Guideline framework for effective targeting of payments for watershed services

Forest Policy and Economics 104 (2019) 93–109

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Forest Policy and Economics journal homepage: www.elsevier.com/locate/forpol

Guideline framework for effective targeting of payments for watershed services

T

Ligia Maria Barrios Campanhão , Victor Eduardo Lima Ranieri ⁎

Escola de Engenharia de São Carlos, Universidade de São Paulo, Avenida Trabalhador São-Carlense, 400, 13566-590, São Carlos, SP, Brazil

ARTICLE INFO

ABSTRACT

Keywords: Payments for environmental services Targeting Prioritization Priority areas Watershed schemes Watershed services

Payments for Watershed Services (PWS) have become popular for the conservation of environmental services. As effectiveness is influenced by PWS design and the local contexts in which they are implemented, deficiencies in the process of targeting providers can affect the success of PWS schemes in achieving their goals. This article presents a framework based on data obtained from systematic reviews of worldwide Payments for Environmental Services (PES) schemes and the scientific literature to guide the process of targeting PWS schemes, especially in rural private areas in fragmented landscapes. The framework comprises four sets of operational guidelines for the targeting process based on the scientific literature. A table explaining the data extracted from the literature and PES schemes is provided, comprising the targeting criteria of benefits, risk, cost, socioeconomic issues, and readiness. The framework supplements current approaches that focus on biophysical criteria and is the first initiative to incorporate multidimensional aspects of PES in targeting guidelines. As it gathers empirical and scientific knowledge to promote an effective scheme design, the framework can contribute to the achievement of PWS goals.

1. Introduction Payments for Environmental Services (PES) (Wunder, 2015, p. 241) are “(1) voluntary transactions (2) between service users (3) and service providers (4) that are conditional on agreed rules of natural resource management (5) for generating offsite services” and have become popular in environmental services conservation. Although industrialized countries have substantial experience with market-based instruments, such as agri-environmental programs in the EU and US, PES has gained prominence in the environmental policy of developing countries, mainly in Latin America (Schomers and Matzdorf, 2013). Conservation practitioners and policy-makers' increasing interest in PES is attributed to alleged benefits such as more cost-effectiveness than command-and-control regulation and Integrated Conservation and Development Projects (ICDPs) (Engel et al., 2008). Moreover, a side goal of PES is poverty alleviation through providing income to poor rural households (Bulte et al., 2008; Pattanayak et al., 2010). The incentive is deemed a potential alternative to achieve environmental and development goals in developing countries (Lipper et al., 2009). Among Payments for Watershed Services (PWS) schemes that cited socioeconomic goals in 2011, almost half aimed to alleviate poverty (Bennett et al., 2013). Other goals are the guarantee of indigenous rights, gender equity, and community management of natural resources (Bennett ⁎

et al., 2013). PES have been driven by the ideology of “market environmentalism” (Kosoy and Corbera, 2010), and a recent discussion on whether the PES underpins the neoliberalization of environmental governance has emerged (Fletcher and Büscher, 2017; Van Hecken et al., 2018). Kosoy and Corbera (2010) affirm that market-based PES would simplify complex human-nature systems, disregard plural values, crowd out conservation behaviors, and overlook power asymmetries. When PES are externally imposed in complex contexts, a conflict with local needs, priorities, and social norms may arise (Wegner, 2016), and diverse and unexpected impacts on environmental governance may occur (Corbera et al., 2007). However, the PES hybridizes with other mechanisms as it encounters contrasting local realities (McAfee and Shapiro, 2010; Shapiro-Garza, 2013), and there is a growing consensus that few PES schemes can be considered “true” markets (Muradian et al., 2010, 2013; Wunder, 2015; Matulis, 2017). While PES has become an attractive tool for policy-makers and conservation practitioners based on their potential multiple benefits (Muradian et al., 2013), this success is related to their design and the political, environmental, and socioeconomic contexts in which they are implemented (Jack et al., 2008; Börner et al., 2017). A PES design aspect is targeting, which is the process of selecting participating parcels among those eligible for a PES scheme (Kroeger, 2013; Engel, 2015).

Corresponding author. E-mail addresses: [email protected] (L.M.B. Campanhão), [email protected] (V.E.L. Ranieri).

https://doi.org/10.1016/j.forpol.2019.04.002 Received 28 June 2018; Received in revised form 26 March 2019; Accepted 2 April 2019 Available online 28 April 2019 1389-9341/ © 2019 Elsevier B.V. All rights reserved.

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Targeting is frequently associated with achieving higher PES efficiency, cost-efficiency, or cost-effectiveness (Alix-Garcia et al., 2008; Wünscher et al., 2008; Chen et al., 2010; Ferraro, 2011; Wünscher and Engel, 2012; Schomers and Matzdorf, 2013), and recommendations to use criteria related to environmental services provision, risk of environmental service loss, cost of applications (Wunder, 2007; Wünscher et al., 2008; Wünscher and Engel, 2012), and cost-benefit targeting methods (Babcock et al., 1997; Alix-Garcia et al., 2008; Wünscher et al., 2008; Chen et al., 2010; Wünscher and Engel, 2012; Duke et al., 2014) have been proposed. However, few PES programs employ such criteria (Wünscher et al., 2008; Wunder et al., 2018) and methods (Duke et al., 2014). On the other hand, targeting based mainly on criteria driven by market concepts and imposed by external actors (i.e., neoliberal-framed targeting) has been criticized (Muradian et al., 2010; Kolinjivadi et al., 2015), for example, those focused on identifying areas of low opportunity costs, high additionality, and high poverty levels (Kolinjivadi et al., 2015). These strategies, which are aimed at maximizing PES efficiency, assume an unrealistic society disconnected from nature (McAfee and Shapiro, 2010) and disregard socioeconomic pressures, political interfaces, or local cultural backgrounds that can shape PES outcomes (Kolinjivadi et al., 2015). Optimizing targeting using costeffective methods may compromise the equitable distribution of payments (Narloch et al., 2011) and raise ethical questions, for example, through prioritizing large landholders to the detriment of smallholders (Pascual et al., 2014). Disregarding the contextual aspects that shape environmental degradation and incidence of poverty and employing neoliberal-framed targeting could lead to the attribution of the “burden” of environmental protection to the poor when historically they are not responsible for the loss of environmental services (Muradian et al., 2010; Kolinjivadi et al., 2015). The poor with the lowest opportunity costs may accept the payments not because they are willing to joining the scheme, but due to their condition (Muradian et al., 2010). This indirectly restricts their freedom to choose alternative land uses (Muradian et al., 2010) and illustrates the power asymmetry between the actors involved in PES implementation, such as sponsors and providers (Kolinjivadi et al., 2015). This impact can negatively influence ecological outcomes through feedback, such as reduced project legitimacy (Pascual et al., 2014). As a result, PES may not produce long-term positive impacts for either poverty or the environment (Kolinjivadi et al., 2015). Improving PES design, particularly the targeting process, is a research priority aimed at enhancing the mechanism's cost-effectiveness (Ferraro, 2011; Schomers and Matzdorf, 2013). Scientific guidelines must be refined and tools, metrics, and methods developed to improve this design (Naeem et al., 2015). The number of incentives has increased, particularly PWS schemes (Bennett et al., 2013). Porras et al. (2008) counted 95 running or implementing PWS schemes in developing countries. In 2011, Bennett et al. (2013) mapped 205 running and 76 proposed programs covering 117 million hectares. A survey by Grima et al. (2016) indicated that half the 40 cases evaluated in Latin America focused on watershed services. Targeting is imperative for several PES schemes, particularly large-scale ones, as a limited budget must be allocated to a large number of eligible providers. Therefore, PES need to be properly designed and implemented to achieve goals while considering the multidimensional aspects that influence their effectiveness. Although the criticism presented is directed to the neoliberal-framed targeting dissociated from local complexities, PES programs can allocate payments to achieve both well-being and ecological goals (Kolinjivadi et al., 2015). Nevertheless, the implementation of PES is a social and political construction, as it will be embedded in pre-

