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Chapter 14 | 1 Despite this idyllic perspective on a landscape with forests on the higher slopes, mid-slope coffee gardens and rice fields in the valley, the Sumberjaya landscape became a focus for evictions, before it became the starting point of negotiated solutions. Photo: World Agroforestry Centre/Meine van Noordwijk Suggested Citation: Kerr J, Verbist B, Suyanto and Pender J. 2017. Placement of a Payment for Watershed Services Program in Indonesia: Social and Ecological Factors. In: Namirembe S, Leimona B, van Noordwijk M, Minang P, eds. Co-investment in ecosystem services: global lessons from payment and incentive schemes. Nairobi: World Agroforestry Centre (ICRAF).
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Page 1: forests on the higher slopes, mid -slope coffee gardens ... · Agroforestry Centre/Meine van Noordwijk Suggested Citation: Kerr J, Verbist B, Suyanto and Pender J. 2017. Placement

Chapter 14 | 1

Despite this idyllic perspective on a landscape with forests on the higher slopes, mid-slope coffee gardens and rice fields in the valley, the Sumberjaya landscape

became a focus for evictions, before it became the starting point of negotiated solutions. Photo: World

Agroforestry Centre/Meine van Noordwijk

Suggested Citation: Kerr J, Verbist B, Suyanto and Pender J. 2017. Placement of a

Payment for Watershed Services Program in Indonesia: Social and Ecological Factors. In: Namirembe S, Leimona B, van Noordwijk M,

Minang P, eds. Co-investment in ecosystem services: global lessons from payment and incentive schemes. Nairobi: World Agroforestry

Centre (ICRAF).

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Chapter 14 | 1

CHAPTER 14 Placement of a payment for watershed services program in Indonesia: Social and ecological factors

John Kerr, Bruno Verbist, Suyanto, and John Pendera

Highlights • Conditional tenure agreements in watershed protection forest can reduce conflict and

provide real incentives.

• Social connectivity and agency played clear roles in the start of the program with selected communities.

• Specific knowledge of erosion hot spots played no role in either the initiation or evaluation of pilot agreements.

• Underlying geology determines environmental services, with modest roles for land cover and management.

• The scheme only partially matches the PES definition in terms of being realistic and conditional, but it provides a win-win option for previously conflicting parties.

14.1 Introduction

A debate in the literature on payment for environmental services (PES) concerns whether it can be used widely as an instrument of government conservation policy, or if it is better suited as a niche approach where a specific buyer can undertake an agreement with specific land users who can provide an environmental service of value to the buyer1,2,3. PES potentially offers a powerful means to secure conservation by creating direct economic value for land users to protect natural resources that otherwise would be of value only to others4. This is an important contrast to alternative approaches, like land-use regulations that may be difficult to enforce, subsidies that have little impact on incentives after the initial investment, or integrated conservation and development projects that only indirectly affect economic incentives and may bring perverse effects.5

On the other hand, the ability to utilize PES widely as a policy instrument is limited because identifying and measuring environmental services—especially watershed services—and linking them to a particular land use is often difficult and costly6,7. In a large-scale program, such knowledge always will be imperfect and trade-offs in program design are unavoidable8. Identifying whether a given environmental service is actually under threat is also difficult,

a The views expressed are those of the authors and should not be attributed to the Economic Research Service or USDA

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2 | Placement of a payment for watershed services program in Indonesia: Social and ecological factors

raising the likelihood that some payments will be made to land managers who would have provided the service even without the payment, while failing to alter the behaviour of some land users who find environmental destruction to be more profitable than conservation. National programs in Mexico9 and Costa Rica10 faced precisely this problem. In short, the same factors that limit the spontaneous emergence of markets for some environmental services like watershed protection or biodiversity conservation constrain their widespread use in policy. Learning how to overcome these challenges will be required.

Young stages of coffee gardens are open and prone to erosion in the Sumberjaya landscape Photo: World Agroforestry Centre/Meine van Noordwijk

In any government program, social factors also determine where projects operate. When a government program is established, potential participants must be aware of it and they must know how to access it. Differences in such knowledge by potential participants will play a role in determining where a program operates.11

This chapter examines program placement in the early implementation phase of Indonesia’s Hutan Kemasyarakatan (HKm) community forestry program, in which groups of farmers living on government forest land are granted secure tenure conditional on using the land in a way that protects a watershed against erosion12. It analyses the confluence of two sets of factors: 1) biophysical conditions that determine which lands are best equipped to provide the environmental service in question, and 2) social and institutional factors that led the program to be placed in certain areas as opposed to others. We offer a case study in which placement follows social forces rather than biophysical criteria, and we discuss some implications. We anticipate that this is typical of payment for watershed services programs because carefully assessing which locations best deliver environmental services is very complex and time-consuming, as can be seen in this paper. The analysis draws on a combination of catchment-level suspended sediment yield assessments to identify watershed services and their sources, and a community-level survey to identify social factors associated with becoming aware of and attracting the program.

