Predicting the Habitat Suitability of a Potential Invasive Fern, Cyclosorus afer in Lafia, Nigeria using Species Distribution Modelling

Abstract

The vast colonisation of some wetlands by Cyclosorus afer in Lafia, Nigeria has been a serious concern to ecologists and indigenous dwellers. In this study, we used the Maximum Entropy (Maxent) modelling technique to predict the habitat suitability of this fern in Lafia, Nigeria. We obtained the presence data of this fern in three already invaded wetlands of size 500 x 500m2 each using multiple 200m transect. Bioclimatic and elevation variables which were obtained from different databases were imputed into the model as predictor variables of C. afer. After that, the Maxent model was run with 70% of the presence data as training and 30% as test data. Our model result revealed that the area under the curve for receiver operating characteristics of training is 0.847 while and test data is 0.970. The model’s sensitivity was observed to be 100%. The model was assessed based on a jackknife test of individual contributions of each predictor variable to the model. Therefore, the environmental predictors of the occurrence of C. afer in this study area include precipitation seasonality, Precipitation of driest quarter, precipitation of coldest quarter and elevation. This model could be described as accurate, and the occurrence of C. afer in Lafia, Nigeria, is influenced by limiting environmental factors

Keywords

• cyclosorus afer
• fern
• invasion
• lafia
• maxent
• modelling