3.1. Municipal (Meso) Scale Analyses
The DID regression model (Table 2
) employed to test REDD+ effectiveness at the municipal scale did not show a significant effect of REDD+ project interventions in reducing forest cover loss after 2010 (DID = Time × REDD interaction term, p
= 0.219). Before REDD+ implementation (2000–2009), mean annual rate of forest cover loss was 0.82 (SD = 0.45) in non-intervened municipalities and 0.73 (SD = 0.40) in REDD+ intervened municipalities. After REDD+ implementation (2010–2018), mean annual forest cover loss decreased to 0.48 (SD = 0.37) in non-intervened and 0.46 (SD = 0.27) in REDD+ intervened municipalities. Change in forest cover rates before and after REDD+ interventions are also similar in non-intervened (mean = −0.34, SD = 0.39) and intervened (mean = −0.27, SD = 0.31) municipalities. The overall DID model of forest cover loss in municipalities was significant (F
= 10.64, df = 228, p
< 0.0001) and explained half of the variance in forest cover loss (R2
= 0.54). Significant covariates associated with forest cover loss included fire density (FireDens, p
< 0.0001), population density (PopDens, p
< 0.0008), percent agricultural area (AgrPer, p
= 0.003), out-of-state population residing after 2005 (OutState05, p
< 0.03), and population-urbanization index (UrbPopClass, p
Difference-in-differences between REDD+ and non-REDD+ municipalities was also evaluated using a set of 42 matched control municipalities selected by PSM (Figure 2
). The matched control units were compared to 42 treated units (REDD+ intervened municipalities) applying Mann–Whitney U test. Change in forest cover rates in non-intervened municipalities (mean = −0.28, SD = 0.36) and intervened (mean = −0.27, SD = 0.32, Figure 3
) municipalities before and after REDD+ funded projects were very similar and not significantly different (U
= 824.5, p
= 0.61). Both DID and PSM results show an overall tendency that REDD+ municipalities have similar forest cover loss trends as non-intervened municipalities, indicating no effect of project interventions in affecting forest cover loss rates at the regional level.
The SCM analyses provided an additional nonparametric test of REDD+ effectiveness in single treated units (municipalities), providing more detailed results that allow for the detection of patterns and trends associated with decreasing forest cover loss, or no reduction and increasing rates of forest cover loss. Table 3
summarizes SCM outputs for all REDD+ municipalities (mapped in Figure 4
) indicating a range of mixed effectiveness in reducing forest cover loss. REDD+ intervention showed no effect in reducing forest cover loss (i.e., no change or increase in deforestation rate) after 2010 in half (20) of the 39 intervened municipalities. Of these municipalities, 14 are in Yucatan state, which contains 83% of all municipalities and are much smaller than in Campeche or Quintana Roo. Notable municipalities in the state of Yucatan showing an absence of REDD+ impacts include Celestun, Chacsinkin, Hunucma, Izamal, Merida, Oxkutzcab, Tekax, and Tizimin. Tizimin is a highly deforested municipality with cattle production land uses, and Merida seats the capital which is a major growing urban center of the Yucatan Peninsula. Municipalities of Tekax, Chacsinkin, and Oxkutzcab in the south are in a deforestation hotspot with expanding commercial agriculture identified as a REDD+ priority region, the Jibio Puuc Biocultural Reserve. Four municipalities in Campeche state (Calakmul, Campeche, Carmen, and Hopelchen) and two in Quintana Roo (Othon P. Blanco and Jose María Morelos) had no effect from REDD+ interventions in reducing rates of forest cover loss. Carmen is a municipality with widespread deforestation for cattle production, while Hopelchen and Campeche are cases of expanding commercial mechanized agriculture. A net forest cover loss and REDD+ ineffectiveness in Calakmul is concerning due to protected area presence and greater investment in REDD+ interventions in the municipality. In Quintana Roo, Othon P. Blanco has been deforested for cattle and sugarcane production while commercial agriculture has expanded in José María Morelos, deterring REDD+ effectiveness. A pattern is observed of municipalities that lack reduced forest cover loss and REDD+ effectiveness located in the southern Yucatan Peninsula region and border zone with Belize and Guatemala.