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Chapter 14 | 3

First meeting between local government officials and one of the contested village. Photo: World Agroforestry Centre/Meine van Noordwijk

Award ceremony for conditional tenure agreements for the forest margin. Photo: World Agroforestry Centre/Suyanto

14.2 Environmental service program placement

14.2.1 Soil erosion, siltation, and watershed services

The main functions of watersheds from a downstream perspective are to provide an adequate supply of high-quality water while avoiding soil transport or flash floods13,14. Differences in rainfall patterns, slope, soil characteristics (influenced by the underlying geology) and land use are generally considered to be the primary determinants of watershed function. Soil types vary in their infiltration and water-holding capacity and their susceptibility to erosion. For soils more prone to erosion, vegetative cover or a layer of leaf litter15 help protect against erosion.

In humid tropical areas such as most of Indonesia, forest is the original land use and watershed functions can be altered when other land uses replace forest. Forest thus has been widely accepted to be the land use capable of maximizing the watershed functions listed above. This belief underpinned legislation in colonial Indonesia16,17, with further refinement after independence in the Suharto era. In the 1990s in Sumberjaya, the study area for this paper, this belief led to the eviction of thousands of coffee farmers when the government was planning to build a hydroelectric dam18. The logic was that if land use reverted back to natural forest, water delivery would increase and siltation, filling up the storage lake, would decrease.

Research has shown that the type of land use that replaces forest is more important than deforestation itself: if the infiltration and water-holding capacity of the soil are reduced, it is likely that dry-season flows will be affected. As forests have higher evapotranspiration rates than most other land use types such as annual crops or agroforestry systems, the balance between reduced evapotranspiration on one hand and lower infiltration on the other will determine the effects on watershed function of deforestation and land-use change.19,20

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4 | Placement of a payment for watershed services program in Indonesia: Social and ecological factors

Erosion from slopes is partially captured in rice paddies in the valley. Photo: World Agroforestry Centre/Meine van Noordwijk

Part of the reason for the persistence of popular belief is that there remains a scarcity of research showing clearly the determinants of watershed function. Worldwide there is a long history of plot-level soil erosion research, which in Indonesia expanded dramatically in the 1970s21. The fact that sediment yield was rarely assessed at the catchment level or at different scales caused discrepancies between measurements at the plot and catchment or basin level that remained unnoticed by policymakers for a long time. At a larger scale, sediment contribution from gullies, bank erosion, mass wasting etc. can play a significant role and plot-level research cannot capture the sediment yield of these processes. Scaling rules as envisaged are not straightforward, although modelling allows prediction of the most efficient position of ‘filter elements’, for example trees controlling sediment loss.22

Measurements at catchment level integrate over different scales and implicitly include the assessment of filters. Dominant processes with negative off-site effects at one scale can be mitigated by filters at another scale. Understanding these relationships is essential for the efficient operation of watershed service programs, which requires offering contracts at the specific location and using the specific land uses that can best influence watershed function.

14.2.2 Socioeconomic determinants of program placement

Governments organize programs for two main reasons: to serve some perceived need and/or to satisfy a political constituency. To the extent that the aim is to serve a particular need, for example provision of watershed services, program officials need to gather the available knowledge about where the need exists and then locate the program accordingly.

Locating an environmental services program requires identifying the location and land use that yield the environmental service, and then identifying a reward mechanism to induce that land use. This is straightforward in principle but difficult in practice, in part because of the scientific uncertainty described above but also because of challenges in identifying the people who control the land use and ensuring that the reward yields the environmental service.1

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Chapter 14 | 5

Many environmental service programs also have a poverty alleviation component. Incorporating poverty alleviation is attractive because many inhabitants of environmentally sensitive areas are poor, and paying them to protect natural resources that provide environmental services is seen as a way to achieve the dual objectives of raising the incomes of the poor while also providing environmental services. In practice, often there are trade-offs between the two objectives1,10,23 but the basic targeting idea remains the same.

Once the government decides where to place a program, local people must be able to access it. Simply because a program operates in a given district does not automatically mean that it will operate in a given village within that district, and just because it is located in a particular village does not mean it will serve every household in the village. For example, local people may be required to meet certain preconditions or to complete an application and may not know how to do so.

Accessing and implementing a government program requires agency and social capital11. Agency refers to the ability to act and bring about change. Social capital is the set of social relationships that enables groups to work collectively. Often social capital is divided into different forms: bonding, which enables people to work collectively within groups of similar people to accomplish something; bridging, which enables people to work across groups of dissimilar people, and linking, which enables them to access people in positions of power24. Social capital may enable a person to learn about a program or gain access to people who can deliver it, while agency enables the person to take advantage of opportunities that arise. Social capital plays additional roles in the context of group- or community-level programs. Linking social capital can enable a community leader to attract a program for the benefit of fellow community members and bonding social capital can play a role in bringing a group together to undertake the project. In India, research11 established that leaders who could help identify and access special government programs and bring them to their villages contributed to better village-level economic performance. These leaders possessed the agency to attract the programs and social capital to harness them for local benefit. In Mexico, PES program placement was found to be related to community capacity including the skills of the leadership and connections to NGOs.25

In the context of HKm, we hypothesize that social capital and agency play a similar role in bringing access to the HKm program. This leads us to ask if there are identifiable factors that characterize those groups that have come together to benefit from HKm. Similarly, do communities with good connections to the right people gain access to HKm before others?

