Climate warming affects lake ecosystems both through its direct effect on the phenology of species and through the alteration of the physical and chemical environments, which in turn affect community composition. In deep lakes, stratification enhancement and mixing reduction have already been observed, leading to hypolimnetic anoxia and to the rise of cyanophytes. The increase in stability depends on the rise of air temperature due to global emissions of greenhouse gases (GHG). Primary production could then either increase with rising epilimnetic temperature and buoyancy or decrease as fewer nutrients are upwelled from deep layers. The prevailing outcome, as well as the quantitative and temporal dynamics of all climate-induced modifications, depend on the specific lake characteristics. Individual analyses are then needed, one-dimensional coupled hydrodynamic-ecological numerical models being suitable tools for such predictions. Here, we simulated with GLM-AED2 (General Lake Model – Aquatic EcoDynamics) the 2020-2085 dynamics of the oligomictic and oligotrophic deep subalpine Lake Maggiore (Italy/Switzerland), according to the Swiss Climate Change Scenarios CH2011. Multiple realisations were performed for each scenario with random meteorological series obtained from the Vector-Autoregressive Weather Generator (VG), highlighting the uncertainties related to meteorology. Increase and decrease of nutrient loads were also tested. Results show that anoxia would occur in the hypolimnion regardless of nutrient input reduction, unless global GHG emissions were immediately reduced. Total phytoplankton biomass would be weakly affected by climate change, strongly depending on nutrient input, yet water warming would cause cyanophytes to compete with diatoms. Therefore, the fate of Lake Maggiore would be tied to both global and local environmental policies.

气候变暖通过对物种物候的直接影响以及物理和化学环境的变化而影响湖泊生态系统，而物理和化学环境的变化又影响了社区的组成。在深湖中，已经观察到分层增强和混合减少，导致低铁性缺氧和蓝藻的生长。稳定性的提高取决于全球温室气体（GHG）排放导致的气温升高。然后，随着表层温度和浮力的升高，初级产量可能增加，或者随着深层营养物质的增加，初级产量可能下降。主要的结果以及所有气候引起的变化的定量和时间动态取决于特定的湖泊特征。然后需要进行个别分析，一维耦合的水动力-生态数值模型是进行此类预测的合适工具。在这里，根据瑞士气候变化方案CH2011，我们使用GLM-AED2（通用湖模型– Aquatic EcoDynamics）模拟了马格里热湖（意大利/瑞士）的低磷和低营养深亚高山湖2020-2085的动力学过程。从矢量自回归天气生成器（VG）获得的随机气象序列对每种情况进行了多种实现，突显了与气象有关的不确定性。还测试了营养负荷的增加和减少。结果表明，除非营养物质的输入减少，否则低营养素会发生缺氧，除非立即减少全球温室气体排放量。气候变化对浮游植物总生物量的影响很小，在很大程度上取决于养分的输入，但是水温升高会导致蓝藻与硅藻竞争。因此，马焦雷湖的命运将与全球和地方环境政策挂钩。