existing social organization structures (Vatn, 2010). Therefore, targeting should be based on multi-criteria evaluation that considers the multiple and contrasting values of social actors, so that priorities can be deliberated continuously rather than defined by an external process that does not recognize local particularities (Kolinjivadi et al., 2015). Although studies have introduced targeting methods (e.g., Wünscher et al., 2006, 2008; Wendland et al., 2010; Viña et al., 2013) and general principles (e.g., Engel et al., 2008; Kroeger, 2013), targeting criteria and recommendations are spread in the literature and no study has synthesized them into a framework. This article proposes a framework for the targeting of PWS schemes in highly fragmented landscapes based on systematic reviews of the scientific literature and PES programs. It is comprised of targeting guidelines, i.e., a set of recommendations to design effective targeting methods, and criteria that can be spatialized through indicators to distinguish areas or providers of environmental services. The framework can be employed to evaluate or redesign PWS scheme targeting approaches in industrialized and developing countries. It incorporates the plural and sometimes contrasting views on multidimensional aspects affecting targeting success found in the PES literature and practice. The framework can promote a deliberative targeting process, since it provides researchers, practitioners, and policy-makers with guidelines and criteria covering several aspects that could be considered. The actors involved in and affected by PES implementation can use the framework to determine which guidelines and criteria are legitimate and relevant to the local context where the incentive will be applied. The paper is organized as follows. Section 2 introduces the conceptual framework of PES effectiveness that guided the analysis of the review data. Section 3 details the methods for data collection and construction of the framework. Section 4 describes the framework, targeting criteria, and guidelines for PWS schemes. Section 5 provides a discussion, and Section 6 provides concluding remarks. 2. Background and concepts PES aims to avoid the loss or restore the provision of environmental services (Pagiola et al., 2005). Conserving and restoring natural cover, implementing agroforestry systems, and other best management practices are activities employed to achieve this goal (Wunder et al., 2008). Some PES schemes have side goals such as poverty alleviation (e.g., PSA Costa Rica, PRONAFOR, and “Grain for Green”) (Wunder et al., 2008). Although PES can achieve these multiple goals (Locatelli et al., 2008), they are not a policy panacea and the results are influenced by implementation contexts, particularly institutional and governance contexts (Jack et al., 2008; Muradian et al., 2013). Moreover, areas with overlapping priority for multiple goals are generally rare (Zhang and Pagiola, 2011). Further evidence is needed regarding the impact of PES programs in alleviating poverty (Engel et al., 2008; Wunder, 2008; Pattanayak et al., 2010; Alix-Garcia and Wolff, 2014). Nonetheless, poor providers can attain other benefits from PES programs besides income, such as strengthened land tenure, community organization, and training in conservation practices (Grieg-Gran et al., 2005; Pagiola et al., 2005; Wunder, 2008; Bremer et al., 2014). The success of PES is related to environmental effectiveness, which comprises four aspects: program costs, additionality, leakage and spillovers, and actual provision of environmental services (Börner et al., 2017). Furthermore, social outcomes such as equity are important when evaluating PES effectiveness (Pascual et al., 2010, 2014; Börner et al., 2017). PES programs usually cover opportunity, transaction, and conservation costs (Wünscher et al., 2008). Opportunity costs refer to the

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profit a provider foregoes when choosing to implement conservation activities over alternative land uses, transaction costs include all expenditures on the signature and maintenance of contracts between providers and users, and conservation costs refer to on-the-ground practices (Wünscher et al., 2008). Calculating costs is imperative in evaluating the cost-effectiveness of PES compared to other conservation tools. Substantial transaction costs may jeopardize the implementation of PES schemes, particularly those publicly funded (Wunder et al., 2008). Additionality refers to the net environmental benefits achieved by PES against a baseline that shows temporal trends in environmental services provision in the absence of the incentive (Wunder, 2005; Pascual et al., 2010). Therefore, benefits must be measured against constant, decreasing, or increasing provision (Wunder, 2005). Based on such trends, policy-makers can speculate whether the payment will increase the supply of environmental services or will not provide additional benefits because the targeted area is under no threat of service loss and would be conserved anyway (Engel et al., 2008). PES programs that target areas with additionality, i.e., areas where the desired service flow is guaranteed only by the incentive, are more cost-effective (Wunder, 2005, 2007; Engel et al., 2008). Nevertheless, the lack of additionality is a common cause of the ineffectiveness of PES schemes (Wunder et al., 2008; Pattanayak et al., 2010; Naeem et al., 2015). In addition, the overall additionality of a PES scheme must consider leakage and spillover effects (Le Velly and Dutilly, 2016), which are described below. The concept of “additionality” mentioned in this article refers to the a priori additionality of each provider, i.e., without considering leakage and spillover impacts. PES schemes may suffer from leakage, i.e., direct and indirect negative impacts of the incentive in areas other than those enrolled in the scheme. For example, leakage occurs when pressures on environmental services are displaced to areas not covered by the incentive (Wunder, 2005; Wunder et al., 2008). Furthermore, the scheme may cause spillovers, i.e., inducing the conservation of non-enrolled areas (Pattanayak et al., 2010). For example, spillover occurs when landowners stop deforestation in non-enrolled lands, because they expect to receive payments in the future (Alix-Garcia and Wolff, 2014). Measuring and monitoring the actual provision of environmental services is difficult, because of complex interactions between the abiotic and biotic components of ecosystems (Fisher et al., 2009). PES programs employ land use proxies that are easily measured and monitored, such as vegetation buffers and total forest cover (Jack et al., 2008). However, the link between land use practices and ecosystem functions needs further investigation (Wunder, 2007; Jack et al., 2008; Wunder et al., 2008), especially at the local and regional scales (De Groot et al., 2010). A clear link indicates that land use practices affect environmental service provision, impacting PES environmental effectiveness (Kosoy et al., 2007; Kroeger, 2013; Alix-Garcia and Wolff, 2014). Equity has many dimensions including stakeholders' power and influence in decision making; distribution of positive and negative impacts of conservation actions; recognition of stakeholders' knowledge, values, social norms, and rights in design and implementation; and the social context shaping stakeholders' engagement in PES programs (e.g., power relations, gender, and education) (Pascual et al., 2014). PES can cause both positive and negative impacts on social equity (e.g., the

inclusion or exclusion, respectively, of vulnerable stakeholders from decision-making), which influence environmental outcomes and efficiency through feedback (Pascual et al., 2014). These impacts and feedbacks are shaped by the implementation context, which requires that their assessment should consider different spatial and temporal scales (Pascual et al., 2014). Long-term environmental outcomes and cost-effectiveness may be impaired if equity concerns are overlooked during program implementation and design (Narloch et al., 2013; Pascual et al., 2014). Therefore, to strengthen the long-term sustainability of the incentive (Adhikari and Boag, 2013; Pascual et al., 2014; Börner et al., 2017), the multidimensional aspects of social equity should be explicitly considered in PES design and implementation (Pascual et al., 2014). Considering equity concerns in design may increase the costs and complexity of PES schemes (Pascual et al., 2014), although cost-effectiveness is not always compromised (Narloch et al., 2013). Accordingly, the interaction between equity and PES effectiveness needs investigation to clarify when equity concerns affect environmental outcomes (Pascual et al., 2014). Essentially, environmental and equity outcomes are influenced by implementation contexts and scheme design (Narloch et al., 2013). The complexities of the local socio-ecological context should be recognized and incorporated to promote the design of effective PES schemes (Adhikari and Boag, 2013; Pascual et al., 2014; Engel, 2015). PES schemes may not succeed if they do not incorporate evidence from practice (Pascual et al., 2014) and are not designed based on scientific evidence (Börner et al., 2017). 3. Data and methods The framework was based on systematic reviews of PES schemes and the scientific literature conducted to collect targeting criteria and recommendations. A systematic review is characterized by explicit rules for the selection, analysis, synthesis, and presentation of empirical evidence for a research topic (Higgins and Green, 2011). This method lessens the author bias associated with narrative reviews, for which review rules are not systematically documented (Cook et al., 1997). Systematic reviews are an efficient way to provide a comprehensive baseline to orientate environmental policy decisions (Pullin et al., 2009; Bilotta et al., 2014; Woodcock et al., 2014). Here, the systematic reviews were performed according to a protocol adapted from Higgins and Green (2011). 3.1. Targeting criteria employed by PES schemes The research question was “What targeting criteria are employed by PES schemes?” First, the PES schemes to be investigated were defined. A list of cases was derived from Wunder et al. (2008), Schomers and Matzdorf (2013), Naeem et al. (2015), and Watershed Markets (2016). The list comprised 92 schemes from Asia, the Americas, Africa, Europe, and Oceania. A second list of 48 Brazilian cases was extracted from Guedes and Seehusen (2011) and Pagiola et al. (2013). All reviewed PES schemes aimed to safeguard watershed services by improving water quality and/or quantity. Many aimed to conserve and restore natural cover, and finance the implementation of best management practices such as terracing and organic farming.