14.3 Sumberjaya and HKm

Sumberjaya is a watershed (or catchment) in West Lampung District of Lampung Province in the southern part of the island of Sumatra (Figure 14.1). It is situated between 104°25’46.5”–4°26’51.4” E and 5° 01’29.9”–5° 02’ 34.2”. It has been inhabited since about 1884, when the Semendo people first settled in the area and practiced shifting cultivation26. The development of Sumberjaya started in earnest in 1951 with the national transmigration program in which people from the densely settled island of Java were moved to different islands. Sumberjaya’s three main ethnic groups are Javanese and Sundanese (both from Java) and Semendo (from southern Sumatra). Migrants often follow their ethnic kin and many villages are mostly homogeneous, but others are more mixed. Sumberjaya contains a combination of private land, protection forest (state forest land classified as such in order to protect watersheds), and a corner of the Bukit Barisan Selatan National Park, which was established in 1982. The protection forest zones were installed with the publication of a government land-use map in 1990. The map appears to have reproduced forest maps from the Dutch colonial era and

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6 | Placement of a payment for watershed services program in Indonesia: Social and ecological factors

unilaterally revoked decrees from earlier Indonesian authorities that transferred some land-use rights to local people18. Private lands in the lower reaches contain rice paddy land, with the surrounding slopes devoted mostly to Robusta coffee gardens.27

High coffee prices on the world market after the 1975 frost in Brazil triggered the expansion of coffee plantations to what was later classified as protection forest and the national park. In the early 1990s, the Government of Indonesia, under former president Suharto, forcibly evicted people from much of the protection forest area as mentioned above18. With generally poor resettlement conditions, many evicted farmers returned within a year to remove the newly planted forest trees and re-establish their former coffee gardens.

Figure 14.1 Map of Lampung province with the Sumberjaya subdistrict with an inset of Indonesia

In the late 1990s, the convergence of several factors attracted a new wave of settlers to Sumberjaya. The Asian financial crisis left many people jobless, the Suharto government fell, and the steep depreciation of the Rupiah had a large upward effect on domestic coffee prices18. The new government introduced a program of reformasi (reform), which aimed to be more decentralized and people-friendly.

HKm is based on a decree from the Ministry of Forests specifying that production forests (officially designated for timber production) and protection forests that have already been deforested are eligible. Under the program, groups of people receive use rights on eligible state forest land if they promise to intercrop their coffee trees with other tree species in a multistrata agroforestry system, conserve soil and water, and protect remaining natural forest areas. This arrangement is illustrative of the reformasi approach to governance and is

consistent with what the World Agroforestry Centre (ICRAF) terms kebun lindung, i.e. achieving watershed protection through agroforestry as opposed to natural forest. HKm contracts last an initial 5-year probationary period before possibly being extended for another 25 years.

The first HKm contracts in Sumberjaya were initiated in 2000. By 2005, six contracts were in place in Sumberjaya, covering an area of about 2000 ha, with an additional 23 groups covering about 13,000 ha in the process of applying for HKm. In 2005, a total of 10 HKm contracts were

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Chapter 14 | 7

in place in all of West Lampung district. Nationwide, the total area under HKm was 50,644 ha in June 2006. In July 2006, 12 new groups in Sumberjaya comprising 5,283 farmers received conditional land tenure for five years, bringing the total in Sumberjaya to 11,633 hectares, about 70 percent of the protection forest area.28

The process was more advanced in Sumberjaya than elsewhere, most likely because of ICRAF, which helped promote the program and supported negotiations between communities and government29. ICRAF’s involvement was part of the RUPES (Rewarding Upland Poor for Environmental Services) project, which conducted action research to address possibilities for payment for environmental services in Asia under funding from IFAD, the International Fund for Agricultural Development.28

HKm contracts covered groups of people who had settled in the area. All group members in Sumberjaya were people who previously had customary tenure. The only people excluded were those who migrated away from the area and did not return; interviewees indicated that such people could negotiate their way into an HKm group if they were to return to the area.

The application for an HKm permit involved several steps. People using a contiguous area of protection forest land formed a group and then submitted a proposal to the Forest Department. The proposal was required to include a map of the proposed area (assembled by the group with assistance from the Forest Department) indicating the area where they could plant coffee and the natural forest area that they would protect against logging and forest fires. They agreed to a contract specifying the tree composition of the multistrata coffee plots they would maintain, and they agreed to implement prescribed soil and water conservation practices. The contract required planting a combination of at least 400 timber and fruit trees per hectare in the coffee gardens, with some flexibility regarding which species to plant. Required soil conservation measures included terraces, sediment pits, grass strips, and planting along the contour. In some areas group members had to pay an annual fee, but the fee varied by district. On the basis of these terms, the groups received a conditional HKm permit for five years, after which they were to be evaluated and may become eligible for a longer-term (25–year) permit.

14.4 Data and methods

This study combines the findings of sediment yield estimations for 10 catchments in the Sumberjaya watershed with the findings of a socioeconomic survey that explores the determinants of how the HKm program spread. It then displays the overlay of the areas best able to provide watershed services with the areas where the program actually was placed. The paper only summarizes the findings of the sediment yield estimations, which are reported in detail elsewhere.30,31

For the purposes of analysis and presentation, land is categorized into five administrative strata as shown in Figure 14.2:

1. National Park land; 2. Private land; 3. Protection forest land with an HKm permit at the time of the 2005 survey; 4. Protection forest land with an HKm permit application in process in 2005; and 5. Protection forest land eligible for HKm where no application had been made.

