DOI: 10.5061/dryad.dz08kps71
title: Modelling the potential distribution of African Wormwood (Artemisia afra) using machine learning algorithm-based approach (MaxEnt) in Sekhukhune District, South Africa

description: 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.
description: Handheld GPS was used for data collection. The collected location
 data was cleaned and prepared using Excel.
description: **README** **Title**: *Modelling the Potential Distribution of African
 Wormwood* (Artemisia afra) *Using a Machine Learning Algorithm-Based
 Approach (MaxEnt) in Sekhukhune District, South Africa* **DOI**:
 [https://doi.org/10.5061/dryad.dz08kps71](https://doi.org/10.5061/dryad.dz08kps71) --- ## Description of the Data and File Structure This dataset contains georeferenced field occurrence records and raster-based environmental predictors used to model the potential distribution of *Artemisia afra* using the MaxEnt algorithm. Field data were collected in the Greater Sekhukhune District Municipality, Limpopo, South Africa. Environmental variables were sourced from publicly available datasets and processed to meet the requirements of MaxEnt. ### File: `Occurrence_Data.zip` Contains presence-only occurrence records for *Artemisia afra* used in model development and validation. * **Artemisia afra train.csv** * 70% of field-verified occurrence points (training set) * Columns: * `Latitude`: Decimal degrees * `Longitude`: Decimal degrees * `Species`: Always listed as `Artemisia afra` * **Artemisia afra test.csv** * 30% of field-verified occurrence points (testing set) * Same column structure as the training set ### File: `ENVIRONMENTAL_LAYERS.zip` Contains raster files of environmental predictors used in the MaxEnt modelling. * **Format**: .asc (ESRI ASCII Raster) * **Projection**: WGS 1984 UTM Zone 35S * **Resolution**: 30 arc seconds (climatic layers), 30 meters (topographic/land layers) | **Variable Name** | **Units** | **Resolution** | **Source** | | :-------------------------------------------- | :-------- | :------------- | :--------------------------------------------------------------------------------------------------------- | | Bio1: Annual Mean Temperature | °C | 30 arc seconds | WorldClim ([https://www.worldclim.org/](https://www.worldclim.org/)) | | Bio2: Mean Diurnal Range | °C | 30 arc seconds | WorldClim | | Bio3: Isothermality (BIO2/BIO7 × 100) | % | 30 arc seconds | WorldClim | | Bio4: Temperature Seasonality | % | 30 arc seconds | WorldClim | | Bio5: Max Temperature of Warmest Month | °C | 30 arc seconds | WorldClim | | Bio6: Min Temperature of Coldest Month | °C | 30 arc seconds | WorldClim | | Bio7: Temperature Annual Range | °C | 30 arc seconds | WorldClim | | Bio8: Mean Temperature of Wettest Qtr | °C | 30 arc seconds | WorldClim | | Bio9: Mean Temperature of Driest Qtr | °C | 30 arc seconds | WorldClim | | Bio10: Mean Temp of Warmest Qtr | °C | 30 arc seconds | WorldClim | | Bio11: Mean Temp of Coldest Qtr | °C | 30 arc seconds | WorldClim | | Bio12: Annual Precipitation | mm | 30 arc seconds | WorldClim | | Bio13: Precipitation of Wettest Period | mm | 30 arc seconds | WorldClim | | Bio14: Precipitation of Driest Period | mm | 30 arc seconds | WorldClim | | Bio15: Precipitation Seasonality (CV) | % | 30 arc seconds | WorldClim | | Bio16: Precipitation of Wettest Qtr | mm | 30 arc seconds | WorldClim | | Bio17: Precipitation of Driest Qtr | mm | 30 arc seconds | WorldClim | | Bio18: Precipitation of Warmest Qtr | mm | 30 arc seconds | WorldClim | | Bio19: Precipitation of Coldest Qtr | mm | 30 arc seconds | WorldClim | | Elevation | meters | 30 m | SRTM DEM ([https://code.earthengine.google.com/](https://code.earthengine.google.com/)) | | Slope | degrees | 30 m | Derived from DEM | | Aspect | degrees | 30 m | Derived from DEM | | Topographic Wetness Index | index | 30 m | Derived from DEM | | Soil | - | 1:1 million | SOTER Database ([https://www.isric.org/explore/soter](https://www.isric.org/explore/soter)) | | Land Cover | - | 30 m | [https://egis.environment.gov.za/gis\_data\_downloads](https://egis.environment.gov.za/gis_data_downloads) | | NDVI (Normalized Difference Vegetation Index) | - | 30 m | Sentinel-2 MSI ([https://code.earthengine.google.com/](https://code.earthengine.google.com/)) | | Distance from Rivers | meters | 1:50,000 | [https://www.dws.gov.za/iwqs/gis\_data/river/](https://www.dws.gov.za/iwqs/gis_data/river/) | **Additional Files and Subfolders:** * `.prj` and `.xml` files: Associated with selected raster layers for projection and metadata * `Selected variables`: Contains the final 13 predictor layers used in model construction * `maxent.cache`: Model-generated internal cache files created by MaxEnt during runs --- ## Code/Software ### 1. MaxEnt (Maximum Entropy Modelling Software) * **Version**: 3.4.1 * **URL**: [https://biodiversityinformatics.amnh.org/open_source/maxent/](https://biodiversityinformatics.amnh.org/open_source/maxent/) * **Usage**: Input: training/testing CSVs + environmental layers in `.asc` format. Output: suitability maps, AUC, response curves, jackknife plots. ### 2. ArcGIS 10.8 (Esri) * Used for raster pre-processing (projection, resampling, masking, format conversion to `.asc`) ### 3. Microsoft Excel / LibreOffice Calc * Used for CSV inspection and editing --- ## Access Information ### Other publicly accessible locations of the data: The dataset is exclusively hosted on Dryad: [https://doi.org/10.5061/dryad.dz08kps71](https://doi.org/10.5061/dryad.dz08kps71) ### Data was derived from the following sources: | Source Name | Description | License | | :----------------- | :----------------------- | :----------------------------------- | | WorldClim v2.1 | Bioclimatic variables | Open for research/non-commercial use | | SRTM (CGIAR-CSI) | Elevation, slope, aspect | Public domain | | MODIS / Sentinel-2 | NDVI | NASA/Public use | | SANLC (DFFE) | Land cover | Open access South Africa | | SoilGrids / SOTER | Soil classification | ODbL license | | HydroSHEDS / DWS | River data and proximity | Free for scientific use | --- This README ensures complete transparency and usability for future users and reviewers.