Modeling of <i> Valeriana wallichii </i> Habitat Suitability and Niche Dynamics in the Himalayan Region under Anticipated Climate Change

Abstract

'Shazia Mushtaq' 'Aneela Gulnaz' 'Bilal Ahamad Paray' 'Lei Xu' 'Qiyong Liu'] Simple Summary In the modern era of the anthropocene, an increase in the accumulation of greenhouse gases in the atmosphere has resulted in the global rise of the Earth’s temperature. This has resulted in the habitat shift of various plant and animal species. Plant species that are endemic show a narrow distribution range and inhabit higher elevations are highly susceptible to the impacts of global warming. The present study discusses the habitat distribution of Valeriana wallichi, an endangered medicinal herb. We also predicted the impact of climate change on its distribution range and niche dynamics. Results reveal significant contraction in the possible habitats of this herb under future climatic scenarios, with RCP 8.5 for 2070 showing the highest habitat loss. Niche equivalency and similarity tests describe that the habitats could be compared but not identical between current and future climatic scenarios. From the current study, we conclude that the habitats of Valeriana wallichii are highly vulnerable to climate shifts. This study can not only be used to alleviate the threat to this plant by documenting the unexplored populations, restoring the degraded habitats through rewilding and launching species recovery plans in the natural habitats but could also be used by various conservation biologists to recover the declining status of various highly valued species across the globe. Abstract An increase in atmospheric greenhouse gases necessitates the use of species distribution models (SDMs) in modeling suitable habitats and projecting the impact of climate change on the future range shifts of the species. The present study is based on the BIOMOD ensemble approach to map the currently suitable habitats and predict the impact of climate change on the niche shift of Valeriana wallichii. We also studied its niche dynamics using the ecospat package in R software. Values of the area under curve (AUC) and true skill statistics (TSS) were highly significant (>0.9), which shows that the model has run better.