Bruno Locatelli

Varinia Rojas

Zenia Salinas

Impacts of payments for environmental services on local development in northern Costa Rica: A fuzzy multi-criteria analysis

Keywords: Payments for environmental services, Forest, Plantation, Local development, Costa Rica

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Introduction

Forest ecosystems provide a wide variety of environmental services such as water regulation, biodiversity conservation, or carbon storage for climate change mitigation [START_REF] De Groot | A typology for the classification, description and valuation of ecosystem functions, goods and services[END_REF]. Market mechanisms for forest environmental services are increasingly being used for promoting environmental conservation and their impacts on development are of considerable interest [START_REF] Grieg-Gran | How can market mechanisms for forest environmental services help the poor? Preliminary lessons from Latin America[END_REF]. Implementing payment for environmental services (PES) mechanisms can be a way to achieve development goals and natural resource conservation, especially in low-income regions [START_REF] Tschakert | Environmental Services and Poverty Reduction: Options for Smallholders in the Sahel[END_REF]. In Costa Rica, a national scheme of Payment for Environmental Services, called PSA1 or "Pago por Servicios Ambientales", was created in 1997 [START_REF] Chomitz | Financing environmental services: the Costa Rican experience and its implications[END_REF] that rewards environmental services provided by different land-uses or forest activities, such as forest conservation, reforestation, and agroforestry. PES for reforestation, or more generally the financial incentives for reforestation, have been widely criticized for their possible negative impacts on local development and environment [START_REF] Bull | Industrial forest plantation subsidies: impacts and implications[END_REF]. This debate has been recently reactivated by the inclusion of afforestation and reforestation projects under the Clean Development Mechanism (CDM) of the Kyoto Protocol [START_REF] Totten | Biodiversity, climate, and the Kyoto Protocol: risks and opportunities[END_REF]. As for PES, payments for carbon under the CDM may contribute to rural development but may also create social tensions or have negative impacts on livelihoods [START_REF] Perez | Can carbon sequestration markets benefit low-income producers[END_REF][START_REF] Smith | Capturing the value of forest carbon for local livelihoods[END_REF].

The PSA in Costa Rica was created primarily for environmental purposes; however, secondary objectives include income generation and employment opportunities for rural populations, thereby justifying our study on the impacts of PSA on local development. In addition, development returns for PSA are important because funding comes from the national budget, international development agencies, and buyers of environmental services who see social benefits as the most important criterion of forestry projects [START_REF] Sell | Decision criteria of European and Latin American market actors for tropical forestry projects providing environmental services[END_REF].

Research has been conducted on the links between poverty and PES. According to [START_REF] Grieg-Gran | How can market mechanisms for forest environmental services help the poor? Preliminary lessons from Latin America[END_REF], three key questions are evaluated: (1) the ability of smallholders to sell environmental services relative to better-off stakeholders, (2) the effect of PES on the livelihoods of the poor directly involved in PES and, (3) the effect of PES on the livelihoods of other poor persons not directly involved in PES. For the second and third questions, [START_REF] Vogel | Markets or Metaphors? A Sustainable Livelihoods Approach to the Management of Environmental Services: Two Cases from Ecuador[END_REF] applied a methodology based on a critique of the Sustainable Livelihoods Approach in Ecuador, and [START_REF] Rosales | Developing pro-poor markets for environmental services in the Philippines[END_REF] studied the institutional process of PES as well as the social and economic impacts (e.g. employment, income, migration, or culture) in the Philippines. In Costa Rica, various empirical field studies dealt with the environmental and social impacts of the PSA [START_REF] Rojas | What are we learning from experiences with markets for environmental services in Costa Rica? A review and critique of the literature[END_REF] and landowner participation [START_REF] Zbinden | Paying for environmental services: an analysis of participation in Costa Rica's PSA program[END_REF]. Studies have been conducted in Central and Northern Costa Rica, utilizing focal groups [START_REF] Miranda | The social impacts of carbon markets in Costa Rica. A case study of the Huetar Norte region[END_REF] or individual interviews [START_REF] Miranda | The social impacts of payments for environmental services in Costa Rica[END_REF] for collection of primary information. Some studies are biased because "benefits are widely applauded, and costs are poorly recorded" [START_REF] Grieg-Gran | A closer look at payments and markets for environmental services[END_REF]. Moreover, in some studies, the impacts of PES are not clearly distinguished from the business-as-usual course, as changes are not necessarily a consequence of the PES. In some studies dealing with the participation of smallholders, the prevailing assumption is that their participation should be increased because of the PES positive impact. This paper evaluates the impacts of reforestation under the PSA on local development in northern Costa Rica. We focused on the perception of impacts by landowners or key persons and on the diversity of landowners. We did not consider reasons for participation. This paper will show that (1) the overall impact of the PSA is positive; (2) negative economic impacts are balanced by positive institutional and cultural impacts; (3) both positive and negative impacts are stronger for poor landowners than better-off landowners; and (4) the support of local organizations improves the impact of the PSA. The hypotheses were evaluated through the application of a multi-criteria analysis with fuzzy set theory.

Materials

In 1997, Costa Rica established a national scheme of Payment for Environmental Services (PSA). Landowners can voluntarily apply to the PSA and receive payment proportional to the area dedicated to forest conservation and reforestation. Forest management had been an eligible activity until 2002, and agroforestry has been eligible since 2003. The PSA considers four environmental services: hydrological services, scenic beauty, carbon sequestration, and biodiversity protection [START_REF] Chomitz | Financing environmental services: the Costa Rican experience and its implications[END_REF]. During our fieldwork in 2004, the PSA paid US$ 550 per reforested hectare during the first 5 years (50% in the first year, then 20%, 15%, 10%, and 5% in years 2 to 5). In 2005, Fonafifo decided to increase the total payment and the initial payment for inversion, as well as the duration of the payment to 10 years. Since 2006, one reforested hectare has been paid US$ 816 (46% during the first year and 6%yearly in the subsequent 9 years). Under both payment schemes, landowners must undertake to conserve the reforestation during at least 15 years [START_REF] Fonafifo | Environmental Services Statistics[END_REF]. In comparison, forest conservation has been paid a total of US$ 64, evenly distributed during 5 years. Between 1997 and 2005, 89% of areas under PSA were dedicated to forest conservation. Reforestation reached 27,000 ha during the same period, representing a reforestation rate of 3000 ha/year. Distinct institutions participate in the implementation of the PSA. The most important public institution is Fonafifo (Fondo Nacional de Financiamiento Forestal). At the national level, Fonafifo collects and manages funds received from a specific tax on fuel and from additional sources, such as carbon credits trade, international donors, local hydroelectric and agribusiness interested in hydrological services, and ecotourism business interested in scenic beauty [START_REF] Rojas | What are we learning from experiences with markets for environmental services in Costa Rica? A review and critique of the literature[END_REF]. Landowners can apply to the PSA at the regional Fonafifo offices. Applicants must present administrative and legal documents, as well as a technical study conducted by a forestry agent, acting as an intermediary between Fonafifo and landowners and receiving a fee paid by landowners. In total, landowners support a transaction cost of 18% of the payment according to [START_REF] Rojas | What are we learning from experiences with markets for environmental services in Costa Rica? A review and critique of the literature[END_REF] or between 22% and 25% including other taxes, according to Baltodano (2000). Some local non-governmental organizations (NGOs), such as Fundecor and Codeforsa, play an important role in providing technical assistance and reduce transaction costs by handling paperwork, a useful help for poorer and less educated applicants [START_REF] Chomitz | Financing environmental services: the Costa Rican experience and its implications[END_REF]. The facilitating NGOs have been gaining experience and recognition in forestry issues by working with groups of small and medium landowners. For their facilitating role in the PSA, these NGOs receive a fee paid by landowners and representing between 12% and 18% of the payment, depending on NGO2 .

Our study zone, located in the Huetar Norte conservation area, was selected because it had the highest density of reforestation under the PSA. According to [START_REF] Barrantes | Programa de Pago por Servicios Ambientales (PSA): su evolución entre 1997 y 2004[END_REF], more PSA funds were assigned to reforestation in this area in 2004 than in any other area. The impacts of the PSA have already been studied in this area but with different approaches (i.e. focal group approach in [START_REF] Miranda | The social impacts of carbon markets in Costa Rica. A case study of the Huetar Norte region[END_REF]. This area, one of 11 administrative units defined by the Ministry of Environment, covers 7662 km2 (15% of Costa Rican territory) and is characterized by a humid tropical climate (average temperature between 25 °C and 27 °C and rainfall between 2500 and 4500 mm). The local economy is based traditionally on agriculture (livestock and cash crops, such as ornamental plants, citrus, or pineapple) but new activities, such as ecotourism, are developing quickly. Familyrun small and medium farms and large agribusiness farms coexist in the area. According to Fonafifo, almost 60% of the area was covered by forest in 1999, with reforestation generally established in pastures. The three most common species planted in Northern Costa Rica are Terminalia amazonia (Terminalia), Vochysia guatemalensis (Chancho), and Hieronyma alchorneoides (Pilón) [START_REF] Piotto | Plantaciones forestales en Costa Rica y Nicaragua: comportamiento de las especies y preferencias de los productores[END_REF].

