Countries considering participating in a REDD+ mechanism need information on what it would cost them to reduce emissions from deforestation and forest degradation. This 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 structured questionnaires, focus group discussions, and forest inventory, respectively. Results show that the community participated in managing the forest by undertaking a range of activities such as tree planting, patrolling, and fire protection. The estimated total cost was USD 418,349.38 while the average cost was USD 79.06/ha. The average carbon stored was 19.75 tC ha−1, which is equivalent to 72.48 tCO2 ha−1. Costs incurred by managing the forest in relation to tCO2 stored were USD 1.0485 tCO2 e−1ha−1. The project was found to be economically feasible at 5%, 10%, 15%, and 20% discount rates with NPVs of USD 107,102,331.83, USD 33,986,255.86, USD 10,312,945, and USD 1,245,905.11, respectively. The internal rate of return was 21.21% which is much higher than the World Bank rate of 15.8% and the Tanzania rate of 14.8%. We therefore conclude that the decision to undertake this REDD+ project was worthwhile and should be favoured against the “do nothing” alternative.
Forests are the largest terrestrial reservoir for atmospheric carbon dioxide [
Globally, CO2 emissions from deforestation and other land use changes were
In Tanzania, forest deforestation and degradation rates are higher around 403,000 ha annually equivalent to 1.16% of the forest estate; hence the country is an important source of greenhouse gases (GHGs) emissions [
In Tanzania there are eight (8) REDD+ pilot projects being implemented in different ecosystems by nongovernmental organizations (NGOs) in collaboration with central, local government, academic institutions, and private sectors in implementing the projects [
Angelsen et al. [
This study was delimited in identifying and estimating transaction costs associated with establishment and implementing of advancing REDD+ in Kolo Hill pilot project. Understanding and minimizing the transaction costs are critical for reducing tropical forest losses [
This study was conducted in Mnenia forest a part of the ARKFor pilot project commonly known as Isabe and Salanga forest reserve and the surrounding village of Mnenia in Kondoa district (Figure
Map of Kondoa district showing the study area.
The sampling unit of the study was households. However in this study a household is defined as a group of people who eat in a common pot and usually share a dwelling house and may cultivate the same land (Poate and Daplyn, 1988 as cited by [
Forest inventory was conducted in Mnenia forest which is part of the Kolo Hill forest reserve. This part of the forest falls under five hills that are Singe, Chemchemi, Kwachondo, Rest-house, and Malawi which covers an area of 5,500 ha. However, the aim of selecting this portion of the project was based on limited time and resources to cover the whole project area of 18000 ha during forest inventory. The information obtained from the forest was extrapolated to cover the whole area due to the fact that the ARKFor project covers the same ecosystem. The Mnenia forest was under joint forest management strategy introduced by the project in the area; hence information on forest carbon stock in relation to the cost accrued by stakeholders assumed to be similar in other forest blocks of the project. Consequently in order to cover the whole area of the forest, systematic sampling design was adopted. The number of sample plots was determined using the following formula:
A cross-sectional design was employed in this study. However, the design allows collection of information at one point in time [
There was one category of data collected during the research as the secondary information. This information was on cost categories in socioeconomic data. However secondary data included other research findings and experience from different case studies related to the transaction cost analysis and carbon stock estimation. Hence data on transaction cost category were collected from pilot project coordinating office in Kondoa and AWF headquarter in Arusha by using existing annual reports and relevant records for two years (January, 2010 to December, 2011). Further, data were obtained from different publications, journals, and visiting websites to form an overview and identify information gaps.
Data from the questionnaires was analysed using the SPSS computer program. The data that were analysed were household characteristics such as age, sex, and occupation of the respondents. The collected data was first coded into meaningful computer language to assist in the analysis. Hence, the analysis which included the determination of descriptive statistics (such as central tendency and dispersion of responses) was summarised and presented as percentage, means, and frequency tables. Data on routine and nonroutine activities of the local community were listed, coded, and analysed through multiple response domain and presented in frequency tables. In addition to that, data on cost (resources) from the local level and reports for ARKFor project were listed, coded, and analysed using Microsoft Excel spreadsheet to generate information on the total cost accrued by the local community and an NGO (AWF). It was assumed that paying per day for local community was equivalent to $3.3 when an exchange rate of $1 was equal to 1500Tsh that depends on the prevailing average farm labours in the study site.
