Savadova-Ratkus Ksenija, Grendaitė Dalia, Karosienė Jūratė, Stonevičius Edvinas, Kasperovičienė Jūratė, Koreivienė Judita
Laboratory of Algology and Microbial Ecology, Nature Research Centre, Akademijos Str. 2, LT-08412, Vilnius, Lithuania.
Laboratory of Climate and Water Research, Nature Research Centre, Akademijos Str. 2, LT-08412, Vilnius, Lithuania; Hydrology and Climatology Department, Institute of Geosciences, Vilnius University, M. K. Čiurlionio 21, LT-03101, Vilnius, Lithuania.
Water Res. 2025 May 1;275:123138. doi: 10.1016/j.watres.2025.123138. Epub 2025 Jan 12.
Cyanobacterial blooms, driven by nutrient loading and temperature, pose significant ecological and economic challenges. This study employs a combined data-driven and trait-based modelling approach to predict changes in cyanobacterial communities in a mono- and a polydominant shallow temperate lakes under varying temperature and nutrient scenarios. Results of the AQUATOX simulation model for two aquatic systems suggest that a 2 °C temperature increase, consistent with Intergovernmental Panel on Climate Change's predictions, may influence cyanobacteria species composition and dominance, with trends indicating a possible shift favouring Nostocales over Oscillatoriales and Chroococcales. Temperature increases by 4 °C clearly promoted the dominance of Nostocales. Nutrient dynamics appear to influence community structure. In a nutrient-rich monodominant lake, temperature was the primary driver, while in a nutrient-limited polydominant lake, phosphorus availability influenced cyanobacteria species dominance. Combined warming and phosphorus alterations significantly affected cyanobacteria bloom intensity and duration, particularly enhancing Nostocales growth. The study highlights the complexity of cyanobacterial responses to climate change, emphasizing the need for more analysis and comprehensive models to predict harmful algal blooms (HABs) in freshwater ecosystems. While the findings suggest that temperature and nutrient availability may be critical drivers of cyanobacterial dominance, additional research across a broader range of systems is necessary.
由养分负荷和温度驱动的蓝藻水华带来了重大的生态和经济挑战。本研究采用数据驱动和基于特征的联合建模方法，预测在不同温度和养分情景下，一个单优势种和一个多优势种的温带浅水湖泊中蓝藻群落的变化。两个水生系统的AQUATOX模拟模型结果表明，与政府间气候变化专门委员会的预测一致，温度升高2°C可能会影响蓝藻的物种组成和优势度，趋势表明可能会出现有利于念珠藻目而非颤藻目和色球藻目的转变。温度升高4°C明显促进了念珠藻目的优势度。养分动态似乎会影响群落结构。在一个富营养的单优势种湖泊中，温度是主要驱动因素，而在一个营养受限的多优势种湖泊中，磷的可利用性影响蓝藻的物种优势度。温度升高和磷变化的综合作用显著影响了蓝藻水华的强度和持续时间，尤其促进了念珠藻目的生长。该研究突出了蓝藻对气候变化反应的复杂性，强调需要更多分析和综合模型来预测淡水生态系统中的有害藻华。虽然研究结果表明温度和养分可利用性可能是蓝藻优势度的关键驱动因素，但还需要在更广泛的系统中进行更多研究。