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8 | Placement of a payment for watershed services program in Indonesia: Social and ecological factors

Figure 14.2 Land status strata in Sumberjaya based on the community survey. The upper Way Besai catchment area upstream of the hydropower dam is marked with the bold black line

Only protection forest land was eligible for HKm. Dividing it into three categories enables analysis of the socioeconomic factors that shaped how the program spread. The sediment yield analysis examines the sources of sediment as determined by topography, geology, soil and land use, and then overlays the findings onto the five land strata to assess the overlap between sources of sedimentation and placement of the watershed services program.

14.4.1 Estimation of sediment yield at catchment level

Catchment-level sediment yield assessment combined detailed data collection in which rainfall, discharge and suspended sediment were measured at several places along the Way Besai river and its most important tributaries (Figure 14.3), and a modelling exercise to translate the data into a prediction of sediment yield. This section summarizes the procedures, detailed elsewhere23. Data collection took place between 2005 and 2007. Points for measuring discharge and suspended sediment were selected at existing or self-constructed bridges.

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Chapter 14 | 9

Figure 14.3 Topographic map of Sumberjaya with the upper Way Besai catchment with main rivers, location of measuring spots with continuous discharge measurements and the highest mountains; the circle indicates the confluence of the Air Hitam and Way Besai

Confluence of the Air Hitam (bottom) and the Way Besai (upper half). Note the clear water of the Air Hitam joining the sediment loaded water of the Way Besai. Photo: KULeuven/Bruno Verbist

Collection of depth-integrated runoff and suspended sediment samples at WB8. Photo: KULeuven/Bruno Verbist

A series of continuous streamflow data were constructed for 10 subwatersheds within the larger Sumberjaya watershed between 1 March 2006 and 28 February 2007. At each site, the cross profile was measured and a staff gauge and a water level sensor were installed. Flow velocity measurements were regularly taken with a flow probe to derive a stage-discharge rating curve for each of the 10 outlets of the subcatchments to convert water level to streamflow discharge. Eventual gaps in the continuous streamflow data were filled using the rainfall data from 19 automatic tipping bucket rain gauges and the VHM model.30

Suspended sediment samples were taken at monthly intervals during the wet season and parts of the dry season. Event-based sampling was included through two intensive one-week

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10 | Placement of a payment for watershed services program in Indonesia: Social and ecological factors

sampling campaigns (12–18 Feb 2005 and 6–12 Feb 2006) during the wet season to focus specifically on high floods when most sediment is being transported.

Sediment rating curves were developed to relate suspended sediment yield with discharge for a certain location at a particular river32,33. Details of the procedure, including bias correction factors and the application of multiple estimation methods to reduce error are described in detail elsewhere30. Bedload was not measured but estimated as 10 percent of the total sediment yield as is often used in studies in Indonesia and was confirmed in a study in the Konto area34. The Konto area is comparable to Sumberjaya in soils, rainfall and land use.

To delineate the catchment boundaries, a digital elevation model (DEM) was derived from a 1:50,000 scale topographic map. Corrections to boundaries and the position of rivers were made using field observations and a more accurate second DEM that covered only 60 percent of the 415 km2 Way Besai catchment. As some of the monitored catchments are nested, an overlay of the sediment yields per subcatchment provides more detailed and mutually exclusive information on which areas produce more sediment. The net catchment areas are presented in Table 14.5. Sediment yield could be estimated for a total area of 369 km2.

For each subcatchment, 27 variables were derived in four main categories (topography, geology, soil and land use). For topography these were catchment area, slope, hypsometric integral, relief ratio, streampower and wetness index. For soil the variables were average soil bulk density, and percentage sand, clay or silt for a depth of 0–20 cm. For geology these were andesites, dacites, old andesites, granites, Ranau tuff and alluvium. For land use these were forest, horticulture, paddy rice, settlement, shrub, (monoculture) sun coffee, simple shade coffee (with 10–75% coverage of shade trees), and multistrata coffee with more than 75% shade tree cover. Stepwise regression and the Akaike Information Criterion (AIC)35 were used to identify the most dominant factors on differences in sediment yield.

14.4.2 Socioeconomic surveys

Data for analysis of the socioeconomic determinants of program placement were collected through surveys at the level of the village, HKm group and household. The survey data presented here address factors related to how communities learned about the program, formed into the groups eligible to apply for the program, went through the application process, and obtained the license. The emphasis is on questions related to social capital and agency11. The village survey was conducted in all of the villages in Sumberjaya with protection forest, and the HKm group survey covered all of the groups that, at the time of the survey, had obtained an HKm permit or were in the process of applying for one. These interviews were conducted with village leaders and group leaders using a semi-structured, mostly qualitative format. At the village level, questions were designed to address the factors affecting the emergence of HKm groups, including awareness of the program and formation of groups to apply for HKm permits. At the HKm group level, questions focused more on the process of forming the groups and applying for permits, including the enabling factors for forming groups.