Data collected from the forest was analysed using the Microsoft Excel spreadsheet so as to obtain above ground carbon stock in terms of tons of biomass and carbon per hectare. A locally available allometric equation developed by Chamsahama et al. [
CBA is the most widely used approach in project appraising and it was the one used in Mnenia forest project a part of the ARKFor pilot project. The aim of doing CBA in this study was to determine whether managing Mnenia forest was economically profitable by using Net Present Value (NPV) as a decision criterion. The formula we used for NPV was:
The objective of this analysis was to find out by what proportion the benefits would have to be reduced before the NPV could fall to zero and eventually becomes negative. Uncertainties associated with the project that could contribute to the reduction of the benefits included change in wage rate and administrative costs; change in the market price of carbon; shortage of labour; unwilling of the community to participate in the project; increase in factors influencing deforestation in the project area,
where the sequestration rate of the forest does not conform with the stipulated assumptions identified for this project.
The findings showed that various activities were identified to be conducted in the area. It showed that the community attended various activities in managing the forest (Table
Activities and their associated cost incurred by community in managing the ARKFor pilot project.
Routine and nonroutine activities | Estimated days and costs | ||||
---|---|---|---|---|---|
Frequency | Per day |
Number of days per month | Number of days per year | Costs | |
Routine activities | |||||
Tree planting | 29 | 3.33* | — | 1 | 96.57 |
Forest patrolling | 29 | 3.33* | 15 | 180 | 17,382.60 |
Forest boundary making | 25 | 3.33* | — | 1 | 83.25 |
Land use planning | 21 | 3.33* | — | 5 | 349.65 |
Attending seminar | 25 | 3.33* | — | 5 | 416.25 |
Selected as a focal farmer | 12 | 3.33* | 5 | 60 | 2397.60 |
Making server stoves | 12 | 3.33* | 5 | 60 | 2397.60 |
Conducting beekeeping activities | 14 | 3.33* | 15 | 210 | 9790.20 |
Nonroutine activities | |||||
Attending the village meeting | 31 | 3.33* | — | 2 | 206.46 |
Forest fire protection | 26 | 3.33* | — | 15 | 1298.70 |
Demarcating forest boundary | 22 | 3.33* | — | 1 | 73.26 |
Preventing keeping and livestock in the forest | 25 | 3.33* | — | 15 | 1248.75 |
Total |
|
Source: field data.
*Pay per day was equivalent to $3.3 when an exchange rate of $1 was equal to 1500Tsh that depends on the prevailing average farm labours in the study site.
Results showed that the costs were incurred by ARKFor in managing the forest divided into two categories that were set up and running costs. Setting cost was divided into two categories that were costs according to function and actors in the project that was estimated to be US$407,391 (Table
Setting up and running costs of the ARKFor pilot project from 2010 to 2011.
Cost centers | NGO main office |
NGO local office (AWF-Kondoa) | Partner | Consultancy | Monitoring body | Verifications | Villages and villagers | Total |
---|---|---|---|---|---|---|---|---|
Setting up costs | ||||||||
Negotiating contracts, planning, decision making, administration, and finances | 150,107 | — | 192,132 | — | — | — | — | 342,239 |
Developing institutions | 1,625 | 2383 | 125 | — | — | 4,133 | ||
Information programs and payment programs/communication | 4908 | — | 4146 | 9,054 | ||||
MRV systems | 48,514 | — | 3451 | — | — | 51,965 | ||
Personnel cost | 12,290 | 42,255 | — | — | 66 | — | — | 54,611 |
Office costs | — | 20,832 | — | — | — | — | — | 20,832 |
Capital assets | — | 74,511 | — | — | — | — | — | 74,511 |
|
||||||||
Running costs | ||||||||
Negotiating contracts, planning, decision making, administration, and finances | 110,225 | — | — | 64,638 | — | — | — | 174,863 |
Developing institutions | 223,313 | — | $2314 | 53,885 | — | — | 46,274 | 325,786 |
Information programs and payment programs/communication | 788 | — | — | 38,582 | — | — | — | 39,370 |
MRV systems | 185 | — | — | 11,201 | — | — | — | 11,386 |
Personnel cost | 26,388 | 58,183 | — | — | 5310 | — | — | 89,881 |
Office costs, include consumables, travelling costs and miscellaneous | 27,986 | 2500 | 3600 | 3500 | — | — | 14,770 | 52,356 |
Capital assets | — | 1426 | — | — | — | — | — | 1,426 |
Total |
|
Source: ARKFor pilot project annual report from 2010 to 2011.
