Abstract
Prediction of the potential geographic distribution of species is essential concerning various purposes in protection and conservation. The present study focused on predicting the distribution of Pinus roxburghii Sarg. (chir pine) in Uttarakhand Himalayas using the MaxEnt model. The model produced AUC curve with significant value of 0.882 (± 0.023). The study results showed that 426200 ha (5.91%) cover highly potential habitat area for chir pine. Whereas 833900 ha (11.56%), 1019200 ha (14.13%) and 4936000 ha (68.41%) cover good potential, moderately potential and least potential habitat areas, respectively. Based on the jacknife test, it was observed that temperature seasonality (bio4), precipitation of seasonality (bio15) and precipitation of driest month (bio14) are the significant contributors to the occurrence of chir pine in Uttarakhand Himalayas. This study exemplifies the usefulness of the prediction model of species distribution and offers a more effective way to manage chir pine forest by all means, which is beneficial for both the wildlife and human beings for future prospects.
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