1. Introduction
Payments for Environmental Services (PES), defined as voluntary transactions between service users and service providers upon mutually agreed natural resource management rules [
1], are widely applied as policy instruments for forest conservation [
2,
3]. PES are assumed to be favorable for mitigating climate change, reducing emissions from deforestation and forest degradation, providing incentives for forest conservation, and enhancing the provision of environmental services [
4,
5,
6]. Within the context of unsustainable forest use, their goal is to induce additional incentives for forest conservation [
7,
8]. Although theoretically sound, their environmental and social outcomes have been scrutinized [
9,
10], thus accentuating the need to better understand the different settings in which PES are embedded [
11,
12]. Two particular concerns arise when assessing their effectiveness. The first is a possible lack of additionality: even without any financial incentive, program participants might exhibit the targeted behavior [
13,
14,
15]. Put simply, they would leave their forest intact even without any payments. The second is leakage: individuals might move their deforesting and forest degradation activities to other areas not covered by PES [
16,
17,
18,
19]. Several empirical studies have analyzed these concerns and found evidence for their practical relevance. In some cases, additionality from self-enrolled low-pressure areas turned out to be negligible [
20,
21,
22,
23]. Empirical evidence exists also on leakage effects (i.e., displaced deforestation) within a PES context [
24,
25,
26].
There exists, therefore, a debate regarding PES effectiveness [
27,
28,
29]. Theoretical considerations [
30] indicate that direct payments could be more cost efficient than indirect approaches, thus suggesting that PES instruments could be effective in reducing deforestation [
31]; adverse self-selection and moral hazard, however, could weaken their effectiveness. Adverse self-selection arises when service providers volunteer their lowest-value forests which might be under the least threat at the same time, implying that less-threatened forested areas could receive payments for conservation while the most threatened areas receive nothing. Moral hazard arises when service providers take unobservable actions—since contract compliance is costly to monitor—that could help them evade the performance of their obligations [
32]. Additionally, some PES instruments do not intendedly provide for a continued flow of data collection and are not designed with the intention of evaluating their effectiveness [
29]. Ultimately, the effectiveness of PES instruments in avoiding deforestation remains an empirical issue [
29,
33]. Existing literature presents mixed evidence as to the extent to which implementing a PES instrument could achieve its intended goals [
9,
10]. Likewise, evidence-based studies that attest to the effectiveness of a PES instrument are also sparse and often very context specific [
23,
34,
35].
In Ecuador, forest cover declined from about 15 million ha in 1990 to approximately 13 million ha by 2016 [
36,
37,
38]. Forests in Ecuador face two major threats: (1) the complete conversion of forested areas to different land uses, usually for agricultural purposes (i.e., deforestation); and (2) a reduction in the capacity of forests to deliver environmental services mainly due to human-induced activities, such as selective logging (i.e., forest degradation) [
39,
40]. As a policy measure to address such threats, the Ecuadorian government designed and implemented in 2008 a PES program called Socio Bosque (SBP) [
41], which has continued in operation since its beginning. It was introduced in 2008, prioritizing specifically targeted forested areas [
42] with the dual objective of forest conservation and poverty alleviation following three main criteria: (1) reducing the deforestation threat, (2) supporting environmental services, and (3) abating poverty. Socio Bosque provides differentiated financial incentives to private individuals and indigenous communities in exchange for mutually agreed forest conservation practices [
20]. Regarding the implementation of SBP, there exists suggestive positive evidence on the reduction in deforestation [
20,
21,
23,
43,
44]. The estimates presented there indicate that implementing SBP in locations across Ecuador achieved its primary goal of reducing deforestation rates in SBP-enrolled areas. The mentioned studies are, however, mainly based upon statistical correlations, leaving aside historical deforestation trends and the non-intended effects of SBP on leakage in adjacent areas. We therefore identified a research gap deserving further scrutiny; this is understanding the leakage effects of SBP implementation on adjacent areas [
45,
46].
