation rate of 046 for theforest (Table 4) According to the feasibility study done by


CAMCO [28] the historical annual deforestation for Kolohills forest is estimated to be 046 They assumed thatfuture rates of deforestation will remain constant after imple-menting the project Therefore it was assumed that undera baseline (business as usual) scenario annual deforestationwould be 046 based on forest area of 5500 ha that is 25hectares of closed forest was deforested (to bush) per year Forthe purposes of the baseline emissions assessment we haveassumed a decrease in carbon stocks of 30 from openedto closed forest The benefit component considered includedthe estimated value that was assumed will be obtainedthrough trading projected carbon credit stored in the forestThe projections were based on reducing deforestation andforest degradation to 50 of baseline levels during years 1ndash5 and achieving 100 reduction between years 6ndash40 that iscompletely preventing deforestation and forest degradationFurther we assumed that the community incentive shouldbe 50 of the benefit obtained in trading the carbon Theanalysis considered the estimated project life span of 40 yearsand the average sequestration rate of 53 tCO

2

haminus1 yrminus1 asreported by Zahabu [29]Themarket price considered in thisstudy was based on the verified carbon standards (VCS) forldquoVoluntaryrdquo of $85 tCO

2

e (Diaz et al 2011)

(2) Discounting RateThe discount rates of 5 10 15 202121231441 and 25 were used in the analysis Throughthis method internal rate of return (IRR) was estimated TheWorldBank recommends a 158 [30] discount rate in projectevaluation for development projects with external fundingwhereas the Bank of Tanzania charges an interest of about148 [31] for long term lending including investment inforestry and carbon projects A switching value approach wasused to perform sensitivity analysis Sensitivity analysis isa procedure that analyses how changes of particular inputvalues (such as income or value of investment) resultingfrom inappropriate prediction or any other reason influ-ence certain criteria values and the total investment projectevaluation [32] According to Kessy et al [27] it is alsodesigned to find out how much should project elementschange in a negative way before the project meets theminimum level of acceptability as indicated by at least oneof the identified measures of project worth Decision makershave the responsibility to find out how likely they felt thatsuch a change was possible in the project

The objective of this analysis was to find out by whatproportion the benefits would have to be reduced before theNPV could fall to zero and eventually becomes negativeUncertainties associated with the project that could con-tribute to the reduction of the benefits included

(i) change in wage rate and administrative costs

(ii) change in the market price of carbon

(iii) shortage of labour

(iv) unwilling of the community to participate in theproject

(v) increase in factors influencing deforestation in theproject area

where the sequestration rate of the forest does not conformwith the stipulated assumptions identified for this project

3 Results

31 Activities and Costs Incurred by Community in ManagingKolo Hills Forest The findings showed that various activitieswere identified to be conducted in the area It showedthat the community attended various activities in managingthe forest (Table 1) Further we found the total amountof costs incurred by community adjacent of the forest inmanaging the forest by considering the identified routineand nonroutine activities were US$3566763 (Table 1) It wasestimated by considering prevailing average of farm laboursin the study site that the pay per day was equivalent toUS$33 when an exchange rate of US$1 was equal to 1500TshThe estimated amount accrued in forest patrolling was US$1738262 The activity of forest patrolling observed to be themain activities in the area performed by community adjacentof the forest such as charcoal making and livestock keepingprevention

32 Cost Incurred by the ARKFor Pilot Project in Managingthe Forest Results showed that the costs were incurred byARKFor in managing the forest divided into two categoriesthat were set up and running costs Setting cost was dividedinto two categories that were costs according to function andactors in the project that was estimated to be US$407391(Table 2) The second category was setting up the projectaccording to paying personnel and purchasing assets of theproject that estimated to beUS$149954 (Table 1) Meanwhilethe total costs incurred in running the project were dividedinto two categories A first categorywas according to functionand actors in the project that estimated to be US$524405The second category was running of the project according topaying personnel and purchasing assets estimated to be US$143663 (Table 2)

In addition to that the actual total cost accrued bythe project in setting up and running the ARKFor projectin Kondoa from January 2010 to December 2011 wasUS$1252413 spent by AWF in managing the forest coversof the whole area of the ARKFor pilot project estimatedto be 18000 ha Meanwhile as the Mnenia forest (part ofthe ARKFor project) covers estimated areas of 5500 ha thenthe cost estimated to manage the forest was $38268175However the findings (Table 2) showed that the estimatedtotal cost accrued by the community surrounding theMneniaforest in managing the forest was US$3566763 Thereforethe total cost assumed to be accrued by stakeholders (AWFand Mnenia community) was estimated to be $4134938 inmanaging the Mnenia forest For that reason the averageestimated cost incurred in managing the Mnenia forest ona hectare basis by stakeholders (AWF and local community)was US$7606ha As a result this amount of US$7606hashowswhat it will cost AWF as an organization administeringREDD+ and community adjacent of the forest to achievethe desired reduction in deforestation and emissions at theMnenia forest on per hectare basis


Table 1 Activities and their associated cost incurred by community in managing the ARKFor pilot project

Routine and nonroutine activitiesEstimated days and costs

Frequency Per day($US)

Number of daysper month

Number ofdays per year

Costs($US)

