标题： 多因素驱动的水生生态系统理论建模与定量研究 显示英文标题

标题： Theoretical modeling and quantitative research on aquatic ecosystems driven by multiple factors

摘要： 理解水温、营养物水平和叶绿素-a动态之间的复杂相互作用对于解决淡水生态系统中的富营养化和有害藻华的扩散至关重要。 然而，许多现有研究往往过于简化这些关系，常常忽视影响叶绿素-a生长的非线性效应和长期时间变化。 在此，我们进行了2020-2024年的多年现场监测，对广东省三个水体的关键环境因素进行了研究，包括总氮（TN）、总磷（TP）、水温和叶绿素-a：天堂山水库（S1）、白沙河水库（S2）和梅州水库（S3）。 基于收集的数据，我们开发了一个多因素相互作用模型，以定量评估叶绿素-a及其环境驱动因素的时空动态。 我们的研究揭示了叶绿素-a浓度显著的时间和空间变异，与TN、TP和水温呈强正相关。 S1和S2的长期数据表明富营养化有明显的上升趋势，其中TN在叶绿素-a的扩散中比TP更具影响力。 所开发的模型准确地再现了观测到的模式，为未来水生生态系统健康预测和管理导向的研究提供了坚实的理论基础。 显示英文摘要

摘要： Understanding the complex interactions between water temperature, nutrient levels, and chlorophyll-a dynamics is essential for addressing eutrophication and the proliferation of harmful algal blooms in freshwater ecosystems algal. However, many existing studies tend to oversimplify thse relationships often neglecting the non-linear effects and long-term temporal variations that influence chlorophyll-a growth. Here, we conducted multi-year field monitoring (2020-2024) of the key environmental factors, including total nitrogen (TN), total phosphorus (TP), water temperature, and chlorophyll-a, across three water bodies in Guangdong Province, China: Tiantangshan Reservoir(S1), Baisha River Reservoir(S2) and Meizhou Reservoir(S3). Based on the collected data, we developed a multi-factor interaction model to quantitatively assess the spatiotemporal dynamics of chlorophyll-a and its environmental drivers. Our research reveal significant temporal and spatial variability in chlorophyll-a concentrations, with strong positive correlations to TN, TP, and water temperature. Long-term data from S1 and S2 demonstrate a clear trend of increasing eutrophication, with TN emerging as a more influential factor than TP in chlorophyll-a proliferation. The developed model accurately reproduces observed patterns, offering a robust theoretical basis for future predictive and management-oriented studies of aquatic ecosystem health.