environmental payment*

ecosystem

service*

Name of the PES scheme

Additional keywords

watershed

95

Fig. 1. Boolean expressions used in the search for PWS schemes targeting criteria. Notes: * = indicates a group of unknown characters or no characters. “” = used for grouping words and searching for the expression.

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payment*

ecosystem

“targeting” service*

watershed

Is the full text available? yes

“prioriti*ation” “priorit* area”

Fig. 2. Boolean expressions used in the systematic review of the scientific literature. Notes: * = indicates a group of unknown characters or no characters. “” = used for grouping words and searching for the expression.

Is the full text written in English, Spanish, or Portuguese? yes

no

Does the study focus on PES or environmental services?

no

yes

The search strategy initially focused on references cited by the studies consulted to extract PES lists and websites of organizations involved in implementing and executing the programs. When necessary, additional searches were performed using Scopus, Google Scholar, and the Google search engine, since much information is provided by documents not indexed by academic databases, such as public edicts, manuals, decrees, and other documents on PES schemes. Boolean expressions combining different keywords (Fig. 1) were used for the database search. Additional keywords such as targeting, priority areas, and prioritiz(s)ation were occasionally used to refine results. Boolean expressions in English plus Spanish and Portuguese were employed, since Latin America has many running PES schemes (Porras et al., 2008; Schomers and Matzdorf, 2013). Therefore, several studies and official documents related to these Latin American schemes were written in the countries' official languages, namely Spanish or Portuguese. Retrieved documents were screened by title and abstract, and those considered relevant were fully read to find criteria for targeting areas (municipalities, watersheds, communities, and rural properties), applications, or providers. The documents were then analyzed according to eligibility criteria for their selection or exclusion. Only documents written in English, Spanish, or Portuguese with identifiable authorship were consulted. We only included the targeting criteria from implemented PES schemes; therefore, programs whose contracts and payments had not yet started were excluded from the review. Targeting criteria applied since 2005 were compiled, and those not updated for more than ten years excluded. When possible, the criteria were exactly transcribed from the source document. However, some criteria were synthesized into one or a few sentences to facilitate data manipulation in the next methodological steps.

Does the study provide criteria or recommendations for PES targeting?

no

yes Are the criteria and recommendations applicable to PWS schemes? yes

no

Are the criteria and recommendations applicable to fragmented landscapes? yes

no

Are the recommendations explicit and supported by the analysis developed in the study? Do the authors justify the choice of targeting criteria?

no

yes Study included in the review Fig. 3. Eligibility criteria for the selection of studies in the systematic literature review.

Muradian et al., 2010; Pagiola et al., 2005; Wunder, 2005; Wunder et al., 2008) to refer to the process of selecting the best applications. This strategy was chosen to increase the comprehensiveness of the search while maintaining its precision, i.e., retrieving a good proportion of existing relevant studies while avoiding identifying a large number of non-relevant studies (Lefebvre et al., 2011). We chose not to consider keywords related to known targeting criteria (e.g., environmental service provision, risk of environmental service loss, and costs) to limit author bias, i.e., to avoid directing the review based on the authors' previous knowledge of the research topic (Bilotta et al., 2014). However, due to the systematic search and selection of studies, it is intrinsic to the systematic review that not all relevant existing studies can be identified. The search was performed in the two databases in June 2016. Records were transferred to reference management software and repeated results merged. In total, 108 studies were read under different filters: first only the title, abstract, and keywords, and then the full text. Eligibility criteria (Fig. 3) were applied to select or exclude studies. By analyzing the studies included in the systematic review, targeting recommendations were extracted. All aspects authors claimed might influence targeting effectiveness were considered.

3.2. Targeting guidelines and criteria from the scientific literature The second research question was as follows: “What criteria and recommendations for PES targeting are provided by the scientific literature?” The aim was to collect criteria for targeting priority areas or providers and recommendations to elaborate the guidelines for effective targeting. The searches were conducted in Scopus and Web of Science, and Boolean expressions with keywords in English were used (Fig. 2). Search terms can be extracted from the research question and relevant articles within the scope of the review by analyzing how authors use different terminologies, spelling, and synonyms (CEE, 2018). The Boolean expressions were defined based on an exploratory bibliographic analysis. The term “payment*” was chosen because it returned more results in both databases when compared to the terms “rewards,” “co-investment,” and “incentives.” The terms “environmental” and “ecosystem” were both employed as they were equally disseminated in the literature. The term “watershed” was used to capture studies which focused on PWS schemes. Since the review focused on both targeting recommendations and criteria, the terms “targeting,” “prioriti*ation,” and “priorit* area*” were selected, as they were employed by relevant high-cited PES studies at the time of the search1 (i.e., Engel et al., 2008; 1

no

Exclusion

environmental

3.3. Construction of the guideline framework Targeting criteria and recommendations were compiled, codified, and categorized following methodology for qualitative data (Flick, 2009). Recommendations representing the same concept were summarized into targeting guidelines, and criteria representing the same concept were synthesized into a single criterion. Indicators, i.e., variables employed to measure a specific criterion, were also collected and presented.

Searches were performed in Google Scholar in 2016. 96

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Risk

Records identified through database search Scopus (n = 161) Web of Science (n = 145)

5

Cost

Socioeconomic issues

3

33

Readiness

11 25

14 records excluded

108 records screened by title, abstract, and keywords

31

35

198 duplicated records

94 records screened by introduction, conclusion, and keywords searching

16 20

69 records screened by results and discussion

Number of PES schemes that employ the criterion

Elegibility criteria

Benefits 1

25 records excluded

30 records excluded

39 records included in the review

Number of PES schemes that do not employ the criterion Fig. 4. Proportion of PES schemes that employ criteria from each class.

Fig. 5. Results of the filtering process of the systematic review.

4. Results

provided criteria and indicators and 31 included recommendations for the targeting process. Finally, 12 studies provided both targeting criteria and recommendations. Furthermore, 19 studies of the total sample and 18 of the 31 studies that provided recommendations use actual program data in the analysis (Supplementary data, Table II). From the 20 cited studies, 92 criteria suitable for PWS schemes were extracted, 84 criteria categorized into the classes described in section 4.1, and 8 criteria excluded because they lacked information for categorization. None of the 20 studies provided readiness criteria, while cost criteria were frequent (Fig. 6), indicating a different scenario from that for PES schemes (Fig. 4). Furthermore, 47 recommendations were extracted from the 31 studies and synthesized into 23 guidelines for effective targeting, which were classified into 4 groups. The first regards the setting of scheme goals, environmental services, targeting criteria, and indicators. Group 2 refers to the measurement of indicators. Group 3 addresses criteria aggregation and targeting methods, and Group 4 describes guidelines for the planning, implementation, and operation of the targeting process. The guidelines were also classified as primary or secondary. Primary guidelines are acknowledged in at least two studies as relevant for targeting effectiveness. Secondary guidelines comprise recommendations from a single study based on conclusions in a specific context. They may be relevant for particular PWS schemes with similar context features.