The village and HKm group surveys covered 21 of the 28 villages in Sumberjaya (the other 7 villages did not have any protection forest and hence were not eligible for HKm), and 29 groups that formed to apply for an HKm permit. At the time of the survey, 6 groups had obtained the permit, 2 had formally applied, 9 had begun preparing the application but had not yet submitted it, and 12 were just beginning the application process. The Sumberjaya subdistrict covers 54,194 ha, of which 58% is officially state-owned forest land. The total population was about 81,000 in 2000.26

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Chapter 14 | 11

The household survey covered 640 households. The sample was drawn from 80 points randomly selected on private land and national park land, and 160 on each of the three HKm categories of land (with a permit, with an application in progress, and without an HKm group. The operator of the plot covering each sampled point was interviewed. Data covered household demographic composition, education, assets, and participation in HKm and other programs and organizations. For these same households, production and management data were collected on the sampled plot and one other randomly selected plot (where applicable) for use in an analysis of the impacts of HKm.36

Survey data in this paper were analysed using descriptive methods to identify factors associated with the spread of HKm and its anticipated impacts. Statistical tests were performed for household-level analysis but not for village- and group-level analysis because all villages and HKm groups in Sumberjaya were surveyed. Discussion of the data draws upon notes from the survey interviews.

14.4.3 Combination of sediment yield and community and household surveys

ArcGIS 9.x and Arcview 3.2 were used to cross-reference the various GIS layers and identify the intersections among them. They are: (1) the estimated annual sediment yields per subcatchment, (2) the administrative status of the land including the HKm status of protection forest areas, and (3) land use in 2002 as derived from satellite imagery. The overlap between sediment load and HKm status helps indicate the effectiveness with which the program targeted areas that can best provide environmental services.

14.5 Analysis

14.5.1 Sediment yield and filters

Thousands of water samples were taken and the suspended sediment concentration measured. Table 14.1 presents the estimated sediment yield for 10 subcatchments based on a one-year continuous series of hourly streamflow data, converted to an annual sediment yield expressed on a per-hectare basis. Sediment yield for mutually exclusive areas was obtained by multiplying the catchment area by the sediment yield per hectare and subtracting the sediment yield of inclusive subcatchments.

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12 | Placement of a payment for watershed services program in Indonesia: Social and ecological factors

Table 14.1 Estimated sediment yield (SY) for 10 subcatchments in Mg ha-1 yr-1

Cat1 % Qbs Catchment area (km2)

Forest cover (%)

SSY (Mg ha-1

yr-1)

SY (Mg ha-1

yr-1) NSE

WT 38.5 7.71 22 7.4 8.2 0.32

WB4 99.8 84.28 15 2.5 2.8 0.83

AH 100.0 55.01 4 1.1 1.2 0.70

WK 52.7 30.37 12 2.8 3.1 0.78

WR 88.5 7.38 31 12.3 13.7 0.94

WB7 65.0 268.09 11 2.4 2.7 0.37

WCP 45.0 42.58 10 3.0 3.3 0.94

WL 66.6 6.69 37 5.1 5.7 0.99

WB8 99.8 358.25 10 3.5 3.9 0.63

WP 97.2 13.91 29 11.6 12.9 0.78

Source: ICRAF hydrological measurements 2005–200630

1 Abbreviations used in the table are as follows: Cat: Catchment; %Qbs: Percentage of measured hourly discharge values (as opposed to values estimated with the VHM model; SSY: Suspended sediment yield; SY Total sediment yield; NSE: Nash-Sutcliffe Efficiency; WT: Way Tebu; WB4: Way Besai4; AH: Air Hitam; WK: Way Kabul; WR: Way Ringkih; WB7: Way Besai7, a location also known as Sukajaya; WCP: Way Campang; WL: Way Lirikan; WB8: Way Besai8, a location also known as Talang Nangka; WP: Way Petai

These sediment yields are indicative only, as they are based on data from only one year. They are however homogeneous and allow comparison between subcatchments. As the difference between catchments is large (one order of magnitude!), robust conclusions can be drawn on which catchments deliver on average more sediment. It appears that only a relatively limited area (18% of the sampled area) is responsible for the highest sediment yields (Figure 14.4). In the southern half of Sumberjaya (WB4, WB7 and AH), suspended sediment yields are all less than 2.4 Mg ha-1 yr-1. Independent of what sediment rating curve was used, the highest suspended yields (> 5 Mg ha-1 yr-1) were all measured in a belt in the northern half of the upper Way Besai catchment.

Rehabilitation of land degraded with mixed coffee agroforestry. Photo: World Agroforestry Centre/Suyanto

Mixed coffee agroforestry garden. Photo: World Agroforestry Centre/Noviana Khususiyah

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Figure 14.4 Estimated mean annual area-specific sediment yield (Mg ha-1yr-1) for mutually exclusive areas of the subcatchments in the upper Way Besai using a bedload percentage of 10% of the total SY. For subcatchments WB4, WB7 and WB8 the area and sediment yield of the nested catchments were subtracted; the circle indicates the confluence of the Air Hitam and Way Besai

Slope, the old Andesites on Bukit Rigis (a mountain in the middle of Sumberjaya) and the silt fraction consistently appeared as the most important variables from topography, soil, geology and land use that affected sediment yield after various iterative stepwise regressions (Table 14.2). The most important factor, old Andesites, corresponds with the sensitive lithology of the central Bukit Rigis. Perhaps surprisingly, land use did not appear to be a significant factor. In addition, as shown in Table 14.1, the subcatchments with the highest forest cover (WT, WL, WP and WT) were those with the highest sediment yield!

