Modeling the Potential Distribution of Typha domingensis (Pers.) in Niger Under Current and Future Climate Scenarios.
Bourahima Adamou Moumouni, Bachirou Seyni Bodo, Manssour Abdou Maman, Aboubacar Awaïss
Abstract
Open AccessThe invasion of water bodies by Typha domingensis is one of the main obstacles to the management and development of wetlands. To ensure the continuous provision of services and the maintenance of development activities in these areas, it is necessary to understand the current distribution of this species, as well as its future distribution in the face of climate change. It is in this context that this study has set the following objectives: (i) identifying the explanatory variables that influence the distribution of T. domingensis habitat and (ii) determining its current and future distribution area in Niger. To do this, bioclimatic variables from Worldclim, slope, elevation, and 378 spatially filtered to minimize clustering T. domingensis occurrence points were used for scientific precision. These data were loaded into the maximum entropy-based geographic distribution modeling program called "MaxEnt, version 3.4.4". The area under the curve (AUC) value and the Jackknife test were used to assess the model stability and the importance of environmental variables for predictive modeling, respectively. The model yielded a high AUC value of 0.98, indicating strong predictive performance. Isothermality (76.7%), precipitation seasonality (10.4%), and altitude (6.4%) are the environmental variables that contribute most to the distribution of T. domingensis range. The distribution of the T. domingensis range currently extends along the Sahelian and Sahelo-Sudanian agroecological zones, with a surface area of 32,036 km2 compared with 4930 km2 in future projections, representing a contraction of around 85%. The approach could be promising for predicting the potential distribution of invasive aquatic plant species and can therefore be an effective tool for adapting conservation and management policies for affected wetlands.