The results of both systematic reviews and the guideline framework are presented below. 4.1. Targeting criteria employed by PES schemes Targeting criteria from 36 PES schemes from all continents, except Oceania, were collected (Supplementary data, Table I). Although three programs were not in the original reference list, they were included, because their criteria were identified during the search of other PES cases. In total, 343 targeting criteria, of which 320 are applicable to watershed schemes, were compiled from the 36 PES programs. The other 23 criteria were excluded, because they were specific to biodiversity and carbon services. The included criteria were categorized into 42 synthesized criteria. Seven criteria were not categorized because of a lack of information, and nine were excluded because they were specific to urban areas and industrial forestry and agroforestry projects. The 42 synthesized criteria were clustered into five classes: (1) benefits, including criteria related to environmental services provision (services expected in a given location) (Wünscher et al., 2008); (2) risk of service loss (Wünscher et al., 2008)2; (3) costs (Wünscher et al., 2008); (4) socioeconomic issues, including criteria related to the socioeconomic goals of the PES; and (5) readiness, namely the local capacity of a targeted area to implement the PES scheme, such as existence of political will, public awareness, and stable institutions (Wünscher and Engel, 2012). PES schemes recognized readiness as an important targeting criterion, but few schemes employed risk and cost criteria (Fig. 4).

4.3. Guideline framework for the targeting of PWS schemes Table A.1 provides the guideline framework comprised of 8 primary and 15 secondary guidelines classified into the groups described in section 4.2. Before consulting the guidelines, PWS management practices such as conserving or restoring natural cover and soil conservation practices must be defined. Some guidelines can be translated into criteria and vice versa according to data availability and the interest of program managers. Some issues can also be considered as a guideline for the targeting process and criterion for the selection of providers such as partnerships with intermediaries. Table A.2 provides the criteria and indicators for targeting PWS schemes based on data extracted from the scientific literature and PES practice. The criteria cover the many dimensions of PWS, and indicators can be spatialized to identify priority areas or providers to receive the incentive. They are divided into five classes (section 4.1): benefits, risk,

4.2. Targeting recommendations and criteria from the scientific literature The outcomes of the systematic review are provided in Fig. 5. Data were extracted from 38 papers and 1 book chapter. Most studies are recent, and almost 60% were published after 2013. Of the 39 studies, 20 2

Although the results emphasize the priority of areas at risk of service loss (i.e., areas with decreasing trends in the provision of watershed services), areas with static or improving baselines could also be targeted, provided that the PWS has the potential to generate additional benefits vis-à-vis the counterfactual baselines (Wunder, 2007). 97

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Benefits 2

6 14

18 Cost

criteria and indicators for targeting PWS areas (Gauvin et al., 2010). The lack of a precise definition of PWS goals may lead to selecting areas that do not provide targeted services (Gjorup et al., 2016). 3) Consider service users' spatial demand and distribution: The definition and measurement of environmental services and identification of priority areas should consider users' distribution regarding the spatial-temporal flow of environmental services (Kroeger, 2013). This is mandatory for watershed services, the demand for which is local, not global (Cimon-Morin et al., 2013). Since the concept of environmental services is related to societal benefits (Kroeger, 2013), targeting criteria for users' demand should be employed in addition to biophysical indicators of service flow (Cimon-Morin et al., 2013). 4) Consider the impacts of spatial synergy: According to Duke et al. (2015), spatial synergy occurs when the conservation of two or more parcels provides more benefits when proximate or contiguous than spatially isolated in the landscape. When possible, the effects of spatial synergy should be quantified and considered, because overlooking them may compromise targeting effectiveness. The authors also state that in areas of potential spatial synergy, PWS applications should be selected according to the land use pattern of the surrounding parcels. For example, parcels not attractive to the PWS scheme should be enrolled if likely to affect environmental services provision in a neighboring priority parcel (Stone and Wu, 2010). This is true for PWS schemes, as the provision of watershed services is affected by upstream practices. Areas of synergy between multiple environmental services should be targeted first if the PWS scheme has other environmental goals (Zhang and Pagiola, 2011). Determining the effects of spatial synergy includes management benefits. PWS schemes usually focus on the property rather than landscape level of management, where many environmental services are produced (Reed et al., 2014; Cooke and Moon, 2015). The enrollment of contiguous rural properties enables coordination between landowners, facilitates collaborative resource management, and optimizes the achievement of conservation goals (Reed et al., 2014; Cooke and Moon, 2015). Besides targeting criteria for contiguity (Table A.2), scheme managers can employ agglomeration bonuses to encourage the enrollment of adjacent areas (Reed et al., 2014) by making an extra payment to areas enrolled contiguously in other PWS parcels (Parkhurst et al., 2002).

Risk

Socioeconomic issues

Readiness

4

8 12 16

20

Number of studies that employ the criterion Number of studies that do not employ the criterion Fig. 6. Proportion of studies that provided criteria from each class.

cost, socioeconomic issues, and readiness. All criteria and indicators can be applied in selecting areas for the activities of conservation or restoration of natural cover, except “Proportion of natural cover” and “Conservation condition,” which have two different targeting criteria for each activity, and “Restoration areas,” which applies only to restoration activities. The number of PES programs or studies that mention each criterion is cited in parentheses. A wide range of watershed services can be provided through the conservation and restoration of natural cover, namely, diverted water supply (e.g., for municipal, agricultural, industrial uses), in situ water supply (e.g., for hydropower generation, recreation, transportation, fish supply), water damage mitigation (e.g., reduction of flood damage, dryland salinization, saltwater intrusion), spiritual and aesthetic purposes (e.g., religious, educational, and tourism values), and supporting services (e.g., water and nutrients for supporting habitats) (Brauman et al., 2007). Risk, cost, socioeconomic, and readiness criteria can be applied by PWS schemes targeting any watershed service. Several benefits criteria can be employed to target multiple services, however, some of them are suited for particular services (e.g., “prioritize areas fragile or vulnerable to natural disasters” is adequate for PWS schemes interested in water damage mitigation). Policy-makers can find further information on watershed sub-services in Brauman et al. (2007) and Kroeger (2013).

4.3.1.2. Secondary guidelines. Set a single or priority goal: PES schemes aiming at multiple goals, such as watershed conservation, carbon stock, biodiversity, and poverty alleviation may not find sufficient target areas that contribute simultaneously to the achievement of these goals (Uthes et al., 2010). The spatial targeting of PWS practices should consider all such goals, but it is more appropriate and effective for areas where a single or priority objective is pursued (Uthes et al., 2010; Meyer et al., 2015). Consider the planning data produced for the area: The goals and priorities of a PWS scheme can be defined based on planning data available for the area. Landscape plans provide a detailed spatial information database on ecological and social functions, local pressures, and impacts, indicating the goals and priorities of the PWS scheme (Haaren and Bathke, 2008). Consider a combined definition of targeting criteria by scheme managers and landowners: Kelly and Huo (2013) found no significant differences between the criteria both stakeholders used to identify areas to enroll in a PES scheme. However, landowners make better decisions on recruiting areas within their property, while scheme

4.3.1. Definition of scheme goals, environmental services, and targeting criteria 4.3.1.1. Primary guidelines. 1) Consider using valuation methods to identify environmental services: Methods such as stated preference and benefit transfer can be employed to identify the environmental services most valued by users (Moore et al., 2013; Reed et al., 2014). Environmental services consensually prioritized by providers and users should be identified and targeted for PWS schemes (Bernués et al., 2014). 2) Consider scheme goals when selecting targeting criteria: Single or multiple scheme goals must be considered during the selection of