Method

The impacts on local development can be broken down into a set of principles (e.g. economic, social, human, institutional, cultural) that may in turn be broken down into criteria and indicators [START_REF] Munda | Social multi-criteria evaluation: methodological foundations and operational consequences[END_REF][START_REF] Phillis | Sustainability: an ill-defined concept and its assessment using fuzzy logic[END_REF]. We applied a multi-criteria analysis integrating fuzzy set theory [START_REF] Zadeh | Fuzzy sets[END_REF]. The fuzzy set theory has been used in many research and operational areas close to the subject of this article, for example, sustainability assessment [START_REF] Cornelissen | Assessment of the contribution of sustainability indicators to sustainable development: a novel approach using fuzzy set theory[END_REF], environmental impact evaluation [START_REF] Enea | Fuzzy approach to the environmental impact evaluation[END_REF], or natural resource management [START_REF] Bender | A fuzzy compromise approach to water resource systems planning under uncertainty[END_REF]. Fuzzy set theory enables researchers to deal with polymorphous and ambiguous concepts for which a straightforward quantification is impossible, to mathematically handle the reasoning for these concepts, and to produce concrete unambiguous answers [START_REF] Phillis | Sustainability: an ill-defined concept and its assessment using fuzzy logic[END_REF]. The core of the fuzzy set theory is the concept of membership function. A fuzzy set in X is characterized by a membership function f that associates each point x in X with a real number in the interval [0,1], representing the grade of membership of x in the fuzzy set [START_REF] Zadeh | Fuzzy sets[END_REF].

Our methodology included four main steps: (1) development of a set of PCI (Principles, Criteria, and Indicators), (2) fieldwork, (3) data analysis, and (4) statistical analysis. In Step 1, we developed a set of PCI to evaluate the impacts of PSA and reforestation on local development. Initially we revised and adjusted similar sets of existing PCI, e.g. by CIFOR [START_REF] Prabhu | Guidelines for developing, testing and selecting criteria and Indicators for sustainable forest management[END_REF], during two meetings with experts in rural development and forestry issues from the Tropical Agricultural Research Education Center (CATIE) in Costa Rica. 3 The experts reviewed the set, adapted it to local conditions and issues, then weighted the adapted set. The weights represent the importance of each principle, criterion, or indicator for evaluating the impacts, and not the possibility of trade-off between dimensions [START_REF] Munda | Social multi-criteria evaluation: methodological foundations and operational consequences[END_REF]. The five principles were assigned weights summing 100, and then the same procedure was applied to the criteria within a principle and to the indicators within a criterion. The relative weights of each elements of the set were calculated and averaged within the group of experts (see Table 1).

During

Step 2, we applied the PCI set in a field setting. First, indicators were converted into questions for guiding interviews. To evaluate the impact of the PSA, we compared the current situation with the baseline situation that would have occurred without the PSA, i.e. without reforestation or payment (in all cases, landowners declared that they would not have reforested without the PSA). We asked to landowners how their situation had changed since the beginning of the PSA and whether reported changes were due to reforestation under the PSA. For instance, the indicator about impacts on the short-term incomes was evaluated by a first question about how the landowners perceived income changes due to the reforestation and the payment during the first years of the plantation and then by secondary questions about how much money was invested, lost, and received because of PSA.

In 2004, we conducted semi-structured interviews with 37 of the 132 landowners receiving PSA for reforestation in the area (see a description of the sample in Table 2). The sampling was stratified according to farm areas and landowner main activities. Due to constraints on landowner availability and accessibility, it was not possible to reach a sampling intensity higher than 28%. Other sources of information included 14 interviews with representatives of NGOs, regional offices of the Ministry of Environment, and small wood transformation industries. In a multi-criteria analysis, giving exact values to indicators may be difficult when indicators have not been measured quantitatively or are ambiguous [START_REF] Phillis | Sustainability: an ill-defined concept and its assessment using fuzzy logic[END_REF]. Instead of assigning a single impact value, we recognized that the border between positive and negative impactswas not sharp and considered degrees of positive or negative possibility [START_REF] Phillis | Sustainability: an ill-defined concept and its assessment using fuzzy logic[END_REF]. Moreover, problems may arise from the aggregation of the indicators into a single impact valuation. Even if stakeholders agree about weights, the aggregation approach could be a subject of dissonance due to a continuum of approaches from very conservative to very liberal. Here an example is given regarding the aggregation of two indicators, I111 "increases in short-term incomes" and I112 "increases in long-term incomes", into criterion C11 "increases in incomes". For a very conservative approach, incomes are considered to increase if both short-term and long-term incomes increase. In the general case, this means that no trade-off is allowed: only the best situations with all positive indicators would result in a positive overall evaluation. The degree µ of membership of C11 in the set of positive impacts is the smallest degree of membership of indicators µ1 or µ2 in the set of positive impacts. In fuzzy set theory, this operation is an intersection and is calculated by applying the minimum operator: µ=min(µ1, µ2). For a very liberal approach, incomes are considered to increase if short-term OR long-term incomes increase. In the general case, this means that trade-off is extreme: a single positive indicator can balance the other negative indicators and result in a positive overall evaluation. This operation is a union and is calculated with the maximum operator: µ=max(µ1, µ2) [START_REF] Dubois | An introduction to fuzzy systems[END_REF].

Intermediate approaches may also be imagined, in which high values of some indicators may compensate low value of others [START_REF] Cornelissen | Assessment of the contribution of sustainability indicators to sustainable development: a novel approach using fuzzy set theory[END_REF] and the degree of trade-off may vary. A parameter α for the degree of trade-off can vary between positive infinity for a liberal approach and negative infinity for a conservative approach. A general equation for aggregation is the following:

If we consider n elements to be aggregated with weights (w k are the weights, k=1 to n), the aggregation is calculated with the following equation [START_REF] Grabisch | Fuzzy aggregation of numerical preferences[END_REF][START_REF] Cornelissen | Assessment of the contribution of sustainability indicators to sustainable development: a novel approach using fuzzy set theory[END_REF]:

During

Step 3, we analyzed the field data by converting each observation into a value between -1 and +1. To avoid personal interpretations of the field data, the two authors conducted separate analyses, compared their findings, and reached consensus. With a fuzzification process, each indicator value was converted into two degrees of membership in the sets of positive and negative impacts by using sigmoid functions (see Fig. 1).

Fig. 1. Membership functions in the sets of positive and negative impacts.

Fig. 2 shows an example of fuzzy inference [START_REF] Cornelissen | Assessment of the contribution of sustainability indicators to sustainable development: a novel approach using fuzzy set theory[END_REF] for two indicators and one criterion, in the case of a liberal approach. If the degrees of membership of I1 and I2 in the set of the positive impacts are 0.04 and 0.23 respectively, the truth-value of the premise "I1 is positive or I2 is positive" is the maximum of 0.04 and 0.23 because of the logical connective OR. As a consequence, the conclusion "C is positive" has a truth-value of 0.23 (graphs a to c). The same procedure is applied to negative impacts, utilizing the minimum operator for the logical connective AND, because the rule for negative impacts always uses the connective opposite to that of the positive rule (d to f). An overall fuzzy conclusion is drawn using the union of the two partial conclusions. A defuzzification process reaches an unambiguous impact value with the center of gravity method (g). For each landowner, the fuzzy inferences were subsequently applied for aggregating indicators into criterion, criteria into principle, and principles into overall evaluation. They were applied with seven distinct approaches from conservative to liberal. We used a linear correction so that the impact value would be +1 for a "best" landowner with all positive impacts, 0 for a "null" landowner with all null impacts, and -1 for a "worst" landowner with all negative impacts. All calculations were done with Matlab™.

In Step 4 statistical t-tests (p<0.05) were used to assess whether the average impact for each principle or criteria was significantly different from 0. When significant, the average impact based on the balanced approach (α=0) was reported qualitatively: Null (between -0.05 and 0.05), Moderately Negative or Positive (between 0.05 and 0.25 in absolute value), Negative or Positive (0.25-0.5), Very Negative or Positive (0.5-0.75), Highly Negative or Positive (0.75-1).