In addition to that the actual total cost accrued by the project in setting up and running the ARKFor project in Kondoa from January, 2010 to December, 2011, was US$1,252,413 spent by AWF in managing the forest covers of the whole area of the ARKFor pilot project estimated to be 18,000 ha. Meanwhile as the Mnenia forest (part of the ARKFor project) covers estimated areas of 5500 ha then the cost estimated to manage the forest was $382,681.75. However, the findings (Table
The results showed that the estimated forest carbon stock of the forest was 19.75 tC ha−1. Findings showed that distribution of forest parameters (biomass and carbon) by DBH class portrays a normal “
Above ground biomass and carbon stock distribution in Mnenia forests, Kolo Hills, Kondoa.
Further we found that the average tone of carbon dioxide (tCO2) stored in the forest was 72.48 tCO2e ha−1.
The results (Table
NPV at various discount rates of 5%, 10%, 15%, 20%, 21.21231441%, and 25%.
Year | Costs | Benefits | Net benefit | NPV | |||||
---|---|---|---|---|---|---|---|---|---|
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1 | 3543152.72 | 0 | −3543152.72 | −3374431.16 | −3221047.92 | −3081002.36 | −2952627.26 | −2923096.33 | −2834522.17 |
2 | 3593028.46 | 0 | −3593028.46 | −3258982.73 | −2969445.01 | −2716845.71 | −2495158.65 | −2445497.20 | −2299538.21 |
3 | 3420371.10 | 0 | −3420371.10 | −2954645.16 | −2569775.43 | −2248949.52 | −1979381.42 | −1920582.63 | −1751230.00 |
4 | 3422613.50 | 0 | −3422613.50 | −2815792.59 | −2337691.07 | −1956890.38 | −1650565.92 | −1585516.93 | −1401902.49 |
5 | 3420373.74 | 0 | −3420373.74 | −2679952.32 | −2123782.99 | −1700530.25 | −1374571.49 | −1307193.39 | −1120788.07 |
6 | 3402751.78 | 0 | −3402751.78 | −2539185.77 | −1920764.67 | −1471103.50 | −1139574.69 | −1072876.68 | −892010.96 |
7 | 44800.00 | 5825985.00 | 5781185.00 | 4108580.25 | 2966662.02 | 2173361.58 | 1613422.63 | 1503798.55 | 1212402.37 |
8 | 42300.00 | 6274785.00 | 6232485.00 | 4218391.17 | 2907500.25 | 2037410.40 | 1449476.82 | 1337479.99 | 1045637.47 |
9 | 36800.00 | 6646447.50 | 6609647.50 | 4260637.71 | 2803135.76 | 1878874.34 | 1280993.97 | 1170193.30 | 887131.87 |
10 | 36800.00 | 7018110.00 | 6981310.00 | 4285918.74 | 2691597.22 | 1725673.06 | 1127520.54 | 1019693.11 | 749612.45 |
11 | 36800.00 | 7389772.50 | 7352972.50 | 4299130.73 | 2577172.00 | 1580471.61 | 989621.76 | 886030.68 | 631615.53 |
12 | 36800.00 | 7761435.00 | 7724635.00 | 4301365.81 | 2461306.77 | 1443789.51 | 866369.22 | 767921.88 | 530832.88 |
13 | 36800.00 | 8133097.50 | 8096297.50 | 4293639.43 | 2345208.99 | 1315874.69 | 756711.37 | 664016.38 | 445098.66 |
14 | 36800.00 | 8469697.50 | 8432897.50 | 4259186.28 | 2220645.48 | 1191810.09 | 656809.43 | 570587.71 | 370882.75 |
15 | 36800.00 | 8876422.50 | 8839622.50 | 4252009.56 | 2116135.35 | 1086340.86 | 573739.87 | 493437.97 | 311016.57 |
