How countries link REDD+ interventions to drivers in their readiness plans: implications for monitoring systems

In recent years the Reducing emissions from deforestation and forest degradation, conservation of forest carbon stocks, sustainable management of forests and enhancement of carbon stocks (REDD+) scheme has gained increased attention in the policy arena. REDD+ represents a potentially valuable incentive for developing countries to reduce greenhouse gas (GHG) emissions and promote sustainable forest management. Nevertheless, issues related to the implementation of the REDD+ scheme are numerous, including how to enhance its effectiveness in addressing the drivers of deforestation and degradation (Angelsen, 2010). Following the UNFCCC requirements for REDD+ implementation, countries should implement a shift from business as usual through activities in the following areas: (i) reducing emissions from deforestation, (ii) reducing emissions from forest degradation, (iii) conservation of forest carbon stocks, (iv) sustainable management of forests and (v) enhancement of carbon stocks. These activities can be implemented through aggregates of concrete interventions that result in verifiable REDD+ through a three-phased approach (UNFCCC 2011). Most countries are still in the first, preparatory or 'readiness' phase, designing a national strategy aimed at tackling drivers of deforestation and forest degradation (DD) (Korhonen-Kurki et al 2014). The second phase focuses on the implementation of a REDD+ strategy, supported by grants or other financial support for capability building and enabling policies. During the third phase REDD+ activities will be implemented using performance-based compensation (UNFCCC 2010).

Strategizing REDD+ interventions requires consideration of the drivers of deforestation/degradation (SBSTA 2013). Drivers of deforestation/degradation are complex to study because they are related to multiple biophysical, social and economic factors that are interdependent, and which result in dynamic land use patterns (Mohamed 2000). These factors include the multiple and often conflicting interests of different stakeholders, which in turn are influenced by other factors such as existing national policies, regional trade, power dynamics, subsistence forest dependency, resource and technology access, population growth and poverty (Angelsen and Kaimowitz 1999). A distinction can be made between direct and underlying drivers of deforestation and forest degradation (DD) (Geist and Lambin 2002, De Fries 2002). Direct drivers are human activities and actions that directly impact forest cover and result in loss of carbon stocks. Underlying drivers are complex interactions of social, economic, political, cultural and technological processes that affect the direct drivers of DD. They act at multiple scales: international (markets, commodity prices), national (population growth, domestic markets, national policies, governance) and local (subsistence, poverty) (Rudel et al 2009, Boucher et al 2011). Clearly, for effective REDD+ interventions both direct and underlying drivers need to be taken into account.

REDD+ interventions can be divided into direct and enabling activities. Direct interventions are specific, often local activities which result in a direct change in the carbon stock (i.e. reforestation, protected area strategies, agricultural intensification to reduce pressure on forests). Enabling interventions are aimed at facilitating the implementation of direct interventions (i.e. improved law enforcement against illegal logging, and land tenure regulation). Hence direct interventions are more directly linked to direct drivers and are focused on local, context-specific activities. REDD+ strategies that focus solely on direct drivers to demonstrate quantifiable emissions reductions may place less emphasis on addressing the critical underlying drivers. It is crucial that these are also addressed if interventions are to succeed in achieving the emissions reductions (Kissinger et al 2012).

Despite the importance of designing interventions that address specific drivers of DD, there is very little literature available on how different countries are selecting and designing interventions. Questions also remain about how countries prioritize different interventions, given their analysis of what the drivers are. However, some information on this can be found in documents prepared by countries in their readiness phase, such as readiness preparation proposals (R-PPs), and UN-REDD National Programme Documents, as well as documents prepared by research organizations and country partner organizations, such as REDD+ country profiles by the Centre for International Forestry Research (CIFOR). These documents, referred to as 'readiness documents' in this paper, are an interesting source of data to be analysed with a view to assessing how countries are linking drivers and interventions.

