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Insights from present distribution of an alpine mammal Royle’s pika ( Ochotona roylei ) to predict future climate change impacts in the Himalaya

Regional Environmental Change(2019)

Cited 14|Views5
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Abstract
Climate change poses a major threat to the survival of alpine mammals living in fragmented habitats with poor dispersal abilities. Among these important prey species, pikas are considered especially vulnerable to rising temperatures that would impede their surface activity and dispersal. We investigated how climatic regimes influence the niche of the Royle’s pika ( Ochotona roylei ), and which climatic drivers and change trajectories may threaten the species’ future sustenance, thereby prioritizing areas for future conservation of this species across its distribution range. We used Royle’s pika presence locations in the MaxEnt framework, along with biologically relevant climatic and topographical variables, to model the present (2010) and the future (2050, 2070) climatic niche under different future scenarios projected by CCSM4 climatic models. Subsequently, we estimated the climatic niche loss across the elevation gradient, longitudinal gradient, and both inside and outside protected areas for all countries within the species’ range. Niche suitability of the Royle’s pika was substantially determined by precipitation of the coldest quarter (~snow cover) and wettest quarter (~monsoon rainfall). As these parameters are known to be vulnerable to global climatic change, our projection revealed significant loss (102 km 2 /year) in the species niche availability across all future scenarios, particularly in non-protected low-elevation regions. By identifying areas where species survival may be threatened, we confirmed that the distribution of Royle’s pika, an important prey species, might be reduced by climate change. Our findings can aid in conservation planning strategies for this species and other alpine fauna and contribute to ongoing efforts to monitor change in the Himalaya.
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Key words
Alpine, Climatic niche, Ecological niche modeling, Himalaya, MaxEnt, Pika
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