Routine activitiesTree planting 29 333lowast mdash 1 9657Forest patrolling 29 333lowast 15 180 1738260Forest boundary making 25 333lowast mdash 1 8325Land use planning 21 333lowast mdash 5 34965Attending seminar 25 333lowast mdash 5 41625Selected as a focal farmer 12 333lowast 5 60 239760Making server stoves 12 333lowast 5 60 239760Conducting beekeeping activities 14 333lowast 15 210 979020

Nonroutine activitiesAttending the village meeting 31 333lowast mdash 2 20646Forest fire protection 26 333lowast mdash 15 129870Demarcating forest boundary 22 333lowast mdash 1 7326Preventing keeping and livestock in the forest 25 333lowast mdash 15 124875

Total 3566763Source field datalowastPay per day was equivalent to $33 when an exchange rate of $1 was equal to 1500Tsh that depends on the prevailing average farm labours in the study site

33 Above Ground Forest Carbon Stock Costs per Tonneof CO

2

and Profitability of the Pilot Project The resultsshowed that the estimated forest carbon stock of the forestwas 1975 tC haminus1 Findings showed that distribution of forestparameters (biomass and carbon) by DBH class portraysa normal ldquo119869rdquo-shaped trend as expected for natural forest(Figure 2) The trees with small DBH have low biomass andcarbon stock content while trees with higher BDH have highamount of biomass and carbon stock

Further we found that the average tone of carbon dioxide(tCO2

) stored in the forest was 7248 tCO2

e haminus1

34 Discounting and Internal Rate of Return The results(Table 3) indicate that even when the discount rate is as highas 2121 the project is still economically efficient Howeverthemagnitude of NPVdecreases by 6827 with the increasein discount rate from 5 to 10 and again the magnitudeof benefits decreases by about 9633 with the increasein discount rate from 10 to 20 For a lower discountrate the present value of future benefits is high comparedto the situation when higher discount rates are used Theproject internal rate of return (IRR) was about 2121 whichmeans that if the project is to recover its investment andoperating expenses in forty years time and still breakeventhen the maximum interest that the project can pay for theresources used is about 2121 The IRR is higher than theWorld bank rate of 158 [30] and the Bank of Tanzaniarate of 148 [31] implying that the project is profitableHowever in the analysis we did not consider some intangiblebenefits from the catchment forest particularly the economicvalue of matured trees for timber production ecologicalbenefits such as regulation of the flow of water by slowing

0100200300400500600700800900

DBH class

Biomass (tha)Carbon (tha)

Biom

ass a

nd ca

rbon

stoc

k (h

aminus1)

DBH ge 1 le 4 DBH ge 5 le 9 DBH ge 10 le 19 DBH ge 20

Figure 2 Above ground biomass and carbon stock distribution inMnenia forests Kolo Hills Kondoa

down run-off absorb and hold water that recharges streamsand groundwater reduce the amount of sediment washingin streams by reducing soil erosion influence on climate-moisture in the air coming from trees via transpirationand evaporation providing habitats for wildlife species andbuffer against noise and aesthetically pleasing to the peoplearound the project area

4 Discussion

41 Routine and Nonroutine Activities and Their AssociatedCosts of Managing the Forest The forest patrolling was


Table 2 Setting up and running costs of the ARKFor pilot project from 2010 to 2011

Cost centersNGO main

office(AWF-Arusha)

NGO localoffice (AWF-Kondoa)

Partner Consultancy Monitoringbody Verifications

Villagesand

villagers

Total(US$)

Setting up costsNegotiating contractsplanning decisionmaking administrationand finances

150107 mdash 192132 mdash mdash mdash mdash 342239

Developing institutions 1625 2383 125 mdash mdash 4133Information programsand paymentprogramscommunication

4908 mdash 4146 9054

MRV systems 48514 mdash 3451 mdash mdash 51965Personnel cost 12290 42255 mdash mdash 66 mdash mdash 54611Office costs mdash 20832 mdash mdash mdash mdash mdash 20832Capital assets mdash 74511 mdash mdash mdash mdash mdash 74511

Running costsNegotiating contractsplanning decisionmaking administrationand finances

110225 mdash mdash 64638 mdash mdash mdash 174863

Developing institutions 223313 mdash $2314 53885 mdash mdash 46274 325786Information programsand paymentprogramscommunication


MRV systems 185 mdash mdash 11201 mdash mdash mdash 11386Personnel cost 26388 58183 mdash mdash 5310 mdash mdash 89881Office costs includeconsumables travellingcosts and miscellaneous

27986 2500 3600 3500 mdash mdash 14770 52356

Capital assets mdash 1426 mdash mdash mdash mdash mdash 1426Total 1252413Source ARKFor pilot project annual report from 2010 to 2011

observed to be the main activities in the area performed bycommunity adjacent of the forest such as charcoal makingand livestock keeping prevention This could be a resultof the amount paid to local communities in attendingthose activities or they have realised the importance of thesurrounding forest in their livelihood Kugonza et al [33]stated that a wide range of socioeconomic factors influencelocal community participation in managing the forest asthey realise the importance of forestry on their livelihoodstrategies Therefore costs incurred by local community werecalculated based on the days or time spent monthly inundertaking those activities for the purpose of managing theforest