We build upon these considerations stating that monitoring systems are needed to assess the effectiveness of interventions in addressing drivers of DD (Romijn et al 2012). Monitoring drivers of DD is needed for several reasons: to understand their importance and processes at work, to attribute emissions to specific causes (i.e. nationally), track their activities over time, to design dedicated mitigation actions that address them, and to assess the impact of these (Herold and Skutsch 2011). Monitoring drivers that lead to DD provides essential information for keeping track of the effectiveness of direct REDD+ interventions. However, current REDD+ monitoring efforts are largely focused to meet international reporting needs and thus are concentrated on the assessment of change in forest area (deforestation) and related carbon emissions, while in only a few cases is the forest area change analysed by linking it to specific driver activities and follow-up land use (GOFC-GOLD 2011, Herold et al 2011). In Mexico for example a deforestation threat map has been developed by correlating past deforestation with social and agricultural data available in secondary sources at the county level (INECC 2012). Nevertheless such analyses rarely incorporate underlying drivers, as they are usually not readily detectable using remote sensing and forest inventory data and would require monitoring capacities beyond these techniques. Moreover, some underlying drivers are not represented in existing databases and their analysis would require more detailed socio-economic data. Others relate to sectoral policies and to conditions in domestic and international markets (Kissinger et al 2012), which are generalized and difficult to connect with specific land cover changes in particular locations.

The above-mentioned three elements (drivers, interventions and monitoring capacities) are interlinked through a logical chain: in order for REDD+ interventions to be effective, they need to be developed with an understanding of specific drivers of DD that they aim to address. Improving monitoring capacities should provide data of progressively better quality and hence increasingly detailed information about drivers, allowing the (re)design of REDD+ policy interventions which are more appropriate to the local conditions and hence more effective. This logic has been described by the Forest Carbon Partnership Facility (FCPF) as follows: 'countries are realizing that the objective of reference level analyses is to better understand and to quantify the relationships among the driver activities of DD, and historical and potential future emissions. The logical chain of: (1) driver analysis, (2) REDD+ strategy development, (3) reference emission levels (REL) exploration, and (4) measurement, report and verification (MRV) design is strongly interlinked. Nevertheless this logical chain has been weak in most RPPs to date' (FCPF 2010). Perhaps one reason for this is that only limited scientific research has focused on these interlinkages. Given the current gap in current knowledge and understanding of the above-mentioned issues, this article focuses on three main objectives: (i) synthesize the direct and enabling REDD+ interventions proposed by each countries, (ii) assess whether the proposed interventions take into account current knowledge of drivers of DD, (iii) reflect on possible implications for future systems to monitor the effectiveness of the proposed interventions (figure 1). The structure of the article reflects these three objectives, as it first presents an analysis of readiness documents and identifies the direct and enabling interventions proposed by different countries.

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This is followed by a second part focussing on the objective to assess to what extent countries explicitly relate interventions considering existing knowledge about DD drivers. In particular, we assessed whether proposed interventions refer to both the relevant direct and underling drivers. Interventions that are proposed to address specific direct drivers of DD have been summarized. The discussion section deals then with possible implications for future monitoring systems, in particular how they could monitor the effectiveness of the proposed interventions. In a concluding section suggestions are made about how to expand monitoring systems beyond the forest sector, through a landscape approach.

Countries participating in REDD+ are being assisted during the readiness phase by two main initiatives: the UN-REDD Programme and the World Bank FCPF. The UN-REDD Programme supports 15 countries, while FCPF assists a total of 36 countries (13 in Africa, 15 in Latin America, and 8 in Asia) following a review of their Readiness Preparation Idea Notes (P-PIN), of which 33 countries have taken the next step by submitting more detailed R-PP (FCPF 2013). A number of bilateral programs including Norway's Government International Climate and Forests Initiative (NICFI) (Ministry of Norwegian Environment 2009) are facilitating the REDD+ readiness process in some countries, such as Indonesia and Brazil. Another source of information used for this paper to add qualitative analysis are country profiles prepared by CIFOR and REDD+ country partners, which followed specific guidelines to analyse contextual conditions that affect the REDD policy environment in each country, and which in particular looked at the politico-economic conditions that drive DD in the respective countries (Brockhaus et al 2012).

The authors reviewed a total of 98 readiness documents of 43 countries: 35REDD+ R-PPs, 15 UN-REDD National Programme Documents and six CIFOR-country profiles (appendix A), available at the websites of World Bank FCPF (http://forestcarbonpartnership.org/), UN-REDD (http://un-redd.org/) and CIFOR (http://cifor.org/) respectively. Six countries (see appendix A) submitted R-PPs to the FCPF as well as documents to the UN-REDD-National Programme. In this study more focus has been given to R-PPs because they contain a more extensive explanation of the proposed interventions, which allowed a more consistent analysis.

Readiness documents have been reviewed to analyse the strategy that each country proposes to address DD based upon their initial knowledge of both direct and underling drivers. The review has been done by identifying and listing all the interventions proposed in all the readiness documents. This list has been used to build intervention categories of enabling and direct interventions.

