Modelling potential range expansion of Invasive Alien Plant Species under predicted climate change

Invasive alien plant species (IAPS) can pose severe threat to biodiversity and stability of native ecosystems, therefore, predicting the distribution of the IAPS plays a crucial role in effective planning and management of ecosystems. Geographical information system (GIS), remote sensing (RS), and species distribution modelling (SDM) have proven to be important for large-scale ecological studies and could be useful while prioritizing the sites for interventions aiming at invasive species control. In the present study, we use Maximum Entropy (MaxEnt) modelling approach to predict the potential of distribution of 11 IAPS under future climatic conditions by 2050 and 2070 under RCP 2.6 and RCP 8.5 in part of Kailash sacred landscape located in Western Himalaya. Prediction accuracy of the model used for analyzing the distribution of the 11 IAPS under present and future time period ranged between 0.942 and 0.997 respectively. Based on the model predictions, distribution of most of the invasive plants is expected to expand under future climatic scenarios, which might pose a serious threat to the native ecosystems through competition for resources in the study area. For instance, Ageratum conyzoides, Erigeron karvinskianus, Xanthium strumarium, Ageratina adenophora, and Bidens pilosa be speculated to expand upward by 1034 m, 981 m, 800 m, 692 m and 682 m respectively from the current elevation range. Native scrublands and subtropical needle-leaved forests will be the most affected ecosystems by expansion of the IAPS. Bio-climatic variables like minimum temperature of coldest month, mean temperature of driest quarter and mean diurnal range play major role and contribute more to the invasion by 11 IAPS in the present study. The present study is first of its kind in the Himalayan landscape in field of invasive plants and the predictions of potential distribution under future climatic conditions from our study could help decision makers in planning and managing these forest ecosystems effectively.

Keywords: Invasive plants, Kailash Sacred Landscape, MaxEnt, Nepal, Species distribution modelling,