4 research outputs found
Biodiversity of the cocoa agroforests of the Bengamisa-Yangambi Forest Landscape in the Democratic Republic of the Congo (DRC)
Cocoa agroforestry has evolved into an accepted natural resource conservation strategy in the tropics. It is regularly proposed as one of the main uses for REDD+ projects (Reducing Emissions from Deforestation and forest Degradation and the role of conservation, sustainable management of forests, and enhancement of forest carbon stocks in developing countries) in the Democratic Republic of the Congo. However, few studies have characterized the cocoa agroforestry systems in this country. Hence, this research proposes to determine the impact of distance from Kisangani (the unique city in the landscape) and land-use intensity on the floristic composition of cocoa agroforests in Bengamisa-Yangambi forest landscape in the Congo Basin. The results revealed that species diversity and density of plants associated with cocoa are influenced by the distance from Kisangani (the main city in the landscape and province). Farmers maintain/introduce trees that play one or more of several roles. They may host caterpillars, provide food, medicine, or timber, or deliver other functions such as providing shade to the cocoa tree. Farmers maintain plants with edible products (mainly oil palms) in their agroforests more than other plants. Thus, these agroforests play key roles in conserving the floristic diversity of degraded areas. As cocoa agroforestry has greater potential for production, biodiversity conservation, and environmental protection, it should be used to slow down or even stop deforestation and forest degradation
Preliminary reflections of the potential of climate smart agriculture (CSA) in the Tshopo Province (DRC)
Building a framework towards climate-smart agriculture in the Yangambi landscape, Democratic Republic of Congo (DRC)
This paper aims to produce a framework for climate-smart agriculture (CSA) in the Yangambi landscape, Democratic Republic of the Congo (DRC). This would enable the authors to identify agricultural practices, assess vulnerability to climate change, identify options for improving agricultural systems from a climate change mitigation and adaptation perspective and finally provide climate-smart agricultural options. The study used household survey methods of data collection. The data were collected using a structured questionnaire survey by interviewing 250 farm households, subdivided using three axes of the Yangambi landscape. Fisher’s exact test was used to determine relationships between two or more variables. Results of the survey revealed that the vast majority (98%) of respondents perceived changes in temperature, rainfall and weather patterns. Reduction of crop yields and the emergence of new weed species and new crop pests are the main impacts on agricultural activities. Although 87.6% of respondents have no means of adaptation and resilience, some of them use crops rotation, fallow practice, fertilizers and bio-pesticides. A framework for CSA is proposed for the Yangambi landscape. Policies and strategies to promote CSA in the study area should take into account local farmers' perceptions of climate change and consider first the adequacy of CSA practices for the specific conditions of the target area before its promotion. This study is thus useful for many REDD+ initiatives that are currently being promoted in DRC and particularly in the Tshopo Province. This study is one of the first studies to focus on CSA in the Yangambi landscape, DRC. It assists the use of agriculture as a response to reducing deforestation while at the same time lowering agriculture’s carbon footprint and promoting a resilient and more productive farming system
Preliminary estimation of above-ground carbon storage in cocoa agroforests of Bengamisa-Yangambi forest landscape (Democratic Republic of Congo)
In the perspective of using cocoa as a response to climate change, a preliminary carbon stock assessment was conducted in cocoa agroforests of the Bengamisa-Yangambi forest landscape in the north-east of Democratic Republic of Congo (DRC). Data were collected in 25 plots of 2500 m2 each, spread over 16 villages. Above-ground carbon stock assessment on cocoa trees and their associated plants revealed that cocoa agroforests store on average 44.48 Mg ha−1 of above-ground carbon of which, cocoa-associated plants represent 83.68%. The diversity (species richness) of cocoa associated plants determine the level of above-ground carbon stored in cocoa agroforests. Trees less than 50 cm in diameter stored a larger amount of above-ground carbon. Cocoa agroforests with associated plants dominated by forest species (Model F) store 1.76 and 1.72 times more carbon, respectively, than those where associated plants are dominated by oil palm (Model P) and a mixture of plant types (forest species mixed with oil palm plants, or Model FP). Associated plants inside cocoa agroforests also play additional roles to support livelihoods such as health care, household consumption and timber. Therefore, beyond carbon storage, cocoa agroforest is an important reservoir of some local species and thus useful for biodiversity conservation and local livelihoods. As cocoa agroforests in DRC are recognized as one of the main responses to climate change, this study constitutes an early contribution to the process of reducing emissions from deforestation and forest degradation (REDD +) in forest landscapes in this country of the Congo Basin