Using t-tests, we looked for impact differences between groups of landowners: farmers, working class, upper class, and agribusiness (see Table 2 for group description). Other comparisons were made between landowners applying to PSA through local organization (n=16) and others. Some groups were defined by degrees of membership (see Fig. 3 and Table 3). When applying t-tests we considered fuzzy memberships as weights to compute weighted averages, standard deviations, and sample size. Finally, to test the robustness of the conclusions, we applied a sensitivity analysis [START_REF] Munda | Social multi-criteria evaluation: methodological foundations and operational consequences[END_REF]. We performed 100 calculations with all weights modified by a random factor between -50% and +50% and we obtained the standard deviation of the results.

Results

Criteria and weighting

The PCI set was organized into five principles that included 12 criteria and 27 indicators (see Table 1), covered three dimensions (socioeconomic for P1 and P2, institutional for P3 and P4, cultural for P5), and two scales (landowner for P1, P3, and P5, indirect beneficiaries for P2 and P4). The indirect beneficiaries are those affected by the PSA through employment or changes in local infrastructures and land tenure. Cultural impacts on indirect beneficiaries seemed too weak and were not included.

Economic impacts were weighted higher (31% for P1 and 21% for P3) than institutional (18% for P2 and 18% for P4) or cultural impacts (13% for P5). The impacts on landowners were weighted higher than the impacts on indirect beneficiaries. The five criteria receiving more weight were C11 (landowner income, 17.4% of total weight), C12 (economic risk reduction for landowner, 13.2%), C21

(employment), C32 (landowner access to financial and technical support), and C31 (legalization of land tenure).

Impact valuation by different approaches

As expected, the total impact increased from conservative to liberal approaches; the conservative approach was highly negative and the liberal approach was highly positive. Even for conservative approaches, the institutional impacts on organizations (P4) and the cultural impacts on beneficiaries (P5) were positive. For balanced approaches (α=0), total impact was positive and only principle P1 showed a moderately negative impact; the others were moderately to highly positive (see Fig. 4). Comparing the different approaches revealed that only five criteria always remained positive: C31 (legalization of land title), C42 (strengthening NGOs), C43 (law enforcement), C51 (landowner awareness of ecosystem services), and C52 (inciting the beneficiary to protect forest resources). Only one criterion always remained negative: C22 (social impacts of land concentration).

Landowner's socioeconomic well being Principle

P1 (landowner's socioeconomic well being) was the only principle with a negative evaluation by a balanced approach. The impact differed according to social class: positive for upper class and negative for three other socioeconomic classes (small farmers: negative, working class: negative, and agribusinesses: moderately negative). The two criteria C11 and C12 were not significantly different from zero because their compounding indicators reached contrasted values. Indicator I111 (impacts on short-term income) was significantly negative in the whole sample and differed between upper class (null) and working class (very negative). Even though the payment was meant to cover only part of the reforestation costs, 60% of the landowners were disappointed because the payment did not compensate costs. Indicator I112 (impact on medium and longterm income) differed between upper class (very positive) and three other groups: small farmers (very negative), working class (negative), and agribusinesses (negative). Large farmers (positive) were different from small farmers (very negative). A majority of landowners (71%) perceived long-term reforestation to be associated with financial benefits. The remaining 29% cited uncertainties regarding wood prices and quality of future harvests.

Indicator I121 (diversification of activities) was very positive and without significant difference between landowner groups. Forty-one percent of the landowners started new activities as a consequence of reforestation under the PSA, for example small sawmills or transportation businesses. Indicator I122 (beneficiary credibility when soliciting credit) was moderately positive and higher for large farmers (positive) than for medium farmers (moderately negative). According to 38% of landowners, banks do not consider reforestation as a loan guarantee. 4 Indicator I123 (decreased economic vulnerability because of increased assets and regular payments) was not significant. Seventy-one percent of landowners were satisfied with the regularity of payments, but payment and reforestation did not create a security asset. Indicator I124 (marketing) was highly negative, without discrimination between groups. No producers had sold products from the final harvest, but almost all landowners had already done a thinning. Ninety-five percent of landowners who tried to sell small-diameter products from thinning had trouble finding a buyer or were disappointed by prices.

Indirect beneficiaries' socioeconomic well being

The impact on socioeconomic well being of indirect beneficiaries (P2) was moderately positive in the whole sample and better for small farmers (positive) or employees (moderately positive) than for upper class landowners (moderately negative). The impact on employment (C21) was very positive. Within this criterion, the strongest impact was on the creation of jobs for product transportation and transformation (I213, highly positive). The impact on the number of farm workers (I211) was also positive whereas the impact on work conditions (I212) was null.

Fifty-one percent of the landowners thought that reforestation, including product transportation or transformation, created additional jobs compared to livestock breeding, 16% thought the contrary, and 33% did not see any change.

The PSA has induced land concentration, considered here as a negative impact because it may bring about social disparities, conflicts, and forced migration. The impact on land concentration (C22) was stronger for upper class landowners, small farmers, and working class landowners. Although impact on land concentration was significant (I221, negative), conflicts and induced migration were insignificant (I222). Twenty-seven percent of landowners had bought more land for reforestation. Interviews with local organizations confirmed that some rich landowners or companies had bought land for reforestation.

Criterion C23 regarding impacts on area social and economic conditions was not significant, nor were the corresponding indicators I231 (social infrastructure) and I232 (other productive activities). According to the majority of landowners and organization representatives, reforestation had not induced regional changes because it is a minor activity compared to agriculture.

Relationships between the landowner and institutions

The impact on the relationships between the landowner and institutions (land tenure institutions, local and national organizations) was positive (P3), especially for landowners applying to the PSA through a local NGO. Criterion C31 (land title legalization) was moderately positive and differed between small farmers (positive) and agribusinesses (null). For 92% of landowners, the PSA had no impact on legalization because they had already regularized their land titles before applying to the PSA. The same results were found for the two indicators I311 (motivation of the beneficiary to regularize land tenure and get titles) and I312 (protection of beneficiary rights). The 8% of landowners that regularized their land title with the PSA felt their rights were more protected in case of settler encroachment.

Criterion C32 (relationships between landowners and local organizations) was positive, especially for landowners applying to the PSA through a local NGO and for small farms, for whom the impact was very positive and significantly different from other groups. The first indicator I321 (possibility of a beneficiary to request and receive support from local and national organizations) was highly positive. The vast majority (84%) of landowners requested support from organizations related to the PSA at least once, and received a good response. The second indicator I322 (reduction of conflictive situations between the beneficiary and organizations) was negative. Sixty-two percent of landowners considered long-term restrictions regarding land-use change under PSA contracts a potential source of conflict with the organizations involved. Moreover, most landowners (89%) thought another source of conflict was the too low payment.

Forestry sector institutions

The impact on strengthening forestry sector institutions (P4) was highly positive, especially regarding NGOs and law enforcement and to a lesser extent for public organizations. The impact was moderately positive on public forestry organizations (C41), as the PSA had not helped these organizations receive additional funds (I412, not significant), even if it had contributed to improving human capacities and physical infrastructure (I411, positive). Representatives from public forestry organizations said that the lack of budget and materials from the PSA impeded the development of capacities and better services. The impact was highly positive on NGOs (C42) and both indicators related to this criterion were highly positive. The difference between NGOs and public sector institutions is that NGOs do receive a fee from the payments, while public sector institutions do not receive additional funds to manage PSA. Stakeholders thought that the NGOs were incited to provide good services as they received a share of the PSA payment. The impact was also highly positive on law enforcement (C43) because the PSA forced stakeholders to respect the law (I431, highly positive) and facilitated law enforcement monitoring (I432, highly positive). Civil servants of the Ministry of Environment regional offices said that they monitor law enforcement when they visit PSA farms.

Cultural impacts

The cultural impacts were very positive (P5), without significant differences between groups. Reforestation and the PSA raised beneficiary awareness about forest ecosystems goods and services (C51, very positive), especially for farmers (highly positive). Satisfaction increased with regard to forest ecosystems goods and services (I511, very positive) and promoted the adoption of sustainable practices by the beneficiary (I512, very positive), especially for large farmers and agribusinesses. Even though most landowners had a negative feeling about the economic benefits of reforestation, 57% had a positive perception of the environmental benefits. Sixty-five percent of landowners had implemented measures for conserving biodiversity, ecosystems or water, after they entered in the PSA program.