We examine the presence of additionality and leakage by focusing on community-owned SBP-enrolled forests and other areas without SBP enrollment for comparison. The latter are adjacent areas, including a sequence of buffer zones around each SBP area, and additionally, comparable reference sites located farther away. We use historical deforestation data from 1990 to 2018 to analyze average annual net deforestation trends within the considered areas. Departing from this information, we question whether the deforestation trends within SBP areas and their adjacent areas would have been the same as those without the presence of SBP, and whether such trends change after the implementation of SBP. In addition, we address the self-selection issue mentioned above by assessing, for a broadened period of time, areas purposely placed under conservation by their communities. We hypothesize that areas under SBP have lower deforestation rates than their adjacent areas after SBP implementation. We provide findings from an evaluation design using t-tests, effect size, and ANOVA analysis that present evidence for additionality in SBP areas, but also for leakage in adjacent areas.
Our study is structured around two intertwined research questions: (1) Has the implementation of SBP caused additional deforestation reduction (compared to the time period before the implementation, and to comparable nonadjacent reference sites)? (2) Has the implementation of SBP induced leakage into their adjacent areas? As a side question, we ask whether the selection process for SBP areas might have been influenced by self-selection, i.e., whether SBP areas might have been located in areas with lower deforestation pressure compared to adjacent areas. In the following sections, we detail the methodology employed for data gathering and choice of empirical approach. We subsequently present our results with respect to the additionality of SBP and leakage effects in our study sites in the Ecuadorian Amazonia. We then discuss our findings in reference to PES design, their applicability for actual policymaking, and methodological challenges for the analysis of additionality and leakage resulting from PES implementation.
4. Discussion
To test the effectiveness of SBP implementation in four Ecuadorian sample sites under the claim of additionality and avoided leakage, we tracked changes in annual net deforestation rates in SBP areas and non-SBP areas, both adjacent to and far away from the study sites; altogether, the analyzed time period was 28 years. The results reveal that the average difference in annual net deforestation rates for SBP areas before and after SBP implementation is marginally low (about 0.02 percent points); however, the overall net deforestation rates in these areas are considerably lower than the nonadjacent reference sites without SBP. Distance to SBP areas is decisive for deforestation intensity, which was shown by a statistically significant linear increasing trend of deforestation departing from SBP areas. Additionally, under the simplifying assumption that effect size estimates accurately represent changes in net deforestation rates, we argue that such changes could be attributed to the implementation of SBP. In analyzing the historical net deforestation trend in SBP and non-SBP areas, it appears as if SBP was mainly introduced in regions where net deforestation was low and stable anyway, while it rose in comparable reference sites and adjacent areas. Currently existing data limitations and methodological challenges for the assessment of additionality and leakage offer, however, scope for interpretation.
4.1. Methodological Issues
We obtained very high estimates of Cohen’s d in the comparison of the tiles located in Chontapunta and Ahuano (Cohen’s d = 7.93) and in SBP vs. non-SBP areas in Ávila (Cohen’s d = 7.93). Although Cohen [
67] and Sawilowsky [
68] provide a rule of thumb when analyzing estimates for effect sizes ranging from very small (0.01) to huge (2.0), Slavin and Smith [
69] indicate that large effect sizes may result from small sample sizes and Börner, Schulz, Wunder, and Pfaff [
60] state that differences in dynamic context factors may also reflect variations in estimates. We therefore ask the reader to use caution in interpreting effect size estimates as a clear indication of self-selection, additionality, and leakage but rather as a signal of the differences in outcomes and the practical consequences of SBP implementation [
59]. Additionally, results obtained from ANOVA and
t-tests indicate a discrepancy in statistical significance;
t-tests returned significant differences whereas ANOVA results did not. A plausible reason is that
t-tests are not additive whereas ANOVA analysis sums up means to find differences among groups [
70]. We argue that there may exist a difference in means when assessed as a group, but due to a high level of noise coming from unaccounted-for contextual factors, such a difference is undetectable in our data. Hence, our individual findings suggest statistical differences, although they do not show it as a group. Such discrepancy indicates that contextual factors and the individual analysis of historical net deforestation trends in SBP areas and comparable reference sites could capture the differences in outcomes when assessing self-selection, additionality, and leakage.
4.2. Additionality and Self-Selection
Additionality of SBP implementation manifests in additionally avoided deforestation in the SBP areas, compared to the counterfactual case. In the absence of true counterfactuals (what would have happened in the absence of SBP in this site?), we made comparisons to diverse reference sites: buffer zones around SBP areas, non-SBP subareas within landscape sections (tiles) that are part of the beforementioned buffer zones, and tiles under comparable conditions far away from the SBP tiles. For all those, deforestation development in time periods before and after the SBP implementation was observed. While the overall effect of deforestation reduction in the SBP areas is marginally low (about 0.02 percent points), deforestation in the considered areas without SBP was higher over the whole time period of 28 years.
