The prediction of species distribution is a cardinal tool for conservation and recuperation planning of medicinally and culturally important plant species. Climate change accompanied with anthropogenic pressures are the imperative factors in changing the alpine vegetation’s habitat and causing their natural habitat to shrink in numbers. Saussurea obvallata (DC.) Sch.Bip., is an important yet highly threatened medicinal herb of the Himalayan region. Overexploitation and unscientific harvesting have resulted in the steep decline of the plant’s natural habitat populations. The present study aims to the model the present and future distribution of S. obvallata, using MaxEnt in Uttarakhand state, India. The authors selected twenty-six variables (bioclimatic, topographic and pedologic) and 38 well-dispersed species occurrence points to predict the potential distribution of S. obvallata in Uttarakhand. Future distributions were projected under two Shared Socioeconomic Pathways (SSP2-4.5, SSP5-8.5) scenarios using two Global Circulation Models for the period 2021–2040 and 2041–2060. Results showed that the MaxEnt model was accurate, with the area under ROC (Receiver Operating Characteristic) curve reaching 0.9352 with isothermality, precipitation of warmest quarter, temperature of annual range, mean diurnal range and aspect emerging as the major contributing variables to the model. The study identified 1378.88 km2 high suitability area and 5135 km2 area with medium suitability for S. obvallata in Uttarakhand. The results of this study can be used to plan conservation strategies and prioritizing the highly suitable areas to be used as rehabilitation sites for S. obvallata. Overall, this study highlights an urgent need for instantaneous policy interventions to protect S. obvallata from habitat fragmentation, unscientific harvesting, and over exploitation.
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