The PSA and reforestation also incited the beneficiaries to protect forest resources (C52, very positive), especially for farmers and agribusinesses (very positive) compared to upper class landowners (null). The PSA motivated the beneficiaries to replant after harvesting, even without payment (I521, very positive), especially for the landowners that applied to the PSA through a local NGO. It also incited landowners to invest time and money in the protection of forest resources (I522, positive). Fifty-seven percent of landowners said they would continue with reforestation even without receiving PSA funding. The commitment of landowners to protecting forest resources (criterion C52 and its indicators) was significantly correlated with two other criteria: C12 (reduction of economic risk) and C32 (financial and technical support by organizations).

Sensitivity analysis

Changes in the weights hardly affected the results (see Fig. 4 where error bars represent the standard deviation of the value during 100 repetitions). For instance, the total impact value was 0.37 on average (positive impact) with a standard deviation of 0.07 (19% of the average). The extreme values were 0.19 (moderately positive) and 0.52 (very positive).

Discussion

The method used revealed the impact of payment for environmental services on local development, considering various dimensions (socioeconomic, institutional, and cultural) as well as distinct scales (landowner and indirect beneficiary). It is important to consider non-market benefits in evaluating impacts [START_REF] Lipper | Land-use change, carbon sequestration and poverty alleviation[END_REF]. Reducing the study to only the socioeconomic impacts on landowners would have drawn a negative portrait of the PSA, as one of the worst impacts was on landowners' short-term incomes and the more positive impacts were observed in the institutional and cultural aspects.

On average, the aggregated impact of the PSA was positive with a balanced evaluation approach and consistent with most studies conducted in Costa Rica [START_REF] Miranda | The social impacts of carbon markets in Costa Rica. A case study of the Huetar Norte region[END_REF]. The negative socioeconomic impacts on landowners seemed to be the major pitfall of the PSA for reforestation. Landowners said that the payment did not sufficiently compensate for reforestation and opportunity costs.

Using secondary data from local organizations, we estimated that, in the first year, reforestation represents a further investment of 200 US$/ha in addition to the PSA payment. In the following years, reforestation costs were compensated by payments. The loss of incomes due to abandonment of pasture averaged 375 US$/ha/year. However, this land opportunity cost varied widely due to natural and socioeconomic conditions.

Landowners without productive farm activities did not suffer loss of income when entering into the PSA. That finding explained why the impact on short-term income was null for upper class landowners and negative for small farmers, working class landowners, and agribusinesses. Many upper class landowners used their farm for recreation purposes and wanted to reforest for scenic beauty. Others wanted to build reforestation capital or start a productive activity that did not require a permanent presence. The PSA allowed these landowners to achieve their plans at lower costs.

Impacts on mid-and long-term income were negative for small farmers and the working class and very positive for upper class landowners, who may consider reforestation as an investment. Landowners with negative perceptions may lack information on income generated by plantation harvest. The negative impact may also reflect a strong preference for present incomes. Our results differed from other studies concluding on positive impacts on incomes, but dealing with the PSA applied to forest conservation [START_REF] Ortiz Malavasi | Impacto del programa de pago de servicios ambientales en Costa Rica como medio de reducción de la pobreza en los medios rurales. Unidad Regional de Asistencia Técnica (RUTA)[END_REF][START_REF] Miranda | The social impacts of payments for environmental services in Costa Rica[END_REF]. Forest conservation under PSA induces payment gains and opportunity costs (potential loss of income from wood harvesting) but impacts are often evaluated positively because opportunity costs are ignored, even though they can be higher than the payments [START_REF] Wunder | Payments for Environmental Services: Some Nuts and Bolts[END_REF].

The initial investment for reforestation, as well as transaction costs and other information or skill barriers, are major hindrances to poor landowner participation.

In addition, the majority of landowners were disappointed by the sale of the first thinning products, because the Costa Rican reforestation product market is not well developed. The lack of information about prices or wood quality technical specifications also reduced profits. The support of local organizations was essential as almost no farmer had experience in reforestation before starting with the PSA.

An important side-impact on the socioeconomic wellbeing of landowners was the diversification of livelihoods, also reported in other countries [START_REF] Grieg-Gran | A closer look at payments and markets for environmental services[END_REF] and in Costa Rica, where landowners see the PSA as an opportunity to realize new economic activities, such as ecotourism or environmental education [START_REF] Miranda | The social impacts of payments for environmental services in Costa Rica[END_REF].

Indirect stakeholders benefited positively from employment creation in the plantation and in the chain of value of wood products, especially with plantations by agribusinesses, which generally hired more workers than small farmers.

Reforestation is labor-intensive: 1 ha of reforestation may generate 300 days of work per rotation, including the wood chain [START_REF] Arias | Análisis del impacto económico y social de las plantaciones forestales en Costa Rica[END_REF]. In contrast, studies on PSA applied to forest conservation reported its impact to be neutral in terms of employment in marginal areas and negative in other areas [START_REF] Ortiz Malavasi | Impacto del programa de pago de servicios ambientales en Costa Rica como medio de reducción de la pobreza en los medios rurales. Unidad Regional de Asistencia Técnica (RUTA)[END_REF]. Under forest conservation, logging-company workers or charcoal makers may lose their jobs [START_REF] Wunder | Payments for Environmental Services: Some Nuts and Bolts[END_REF].

Negative impacts were observed with land concentration. Richer landowners and companies reforesting for profit were more likely to buy land and cause land concentration problems than farmers whose livelihoods depend on farm activities. Impacts on infrastructure or service provisions (e.g. roads, schools, health centers, or water supply) were not significant because reforestation is a minor activity in the area, as in other Costa Rican areas [START_REF] Miranda | The social impacts of payments for environmental services in Costa Rica[END_REF].

The PSA contributed to improving relationship between landowners and institutions. Legalization of land title was only moderately improved by the PSA because most landowners already had legal titles. The PSA moderately improved land tenure security, but to a lesser extent than in other Latin American countries [START_REF] Rosa | Compensation for Environmental Services and Rural Communities[END_REF][START_REF] Wunder | Payments for Environmental Services: Some Nuts and Bolts[END_REF]. The land title requisite for PSA applications is generally analyzed as positive if it promotes legalization and provides better landowner security, but it may limit the role of PSA in poverty alleviation, as many poor people do not own their lands [START_REF] Wunder | Payments for Environmental Services: Some Nuts and Bolts[END_REF].

The support provided by local organizations to landowners under the PSA is another very positive impact. Contacts between landowners and local organizations facilitate capacity building and information dissemination, even regarding other businesses [START_REF] Wunder | Payments for Environmental Services: Some Nuts and Bolts[END_REF]. Potential conflicts between landowners and Fonafifo were identified, especially regarding the imposed land-use change restrictions, which had been misunderstood by some landowners when entering in the PSA. One landowner felt he was "trapped" by the implications of the PSA contract as he desired to transform the reforested land into another use. The payment level was also a source of discontent. However, this argument must be analyzed with caution as landowners may strategically argue in order to push for an increased payment [START_REF] Echavarría | The impacts of payments for watershed services in Ecuador: emerging lessons from Pimampiro and Cuenca[END_REF].

The PSA contributed to strengthening the forestry sector institutions (P4). Other studies found that institutional innovation and de-bureaucratization were necessary for developing and implementing the PSA [START_REF] Miranda | The social impacts of payments for environmental services in Costa Rica[END_REF]. Some NGOs benefited from wide recognition in Costa Rica and abroad for their contributions to the implementation of the innovative PSA mechanism.

The PSA also increased law enforcement by facilitating monitoring and improving landowner awareness. The PSA had very positive impacts on landowner perceptions of environment or forest and incited forest protection. It was difficult to distinguish the impacts of the PSA from the effects of Costa Rican environmental education programs. However, changes in the perceptions of reforestation are probably due to the PSA because the landowners had not reforested prior to the PSA. Local organizations played an important role in providing information and organizing capacity building for landowners. In other locations throughout Costa Rica, the PSA provided training sessions, environmental education, and new forest and farm management knowledge [START_REF] Miranda | The social impacts of payments for environmental services in Costa Rica[END_REF].

Conclusion

Our evaluation of the PSA applied to reforestation is globally positive; the negative economic impacts are balanced by the positive institutional and cultural impacts.

The impact on local development depends on the composition of the set of beneficiaries [START_REF] Pagiola | Can payments for environmental services help reduce poverty? An exploration of the issues and the evidence to date[END_REF]. In other places in Costa Rica, for instance in the Virilla watershed [START_REF] Miranda | The social impacts of payments for environmental services in Costa Rica[END_REF], the large majority of landowners receiving PSA are upper class and do not depend on the farm for their livelihoods. In our sample, the impacts of the PSA on the poorest landowners (small farmers and working class landowners) were notably positive in most dimensions, except regarding income. On the contrary, the impacts were often null for upper class landowners and in some cases, such as land concentration, negative.