16 | 36800.00 | 9248085.00 | 9211285.00 | 4219795.79 | 2004643.99 | 984361.85 | 498219.00 | 424201.62 | 259274.62 |
17 | 36800.00 | 9619747.50 | 9582947.50 | 4181008.25 | 1895935.08 | 890503.89 | 431934.53 | 364086.41 | 215788.79 |
18 | 36800.00 | 9991410.00 | 9954610.00 | 4136346.07 | 1790424.11 | 804383.44 | 373905.47 | 312020.31 | 179326.31 |
19 | 36800.00 | 10363072.50 | 10326272.50 | 4086456.68 | 1688428.07 | 725578.85 | 323221.25 | 267027.17 | 148817.27 |
20 | 36800.00 | 10734735.00 | 10697935.00 | 4031939.19 | 1590179.87 | 653646.81 | 279045.51 | 228225.98 | 123338.79 |
21 | 36800.00 | 11106397.50 | 11069597.50 | 3973347.50 | 1495841.03 | 588135.21 | 240616.64 | 194827.48 | 102099.02 |
22 | 36800.00 | 11478060.00 | 11441260.00 | 3911193.26 | 1405512.72 | 528592.95 | 207246.14 | 166129.02 | 84421.60 |
23 | 36800.00 | 11849722.50 | 11812922.50 | 3845948.60 | 1319245.42 | 474577.37 | 178315.34 | 141508.41 | 69731.19 |
24 | 36800.00 | 12221385.00 | 12184585.00 | 3778048.81 | 1237047.28 | 425659.74 | 153271.30 | 120417.30 | 57540.08 |
25 | 36800.00 | 12593047.50 | 12556247.50 | 3707894.69 | 1158891.40 | 381429.13 | 131622.07 | 102374.38 | 47436.16 |
26 | 36800.00 | 12957697.50 | 12920897.50 | 3633882.71 | 1084133.76 | 341309.86 | 112870.46 | 86911.52 | 39051.02 |
27 | 36800.00 | 13336372.50 | 13299572.50 | 3562268.14 | 1014460.59 | 305489.29 | 96815.31 | 73803.27 | 32156.39 |
28 | 35000.00 | 13708035.00 | 13673035.00 | 3487904.23 | 948134.04 | 273102.32 | 82944.97 | 62597.37 | 26447.50 |
29 | 35000.00 | 14079697.50 | 14044697.50 | 3412107.59 | 885369.42 | 243935.51 | 70999.66 | 53046.51 | 21733.12 |
30 | 35000.00 | 14451360.00 | 14416360.00 | 3335620.60 | 826180.74 | 217731.07 | 60732.09 | 44921.40 | 17846.59 |
31 | 35000.00 | 14823022.50 | 14788022.50 | 3258680.87 | 770436.52 | 194212.44 | 51914.83 | 38015.53 | 14645.35 |
32 | 35000.00 | 15194685.00 | 15159685.00 | 3181504.98 | 717999.68 | 173124.80 | 44349.66 | 32150.99 | 12010.74 |
33 | 35000.00 | 15566347.50 | 15531347.50 | 3104289.87 | 668729.57 | 154234.10 | 37864.13 | 27174.81 | 9844.16 |
34 | 35000.00 | 15938010.00 | 15903010.00 | 3027214.28 | 622483.78 | 137326.00 | 32308.51 | 22955.67 | 8063.78 |
35 | 35000.00 | 16309672.50 | 16274672.50 | 2950440.02 | 579119.62 | 122204.68 | 27552.98 | 19381.00 | 6601.79 |
36 | 35000.00 | 16681335.00 | 16646335.00 | 2874113.16 | 538495.36 | 108691.70 | 23485.17 | 16354.45 | 5402.04 |
37 | 35000.00 | 17052997.50 | 17017997.50 | 2798365.19 | 500471.22 | 96624.75 | 20007.94 | 13793.64 | 4418.12 |
38 | 35000.00 | 17424660.00 | 17389660.00 | 2723314.05 | 464910.18 | 85856.50 | 17037.42 | 11628.26 | 3611.69 |
39 | 35000.00 | 17796322.50 | 17761322.50 | 2649065.13 | 431678.66 | 76253.46 | 14501.29 | 9798.34 | 2951.11 |
40 | 35000.00 | 18167985.00 | 18132985.00 | 2575712.23 | 400647.00 | 67694.86 | 12337.28 | 8252.77 | 2410.29 |
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Estimated amount of GHG abated (CER/ERU).