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managers are better able to select the properties to be enrolled at the landscape level. Therefore, in areas with several small properties and high administrative costs associated with price signals, the authors suggest targeting criteria can be defined by combining managers and landowners' preferences. Consider the existence of service provision thresholds:Stone and Wu (2010) discuss that the selection of priority areas for PWS schemes should focus on enrolling parcels that contribute to achieving thresholds, not on parcels that do not contribute. The threshold is the point where watershed service provision is significantly improved in a certain number of enrolled areas. PWS schemes should enroll sufficient areas in a single watershed to surpass its service threshold, rather than target several watersheds whose enrolled areas cannot achieve the threshold. Consider the impact of the PWS incentive on the intrinsic conservation motivation of providers: According to Alpízar et al. (2015), compensating an agent who makes no or few contributions to forest conservation may undermine the intrinsic conservation motivation of agents excluded from the rebate. Therefore, intrinsic conservation motivation should be considered during the targeting process to avoid negative impacts. The authors affirm this effect is likely when the argument for agent exclusion is previous conservation behavior, whereas the non-priority of the area is a better argument for agent exclusion and less likely to undermine intrinsic motivations. Contemplate the effect of social diffusion on targeting areas with additionality: The selection of areas with little or no additionality may not compromise the effectiveness of the scheme (GoldmanBenner et al., 2012). According to social diffusion theory, a behavioral change in a small share of the population can affect it entirely through spillover effects (Goldman-Benner et al., 2012) such as conservation of a non-enrolled area (Pattanayak et al., 2010). If this effect is likely, it is more effective to enroll areas with low additionality, but whose landowners are willing to fulfill the PES contract without high payments, not areas with high additionality and higher enforcement costs (Goldman-Benner et al., 2012).

4.3.3. Criteria aggregation and targeting methods 4.3.3.1. Primary guidelines. 1) Employ cost-effective targeting methods: This guideline endorses employing flexible payments and the Benefit-Cost Ratio to target applicants (Wünscher et al., 2006; Alix-Garcia et al., 2008; Chen et al., 2010; Jack, 2013; Duke et al., 2014). Additionality/Cost Targeting is considered the most effective method (Wünscher et al., 2008), while Benefit Targeting and Cost Targeting are highly inefficient and must be avoided (Duke et al., 2014). While complex approaches such as optimization algorithms can be applied (Hajkowicz et al., 2008; Duke et al., 2014), a simple assessment of the Benefit-Cost Ratio improves targeting effectiveness and performs as well as algorithms (Duke et al., 2014). However, the impact of these methods depends on indicators' heterogeneity (Wünscher et al., 2008; Chen et al., 2010; Gauvin et al., 2010) and correlation, which varies according to regions and scales (Wünscher et al., 2008). Cost-effective methods may not be easily applied because of data scarcity and low institutional capacity (Gauvin et al., 2010). Therefore, efficiency gains and costs related to implementation should be weighted (Wünscher et al., 2006). However, available local data can be used and the production of primary data for costeffective targeting is unnecessary (Duke et al., 2014). Another costeffective approach is reverse auctions (Jack, 2013), but the transaction costs should be weighed against efficiency gains (Wünscher et al., 2008). Stone and Wu (2010) pointed out that when conservation affects the price of crops and shifts production to nonenrolled lands (i.e., leakage), the effectiveness of benefit-cost targeting may be impaired. According to the authors, when such leakage is likely to occur, a benefit-maximizing targeting approach may be more appropriate. In this method, decision makers consider the possible effect of changes in commodity prices, and avoid lands that might be a source of leakage. 2) Define criteria weights: The relevance of each criterion in achieving scheme goals should be considered in the targeting procedure (Romero, 2012; Gjorup et al., 2016). The selection of priority parcels to achieve PWS goals may be hindered if greater weights are not assigned to the most important criteria (Romero, 2012). For example, Romero (2012) observed the Mexican scheme PRONAFOR employed numerous secondary criteria and few primary criteria (which are more relevant for the targeting of watershed services) that were equally weighted. The scoring approach led to selecting areas with low scores and excluding areas with higher scores for the primary criteria, because the many secondary criteria diluted the priority value. Weighting approaches include statistical and participatory methods (OECD, 2008).

4.3.2. Measurement of indicators 4.3.2.1. Secondary guidelines. Scale of indicators:Crossman et al. (2011) observed that site-scale indicators produced for a specific region slightly influenced the targeting of PWS contracts in comparison to landscape-scale indicators alone. Therefore, using landscape-scale indicators to select PES priority areas is satisfactory and the production of fine-scale indicators is unnecessary. Site-scale data should be elaborated only if decision-makers judge it necessary. Measurement of environmental services: According to Reed et al. (2014), some methods to estimate indicators can be employed when selecting areas that effectively provide environmental services. Pressure-response functions can help in assessing the link between anthropogenic pressures and ecosystem functions related to environmental services. Modeling approaches can be applied to identify areas where environmental services can be provided by specific management practices. If those tools are not available to scheme managers due to a program's budget constraints, a group of experts can evaluate these issues (De Groot et al., 2010; Reed et al., 2014). Methods must be validated and calibrated for a specific context as different methods produce different results (Reed et al., 2014). Measurement of deforestation risk: According to Alix-Garcia et al. (2008), this indicator should be measured by a predicted index, not according to the current deforestation rate. The predicted index should be based on variables that cannot be manipulated by landowners to avoid rewarding providers' bad conservation behavior.

4.3.3.2. Secondary guidelines. Contemplate regionalized targeting methods: According to Haaren and Bathke (2008), large-area schemes with multiple goals can select providers through different targeting approaches. In areas where environmental services are spatially restricted or vulnerable and exhibit a specific user demand, providers can be targeted and paid based on their success in protecting these services. In contrast, competitive methods like reverse auctions are more efficient for selecting service providers with a broader spatial distribution. Check correlations between indicators: Ignoring the correlations between indicators may lead to over-evaluating or under-evaluating criteria, producing biased results (OECD, 2008; Gjorup et al., 2016). Existing correlations can define the number and weight of criteria (OECD, 2008). For this refinement, the statistical results and

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managers understand the elements that drive or restrict providers' adherence. Promote the PWS scheme in the most relevant areas to achieve scheme goals: Adverse self-selection and inefficient targeting can strongly affect the effectiveness of PES, as they favor targeting unthreatened or low-benefit areas (Ferraro, 2011). Adverse selection is more likely when willingness to participate is low (Martin-Persson and Alpízar, 2013). Promoting the PES scheme in the most relevant areas where providers have low willingness to participate may help to avoid self-selection bias (Romero, 2012). Conduct adaptive management of the scheme: Adaptive management enables learning from practice, since the measurement, monitoring, valuation, and management of environmental services are permeated by uncertainties (Farley and Costanza, 2010). It can improve PES targeting over time, because it comprises an experimental design of the program, systematic monitoring and impact assessment to inform policy and generate feedback, and continuous reshaping of policy in response to feedback (Sims et al., 2014). According to the authors, three program features facilitate the employment of adaptive management: a policy environment that supports experimentation, critical thinking, and long-term funding; available high-quality data and technical capacity; and participation of stakeholders and external evaluators in implementing and redesigning the program.

contribution of the variable to the index under construction should be considered (OECD, 2008). Validate the targeting method: The method is deemed effective by comparing its selected areas with those obtained through another targeting method or those enrolled in a PWS scheme (Gjorup et al., 2016). Gauvin et al. (2010) compared their targeting method with five alternative methods, highlighting the advantage of their proposal. Wünscher et al. (2008) and Viña et al. (2013) compared the parcels selected through their proposed tools with those enrolled in running PES schemes. 4.3.4. Planning, implementation, and operation 4.3.4.1. Primary guidelines. 1) Undertake collaborative design of the PWS scheme: Collaborative design employs knowledge about the contextual dynamics and factors related to providers' adherence to implement an effective PES scheme (Petheram and Campbell, 2010). Landowners' participation in the design and implementation processes strengthens collaboration between providers (Reed et al., 2014; Cooke and Moon, 2015), contributes to the community's legitimization of the targeting approach (Reed et al., 2014), and favors landscape-scale management of the scheme (Cooke and Moon, 2015). Advantages including greater cooperation, credibility, and approval by providers are associated with the collaborative process of planning and data collection (Haaren and Bathke, 2008). Kolinjivadi et al. (2015) consider collaborative design a way of overcoming the targeting imposed by external agents who disregard the complexities of socio-ecological systems, political contexts, and cultural issues. PES targeting should be a social construction that considers stakeholders' priorities and is shaped by their continuous deliberation (Kolinjivadi et al., 2015). 2) Strengthen partnerships with local intermediaries: Intermediaries are key in providing assistance and information to providers (Petheram and Campbell, 2010; Schomers et al., 2015). They select relevant areas to achieve scheme goals, elaborate competitive applications regarding environmental benefits, and increase providers' interest (Higgins et al., 2014; Schomers et al., 2015). Intermediaries can adapt the PES to a specific implementation context and make it runnable (Higgins et al., 2014). They also facilitate cooperation among landowners at the landscape scale (Schomers et al., 2015) and the accessibility of small landowners by assisting them in the eligibility and documentation phases (Bremer et al., 2014). These intermediaries should be aggregated into the targeting framework; however, they must be locally recognized, accessible, and have trustful relationships with the community (Schomers et al., 2015).