On the other hand, potential REDD+ effectiveness was found in the remaining half of REDD+ -intervened municipalities, these included 13 in Yucatan, 3 in Campeche, and 3 in Quintana Roo. In Campeche, municipalities with historic deforestation for agricultural and cattle production, such as Calkini, Escarcega, and Champoton, indicated reduced tree cover loss associated with REDD+ interventions when compared to their synthetic matches. The latter two municipalities have an important role in the state´s forestry sector. In Quintana Roo, municipalities that show REDD+ effectiveness, Felipe Carrillo Puerto, Lazaro Cardenas, and Tulum, are important to maintaining carbon reserves in the landscape. Felipe Carrillo Puerto has low deforestation rates with extensive forest management and subsistence agriculture land uses, while Tulum also has low deforestation and predominant land uses of subsistence agriculture and some forestry. The municipality of Lazaro Cárdenas has had greater deforestation for cattle raising but is also near the major urban and tourism hub of Cancun. Municipalities with REDD+ effectiveness in the state of Yucatan included cases such as Cantamayec, Tekal de Venegas, Tzucacab, Uman, and Yaxcaba. Among REDD+ effective municipalities in Yucatan state were large forested areas in the central and eastern region and surrounding the urban municipality of Merida.
indicates that more funders or projects intervening in a municipality do not necessarily result in REDD+ effectiveness. Municipalities receiving the most attention by all three major REDD+ funders (AMREDD, CONAFOR, and UNDP) and with greater number of projects (363) did not show improvements in reducing their rates of deforestation. These include important municipalities for forest conservation: Calakmul and Champoton in Campeche, José María Morelos and Othon P. Blanco in Quintana Roo, and Tekax in Yucatan. Greater REDD+ effectiveness was found among municipalities where AMREDD and CONAFOR or UNDP projects were both present, and the least effectiveness was found where the smallest number of projects were present. Nevertheless, there does not appear to be any clear or strong positive trend in the level of project effort and REDD+ effectiveness. Major land use cover and productive activities present in municipalities are apparently more associated with REDD+ effectiveness at the meso scale as noted above. Figure 5
shows the average REDD+ effect on forest cover loss rates among municipalities categorized according to their dominant productive land uses. These results show that REDD+ interventions in municipalities where subsistence agriculture and forestry are major land uses tend to be effective in reducing deforestation. Also, interventions in municipalities with cattle, commercial agriculture, and forestry land uses combined performed well. However, in municipalities where commercial agriculture dominates (with the presence of mechanized farming), deforestation was not reduced. Even when forestry production is present, these municipalities failed to show a reduction in the rates of forest cover loss from REDD+ interventions. In municipalities where cattle production dominates, there was on average a small reduction in the rate of forest cover loss, representing municipalities such as Lazaro Cardenas in Quintana Roo and Dzilam de Bravo in Yucatan. Yet, half of these cattle ranching municipalities did not show REDD+ effectiveness in reducing forest cover loss.
3.2. Community (Micro) Scale Analyses
Community or ejido-scale DID regression results were similar to the municipal-scale results, showing no significant effect of the interaction term (DID = Time × REDD, p
= 0.738). The overall regression model, while significant (p
= 0.0001), had a poor fit (R2
= 0.02). Significant covariates associated with forest cover loss were the ejido area parceled as private land (PrivParc, p
= 0.0005) and the area under agricultural or cattle production (CatpastPer, p
= 0.0001). The variability in proportion of forest loss rates (0–8%) among community sample units was large compared to municipal sample units. Mean annual rates of forest cover change before REDD+ interventions were 4.16 (SD = 22.1) in non-intervened ejidos and 1.95 (SD = 3.67) in REDD+ intervened ejidos. After REDD+ implementation, mean annual forest cover loss rates were reduced to 2.91 (SD = 14.67) in non-intervened ejidos and to 1.45 (SD = 2.68) in REDD+ intervened communities. Mean changes in annual forest cover rate after REDD+ intervention were −1.23 (SD = 11.07) in non-intervened ejidos and −0.50 (SD = 1.60) in ejidos with REDD+ projects. Matched control units (non REDD+ communities) derived from PSM results reduced variability and had a much closer mean rate of forest cover change (−0.61, SD = 2.0) to that of REDD+ intervened communities (−0.45, SD = 1.45) (Figure 6
). The difference was not strongly significant (U
= 11399.5, p
= 0.09) but significant to the α = 0.10 level (Figure 7
). Although, forest cover loss decreased in REDD+ -intervened ejidos, the reduction was less than in control ejidos, showing overall REDD+ ineffectiveness in community territories on the Yucatan Peninsula.
