International Journal of the Commons Vol. 3, no 1 May 2009, pp. 108–130 Publisher: Igitur, Utrecht Publishing & Archiving Services for IASC URL:http://www.thecommonsjournal.org URN:NBN:NL:UI:10-1-100053 Copyright: content is licensed under a Creative Commons Attribution 3.0 License ISSN:1875-0281 Carbon finance options for smallholders’ agroforestry in Indonesia Christina Seeberg-Elverfeldt Climate Change and Bioenergy Unit (NRCB) FAO, Viale delle Terme di Caracalla 00153 Rome, Italy; [email protected] Stefan Schwarze Georg-August Universität Göttingen Department of Agricultural Economics and Rural Development Waldweg 26, 37073 Göttingen, Germany Manfred Zeller University of Hohenheim Institute of Agricultural Economics and Social Sciences in the Tropics and Subtropics Schloß, Ostflügel (490a), 70599 Stuttgart, Germany Abstract: Up to 25 percent of all anthropogenic greenhouse gas emissions are caused by deforestation, and Indonesia is the third largest greenhouse gas emitter worldwide due to land use change and deforestation. On the island of Sulawesi in the vicinity of the Lore Lindu National Park (LLNP), many smallholders contribute to conversion processes at the forest margin as a result of their agricultural practices. Specifically the area dedicated to cacao plantations has increased from zero (1979) to nearly 18,000 hectares (2001). Some of these plots have been established inside the 220,000 hectares of the LLNP. An intensification process is observed with a consequent reduction of the shade tree density. This study assesses which impact carbon sequestration payments for forest management systems have on the prevailing land-use systems. Additionally, the level of incentives is determined which motivates farmers to desist from further deforestation and land use intensification activities. Household behaviour and Carbon finance options for smallholders’ agroforestry in Indonesia 109 resource allocation is analysed with a comparative static linear programming model. As these models are used as a tool for policy analysis, the output can indicate the adjustments in resource allocation and land use shifts when introducing compensation payments. The data were collected in a household survey in six villages around the LLNP. Four household categories are identified according to their dominant agroforestry systems. These range from low intensity management with a high degree of shading to highly intensified systems with no shade cover. At the plot level, the payments required for inducing the adoption of more sustainable land use practices are the highest for the full shade cacao agroforestry system, but with low carbon prices of €5 tCO e–1 these constitute 5 percent of the 2 cacao gross margin. Focusing on the household level, however, an increase up to 18 percent of the total gross margin can be realised. Furthermore, for differentiated carbon prices up to €32 tCO e–1 the majority of the households have an incentive 2 to adopt the more sustainable shade intensive agroforestry system. Additionally, the results show that the deforestation activities of most households could be stopped with current carbon prices. Keywords: Avoided deforestation, cacao, carbon sequestration, economic incentives, linear programming, Lore Lindu National Park, payments for environmental services Acknowledgements: We would like to thank Prof. Stephan v. Cramon- Taubadel and three anonymous reviewers who provided constructive feedback and comments on an earlier draft of this paper. Funding for the research was provided by the University of Göttingen and the German Research Foundation (DFG) through the “Stability of Rainforest Margins in Indonesia” (STORMA) project. 1. Introduction The net global change in forest area has been slowing down from –8.9 million hectares per year in the 1990s to –7.3 million hectares during the last years due to plantations and restoration of degraded land, especially in Europe, North America and East Asia. However, primary forests are still lost or modified at a rate of six million hectares per year because of selective logging or deforestation, and there is no indication that the rate is slowing (FAO 2006). Deforestation in turn plays an important role in the global warming process, as it accounts for up to 25 percent of global greenhouse gas emissions (IPCC 2007). Indonesia has the second highest annual net loss in forest area worldwide. Between 2000 and 2005 two percent of its remaining forest area was lost every year (FAO 2006). Additionally, it is among the top three greenhouse gas emitters, primarily because of deforestation, peatland degradation and forest fires. 