The best option for enhancing local development impacts would be to focus the PSA on the poorest landowners. However, the major problem is that the incomes of the poorest landowners, especially their short-term incomes, decreased as a consequence of reforestation. This problem may engender negative outcomes and reduce the participation of the poorest landowners. Proactive effortsmust bemade to ease the participation of less educated and poorer applicants for the PSA to be used as an instrument of poverty reduction. To improve income impacts, additional support could be provided to the poorest landowners when reforesting under the PSA. This could be done through additional financial incentives, such as advance payments for wood purchase, implemented by Fundecor in Costa Rica.

The strongest positive impacts were for landowners applying to the PSA through a local NGO. These organizations provided services to the landowners beyond the payment that partly explain the positive impact. The organizations also reduced transaction costs and paperwork, so that less educated and poor landowners could participate in the PSA. However, this positive impact cannot necessarily be generalized to other cases because of the specificities of two local organizations in Central and Northern Costa Rica (Fundecor and Codeforsa). They are locally and internationally well-known and respected for their capacity to adapt to changing legal and economic conditions, to generate new technical knowledge, and to create innovative approaches for protecting or enhancing forest resources [START_REF] Camacho | Gestión local y participación en torno al pago por servicios ambientales: Estudios de caso en Costa Rica[END_REF]. Many positive aspects of the PSA applied to reforestation are due to the productive nature of activities. Compared to payment for forest conservation or other economically reducing activities, the impacts of reforestation on employment and long-term income are better [START_REF] Pagiola | Can payments for environmental services help reduce poverty? An exploration of the issues and the evidence to date[END_REF]. The impacts on incomes depend on the existence of timber markets and the capacity of landowners to negotiate prices. As incentives to reforestation prior to the PSA ended in failure because of a lack of markets for timber, special attention should be given to marketing issues.

The PES programs applied to reforestation are not a panacea for local development problems but they may have positive impacts on various dimensions of sustainable development. They may promote the introduction of trees in the landscapes and provide goods and services for local communities. They may also provide more environmental awareness in the population, more diversification of the local economy, and stronger institutions. For impacts to be positive, the PES programs should involve and support small landowners. However, this may increase the complexity of PES programs, raise transaction costs, and reduce the total supply of environmental services. As mentioned by other authors [START_REF] Kosoy | Payments for environmental services in watersheds: Insights from a comparative study of three cases in Central America[END_REF], a trade-off must be found between the environmental and social goals in PES programs.

Fig. 2 .

 2 Fig. 2. Fuzzy inference and defuzzification in the case of two fuzzy rules for aggregating two indicators I1 and I2 in one criterion C.

Fig. 3 .

 3 Fig. 3. Degree of membership µ in the sets of small, medium, and large farms.

Fig. 4 .

 4 Fig.4. Impact valuation by different approaches (error bars represent the standard deviation calculated in the sensitivity analysis).

Table 2 Sample description Landowner characteristics N Farm area in hectares (mean and standard deviation) Percent of area reforested (mean and standard deviation)

 2

	All landowners	37 93 (69)	52% (35%)
	Farmers	9	105 (65)	55% (43%)
	Working class (drivers,	12 70 (59)	53% (32%)
	teachers, carpenters, social
	workers, domestic workers)
	Upper class (lawyers,	8	76 (47)	51% (27%)
	businessmen, engineers)
	Agribusinesses (forest and	8	131 (94)	49% (42%)
	agriculture companies)

Table 3 .

 3 Fuzzy definition of landowner groups

Landowner group and size Fuzzy definition (µ=degree of membership)

	Small farm (∑µ=14.74),	Based on farm area (See Fig. 3) with 40, 90, and
	Medium farm (∑µ=9.26),	140 ha as thresholds. Thresholds were based on
	Large farm (∑µ=13.00)	percentiles of the distribution of farm areas.
	Small farmer (∑µ=2.82)	µ(Small farm) if landowner is a farmer
	Large farmer (∑µ=4.23)	µ(Large farm) if landowner is a farmer
	Depending on farm for	µ=1: Farmers (agriculture or livestock), µ=0.5:
	livelihoods (∑µ=15)	working class (driver, teacher, carpenter, social
		worker, domestic worker)

In this paper, PES is used as general term and PSA refers to the Costa Rican PES.

Guillermo Navarro, CATIE, pers.comm., Sept. 2007.

We acknowledge Andrés García, Bastiaan Louman, David Quirós, Dietmar Stoian, Fernando Carrera, Guillermo Navarro, Kees Prins, Mario Piedra, Miluzka Garay, Mónica Salazar, Octavio Galván, Sara Yalle, Vanessa Sequeira, and Zaira Ramos for their participation.

This information was confirmed by other informants. Another incompatibility between bank loans and the PSA was that, until very recently, Fonafifo did not accept farms with mortgages and even those that are now accepted have drastic restrictions.

Acknowledgements

We acknowledge with gratitude the valuable help of the landowners and representatives of Fundecor, Minae, Fonafifo, and Codeforsa. We thank Guillermo Navarro, Cornelius Prins, Zenia Salinas, and Dietmar Stoain for their comments. This work was supported by the Finnish Department for International Development Cooperation (Finnida).


Bruno Locatelli
email: bruno.locatelli@cirad.fr

Lucio Pedroni

Accounting methods for carbon credits: impacts on the minimum area of forestry projects under the Clean Development Mechanism

Keywords: Kyoto Protocol, Clean Development Mechanism, Non-permanence, Forestry project, Carbon accounting, Small-scale project

The Ninth Conference of the Parties (COP-9) decided to adopt an accounting system based on expiring carbon credits to address the problem of non-permanent carbon storage in forests established under the Clean Development Mechanism (CDM). This article reviews and discusses carbon accounting methods that were under consideration before COP-9 and presents a model which calculates the minimum area that forest plantation projects should reach to be able to compensate CDM transaction costs with the revenues from carbon credits. The model compares different accounting methods under various sets of parameters on project management, transaction costs, and carbon prices. Model results show that under current carbon price and average transaction costs, projects with an area of less than 500 ha are excluded from the CDM, whatever accounting method is used. Temporary crediting appears to be the most favorable approach to account for non-permanent carbon removal in forests and also for the feasibility of smaller projects. However, lower prices for credits with finite lifetimes may prevent the establishment of CDM forestry projects. Also, plantation projects with low risk of unexpected carbon loss and sufficient capacity for insuring or buffering the risk of carbon re-emission would benefit from equivalence-adjusted average carbon storage accounting rather than from temporary crediting.

Introduction

Carbon storage in forests is not permanent. After a finite residence time in vegetation and soil, it may be released into the atmosphere through respiration, decomposition, digestion, or fire. Nevertheless, it is generally accepted that temporary carbon removal by forests contributes to mitigating climate change.

In Bonn (2001), the Kyoto Protocol negotiators had already agreed that atmospheric carbon removal by newly afforested or reforested landscapes has such a value for climate change mitigation that it should be awarded under the Clean Development Mechanism (CDM). In this context, we need to ask how to quantify the value of temporary carbon removal for climate change mitigation in comparison to the value of permanent greenhouse gas (GHG) emission reductions. This is the essence of the nonpermanence problem.

For Kyoto Protocol carbon accounting, non-permanence is uniquely a problem of forestry projects in the CDM. Greenhouse gas (GHG) emission reductions achieved through CDM projects in the energy sector are assumed to be permanent because the energy supplied by these projects will never be demanded again (Chomitz, 2000a). The non-permanence of carbon removals by forests of Annex I countries is not a problem for GHG emission accounting because these countries have assigned amounts of GHG emissions. Therefore, if carbon dioxide (CO2) is released from an Annex I forest, an equivalent amount of CO2 emissions is debited in the national GHG accounting book of that country. Similarly, when CO2 is removed by Annex I forests, the corresponding amounts of CO2 are credited to those countries. Since non-Annex I countries do not have quantified emission limitations and reduction commitments, this type of national accounting cannot be made, and carbon removal in specific forestry projects must be assumed to be non-permanent [START_REF] Ellis | Forestry Projects: Permanence, Credit Accounting and Lifetime[END_REF].

