Modelling the current and future spatial distribution of suitable areas for V. polyanthes using maxent in Zimbabwe
摘要
Climate change has contributed to the spread of invasive terrestrial species. Vernonanthura polyanthes, a species native to South America, has recently emerged as an invasive plant in parts of Zimbabwe. This study aimed to predict the current and future distribution of Vernonanthura polyanthes in Mutare, Chimanimani, and Mutasa districts, and to identify the environmental and climatic factors influencing its spread. Species presence data were collected using a GPS device. Nineteen bioclimatic variables related to temperature and precipitation were considered. The MaxEnt model was used to estimate the relationship between species occurrences and environmental variables. Environmental layers were obtained from the Africlim portal, and variables were selected based on their biological relevance to plant distribution. MaxEnt output included variable contributions and jackknife tests to assess the importance of each variable. Models were run by excluding one variable at a time and by running each variable independently. The final model included quadratic, hinge, and linear feature types. Model performance was evaluated using the area under the curve (AUC) as well as the Continuous Boyce Index (CBI). The model showed that the presence of V. polyanthes was primarily associated with annual precipitation (65.3) and mean temperature coolest month (34.7) and permutation importance of 74 and 36% respectively. Results indicated that approximately 2181.95, 265.16,1532.42 and 4895.66km2 is not suitable all time, suitable now and not suitable in future, not suitable now but suitable in future, and always suitable respectively. Both the AUC (0.87) and CBI (0.5) indicated that the MaxEnt model provided useful predictions for identifying potentially suitable habitats for V. polyanthes. These findings suggest that V. polyanthes is an invasive species with the potential to spread to areas with similar environmental and climatic conditions. The findings emphasize the need for proactive management strategies to prevent its further spread into ecologically vulnerable regions.