110 Christina Seeberg-Elverfeldt et al. Deforestation is a difficult issue to tackle on a national scale, as its drivers are complex. Five broad categories can be determined as its underlying driving forces. These are demographic, economic, technological, policy, and institutional and cultural factors. In general, at the proximate level infrastructure extension, agricultural expansion, as well as wood extraction are the main driving forces for tropical deforestation and land use change (Geist et al. 2002). The majority of deforestation incidences are connected to agricultural expansion. The incentive for forest conversion for many smallholders can be attributed to the fact that other land uses such as permanent cropping, cattle ranching, shifting cultivation, and colonization agriculture yield higher revenues than forestry. Through their traditional land use practices, smallholders often contribute to deforestation processes. Hence, local emissions of carbon are affected and carbon stocks and associated fluxes are often negatively influenced. In the Kyoto Protocol, forestry activities, or so-called carbon sink projects1 are recognized as an important means of mitigating greenhouse gas emissions, since carbon dioxide is removed through photosynthesis. Thus, forestry projects which result in additional greenhouse gases being actively sequestered from the atmosphere and stored in sinks can generate certified emission reductions (CER).2 In order to create a homogenous tradable commodity, emission reductions of any greenhouse gas are traded in form of tonnes of carbon dioxide equivalent (CO e) which means that the climate change 2 potential of each greenhouse gas is expressed as an equivalent of the climate change potential of CO (UNFCCC 1997). Under the current rules established for 2 the Clean Development Mechanism (CDM),3 only afforestation and reforestation activities are considered eligible. However, in the on-going climate discussions, as during the UNFCCC Climate Conference in Bali in 2007, other sink activities, such as reducing emissions from deforestation or “compensated reduction” are high on the political agenda. This discussion was first initiated by the Rainforest Coalition, a group of developing nations with rainforest who formally offered voluntary carbon emission reductions by conserving forests in exchange for access to international markets for emissions trading. Especially the forest-rich countries, such as Brazil and Indonesia, are pushing for a financial acknowledgement of forest conservation. On the island of Sulawesi in Indonesia the forest margin of the Lore Lindu National Park (LLNP), which covers 220,000 hectares, has been facing 1 The term carbon sinks is applied to pools or reservoirs, such as forests, oceans and soils, which absorb carbon, and for which carbon storage exceeds carbon release. The process of capturing carbon from the atmosphere and storing it in vegetation biomass is referred to as sequestration. 2 The terms certificates, carbon credits and CER are used interchangeably. One credit is the equiva- lent of one tonne of CO emissions. 2 3 For fulfilling the reduction obligations, the Kyoto Protocol offers three flexible mechanisms, namely Emissions Trading, Joint Implementation and the CDM. The CDM provides for Annex I Par- ties (most OECD countries and countries in transition) to implement projects that reduce emissions in non-Annex I countries in return for CER, and assist the host Parties in achieving sustainable develop- ment. The CERs can be used by Annex I countries to help meet their emission targets (FAO 2004). Carbon finance options for smallholders’ agroforestry in Indonesia 111 encroachment and consequently deforestation. The main activities to be observed are an expansion of the area dedicated to agricultural activities by 20 percent during the last two decades, the tripling of the perennial crop plantations area and expansion into former forest areas, as well as selective and clear-cut logging. A village survey in 2001 revealed that 70 percent of the villages bordering the LLNP have agricultural land inside the park (Maertens 2003). A satellite image analysis detected a mean annual deforestation rate of 0.3 percent in the research region between 1983 and 2002 (Erasmi and Priess 2007). However, cacao plantations under shade trees cannot be detected by optical satellite instruments, thus the encroachment process at the forest margin is not fully reflected by this figure. In the vicinity of the LLNP a great spatial heterogeneity of agricultural production is apparent. In general, human activities are much more concentrated in the northern and western part of the park than in the south. In the north-east the closed forest decreased by 35 percent between 2001 and 2004 due to logging, whereas the area covered by cacao plantations increased by 11 percent (Rohwer 2006). In addition, an intensification process among the cacao agroforestry systems (AFS), whereby farmers gradually reduce the shade tree cover, can be observed. The focus of the present research is therefore twofold. We assess the impact of payments for carbon sequestration activities on the land use systems of smallholders in the regions bordering the LLNP in Indonesia, and whether such payments can provide an incentive for the adoption of more sustainable and shade tree covered land use practices and contribute to the conservation of the rainforest. 