Prosopis juliflora (Swartz) DC has become one of the world's 100 most dominant invasive species. It is spreading quickly in different parts of the country leading to growing public concern. Effective management of invasive plants requires information regarding their spatial distributions and identifying areas vulnerable to Invasive Alien Plant Species (IAPS). This study combines Worldclim bioclimatic data with Global Biodiversity Information Facility (GBIF) and Indian biodiversity portal mediated occurrence points to model climatic suitability for P. juliflora in India under current and future climatic conditions using MaxEnt. For evaluating the importance of the environmental variables for predictive modeling, the Jack-knife test was performed. MaxEnt model was highly accurate with a statistically significant AUC value of 0.92. We observed that a larger extent of the Indian landscape currently invaded will remain suitable for P. juliflora growth and patterns of range expansion will take place soon unless management measures are initiated. Some states of North, North-western, and Southern India are projected to have higher climatic suitability for P. juliflora in the future. The findings of this study could be used as an early warning tool for the environmental monitoring of the areas which are highly vulnerable to the invasion of the species.

Prosopis juliflora (Swartz) DC 已成为世界上 100 种最主要的入侵物种之一。它正在该国不同地区迅速传播，导致公众越来越关注。入侵植物的有效管理需要有关其空间分布的信息，并确定易受外来入侵植物物种 (IAPS) 影响的区域。本研究将 Worldclim 生物气候数据与全球生物多样性信息设施 (GBIF) 和印度生物多样性门户介导的发生点相结合，为P. juliflora 的气候适宜性建模在印度使用 MaxEnt 在当前和未来的气候条件下。为了评估环境变量对预测建模的重要性，进行了杰克刀测试。MaxEnt 模型高度准确，具有统计学意义的 AUC 值为 0.92。我们观察到，目前入侵的更大范围的印度景观将仍然适合P. juliflora 的生长，除非采取管理措施，否则很快就会出现范围扩大的模式。印度北部、西北部和南部的一些州预计对P. juliflora具有更高的气候适宜性在将来。这项研究的结果可用作早期预警工具，用于对极易受到物种入侵的地区进行环境监测。