In addition to that the community adjacent of theforest was observed to devote much of its time in forestpatrolling This could be possibly due to the presence ofvarious human activities like crop cultivation in the forestas shifting cultivation and cut down of the trees for charcoalmaking buildings and fire woods hence patrolling activitiesaccrue much time or costs than other activities in the areaIn addition to that it was learned that in the village therewere forest guards trained by AWF and VNRC members

who were involved in the forest patrolling activity Howeverit was noted that the established institution in communityfaces a range of challenges like lack of forest patrollingequipments but devoted much of their time in the managingthe forests This is because Mnenia forest was the source ofwater for irrigation and domestic purposes and other forestproducts such as honey and fuel wood obtained from thatforest Meshack et al [34] reported that in a situation inwhich forestry is just one of many livelihood activities costsas a proportion of total costs can be significantly highermarking up to 20 of the costs In addition to the estimatedcost incurred by communities adjacent of the forest othercosts incurred by an NGO (AWF) and other partners wereestimated in order to estimate the total costs accrued inmanaging the forest It involved the actual cost incurred insetup and running the ARKFor project based on functionactors and budget of the project

42 The Cost Incurred by ARKfor Pilot Project421 The Starting Costs The cost of negotiating planningdecision making and administration arises due to time


Table 3 NPV at various discount rates of 5 10 15 20 2121231441 and 25

Year Costs Benefits Net benefit NPV119903 = 5 119903 = 10 119903 = 15 119903 = 20 119903 = 2121231441 119903 = 25

1 354315272 0 minus354315272 minus337443116 minus322104792 minus308100236 minus295262726 minus292309633 minus2834522172 359302846 0 minus359302846 minus325898273 minus296944501 minus271684571 minus249515865 minus244549720 minus2299538213 342037110 0 minus342037110 minus295464516 minus256977543 minus224894952 minus197938142 minus192058263 minus1751230004 342261350 0 minus342261350 minus281579259 minus233769107 minus195689038 minus165056592 minus158551693 minus1401902495 342037374 0 minus342037374 minus267995232 minus212378299 minus170053025 minus137457149 minus130719339 minus1120788076 340275178 0 minus340275178 minus253918577 minus192076467 minus147110350 minus113957469 minus107287668 minus892010967 4480000 582598500 578118500 410858025 296666202 217336158 161342263 150379855 1212402378 4230000 627478500 623248500 421839117 290750025 203741040 144947682 133747999 1045637479 3680000 664644750 660964750 426063771 280313576 187887434 128099397 117019330 8871318710 3680000 701811000 698131000 428591874 269159722 172567306 112752054 101969311 7496124511 3680000 738977250 735297250 429913073 257717200 158047161 98962176 88603068 6316155312 3680000 776143500 772463500 430136581 246130677 144378951 86636922 76792188 5308328813 3680000 813309750 809629750 429363943 234520899 131587469 75671137 66401638 4450986614 3680000 846969750 843289750 425918628 222064548 119181009 65680943 57058771 3708827515 3680000 887642250 883962250 425200956 211613535 108634086 57373987 49343797 3110165716 3680000 924808500 921128500 421979579 200464399 98436185 49821900 42420162 2592746217 3680000 961974750 958294750 418100825 189593508 89050389 43193453 36408641 2157887918 3680000 999141000 995461000 413634607 179042411 80438344 37390547 31202031 1793263119 3680000 1036307250 1032627250 408645668 168842807 72557885 32322125 26702717 1488172720 3680000 1073473500 1069793500 403193919 159017987 65364681 27904551 22822598 1233387921 3680000 1110639750 1106959750 397334750 149584103 58813521 24061664 19482748 1020990222 3680000 1147806000 1144126000 391119326 140551272 52859295 20724614 16612902 844216023 3680000 1184972250 1181292250 384594860 131924542 47457737 17831534 14150841 697311924 3680000 1222138500 1218458500 377804881 123704728 42565974 15327130 12041730 575400825 3680000 1259304750 1255624750 370789469 115889140 38142913 13162207 10237438 474361626 3680000 1295769750 1292089750 363388271 108413376 34130986 11287046 8691152 390510227 3680000 1333637250 1329957250 356226814 101446059 30548929 9681531 7380327 321563928 3500000 1370803500 1367303500 348790423 94813404 27310232 8294497 6259737 264475029 3500000 1407969750 1404469750 341210759 88536942 24393551 7099966 5304651 217331230 3500000 1445136000 1441636000 333562060 82618074 21773107 6073209 4492140 178465931 3500000 1482302250 1478802250 325868087 77043652 19421244 5191483 3801553 146453532 3500000 1519468500 1515968500 318150498 71799968 17312480 4434966 3215099 120107433 3500000 1556634750 1553134750 310428987 66872957 15423410 3786413 2717481 98441634 3500000 1593801000 1590301000 302721428 62248378 13732600 3230851 2295567 80637835 3500000 1630967250 1627467250 295044002 57911962 12220468 2755298 1938100 66017936 3500000 1668133500 1664633500 287411316 53849536 10869170 2348517 1635445 54020437 3500000 1705299750 1701799750 279836519 50047122 9662475 2000794 1379364 44181238 3500000 1742466000 1738966000 272331405 46491018 8585650 1703742 1162826 36116939 3500000 1779632250 1776132250 264906513 43167866 7625346 1450129 979834 29511140 3500000 1816798500 1813298500 257571223 40064700 6769486 1233728 825277 241029