Table 14.2 Results of stepwise regression between sediment yield and the most important variables from topography, soil, geology and land use

Estimate Std. Error t value Pr(>|t|)

(Intercept) -23.01 9.31 -2.47 0.048*

Old Andesite 0.37 0.09 4.19 0.006**

Slope 0.84 0.35 2.40 0.054˙

Silt 0.25 0.12 2.04 0.087˙

˙ Significant at 0.1 level (2-tailed) * Significant at 0.05 level (2-tailed) ** Significant at 0.01 level (2-tailed) whereby the residual standard error: 1.893 on 6 degrees of freedom, Multiple R-Squared: 0.91, Adjusted R-squared: 0.86, F-statistic: 20.09 on 3 and 6 DF, p-value: 0.001567

Besides a dilution effect of tributaries like AH, the large flat floodplain south and east of Bukit Rigis, where the Way Besai is meandering, seems to be able to filter a part of the high sediment flowing in from Way Tebu. The same is likely also of many small catchments on the south side of Bukit Rigis. That flood plain is largely covered with a mosaic of various coffee systems on the slopes and paddy rice in the valleys. The sediment-rich tributaries (WR, WL, WP

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14 | Placement of a payment for watershed services program in Indonesia: Social and ecological factors

and smaller rivers in the WB8 area) however almost directly deliver their sediment into the hydropower storage lake.

Less than 20% of the catchment area produces almost 60% of the sediment yield. The reduction of negative off-site effects on e.g. the life time of a storage reservoir would benefit greatly from an improved assessment of the lithologies in volcanic landscapes and the consideration of potential sediment source and sink areas. The quantification of land use effects on dominant erosive processes such as river bank and river bed erosion, landslides and the concentrated flow erosion on footpaths and roads can contribute to more targeted efforts and relevant incentives to reduce (or live with) sediment load of the rivers.

Table 14.3 Personal relationships that may facilitate HKm, by village1

Source: ICRAF/MSU/IFPRI HKm village survey 1 All villages with protection forest only. 7 additional villages have no protection forest so HKm is not applicable 2 Of these four villages, respondents in one had never heard of the HKm program 3 Indicates the percentage of villages per category with at least one such person 4 The mean number of such people per village, across all villages (not only those with such contacts) 5 Watala is an NGO that ICRAF hired to help promote HKm

Source: ICRAF/MSU/IFPRI village survey

14.5.2 Community survey of factors contributing to program placement

By 2005, nearly all farmers in Sumberjaya’s protection forest area had organized into groups for pursuing HKm agreements. The first groups were formed in 2000 after which the number of groups rose steadily. There was clearly a regional factor at work as word of the program spread quite quickly through the area, partly due to ICRAF’s presence. In 2000, ICRAF and the

Villages with at least one HKm group with permit (n=5)

Villages with group applying for HKm permit (n=12)

Villages with no HKm group (n=4)2

Percent 3 Mean

values4 Percent 3 Percent 3 Percent 3

Mean values4

Forest Department officials live in the village

40% 0.8 25% 0.42 0% 0

Villagers have friends in Forest Department

60% 0.6 17% 0.17 25% 0.25

Other government officials live in the village

80% 2.2 42% 0.92 25% 1.0

Villagers have friends in other govt. offices

40% 0.4 0 0 0% 0

Watala5 officials live in the village

0 0 0 0 0% 0

Villagers have friends in Watala5

40% 0.6 8% 0.08 0% 0

Officials of other NGOs live in the village

0 0 42% 0.67 0% 0

Villagers have friends in other NGOs

20% 0.2 80% 0.08 0% 0

Villagers have personal relationship with outsiders who helped form group

50% n.a. 26% n.a. n.a. n.a.

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local NGO Watala began a collaborative program to help build trust and support negotiations between people and the government.

The program was first announced in 1999, shortly after the reformasi period began. The first people to learn of it in Sumberjaya were in the village of Tribudi Syukur, not coincidentally home to three forest department employees (out of nine living in all of Sumberjaya). This kind of social relationship that helps people gain access to programs and services appears to have played a role in spreading HKm, but it is not a necessary condition. Table 14.3 compares the characteristics of the earliest villages to secure an HKm contract with those that were still in the process of applying for HKm at the time of the survey.

Table 14.4 Other indicators of social capital, access and agency, by group

Indicator Groups with an approved HKm permit

Groups still applying for HKm permit

Mean year the village was established 1960 1957

Mean year the protection forest was first cultivated

1969 1971

Mean concentration of dominant ethnic1 group 81% 70%

Dominant ethnic group, n and (%) villages2

Sundanese 4 (67) 10.53 (46)

Javanese 2 (33) 8.53 (37)

Semendo 0 (0) 4 (17)

Mean education of group leader (years)4 10.1 10.0

Number of motorcycles per group member5 0.19 0.13

Mean walking time in minutes from protection forest to nearest paved road5

Closest 38 49

Farthest 108 109

Unweighted mean 92 103

Source: ICRAF/MSU/IFPRI HKm group survey

1 Ethnic heterogeneity is often considered to reduce the prospects for collective action (bonding social capital) 2 Javanese and Sundanese are the groups that dominate governmental jobs. Semendo people have a local reputation of

being less prone to work collaboratively compared to other ethnic groups, but we have no specific evidence to confirm or refute this reputation

3 One village is half Sundanese and half Javanese so the value is one half for each of these groups 4 Higher educational status could indicate better ability to access a program 5 Groups with more motorcycles and groups closer to the main road may have better access to outsiders who can help

deliver HKm

Other indicators of access, social capital and agency also show differences between groups with and without an HKm license. Table 14.4 shows that licensed groups on average had 40% more motorcycles per member, which is an indicator of wealth but also of mobility for access to the outside world. Their dominant ethnic group was Javanese or Sundanese, which are the groups that predominate in government. There is virtually no difference in how long ago the villages were established or when they began cultivating the protection forest, and nearly all groups experienced eviction in the 1990s. There is also virtually no difference in educational attainment by the leaders of groups with and without HKm.

