Conserving the critically endangered Hangul (Cervus hanglu hanglu) - Future distribution and efficiency of protected areas under climate change: Implications for the conservation of Dachigam landscape

Abstract

Abstract Climate change is impacting species distribution, posing a significant threat to biodiversity. Special attention is needed for vulnerable species like the Kashmir Red Deer (Cervus hanglu hanglu). Despite being a global conservation symbol, holistic management is hindered by limited research. A comprehensive study mapping the potential habitat changes for the Hangul in the Dachigam landscape is crucial to enhance conservation efforts. We examined the prospective effects of expected global warming on the distribution of Hangul by assessing species range shifts and employing a maximum entropy approach. The Hangul was anticipated to be sensitive to upcoming global warming and would raise its risk of local extinction. The severity of repercussions from climate change grew as the time horizon increased and decreased the species' suitable habitat. By 2080, predictions indicated a gradual reduction in range or, in some scenarios, the complete loss of habitat, regardless of the potential for Hangul to disperse indefinitely. We estimated that the overall very highly suitable habitat in the protected region is currently 2220 ha, while its huge distribution area in the unprotected zone is 30,445 ha, emphasizing the necessity of establishing corridor connectivity between fragment populations and promoting conservation efforts. Among various climate conditions, the core-to-edge ratio is at its highest level in the current conditions. Our study reveals two critical findings: Firstly, endangered species unique to a particular region are highly susceptible to the ramifications of global warming. Secondly, when evaluating the outcomes of global warming, the highly suitable habitat is expected to shift under predicted climatic changes, with an average altitudinal migration of 700m. Consequently, conservation strategies must consider the expected regional shifts and are designed with a clear understanding of the accuracy in projecting climate change effects.