Identifying climate refugia and its potential impact on Tibetan brown bear (Ursus arctos pruinosus) in Sanjiangyuan National Park, China

Abstract

Climate change has direct impacts on wildlife and future biodiversity protection efforts. Vulnerability assessment and habitat connectivity analyses are necessary for drafting effective conservation strategies for threatened species such as the Tibetan brown bear (Ursus arctos pruinosus). We used the maximum entropy (MaxEnt) model to assess the current (1950–2000) and future (2041–2060) habitat suitability by combining bioclimatic and environmental variables, and identified potential climate refugia for Tibetan brown bears in Sanjiangyuan National Park, China. Next, we selected Circuit model to simulate potential migration paths based on current and future climatically suitable habitat. Results indicate a total area of potential suitable habitat under the current climate scenario of approximately 31,649.46 km2, of which 28,778.29 km2 would be unsuitable by the 2050s. Potentially suitable habitat under the future climate scenario was projected to cover an area of 23,738.6 km2. Climate refugia occupied 2,871.17 km2, primarily in the midwestern and northeastern regions of Yangtze River Zone, as well as the northern region of Yellow River Zone. The altitude of climate refugia ranged from 4,307 to 5,524 m, with 52.93% lying at altitudes between 4,300 and 4,600 m. Refugia were mainly distributed on bare rock, alpine steppe, and alpine meadow. Corridors linking areas of potentially suitable brown bear habitat and a substantial portion of paths with low‐resistance value were distributed in climate refugia. We recommend various actions to ameliorate the impact of climate change on brown bears, such as protecting climatically suitable habitat, establishing habitat corridors, restructuring conservation areas, and strengthening monitoring efforts.

Identifying the risk regions of house break‐ins caused by Tibetan brown bears (Ursus arctos pruinosus) in the Sanjiangyuan region, China

“…Province. Presence points of bear damage were collected by conducting household surveys and semi-structured interviews during field surveys carried out as part of other research projects (Dai, Hacker, et al, 2019;. Coordinates of bear damage were recorded with GPS.…”

“…Only 16 households did not experience bear damage. In order to reduce autocorrelation, we filtered occurrence points by randomly selecting one point in each grid of 1 km 2 according to model optimization recommendations and previous studies (Aryal et al, 2016;Dai, Hacker, et al, 2019;Li, Liu, Xue, Zhang, & Li, 2017;Phillips, Anderson, & Schapire, 2006).…”

“…AUC is an independent threshold value to verify the accuracy of model outputs, and its value ranges from 0 to 1. When AUC is closer to 1, the accuracy of the model is higher (Araujo, Pearson, Thuiller, & Erhard, 2005;Dai, Hacker, et al, 2019;Phillips et al, 2006).…”

“…Circuit model is based on circuit theory, predicting the movement of random walkers between source and target cells across a landscape by electricity patterns (Dai, Hacker, et al, 2019;McRae & Beier, 2007;McRae, Shah, & Mohapatra, 2013;Walpole, Bowman, Murray, & Wilson, 2012). We simulated risk diffusion paths for brown bears based on the risk map from our MaxEnt model by using Circuitscape software 4.0 (https ://circu itsca pe.org/).…”

“…The Tibetan brown bear ( Ursus arctos pruinosus ; Figure ), also known as the Tibetan blue bear, is a rare subspecies of brown bear living at high altitudes in close proximity to humans in Central Asia (Dai, Hacker, et al, ; Dai, Li, et al, ; Dai, Xue, et al, ; Xu et al, ). The species population estimate is between 5,000 and 6,000 individuals (Wu, ).…”