Several countries in the Congo Basin are aware of the importance of forest potential and have embarked on the REDD+ process. Consequently, they are making institutional arrangements in sectors that are drivers of deforestation (e.g., agriculture, land tenure, land use, energy, forestry, governance) and are developing a national framework to harmonize and facilitate REDD+ implementation. But while the countries of the Congo Basin are all keen to reduce emissions related to deforestation, their levels of commitment differ. Indeed, while some are sidestepping the REDD+ process, others are considered “good students” of the process and are thus involved in all the initiatives (Sufo Kankeu 2019).
Tag: deforestation
Using high-resolution imagery and deep learning to classify land-use following deforestation: a case study in Ethiopia
National-scale assessments of post-deforestation land-use are crucial for decreasing deforestation and forest degradation-related emissions. In this research, we assess the potential of different satellite data modalities (single-date, multi-date, multi-resolution, and an ensemble of multi-sensor images) for classifying land-use following deforestation in Ethiopia using the U-Net deep neural network architecture enhanced with attention. We performed the analysis on satellite image data retrieved across Ethiopia from freely available Landsat-8, Sentinel-2 and Planet-NICFI satellite data. The experiments aimed at an analysis of (a) single-date images from individual sensors to account for the differences in spatial resolution between image sensors in detecting land-uses, (b) ensembles of multiple images from different sensors (Planet-NICFI/Sentinel-2/Landsat-8) with different spatial resolutions, (c) the use of multi-date data to account for the contribution of temporal information in detecting land-uses, and, finally, (d) the identification of regional differences in terms of land-use following deforestation in Ethiopia. We hypothesize that choosing the right satellite imagery (sensor) type is crucial for the task. Based on a comprehensive visually interpreted reference dataset of 11 types of post-deforestation land-uses, we find that either detailed spatial patterns (single-date Planet-NICFI) or detailed temporal patterns (multi-date Sentinel-2, Landsat-8) are required for identifying land-use following deforestation, while medium-resolution single-date imagery is not sufficient to achieve high classification accuracy. We also find that adding soft-attention to the standard U-Net improved the classification accuracy, especially for small-scale land-uses. The models and products presented in this work can be used as a powerful data resource for governmental and forest monitoring agencies to design and monitor deforestation mitigation measures and data-driven land-use policy.
Assessing the Potential for Private Sector Engagement in Integrated Landscape Approaches: Insights from Value-Chain Analyses in Southern Zambia
Agricultural and forested landscapes in Africa are changing rapidly in response to socio-economic and environmental pressures. Integrated landscape approaches provide an opportunity for a more holistic and coordinated resource management strategy through the engagement of multiple stakeholders. Despite their influence as landscape actors, participation of private businesses in such initiatives has thus far been limited. This study focuses on the Kalomo District in southern Zambia, which provides an example of a rural landscape characterized by high levels of poverty, low agricultural productivity, and widespread deforestation and forest degradation. The study applied a value-chain analysis approach to better understand how the production of four locally important commodities (maize, tobacco, cattle, and charcoal) impacts land use, local livelihoods, and environmental objectives in this landscape, focusing on the role and influence of private sector actors. Data were collected through focus group discussions and key informant semi-structured interviews. Qualitative content analysis was employed to analyze the data and contextualize the findings. Results indicate three key potential entry points for increased private sector engagement: (1) improving water security for smallholders; (2) empowering small and medium-sized enterprises (SMEs) as private sector actors; and (3) collective planning for sustainable landscape activities with deliberate measures to involve private sector actors. We discuss options for optimizing benefits from the identified entry points.
Central African countries’ international commitments on climate change
Article 4 of the United Nations Framework Convention on Climate Change (UNFCCC) sets out the main commitments of the Parties, “taking into account their common but differentiated responsibilities and their specific national and regional development priorities, objectives and circumstances”. As Central African countries work to revise their Nationally Determined Contributions (NDCs) under the Paris Agreement and strengthen their efforts to meet their international climate change commitments, it is important that we take stock of the current situation.
Addressing imported deforestation and zero deforestation commitments
Over a quarter of deforestation (27 percent) is caused by land use change attributed to the production of commodities (Curtis et al. 2018). Estimates of tropical forest lost attributed to expanding cropland, pastures and forest plantations range from between 62 to 80 percent (Pendrill et al. 2019, Hosonuma et al. 2012) with 26 percent of tropical forest loss attributed to the international demand for commodities (Pendrill et al. 2019). Deforestation has thus been seen as a worldwide responsibility, since products linked to deforestation in a specific location are sold and consumed worldwide. It has been estimated that 10 percent of deforestation is linked to the consumption of unsustainably sourced commodities within member countries of the EU, caused by imported commodities since deforestation within Europe is negligible (Cuypers et al. 2013). This phenomenon results in what is currently known as forest-risk commodities and commodity-driven deforestation. Commodities associated with imported deforestation produced in Central Africa are palm oil, cocoa, coffee, natural rubber, timber and cotton.