10710233183 3398625586 1031294500 124590511 000 minus262079384

and resources spent to wrap up the negotiations planningcommunication and travel costs In addition to that asthe project was in the initial stage this tends to incurmuch cost possibly because as the foundation of the projectlay properly then the project could be thriving Dudekand Wiener [35] stated that negotiation costs would arisein the form of time spent to conclude the negotiations

communication and travel costs and possibly a fee forspecialised consultants in legal or financial matters Furtherit was found that purchasing of capital assets accrued moreduring stating the project This could be due to the fact thatthe project was in the establishment stage then things likevehicles and other important assets must be purchased forproper management of the project Milne [36] stated that


Table 4 Estimated amount of GHG abated (CERERU)

Year

Estimation ofbaseline net GHGremovals by sinks

Estimation ofactual net GHGremovals by sinks

Estimation ofleakage(tCO2e)

Estimation of netanthropogenic GHGremovals by sinks

Estimation of netbenefit accrued bytrading carbon

(tonnes of CO2e) (tonnes of CO2e) (tonnes of CO2e) (USD)0 39680626 0 0 minus39680626 minus3372853181 39772313 0 0 minus39772313 minus3380646592 39680836 0 0 minus39680836 minus3372871103 39589571 0 0 minus39589571 minus3365113504 39498515 0 0 minus39498515 minus3357373745 39407668 0 0 minus39407668 minus3349651786 0 42779000 0 42779000 3636215007 0 45694000 0 45694000 3883990008 0 49214000 0 49214000 4183190009 0 52129000 0 52129000 44309650010 0 55044000 0 55044000 46787400011 0 57959000 0 57959000 49265150012 0 60874000 0 60874000 51742900013 0 63789000 0 63789000 54220650014 0 66429000 0 66429000 56464650015 0 69619000 0 69619000 59176150016 0 72534000 0 72534000 61653900017 0 75449000 0 75449000 64131650018 0 78364000 0 78364000 66609400019 0 81279000 0 81279000 69087150020 0 84194000 0 84194000 71564900021 0 87109000 0 87109000 74042650022 0 90024000 0 90024000 76520400023 0 92939000 0 92939000 78998150024 0 95854000 0 95854000 81475900025 0 98769000 0 98769000 83953650026 0 101629000 0 101629000 86384650027 0 104599000 0 104599000 88909150028 0 107514000 0 107514000 91386900029 0 110429000 0 110429000 93864650030 0 113344000 0 113344000 96342400031 0 116259000 0 116259000 98820150032 0 119174000 0 119174000 101297900033 0 122089000 0 122089000 103775650034 0 125004000 0 125004000 106253400035 0 127919000 0 127919000 108731150036 0 130834000 0 130834000 111208900037 0 133749000 0 133749000 113686650038 0 136664000 0 136664000 116164400039 0 139579000 0 139579000 118642150040 0 142494000 0 142494000 1211199000Average overCrediting period(2010ndash2040)(tCO2e)

5795842 79300610 0 73504768 624790525

Total forCrediting period(2010ndash2040)(tCO2e)

237629528 3251325000 0 3013695472 25616411512

NB baseline deforestation rate was 046 sequestration rate was 53 tCO2hayear and price per carbon was 85USDtCO2e


procurement scheme design and negotiation are importantcategories of transaction costs during establishment of REDDprojects

422 Running Cost The developed institution (such as theestablished JFM in the village plan training communitiesand register JFM and conducting training to communities)accrued high cost in managing the forest This was possiblydue to the fact that more attention was given to each villageadjacent of the forest involved in managing the ARKForpilot project which has a credible management institutionthat will oversee all the activity in the community It waslearned that in running the developed institution in thevillage training of local communities was undertaken toensure its sustainabilityThe high cost incurred in developingan institution for example in Tanzania is involved in estab-lishing a joint management plan and development agreementbetween local communities surrounding the forest Furtherit requires much time and resources in completing Bond etal [37] argued that realising REDD projects or schemes inweak governance settings is likely to imply higher transactioncosts than in settings or runningwhere institutions and rightsare well defined and well functioning Further it was foundthat personnel cost such as salaries and fringe benefit ofthe staff project accrued more cost than other cost centersThis was possibly due to the initial stage of the projectthat requires more personnel who will make sure that theestablished activities in the area are properly managed likeproject coordinator and other supporting staff Further it waslearned that the project provides a contract for conductingbaseline on establishing an MRV system in the area thatleads in employing various people hence more resourceswere spent for paying personnel and execute administrativeactivities

423 Above Ground Forest Biomass Carbon Stock Costsper Tonne of CO

2

and Profitability of the Pilot ProjectDespite differences in methodologies and environmentalconditions other Miombo woodlands studies have reportedsimilar carbon (C) stock and cost per tonne of CO

2

tothose obtained in this study Shirima et al [38] reported thateastern Miombo woodlands in Tanzania have been shownto have C storage potential of between 25 and 80 tChaminus1Zahabu [29] found that in Kitulangalo Forest Resource theC stock was 176ndash229 tC haminus1 equivalent to 6459 tCO

2

haminus1and 8404 tCO

2

haminus1 respectively Nhantumbo and Izidine[39] reported that Nambita forest project in Mozambiquewith 19 tC haminus1equivalent to 6973 tCO

2

haminus1 at a price of$4 tCo

2

minus1 and a net benefit of $476 was feasible and profitableat discount rate of 10

