集体学习模型确定了河流微生物群落在应对热浪时的适应分类和转折点
Qian Qu1, Jing Xu2, Weilu Kang1
1Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, China.
Global change biology
|October 17, 2023
概括
全球河流微生物群落因热浪而面临重大变化. 预计许多人将难以适应,这凸显了对生态系统管理策略的迫切需要.
科学领域:
- 环境微生物学环境微生物学
- 生态系统生态学的生态学.
- 气候变化影响气候变化的影响.
背景情况:
- 全球热浪对微生物种群和生态系统健康构成重大威胁.
- 河流微生物群落对极端高温事件的反应及其适应性极限仍然不太清楚.
- 了解这些反应对于管理脆弱的水生生态系统至关重要.
研究的目的:
- 为了研究微生物社区对河流脉冲温度升高的反应.
- 预测全球河流系统中微生物适应高温的潜力.
- 评估人类活动对热浪影响的影响,以颗粒物 (PM2.5) 表示.
主要方法:
- 为脉冲温度诱导的微生物反应开发了四种不同的模型.
- 整体机器学习模型的应用,以预测全球河流中的微生物适应.
- 分析二倍增长的颗粒物 (PM2.5) 排放对河流微生物适应的影响.
主要成果:
- 南美洲 (巴西,智利) 和东南亚 (越南) 河流中的微生物群落容易受到热浪干扰 (25-37°C).
- 全球约48.4%的河道测量站表现出快速应力不适应的趋势.
- 预计超过76.9%的这些站将超过热浪后的微生物适应值;如果PM2.5增加两倍,可能会使快速应激适应减少约13.7%.
结论:
- 河流微生物群落对热浪的反应各不相同,许多全球地点面临超过适应限度的风险.
- 颗粒物排放可能会影响河流微生物适应热应激的能力.
- 有效的生态系统管理策略对于保护敏感的河流系统免受升级的热浪事件至关重要.
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