Species distribution modelling to identify invasion hotspots of Ageratina riparia in Mizoram, India

Abstract. Sengupta R, Dash SS. 2024. Species distribution modelling to identify invasion hotspots of Ageratina riparia in Mizoram, India. Asian J For 8: 184-193. The accelerated pace of globalization, increased human mobility, and the intensification of global trade have significantly amplified the spread of non-native species worldwide. The introduction of these alien species has triggered invasive consequences, further intensified by climate change. Accurately predicting the spread of invasive species under changing climatic conditions is essential for identifying vulnerable regions and formulating effective management strategies to limit their spread. This study projected and identified invasion hotspots for the neo-invasive species Ageratina riparia in Mizoram, using its current distribution patterns and projected climate changes. Habitat suitability modelling, performed with the Maximum Entropy (MaxEnt) machine learning algorithm using default settings, showed that the current distribution of A. riparia encompasses 4.78% of Mizoram's area, deemed suitable for varying levels of invasion. Projections for 2050 and 2070 indicated that suitable habitats for A. riparia could expand to 6.19% of Mizoram's area by 2050 under the RCP 4.5 scenario, relative to its present distribution. This anticipated expansion, combined with an upward shift in elevation, highlights the urgent need for effective management strategies to mitigate the invasion by A. riparia. The findings provide critical insights for identifying and projecting invasion hotspots, which are essential for early-stage management of A. riparia invasions.