5 Conclusion and Recommendations

According to the stated assumptions the project was foundto be economically feasible at 5 10 15 and 20discount rates with NPVs of about USD 10710233183US$ 3398625586 US$ 1031294500 and USD 124590511respectively The internal rate of return (IRR) was found

to be about 2121 which is much higher than the WorldBank rate of 158 [30] and the Tanzanian rate of 148 [31]We therefore conclude that the decision to undertaking thisproject was worthwhile and should be favoured against theldquodo nothingrdquo alternative Although the estimates suggest thatabatement costs observed in the ARKFor pilot project wasbetween the ranges of the estimates in non-Annex I countriesmore investigation should be done to other forest ecosystemsin Tanzania Further knowledge gained by the communitiessurrounding the forest could be disseminated to other partsof the country to improve conservation and reduce forestdegradation through deforestation

Conflict of Interests

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

Acknowledgments

This paper has been produced under a research projectldquoREDD+Architecture in Tanzaniardquo funded by theNorwegianGovernment through a Programme on Climate ChangeMitigation and Adaptation for Tanzania based at SokoineUniversity of Agriculture The findings and views expressedin this document are the sole responsibility of the authorsand do not necessarily represent the views of the institutionsinvolved in this project or the funder The authors would liketo express their sincere acknowledgement to the Royal Nor-wegian Government for supporting this work REDD+ PilotProject under the African Wildlife Foundation Leaders ofthe Local Government inKondoa district andMnenia villagecouncil are highly acknowledged Lastly the communities inMnenia village are acknowledged for agreeing to participatein this research

References

[1] G A Alexandrov ldquoCarbon stock growth in a forest stand thepower of agerdquo Carbon Balance and Management vol 2 no 2article 4 2007

[2] 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 pp 10ndash13 2007

[3] FAO Managing Forest for Climate Change FAO Rome Italy2010

[4] URT National Forest Policy Ministry of Natural Resources andTourism Forest and Beekeping Division Government PrinterDar es Salaam Tanzania 1998

[5] K Forester-Kibuga and B Samweli ldquoAnalysis of the drivers ofdeforestation and stakeholders in the Kilosa project siterdquo TechRep 27 TFCG Dar es Salaam Tanzania 2010

[6] G Tejaswi Manual on Deforestation Degradation and Frag-mentation Using Remote Sensing and GIS MAR-SFM WorkingPaper 52007 Food and Agriculture Organization of the UnitedNations Rome Italy 2007

[7] GCP ldquoGlobal carbon budgetrdquo 2014 httpwwwglobalcarbon-projectorgcarbonbudget13hl-fullHtm


[8] MObersteinerMHuettner F Kraxner et al ldquoOn fair effectiveand efficient REDD mechanism designrdquo Carbon Balance andManagement vol 4 article 11 2009

[9] K D Mutabazi C K George A S dos Santos and M MFelister ldquoLivelihood implications of REDD+ and costs-benefitsof agricultural intensification in REDD+ pilot area of KilosaTanzaniardquo Journal of EcosystemampEcography vol 4 p 144 2014

[10] UN-REDD UN-REDD Programme Newsletter Archive No 292012 httpwwwun-reddorgNewsletterArchivetabid5420Defaultaspx

[11] URT National Framework for REDD Vice Presidentrsquos OfficeDar Es Salaam Tanzania 2009

[12] N Olsen and J Bishop The Financial Costs of REDD Evidencefrom Brazil and Indonesia IUCN Gland Switzerland 2009

[13] A Angelsen M Brockhaus W D Sunderlin and L V VerchotEds Analysing REDD+ Challenges and Choices The Centerfor International Forestry Research (CIFOR) Bogor Indonesia2012

[14] S Pagiola and B Bosquet Estimating the Costs of REDD at theCountry Level Version 22 Forest Carbon Partnership FacilityWorld Bank 2009

[15] SWertz-Kanounnikoff ldquoEstimating the costs of reducing forestemissions a review of methodsrdquo A Working Paper CIFORBogor Indonesia 2008

[16] R Lubowski The Role of REDD in Stabilising Greenhouse GasConcentrations Lessons from Economic Models Infobrief 18CIFOR Bogor Indonesia 2008

[17] L J Alston and K Andersson ldquoReducing greenhouse gasemissions by forest protection the transaction cost of REDDrdquoNBER Working Paper Series National Bureau of Economic2011

[18] G C Kajembe ldquoSociomdasheconomic aspects of tree farming inNjombe Districtrdquo Consultancy Report to the Natural ResourcesConservation and Land Use Management Project FORCON-SULT Faculty of Forestry and Nature Conservation SokoineUniversity of Agriculture Morogoro Tanzania 1996

[19] H K R Boyd E Westfall and S F StaschMarketing ResearchText and Cases Richard D Irwin Homewood Ill USA 1981

[20] C R Kothari Research Methodology Methods and TechniquesNew Age International New Delhi India 2nd edition 2004

[21] H J A Haule Assessment of forest condition threats and man-agement effectiveness in the catchment of Malagarasi-MuyovoziWetland Urambo District Tanzania [MS thesis] SokoineUniversity of Agriculture Morogoro Tanzania 2007

[22] URT Field Manual Biophysical Survey National ForestryResource Monitoring and Assessment of Tanzania(NAFORMA) Dar es Salaam Tanzania 2010