Before the ninth Conference of the Parties (COP-9) decided how to address the non-permanence problem, there were many suggestions on how to deal with this issue in CDM forestry projects. The leading paradigm was to address non-permanence through specific carbon accounting methods. The IPCC Special Report on Land Use, Land-Use Change and Forestry (LULUCF) describes at least three conceptually distinct accounting methods (IPCC, 2000). From the submissions that different countries presented to the UNFCCC Secretary, it appeared that Parties of the United Nations Framework Convention on Climate Change (UNFCCC) held different positions and interpretations regarding these accounting methods. In addition (Chomitz, 2000b), Colombia and, later, the European Union and other countries, advanced proposals regarding a temporary accounting regime, which received increasing support by the Parties of the Convention (UNFCCC, 2002). A temporary carbon accounting approach based on expiring temporary Certified Emission Reductions (tCERs) and long-term CERs (lCERs) was finally adopted at COP-9 (UNFCCC, 2004). In this article, we analyze the main accounting methods considered before the ninth Conference of the Parties (COP-9, Milan, Italy, 1-12 December 2003). 1Carbon accounting methods have a strong impact on project viability and on the scale at which projects are benefiting from the CDM. The issuance of carbon credits, or Certified Emission Reductions (CERs), as these are called under the CDM, is the last stage of a project development sequence that requires many investments that are clearly above business-as-usual practices in forest plantation entrepreneurship. They include additional costs at the stages of project design, negotiation, validation, monitoring, verification, and issuance of carbon credits [START_REF] Aukland | Laying the Foundations for Clean Development: Preparing the Land Use Sector. A Quick Guide to the CDM[END_REF][START_REF] Pcf | Validation, Verification and Certification for PCF Projects[END_REF][START_REF] Vine | Guidelines for the Monitoring, Evaluation, Reporting, Verification, and Certification of Forestry Projects for Climate Change Mitigation[END_REF]. These so called 'transaction costs' reduce the attractiveness of the CDM [START_REF] Michaelowa | Transaction costs of the Kyoto Mechanisms[END_REF]. They are independent of carbon accounting methods, but the number and price of credits that can be awarded to the projects are very dependent on the accounting method used.

The question of the scale at which projects are viable for the CDM is relevant from at least three points of view. The first is equity. If only large-scale projects would turn out to be feasible, many countries, and in particular small community forestry projects, would be excluded from the CDM. The second is the impacts on local livelihoods, biological diversity, and the local environment [START_REF] Smith | Forest Carbon and Local Livelihoods: Assessment of Opportunities and Policy Recommendations[END_REF][START_REF] Orlando | Carbon, Forests and People: Towards the Integrated Management of Carbon Sequestration, the Environment and Sustainable Livelihoods[END_REF]. Plantation projects may bring positive impacts on sustainable development but not in all situations. Large-scale projects are believed to be particularly prone to having negative impacts on local livelihoods, biological diversity, and the local environment. The third is leakage. Largescale projects may inundate local, regional, and even global markets with their forest-derived products and therefore lower the prices of those products. This might discourage forest entrepreneurship at other locations, where new forests would have been established in the absence of such large projects.

The aim of this article is to show the impact of accounting methods of carbon credits on the minimum area at which forest plantation projects would start to benefit from the CDM. First, the article reviews the most discussed accounting methods that were under consideration before COP-9, their possible interpretations, as well as their respective implications on the incentives for forestry projects and on the risks for climate mitigation. Then, the model used to calculate the minimum area of the projects is described and, finally, model results are presented and discussed.

Accounting methods

Accounting methods for carbon credits for CDM forestry projects have been summarized and discussed by IPCC (2000), [START_REF] Fearnside | Accounting for time in mitigating global warming[END_REF],), [START_REF] Ellis | Forestry Projects: Permanence, Credit Accounting and Lifetime[END_REF], [START_REF] Marland | Accounting for sequestered carbon: the question of permanence[END_REF], [START_REF] Dutschke | Permanence of CDM Forests or Non-permanence of Land Use Related Carbon Credits? HWWA Discussion Paper 134[END_REF], [START_REF] Subak | Replacing carbon lost from forests: an assessment of insurance, reserves, and expiring credits[END_REF] and in many submissions of Parties on the UNFCCC, among others. As the interpretations of these methods can vary, a review and discussion of each of them is required.

Ton-year

The ton-year accounting method (or equivalence-factor yearly crediting) assumes that, to prevent the cumulative radiative forcing effect exerted by CO2 during its residence time in the atmosphere, it is necessary to store an equivalent amount of CO2 as carbon in biomass or soil during a period of time called 'equivalence time' (Te) [START_REF] Moura-Costa | An equivalence factor between CO2 avoided emissions and sequestration: description and applications in forestry[END_REF]. To apply this method, an agreement on the value of Te is required. Proposed lengths vary between 50 and >100 years (Chomitz, 2000a;IPCC, 2000). The model developed for this study assumes 100 years, as proposed by [START_REF] Fearnside | Accounting for time in mitigating global warming[END_REF] since this timeframe has been adopted under the Kyoto Protocol to establish the CO2 equivalence of the global warming potentials of all other GHGs (UNFCCC, 1997).

According to Equation (1), used to calculate ton-year credits, one credit would be awarded to a project that stores 1 ton of CO2 during Te years as well as to a project that would store Te tons of CO2 during 1 year. The amount of 'ton-year' credits issued during a given period of time is calculated as follows:

( 1 )

where Te is the 'equivalence time' as defined before, x is the beginning of a crediting period, and i is its duration in years. Instead of Te in the denominator, in some publications the nominator is multiplied by an equivalence factor (Ef), which is 1/Te. Ton-year accounting can be considered safe for the climate under two conditions: the concept of equivalence between avoided emissions and temporary removal is accepted and defined, and credits are awarded ex post, that is after verifying that the carbon removals to be credited have effectively been stored. Only achieved climate change mitigation would be credited, and the maintenance of the verified carbon removals after credit issuance would therefore not be required. The greatest disadvantage of this accounting method is that projects would earn credits very slowly, which would make the CDM unattractive to them (Figure 1).

Equivalence-adjusted average carbon storage

The equivalence-adjusted average carbon storage (ACS) accounting method is based on the same theoretical assumption as the 'ton-year' method [START_REF] Moura-Costa | An equivalence factor between CO2 avoided emissions and sequestration: description and applications in forestry[END_REF]. Carbon removal would be considered equivalent to permanent if the duration is at least equal to Te or fractioned for Te.

The difference from the 'ton-year' method is that the total amount of credits is calculated as the average quantity of CO2 stored by the project during its lifetime. Since projects have different lifetimes, the average removal has to be adjusted for Te in the denominator of Equation ( 2) instead of the project lifetime n. This would make credits issued from projects of different durations fully comparable. The total amount of ACS credits would be calculated as follows:

( 2 )

where Te is the 'equivalence time' which is defined above, and n is the project duration in years.

There are at least two interpretations of this method regarding the point in time at which credits should be awarded. The first interpretation is to assign credits in line with removals, that is to say that credits would be equal to removals, but once the total amount of credits is equal to the equivalence-adjusted average removal, projects would not be able to issue additional credits. This approach is used by the model in this study. The second interpretation is to calculate credits in line with the running equivalence-adjusted average removal, which would delay the issuance of credits compared with the first interpretation [START_REF] Groen | Carbon Accounting and Cost Estimation in Land Use, Land Use Change and Forestry Projects using CO2Fix V.3[END_REF].

In both interpretations, the way that credits are assigned to the projects is risky for the climate. ACSaccounting allows the projects to be credited very early in their lifetime, but credits are awarded for the amount of carbon that will be stored on average during the whole project duration according to projected growth, mortality, and harvest. Therefore, the method does not take into account that in the time interval between credit issuance and predicted project end ('uncertainty time') growth could turn out to be less than predicted, and that disturbances might occur that could revert carbon flows toward the atmosphere. Of course, ACS-accounting generates credits earlier than the 'ton-year' approach (Figure 1), which is more attractive to projects, unless credit calculations are discounted with a high rate to account for risks and uncertainties.

Temporary crediting

In contrast to the previous methods, temporary crediting does not result in credits that would be fungible with permanent credits issued from projects in the energy sector. Temporary crediting assigns a lifetime to the credits, thus fully recognizing the finite period of time that carbon can be stored in forests (Chomitz, 2000b). Once temporary credits expire, they have to be replaced by the buyer with new temporary or permanent credits.

The original Colombian proposal of temporary crediting (UNFCCC, 2000) assigns a variable lifetime to the credits, depending on the period of time between credit issuance and tree harvesting or project expiration. This option is similar to the lCER method, proposed by COP-9.

Most likely, there would be a market preference for permanent and long-lived credits, which would differentiate their price and would lower, in particular, the price of short-term credits. International bookkeeping of transactions of credits with different lifetime and expiration date will certainly not be easy. Another issue is that credits with long lifetimes would be risky for the climate, since they would be awarded at the beginning of a projected lifetime.

A variation of the Colombian proposal presented by the European Union (UNFCCC, 2002) is to assign the same lifetime to all temporary credits, for instance 5 years. Periodically, carbon removals would then be verified, and if they were still present at each verification, new temporary credits would be issued accordingly or, respectively, the original credits would be renewed for additional 5-year time periods. This option is called tCER in the COP-9 decision.

