Daï Emilienne Houévo, Hermann Houndonougbo Juliano Sènanmi, Idohou Rodrigue, Ouédraogo Amadé, Kakaï Romain Glèlè, Hotes Stefan, Assogbadjo Achille Ephrem
Laboratoire de Biomathématiques et d'Estimations Forestières, Faculté des Sciences Agronomiques, Université d'Abomey-Calavi, 04 BP 1525, Cotonou, Benin.
Laboratoire d'Ecologie Appliquée, Faculté des Sciences Agronomiques, Université d'Abomey-Calavi, 01 BP 526, Cotonou, Benin.
Heliyon. 2023 Feb 11;9(2):e13658. doi: 10.1016/j.heliyon.2023.e13658. eCollection 2023 Feb.
is a wild shrub species widely used as a source for traditional medicine, food and fuel in West Africa. The species is threatened by uncontrolled harvesting of its roots for pharmaceutical applications and by the extension of agricultural land. This study assessed the role of environmental variables for the current distribution and the potential impact of climate change on the future spatial distribution of in Benin. We used data related to climate, soil, topography and land cover to model the distribution of the species. Occurrence data were combined with six least correlated bioclimatic variables derived from the WorldClim database, data on soil layers (texture and pH) and topography (slope) obtained from the FAO world database and land cover from the DIVA-GIS site. Random Forest (RF), Generalized Additive Models (GAM), Generalized Linear Models (GLM) and the Maximum Entropy (MaxEnt) algorithm were used to predict the current and future (2050-2070) distribution of the species. Two climate change scenarios (SSP245 and SSP585) were considered for the future predictions. The results showed that climate (i.e., water availability) and soil type are the key predictors of the distribution of the species. Based on future climate projections, RF, GLM and GAM models predict that the Guinean-Congolian and Sudano-Guinean zones of Benin will remain suitable for , while it will decline in these zones according to the MaxEnt model. These results call for a timely management effort for the species in Benin through its introduction into agroforestry systems to ensure the continuity of its ecosystem services.
是一种野生灌木物种，在西非被广泛用作传统药物、食物和燃料的来源。该物种受到因制药用途而对其根部进行无节制采挖以及农业用地扩张的威胁。本研究评估了环境变量对贝宁当前分布的作用以及气候变化对其未来空间分布的潜在影响。我们使用了与气候、土壤、地形和土地覆盖相关的数据来模拟该物种的分布。出现数据与从WorldClim数据库导出的六个相关性最小的生物气候变量、从粮农组织世界数据库获得的土壤层（质地和pH值）和地形（坡度）数据以及DIVA - GIS网站的土地覆盖数据相结合。随机森林（RF）、广义相加模型（GAM）、广义线性模型（GLM）和最大熵（MaxEnt）算法被用于预测该物种当前和未来（2050 - 2070年）的分布。未来预测考虑了两种气候变化情景（SSP245和SSP585）。结果表明，气候（即水分可利用性）和土壤类型是该物种分布的关键预测因子。基于未来气候预测，RF、GLM和GAM模型预测贝宁的几内亚 - 刚果和苏丹 - 几内亚地区将仍然适合该物种生长，而根据MaxEnt模型，该物种在这些地区的分布将减少。这些结果呼吁通过将其引入农林业系统，对贝宁的该物种及时进行管理，以确保其生态系统服务的连续性。