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16 | Placement of a payment for watershed services program in Indonesia: Social and ecological factors

Bonding social capital refers to factors that strengthen relationships within a group, helping them act collectively to take action and solve problems. In this regard, Table 14.4 shows that groups with HKm are more ethnically homogeneous, with a higher concentration of the largest ethnic group.

Some studies have suggested that collective action is more likely in one arena when it builds on collective action in another arena37,38. We explored whether groups with an HKm permit differed from other protection forest farmers in the extent to which they could draw upon collective action in other contexts. Group-level data did not show much difference between the two types of HKm groups, but household data showed that members of HKm groups with a permit much more frequently belonged to other groups than respondents who were part of a group still applying for an HKm permit. The latter in turn belonged to other groups more frequently than protection forest farmers with no HKm group. Table 14.5 shows that this difference is statistically significant for coffee farmer groups, labour-sharing groups, water-user groups, women’s groups and religious groups. Respondents rarely reported any direct relationship between these groups and the HKm group, but indirect links may have been important nonetheless.

Table 14.5 Number of respondents belonging to other types of social groups, by HKm status

Strata

Number and (percent) of respondents belonging to group, by type Labour-sharing (men)1

Labour-sharing

(women)2

Coffee farmers’ group3

Water users

assoc.4 Women’s

group5 Religious

group6 HKM permit 38 (32) 15 (13) 17 (14) 61 (51) 24 (20) 106 (88)

HKM in process

13 (11) 5 (4) 4 (3) 10 (8) 3 (3) 76 (63)

No HKM eviction

9 (8) 1 (1) 0 (0) 6 (5) 12 (10) 64 (53)

Source: ICRAF/MSU/IFPRI HKm household survey 1Pearson chi-square = 28.7, df=2, p<.001); 2Pearson chi-square = 15.5, df=2, p<.001); 3Pearson chi-square = 23.6, df=2, p<.001); 4Pearson chi-square = 87.3, df=2, p<.001); 5Pearson chi-square = 18.6, df=2, p<.001); 6Pearson chi-square = 23.4, df=2, p<.001)

A history of evictions in the protection forest in Sumberjaya increased interest in the program as a means of gaining more secure tenure; this could stimulate collective action within groups. The household survey showed that 54 percent of households who are part of a group with an HKm permit had been evicted in the 1980s or 1990s compared to 34 percent for those with an HKm application in process and 31 percent for those with no HKm group. This difference was statistically significant (Pearson chi-square = 10.7, df=2, p<.01). This could indicate that previous experience with eviction helped stimulate these groups to apply for the program.

14.5.3 How do the HKm group boundaries overlap with the areas where erosion matters?

The results of an overlay between the estimated sediment yields and the various land status strata are presented in Figure 14.5. The ranges are very similar for all land status strata, with the exception of stratum 1, the national park. For the remaining strata, it appears that relatively high sediment-yielding areas are well distributed over all the strata. Overall, the relationship between sediment yield and the location of HKm areas seems at most to be a very weak one.

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Figure 14.5 Sediment yield by land status stratum, showing the area of the subcatchment associated with each observation

14.6 Discussion

This paper has two main findings: that watershed services are difficult to understand ex ante and that program placement is influenced by factors related to social capital and agency that have little to do with the ability to provide the watershed service.

14.6.1 Watershed function

The findings show clearly that in Sumberjaya, underlying geological factors are far more important than land use. Further analysis31 of the Sumberjaya case found that land use can be important, but not as much as geology, and not always as authorities believe. The program requirement of planting large numbers of trees, for example, does not necessarily help watershed functions and probably will reduce the amount of water to the hydroelectric dam. A perhaps surprising result from the catchment-level sediment yield estimations is that the highest sediment yields come from those catchments with the highest forest cover (Way Lirikan; Table 14.1). Also, in the stepwise regression, not a single land use seemed to be able to fully explain the variance when compared with other factors like geology (the lithology of the Bukit Rigis), topography (slope) and soil texture (the percentage of silt). Land status also seems to be unrelated to sediment yields. The only possible exception could be the national park, which is characterized by very low sediment yields (< 3.3 Mg ha-1). A perhaps sobering observation from Table 14.1 is that the area with the lowest sediment yield is mainly in the Air Hitam subcatchment, where there is only 4% forest cover left!

