The influence of cash and technical assistance on household-level outcomes in payments for hydrological services programs in Chiapas, Mexico

Ecosystem Services 31 (2018) 208–218

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The influence of cash and technical assistance on household-level outcomes in payments for hydrological services programs in Chiapas, Mexico Kelly W. Jones a,⇑, Carlos L. Muñoz Brenes b, Xoco A. Shinbrot c, Walter López-Báez d, Andrómeda Rivera-Castañeda e a

Department of Human Dimensions of Natural Resources, Colorado State University, Fort Collins, CO, USA Department of Natural Resources and Society, University of Idaho, Moscow, ID, USA c Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, USA d Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Chiapas, Mexico e Fondo de Conservación El Triunfo, Chiapas, Mexico b

a r t i c l e

i n f o

Article history: Received 12 July 2017 Received in revised form 7 March 2018 Accepted 25 April 2018

Keywords: Common property Ejido Extrinsic motivators Forest conservation Impact evaluation Payment for ecosystem services

a b s t r a c t This paper examines whether and how payments for hydrological services (PHS) programs implemented on communal lands in Mexico result in household-level conservation and human wellbeing outcomes. We first use evaluation methods to establish the impact of PHS by comparing outcomes across seven communities enrolled, and one community not enrolled, in PHS. Second, we exploit variations in PHS program design across the enrolled communities to test the role of cash and technical assistance on outcomes. Data come from a 2016 cross-sectional survey of 261 households around El Triunfo Biosphere Reserve, in Chiapas, Mexico. We find that households enrolled in PHS implement more conservation actions and that some own more assets than similar households not enrolled in PHS. We find that asset ownership is positively correlated with a household’s payment amount and that conservation practices are related to amount of assistance received. We also measure perceived equity and benefits for households enrolled in PHS and find that perceptions are correlated with both payment and assistance, and strongly influenced by community organization. Our results provide evidence that common-property PHS contracts can change household-level conservation and human wellbeing outcomes, but that these changes are dependent on the type of external motivator and community organization. Ó 2018 Elsevier B.V. All rights reserved.

1. Introduction Payments for hydrological services (PHS) programs are being implemented throughout Latin America to address water scarcity and quality concerns (Martin-Ortega et al. 2013; Bremer et al. 2016; Grima et al. 2016). They are part of a broader suite of tools known as payments for ecosystem services (PES). PES are voluntary transactions where ecosystem services users provide extrinsic incentives to ecosystem services providers for changes in land use or natural resources management behaviors (Wunder 2015). These extrinsic incentives are considered necessary in order to overcome opportunity costs of conservation activities (Wunder 2006; Kosoy et al. 2007; Engel et al. 2008; Wunder 2013). Extrinsic motivators come in many forms, including cash, in-kind materials,

⇑ Corresponding author. E-mail address: [email protected] (K.W. Jones). https://doi.org/10.1016/j.ecoser.2018.04.008 2212-0416/Ó 2018 Elsevier B.V. All rights reserved.

education, and technical assistance (Cetas and Yasue 2016). A number of empirical studies have shown that ecosystem services providers often have pre-existing intrinsic, or inherent, motivations toward conservation (Kosoy et al. 2008; Sommerville et al. 2010; Zanella et al. 2014; Bremer et al. 2014a; Mendez-Lopez et al. 2015; Rodriguez-Robayo et al. 2016; Figueroa et al. 2016). Extrinsic motivators may crowd in or crowd out these intrinsic motivators (Chan et al. 2017). Counterfactual evidence of the impacts of extrinsic motivators provided through PES programs on conservation and human wellbeing outcomes is increasing but still remains modest (Pattanayak et al. 2010; Ferraro 2011; Samii et al. 2014; Borner et al. 2016; Borner et al. 2017). PHS programs in Latin America target many types of land-use activities in order to improve ecosystem services, including protection of forest, reforestation, soil conservation, living barriers, and silvopastoral practices (Bremer et al. 2016). Most evaluations of PES focus on avoided deforestation. In Latin

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America, findings suggest that PES schemes have reduced deforestation but the net change in area dedicated to forest is often modest due to low levels of deforestation before payments began (Scullion et al. 2011; Alix-Garcia et al. 2012; Arriagada et al. 2012; Robalino and Pfaff 2013; Robalino et al. 2015; Costedoat et al. 2015; Sims and Alix-Garcia 2016; Le Velly et al. 2017; Jones et al. 2017). A smaller number of studies have assessed the impact of PES on other land-use outcomes, and find a positive relationship between extrinsic motivators and changes in silvopastoral (Garbach et al. 2012; Pagiola et al. 2010; Pagiola et al. 2016), agroforestry (Hedge and Bull 2011), and grazing practices (Hayes et al. 2017). In many Latin American PES schemes conservation outcomes are linked with objectives of poverty alleviation and rural development (de Koning et al. 2011; Pagiola et al. 2005; Pagiola et al. 2010; Torres et al. 2013). Studies linking PES to human wellbeing or livelihood outcomes have mostly been descriptive but suggest positive connections between PES and wellbeing (Hejnowicz et al., 2014; Bremer et al., 2014b). There are few impact evaluations of PES on human wellbeing (Samii et al. 2014; Borner et al. 2016, 2017), with most evaluations focusing on changes in material wellbeing. Empirical results suggest small to no difference in material wellbeing between households that participate in PES and households that do not participate (Uchida et al. 2007; Hedge and Bull 2011; Samii et al. 2014; Arriagada et al. 2015; Alix-Garcia et al. 2015; Sims and Alix-Garcia 2016; Borner et al. 2017). There are few impact evaluations of PES on other objective wellbeing outcomes; an exception is a study that finds increased expenditures on food consumption due to PES (Hedge and Bull 2011). Positive perceptions of PES programs by participants is an important component of subjective wellbeing (Martin et al. 2014; Perevochtchikova and Negrete 2015; Rodriguez-Robayo et al. 2016; Bennett 2016). This includes perceived equity of the PES program, especially procedural (fairness in decision making) and distributive (fairness in costs and benefits) equity (Corbera et al. 2007; Pascual et al. 2010; Pascual et al. 2014; Klein et al. 2015; Calvet-Mir et al. 2015; Althor et al. 2016). The perceived equity and benefits of the PES program can create positive or negative feedbacks that influence the legitimacy and sustainability of the PES initiative over time (Pascual et al. 2010; Pascual et al. 2014). Equity concerns may be heightened in common-property PES programs, since community leaders decide whether to participate and how cash payments are distributed. A number of issues have been documented in common-property PES, such as differences in perceived equity of PES across leaders and community members (Perevochtchikova and Negrete 2015; Almeida-Lenero et al. 2017), lack of recognition of participation in PES by all community members (Neitzel et al. 2014) and exacerbation of preexisting power dynamics, inequities and vulnerabilities among community members (Corbera et al. 2007; Rodriguez de Francisco et al. 2013). The goal of this paper is to provide evidence on whether and how PHS programs lead to conservation and human wellbeing outcomes in Mexico. The objectives are twofold. First, we assess whether common-property PHS impact household-level conservation and human wellbeing by comparing outcomes across enrolled and non-enrolled households. Most of Mexico’s cultivable lands are under common-property land tenure arrangements (Assies 2008). The ability of common-property PES contracts to affect household-level conservation and human wellbeing outcomes is not well understood (Clements et al. 2010; Sommerville et al. 2010; Krause and Loft 2013; Hayes et al. 2015, 2017). We test whether PHS leads to differences in household-level measures of conservation actions, which are promoted by some PHS programs in the study area. These conservation actions are intended for individual parcels of land and could lead to ecosystem services