However, as in the meso-scale analysis, SCM outputs show mixed results when assessing REDD+ effectiveness at the community scale. Figure 4
maps the location of REDD+ -intervened communities based on effectiveness in reducing deforestation. In the state of Campeche, from a total of 37 ejidos with REDD+ -related projects (Table A1
, Appendix A
), half (19) did not have a reduction in forest loss rate from REDD+ intervention and the other half (18) demonstrated REDD+ effectiveness (Figure 8
). Similarly, in Yucatan state, 33 communities (48%) indicated REDD+ effectiveness in reducing deforestation while 36 communities (52%) did not (Figure 8
, Table A2
). Quintana Roo had a greater proportion of REDD+ effective communities, 31 or 63%, compared to 18 or 37% that had constant or increased deforestation rates (Figure 8
and Table A3
). Like the meso-scale SCM results, a clearer pattern is seen of communities that lacked REDD+ effectiveness in reducing deforestation clustered in southern municipalities of the Yucatan Peninsula bordering Belize and Guatemala. Table 5
shows the average effect on the rate of forest cover loss among communities grouped according to funders and number of projects. As observed at the municipal scale, the level of effort related to funders and number of projects fails to show any pattern related to REDD+ effectiveness. Contrary to meso-scale results, the nine communities that showed the greatest average reduction in rates of forest cover loss (−0.44) had projects (70) with all three major funders. For the most part, these were community forest ejidos located in the central municipality of Felipe Carrillo Puerto in Quintana Roo (Figure 4
). A group of nine communities with a total of 40 projects funded by both CONAFOR and UNDP had the highest gain in forest cover loss and included large forestry ejidos in southern Quintana Roo, for example, Laguna Om, Caoba, and Tres Garantias. The level of effort in the latter two communities had been significant due to their Forest Stewardship Council (FSC) certification for sustainable forest management.
SCM community scale results show a more straightforward trend than the meso-scale evaluation on the role dominant land uses or production activities have on REDD+ outcomes (Figure 9
). REDD+ effectiveness in reducing forest cover loss rates was most successful among communities where forestry and commercial or subsistence agriculture land uses are shared. Moreover, communities where subsistence agriculture or both commercial and subsistence agriculture are present were also effective in reducing the rate of forest loss. Contrarily, communities that failed to reduce deforestation and had the highest increase in deforestation were associated with regions where cattle ranching dominates or where cattle ranching, commercial agriculture, and forestry are combined. In general, where land use for cattle is present, REDD+ interventions tend to be ineffective; communities where commercial agriculture dominates also showed increased deforestation.
shows most of the REDD+ project communities in the state of Campeche without a reduction in forest cover loss located in the southern municipalities of Calakmul, Carmen, and Escarcega where cattle ranching is prominent. Fewer were located towards the central region of the state, Champoton, Hopelchen, and Calkini, where greater forest production and subsistence agriculture exist. Positive results for REDD+ communities in the municipality of Hopelchen are encouraging, being a deforestation hotspot. In addition, important forestry ejidos of Campeche state, for example, Nuevo Becal and Miguel Colorado in Calakmul and Champoton had positive REDD+ outcomes. Successes in the municipality of Calakmul are also meaningful to REDD+ goals. REDD+ effective cases in major commercial agriculture and cattle ranching regions of Campeche should be explored in detail to identify key institutional, governance, or socioeconomic factors that lead to REDD+ effectiveness.