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18 | Placement of a payment for watershed services program in Indonesia: Social and ecological factors

Placement of the HKm program was of course limited to the protection forest area, which depended on the government’s designation of these areas in 1990, and where topography (steepness of the slopes) was the dominant criterion and not geology. Evidence presented here suggests that these areas are not particularly relevant for protecting watershed functions. As a result, it was not possible for the HKm program itself to target important sedimentation sources very well. Even within protection forest areas we see no real relationship between sediment yield and placement of the HKm contracts. Of course, it was not possible for program officials to know the sediment yield of each area of protection forest at the time the program was initiated, so the weak relationship is to be expected.

Tree planting can in principle improve the soil infiltration capacity, which would reduce peak flows, but a delay of at least years between tree planting and reduction of soil infiltration capacity is to be expected where land use can make a difference with regard to erosion and sediment yield is in steep and lithologically sensitive areas. Unfortunately, a lack of good baseline data prevents a reliable identification of these sensitive areas in protection forest. The conversion from the current geology maps to sensitivity classes is at best very coarse. Thus, even if forest officials had understood the conditions under which land use could reduce sedimentation, data limitations would have restricted their ability to act.

Regardless of how poorly the HKm program actually targeted important sedimentation sources, the research results show that the very idea that farmers are the main cause of watershed problems in Sumberjaya was misplaced and that coffee gardens play only a limited role in sedimentation. The lower evapotranspiration of the coffee gardens compared to dense tropical forest actually had beneficial effects on the production potential of the electric power plant. By legitimizing these coffee farms, the HKm program largely benefitted local people without negatively affecting the watershed. The poor targeting of the HKm program is a consequence of the earlier misguided delineation of the protection forest, and thus not an argument for abolishing the HKm program. Nevertheless, a set of different measures will be needed to effectively reduce the sediment influx in the storage lake.

14.6.2 Program placement

Within the protection forest area, placement of HKm shows clear signs of having followed factors related to social capital and agency. Particularly striking were the relationships that people had with those in a position of power. Villages with more HKm groups had more contacts in the forest department and other government officials, the NGO Watala, and other friends outside the village that helped them establish their groups. HKm groups with an approved permit had a higher number of motorcycles per member, indicating both more wealth and better access to the outside world.

The groups with an approved HKm permit also showed some differences in bonding forms of social capital. Those with an approved permit had a higher concentration of people belonging to a dominant ethnic group. They had a much higher percentage of members who belonged to other types of cooperative groups before the HKm group was formed, possibly giving them more experience in working collectively. They also had more people who had experienced eviction, thus perhaps increasing their interest in gaining access to the program. An evaluation of household-level resources showed that participation in HKm increased equity in the villages39. When given a choice between multiple types of contracts, farmers preferred long-time security over direct financial gain40. This confirmed farm-level economic analysis that suggested that at low discount rates, reflecting tenure security, multi-strata agroforestry is more profitable and low-risk than the coffee monocultures that are superior at high discount rates (uncertain tenure conditions).41,42

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Subsequent efforts in Sumberjaya have explored, in action-research mode, other environmental service reward mechanisms, applicable in the private-lands zone. These include auctions to get voluntary commitment to apply soil conservation practices43,44,45 and a community-scale ‘Rivercare’ conditional reward scheme46,47. Further findings from Sumberjaya are discussed elsewhere48,49 in this book and in wider syntheses of natural resource management.50,51

Conclusion

Two main lessons from this paper have broader applicability outside of Sumberjaya. First, program placement is likely to be strongly influenced by village-level social capital and agency variables, completely separate from whether the location in question can supply the environmental service. At the same time, the cause-effect chain between certain watershed functions and land use is far less linear and simple than often thought. The above discussion makes clear how obviously difficult and time-consuming it is to assess where watershed services come from. This makes it very difficult for PWS (as a specific form of PES) to be well targeted if used as a blanket policy tool. A blanket approach will likely suffer from leakage, whereby stakeholders will be rewarded for a service they only appear to deliver or that those who can in fact supply the service will not be included. This is particularly so because of the role of socioeconomic factors in determining program placement. A well-targeted case-by-case approach could however be meaningful, but would generally require the collection of baseline data that are generally not available in most countries.

Acknowledgements

The authors thank many people for their assistance on this paper. Meine van Noordwijk facilitated the research effort and helped to edit and update the paper for publication. Brent Swallow and Ruth Meinzen-Dick helped develop the ideas and secure funding for the socioeconomic aspects of this research. Noviana Khususiyah led the survey, and many others at ICRAF and in Sumberjaya provided assistance. We are especially grateful to the many farmers, community leaders, and government and non-government officials in the West Lampung District who participated in the interviews conducted for this study. The community and household surveys were conducted under a project entitled “Property rights, Environmental Service Mechanisms and Poverty in Indonesia.” The project was supported by the Broadening Access and Strengthening Input Systems (BASIS) Collaborative Research Support Program (CRSP), funded by the United States Agency for International Development. The hydrological surveys and sediment yield assessment were made possible through funding from the Australian Centre for International Agricultural Research (ACIAR), a one year PhD fellowship from KULeuven and a South Initiative funded by VLIR-UOS. The assistance of local farmers and Susanto, Endri Subagyo, Pratiknyo Purnomosidhi from the ICRAF Sumberjaya team to collect the thousands of suspended sediment samples was invaluable. The write-up was partially supported by the USDA National Institute of Food and Agriculture, Hatch project number MICL02244 and the VLIR-UOS funded research platform KLIMOS.

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