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

Cartographie de la dynamique de l’occupation du sol dans la concession de l’INERA-Yangambi en République Démocratique du Congo

The DR Congo has vast tracts of forest that contribute to the well-being of the local population and to climate regulation. However, for several decades now, these forests have been subject to strong anthropic pressure, resulting in deforestation and the fragmentation of these forest ecosystems. The Yangambi region, one of the richest forest regions in DR Congo, is also suffering from the same situations related to deforestation and habitat fragmentation. This is why the aim of this study is to carry out a cartographic and quantitative analysis by remote sensing of the dynamics of land use in the INERA-Yangambi concession. The classification by object with the supervised approach of Landsat images allowed to characterize the land cover in three dates (1990, 2010 and 2018). For study purposes, six land cover classes were selected according to the realities on the ground: built/bare ground, agricultural complex, wasteland, plantations, secondary forest and primary forest. The analysis of landscape dynamics and fragmentation was carried out by means of transition matrices and certain indices of the spatial structure of the landscape. The results showed that there was a change in land use over a period of 28 years. We also found that forest formations (primary forest and secondary forest) have experienced a significant regression in favour of anthropogenic classes (built/bare ground and agricultural complex), with an annual deforestation rate from 1990-2010, 2010-2018 and 1990 and 2018 estimated at 0.29%, 0.96% and 0.89% respectively. It should also be noted that there has been a progressive fragmentation of forests (primary and secondary) evidenced by the continuous increase in the number of patches, the decrease in the density of patch perimeters and the impressive decrease in their average area. Also, the average distance between two neighbouring patches has increased, indicating an increased isolation of patches. These results suggest the need for a management plan for the sustainable management of the concession and its natural resources.  Key words: Landscape dynamics, land use, deforestation, landscape fragmentation, remote sensing, spatial structure, INERA-YangambiLa RD Congo dispose des vastes étendues forestières qui contribuent au bien-être des populations riveraines et à la régulation du climat. Mais, il y a plusieurs décennies que ces forêts sont soumises à une forte pression anthropique avec comme conséquences la déforestation et la fragmentation de ces écosystèmes forestiers. La région de Yangambi, une des plus riches des régions forestières en RD Congo subit aussi les mêmes situations liées à la déforestation et à la fragmentation d’habitat. C’est pourquoi le but de cette étude est de faire une analyse cartographique et quantitative par télédétection de la dynamique de l’occupation du sol dans la concession de l’INERA-Yangambi. La classification par objet avec l’approche supervisée des images Landsat a permis de caractériser l’occupation du sol en trois dates (1990, 2010 et 2018). Pour des raisons d’étude, six classes d’occupation du sol ont été retenues en fonction des réalités sur terrain : le bâti/sol nu, le complexe agricole, les friches, les plantations, la forêt secondaire et la forêt primaire. L’analyse de la dynamique du paysage et de la fragmentation s’est faite par le biais des matrices de transitions, et de certains indices de la structure spatiale du paysage. Les résultats obtenus ont montré qu’il y a eu un changement dans l’occupation du sol en l’espace de 28 ans. Nous avions aussi constaté que les formations forestières (forêt primaire et forêt secondaire) ont connu une régression significative au profit des classes anthropiques (bâti/sol nu et complexe agricole), avec un taux de déforestation annuel de 1990-2010, de 2010-2018 et de 1990 et 2018 estimé à 0,29 %, 0,96 % et 0,89 % respectivement. Il faut noter aussi qu’il y a eu fragmentation progressive des forêts (primaires et secondaire) mis en évidence par l’augmentation continuelle du nombre des taches, la diminution de la densité des périmètres des taches et la diminution impressionnante de leur aire moyenne. Aussi, la distance moyenne entre deux taches voisines a augmenté indiquant ainsi un isolement accru des taches. Ces résultats suggèrent la nécessité de la mise en place d’un plan d’aménagement en vue de la gestion durable de la concession et des ressources naturelles qui s’y trouvent. Mots clés : Dynamique paysagère, occupation du sol, déforestation, fragmentation du paysage, télédétection, structure spatiale, INERA-Yangamb

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

Allometric equation for predicting aboveground biomass of three tree species

Allometric equations, which predict the aboveground dry biomass of a tree from its diameter and/or height, are needed to estimate carbon stocks in forests. Although pantropical multispecies biomass equations have been developed for tropical rain forests, very few tree biomass measurements are available for central Africa, and none of these measurements were used to fit the pantropical equations. We measured the biomass of 12 trees belonging to three species at Yangambi in the Democratic Republic of Congo. Using these data, we developed a site-specific biomass equation and checked whether the pantropical equations were consistent with it. The pantropical equations were within the 95% confidence interval of the fitted site-specific equation, but with a bias for measurements that ranged from 26 to 32%. Although the pantropical biomass equations were consistent with the biomass measurements at Yangambi, larger data sets (including larger trees and more species) and more precise estimate of the wood specific gravity would be required to confirm the result. © Forest Research Institute Malaysia

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