2. Framework The research is motivated by the need to understand which level of incentives is required to stimulate the farmers to desist from further deforestation and land use intensification activities. Internationally the awareness for the requirement to develop and support payment mechanisms and incentives for the provision and preservation of environmental services is growing. Initiatives and projects are promoted where local actors are given payments in return for switching to more sustainable land- use practices and ecosystem protection. They usually imply the payments to be made by the beneficiaries of the environmental services. These payments for environmental services (PES) policies have been defined by Wunder (2007), as voluntary, conditional agreements between at least one seller and one buyer over a well-defined environmental service – or a land use presumed to produce that service. Carbon sequestration is a typical positive externality, as it is an unplanned side effect of sustainable forest management and conservation in a specific area, and the benefits are not confined locally, but accrue to all of humanity. PES, being market-based mechanisms, can render forestry to be a competitive land use and farmers and loggers might decide to change their land use practices to retain or replant trees if they receive sufficient remuneration. In the case of deforestation avoidance, farmers can receive a compensation payment as an incentive not to cut down the forest and use the timber or put the land to agricultural 112 Christina Seeberg-Elverfeldt et al. use. This is in line with the “compensated reduction” proposal, according to which countries electing to reduce their national emissions from deforestation would be authorized to issue carbon certificates which could be sold to governments or private investors to fulfil their emission targets (Santilli et al. 2005). In the region around the LLNP four cacao AFS can be distinguished according to the species type of shade trees and their canopy cover proportion, as well as the management intensity: AFS I exhibits a high degree of shading with natural forest trees with a canopy cover above 85 percent and they are managed with very few agricultural inputs; AFS II is shaded by a diverse spectrum of planted trees and naturally grown after clear-cutting, it has a shade cover of approximately 66–85 percent; AFS III exhibits a low density of a shade tree layer, which is dominated by the non-indigenous leguminous trees Gliricida sepium and Erythrina subumbrans, with a canopy cover between 36–65 percent; finally, the AFS IV has very few to no shade trees (5–35 percent shade canopy cover) and is intensively managed. The forest and the cacao agroforestry systems provide a variety of goods and services such as non-timber forest products, watershed and pollination services (Priess et al. 2007). The gross margins of cacao consistently increase along the cacao AFS gradient from I towards IV. There seems to be a trade-off situation between an intensification of the cacao cultivation with shade free plantations and higher economic returns and shade-grown, low intensity management cacao with lower returns and biodiversity conservation. Even though the cacao grown in full sun has higher mean yields and obtains substantially higher gross margin values in comparison with shade grown cacao, in the long run the intensification is likely to be ecologically unsustainable. Results from studies show that tree crops which are grown in shaded systems tend to maintain productivity in the long run and are less susceptible to insect and disease losses than full-sun monocultures (Belsky and Siebert 2002; Young 1989). Reducing shade often implies an increase in yields, but increases physiological stress, the susceptibility to pests and diseases and thus, the amount of inputs required (Y. Clough, personal communication). Previous research in the same region indi- cates that shaded AFSs provide high biodiversity values and habitat for the native fauna, whereas completely shade free systems harbour significantly lower species richness (Schulze et al. 2004). Similarly, studies with other perennial crops indicate that at the transition from shaded agroforestry systems to intensively managed shade free monocultures, a major loss of overall biodiversity occurs (Perfecto et al. 1996). The species-richness of plants, animals and ecosystem functioning of the AFS was assessed in a multi-disciplinary study by (Steffan-Dewenter et al. 2007). They did not discover a linear gradient of biodiversity and ecosystem functioning loss from the first to the third AFS, but deduced that the complete reduction of shade trees as a consequence of the land use intensification is an ecologically unsustainable path and results in disproportionate ecological losses in the long run. Unfortunately, the intensification process already takes place in the region. A willingness to pay study, which suggests a higher preference for low shade AFS among the local farmers, supports these results (Glenk et al. 2006). Thus, Carbon finance options for smallholders’ agroforestry in Indonesia 113 to prevent an