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provision, in addition to that provided from common-property forest conservation, and improve local livelihoods. We also evaluate whether PHS has impacted material wellbeing; PES is hypothesized to lead to changes in rural income and consumption (Samii et al. 2014). Second, we examine which components of PHS programs influence conservation and human wellbeing outcomes. PHS programs in our study area use a combination of cash payment and technical assistance. By exploiting variation in the amount of payment received and technical assistance provided, across households enrolled in PHS, we test how these different extrinsic motivators are related to conservation actions, material wellbeing, and perceived equity and benefits. Few studies have directly compared how different types of motivators within the same PES program lead to conservation or human wellbeing outcomes. This information can inform future PES design. Jointly, our research contributes evidence on: whether PHS programs motivate additional changes to household-level land-use practices; how PHS programs affect human wellbeing, including both objective and subjective wellbeing; and the role of different extrinsic motivators in generating these outcomes.

2. Background on study area and PHS programs Mexico created a national PHS (N-PHS) program in 2003 to secure the provision of hydrological services by paying for forest conservation (Muñoz-Piña et al. 2008). Both individuals and communities with formally recognized land tenure can enroll in the program, and as of 2015, 10% of Mexico’s forests were under contract with the PHS program (CONAFOR 2017). In 2008, Mexico added a decentralized version of the program, Fondos Concurrentes, referred to here as the matching fund PHS program (MF-PHS), because the national government provides up to 50% of financing needed to establish the PHS program and local ecosystem services users provide the rest. The MF-PHS program has spread rapidly with more than 50 programs across the country (Saldaña-Herrera 2013). While several studies have tested the effect of the N-PHS program on deforestation, few studies measure the impact of Mexico’s PHS programs on other conservation outcomes or human wellbeing. The state of Chiapas, Mexico is a strategic zone for water recharge, erosion control and flood regulation. It contains about 30% of the freshwater resources in the country and supplies 42% of the hydropower for Mexico (López-Báez et al. 2012). El Triunfo Biosphere Reserve in southwestern Chiapas is located in the Sierra Madre Mountains and is a biodiversity hotspot. The steep mountainous region (1000 to 2600 msnm) is highly susceptible to natural disasters including hurricanes, flooding, and landslides, which affect hydrological services and livelihoods (López-Báez et al. 2012). El Triunfo consists of five core protected areas, covering about 26,000 ha (Fig. 1). No people live within the core zone. A buffer zone of about 93,000 ha surrounds the core zone. The buffer zone is an important conservation priority since it provides habitat connectivity and influences hydrological services. Similar to other biosphere reserves, people are allowed to live and utilize the land in the surrounding buffer zone. About 20,000 people live in the buffer zone and more than 200,000 people live in the buffer and transition area surrounding the reserve (UNESCO 1999). Households located within and around the buffer zone are primarily farmers, earning income from cash crops like coffee while also farming a maize-bean mix known as milpa (Jurjonas et al. 2016). The majority of households in the buffer and transition areas of El Triunfo are organized in communal land tenure systems known as ejidos. The ejido land tenure system resulted from a 1917 constitutional change that redistributed about half of Mexico’s lands to

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Fig. 1. Location of El Triunfo Biosphere Reserve in Chiapas State, Mexico.

peasant organizations (Assies 2008). This agrarian land reform also created a second type of communal land tenure system, known as comunidades agrarias (agrarian communities). Agrarian communities were established as collective farm systems, but were not heavily promoted by the government, and today comprise only about 6% of common-property areas in Mexico (SEDATU 2016). There are few agrarian communities in Chiapas. Ejido land tenure systems are much more common throughout Mexico, including Chiapas, and include both landholdings controlled by individuals and shared-access common-use lands (Assies 2008). Individual lands are primarily used for agricultural activities. Common-use lands are collectively managed and often dedicated to forest or pasture; more than half of the forest enrolled in Mexico’s national PHS program are on common-use ejido lands (Muñoz-Piña et al. 2008). Ejidos are made up of members, known as ejidatarios, and non-members, or non-ejidatarios. Ejido members are governed by formal assemblies, which are led by ejido leaders. Nonejidatarios do not have formal voting rights in assemblies and no formal land. Both the N-PHS program and a local, MF-PHS program operate in and around the buffer of El Triunfo. In 2010–2015, the N-PHS program had around 4000 ha of land in contract across four ejidos in this area; the MF-PHS program had close to 5000 ha of land across 15 ejidos. Each PHS program works directly with ejido leaders and the ejido’s common-use forest is enrolled in the program.1 The two PHS programs paid a similar annual rate per hectare in 2015 (
740 pesos/ha or 46USD/ha), with the MF-PHS program adjusting 1 While ejidatarios can enroll their individual parcels in PHS contracts, in our study area, only the ejido’s common-use forest is enrolled in PHS.