As Figure 2 shows, before COP-9 different interpretations of this accounting method were possible. The different interpretations have implications for the climatic risk associated to the credits. A first interpretation (tCER1) is that credits would be awarded for the current removal at the time of verification. It assumes that on average the verified removals existed previous to the date of verification for a period of time half as long as the credit lifetime, and that they would be maintained for the other half. For the sake of simplicity, credits issuance is only represented for year 20. The curve shows carbon removal, the arrow shows the amount of credits issued at year 20, and the gray box shows the 5-year removal for which credits are issued A more conservative option (tCER2) would be to calculate the credits as the average carbon quantity stored during the period of time as long as the credit lifetime and preceding the verification. This interpretation eliminates the risk of overestimating the amount of carbon stored by the projects over time and is safe for the climate because the verified removals would not have to be maintained after the point in time that their existence has been verified. Of course, this second interpretation results in slightly less credits for the projects than the previous interpretation does (Figure 2).

The most conservative option (tCER3) is the issuance of credits for the minimum removal observed during the period of time as long as the credit lifetime and preceding verification. For a specific crediting period, tCER3 will result in fewer credits than the two other alternatives or, in some cases, in the same amount as tCER1 but with a 5-year delay in issuance. Therefore tCER3 has no advantage for the project compared with the two other options. For this reason, the model developed in this study will not use tCER3.

None of these interpretations addresses the problem of the price of temporary credits. If the price of permanent carbon credits (CERs) increases in the future, Annex I countries will have little or no incentive to buy short-lived carbon credits because at their expiration these would have to be replaced with new and more expensive credits [START_REF] Chomitz | Temporary sequestration credits: an instrument for carbon bears[END_REF].

Risks for the climate associated with issued carbon credits are different from those associated with projected credits as defined during the project design stage [START_REF] Dutschke | Risk for Forestry Investment under the Clean Development Mechanism[END_REF]. At the project design stage, risks and uncertainties are associated with all accounting methods. At the project verification stage, when credits are awarded to the projects, uncertainties are lower because data from monitoring become available. However, the associated risk for the climate is strongly related to the accounting method used.

There are few risks for the climate when using 'ton-year' crediting (provided the concept of equivalence time is accepted and defined) or temporary crediting of the average quantity of carbon stored in the past period of time (tCER2). There are slightly more risks when using the other interpretation of temporary crediting (tCER1), and there is a higher level of risks when using equivalence-adjusted crediting (ACS). Risks exist only for methods that require assumptions about the future evolution of removals during a specific 'uncertainty time': the longer the 'uncertainty time' the higher the risks. Accounting methods that require this type of assumptions should therefore be complemented by appropriate methods to account for risks and uncertainties, such as the issuance of insured credits, as proposed by Canada (UNFCCC, 2003).

Another issue of relevance for carbon credits accounting is the duration of the crediting period, which is the period of time during which the project baseline is considered as valid and credits can be issued. COP-9 decided to limit the validity of the baseline of CDM forestry projects to a period of 20 years, with two options of renewal (for a maximum crediting period of 60 years), or 30 years without option of renewal. As this decision was not yet available at the time this study was prepared, the crediting periods considered here are of 10, 30, and 50 years.

Model and assumptions

The purpose of the model developed in this study is to calculate the minimum area at which CDM plantations would be viable, taking into account the following factors:

• Plantation project: management (plantation density, thinning, harvesting); environment and trees (wood density, carbon fraction, growth, allometric equations, expansion factor, and natural mortality rate); spatial arrangements and economics (project duration, number of stands, economic discount rate).

• CDM-modalities: accounting methods, period of validity of the baseline (crediting period), and interval between verifications.

• Carbon market: price of carbon credits (CERs) and its variation rate, transaction costs (project design, validation, monitoring, and verification), and share of proceeds (national and international levy on CDM credits).

The model represents the point of view of the project and does not take into account the use of credits by Annex I countries. Consequently, the model does not consider the commitment periods in which credits are issued, neither does it consider the possibility of different future rules in the international regime on climate mitigation.

To be able to consider the effects of all factors on the minimum area of the projects, simulation scenarios were calculated for a hypothetical plantation project as shown in Table 1.

The minimum area estimated for each scenario was defined as the area at which the present value of transaction costs would be equal to the present value of the revenues from CER sales. Through a Visual Basic program written in-house, 7776 sets of parameters (scenarios) were calculated using all combinations presented in Table 2. The values of transaction costs were obtained from interviews with experts, literature review [START_REF] Michaelowa | Transaction costs of the Kyoto Mechanisms[END_REF], certification agency data, and existing project case studies. The model used the estimated current CER price (US$3/tCO2e) and three higher prices [START_REF] Grütter | Greenhouse Gases Market Trends: Third Quarter 2002[END_REF].

The model includes important assumptions about risks, monitoring, and the price of tCERs. It assumes that risks depend on an annual risk factor (characterizing the local situation) and on an uncertainty time related to the accounting method. When calculating credits with the 'ton-year' and the tCER2 methods, there is no uncertainty time and therefore no risks, as the issuance of credits is totally ex post.

For the ACS method, the uncertainty time is the period of time between project verification and project end. For the tCER1 method, the uncertainty time is half the credit lifetime (or half of the interval between verifications).

The risks are taken into account by discounting a part of the carbon stored. The discounted quantity can be interpreted as the cost of insuring the credits, or as a buffer or insurance stock, usable in case of unexpected carbon stock decrease.

Regarding carbon monitoring, the model assumes that it would be carried out only at the years of verification and during the crediting period.

For the price of temporary credits, the model uses the Equation ( 3):

( 3 )

where $tCER is the price estimated for temporary credits, $CER1 is the current market price for permanent CERs, $CER2 is the future market price of permanent CERs (at the time when tCERs expire), and i is the discount rate.

Equation ( 3) shows that if the price of permanent CERs raises more quickly than the discount rate i, then the price of tCERs would turn out to be negative. In this study, since $CER2 cannot be known, we assumed three scenarios: constant CER price ($CER1 = $CER2), increasing or decreasing CER price (plus or minus 3% annually). In the model, the variation rate for the CER price was only used in the calculation of tCER prices and can be interpreted as the perception of future price variation rate by the buyers of credits.

Other model assumptions are that the baseline is zero, leakage is zero, project length is 75 years, equivalence time is 100 years, and the share of proceeds is 7% (2% for the Adaptation Fund, and 5% for national and international administrative costs of the CDM).

Results

The planted forest stand simulated in the model reaches a total removal of 140 Mg of carbon per hectare (or 520 Mg of CO2 per hectare) after 25 years in the aboveground biomass, which is the only carbon compartment taken into account in this study. The average removal during a rotation is 45 Mg of carbon per hectare or 166 Mg of CO2 per hectare.

On average, in the whole multiple-stand plantation project, the removal increases during the first 25 years as the stands are being successively planted, and stabilizes around 170 Mg of CO2 per hectare (Figure 3). According to the 7776 simulations, the minimum area for carbon trading being profitable to the project varies between 100 ha and more than 1 million ha, depending on the combination of parameters and accounting methods used. The median value is 4200 ha, which corresponds to an equivalence-adjusted average removal of 530,000 Mg of CO2 during the 75-year project lifetime. Interpreting project scale in terms of CO2 is not easy, as distinct indicators are often used, such as the cumulated net removal or the total removal over lifetime (IPCC, 2000). For this reason, the following results will be expressed in terms of area.

Only 7.1% of the parameter sets allow that projects smaller than 500 ha take advantage of the CDM, and only 18.5% for projects smaller than 1000 ha.

The model results differ according to the carbon credits accounting method. The median value of the minimum area is the lowest for the tCER1 method and the highest for the 'ton-year' method (Table 3). The latter method does not allow projects smaller than 500 ha to be profitable within the CDM, whereas the former method allows them in 13.7% of the simulations. Assuming a CER price of US$3/tCO2e, a crediting period of 50 years, and standard or average values for the other parameters (economic discount rate: 6%; design and validation cost: US$80,000; monitoring cost: US$4,000 + US$0.2/ha; verification cost: US$30,000; risk discounting: 1% annual; verification interval: 5; share of proceeds: 7%), projects smaller than 1000 ha cannot profit from the CDM. Even with lower transaction costs (half of the previous ones), projects smaller than 500 ha cannot profit from the CDM.