5. Discussion A mismatch between science and practice emerged in the results reported in sections 4.1 and 4.2. Although the scientific literature considers cost criteria and cost-effective targeting methods important elements in an effective targeting process (Fig. 6; Table A.1), they are poorly addressed in the PES schemes investigated (Fig. 4). Wunder et al. (2018) obtained similar results for 70 reviewed PES cases. On the other hand, readiness is commonly addressed in PES schemes (Fig. 4) and highlighted by the scientific literature as an important element for targeting effectiveness (Table A.1). However, it has not been assimilated by targeting tools published in the literature, since no readiness criterion was extracted from such studies. The framework in this article includes the standard benefits and risk and cost criteria, and provides targeting indicators to assess socioeconomic goals and readiness aspects, supplementing previous targeting tools that do not consider these issues (e.g., Wünscher et al., 2006, 2008; Wendland et al., 2010). Therefore, the framework contributes to better alignment between science and practice so that PES programs can achieve their goals. The framework reinforces recommendations for PES's success cited in previous pieces on PES design (e.g., Wunder, 2007; Asquith and Wunder, 2008; Engel et al., 2008; Porras et al., 2008; Kroeger, 2013; Engel, 2015; FAO/UNECE, 2018), such as the involvement of stakeholders in the design and implementation of PES, consideration of local capacity (i.e., readiness), establishment of partnerships with intermediaries, employment of adaptive management, application of costeffective targeting methods, and effects of spatial synergy. The proposed framework supplements these efforts, since it is the first approach for targeting elaborated from evidence systematically extracted from the PES literature and practice. Systematic reviews are employed to reduce author bias, which is often associated with narrative reviews; therefore, the framework is not influenced by our professional and academic backgrounds. It offers a different perspective for PES research as it incorporates the plural ideas and approaches that permeate PES literature and practices.

4.3.4.2. Secondary guidelines. Assess providers' perceptions before implementing the PWS scheme:Richards et al. (2015) emphasized that the enrollment of providers in a Brazilian PWS scheme was tricky. Scheme managers had to persuade and even threaten landowners noncompliant with the Brazilian command-and-control mechanism to convince them to join the program. Decision makers should understand how providers value their land and regard the incentive to facilitate the targeting process (Richards et al., 2015). Several aspects intrinsic to the landowner and property affect providers' willingness to accept and fulfill the contract (Zbinden and Lee, 2005; Mudaca et al., 2015). A model by Petheram and Campbell (2010) may help scheme

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Fig. 7. Spatial distribution of a readiness indicator in São Paulo state, Brazil. Source: Instituto Brasileiro de Geografia e Estatística (2006)

schemes and improved targeting could offset them (Wünscher et al., 2008). The framework could reduce the transaction costs associated with targeting large and small-scale schemes, particularly start-up costs.3 The flexibility of guidelines and diversity of criteria can help reduce the costs associated with activities and information gathering in several design phases. Instead of allowing all plots to be eligible, managers of large-scale schemes can use the framework to identify priority regions. The framework could help target areas with low opportunity costs, institutional and contextual settings favorable to PES, or where it is legitimized by local communities. Therefore, PES can be targeted to regions where it is feasible, preventing it from being imposed where it is undesirable. The framework can help to assess the factors that favor or hinder the implementation of small-scale schemes. By assessing the conditions related to targeting effectiveness and, hence, PES success, policy-makers can determine whether the incentive is feasible for the watershed, or if another conservation mechanism is preferred. The following paragraphs illustrate how the framework can facilitate targeting and reduce the associated transaction costs. Table A.2 offers policy-makers a range of indicators that can be spatialized to determine PWS priority areas. A PWS scheme does not need to employ all the classes of targeting criteria and indicators, as their selection should follow the guidelines and depends on scheme goals and activities, as well as stakeholders' preferences. Although the framework is suitable for local and regional targeting, it can be applied across different spatial scales. Scale transposition of targeting criteria depends mainly on the pertinence of the criterion and the availability of indicators at the desired scale (Feld et al., 2009). Readiness criteria are more suitable for local and regional scales, as many of them operate at a higher scale of aggregation (i.e., distinguishing communities or regions). Risk criteria are more difficult to apply at finer scales (e.g., plot scale), since detailing a baseline for each eligible farm would be costly. Nevertheless, data such as deforestation risk indexes (e.g., Índice de Presion Económica a la Deforestación elaborated by the Mexican government and used in the PRONAFOR program) with adequate resolutions can be applied for this purpose. Interviews with landowners about the existence of household practices that threaten water quality and quantity are an alternative (Kolinjivadi et al., 2015). However, data

The guidelines are not intended to be a normative prescription to prevent PES programs from failing. Rather, the framework highlights the matters noted in the literature as relevant when planning an effective targeting approach. The published evidence was systematically extracted from the PES literature and compiled to make them easily available to policy-makers. Moreover, the framework can be a milestone for PES research by orientating forthcoming studies. The primary guidelines are more generalizable, but secondary guidelines can be complex and difficult to implement. Since they are cited by only one study, more evidence from theory and practice is needed to expand the knowledge about their impact on targeting effectiveness. PES programs that exhibit similar features to those addressed by the secondary guidelines may benefit from their recommendations. For the implementation of targeting guidelines and criteria, their relevance and legitimacy must be assessed through an analysis of local particularities and factors shaping social relations, rural poverty, and the loss of environmental services (Muradian et al., 2010; Kolinjivadi et al., 2015). In the Amazon forest, for example, poverty is linked to deforestation and settlement patterns (Eloy et al., 2012), and deforestation risk is linked to land tenure categories and overlapping forms (Holland et al., 2014). Therefore, the engagement of local communities must be promoted (Wegner, 2016), and targeting oriented by local knowledge with the support of external knowledge (Kolinjivadi et al., 2015). Start-up transaction costs can be substantial due to the volume of information and activities needed before the design of PES schemes can begin (Wunder et al., 2008). Publicly funded and large-scale programs are associated with low transaction costs (Wunder et al., 2008) due to the presence of public institutions acting as intermediaries (Vatn, 2018). Since they are applied to the watershed-scale, which facilitates the identification of users and providers, the transaction costs of PWS schemes tend to be lower than those of schemes targeting other environmental services (Alston et al., 2013). However, publicly funded and large-scale schemes often enroll parcels with no priority assessment and offer flat payments, which can counterbalance the low transaction costs (Wunder et al., 2008). On the other hand, small-scale schemes must enroll sufficient areas in a single watershed to surpass service thresholds; therefore; difficulty in enrolling landowners can raise transaction costs (Alston et al., 2013). Implementing and maintaining a targeting tool may increase transaction costs; however, they would be modest in large-scale

3 Although we discuss the impact of the framework on transaction costs of targeting, the discussion on transaction costs of PES vis-à-vis other conservation mechanisms (e.g., command-and-control) is not presented because it is outside the scope of this paper.