annually for inflation. Distribution of payment by ejido leaders amongst ejidatarios is determined by the rules of that ejido. While most PHS program operators in the study area believe distribution is equitable, our experience suggests at least three sets of rules in operation for how the payment is distributed across members: (1) egalitarian; (2) priority to ejido leaders and then equal across other members; and (3) proportional to individual parcel size. Thus, the amount of payment received by an ejidatario varies as a function of the total common-use forest enrolled in PHS and the specific rules adopted by that ejido. The N-PHS program is administered by the National Forestry Commission (CONAFOR); it consists of 5-year contracts with forest owners who agree to maintain forest cover in good condition (CONAFOR 2015). CONAFOR outlines requirements that participants in the program must comply with on the forest that is enrolled in the program; these include things such as avoiding changes in land use, placing signage around the enrolled area, creating a fire brigade to protect the forest, and improving capacity to manage the forest. Additionally, CONAFOR has a list of best management practices that communities must choose from and implement on enrolled forests. Part of the collective payment is allocated to hiring a technician and to implementing these best management practices on common-use forests. These practices can include conservation, restoration, and protection activities, or sustainable forest management practices, depending on the needs of the participants. In our study, the obligations and best management practices outlined by CONAFOR apply to the enrolled common-use forests, but not individual parcels where agricultural activities take place. As of 2015, the N-PHS program did not require ejidos to invest any portion of the collective payment in community-level projects.

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The MF-PHS program is administered by El Triunfo Conservation Fund (FONCET in Spanish), which works in close collaboration with the National Institute for Forestry, Agriculture and Livestock (INIFAP in Spanish), and The Nature Conservancy-Mexico (TNC). It began in 2010 and contracts are offered for 5 or 10 years; all ejidos in our study were signed up for 10 year contracts (see Section 3). Since half of the funding for the MF-PHS comes from CONAFOR, the same rules and best management practices described above apply to the ejido’s enrolled common-use forest. A major difference is that FONCET hires the technician directly to work with the communities, whereas in the N-PHS program the community is tasked with hiring the technician. Ejidos enrolled in FONCET’s MF-PHS program are also required to invest a portion of the overall payment in community development before funds are distributed to households. There is no stipulation on the type of community investment, and most ejidos have used the money to finance community centers and roads. FONCET and its partners conducted a study of the N-PHS program before designing their local MF-PHS program (INIFAP, N.D.). The findings from this study led FONCET to hire technicians directly; to require a portion of the payment be used for collective projects; and to offer longer contracts. Additionally, the findings from this study led FONCET to develop an integrated water resources management (IWRM) approach aimed at achieving long-term sustainable livelihood and conservation outcomes in the buffer zone of the reserve. The IWRM approach includes payment for forest conservation through the MF-PHS, but also provides capacity-building workshops, facilitates community-based watershed governance, and provides education and technical assistance on reforestation and sustainable agricultural activities, including agroforestry and soil conservation practices (INIFAP 2014). These latter activities are targeted at individual ejidatario parcels. Due to the cost of these additional activities, FONCET has implemented the IWRM approach in only a handful of ejidos, but would like to expand this approach in the study area. A major motivation for this study was to evaluate the conservation and human wellbeing outcomes of the newer MF-PHS program, with and without the IWRM approach, and compare it to the N-PHS program.

3. Methods 3.1. Data collection We developed and implemented a household survey in 2016 to measure household-level conservation activities and human wellbeing. The survey was co-developed with FONCET and INIFAP. The survey was in Spanish and pre-tested prior to implementation. Average survey time was 60 min. The survey collected information about: (1) household demographics; (2) land use; (3) wealth and assets; (4) perceptions of equity and benefits of PHS; (5) conservation information and actions; and (6) community organization and capacity of the ejido. We asked respondents to recall assets, crops, and individual parcel size for 2010 (prior to PHS) and 2015 (the year prior to the survey). Retrospective questions are a common way to get at pre-existing conditions when baseline data is unavailable (Mullan et al. 2014). The survey can be found in Appendix A. We conducted a stratified, random sample of ejidatarios in eight ejidos (Table 1). We surveyed: (1) two ejidos in N-PHS; (2) three ejidos in FONCET’s MF-PHS2; (3) two ejidos in the same MF-PHS 2 Ejidos number four and five were originally part of the same ejido, but were split and households relocated to form two smaller ejidos following Hurricane Mitch in 1998.

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program but with the IWRM approach; and (4) one ejido not enrolled in a PHS program (Table 1). We initially targeted two ejidos for each stratum. Due to field logistics, however, we were not able to survey the second ejido in the non-PHS group. We aimed for at least 50 household surveys per stratum, and in total collected 261 household surveys. PHS started in 2013 for six ejidos and 2010 for one ejido. Ejido selection was based on accessibility, proximity to one another, and approval from community leaders3. We obtained a list of all ejidatarios and conducted a random sample of head of households who were present during summer 2016. Each household was asked for their verbal consent prior to implementing the survey. Non-members were excluded; non-members represent <10% of the population in the ejidos sampled. 3.2. Variables 3.2.1. Outcome variables We measured household-level conservation actions as selfreported implementation of five land-use activities on a household’s individual land parcel. Information and training on these five activities are part of the IWRM approach that FONCET is implementing in some ejidos and included: reforestation, planting living fences, building living dams, implementing soil conservation practices, and not burning agricultural fields after harvest. Responses were binary (yes/no) and summed to create a scale ranging between zero and five (Table 1). The average adoption of conservation actions varies between 2.5 and 3.9 across ejidos (Table 1) and differences in adoption are statistically different across PHS and non-PHS households (Appendix B, Table B.1). To capture changes in material wellbeing we asked respondents to report on assets owned in 2015 and 2010. The original list included: vehicles, motorcycles, bicycles, cell phones, chainsaws, gas stoves, electricity, running water, and televisions. We omitted televisions from analysis after finding out about a political campaign that gave away free televisions to households. We used principal component analysis (PCA) to create a weighted average of the remaining eight assets for 2010 and 2015 (OECD 2008; Table 1). This asset index varies considerably across ejidos in 2010 and 2015, but difference in assets between all PHS and non-PHS households is not statistically significant (Appendix B, Table B.1). We originally included 10 statements to capture householdlevel perceptions of equity and benefits from participating in the PHS program; only households enrolled in PHS were asked these statements. We included statements on both distributive and procedural equity. Statements on perceived benefits focused on economic and non-economic benefits to the household and ejido from participating in PHS. Respondents replied using a five-point scale of totally disagree, disagree, neutral, agree, or totally agree. We used Cronbach’s alpha to determine the reliability and consistency of statements, with a cutoff of 0.65 indicating reliability (Vaske 2008). Three of the items were not consistent and were dropped. Our final composite measure of perceived equity and benefits (Table 1) is the average of seven statements (Appendix B, Table B.2) with a reliability score of 0.65. Perceived equity and benefits is positive across all ejidos, ranging between 3.7 and 4.5 (Table 1). 3.2.2. Treatment variables We implement tests of whether PHS has an effect on conservation actions and material wellbeing using (1) all PHS households versus households without PHS and (2) each individual PHS approach (i.e., N-PHS, etc.) versus households without PHS. For 3 A description of the study’s research objectives and procedures was explained to each ejido general assembly and approval was sought; no ejido declined to participate.