Likewise, in Quintana Roo, REDD+ effectiveness is concentrated in communities of the central municipalities of Felipe Carrillo Puerto and Jose Maria Morelos where forest production is shared with subsistence or commercial agriculture. Felipe Carrillo Puerto is recognized for its low deforestation rate. On the other hand, communities in the southern municipality of Othon P. Blanco where cattle ranching, commercial agriculture, and forestry activities are present had an increase in deforestation. Contrary to the municipalities of Felipe Carrillo Puerto and José Maria Morelos, important forest management ejidos in the municipality of Othon P. Blanco, such as Botes, Caobas, Guadalajara, and Tres Garantías, were among communities that did not show reduced forest cover loss from REDD+ intervention. In these ejidos, cattle ranchings and sugarcane production are also common land uses. Other community cases showing increased forest loss in Quintana Roo included tourism-related communities in the municipality of Tulum (Chancen Chico and Hodzonot) and Lazaro Cardenas (Holbox).
In the state of Yucatan, ejidos that increased their deforestation despite REDD+ intervention were mostly located in the southern municipality of Tekax where commercial agriculture is shared with forestry activities and in the northern cattle ranching municipality of Tizimin. However, REDD+ effectiveness is noted in ejidos in eastern (Tzucacab, Tixcalpupul and Yaxcaba) and northern (Merida, Chocholá, and Tekal de Venegas) municipalities, many of these showing high deforestation rates before REDD+ intervention. Ejidos involved in forest management are few in the state of Yucatan, and most REDD+ effective ejidos are dependent on small-scale commercial maize production and subsistence agriculture with larger areas under forest cover compared to other communities.
Our results showed no overall effect of REDD+ interventions after 2010, deterring deforestation on the Yucatan Peninsula, concurring with a subnational assessment [7
], trends documented in other countries [10
], and a range of other forest conservation interventions across the globe [79
]. At the municipal scale (meso-scale), the DID regression model signaled population density, agricultural immigration, fire, and urbanization as major determinants of forest cover loss, potentially overwhelming REDD+ interventions. At the community scale (micro-scale), DID regression indicated that land privatization and the area under cattle and agricultural production were associated with higher rates of forest loss, demonstrating local barriers to REDD+ effectiveness. This general trend in REDD+ effectiveness across the Yucatan Peninsula was strongly confirmed through our PSM analyses that revealed similar values in forest cover loss rates among control and REDD+ -intervened municipalities and communities before and after intervention, having no significant differences when statistically compared.
The generalized negative outcome of REDD+ interventions in municipalities and communities stresses the importance of improving subnational jurisdictional efforts and strategies to halt forest cover loss by strengthening state and municipal governments. Stickler et al. [7
] also found that the three states of Campeche, Quintana Roo, and Yucatan failed to make any significant progress towards achieving their committed targets of reducing deforestation by 80% by 2020, accorded through their signing of the Rio Branco Declaration; the authors claim that lack of authority and limitations in subnational jurisdictions (state and municipal) and a centralized federal policy and approach towards REDD+ implementation are chiefly responsible. Bos et al. [10
] hypothesized other potential reasons behind REDD+´s apparent lack of effectiveness in 23 subnational initiatives in Brazil, Peru, Cameroon, Tanzania, Indonesia, and Vietnam. Possible causes included flaws in the design of interventions and problems with assessment methods. In Mexico, the main design flaw identified in REDD+ interventions is not targeting important forest loss drivers (e.g., commercial agricultural and cattle land uses) while focusing on low deforestation land uses such as forest management and traditional agricultural practices [10
]. The limitations in analysis methods pertain to differences in REDD+ projects and implementation periods and an emphasis on measuring deforestation outcomes without considering degradation, carbon storage, or accumulation. This study also has similar limitations in forest cover data and criteria used in the analyses that may influence generalized results of REDD+ ineffectiveness. For example, the time that the intervention begins in a community was not considered in our study. REDD+ in Mexico is only now phasing out of their preparation and piloting phases, so any effectiveness may be still too soon to detect.