[23] S A O Chamshama A G Mugasha and E Zahabu ldquoStandbiomass and volume estimation for Miombo woodlands atKitulangalo Morogoro Tanzaniardquo Southern African ForestryJournal vol 200 pp 59ndash70 2004

[24] IPCC Good Practice Guidance for Land Use Land-Use Changesand Forestry Institute of Global Environmental StrategiesKanagawa Japan 2003

[25] K G MacDicken A Guide to Monitoring Carbon Storagein Forestry and Agroforestry Projects Winrock InternationalInstitute for Agricultural Development 1997

[26] S Brown ldquoMeasuring monitoring and verification of carbonbenefits for forest based projectsrdquo in Capturing Carbon andConserving Biodiversity The Market Approach I R SwinglanEd pp 118ndash133 Earthscan Publications London UK 2003

[27] J F Kessy A Orsquokitingati and B Solberg The Economics ofRehabilitating Denuded Areas in Tanzania The Case of LeghoMulo Project in Moshi Tanzania 1993

[28] CAMCO Advancing REDD in the Kolo Hills Forests FeasibilityStudy African Wildlife Foundation 2010

[29] E Zahabu Sinks and sources a strategy to involve forestcommunities in Tanzania in global climate policy [PhD thesis]University of Twente Enschede The Netherlands 2008

[30] The World Bank The World Bank Report 2014 httpdataworldbankorgindicatorFRINRLENDhtm

[31] BOT ldquoBank of Tanzaniardquo 2011 httpwwwbot-tzorgpublica-tionsEconomicIndicatorsInterest Rateshtm

[32] P Jovanovic ldquoApplication of sensitivity analysis in investmentproject evaluation under uncertainty and riskrdquo InternationalJournal of Project Management vol 17 no 4 pp 217ndash222 1999

[33] A Kugonza M Buyinza and P Byakagaba ldquoLinking localcommunities livelihoods and forest conservation in Masindidistrict North Western Ugandardquo Research Journal of AppliedSciences vol 4 no 1 pp 10ndash16 2009

[34] C K Meshack B Ahdikari N Doggart and J C LovettldquoTransaction costs of community-based forest managementempirical evidence from Tanzaniardquo African Journal of Ecologyvol 44 no 4 pp 468ndash477 2006

[35] D J Dudek and J B Wiener ldquoJoint implementationrdquo inTransaction Costs and Climate Change Paris France 1996

[36] M Milne ldquoTransaction costs of forest carbon projectsrdquo Work-ing Paper CC05 ACIAR Project ASEM 1999093 Centre forInternational Forestry Research (CIFOR) Bogor Indonesia1999

[37] I Bond M Grieg-Green S Wertz-Kanounnikoff S Wunderand A Angelsen Incentives to Sustain Forest Ecosystem ServicesA Review and Lessons for REDD International Institute forEnvironment and Development London UK CIFOR BogorIndonesia World Resources Institute Washington DC USA2009

[38] 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

[39] I Nhantumbo and S Izidine Preparing for REDD in Dry-land Forests Investigating the Options and Potential Synergyfor REDD Payments in the Miombo Eco-Region (MozambiqueCountry Study) International Institute for Environment andDevelopment (IIED) London UK 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


Globally CO2

emissions from deforestation and otherland use changes were 09 plusmn 05GtC on average during2003ndash2012 accounting for about 8 of all emissions fromhuman activity (fossil fuel cement and land use change)[7] Reducing forest loss is therefore of utmost impor-tance for climate change mitigation and this is reflectedin the commitment to include reduced emissions fromdeforestation and forest degradation plus sustainable for-est management enhancement of carbon stock and con-servation (REDD+) in the post-2012 agreements of theUnited Nation Framework Convention on Climate Change[8]

In Tanzania forest deforestation and degradation ratesare higher around 403000 ha annually equivalent to 116 ofthe forest estate hence the country is an important sourceof greenhouse gases (GHGs) emissions [3 9] REDD+ is aconcept that has been gaining momentum in climate changepolicy negotiations at both the international and nationallevels Hence a number of government funds have been estab-lished to support REDD+ activities such as the AustralianForest and Climate Initiative the GermanClimate ProtectionProgram and the Norwegian governmentrsquos fund Also anumber of developing countries announced initiatives toaddress emissions fromdeforestation and degradation At thesame time conservation organizations project developersand governments were beginning to implement voluntarymarket-based REDD+ pilot activities on the ground in devel-oping countries Currently sixteen (16) countries includingTanzania were receiving funding for piloting the REDD+under the UN-REDD program The programrsquos policy boardapproved a total of US$593 million for national programmesin these 16 partner countries These funds help to supportthe development and implementation of national REDD+strategies in the respective countries [10] Also there were 28UN-REDD program countries not receiving direct supportto national programmes but engage with the program in anumber of ways including observers to the programrsquos policyboard and through participation in regional workshops andknowledge sharing facilitated by the programrsquos interactiveonline workspace [10]

In Tanzania there are eight (8) REDD+ pilot projectsbeing implemented in different ecosystems by nongovern-mental organizations (NGOs) in collaboration with centrallocal government academic institutions and private sectorsin implementing the projects [11] Among those projectswas advancing REDD+ in Kolo Hills Forest (ARKFor)under AfricanWildlife Foundation (AWF) [11]The potentialof REDD+ pilot projects as part of a post-2012 climatechange regime remains uncertain in part due to lack ofdetailed information on the likely costs associated withforest carbon projects and REDD+ programmes in particular[12]