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Table 1 Ejido and ejidatario characteristics.

Ejido Characteristics Total area (ha) Total population Surveys collected Common-use forest area enrolled in PHS (total ha) PHS payment (total pesos/year for the ejido, 2015) Ejidatario Characteristics from Household Survey PHS household payment (pesos/year for the household, 2015)* Technical assistance (0 to 5)* Conservation actions (0 to 5)* Perceived equity & benefits from PHS (0 to 5)* Asset index 2010 (3.4 to 3.8)* Asset index 2015 (2.0 to 3.6)* Community organization index (0 to 5)* Age* Number of people in household* Percent respondents that were male (%) Percent head of household with any education (%) Number of groups family participates in* Hectares 2010* Hectares 2015* *

MF-PHS & IWRM Ejidos

MF-PHS Ejidos

1

2

3

4

5

6

7

8

104 93 18 46 34,000

363 322 38 105 77,500

681 460 17 329 243,100

2327 53 31 1000 740,000

1266 21 14 423 313,000

3282 1055 50 1101 817,000

2266 553 23 650 378,530

5834 2203 70 Not applicable (N/A) N/A

N-PHS Ejidos

No PHS Ejido

480 (185) 620 (310) 1300 (450) 11,000 (7000) 2800 (940) 2500 (1000) 1800 (450) N/A 4.0 (1.4) 3.1 (14) 4.1 (0.7) 1.1 (1.1) 1.5 (0.6) 4.1 (0.6) 45 (13) 4.0 (1.7) 61 83 2.2 (1.1) 3.3 (6.7) 2.9 (4.8)

4.4 (1.1) 3.9 (1.1) 4.2 (0.4) 0.1 (1.6) 0.1 (1.4) 4.0 (0.5) 50 (13) 4.9 (2.3) 81 71 2.5 (0.8) 3.5 (3.5) 3.9 (4.2)

4.4 (0.9) 3.8 (1.1) 4.0 (0.3) 0.4 (1.5) 1.0 (1.3) 3.5 (0.7) 53 (13) 4.9 (2.0) 88 71 2.3 (1.4) 7.9 (7.0) 7.4 (6.5)

4.4 (0.7) 3.3 (1.3) 3.9 (0.7) 0.4 (0.9) 0.03 (1.0) 3.7 (0.6) 52 (11) 5.3 (1.7) 62 77 1.7 (0.7) 36.3 (18.5) 36.3 (18.5)

4.1 (1.1) 3.8 (0.9) 4.5 (0.3) 0.6 (1.6) 0.8 (1.0) 3.8 (0.6) 55 (13) 4.6 (1.5) 71 100 1.7 (0.7) 12.7 (7.1) 12.3 (6.8)

3.6 (1.5) 3.7 (1.0) 3.9 (0.7) 0.05 (1.2) 0.2 (1.4) 3.4 (0.9) 53 (16) 5.7 (2.2) 86 74 2.0 (1.2) 6.8 (6.5) 6.4 (4.4)

3.1 (1.3) 2.7 (1.2) 3.7 (0.5) 0.2 (1.2) 0.4 (1.3) 3.6 (0.6) 53 (13) 5.7 (1.6) 100 45 1.6 (0.9) 6.0 (4.5) 7.7 (5.5)

N/A 2.5 (1.0) N/A 0.2 (1.3) 0.03 (1.2) 3.4 (0.5) 56 (11) 4.8 (1.9) 89 73 1.7 (0.9) 10.7 (10.2) 10.9 (10.7)

Mean values with standard deviations in parentheses.

these tests, we include PHS as a dummy variable where ‘‘100 indicates participating in PHS, and ‘‘0” otherwise. To examine how specific extrinsic motivators influence conservation actions, material wellbeing, and subjective wellbeing, we substitute the PHS dummy variable with (1) household payment amount in pesos (self-reported by head of household; Table 1) and (2) technical assistance. Household payment amount (Table 1, bottom panel) varies between 500 and 11,000 pesos per year in our sample; this is the total annual amount received by the household (Table 1, top panel). We log-transform PHS payment amount to normalize the distribution. We asked each respondent if they had received technical assistance or information on the same five land use activities measured in the conservation actions index; responses were binary (yes/no) and summed to create a scale between zero and five (Table 1). Technical assistance ranges between 3.1 and 4.4 for ejidos enrolled in PHS (Table 1). It is possible that households receive information on some of these five topics through the technicians that provide training on forest conservation, restoration, and protection activities for the ejido’s enrolled common-use forest. 3.2.3. Independent variables We measured several household and individual parcel characteristics expected to influence the outcomes above based on our knowledge of the study area and previous household-level PES evaluations (e.g., Arriagada et al., 2012; Alix-Garcia et al., 2012). For each head of household, we recorded their age, gender, whether they had attended school, size of household, and number of groups the household participated in during 2015 (Table 1). PHS and non-PHS households have statistically significant differences in the mean values of age, gender, and participation in groups (Appendix B, Table B.1). To measure wealth, we asked respondents to report the size of individual parcels of land in 2010 and 2015 (Table 1). There are large differences in parcel size across PHS and non-PHS households (Appendix B, Table B.1). These differences across participants and non-participants suggest selection bias, and indicates the need for a quasi-experimental evaluation approach to estimate the impact of the PHS programs (see Section 3.3.1).