Nevertheless, SCM applied in this research provided an additional tool that indicated REDD+ interventions had mixed effects on deforestation among intervened municipalities and ejido communities of the Yucatan Peninsula. Moreover, SCM proved to be a much more valuable means to evaluate REDD+ effectiveness, allowing for more useful assessments of individual cases of intervened municipalities or communities. We find that intervened municipalities with cattle and commercial agriculture (e.g., sugarcane, maize, and soy) land uses were typically unsuccessful in reducing forest cover loss. SCM results show that this trend is even stronger at the community scale. Ejidos where land use includes cattle rearing tend to increase their rates of forest loss the most, even when forestry is present. Communities where the dominant land use is mechanized farming also increase their loss of forest cover. In addition to land use, a pattern in the location of intervened municipalities and communities with a lack of REDD+ effectiveness was observed. REDD+ -intervened communities that substantially increased forest loss were concentrated in the southern peninsular region. This border zone with Guatemala and Belize is a remote forested frontier region where significant deforestation has occurred in the last 10 years due to the expansion of cattle pasture and agriculture, specifically in the municipalities of Carmen, Candelaria, Calakmul, and Othon P. Blanco [35
]. The area is also known for illicit activities of logging, drug smuggling, migration, and contraband which can interfere with the implementation of programs and projects. In neighboring Guatemalan forests, Devine et al. [80
] describe how narcotrafficking is linked to cattle production and deforestation. There is little reason to doubt that this process may be occurring within Mexican forests near the border.
In addition, through SCM analyses, we were able to determine that the level of effort of REDD+ projects or funders working in a municipality or community had no bearing on effectiveness in reducing forest cover loss, leaving effectiveness closely tied to productive activities and location. For example, more funding and projects focused on the Calakmul Biosphere Reserve did not result in REDD+ effectiveness. However, some municipalities and communities in deforestation hotspots had improved outcomes from REDD+ interventions, including forest management, agricultural, and capacity-building projects. For example, despite the presence of suitable soils for mechanized agriculture in central municipalities of Hopelchen in Campeche and José María Morelos in Quintana Roo, a group of REDD+ -intervened ejidos reduced their forest cover loss. Among them were communities with forest management or agricultural communities with AMREDD projects aimed at strengthening governance and capacity-building. UNDP community-based small grant projects, particularly in agricultural areas of Yucatan state, also tended to reflect positive REDD+ outcomes. Other studies have also indicated that, when REDD+ is evaluated at the regional or meso scales the effectiveness in reducing deforestation is often not observed; on the other hand, effectiveness at local or micro scales is demonstrated in cases [10
]. In that respect, our study also confirms the importance of evaluating REDD+ effectiveness at the local scale or project levels, using counterfactuals and quasi-experimental methods such as BACI and SCM [6
]. Moreover, our results also corroborate that local funding and community-based projects may be more effective in reducing deforestation than regional jurisdictional interventions with government institutions [15
With some caveats, our results echo the Skutsch and Turnhout [41
] analysis which considers that REDD+ is not effective at tackling the most important drivers of deforestation and forest degradation. In the region, REDD+ is more often effective in locales with already low deforestation rates, particularly in those with community forest management and subsistence agriculture, where much of the REDD+ effort has concentrated [18
]. Conversely, our results suggest that REDD+ is more often ineffective in communities with significant presence of industrial agriculture and cattle ranching where opportunity costs may be higher and low emissions development initiatives compete with business-as-usual incentives [44
], illegal activities [80
], and disproportionately larger agricultural subsidies [18
]. Among the first lessons from initial REDD+ activities was the need to consider cross-sectoral transformation to change the course of drivers of deforestation and degradation [81
]. Our study confirms that this challenge is still relevant in Mexico, especially the long-recognized need for better coordination between forest and agricultural policy. Some authors claim that REDD+ should be coupled with specific agricultural interventions (e.g., deforestation-free supply chain) [82
Although important forestry communities with competing agricultural and cattle lands uses (e.g., Tres Garantias, Caobas, and Botes) showed no effects of REDD+ reducing deforestation. These ejidos were also located in the southern border zone region known to be affected by internal conflicts and illegal activities. However, our results show cases of forestry communities where commercial agriculture is present and REDD+ interventions were effective in reducing deforestation. We hypothesize that strengthening community governance and organizational capacity results in REDD+ effectiveness. However, the observed successes in communities certainly merit closer examination and further research for REDD+ planning and strategies. As Duchelle et al. [83
] points out: “REDD+ on the ground is a customized basket of integrated interventions, including information, institutions, and incentives. Unsurprisingly, its effects are thus highly diverse.”
