气候变化对中国主要旱獭分布及其鼠疫传播风险的动态影响:基于最大熵和最小累积阻力模型的综合预测
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1.新疆大学;2.新疆维吾尔自治区蝗虫鼠害预测预报防治中心站;3.新疆大学地理与遥感科学学院

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新疆重点野生疫源动物种群分布遥感监测项目(202334140017);新疆维吾尔自治区2023年天山英才培养计划青年托举人才项目(2023TSYCQNTJ0019);鼠害遥感专项调查(202434140008)


Dynamic effects of climate change on the distribution of major Marmota and the risk of plague transmission in China: a combined prediction based on maximum entropy and minimum cumulative resistance models
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Affiliation:

1.Xinjiang University;2.Locust and Rodent Pest Prediction, Forecasting and Control Center Station of Xinjiang Uygur Autonomous Region;3.College of Geography and Remote Sensing Sciences, Xinjiang University

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Remote Sensing Monitoring of the Distribution of Key Wild Epidemiological Animal Populations in Xinjiang (202334140017); Xinjiang Uygur Autonomous Region 2023 Tianshan Talent Cultivation Program for Young Tolerate Talents (2023TSYCQNTJ0019); Special Survey on Remote Sensing of Rodent Pests (202434140008)

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    摘要:

    旱獭是中国最主要的疫源动物之一,宿主动物种群的分布变化对于鼠疫的传播和扩散具有着重要的作用。为了解气候变化对旱獭的空间分布的影响,识别旱獭与人类未来潜在的时空重合区域。本研究采用最大熵(Maximum Entropy)模型,选择了43个可能影响旱獭空间分布的变量,包括生物气候、地形、土壤、植被数据,通过 Spearman 相关系数和刀切法筛选变量,确定了22个变量。在三种共享经济路径下(SSP126、SSP245 和 SSP585)对2050s和2070s中国境内的主要旱獭的分布进行预测,同时利用最小累积阻力(Minimal Cumulative Resistance,MCR)模型模拟旱獭未来潜在的迁移路径,并结合未来土地利用数据识别未来的旱獭鼠疫风险区域。结果表明,当前旱獭适生区总面积为147×104km2,主要分布在中国的新疆西缘和南缘,西藏中部和东部、青海省东部、四川省西部以及甘肃省西南部等地,在未来多种气候情景下旱獭适生区面积表现出不同的增减趋势;西藏中部、四川省西部、青海省东部以及新疆南缘是旱獭适生区变化的主要区域;适生区增减变化形成了以新疆南部地州的草原地带和西藏中部地区为主的旱獭迁移主要的途经区域,此外,不同气候情景下,风险区主要分布在新疆北部、南缘和西缘、西藏中部和东部、青海省东部、四川省西部和甘肃省西南部等区域,在未来风险区域会发生中低风险区的互相转移,在短期和低CO2浓度排放情景下土地利用类型的变化对风险区转移的影响较大,但在长期和高CO2浓度排放情景下气候变化占主导。本研究旨在为旱獭分布监测及其鼠疫防控管理提供参考。

    Abstract:

    Marmota, a key host for the plague in China, plays a crucial role in the transmission and spread of this deadly disease. As climate change continues to alter environmental conditions, the spatial distribution of Marmota populations is also expected to change. These changes may, in turn, affect the dynamics of plague transmission and create new areas of risk for humans. To explore this effect, this study aims to assess the impact of climate change on the distribution of Marmota and identify potential spatial and temporal overlaps between Marmota habitats and human populations in the future. To achieve this, the study employed the Maximum Entropy (MaxEnt) model to analyze 43 environmental variables that may influence Marmota's spatial distribution. These variables included bioclimatic, topographic, soil, and vegetation data. Twenty-two of the 43 variables were selected for modeling through Spearman's correlation analysis and the knife-cut method. The study then used these variables to predict the future distribution of Marmota under three Shared Socioeconomic Pathways (SSPs)—SSP126, SSP245, and SSP585—during two timeframes: the 2050s and the 2070s. Potential migration pathways of Marmota under different future climate scenarios were simulated using the Minimum Cumulative Resistance (MCR) model in conjunction with future land use projections. The results revealed that the current Marmota habitat spans approximately 147,000,0 km2, primarily in the western and southern regions of Xinjiang, central and eastern Tibet, eastern Qinghai, western Sichuan, and southwestern Gansu. Under different climate scenarios, the Marmota's habitat is expected to expand or contract, with central Tibet, western Sichuan, eastern Qinghai and southern Xinjiang expected to be its main migratory passages. The study also identified areas of risk for Marmota-human overlap, which are mainly located in the northern, southern, and western edges of Xinjiang, central and eastern Tibet, eastern Qinghai, western Sichuan, and southwestern Gansu. These risk zones are likely to change under various climate scenarios, with changes in land-use types having a greater impact on shifting risk zones under short-term and low CO2 concentration emission scenarios, while climate change dominates under long-term and high CO2 concentration emission scenarios. This research underscores the complex interplay between climate change and land use in shaping the future distribution of Marmota populations and the associated risk for plague transmission. The study's findings are crucial for developing effective monitoring and management strategies aimed at controlling the spread of plague, particularly in regions where Marmota populations overlap with human settlements. By providing a detailed assessment of future Marmota habitat changes and identifying high-risk areas, this research offers valuable insights that could inform public health and conservation efforts in the face of a changing climate.

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刘宣,李璇,郑江华,林峻,刘亮,田瑞康.气候变化对中国主要旱獭分布及其鼠疫传播风险的动态影响:基于最大熵和最小累积阻力模型的综合预测.生态学报,,(). http://dx. doi. org/[doi]

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