intensification of the AFS to monocultures in the region, economic incentives are required. These could be price premiums, as they are already available for a long time for fair trade and organic coffee. Recently premiums have been introduced for fair trade and organic cocoa. The fair trade premium for standard quality cocoa is €100 per tonne. Also for organic cocoa producers receive a higher price which ranges between €75 to 225 per tonne (ICCO 2007). Alternatives could also be price premiums offered through carbon certificates to provide an incentive for the more shade grown, biodiversity rich and sustainable cacao AFS and slow down the intensification process. An important phenomenon in the region is that many Bugi households settled in the 1990s from South Sulawesi and Poso into the research area and started to buy land from the local Kaili households. In many cases the local ethnic households had originally obtained this land by clearing primary forest on the border of the National Park (Faust et al. 2003). They consider themselves to be the owners of the village territory and do not see the necessity to buy land, but in turn realise the opportunity to generate additional income by selling parts of their land. This provokes a vicious cycle, because after a while the local households spend the income gained through the land sales on ceremonial purposes or status symbols. In due course, when they are short of money again, they convert further forest to satisfy their financial needs. Incentive-based schemes have become very common during the last decade, and throughout the world hundreds of new and very elaborate PES initiatives have been implemented. For example, in Costa Rica the National Fund for Forest Financing operates a scheme which bundles funding from various sources, including international donors, carbon buyers, the Costa Rican public through a national fuel tax, and local industries interested in water quality and flows. Consequently, land users can receive payments for specified land uses, such as new plantations, sustainable logging, and conservation of natural forests. In Mexico, a payment for a hydrological environmental services programme is carried out. In Asia one of the most prominent programmes is RUPES (Rewarding the Upland Poor for Ecosystem Services). In one of these projects in Indonesia farmers are assisted to obtain conditional land tenure in exchange for adopting mixed agro- forestry systems that increase erosion control and biodiversity (Jack et al. 2007). For avoided deforestation projects the main sources of funding are from voluntary sources, but also the World Bank provides through its newly established Forest Carbon Partnership Facility additional financial resources. A great variety of studies have been conducted employing different methods and considering the supply and/or the demand side aspects to determine the value of environmental services as done by Antle et al. (2007), Olschweski and Benítez (2005) and Pattanayak (2004). The challenge, however, remains to find the specific price at which the marginal cost of the payment equals the marginal benefit of the behaviour that it stimulates. The prices for carbon certificates fluctuate widely, depending on the type of certificate, whether it is an emission 114 Christina Seeberg-Elverfeldt et al. reduction generated through a project-based activity, such as CER, or allowance based transactions, allocated under existing cap-and-trade regimes, such as the EU allowances. Additionally, the voluntary greenhouse gas emission offset markets are evolving rapidly, especially in the United States. Looking at permanent CER, a wide variation of prices can be observed. In 2006 certificates were traded in a range between €5 up to €21.50 per tCO e, with an average of €10.90 (Capoor and 2 Ambrosi 2007). Accordingly, we investigate whether current carbon credit prices are sufficient on the one hand to induce farmers to adopt more sustainable land use practices and on the other hand to make them desist from further forest conversion activities. The purpose of this paper is to provide an insight into whether environmental service payment schemes could have an impact on land use changes, and specifically which level of incentives would be necessary for the currently demanded policies to reduce emissions from deforestation, and thus, contribute to the conservation of the rainforest. 