In assessing changes in annual net deforestation rates between time periods, we observed the difference before and after SBP implementation. An alternative view involves scrutinizing the changes in the number of hectares in forest areas. Over a period of 28 years, comparable reference sites (tiles) lost on average 25.69% of their forest areas (Chontapunta 29%, Carlos Julio Arosemena Tola 20%, San José de Dahuano 45%, and Arajuno 9%) in comparison with 0.83% of forest area loss in SBP tiles (Ahuano 0.20%, Rukullacta 0.26%, Ávila 0.41%, and Canelos 2.96%). Despite having a relatively low percentage change in deforestation rates, there is indeed some change in terms of forest area. In each case, however, SBP-enrolled areas had a smaller loss of forested areas when compared against several references.
Notable, however, is the fact that the annual net deforestation rates in SBP areas were distinctly lower already before SBP implementation, which questions the presence of deforestation risk in these sites and therefore the additionally effect. The literature indicates that PES’ impact on the abatement of deforestation is low [
29]. For the case of Ecuador, our finding of low changes in annual net deforestation avoidance in SBP areas is similar to other empirical work [
20,
21,
22,
23,
71] using different methodologies (e.g., randomized control trials, score matching). The low annual net deforestation rates in enrolled SBP areas need not be interpreted as SBP being ineffective but rather as possibly exposing a landowner´s decision to assign an area of land into a profitable activity (i.e., conservation under a PES instrument) [
72]. From this perspective, landowners might already have been aware of the profitability of conserving forested areas before the existence of SBP, and this awareness prompted them to “secure” these areas by joining SBP once this program was available. Under these circumstances, it seems reasonable to assume that the financial incentives provided by SBP reinforced their desired investment behavior. The pattern of low deforestation in SBP areas and intensified land use in adjacent areas was already present long before SBP was designed or implemented in our study sites. In short, such behavior would have been maintained even in the absence of payments [
9,
13,
25]. It is likely that those proactively secured areas are of lower suitability for other land uses, thus causing comparatively low opportunity costs of forest conservation. The deforestation risk attributed to those areas might therefore be rated as low. Such behavior reveals asymmetric information and flawed spatial targeting that exacerbates the degree of non-compliance and spatial spillovers [
32]. It becomes unclear, however, whether SBP implementation is the main factor of influence for avoiding deforestation, absent an initial deforestation risk.
Furthermore, joining SBP implies self-enforcement, since failure to comply with agreed management rules translates into penalties [
73]. Additionally, an issue connected to self-enforcement is the number of hectares under conservation agreement for which monetary incentives are provided (an overview of the levels of monetary incentives received by individuals and communities is detailed by [
20]). We argue, therefore, that abiding by contract rules prompts communities to maintain compliance at a minimum, receive financial benefits, and maintain a more intense land use in adjacent areas. All in all, this reduces additionality [
45].
4.3. Leakage
We observe a change in deforestation rates in SBP areas and adjacent buffer zones after SBP implementation. A comparison of deforestation rates across time periods revealed consistency in deforestation patterns. In the ten km buffer zone around SBP areas, the average net deforestation rate decreased to a higher degree (−0.42%) than in the SBP areas themselves (−0.02%) (see
Figure 3 and cf. [
49]); an evident decrease in deforestation after SBP implementation over time. Since this change in net deforestation rates for SBP areas between periods is marginally small, it makes it troublesome to attribute the aforementioned change in deforestation behavior to the implementation of SBP. Our finding of higher deforestation rates in buffer zones is, however, similar to the empirical work of Ford et al. [
74], conducted in tropical and subtropical regions of America, Africa, and Asia, in which deforestation rates were higher in 10 km buffer zones than in protected and control areas, thus undermining forest conservation efforts.
We detect that forest cover changes (decreases and increases in net deforestation rates) in SBP areas happen in the same direction as in the surrounding areas. For example, Ahuano had the highest deforestation rates in its buffer zones after SBP implementation, which increased over time. In the same direction, Ahuano showed a slight increase in deforestation within the SBP area as well. All other SBP areas showed a decrease in deforestation rates after SBP implementation. This decrease was also observable in the surrounding buffer zones, which maintained, however, a high rate of deforestation. Only in the buffer zones of Rukullacta did reforestation occur after SBP implementation, up to the 7 km buffer zone.