Readiness documents were evaluated to meet the following objectives:

• 1.  
  Synthesize the direct and enabling REDD+ interventions proposed by each countries
• 2.  
  Assess whether the proposed interventions take into account current knowledge of drivers of DD; in particular:

  • a.  
    Assess whether the proposed interventions refer to both relevant direct and underling drivers
  • b.  
    Summarize the interventions that are proposed to address specific direct drivers of DD
• 3.  
  Reflect on possible implications for future systems to monitor the effectiveness of the proposed interventions.

These objectives expand on the work carried out by Kissinger et al (2012), who made a preliminary analysis of drivers and interventions described by REDD+ countries in 46 Readiness documents.

2.1. Synthesis of the direct and enabling REDD+ interventions

2.2. Assessment of the linkage between intervention and current knowledge of drivers

2.3. Implications for future monitoring systems

3.1. Synthesis of the direct and enabling REDD+ interventions

3.2. Assessment of linkages between interventions and current knowledge of drivers of DD

3.2.1. Interventions proposed referring to direct and underling drivers

The majority of countries (68%) are aware of the importance of designing interventions that are specifically linked to the drivers of DD that they aim to address (figure 2). About 48% of the countries fall into subcategory (i) interventions aimed to address both the direct and underling drivers and 20% belong to subcategory (ii) interventions aimed to address the direct drivers. The minority of countries (32%) propose interventions without referring to the drivers (category interventions without linkage). In this category 12% of the countries belong to subcategory (iii) interventions mainly aimed at increasing carbon stocks and 20% belong to subcategory (iv) no linkage reported. Concerning the linkage between the category of interventions and the quality of national driver data, within category Interventions with linkage, about half of countries of subcategory (i) have good-quality driver data (Ratio scale). A different trend is shown in subcategory (ii) to which belong countries which propose interventions that refer to specific direct drivers, and where the majority have low data quality (Nominal scale). Although the pattern is not very clear, there is tendency that countries with better quality driver data also do a better job in aiming to link both drivers, direct and underlying, with interventions. There are also a number of countries that have low quality driver data but are still able to link the interventions to drivers. This raises the question whether the proposed interventions based on lower quality data will be targeting the highest priority drivers. It can be expected that these countries will build monitoring capacities to gain better understanding on drivers if this is properly considered and integrated in their REDD+ readiness program. There are also countries that have good quality driver data but it seems these were not used when designing their interventions. In this case countries should be encouraged to better use their available data for their REDD+ intervention planning.

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3.2.2. Direct interventions proposed to address specific direct drivers

Out of the ten countries that have provided information on linking direct drivers and interventions, agricultural intensification is the most common intervention proposed to address agriculture as a driver, followed by agroforestry and improvement of livestock management (table 4). Improving charcoal efficiency use has been proposed by 30% of countries to address unsustainable production of biomass energy and firewood harvesting, followed by sustainable management of forests/woodlands for biomass harvesting (30%) and increasing biomass/trees on farmland (20%). Interventions to address timber harvesting are mentioned by a minority of countries, while the most common interventions to address unsustainable/illegal logging are forest plantations and sustainable forest management.

Table 4.  List of main drivers and direct interventions described in readiness documents and percentage of countries proposing each intervention. The driver 'agriculture' includes livestock management activities.

Main driver	Specific intervention
Agriculture	Agricultural intensification	50%
	Agroforestry	40%
	Improvement of livestock management	40%
	Sustainable forest management	30%
	More efficient land use	20%
Unsustainable production of biomass energy +	Improve charcoal efficiency use	50%
	Sustainable management of forests/woodlands for biomass harvesting	30%
	Alternative renewable energy sources (wind, solar, biogas)	30%
	Increase biomass/trees on farmland	20%
Firewood harvesting	Expansion of electrification network	10%
	Community-based use of biofuels for lighting and cooking thus reducing demand for fuel-wood	10%
	Plantation establishment of fast growing fuel wood	10%
	Agroforestry	10%
Timber harvesting	Forest management planning (zone and protect timber production that meets demand and restock for future)	10%
	Increase timber stocks in natural forests	10%
Unsustainable/illegal logging	Forest plantations to avoid deforestation of primary forests	30%
	Sustainable forest management	30%
	Strengthen urban planning and zoning	20%
	Afforestation/reforestation	10%
Urban development	Minimizing conversion of forests during construction	10%
Mining	Sustainable mining	20%
	Protected areas and buffer zones	10%
Forest fires	Fire management and control plan	20%

