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生态学杂志 ›› 2025, Vol. 44 ›› Issue (10): 3447-3456.doi: 10.13292/j.1000-4890.202510.025

• 研究报告 • 上一篇    下一篇

气候变化对极危物种黄胸鹀繁殖适生区的影响

王茂琳1,2,雷宇2,颜尉珂2,李红霆2,刘强1,2*   

  1. 1西南林业大学云南省高原湿地保护修复与生态服务重点实验室, 昆明 650224; 2西南林业大学国家高原湿地研究中心/生态与环境学院, 昆明 650224)

  • 出版日期:2025-10-10 发布日期:2025-10-14

Impacts of climate change on the suitable breeding area of the critically endangered yellow-breasted bunting (Emberiza aureola).

WANG Maolin1,2, LEI Yu2, YAN Weike2, LI Hongting2, LIU Qiang1,2*#br#   

  1. (1Yunnan Key Laboratory of Plateau Wetland Conservation, Restoration and Ecological Services, Southwest Forestry University, Kunming 650224, China; 2National Plateau Wetlands Research Center/College of Ecology and Environment, Southwest Forestry University, Kunming 650224, China).

  • Online:2025-10-10 Published:2025-10-14

摘要: 黄胸鹀(Emberiza aureola)是曾广布于亚欧大陆的一种鸣禽,近年来其保护地位不断上升,已成为世界性“极危”物种,在我国被列为国家一级重点保护野生动物。导致黄胸鹀种群数量急剧下降的原因曾被归结为中国东部地区的非法狩猎,却忽视了气候因素对繁殖区黄胸鹀种群的潜在影响。本研究应用气候生态位理论,结合黄胸鹀繁殖区的气候变量和分布点,基于MaxEnt最大熵模型预测现时期黄胸鹀潜在繁殖适生区以及在未来气候变化背景下两个时期(2050s和2070s时期)的适生区变化趋势。结果表明:(1)影响黄胸鹀繁殖区分布的主要变量是最暖季度降雨量(贡献率35.4%)、年平均气温(贡献率35.3%)、温度季节性变化系数(贡献率12.4%)。(2)现时期黄胸鹀繁殖适生区总面积为1131.18万km2,主要分布于俄罗斯(77.93%)、其次是中国(10.52%)、蒙古(5.30%)、芬兰(3.22%)以及其他国家如瑞典(3.03%)。(3)未来气候变化背景下,适宜黄胸鹀繁殖区的面积不断缩减,2050s和2070s时期相比现时期分别减少15.50%和32.99%;其中,我国在未来两个时期的降幅分别为79.22%和91.39%。(4)质心迁移结果显示,黄胸鹀繁殖区分布中心表现出向东北方向移动的趋势,即在空间上,适生区向高纬度转移,低纬度地区萎缩,西部欧洲部分萎缩,东北亚部分适生区增加。本研究凸显出气候变化在种群层面上对黄胸鹀的巨大威胁,对于此类物种的保护管理仅禁猎是不够的,必须从全球尺度上遏制气候变暖趋势,才能减缓气候变化对濒危物种的负面影响。


关键词: 黄胸鹀, 濒危物种, 最大熵模型, 分布区萎缩

Abstract: The yellow-breasted bunting (Emberiza aureola) is a songbird that was once widely distributed across Eurasia. In recent years, its conservation status has continuously risen, and it has become a globally “Critically Endangered” species. In China, it is listed as a National First-Class Key Protected Wild Animal. In recent years, the yellow-breasted bunting has experienced a dramatic decline, which was once attributed to the illegal hunting in eastern China. However, the potential influence of climatic factors on the yellow-breasted bunting population in the breeding areas has been neglected. In this study, we applied the theory of climatic ecological niche by combining climatic variables and distribution points in the breeding areas of yellow-breasted buntings. This approach allowed us to predict, based on the Maximum Entropy Model (MaxEnt), the potential breeding area suitable for yellowbreasted buntings in the present period, as well as the trend of suitable areas in two future periods, the 2050s and 2070s, under the backdrop of climate change. The results showed that: (1) The main variables affecting the distribution of the breeding area of the yellowbreasted bunting were the rainfall in the warmest season (a contribution rate of 35.4%), the mean annual air temperature (a contribution rate of 35.3%), and the coefficient of seasonal variation of temperature (a contribution rate of 12.4%). (2) The total area of suitable breeding areas in the current period is 11.3118 million km2, mainly distributed in Russia (77.93%), followed by China (10.52%), Mongolia (5.30%), Finland (3.22%), and other countries such as Sweden (3.03%). (3) Under the background of future climate change, the area of suitable breeding grounds will continue to shrink. Compared with the current period, the suitable area will decrease by 15.50% in the 2050s and 32.99% in the 2070s. Among them, China will see a significant reduction in suitable breeding areas, with a decline of 79.22% in the 2050s and 91.39% in the 2070s. (4) The centroid of the breeding range is shifting northeastward. The suitable area is shifting towards higher latitudes, while that in the low-latitude areas is shrinking, with contraction in western part of Europe and expansion in Northeastern Asia. Our results suggest that climate change poses a significant threat to the yellow-breasted bunting. Hunting bans alone are insufficient for the conservation and management of this species. Global efforts to curb warming are essential to mitigate the negative impacts of climate change on endangered species.


Key words: Emberiza aureola, endangered species, maximum entropy model, range contraction