We created a community organization index to control for the potential influence of community, or social, capital on the effectiveness or equity of PHS programs4 (Table 1). We asked respondents eight questions about their ejido’s organizational capacity (Appendix B, Table B.3). These were developed by the authors based on similar questions used to assess community organization in the PES literature (e.g., Hayes et al. 2015; Hayes et al. 2017). Respondents replied using the same five-point scale described above. Consistency and reliability of statements using Cronbach’s alpha was 0.69. Community organization varies between 3.4 and 4.1 (Table 1), and is statistically different across PHS and non-PHS households (Appendix B, Table B.1). 3.3. Analysis 3.3.1. Impact evaluation We use matching methods to test whether households in PHS adopted more conservation actions than households not in PHS. Matching is a quasi-experimental approach that helps reduce selection bias between observations that are in a program – the treated – and observations not in a program – the control group (Rubin 2006; Imbens and Wooldridge 2009). PHS enrollment is a collective decision in our study area; however, matching is still useful for controlling for differences across household characteristics (Appendix B, Table B.1). Matching selects the sample of control households that are most similar in observable characteristics to the treatment group, and then compares average outcomes across the treated and this constructed control group. Mathematically, this is represented by:

s¼

N 1 X Y i ð1Þ  Y i ð0Þ; N 1;PHSi¼1

ð1Þ

where N is the total number of observations, PHSi ¼ 1 when a household, i, is enrolled in PHS, Y i ð1Þ is the outcome with the PHS 4 It is possible that conservation programs influence community organization, but given the start date of PHS in our study area (i.e., 2013 for most ejidos) we assume no direct impact from PHS.

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program and Y i ð0Þ is the outcome without the program. Since we can never observe Y i ð0Þ for the treatment group, the control group is used to measure the counterfactual outcome. The difference between these two outcomes, s, gives the average treatment effect among the treated (ATET). We use nearest neighbor covariate matching to estimate the ATET (Abadie and Imbens 2006), and implement it using bias-adjustment and robust standard errors. We present matching results with two different metrics—inverse sample standard errors and Mahalanobis metric—and with one and five nearest neighbors. We match on the following household characteristics: age, gender, education, participation in groups, household size, and 2010 parcel size. Matching is done with replacement. For material wellbeing, we first implement nearest neighbor matching as described above to test the effect of being enrolled in a PHS program on assets. The outcome variable is the 2015 asset index and we include the 2010 asset index as a covariate in the match. Second, since we have retrospective information on assets we use a difference-in-differences estimator, also known as a before-after-control-intervention approach, to test whether participation in PHS leads to a change in the asset index. We implement this estimator using the following fixed effects panel regression model (Angrist and Pischke 2009):

Y it ¼ b1 PHSit þ b2 HHit þ b3 Timet þ li þ eit ;

ð2Þ

where i is the household, t is the two time periods, Y it is the asset index, and HHit are household characteristics. Because of the individual fixed effects, li , only time-variant household characteristics can be included; thus, HHit only includes individual parcel size. The effect of time on asset accumulation is controlled for with b3 . The parameter of interest is b1 .

3.3.2. Regression analysis of extrinsic motivators We estimate ordinary least squares (OLS) regression models to test how technical assistance and cash payment are related to conservation actions, material wellbeing, and subjective wellbeing. The basic OLS model for household, i, located in ejido, j, is:

Y i ¼ b1 Cashi þ b2 Assistancei þ b3 HHi þ b4 Ejidoj þ ei :

ð3Þ

Y i is the dependent variable, measured as either the conservation action index, 2015 asset index, or perceived equity and benefits index. HHi is the set of household covariates and includes age, gender, education, participation in groups, household size, and 2010 parcel size, for all regressions. When 2015 asset index is the dependent variable we also control for 2010 asset index. When perceived equity and benefits is the dependent variable we control for community organization. In all regressions, we control for ejido-level characteristics through b4 ; this captures ejido differences that might influence these outcomes, such as size of the ejido or presence of other conservation and rural development programs. We estimate Eq. (3) with both cash payment and technical assistance jointly; our parameters of interest are b1 and b2 . We restrict the sample when estimating Eq. (3) to households enrolled in PHS (N = 191) to capture the effect of extrinsic motivators provided through the PHS programs. Given the large variation in PHS payment amounts made to ejidatarios (Table 1), when b1 is statistically significant, we also estimate Eq. (3) excluding the top 10% of PHS payments to test whether differences are driven by the amount of payment received. This excludes households that receive more than 8000 pesos per year from the PHS program (N = 19).

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3.4. Limitations Our results should be interpreted considering the following limitations. First, our outcome measures are self-reported. This is typical for perceptions and assets, but for land-use outcomes it would be preferable to verify information in the field. Unfortunately, we did not have the resources to visit individual parcels. Second, we only have one ejido not in PHS in the sample. It would be preferable to have a larger set of control ejidos. This ejido applied to the N-PHS program in 2015 but was rejected due to an insufficient sustainable forest management plan. A third limitation is the external validity of our study. Generalizability of our results to other common-property PHS contracts in Mexico is limited by differences in ejido-level governance across Mexico and variations in the rules of different PHS programs. Despite these limitations, this study contributes knowledge about household-level outcomes from an increasingly used mechanism for PHS: collective- or community-PES contracts. Additionally, it provides unique insight on how the type of extrinsic motivator within PES programs influences conservation and human wellbeing outcomes.