Angelsen et al [13] argue that there is no doubt thatREDD+ payments can do many activities that lead todeforestation and degradation less attractive However coun-tries considering participating in a REDD+ mechanismneed information on what it would cost them to reduceemissions from deforestation and forest degradation [14]Therefore as Tanzania prepares to embark on REDD+

it needs information on the future costs and benefits ofthese programmes This is because it will remain difficult todevelop REDD+ policy for initiating future REDD+ activitieswithout empirical evidences of the costs and benefits ofdeforestation and degradation and the avoidance of suchactivities Meanwhile several studies for example Wertz-Kanounnikoff [15] and Lubowski [16] have developed someeconomic models and estimated several costs associated toREDD+ at global level The costs include the opportunitycosts the transaction costs and the management costsamong others But according to Pagiola and Bosquets [14]these estimates provide very little guidance in this regard asin addition to the inevitable crude approximations that mustbe made in any such large-scale exercise conditions withinany given country (such as Tanzania) will differ substantiallyfrom any international and indeed any non-Annex 1 countryconditions AlsoWertz-Kanounnikoff [15] argued that infor-mation on the transaction costs of REDD+ schemes remainslimited

This study was delimited in identifying and estimatingtransaction costs associated with establishment and imple-menting of advancing REDD+ in Kolo Hill pilot projectUnderstanding and minimizing the transaction costs arecritical for reducing tropical forest losses [17] The resultswill help in identifying costs per specific areas in the courseof implementing REDD+ project and will help in assessingthe economic viability of the project This due to the factthat more attention to transaction costs would benefit theinstitutional design of a new global program intended tocombat tropical deforestation in developing countries andprovide information on how emission reductions mightpotentially be able to ldquosellrdquo to a REDD+ mechanism at agiven price It will also serve as a source of informationto policy makers and planners for initiating cost-effectivefuture REDD+ activities Therefore the aim of this study wasto identify and estimate the transaction cost associated inmanaging forest carbon under REDD+ initiatives at Kolo hillsforests Specifically it was based on identifying routine andnonroutine activities in establishing and running the projectThereafter we estimated their associated transaction costsincurred in setting up and running the project Finally weestimated carbon stock in Kolo Hill forest under REDD+project

2 Material and Methods

21 Location of the Study Area This study was conductedin Mnenia forest a part of the ARKFor pilot project com-monly known as Isabe and Salanga forest reserve and thesurrounding village of Mnenia in Kondoa district (Figure 1)The Mnenia forest in which the study conducted composedof five (5) hills namely Singe Chemchemi Kwachondo Rest-house and Malawi The forest is located 30 km east-southof Kondoa district The Kolo hills forest is estimated to be18000 ha The village and the forest are located in Kondoadistrict Dodoma at S 4∘54101584098310158401015840 andE 35∘47101584093710158401015840Thereforethe average altitude of an area ranges from 1650 to 2000Mabove sea level


Kondoa

Kondoa

MpwapwaDodoma

Kongwa

Bumbuta

To Kondoa

Mnenia Ward

Mnenia

Kwachondo

Singe Hill

To Pahi

N

(km)

Hill


Lake

Nya

sa

Lake

Tan

gnyi

ka

DistrictGoima

144000

144000 146000 148000 150000 152000

9488000

9488000

9484000

9484000

9480000

9480000

9476000

9476000

146000 148000 150000 152000

Forest

420


Mnenia Forest

Mnenia villageRoad

Rural

Busi

Kwadelo

Jangalo

PahiHaubi

KikoreKisese

KikdoMasange

MneniaSoeraThawi

Changaa KoloKalamba


Ovada

Lalta

Suruke

Kingale

Sanzawa

Mpendo

Farkwa

Makorongo

Gwandi

Paranga

Chemba









231 Primary Data












2

= ATCtCO2


2


2



NPV =119899

sum

119905=1

119861119905 minus 119862119905

(1 + 119903)119905

(1)





2


2

e (Diaz et al 2011)









3 Results










Costs($US)





2




e haminus1


0100200300400500600700800900

DBH class


Biom

ass a

nd ca

rbon

stoc

k (h

aminus1)




4 Discussion





office(AWF-Arusha)



Villagesand

villagers

Total(US$)




4908 mdash 4146 9054







27986 2500 3600 3500 mdash mdash 14770 52356










10710233183 3398625586 1031294500 124590511 000 minus262079384





Year







5795842 79300610 0 73504768 624790525


237629528 3251325000 0 3013695472 25616411512






2


2


2


2


2


2







Acknowledgments


References













































Journal of












Volume 2014

Advances in









Geophysics















Kondoa

Kondoa

MpwapwaDodoma

Kongwa

Bumbuta

To Kondoa

Mnenia Ward

Mnenia

Kwachondo

Singe Hill

To Pahi

N

(km)