Year | Estimation of baseline net GHG removals by sinks | Estimation of actual net GHG removals by sinks |
Estimation of |
Estimation of net anthropogenic GHG removals by sinks | Estimation of net benefit accrued by trading carbon |
---|---|---|---|---|---|
(tonnes of CO2e) | (tonnes of CO2e) | (tonnes of CO2e) | (USD) | ||
0 | 396,806.26 | 0 | 0 | −396,806.26 | −3,372,853.18 |
1 | 397,723.13 | 0 | 0 | −397,723.13 | −3,380,646.59 |
2 | 396,808.36 | 0 | 0 | −396,808.36 | −3,372,871.10 |
3 | 395,895.71 | 0 | 0 | −395,895.71 | −3,365,113.50 |
4 | 394,985.15 | 0 | 0 | −394,985.15 | −3,357,373.74 |
5 | 394,076.68 | 0 | 0 | −394,076.68 | −3,349,651.78 |
6 | 0 | 427,790.00 | 0 | 427,790.00 | 3,636,215.00 |
7 | 0 | 456,940.00 | 0 | 456,940.00 | 3,883,990.00 |
8 | 0 | 492,140.00 | 0 | 492,140.00 | 4,183,190.00 |
9 | 0 | 521,290.00 | 0 | 521,290.00 | 4,430,965.00 |
10 | 0 | 550,440.00 | 0 | 550,440.00 | 4,678,740.00 |
11 | 0 | 579,590.00 | 0 | 579,590.00 | 4,926,515.00 |
12 | 0 | 608,740.00 | 0 | 608,740.00 | 5,174,290.00 |
13 | 0 | 637,890.00 | 0 | 637,890.00 | 5,422,065.00 |
14 | 0 | 664,290.00 | 0 | 664,290.00 | 5,646,465.00 |
15 | 0 | 696,190.00 | 0 | 696,190.00 | 5,917,615.00 |
16 | 0 | 725,340.00 | 0 | 725,340.00 | 6,165,390.00 |
17 | 0 | 754,490.00 | 0 | 754,490.00 | 6,413,165.00 |
18 | 0 | 783,640.00 | 0 | 783,640.00 | 6,660,940.00 |
19 | 0 | 812,790.00 | 0 | 812,790.00 | 6,908,715.00 |
20 | 0 | 841,940.00 | 0 | 841,940.00 | 7,156,490.00 |
21 | 0 | 871,090.00 | 0 | 871,090.00 | 7,404,265.00 |
22 | 0 | 900,240.00 | 0 | 900,240.00 | 7,652,040.00 |
23 | 0 | 929,390.00 | 0 | 929,390.00 | 7,899,815.00 |
24 | 0 | 958,540.00 | 0 | 958,540.00 | 8,147,590.00 |
25 | 0 | 987,690.00 | 0 | 987,690.00 | 8,395,365.00 |
26 | 0 | 1,016,290.00 | 0 | 1,016,290.00 | 8,638,465.00 |
27 | 0 | 1,045,990.00 | 0 | 1,045,990.00 | 8,890,915.00 |
28 | 0 | 1,075,140.00 | 0 | 1,075,140.00 | 9,138,690.00 |
29 | 0 | 1,104,290.00 | 0 | 1,104,290.00 | 9,386,465.00 |
30 | 0 | 1,133,440.00 | 0 | 1,133,440.00 | 9,634,240.00 |
31 | 0 | 1,162,590.00 | 0 | 1,162,590.00 | 9,882,015.00 |
32 | 0 | 1,191,740.00 | 0 | 1,191,740.00 | 10,129,790.00 |
33 | 0 | 1,220,890.00 | 0 | 1,220,890.00 | 10,377,565.00 |
34 | 0 | 1,250,040.00 | 0 | 1,250,040.00 | 10,625,340.00 |
35 | 0 | 1,279,190.00 | 0 | 1,279,190.00 | 10,873,115.00 |
36 | 0 | 1,308,340.00 | 0 | 1,308,340.00 | 11,120,890.00 |
37 | 0 | 1,337,490.00 | 0 | 1,337,490.00 | 11,368,665.00 |
38 | 0 | 1,366,640.00 | 0 | 1,366,640.00 | 11,616,440.00 |
39 | 0 | 1,395,790.00 | 0 | 1,395,790.00 | 11,864,215.00 |
40 | 0 | 1,424,940.00 | 0 | 1,424,940.00 | 12,111,990.00 |
Average over |
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Total for |
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NB: baseline deforestation rate was 0.46%, sequestration rate was 5.3 tCO2/ha/year, and price per carbon was 8.5 USD/tCO2e.