4. Results & discussion 4.1. Differences in outcomes between PHS and non-PHS households Impact evaluation results establish whether there is a link between being in the PHS program and changes in conservation actions or material wellbeing. Participating in a PHS program led, on average, to the adoption of one additional conservation action on an individual’s parcel of land (Table 2). Households in each PHS type are more likely to adopt conservation actions versus households not in PHS, with effect size ranging between 0.8 and 1.4. The impact on PHS households may be due to the interaction with program technicians, and taking what is learned about conservation, restoration, and protection activities on common-use forest, and applying it to an individual’s parcel. However, the MF-PHS plus IWRM has a larger treatment effect than the other two PHS groups, suggesting that the additional information and technical assistance provided by the IWRM approach resulted in more adoption of conservation actions than the PHS program alone. The treatment effect of PHS on conservation actions is qualitatively similar when the number of covariates in the matching algorithm is reduced to the four that are significantly different across PHS and non-PHS households in Appendix B, Table B.1. The finding that all PHS programs are influencing the adoption of individual parcel-level conservation actions suggests that common-property PHS contracts—where payment is for forest conservation on collectively managed land—can lead to additional land management improvements on individual parcels that should positively affect provision of ecosystem services and livelihood outcomes. In the N-PHS and MF-PHS program, these additional land management actions can be considered positive spillovers of participating in the PHS program, since the program does not specifically target land use changes on individual parcels. In the IWRM approach the objective is to influence household-level land use changes, and it does appear to induce more change than the programs that do not use this approach. There is no statistically significant effect of PHS on changes in household-level material assets when all PHS households are compared to non-PHS households (Table 3). Households in the MF-PHS program are the only set of households that appear to have increased their assets due to being in the PHS program when compared to households not in PHS. The treatment effect is statistically significant at the 95% level, with a coefficient of about 0.5 using both difference-in-differences and matching methods with five

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Table 2 Treatment Effect of PHS on Conservation Actions.

Inverse metric – 1 match Inverse metric – 5 matches Mahalanobis metric – 1 match Mahalanobis metric – 5 matches N

All PHS vs No PHS

MF-PHS & IWRM vs No PHS

MF-PHS vs No PHS

N-PHS vs No PHS

0.94*** 0.85*** 0.89*** 0.85*** 248

1.26*** 1.27*** 1.35*** 1.24*** 119

0.87*** (0.22) 0.85*** (0.21) 0.88*** (0.22) 0.82***(0.21) 127

0.81*** 0.81*** 0.77*** 0.77*** 138

(0.18) (0.17) (0.18) (0.17)

(0.25) (0.22) (0.29) (0.22)

(0.29) (0.22) (0.26) (0.22)

*p  0.10, **p  0.05, ***p  0.01. Note: Matching results based on nearest neighbor matching with bias-adjustment and robust standard errors (in parentheses). Two matching metrics—inverse sample standard errors and Mahalanobis metric—and one and five nearest neighbors are used. Covariates in the match include: age, gender, education, participation in groups, household size, and 2010 parcel size.

Table 3 Treatment Effect of PHS on Asset Index.

Difference-in-differences approach (Fixed effects panel regression) N Inverse metric – 1 match Inverse metric – 5 matches Mahalanobis metric – 1 match Mahalanobis metric – 5 matches N

All PHS vs No PHS

MF-PHS & IWRM vs No PHS

MF-PHS vs No PHS

N-PHS vs No PHS

0.24 497 0.15 0.21 0.12 0.22 255

0.02 (0.20) 238 0.004 (0.30) 0.03 (0.25) 0.09 (0.27) 0.01 (0.24) 123

0.48** (0.24) 250 0.15 (0.25) 0.47** (0.22) 0.14 (0.24) 0.45** (0.22) 129

0.21 273 0.34 0.13 0.34 0.12 141

(0.16) (0.20) (0.18) (0.19) (0.17)

(0.20) (0.22) (0.22) (0.22) (0.22)

*p  0.10, **p  0.05, ***p  0.01. Note: Matching results based on nearest neighbor matching with bias-adjustment and robust standard errors (in parentheses). Two matching metrics—inverse sample standard errors and Mahalanobis metric—and one and five nearest neighbors are used. Covariates in the match include: 2010 asset index, age, gender, education, participation in groups, household size, and 2010 parcel size. Difference-in-differences is estimated using fixed effects panel regression with robust standard errors.

nearest neighbors. Thus, on average, households in the MF-PHS program increased their assets by a half-point compared to households not in PHS. The treatment effect is qualitatively similar when the number of covariates is reduced in the matching algorithm to only those four that are significantly different across PHS and non-PHS households in Appendix B, Table B.1. The small to null effect of PHS on material wellbeing, when compared to households without PHS, is similar to impact evaluation results of other PES programs (Uchida et al. 2007; Samii et al. 2014; Alix-Garcia et al. 2015; Arriagada et al. 2015; Clements and Milner-Gulland 2015; Borner et al. 2017). Assets and income, common indicators of material wellbeing, are affected by a number of pre-existing conditions and large shifts in wealth may be unlikely given the size of most PES payments (Clements and Milner-Gulland 2015). Most households enrolled in PES programs report using the cash payment to meet daily needs, such as purchasing food or clothes (Hejnowicz et al. 2014; Bremer et al. 2014b; Jones et al. 2017), and not for physical or material assets. Similar responses were found in our sample, with the majority of PHS households stating they used the money for food and daily expenses.

4.2. The role of cash payment and technical assistance on outcomes Regression analysis provides insight into whether receiving cash payment and or technical assistance, through the PHS program, influences conservation or human wellbeing outcomes. We find a statistically significant relationship between receiving technical assistance and conservation actions (Table 4). An additional training leads to a 0.3 increase in adoption of conservation landuse practices on an individual’s parcel. The correlation between technical assistance and conservation actions is robust to reducing the number of covariates. The literature on adoption of on-farm sustainable land use practices has found strong correlation between information or assistance and adoption (Pattanayak et al. 2003; Mercer 2004; Knowler and Bradshaw 2007; Meijer et al. 2015). However, these studies also conclude that a number of other household and farm-level characteristics are important