Mixed effectiveness of REDD+ has been described in other evaluations, also showing reduced forest loss in communities with forestry and subsistence livelihoods and increased deforestation with cattle and commercial agriculture land uses [6
]. Our study suggests that additional factors, such as land tenure, local governance and organization, and financial credit and subsidies may also be driving heterogeneity among ejidos and suggest that future analysis include more details that can allow for a more nuanced and situated interpretation. Secure land tenure is often touted as the single most important factor for the success of conservation and development interventions such as REDD+ [85
]. Land tenure rights in Mexican ejidos are relatively secure, and illegal land uses are limited compared to other regions of Latin America [86
]. Our results highlight the insufficiency in secure land rights for ensuring REDD+ effectiveness. However, our results do show an important role of the type of land tenure in deforestation. At the micro-scale, forest cover loss is higher in privatized ejido lands. Notably, in community forestry ejidos, land tend tenure and resource use decisions tend to be collective, whereas for agriculture, individual land management and decisions prevail [87
]. In that respect, community governance and organizational strength may also play a significant role in determining REDD+ effectiveness. This research shows cases of well-organized community forestry ejidos certified by Forest Steward Council for sustainable management (e.g., Nuevo Becal, Noh Bec, and Petcacab) with REDD+ effectiveness. Ramón Corona in Campeche state is among the few communities that have collectively implemented and participated in pilot silvopastoral and conservation agriculture projects, demonstrating REDD+ success in a high deforestation municipality [89
]. The potential association between local REDD+ participation and legitimacy with the effectiveness of interventions [18
] merit detailed exploration beyond individual case studies. REDD+ is being conceptually contested [91
], and the governance processes associated with it are intensively scrutinized and sometimes challenged [3
]. As the mixed effectiveness of REDD+ continues to be documented, the need to reexamine both the reaches and the blind spots of the current model of global sustainable forest governance become increasingly apparent [94
Beyond how correct the theory of change is assumed by individual REDD+ projects in a specific locale [3
], the opportunity costs associated with reducing deforestation and forest degradation can be expected to vary widely across sites, influencing intervention outcomes. Within the complex suite of factors that may explain the limited efficacy of REDD+ lies a relative meager funding [79
]. International funding in Mexico has been very limited and decreasing compared with other countries like Brazil and Indonesia, where higher REDD+ effectiveness has been reported [7
]. Moreover, coordinating interests is a major challenge for REDD+ as conflicting subsidies and policies pervade across REDD+ countries [3
]. As occurs elsewhere [79
], REDD+ projects often are a form of continuation of previously existing conservation and development initiatives, government programs, and governance platforms, now branded under the REDD+ umbrella (e.g., CONAFOR implementation of REDD+), while other REDD+ projects do represent an actual innovation for the region (e.g., AMREDD). Moreover, as various government-funded programs that historically supported CFM are defunded or cancelled, REDD+ has become a key element in community forestry policy. As pointed out by Pirard et al. [95
], these compounded interventions over time often make the effects of individual initiatives “difficult to disentangle”.