Abstract：
Heatwaves are a global issue that threaten microbial populations and deteriorate ecosystems. However, how river microbial communities respond to heatwaves and whether and how high temperatures exceed microbial adaptation remain unclear. In this study, we proposed four types of pulse temperature-induced microbial responses and predicted the possibility of microbial adaptation to high temperature in global rivers using ensemble machine learning models. Our findings suggest that microbial communities in parts of South American (e.g., Brazil and Chile) and Southeast Asian (e.g., Vietnam) countries are likely to change due to heatwave disturbance from 25 to 37°C for consecutive days. Furthermore, the microbial communities in approximately 48.4% of the global river gauge stations are prone to fast stress inadaptation, with approximately 76.9% of these stations expected to exceed microbial adaptation after heatwave disturbances. If emissions of particulate matter with sizes not more than 2.5 μm (PM2.5, an indicator of human activities) increase by twofold, the number of global rivers associated with the fast stress adaptation type will decrease by ~13.7% after heatwave disturbances. Understanding microbial responses is crucially important for effective ecosystem management, especially for fragile and sensitive rivers facing heatwave events.
摘要：
热浪是威胁微生物种群和恶化生态系统的全球性问题。然而,河流微生物群落对热浪的反应以及高温是否以及如何超过微生物的适应性仍不清楚。在这项研究中,我们提出了四种类型的脉冲温度诱导的微生物反应，并预测了微生物适应全球河流高温的可能性使用集成机器学习模型。我们的研究结果表明，南美部分地区的微生物群落(例如，巴西和智利)和东南亚(例如，越南）由于连续几天从25到37°C的热浪扰动，国家可能会发生变化。此外，大约48.4%的全球河流测站的微生物群落容易快速适应压力，在热浪干扰后，这些站点中约有76.9％的站点有望超过微生物的适应性。如果尺寸不超过2.5μm的颗粒物（PM2.5，人类活动指标）的排放量增加两倍，热浪扰动后，与快速应力适应类型相关的全球河流数量将减少约13.7%。了解微生物反应对于有效的生态系统管理至关重要，特别是对于面对热浪事件的脆弱和敏感的河流。
