Modelling the potential distribution of African Wormwood (Artemisia afra) using machine learning algorithm-based approach (MaxEnt) in Sekhukhune District, South Africa

Artemisia afra Jacq. Ex Willd, commonly known as African wormwood, is a native medicinal plant that has been unsustainable harvested primarily for its leaves due to its medicinal properties. The unsustainable harvesting of this plant underscores the urgent need for conservation and management practices. This study, therefore, used the MaxEnt model of the potential distribution of A. afra. Location: Sekhukhune District Municipality, South Africa. We used 105 sampled records and 27 environmental variables to model the potential spatial distribution of A. afra using the MaxEnt modelling approach. The predictions were performed using current climatic and topographic conditions. A significant portion of the area, 54.46%, is highly suitable for the distribution of A. afra, with various suitability degrees. Precipitation contributed 33.6% to the suitability predictions, followed by NDVI, soil, and distance from rivers with 27.1%, 8.1%, and 5.7%, respectively. Artemisia afra is predicted to be persistent in mountainous areas and along riverbanks.

Methods
Handheld GPS was used for data collection. The collected location data was cleaned and prepared using Excel.