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collection at the farm-level can increase transaction costs of programs and may not strongly influence targeting effectiveness (Crossman et al., 2011). Indicators in Table A.2 can be employed using secondary data such as those elaborated by censuses or public authorities. We performed an exploratory search to identify which criteria could be applied to prioritize municipalities in São Paulo, the richest state of Brazil, where the state government currently coordinates a PES scheme called Mina d'Água. We identified that 25 out of 42 criteria from all classes in Table A.2 could be measured using open public data. Fig. 7 shows the spatial distribution of an indicator for the “intermediaries” criterion. The symbology distinguishes the percentage of rural properties in each municipality that received technical assistance in 2006 according to the Brazilian agricultural census. The variable values could be reclassified to attribute more priority to municipalities with higher percentages. Although some criteria are easily assessed using secondary biophysical or socioeconomic data, others are more difficult to measure and demand efforts from practitioners for their application in the targeting process. Hydrologic tools can be employed to measure benefits criteria (Table A.2), such as the “susceptibility to soil erosion” criterion, which was widely employed by PES schemes and cited often in the literature. Models that incorporate the Universal Soil Loss Equation (USLE) and derived equations (e.g., the Revised Universal Loss Equation - RUSLE and the Modified Universal Soil Loss Equation - MUSLE) measure water quality through the simulation of soil erosion processes and can be used to identify the most important parcels for service provision (Quintero et al., 2009). The reviewed studies and PES schemes employed models such as the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) (e.g., Duarte et al., 2016; Fondo de Agua por la Vida e La Sostenibilidad program – Calvache and Tallis, 2013) and the Soil and Water Assessment Tool (SWAT) (e.g., Proyecto Especial Alto Mayo program - Estrada et al., 2009). The SWAT model estimates soil loss at Hydrological Response Units (HRU), which are spatial units with similar landscape characteristics. Another model is the Economic, Social, and Environmental Evaluation of Land Use (ECOSAUT), which compares future and current scenarios by analyzing the environmental and socioeconomic impacts of land use change (Quintero et al., 2006). ECOSAUT employs SWAT's HRUs and identifies the activities, period, and location in which the environmental benefits and farmers' net income are expected (Quintero et al., 2006). This model can be used to identify “...applications that when implemented, significantly improve environmental quality,” “...applications with relevant management practices suitable to produce expected benefits,” and “...areas where management practices are likely to be accepted and implemented by providers” (Table A.2). If indicators are not available in the desirable spatial scale, expert knowledge can be applied to generate indicator data such as the environmental value of a property, risk of service loss, or relevance of management in a specific area (Hajkowicz et al., 2008). Furthermore, experts can help to select and weight criteria (Crossman et al., 2011) together with the local stakeholders who deliberate the targeting process (Kolinjivadi et al., 2015). The team of experts could include academics from different scientific disciplines and professionals with expertise in environmental management and economic incentives for the conservation of natural resources (Crossman et al., 2011). Targeting criteria and indicators can also be selected through decision criteria

including transparency, low data requirements, flexibility (Wünscher and Engel, 2012), and scale suitability. According to the authors, transparency refers to the clarity of data used in the production of an indicator, whereas low data requirements refer to the quantity, diversity, and complexity of the information necessary to produce an indicator and its availability at the desired scale. Flexibility measures the adaptability of the criterion to the integration of new data or other variables. Finally, scale suitability indicates whether the criterion is suitable for the targeting scale and if available indicators properly represent the environment at that scale. The framework presents a static analysis, so it needs feedback on the provision and demand of environmental services, opportunity costs, climate change, synergies (Wendland et al., 2010), and socioeconomic and political contexts. Targeting must be updated to capture the changes in socio-ecological systems through a continuous collaborative and deliberative process. Criteria and indicators measured by open public data can be reviewed as they are periodically updated. Indicators that do not require high costs for updating, based on historical trends, or on local or traditional knowledge, or obtained in collaboration with research institutions or citizen science projects can also facilitate this process. 6. Conclusions PES schemes to conserve natural ecosystems, the implementation of which has increased over the past years, must be properly designed to achieve goals. A targeting framework for PWS schemes was proposed to address this issue, and it is suitable for targeting publicly funded programs implemented in private areas in highly fragmented landscapes. The framework comprises targeting guidelines, criteria, and indicators. The guidelines, extracted from the scientific literature, cover four stages of the targeting process and can be followed by practitioners in industrialized and developing countries to design PWS programs. A table of criteria and indicators for targeting PWS areas synthesizes the knowledge gathered from PES practice and the scientific literature. Criteria covering environmental benefits, risk of service loss, cost, socioeconomic issues, and readiness are included. The framework is the first targeting approach to integrate the multidimensional aspects permeating PES. It strengthens the connection between science and practice by highlighting the evidence from both areas and incorporating it into the targeting process. Although elaborated for PWS schemes, several guidelines and criteria are relevant to the targeting of other environmental services. We hope that the framework serves as a milestone for future research and contributes to the implementation of more effective PWS schemes to achieve environmental and other goals. Declarations of interest None. Funding This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES – Brazil).

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Haaren and Bathke (2008) Uthes et al. (2010) Kelly and Huo (2013) Alpízar et al. (2015) Stone and Wu (2010) Goldman-Benner et al. (2012)

Crossman et al. (2011) Reed et al. (2014) Alix-Garcia et al. (2008)

Secondary guidelines Consider the planning data produced for the area Set a single or priority goal Consider a combined definition of targeting criteria by scheme managers and landowners Consider the impact of the PWS incentive on the intrinsic conservation motivation of providers Consider the existence of service provision thresholds Contemplate the effect of social diffusion on targeting areas with additionality

2) Measurement of indicators Secondary guidelines Scale of indicators Measurement of environmental services Measurement of deforestation risk

Haaren and Bathke (2008) Gjorup et al. (2016) Gjorup et al. (2016)

Haaren and Bathke (2008), Reed et al. (2014), Cooke and Moon (2015), and Kolinjivadi et al. (2015) Bremer et al. (2014), Higgins et al. (2014), and Schomers et al. (2015) Richards et al. (2015) Romero (2012) Sims et al. (2014)

Secondary guidelines Contemplate regionalized targeting methods Check correlations between indicators Validate the targeting method

4) Planning, implementation, and operation Primary guidelines Undertake collaborative design of the PWS scheme Strengthen partnerships with local intermediaries

Secondary guidelines Assess providers' perceptions before implementing the PWS scheme Promote the PWS scheme in the most relevant areas to achieve scheme goals Conduct adaptive management of the PWS scheme

Define criteria weights

Alix-Garcia et al. (2008), Hajkowicz et al. (2008), Wünscher et al. (2006, 2008), Chen et al. (2010), Gauvin et al. (2010), Stone and Wu (2010), Jack (2013), and Duke et al. (2014) Romero (2012) and Gjorup et al. (2016)

Moore et al. (2013), Bernués et al. (2014), and Reed et al. (2014) Gauvin et al. (2010) and Gjorup et al. (2016) Cimon-Morin et al. (2013) and Kroeger (2013) Stone and Wu (2010), Zhang and Pagiola (2011), Reed et al. (2014), Cooke and Moon (2015), and Duke et al. (2015)

1) Definition of scheme goals, environmental services, and targeting criteria Primary guidelines Consider using valuation methods to identify environmental services Consider scheme goals when selecting targeting criteria Consider service users' spatial demand and distribution Consider the impacts of spatial synergy

3) Criteria aggregation and targeting methods Primary guidelines Employ cost-effective targeting methods

References

Targeting guidelines

Guideline framework for the targeting of PWS schemes.