3. Data and methods 3.1. Linear programming model We chose a comparative static linear programming model to analyse the behaviour of the households and their resource allocation. These models simulate the farmers’ reaction to interventions and the effect of technology changes on economic decisions about natural resource use management (Barbier and Bergeron 1999; Bertomeu et al. 2006; Mudhara et al. 2003). Linear programming has been used by several authors as a method for studying the impact of policy activities (Vosti et al. 2002), such as in this case carbon payments. As with all methods, there are some limitations, such as the assumption of certain values and preferences when specifying the objective function, the possibility of non-linearity and feedback between variables, as well as the dynamics of systems. While one has to be aware of these problems, for the purpose of this research linear programming has been considered an appropriate method. It is a useful technique to assess technology changes or adoption potentials ex ante, so that careful planning for new policies or strategies can be undertaken. As an input for the model, the gross margins for the main cropping activities paddy rice, upland rice, maize and cocoa were calculated. Additionally, forest conversion activities based on various economic- political-environmental parameters from the research region were included to portray the behaviour of the smallholders as realistically as possible. Given the objective function, the solution procedure maximises the total gross margin (TGM) of the farm by finding the optimal set of activities for the household type, under the respective restrictions such as farm size, suitability of the land for various crops, food security, the credit limit, family work force, and the seasonal peak requirement of labour for each activity. The credit limit is the maximum amount of credit that a household expects to be able to borrow from formal and Carbon finance options for smallholders’ agroforestry in Indonesia 115 informal sources (Diagne and Zeller 2001). The farm conditions are stable, thus time dimensions are not included in the model. In the research region most of the agroforestry plots contain trees of mixed age, therefore there is no clearly defined investment period and time of returns. Hence, the time lag between investment and returns has been ignored, as there are always some trees which can already be harvested whilst the others still mature. Furthermore, initial investment costs are very low and the additional labour in the first three unproductive years of the cacao tree cannot be clearly separated from other activities necessary for the already productive trees on the cacao plots. As the farmer has information about alternative production activities and input and output prices, risk does not need to be accounted for (Vosti et al. 2002). In another study in the same region which focused on smallholder cacao farmers’ technology adoption, application and optimisation, the same conditions apply and similar assumptions were used for the linear programming model (Taher 1996). In Appendix I the linear programming model for Household II is depicted.4 3.2. Farm household types The data on the existing agricultural production systems for the model were collected in a household survey in the surroundings of the LLNP in 2006. We categorised the households according to the dominant AFS among their cacao plots, and determined four corresponding household types (HH–HH ). A random I IV sample of 46 households in six villages was drawn from the total sample of 325 households in 13 villages from the research project. These had been randomly selected based on a stratified sampling method for a household survey in 2001 and 2004. For the specific sampling procedure see (Zeller et al. 2002). The survey at hand focused on general aspects of the household and farm characteristics, land resources and their use, agricultural production activities, and forest usage. The four household types have different resource endowments, such as land and labour availability and credit limit. The major characteristics are presented in Table 1 to indicate the differences between them. Thus, one can see that the household type I has the lowest credit limit and the least cultivated land. The main share of the land is dedicated to the cacao AFS I. Mainly the indigenous households own this plot type. Household types II and III have an increasing credit limit and most land available for cultivation, and they dedicate most of their land to AFS II and AFS II, respectively. In these household classes the share of migrants becomes more dominant. Household type IV, who is mainly non-indigenous, predominantly grows the intensively managed AFS IV. However, its credit limit is only the second highest and its land availability is the same as that of household type I. This could be an indication that with limited credit and land availability they adopt a more intensive production system in comparison to the other household types. With the help of a poverty assessment 4 Interested readers can contact the authors for further LP models and base data. 116 Christina Seeberg-Elverfeldt et al. Table 1: Characteristics of household classes I–IV. Household class I II III IV Total cultivated land (ha) 2.5 2.8 2.8 2.5 Rice (ha) 0.18 0.18 0.10 0. 13 Maize (ha) 0 0.012 0.012 0.38 Cacao AFS I (ha) 1.49 0.24 0 0 Cacao AFS II (ha) 0.77 1.31 1.09 0.33 Cacao AFS III (ha) 0.25 1.16 1.73 0 Cacao AFS IV (ha) 0.02 0 0 1.72 Family labour days per month 32.4 29.5 34.4 31.6 Credit limit (€/year) 33 720 1,015 570 Ethnicity (% non-indigenous HHs) 0 19 22 80 Poverty status Poorest Poor Poor Better-off tool based on principle component analysis (Zeller et al. 2006) the households in the region were classified into poverty groups according to their relative welfare. The poverty index allows grouping the households into terciles and makes it possible to draw comparisons between the poorest, poor and better-off households. 