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全球湖泊中藻类繁殖对未来气候和土地利用变化的预测反应:机器学习方法

Jinge Ma¹, Hongtao Duan², Cheng Chen³

¹The National Key Laboratory of Water Disaster Prevention, Nanjing Hydraulic Research Institute, Nanjing 210029, China; Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; Center for Eco-Environmental Research, Nanjing Hydraulic Research Institute, Nanjing 210029, China.

|December 7, 2024

概括

预计到2100年,全球的湖藻类繁殖将恶化,特别是在非洲,亚洲和北美,在更高的社会经济发展情景下. 气候变化和人类活动可能会压倒水质控制工作.

科学领域:

环境科学环境科学
气候科学气候科学
临界技术临界技术

背景情况:

湖泊缩和藻类繁殖正在迫使全球环境问题.
全球变暖和人类活动对水质和藻类繁殖趋势造成了复杂的非线性影响.
由于数据稀缺,全球湖泊藻类繁殖的未来预测是不确定的.

研究的目的:

开发一个全球预测模型来预测未来的湖藻类繁殖趋势.
根据各种社会经济发展途径评估藻类繁殖的发生情况.
分析2020年至2100年的藻类开花的时空分布.

主要方法:

专注于161个大型自然湖泊 (>500平方公里).
采用机器学习模型,其中随机森林显示出最佳性能 (准确度:0.9697,卡帕:0.8721).
根据不同的共享社会经济路径 (SSP) 预测的趋势,包括SSP370和SSP585.

主要成果:

预计在更高的强迫场景 (SSP370,SSP585) 下,到本世纪末,藻类繁殖的数量和强度将增加.
繁花增加的地区包括非洲,亚洲和北美;欧洲显示下降趋势.
欠发达的地区,特别是非洲,对场景变化更为敏感.

结论:

由于气候变化和人类活动导致的藻类繁殖加剧,可能会抵消改善水质的努力.
这项研究提供了一个关于全球湖藻类繁殖的时空空间展望,突出了区域差异.
需要紧急,有针对性的缓解策略,特别是在脆弱地区.

关键词:

藻类开花预测的预测气候变化气候变化气候变化全球湖泊全球湖泊土地使用情况土地使用情况机器学习是机器学习.

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