3.2.3. Comparison of types of interventions proposed by countries in different groups

As figure 3 shows, interventions proposed by countries of Group 1 (described in paragraph 2.2) are mentioned by a different percentage than the interventions proposed by countries in Group 2. In particular the majority of interventions proposed by Group 1 tend to be related to the non-forest sector (livestock/rangeland management, agricultural intensification), while the majority of countries in Group 2 propose mainly forest-related interventions (sustainable management of forest, protected areas strategies, afforestation/reforestation). This result is not surprising since Group 1 countries take into account the drivers while developing interventions. Since most drivers of DD originate outside the forest sector (Hosonuma et al 2012, Kissinger et al 2012), it stands to reason that these interventions will focus on non-forest sector strategies. Countries that don't consider their drivers, might not have this insight, and focus more on forest sector interventions. It should be noted however that neither group provides much evidence in their documentation about track record of these different strategies in their countries, and whether they are in reality likely to be effective.

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4.1. Implications for future REDD+ monitoring

This study provides a comprehensive overview of the current strategies for addressing drivers of DD as presented by 43 REDD+ countries in 98 readiness documents. The analysis allowed for a deeper understanding of implications for monitoring systems. We build our assessment upon a logical interaction between identified (and reported) drivers of DD, proposed REDD+ interventions and systems to monitor the effectiveness of interventions. In order for REDD+ interventions to be effective they should be directly linked with the drivers of DD that they aim to address. The effectiveness of interventions in addressing drivers should be monitored systematically. Improving monitoring capacities provides data of progressively better quality and hence increasingly detailed information about drivers, allowing to (re)design REDD policy interventions, so that they will be more suited to the local conditions and hence more effective.

We explored the elements of this logical chain in three steps. Firstly we synthesized information on the direct and enabling interventions proposed by countries wishing to participate in REDD+; secondly we assessed to what extent countries propose interventions by taking into account what they know (and report) about drivers of DD; thirdly we considered the implications for future monitoring of the effectiveness of interventions.

Results show that the interventions proposed by many countries focus less on activities to reduce deforestation, but rather on those that should result in reducing forest degradation and enhancing forest carbon stocks. These results indicate a need for a deeper understanding of why countries tend to focus in their proposals on tackling forest degradation instead of deforestation, and the possible implications for effectiveness of proposed interventions if further evidence on drivers of DD indeed suggest a mismatch. The currently proposed measures do have already strong implication for monitoring systems. While monitoring deforestation greatly relies on remote sensing time series, monitoring other forest-related activities relies more on ground level approaches, such as interviews with local experts, who can provide information about the location of activities such as fuel-wood use, forest degradation and tree planting. These monitoring approaches will be much more focused on assessing smaller-scale impacts, which generally tend to be more costly.

In addition, most of the driver-specific interventions proposed address drivers not only inside but also outside the forest sector. However current monitoring efforts are focused on monitoring carbon dynamics within forest stands to meet national and international reporting requirements. These findings suggest that REDD+ monitoring should be extended by looking at effectiveness of REDD+ activities also outside the forest sector, including agriculture and other land use changes. This is important for two main reasons. Firstly it helps to capture interactive effects: where for instance agriculture is driving forest loss and where management (such as agroforestry) is driving carbon sequestration. Secondly it addresses confusion over boundaries—where one land use begins and another ends, what is forest and what is not. This is important because shifts in boundaries can result in large shifts in carbon accounting over time or across countries.

Nevertheless developing capacities to extend monitoring systems beyond the forest sector implies the use of additional resources for monitoring, which already accounts for a large part of countries' REDD+ readiness activities (Romijn et al 2012). Hence REDD+ countries should carefully evaluate how to employ their resources in such a way that is cost-effective. One way in which this could perhaps be done is by involving local communities in monitoring, which is also vital to increase the quality and quantity of data and at the same time might empower local communities and generates local employment opportunities (Danielsen et al 2011).

Concerning enabling interventions, a large number have been described, of which the most common are stakeholder involvement, tenure and rights regularization and policy and governance reform. Proposed enabling interventions remain rather vague and explicit linkages to existing or planned policies and national development programmes that are potentially driving deforestation are rarely made. Moreover, for enabling interventions to be effective, they need to be bundled. For instance agricultural intensification should be combined with zoning, protected areas or rehabilitation of degraded lands to prevent further forest clearing. Only few of the readiness-documents reviewed explicitly mention the importance of implementing interventions in a combined way, and countries may need to give more attention to this.