to adoption, but no other variables are statistically significant in our regression (Table 4). This may be due to limited variability across these variables in our sample of PHS households. PHS payment is not correlated with household-level implementation of conservation actions. PES theory suggests that cash incentives are needed in the case where the public benefits of adopting land-use activities are high relative to the private benefits, or where the up-front costs of adoption are high (Wunder 2006; Wunder 2013; Wunder 2015; Garbach et al. 2012). The land-use activities we consider in this study, e.g., reforestation, constructing living barriers, or soil conservation, confer private benefits but also contribute positively to public ecosystem services benefits (Jose 2009). Cash payment may not incentivize adoption of these individual land-use practices in our study, however, because the common-property PHS contracts are not made with specific conditionalities on adopting these practices on individual parcels. Where payments are tied to the adoption of land-use practices on individual’s parcels, the combination of cash payment and technical assistance can have a large impact on implementation (Garbach et al. 2012; Narloch et al. 2012; Torres et al. 2013). When we measure the effect of extrinsic motivators on assets we find that PHS payment amount is statistically correlated with a change in a household’s asset index (Table 4). A one-percent increase in PHS payment results in a 0.0045 increase in the asset index. The 2015 asset index is strongly determined by the household’s 2010 asset index. Technical assistance has no effect on the asset index. The correlation between PHS payment amount and the 2015 asset index is robust to reducing the number of covariates in the regression and to excluding households receiving the largest amount of payments (Appendix B, Table B.4). Thus, there is a clear relationship between the amount of cash a household receives and increases in material assets. This suggests that investment of PHS payments into material wellbeing is limited for most households by the size of the payment they receive, explaining why the differ-

5 A one-percent increase in a log-transformed independent variable results in a (coefficient/100) change in the dependent variable.

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K.W. Jones et al. / Ecosystem Services 31 (2018) 208–218 Table 4 Role of Extrinsic Motivators on PHS Outcomes. Independent Variables

Technical assistance PHS payment (log-transformed) Age Gender Education Number of groups Household size Hectares 2010 Asset index 2010 Community organization index Ejido dummy R2 N

Dependent Variable Conservation Action Index

Asset Index

Perceived Equity and Benefits Index

0.28*** (0.07) 0.01 (0.19) 0.004 (0.01) 0.08 (0.26) 0.28 (0.21) 0.05 (0.10) 0.02 (0.04) 0.004 (0.01)

0.02 (0.06) 0.35** (0.17) 0.01 (0.01) 0.01 (0.22) 0.16 (0.23) 0.05 (0.10) 0.06 (0.04) 0.0001 (0.01) 0.45*** (0.07)

0.08** (0.03) 0.19** (0.09) 0.01 (0.003) 0.15 (0.10) 0.17* (0.09) 0.02 (0.04) 0.001 (0.02) 0.01 (0.01)

YES 0.22 169

YES 0.46 172

0.26*** (0.06) YES 0.31 172

*p  0.10, **p  0.05, ***p  0.01. Note: Ordinary least squares regression results with robust standard errors in parentheses. Sample includes only households participating in a PHS program.

ence in assets between an average household enrolled in PHS and a household not enrolled in PHS is null (Table 3). However, when payment is large enough, households do appear to increase their investments in material assets (Table 4). Both technical assistance and PHS payment amount influence perceived equity and benefits of the PHS program (Table 4). An additional training increases perceived equity and benefits by about 0.08. A one-percent increase in PHS payment amount results in a 0.002 increase in perceived equity and benefits. That both types of extrinsic motivators are related to positive perceptions of the PHS program parallels findings that many ecosystem services providers would like technical assistance, in-kind materials, or rural development benefits, in addition to cash, to be part of PES contracts (Kosoy et al. 2008; Torres et al. 2013; MendezLopez et al. 2015; Figueroa et al. 2016). Cash payment also plays a critical role in why communities and individuals participate in PES programs and the perceived benefits of such programs (Kosoy et al. 2008; Torres et al. 2013; Mendez-Lopez et al. 2015; Figueroa et al. 2016). When we exclude respondents that receive the top 10% of PHS payments (Appendix B, Table B.4), we find that PHS payment amount is no longer correlated with perceptions. However, receiving technical assistance remains statistically significant and has a similar size coefficient. This change in the coefficient on PHS payment suggests that households that receive lower payment amounts do not perceive as much economic benefit from the program, and or that these households are less likely to perceive the program as fair. We checked pairwise correlations across statements in Appendix B, Table B.2 and the amount of cash received, after excluding households that receive the top 10% of payments. The strongest correlation was between cash received by these households and disagreeing with the statement in Appendix B, Table B.2 that states ‘‘benefits from PHS are shared fairly across ejido members”. This suggests that households receiving less cash payment perceive PHS as less equitable in distribution of benefits than households receiving the top 10% of payments. The community organization index has the largest impact on perceiving the PHS program as fair and beneficial (Table 4). A one-point increase in community organization increased perceived equity and benefits by about 0.3. Community organization and capacity have been related to effective and equitable PES programs in other contexts (Clements et al. 2010; Pascual et al. 2010; Pascual et al. 2014; Hayes et al. 2015; Hayes et al. 2017). Organized communities are more likely to adopt equitable rules of distribution of collective PES payment, and PES programs implemented amidst weak institutions may exacerbate underlying community power

asymmetries (Corbera et al. 2007; Clements et al. 2010; Rodriguez de Francisco et al. 2013; Almeida-Lenero et al. 2017). This would explain why community organization is positively associated with positive perceptions of equity. Strong community organization and capacity may also increase PES effectiveness through self-monitoring and enforcement of program rules (Hayes et al. 2015; Hayes et al. 2017), and may explain why PHS participants perceive more benefits from PHS programs if their ejido is well organized. Having received education has a statistically significant (90% level) and negative effect on perceived equity and benefits (Table 4). More educated households may have higher expectations of PHS programs and therefore be more likely to rate the equity and benefits lower. The size of an individual’s parcel becomes statistically significant (90% level) with a negative effect on perceptions when households receiving the top 10% of payments are dropped (Appendix B, Table B.4). This suggests that households with more land view the program as less equitable and beneficial than those with smaller parcels, probably because their relative proportion of benefits to land size is smaller. 4.3. Implications for PHS programs Our impact evaluation results suggest that common-use PHS contracts are positively influencing household-level land use changes on individual parcels and have modest impacts on material wellbeing in our study area. Most PHS participants have positive perceptions of the PHS program. However, the two extrinsic motivators considered in this study—cash payment and technical assistance—contribute differently to achieving these outcomes based on our regression results. Technical assistance contributes positively to adopting conservation actions and perceiving the PHS program as equitable and beneficial. Technical assistance is provided for common-use enrolled forest by all PHS programs in our study, but the MF-PHS operators also developed a more intensive technical assistance and outreach program aimed at household-level changes to land use. This IWRM approach does appear to result in additional adoption of land use actions on individual parcels (Table 2), but the relative difference between providing this type of assistance versus interacting with the technicians provided by all PHS approaches is not as large as one might expect. Thus, we cannot conclude that the costs of adding IWRM to the MF-PHS program are worth the additional benefits to adoption of land use activities alone. Of course, IWRM targets other benefits not measured in this study, including capacity building, development of watershed committees, and climate