Hill


Lake

Nya

sa

Lake

Tan

gnyi

ka

DistrictGoima

144000

144000 146000 148000 150000 152000

9488000

9488000

9484000

9484000

9480000

9480000

9476000

9476000

146000 148000 150000 152000

Forest

420


Mnenia Forest

Mnenia villageRoad

Rural

Busi

Kwadelo

Jangalo

PahiHaubi

KikoreKisese

KikdoMasange

MneniaSoeraThawi

Changaa KoloKalamba


Ovada

Lalta

Suruke

Kingale

Sanzawa

Mpendo

Farkwa

Makorongo

Gwandi

Paranga

Chemba









231 Primary Data












2

= ATCtCO2


2


2



NPV =119899

sum

119905=1

119861119905 minus 119862119905

(1 + 119903)119905

(1)





2


2

e (Diaz et al 2011)









3 Results










Costs($US)





2




e haminus1


0100200300400500600700800900

DBH class


Biom

ass a

nd ca

rbon

stoc

k (h

aminus1)




4 Discussion





office(AWF-Arusha)



Villagesand

villagers

Total(US$)




4908 mdash 4146 9054







27986 2500 3600 3500 mdash mdash 14770 52356










10710233183 3398625586 1031294500 124590511 000 minus262079384





Year







5795842 79300610 0 73504768 624790525


237629528 3251325000 0 3013695472 25616411512






2


2


2


2


2


2







Acknowledgments


References













































Journal of












Volume 2014

Advances in









Geophysics




















231 Primary Data












2

= ATCtCO2


2


2



NPV =119899

sum

119905=1

119861119905 minus 119862119905

(1 + 119903)119905

(1)





2


2

e (Diaz et al 2011)









3 Results










Costs($US)





2




e haminus1


0100200300400500600700800900

DBH class


Biom

ass a

nd ca

rbon

stoc

k (h

aminus1)




4 Discussion





office(AWF-Arusha)



Villagesand

villagers

Total(US$)




4908 mdash 4146 9054







27986 2500 3600 3500 mdash mdash 14770 52356










10710233183 3398625586 1031294500 124590511 000 minus262079384





Year







5795842 79300610 0 73504768 624790525


237629528 3251325000 0 3013695472 25616411512






2


2


2


2


2


2







Acknowledgments


References













































Journal of












Volume 2014

Advances in









Geophysics























2

= ATCtCO2


2


2



NPV =119899

sum

119905=1

119861119905 minus 119862119905

(1 + 119903)119905

(1)





2


2

e (Diaz et al 2011)









3 Results










Costs($US)





2




e haminus1


0100200300400500600700800900

DBH class


Biom

ass a

nd ca

rbon

stoc

k (h

aminus1)




4 Discussion





office(AWF-Arusha)



Villagesand

villagers

Total(US$)




4908 mdash 4146 9054







27986 2500 3600 3500 mdash mdash 14770 52356










10710233183 3398625586 1031294500 124590511 000 minus262079384





Year







5795842 79300610 0 73504768 624790525


237629528 3251325000 0 3013695472 25616411512






2


2


2


2


2


2







Acknowledgments


References













































Journal of












Volume 2014

Advances in









Geophysics
















2


2

e (Diaz et al 2011)









3 Results










Costs($US)





2




e haminus1


0100200300400500600700800900

DBH class


Biom

ass a

nd ca

rbon

stoc

k (h

aminus1)




4 Discussion





office(AWF-Arusha)



Villagesand

villagers

Total(US$)




4908 mdash 4146 9054







27986 2500 3600 3500 mdash mdash 14770 52356










10710233183 3398625586 1031294500 124590511 000 minus262079384





Year







5795842 79300610 0 73504768 624790525


237629528 3251325000 0 3013695472 25616411512






2


2


2


2


2


2







Acknowledgments


References













































Journal of












Volume 2014

Advances in









Geophysics




















Costs($US)





2




e haminus1


0100200300400500600700800900

DBH class


Biom

ass a

nd ca

rbon

stoc

k (h

aminus1)




4 Discussion





office(AWF-Arusha)



Villagesand

villagers

Total(US$)




4908 mdash 4146 9054







27986 2500 3600 3500 mdash mdash 14770 52356










10710233183 3398625586 1031294500 124590511 000 minus262079384





Year







5795842 79300610 0 73504768 624790525


237629528 3251325000 0 3013695472 25616411512






2


2


2


2


2


2







Acknowledgments


References













































Journal of












Volume 2014

Advances in









Geophysics

















office(AWF-Arusha)



Villagesand

villagers

Total(US$)




4908 mdash 4146 9054







27986 2500 3600 3500 mdash mdash 14770 52356










10710233183 3398625586 1031294500 124590511 000 minus262079384





Year







5795842 79300610 0 73504768 624790525


237629528 3251325000 0 3013695472 25616411512






2


2


2


2


2


2







Acknowledgments


References













































Journal of












Volume 2014

Advances in









Geophysics


















10710233183 3398625586 1031294500 124590511 000 minus262079384





Year







5795842 79300610 0 73504768 624790525


237629528 3251325000 0 3013695472 25616411512






2


2


2


2


2


2







Acknowledgments


References













































Journal of












Volume 2014

Advances in









Geophysics
















Year







5795842 79300610 0 73504768 624790525


237629528 3251325000 0 3013695472 25616411512






2


2


2


2


2


2







Acknowledgments


References













































Journal of












Volume 2014

Advances in









Geophysics


















2


2


2


2


2


2







Acknowledgments


References













































Journal of












Volume 2014

Advances in









Geophysics



















































Journal of












Volume 2014

Advances in









Geophysics














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