Oil palm and rubber-driven deforestation in Indonesia and Malaysia (2000-2021) and efforts toward zero deforestation commitments
This study evaluates the oil palm and rubber-driven deforestation in Indonesia and Malaysia between 2000–2021 through secondary data analysis from a rich data set by collecting and integrating secondary data from multiple sources. Results show a significant tree cover loss, including 82% and 250% of primary forest loss in Indonesia and Malaysia. Oil palm harvested area increased by 650% in Indonesia and 50% in Malaysia, while palm oil production rose by 566% in Indonesia and 65% in Malaysia over the same period. The study also find that rubber-harvested areas increased by 54% in Indonesia but decreased by 20% in Malaysia, with rubber production increasing by 108% in Indonesia but decreasing by 49% in Malaysia. Over the past two decades, Indonesia’s palm oil export volume has risen by 619%, while Malaysia’s has increased by 83%. Indonesia’s natural rubber export volume also increased by 69%, but Malaysia’s decreased by 33%. The study reveals that the impact of oil palm and rubber on deforestation varies by region and period. However, plantation expansion and associated forest conversion have slowed, which can be associated with the consumer demand for no deforestation oil palm and rubber products. Many of the world’s largest traders and producers have pledged zero deforestation commitments, guaranteeing the elimination of deforestation from their supply chains in Indonesia and Malaysia. Such commitments can only be accomplished through government, private sector, farmers, and community collaboration. Finally, to ensure sustainability in these sectors, comprehensive policies and practical solutions that support farmers’ livelihoods are also crucial.
Ensuring Zero Agricultural Land Expansion into High-Carbon Ecosystems
Relative to agricultural systems, high-carbon ecosystems – such as forests, peatlands, and mangroves – store large amounts of carbon in relatively small areas. Agricultural expansion often comes at the expense of high-carbon ecosystems, contributing to climate change. The food system is connected to these challenges. Ensuring no further agricultural expansion occurs in high-carbon ecosystems is a substantial climate change mitigation opportunity. The estimated costs of avoiding deforestation range from US$1.1 to US$395 billion per year, depending on growth scenarios and carbon prices; this is a bargain compared to the leverage these systems have on climate change and its social costs. Individuals, indigenous people, policies, institutions, and investments are all agents of change and will have to work together to avoid further land conversion.
Effectiveness of the Yangambi Biosphere Reserve in Reducing Deforestation in the Democratic Republic of the Congo
Establishing protected areas creates an opportunity to reduce deforestation. This study aims to inform the Congolese government’s efforts to promote forest and biodiversity conservation by assessing the effectiveness of the Yangambi Biosphere Reserve (YBR) in reducing deforestation. Group and individual interviews designed to understand the causes of pressure on forest cover in the Yangambi landscape complemented satellite imagery analyses. The results indicate that deforestation inside the YBR is not significantly different from outside the YBR. They demonstrate the lack of impact of the YBR in reducing deforestation. The dependence of communities on forest resources would have led to an explosion of bare and fallow land replacing forest areas. A sufficient budget allocation for conservation coupled with capacity building of managers to implement integrated conservation projects could offer alternative livelihoods at the community level, reduce pressure on natural resources from local development and ensure biodiversity conservation in and around the YBR.
Archetype analysis of forest policies and measures: towards a new typology
Decision makers have access to a large and growing toolbox of policies and measures that can, in theory, contribute to reducing deforestation and forest degradation. Middle-range theories can be formulated to summarize the conditions under which forest policies and measures are effective in halting deforestation and forest degradation. Such a diagnostics approach can, in turn, provide useful information to help decision makers avoid the trap of one-size-fits-all policy solutions and implement well-informed, context-specific policy solutions. A key element in this approach is the construction of a typology of forest policies and measures. Here we develop and apply an archetype analysis of forest policy and measures as a systematic, bottom-up and replicable way to build such a typology. Our empirical approach is based on three key elements: a broad universe of cases of forest policies and measures, a generic theory of change (ToC) of forest policies and measures, and a list of attributes characterizing this theory of change. Overall, we identify and characterize 10 broad types of forest policies. On the hand, these encompass historical solutions aimed at changing producers’ behaviours such as command-and-control policies and economic incentives. On the other, they encompass emerging demand-side policies and policies triggering psychological mechanisms such as social belongingness.
Declining Amazon biomass due to deforestation and subsequent degradation losses exceeding gains
In the Amazon, deforestation and climate change lead to increased vulnerability to forest degradation, threatening its existing carbon stocks and its capacity as a carbon sink. We use satellite L-Band Vegetation Optical Depth (L-VOD) data that provide an integrated (top-down) estimate of biomass carbon to track changes over 2011–2019. Because the spatial resolution of L-VOD is coarse (0.25°), it allows limited attribution of the observed changes. We therefore combined high-resolution annual maps of forest cover and disturbances with biomass maps to model carbon losses (bottom-up) from deforestation and degradation, and gains from regrowing secondary forests. We show an increase of deforestation and associated degradation losses since 2012 which greatly outweigh secondary forest gains. Degradation accounted for 40% of gross losses. After an increase in 2011, old-growth forests show a net loss of above-ground carbon between 2012 and 2019. The sum of component carbon fluxes in our model is consistent with the total biomass change from L-VOD of 1.3 Pg C over 2012-2019. Across nine Amazon countries, we found that while Brazil contains the majority of biomass stocks (64%), its losses from disturbances were disproportionately high (79% of gross losses). Our multi-source analysis provides a pessimistic assessment of the Amazon carbon balance and highlights the urgent need to stop the recent rise of deforestation and degradation, particularly in the Brazilian Amazon.