Our results are similar to those reported by Arturo Sánchez-Azofeifa et al. [
75] in a study on Costa Rica’s national parks and biological reserves, and buffer zones around them; their results indicate that as distance increases from protected areas (in this case national parks and biological reserves), total deforestation and deforestation rates also increase. There exists, however, the possibility that leakage effects on nearby parcels could be positive or absent, possibly due to differences in pressure, as emphasized by Nolte et al. [
76] in a study conducted in the USA on 26 years of protection and land-cover change.
Areas enrolled for conservation are surrounded by areas which are modified for purposes different from conservation, and, hence, it is plausible that landowners manage them differently [
77]. However, since we do not have information on the contextual factors in SBP areas and their buffer zones, we may not have captured the true determinants of leakage. Ideally, in-depth information on the characteristics of SBP areas and their buffer zones is needed to identify landowners´ decision making, since this is associated with spatial patterns of deforestation influenced by their specific socio-economic characteristics [
78,
79].
An overall reduction in deforestation rates occurred over SBP areas and buffer zones, which can be interpreted as a positive spillover effect. However, there was an evident distance-related increase in deforestation across the buffer zones. We argue that this type of behavior may have existed even before SBP was implemented. Such land-use patterns enabling self-selection occurred also before the implementation of a protected area in Peru [
80]. In Ecuador, within the context of SBP, this effect takes place when communities separate an area with low deforestation risk and low opportunity costs and assign it for conservation, thus shifting their land-use decisions onto adjacent areas belonging to these communities [
45]. However, after the implementation of SBP, the deforestation rates in the buffer zones were lower than before SBP. On average, the reduction in the annual net deforestation rate along all buffers was around −55% after SBP implementation (when compared with the deforestation rate before SBP). These findings stress the need to extend the analysis of SBP performance to their surrounding areas, since any effect of SBP implementation in enrolled areas may extend beyond their boundaries and must be assessed so as to reflect the net effect of conservation efforts [
46,
81].
4.4. Implications for PES Design
The results presented in this study reveal that net deforestation rates remained low even in the absence of SBP, and that the sustained deforestation pattern in adjacent areas remained a problem, as is the case for many other conservation programs in different contexts [
26,
82,
83]. Identifying the impact on the abatement of deforestation is therefore only partial as long as the focus remains on the enrolled areas only. Therefore, to address such challenges in PES design, before accepting an area for enrollment, selection criteria should address not only the potentially enrolled areas but also their surroundings [
84,
85].
We also present evidence showing that at a time in which SBP had not yet been designed or implemented, there were already changes in the SBP areas and their buffer zones. Changes in deforestation therefore may not originate from the implementation of SBP alone, but due to some other unaccounted-for reasons. Our findings suggest the need to disentangle monetary payments, area size, and historical deforestation behavior from other program characteristics and to consider a potential deforestation risk. Additionally, the variety of characteristics of the study sites and their buffer zones demands the development of framework analysis that considers broader social and ecological features [
55].
4.5. Limitations of Our Study
A challenge when assessing the influence of SBP on additionality and leakage is the observability of improvements through time; a convenient approximation is that change occurs linearly [
86]. We cannot, therefore, rule out the possibility of unobserved factors unaccounted for in our study influencing our findings. Additionally, to the best of our knowledge, based on governmental documentation, SBP is not directly linked to the delivery of a particular environmental service, but rather states a mutually agreed set of land-use restrictions aimed at conserving forests under risk of deforestation, thus delivering desired environmental services. Hence, our study does not consider how or how much the provided financial incentive influences particular attributes (e.g., delivery of environmental services), nor whether the change in behavior, as a plausible result of the implementation of the program, is in fact helping achieve the intended goal of SBP. Additionally, deforestation rates in Ecuador and in our study sites have shown fluctuations during the time period of analysis, thus complicating the detection of impacts attributable only to SBP but possibly reflecting the overall success of national and local governmental efforts to reduce deforestation in the Ecuadorian Amazonia. Notwithstanding these arguments, our study contributes important aspects for scrutinizing landowners’ decision making, and how these decisions contribute to additionality and leakage in SBP and adjacent areas.