Table A.1

Appendix A

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Prioritize water drainage and recharge areas and associated riparian buffers and natural cover

Drainage and recharge areas (9p/4 s)

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Prioritize areas where vegetation, soil, and water resources are either conserved or in a better status of conservation

Prioritize areas where vegetation, soil, and water resources are either degraded or in a poorer status of conservation

Conservation condition (17 ps) Conserved areas (7p/3 s)

Degraded areas (6p/1 s)

Prioritize applications that will implement the largest number of management practices or address the largest number of conservation concerns Prioritize enrolled parcels to continue or expand conservation actions in the area Prioritize applications that when implemented, significantly improve environmental quality Prioritize applications that protect the larger area

Continuity of actions (3p) Degree of environmental improvement (3p)

Total protected area (1p/1 s)

Impact of management practices (16 ps) Number of implemented practices (7p)

Prioritize areas highly susceptible to soil erosion

Susceptibility to soil erosion (22 ps) Susceptibility to soil erosion (10p/12 s)

Rarity or distinction (2 s)

Fragility and vulnerability

Reservoir watersheds Population supplied by the source (n° of people) Downstream area supplied by the source (ha) Upstream areas of the watershed Accumulated flow rate (ML/ha/yr) Presence of a water intake system Water demand (L/s) Cloud forests within dam watersheds Proportion of water resources (%) Drainage density (km/km2) Groundwater recharge areas Headwater, river, lake, and reservoir buffers Wetlands

Indicators

(continued on next page)

Number of management practices to be implemented (n°) Number of conservation concerns to be addressed (n°) Enrollment status in the PWS scheme Degree of environmental quality improvement associated with management practices Area to be protected (ha)

Conservation status of riparian vegetation Conservation status of water resources Level of ecological succession of vegetation Absence of invasive species Soils with no visible degradation problems Conservation status of riparian vegetation Conservation status of water resources Presence of soil with visible degradation problems such as desertification and salinization

Slope (% or °) Potential wind or water erodibility Soil erosion rate (t/ha/yr) Proportion of land affected by gully erosion (%)

Prioritize areas near or within protected areas or their buffer zones Presence of protected areas or buffer zones Prioritize applications in priority areas for conservation according to basin plans, zoning, non-government organizations Priority areas for conservation identified by other sources (NGOs), etc. Prioritize areas fragile or vulnerable to natural disasters and climate change impacts (3p) Risk of natural disasters Vulnerability to climate changes Prioritize areas vulnerable to salinization or pollution (3 s) Risk of soil salinity Vulnerability to groundwater pollution Prioritize areas with distinct or rare hydrological or geological features associated with the aquatic habitat Presence of distinct or rare hydrological or geological features

Prioritize areas of sources of water supply or that provide water to downstream sources

Benefits Water resources (41 ps) Water supply (18p/10s)

Priority areas (27 ps) Protected areas (10p) Priority areas for conservation (9p)

Targeting criterion

Theme

Criteria and indicators for the targeting of PWS schemes. ps = number of PES programs or studies that employed the criterion; p = number of PES programs that employed the criterion; s = number of studies that employed the criterion.

Table A.2

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Prioritize applications with relevant management practices suitable to produce expected benefits

Relevance of management (1 s)

Prioritize areas of identified water quantity concerns

Water quantity (4p/1 s)

105 Prioritize parcels that are contiguous or close to others enrolled in the PWS scheme Prioritize areas where vegetation remnants are connected to each other or a protected area Prioritize agricultural areas, followed by silvicultural areas to restore natural cover Prioritize areas at risk of deforestation Prioritize areas susceptible to population pressure or pressure on natural resources

Prioritize areas with decreasing trends in the provision of environmental services Prioritize applications with the highest cost-effective ratio or low costs per area

Spatial synergy (9 ps) Contiguity (4p) Connectivitya (5p)

Restoration areas (1 ps) Restoration areas (1 s)

RISK Deforestation probability (4p/3 s)

Anthropogenic pressure (3p/3 s)

Trends in environmental services provision (1p)

COST Cost of applications (3p/12 s)

Prioritize areas with a lower ratio of natural cover (1p) Prioritize areas with a higher ratio of natural cover (8p)

Prioritize areas of identified water quality concerns

Water quantity and quality (11 ps) Water quality (5p/1 s)

Proportion of natural cover (9 ps) Proportion of natural cover

Prioritize rural properties with sustainable productive alternatives

Sustainable productive alternatives (6p)

Best management practices (12 ps) Best management practices in the property (5p/1 s) Prioritize rural properties that apply best management practices for natural resources

Targeting criterion

Theme

Table A.2 (continued)

Land opportunity cost ($/ha) Participation cost ($/ha) Application cost ($/ha)

(continued on next page)

Risk of deforestation Historical or current deforestation rate Ecosystem level of threat from anthropogenic pressure Historical or potential pressure on natural resources Population density (people/km2) Proximity to access roads (m) Historical flow trend

Land use and land cover

Proximity to other PWS parcels (m) Connectivity index

Proportion of the area with natural cover (%) Proportion of the area with natural cover (%)

Load of sediments, nutrients, pesticides, and pathogens in water Water salinity Flood problems Inefficient use of water Water shortage Overexploited aquifers Availability of water

Existence of conservation practices for natural resources Awards or acknowledgments in environmental matters Presence of firebreaks or other fire control methods Distance between sewage systems and water bodies (m) Location of the animal watering point outside the water body Fences that restrict the access of domesticated animals to natural areas Current forest certification Certified organic farming Agro-ecological farming systems Ecotourism activities Use of biological pest control Non-use of pesticides

Relevance of management practices

Indicators

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Prioritize areas with a high poverty level or low level of social development

Prioritize areas belonging to familiar smallholders Prioritize areas held by women and young landowners or areas with public policies for such groups Prioritize areas held by traditional or indigenous populations or land reform settlers Prioritize areas where providers have never received the PWS incentive Prioritize areas targeted by social inclusion programs Prioritize areas where rural properties and communities have some degree of organization

SOCIOECONOMIC ISSUES Poverty and social development (7p/4 s)

Familiar smallholdings (8p)

Female and young landowners (3p)

Traditional and indigenous populations and land reform settlers (3p)

First applicants (2p) Social inclusion policies (2p)

READINESS Providers' organization (5p)

106 Prioritize areas showing features for the formation of an environmental services market

Prioritize areas where providers recognize the condition of the environmental service and are willing to adopt the management practices financed by the scheme Prioritize areas where management practices are likely to be accepted and implemented by providers Prioritize areas where land tenure or control is secured

Market features (2p)

Providers' awareness (2p)

Social feasibility (2p) Tenure security (2p)

Presence of partner institutions Existence of local institutions Presence of collaborators such as NGOs Existence of government institutions Existence of rural extension programs Existence of Conservation Zoning Environmental projects undertaken by local organizations Presence of other conservation mechanisms Number of service users (n°) Number of service providers (n°) Potential to create a market Link between land use and environmental services provision Providers' awareness of the environmental problem Providers' willingness to change land use practices Providers' willingness to sign and comply with the contract Social feasibility of management practices Land tenure or land control

Presence of organized community groups Existence of agricultural production cooperatives Presence of community-based environmental monitoring Level of compliance with environmental regulatory mechanisms

Net income ($) Household assets ($) Index of Human Development Index of Unsatisfied Basic Needs Risk of Food Security Incidence of hunger Size of the rural property (ha) Proportion of family farms (n° or %) Land held by female landowners (n° or %) Land held by young landowners (n° or %) Beneficiaries of public policies for rural youth (n° or %) Indigenous population (n° or %) Traditional population (n° or %) Land reform settlements (n° or %) Providers who were never enrolled in the PWS scheme Beneficiaries of social inclusion programs (n° or %)

Indicators

The link between landscape connectivity and watershed services lacks theories and evidence (Mitchell et al., 2013; Turner and Gardner, 2015). Consequently, this criterion must be carefully considered in the targeting of schemes restricted to watershed services.

a

Prioritize areas where other conservation mechanisms have been implemented

Pre-existing conservation activities (3p)

Compliance with command-and-control regulation Prioritize areas compliant with any environmental regulations (3p) Intermediaries (3p) Prioritize areas of qualified and motivated intermediaries to implement the PWS scheme

Targeting criterion

Theme

Table A.2 (continued)

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Appendix B. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.forpol.2019.04.002.

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