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Predicting the Effects of Future Climate Change on the Potential Distribution of Eolagurus luteus in Xinjiang

Qinghui An, Jianghua Zheng (), Jingyun Guan, Jianguo Wu, Jun Lin, Xifeng Ju and Rui Wu
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Qinghui An: College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China
Jianghua Zheng: College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China
Jingyun Guan: College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China
Jianguo Wu: Locust and Rodent Control Headquarters of Xinjiang Uygur Autonomous Region, Urumqi 830001, China
Jun Lin: Locust and Rodent Control Headquarters of Xinjiang Uygur Autonomous Region, Urumqi 830001, China
Xifeng Ju: College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China
Rui Wu: College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China

Sustainability, 2023, vol. 15, issue 10, 1-15

Abstract: Eolagurus luteus (yellow steppe lemming Eolagurus luteus Eversmann, 1840) is a keystone species in the desert steppe of northern Xinjiang, one of the regions most affected by global climate change. Their behavior of eating grassland vegetation and digging holes has resulted in the reduction of grassland vegetation and soil erosion in northern Xinjiang, which has seriously affected the ecological balance of the grassland in northern Xinjiang, and pathogens carried by E. luteus pose a great threat to human health. Climate change exacerbates the uncertainty of the outbreak of E. luteus . Predicting the suitable habitat area of this species under climate change scenarios will help farmers and herders deal with the potential threat of an E. luteus outbreak. In this study, 117 actual occurrence points of E. luteus were used, and 24 climate models, 6 soil factors and 3 topographic factors from the Coupled Model Intercomparison Project (CMIP6) were taken into account. Combining the MaxEnt model and the overlay analysis function of ArcGIS software, the potential geographic distribution of E. luteus in 2030 and 2050 for the green development path (SSP126), the intermediate development path (SSP245), the regional competition path (SSP370), and the high development path (SSP585) was predicted. The change trend of the suitable area and distribution pattern of E. luteus in Xinjiang under future climate conditions was analyzed, and the main environmental factors affecting the distribution of E. luteus are discussed. The results show that the average area under curve (AUC) and true skill statistics (TSS) of the MaxEnt model are 0.993 and 0.8816, respectively, indicating that the model has a good prediction effect. The analysis of environmental factors showed that the main environmental factors affecting the potential geographical distribution of E. luteus are average annual temperature, isotherm, average temperature in the wettest quarter, average temperature in the driest quarter, and precipitation variation coefficient. With the increase of radiation intensity and time, the suitable areas of E. luteus will continue to decrease. Especially in the 2050s under the SSP585 scenario, the middle and high suitable areas will decrease by 2.58 × 10 4 km 2 and 1.52 × 10 4 km 2 , respectively. Although the potential habitat area of E. luteus is shrinking, the future threat of E. luteus to grassland ecological security and human health should not be underestimated due to ecological adaptation of the community and the frequent occurrence of extreme weather. Therefore, studying changes in the potential geographic distribution of E. luteus under climate change scenarios and developing appropriate monitoring programs are of great importance for grassland ecological security and human health. This study fills in the gaps in the study of the potential geographical distribution of E. luteus and provides methodological and literature support for the study of the potential geographical distribution of other rodents.

Keywords: maximum entropy model; Eolagurus luteus; climate change; suitable area (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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