The forest patrolling was observed to be the main activities in the area performed by community adjacent of the forest such as charcoal making and livestock keeping prevention. This could be a result of the amount paid to local communities in attending those activities or they have realised the importance of the surrounding forest in their livelihood. Kugonza et al. [
In addition to that, the community adjacent of the forest was observed to devote much of its time in forest patrolling. This could be possibly due to the presence of various human activities like crop cultivation in the forest as shifting cultivation and cut down of the trees for charcoal making, buildings, and fire woods; hence patrolling activities accrue much time or costs than other activities in the area. In addition to that it was learned that in the village there were forest guards trained by AWF and VNRC members who were involved in the forest patrolling activity. However, it was noted that the established institution in community faces a range of challenges like lack of forest patrolling equipments but devoted much of their time in the managing the forests. This is because Mnenia forest was the source of water for irrigation and domestic purposes, and other forest products such as honey and fuel wood obtained from that forest. Meshack et al., [
The cost of negotiating, planning, decision making, and administration arises due to time and resources spent to wrap up the negotiations, planning, communication, and travel costs. In addition to that, as the project was in the initial stage this tends to incur much cost possibly because as the foundation of the project lay properly then the project could be thriving. Dudek and Wiener [
The developed institution (such as the established JFM in the village, plan, training communities, and register JFM and conducting training to communities) accrued high cost in managing the forest. This was possibly due to the fact that more attention was given to each village adjacent of the forest involved in managing the ARKFor pilot project which has a credible management institution that will oversee all the activity in the community. It was learned that in running the developed institution in the village, training of local communities was undertaken to ensure its sustainability. The high cost incurred in developing an institution, for example, in Tanzania, is involved in establishing a joint management plan and development agreement between local communities surrounding the forest. Further, it requires much time and resources in completing. Bond et al. [
Despite differences in methodologies and environmental conditions other Miombo woodlands studies have reported similar carbon (C) stock and cost per tonne of CO2 to those obtained in this study. Shirima et al. [
According to the stated assumptions, the project was found to be economically feasible at 5%, 10%, 15%, and 20% discount rates with NPVs of about USD. 107,102,331.83, US$ 33,986,255.86, US$ 10,312,945.00, and USD. 1,245,905.11, respectively. The internal rate of return (IRR) was found to be about 21.21% which is much higher than the World Bank rate of 15.8% [
The authors declare that there is no conflict of interests regarding the publication of this paper.
This paper has been produced under a research project “REDD+ Architecture in Tanzania” funded by the Norwegian Government through a Programme on Climate Change Mitigation and Adaptation for Tanzania based at Sokoine University of Agriculture. The findings and views expressed in this document are the sole responsibility of the authors and do not necessarily represent the views of the institutions involved in this project or the funder. The authors would like to express their sincere acknowledgement to the Royal Norwegian Government for supporting this work. REDD+ Pilot Project under the African Wildlife Foundation, Leaders of the Local Government in Kondoa district, and Mnenia village council are highly acknowledged. Lastly the communities in Mnenia village are acknowledged for agreeing to participate in this research.