67 percent of the type I households belong to the poorest households, whereas 63 percent of the type IV households can be categorised as better off. The households of the two other categories fall into all three welfare groups. We note that there is a poverty gradient to be found from HH towards HH . I IV 3.3. Carbon accounting methodology For carbon accounting the amount of carbon sequestration which is to be claimed as a credit is limited to the net amount of change in the total forest carbon pool from one period to the next. In order to obtain the site specific total above- and below-ground biomass for cacao trees, a logarithmic growth regression model was adopted. The biomass can then be converted to carbon using a conversion factor of 0.5 g of carbon respectively for 1 g of biomass (Brown 1997). To obtain the tradable commodity CO e, the conversion factor for carbon of 3.667 is used. 2 The results show that for this specific region a cacao tree, on average, stores 8.05 kg carbon over a time span of 25 years, with the more intensively managed and densely planted AFS IV accumulating more carbon (46 kg/ha) than the less intensively managed systems I–III (39 kg/ha). Additionally, 0.5 t ha–1 yr–1 of soil organic carbon was added, a figure from the literature (Hamburg 2000), as no site- specific data exist. Due to lack of data, the calculation for carbon accumulation in soils is assumed to occur linearly in time.5 All carbon measurements for above-, 5 For comparison, the total carbon pool has also been calculated excluding soil carbon. As the difference is quite small (3 percent decrease in annuity payment), it is assumed that it is acceptable to include soil carbon. Carbon finance options for smallholders’ agroforestry in Indonesia 117 below-ground and soil carbon were added up to obtain an estimate of the total carbon per hectare of the cacao trees. Finally, this amount was converted to CO e, 2 which is the basis to calculate the amount of certificates to be obtained for the different agroforestry systems. According to the Kyoto protocol, all credits from sink projects have a temporary status and expire after a certain time. Only trees which are planted at the beginning of the crediting period can be assigned temporary certificates of emission reductions (tCER). A tCER is defined as a CER issued for an afforestation project activity under the CDM, which expires at the end of the commitment period following the one in which it is issued (UNFCCC 2003). The tCER are limited to five years, after which they can be re-issued. Once the tCER are not re-certified, a permanent solution is needed to fulfil the reduction requirements. To make things straightforward for this calculation, we assumed that the credits are synchronous with the commitment periods, so that they are issued at the end of the first commitment period and expire five years later at the end of the next commitment period (Dutschke and Schlamadinger 2003; Olschewski and Benitez 2005). In addition, we argue that the annual net rate of carbon accumulation of the shading trees in the first three land-use systems should be accounted for. Otherwise there is a great incentive for purely sun grown cacao plantations, as these are more densely planted and hence, the total carbon accumulation per hectare is higher than in the more shade intensive AFS. This could even foster further cutting down of the shading trees. The carbon fixation of the shade trees has been estimated based on a study by Brown et al. (1996) and included in the carbon budget for the AFS I, II and III. The tCER for the first five year crediting period are related to the cumulative carbon storage of the AFS system. The first credits are generated after five years. These tCER expire after five years, but are reissued in year 10 together with additional tCER. The same procedure is applied for the following 5-year periods until the last issuance of tCER in year 25, and reflects the total net storage of CO since the project started. 2 The prices for tCERs represent only a fraction of the prices for regular CERs from other project categories such as energy projects. Forestry certificates expire after a certain time period, so they are only allocated non-permanent certificates. These must be replaced by permanent ones at some point in the future, hence, the non-permanent credits need to be converted to permanent CER. Therefore, the value of the temporary credits can be seen as the difference between the current permanent credit price and the discounted value of the future permanent credit price: P P =P CERT (1) tCER0 CER0 (1+d*)T where P is the price, CER is the price of the CERs today and CER the price of 0 T permanent CERs discounted at rate d* found in Annex I-countries and T is the expiring time of tCER (Subak 2003).