At a glance :
- A recent study examined 98 readiness documents produced by 43 REDD+ countries to assess if proposed interventions refer to the drivers of deforestation and degradation that they aim to address and how the effectiveness of in tackling drivers could be monitored.
- Most direct interventions aim to reduce forest degradation, rather than deforestation
- Proposed interventions rarely make explicit linkages to drivers of deforestation and forest degradation.
- Systems should be set up to monitor the effectiveness of policy interventions; these systems should move beyond detecting deforestation (remote sensing analysis of satellite images) and include other land uses such as agriculture and infrastructure development.
In Brazil, it’s cattle ranching. In Indonesia it’s palm oil. In Mozambique it’s cross border trade. Diverse are the activities that largely drive deforestation and forest degradation in some of the world’s most forested countries. So too are the policy interventions that countries have started implementing in recent years to address these activities.
Which interventions are countries proposing? How do they refer to the drivers of deforestation and forest degradation, if at all? And how do we monitor that they are effective? We explored these questions in a study published recently in Environmental Research Letters.
Efforts to combat deforestation and forest degradation have been largely driven by international pressure to reduce greenhouse gas emissions. One of the more well-known internationally-led efforts has been the REDD+ scheme, which provides financial incentives for developing countries to promote sustainable forest management and thus reduce greenhouse gases.
Most countries are still in the preparatory phase of REDD+, where they need to submit what’s called a “Readiness Preparation Proposal (R-PP)”. This proposal, which helps countries design a national strategy to tackle drivers of deforestation and forest degradation, outlines the nature of external support required, partners and organizations involved with REDD+ and an assessment of the social and environmental impacts, and potential additional benefits, of REDD+ in the country.
Our study examined 98 readiness documents from 43 countries implementing REDD+. We first assessed if the interventions proposed in the readiness documents referred to the drivers that they aim to address. Then we reflected about how the effectiveness of such proposed interventions in tackling drivers could be monitored.
Interventions, drivers and monitoring capacities are interlinked through a logical chain: for REDD+ interventions to be effective, they need to consider the specific drivers of deforestation and degradation that they aim to address. These interventions should be monitored in order to assess if they are effective in their aim.
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. Nevertheless this logical chain has been weak in most R-PPs to date.
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, our analysis aimed at 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 deforestation and degradation, iii) reflect on possible implications for future systems to monitor the effectiveness of the proposed interventions.
REDD+ rarely makes linkages to policies driving deforestation
REDD+ interventions can be divided into direct interventions and enabling activities.
Direct interventions are specific, often local activities that result in a direct change in the carbon stock. The most common direct interventions we found are sustainable forest management (proposed by 62% of countries), followed by fuel wood efficiency (47%) and agroforestry (44%).
These direct interventions focus more on activities to reduce forest degradation rather than reducing deforestation. Designing interventions to address forest degradation is important because even if forest degradation has a relatively low carbon impact per unit area, it can have large cumulative effects over vast areas and hence cause large GHG emissions.
If we look now at enabling interventions, which try to facilitate the implementation of direct interventions, the most frequently proposed were improving governance (83%), policies (51%), stakeholder involvement (46%) and tenure and rights (43%).
But even if these interventions are necessary to enable the direct interventions, our results show that explicit linkages are rarely made to existing or planned policies and national development programmes that are potentially driving deforestation.
For instance, we found that proposed enabling interventions have little concrete proposals to remove perverse incentives that drive deforestation such as ranching in Brazil, palm oil development in Indonesia, and tackle large scale drivers such as timber extraction through concessions in Cameroon, cross border trade in Mozambique, or supply and demand gaps in industrial timber processing in Vietnam.
These findings have strong implications for monitoring systems.
Forest monitoring systems cannot readily detect drivers
Monitoring systems are needed for several reasons: to attribute emissions to specific causes, track their activities over time, to design dedicated mitigation actions that address them, and to assess the impact of these.
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. In only a few cases is the forest area change analyzed by linking it to specific driver activities and follow-up land use. 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.
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.
While monitoring deforestation can be detected with remote sensing because vegetation cuts can be clearly detectable on the satellite image, forest degradation activities are less easily seen on the image because they occur under the canopy cover, and hence hidden.
Due to this, different approaches are needed to obtain forest degradation activity data. For instance, household surveys and interviews with local experts can provide information about the specific location of activities that result in changes in stocks within the forest. These surveys are also providing information about why local people make decisions and how these decisions could be steered by interventions to reduce forest degradation. This information is crucial to redesign interventions that consider local drivers of deforestation and degradation.
Improving monitoring capacities is important. As mentioned earlier, it will provide 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.
Monitoring systems should expand to assess REDD+ effectiveness outside the forest sector
Our results show that most of the driver-specific interventions are associated with driver activities that relate not only to the forest sector (logging, firewood and timber harvesting, forest fires) but also to a large extent to the non-forest sector (agriculture, urban development and mining).
Current efforts are focused on monitoring carbon dynamics within forest stands to meet national and international reporting requirements. While this is essential for REDD+ monitoring, reporting and verification, we suggest that countries extend monitoring systems beyond the forest sector, to monitor the effectiveness of policy interventions in addressing drivers of deforestation and forest degradation, such as agriculture and other land use changes. This would allow tracking of activities and feedback to policy makers to improve their policies and make them more appropriate to the local conditions and hence more effective.
We also need systems to facilitate coordination of policies from different sectors so that efforts in lowering drivers of deforestation are in harmony with other goals such as infrastructure development, food production and development.
In practice, tools are needed to ensure that multiple and often contrasting objectives in land use are coordinated as a whole, with a landscape perspective rather than a sectorial one.
This begs the question: Will landscape monitoring be the next challenge for REDD+?
Giulia Salvini is a PhD candidate at Wageningen University. Her PhD focuses on the effectiveness of REDD+ policies in addressing drivers of deforestation and forest degradation at the national and local scale. She holds a Masters in Natural Resources Management from the University of Bologna (Italy) and she has been working as a researcher in Italy and the Netherlands in the field of forest management in developing countries (Tanzania, Ethiopia and Vietnam). Her current research interests focus on how stakeholder involvement through participatory approaches can help selecting landscape strategies in REDD+ that merge land-based climate mitigation with adaptive agriculture.