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adaptation strategies; these other benefits would need to be measured to do a full benefit-cost analysis of this approach. Households that received more information and technical assistance perceived the PHS program as more equitable and beneficial. The influence of technical assistance on perceptions, or subjective wellbeing, reinforces findings in other studies that many PES participants would like ‘‘activity enhancing” versus only ‘‘activity restricting” activities as part of the PES design (Kosoy et al. 2008; Torres et al. 2013; Mendez-Lopez et al. 2015; Figueroa et al. 2016; Jones et al. 2017). This preference may be related to market and credit constraints in rural areas that limit the ability of cash alone to lead to livelihood changes (Jayachandran 2013; Jones et al. 2017). Additionally, the amount of cash payment received through PES contracts is often too small to result in large economic benefits to households (Clements and Milner-Gulland 2015). Thus, including non-monetary types of extrinsic motivators in PES programs, in combination with cash payment or alone, may be needed to achieve longer-term livelihood and ecosystem sustainability. Related to the latter, studies have found that activity-enhancing PES can lead to permanent changes in land use practices (Pagiola et al. 2016), whereas activity-restricting PES is unlikely to lead to permanence in ecosystem services provision (Le Velly et al. 2017). The findings in this study suggest tradeoffs in how cash payment influences material and subjective wellbeing measures. PES programs that want to change material wellbeing, an important target in poverty alleviation programs, may need to offer larger annual payment amounts. This is suggested by the strong correlation between cash and investment in material assets in our study. However, increasing cash amounts could result in crowding out of intrinsic motivations versus crowding in inherent reasons for participating in PES programs (Rode et al. 2015; Chan et al. 2017). Increasing cash payment in common-property PES contracts could also lead to elite capture of benefits and exacerbate negative perceptions of equity within communities if benefits are not distributed fairly (Pascual et al. 2014). Our results suggest that ejidatarios that receive smaller cash payment are less likely to view the distribution of benefits from the PHS program as fair; this could undermine the legitimacy of the PHS program in the long-term and have implications for future community-level projects. The above finding highlights the importance of community organization and governance in achieving equitable and effective PES outcomes. Community organization is critical to individual satisfaction with PHS programs in our study, regardless of payment level or having received technical assistance, and has been linked to conservation effectiveness and equity in other commonproperty PES programs (Clements et al. 2010; Hayes et al. 2015; Hayes et al. 2017). Currently, PHS programs in Mexico do not delegate how individual cash benefits are distributed within common-property contracts. The equity challenges of community-based conservation approaches are not unique to PES (Pelletier et al. 2016), and suggests that to achieve equitable PES, program operators may need to give more attention and oversight to payment distribution. Of course, providing conditionalities on how money is distributed could undermine feelings of autonomy and control between program participants and program operators, a component of procedural equity. In some PES approaches, there has been a shift away from providing cash payment to providing more in-kind benefits or vouchers (Bulte et al. 2016). Elite capture may be less likely using these other forms of extrinsic motivators. We do not find any association between cash payment and implementing individual conservation actions in our study. However, the PHS payment may affect forest conservation on common-use lands, and so we cannot conclude that payment does not result in conservation outcomes. Several studies have measured additionality of forest conservation from PHS contracts in Mexico and found that these programs have avoided modest

amounts of deforestation due to the cash payments (Scullion et al. 2011; Alix-Garcia et al. 2012; Alix-Garcia et al. 2015; Costedoat et al. 2015; Sims and Alix-Garcia 2016; Le Velly et al. 2017). In sum, our findings, coupled with other PES studies, suggest that PES cash payments may be useful as a ‘‘fast” policy response (Walker et al., 2012) to avoid deforestation, but combining cash payments with ‘‘slower” policy responses (Walker et al., 2012), such as technical assistance or capacity building, will help achieve sustainable and long-term impacts on ecosystem services provision (Petheram and Campbell 2010; Garbach et al. 2012; García-Amado et al. 2011; Pagiola et al. 2016; Cetas and Yasue 2016). Utilizing non-cash forms of extrinsic motivators may also help ensure equity within common-property PES contracts and may lead to material and non-material benefits. 5. Conclusion There is increasing emphasis on evidence-based conservation and the use of impact evaluation methods to assess outcomes from conservation interventions. We use quasi-experimental methods to test for differences in household-level outcomes across respondents participating and not participating in common-property PHS contracts, and find evidence that PHS affects adoption of conservation actions and in some cases, material assets. These householdlevel effects suggest that PHS contracts on communal lands can lead to positive changes for individual’s parcels and material wellbeing. We use regression analysis to tease out the role of cash payment and technical assistance, both provided within the PHS programs, on conservation and human wellbeing outcomes for those households participating in PHS. Material and subjective wellbeing are both positively influenced by the amount of cash payment a household receives, but the latter holds only for those households that receive the largest payment amounts. Subjective wellbeing is positively related to technical assistance for all households. The adoption of land use practices on an individual’s parcel is positively correlated with receiving technical assistance but not cash payment. These differences highlight the need to consider PES not as a uniform conservation approach but as the combination of different types of external motivators, with different influences on conservation and human wellbeing outcomes. This study also highlights the importance of community-level organization and capacity in the success of conservation programs such as PES. Acknowledgements This paper has benefitted significantly from the comments of two anonymous reviewers. This research would not have been possible without significant support from FONCET, INIFAP, and TNCMexico. We thank the Chiapas CONAFOR office for their time and willingness to share data. Lastly, we are indebted to the communities and individuals that participated in this research for their time and assistance. Financial support KWJ acknowledges field support from the Department of Human Dimensions of Natural Resources, Colorado State University. FONCET, INIFAP, and TNC-Mexico all contributed in-kind or financial support to this study. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.ecoser.2018.04.008.

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