The dependence of net benefits from carbon selling on the total project area was estimated for the current value of CER price (US$3/tCO2e), a crediting period of 50 years and standard or average values for the other parameters, as specified above. With the assumption of constant CER prices, the two tCER methods appear to be the most profitable for the project. They allow projects of approximately 1400 ha to gain advantage from the CDM, whereas the limit is around 3500 ha for ACS and 7000 ha for 'tonyear'.

If CER prices increase, the price of tCERs would be lower and the tCER method would be less profitable for the project. Using the same parameter set as specified above, and assuming a hypothetical increase rate of CER price rate of 4.5%, the model shows that the profit for the project would be higher with the ACS method than with the tCER method. Under these assumptions, the tCER accounting methods would be of benefit only to projects larger than 5000 ha, compared with 3500 ha for ACS.

We define the 'best' accounting method as the one that allows the smallest projects to benefit from the CDM. The tCER1 method is the best method in 65% of the simulations and the ACS method is the best in 39% of the simulations (the sum is more than 100% because two methods may give the same best result). The two other methods can be qualified as the best methods in very few cases (6% for tCER2 and 1% for 'ton-year'). The 'ton-year' is the best method only when risk discounting disadvantages the ACS method and increasing CER prices disadvantage the tCER method.

Due to the equation used to calculate the price of tCERs, the results of the tCER methods are highly dependent on the CER price variation. Assuming constant CER prices, the tCER1 method is definitely more profitable for small projects as it is the best method in 75% of the simulations, compared with 31% for ACS. However, if the price of CERs was expected to increase, the ACS method would be the best in 66% of the simulations, compared with 38% for tCER1.

The CER price variation is not the only factor that determines the best method. With high risk discounting, the ACS method is disadvantaged and turns out to be the best method in only 17% of the simulations, compared with 85% for tCER1. If risk discounting is zero, 61% of the simulations show that the ACS method is the best one, compared with 46% for tCER1.

Under 'extreme conditions', unfavorable for CDM projects, the tCER1 method appears to be the best, except when the price of CERs increases (Table 4). In this case, the disadvantage of the tCER1 method is very high compared with the ACS method: the minimal project scale is respectively 14,550 ha and 3000 ha.

The most limiting extreme condition is related to the crediting period: if it were limited to only 10 years, only very large projects would benefit from the CDM (Table 4).

Discussion and conclusions

Only long crediting periods allow small to medium sized projects to benefit from the CDM, particularly crediting periods longer than the stand rotation cycle. Most likely, a 20-year crediting period will result in large projects, promote the use of fast-growing species, and increase the likelihood of negative socioeconomic and environmental impacts of CDM forestry projects. As only long crediting periods encourage the use of native species, the establishment of near-permanent forest, and the participation of smaller projects, longer crediting periods should be considered in the forthcoming discussions on the post-2012 period. Our analysis of accounting methods suggests that if carbon accounting methods were to be reconsidered for the second commitment period, the discussion should focus on the ACS and tCER methods, since the 'ton-year' method would make carbon selling a very poor incentive for forestry projects.

The climatic risks associated with the ACS method require the establishment of a clear liability regime. This regime would specify how much compensation would be required in the case that the carbon credited would be involuntarily or deliberately re-emitted. This liability regime could be based on the 'ton-year' method to calculate the project contribution to climate change mitigation up to the moment of carbon re-emission. Under this approach, liability would not last forever and credits could be bundled with an insurance coverage for a limited period of time. Provided that the concept of equivalence between avoided emissions and temporary removal is accepted and defined, the amount of ACS credits to be insured would decrease over time as the cumulative ton-year line increases. Liability would end when the cumulative ton-year value is equal to the ACS amount (Figure 1).

TCER methods appear to be more appropriate to address the non-permanence of carbon in forests. However, the lower price of expiring CERs may not be sufficient to motivate the establishment of CDM forests, particularly of smaller ones.

From a climatic point of view there is no reason to decide on a single accounting method. Therefore, the possibility of letting the project decide about the most convenient accounting method should not be excluded a priori. According to the intended project duration, the local risks of non-permanence, the availability of insurance providers, and the expected variation of CER prices, a project may choose one or the other accounting method. This flexibility may help more initiatives to participate to the CDM after 2012.

The high transaction costs generated by the modalities and procedures of the CDM and the few credits resulting from the different accounting methods appear to exclude small plantation projects from the CDM. Because of equity and leakage considerations, and because small-scale projects are more prone to induce positive impacts on sustainable development than large projects, there is an interest in proposing regulations and institutional arrangements that would facilitate the participation of smallscale projects. The challenge is how to define these rules without increasing climatic risks and transaction costs. The discussion on simplified modalities and procedures for small-scale projects has so far not provided evidence that significant transaction cost savings can be made in the case of CDM forestry projects. Eventually, more attention should be given to measures to facilitate the implementation of small-scale projects, such as bundling of small-scale projects under an umbrella organization. Such bundling may facilitate the participation of small and medium stakeholders in the CDM as economy of scale and knowledge concentration becomes possible. However, this type of organization requires important institutional capacities, as large numbers of small projects must be managed and coordinated. Furthermore, host countries might have to design and implement innovative financial schemes to create incentives for small forest plantations. The entity managing such umbrella projects and incentives could finance small projects under its proper rules and, at the same time, sell carbon credits under the CDM rules. The challenge is to develop schemes that are real incentives for small plantations and that guarantee the long-term financial viability of the umbrella organization.

The participation of small forestry projects might be eased by the addition of other climate-related activities, such as energy mitigation activities or adaptation activities. The combination of a small forestry project with an energy project producing electricity from woody residues may allow the generation of permanent credits and a more effective contribution to sustainable development. Indeed, under some conditions, this type of arrangement would provide constant energy to the local population and at the same time avoid emissions from fossil fuel consumption and develop or maintain plantation areas as a result of a permanent wood demand.

Figure 1 .

 1 Figure 1. Net removal (thin gray line; Mg CO2e/ha), cumulated 'ton-year' credits (dotted line; Te = 100 years), and cumulated ACS credits (thick black line; Te = 100 years) for a 25-year rotation plantation, 75-year project

Figure 2 .

 2 Figure 2. Removals and tCER credits (all interpretations): tCER1, current removal at verification time (year 20); tCER2, average removal during past verification interval (years 15-20); tCER3, minimum removal during past verification interval (years 15-20). For the sake of simplicity, credits issuance is only represented for year 20. The curve shows carbon removal, the arrow shows the amount of credits issued at year 20, and the gray box shows the 5-year removal for which credits are issued

Figure 3 .

 3 Figure 3. Net removal (Mg CO2e/ha or tCO2e/ha) in the whole plantation for Years years 0-75

Table 1 .

 1 Summary of features of the hypothetical project

	Parameter	Value
	Project duration	75 years
	Rotation duration	25 years
	Total plot number	25
	Initial plantation density	1500 trees per hectare
	Thinning	45% of the trees removed at year 5, 35% at year 10, 25% at year 15
	Natural mortality	2% per year
	Diameter growth (m/year) 0.0018 between years 0-25; 0.009 between years 25-35; 0.005 after year 35
	Height growth (m/year)	1.8 between years 0-20; 1.1 between years 20-30; 0.4 after year 30.
	Allometric equation	Commercial volume = 0.2 D²H (D is diameter in m, H is height in m).
	Expansion factor	1.55 (total volume/commercial volume)
	Wood density	0.45 (tons of dry wood per m3)
	Carbon ratio	0.5 (carbon weight/dry wood weight)

Table 2 .

 2 Sets of parameters used in the model

	Parameter	Range

Table 3 .

 3 Some key factors describing the distribution of model results according to the carbon credits accounting method

	Method Median
	value (ha)

Percentage of the simulations allowing projects smaller than 500 ha to be profitable in the CDM Percentage of the simulations allowing projects smaller than 1000 ha to be profitable in the CDM

	Ton-	11,000	0	2.8
	year
	ACS	3,000	5.1	17.7
	tCER1	2,300	13.7	30.2
	tCER2	3,250	9.7	23.1

Table 4 .

 4 Median value of minimum project area under extreme conditions

	Extreme condition	Median value of minimum project area (ha)
		With ton-	With	With	With	All
		year	ACS	tCER1	tCER2	methods
	The crediting period is only 10 years	275,000	14,200	3,000	50,000	50,000
	The CER price is only US$3/tCO2e	30,000	6,750	4,500	6,550	8,900
	The transaction costs are the highest	18,550	5,650	3,700	5,000	8 , 3 0 0
	The risk discounting is the highest (2%	11,000	5,150	2,400	3,250	5,300
	annual)
	The CER price is foreseen to increase 3%	11,000	3,000	14,550	30,000	7,300
	annual
	Without any condition (all simulations)	11,000	3,000	2,300	3,250	4,200

This article was written and submitted for publication before COP-9.