Department of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, Kiel, Germany; UK Centre for Ecology and Hydrology, Wallingford, United Kingdom.
Department of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, Kiel, Germany; Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, China.
Sci Total Environ. 2022 Dec 10;851(Pt 2):158209. doi: 10.1016/j.scitotenv.2022.158209. Epub 2022 Aug 29.
Given the many threats to freshwater biodiversity, we need to be able to resolve which of the multiple stressors present in rivers are most important in driving change. Phytoplankton are a key component of the aquatic ecosystem, their abundance, species richness and functional richness are important indicators of ecosystem health. In this study, spatial variables, physiochemical conditions, water flow alterations and land use patterns were considered as the joint stressors from a lowland rural catchment. A modeling approach combining an ecohydrological model with machine learning was applied. The results implied that land use and flow regime, rather than nutrients, were most important in explaining differences in the phytoplankton community. In particular, the percentage of water body area and medium level residential urban area were key to driving the rising phytoplankton abundance in this rural catchment. The proportion of forest and pasture area were the leading factors controlling the variations of species richness. In this case deciduous forest cover affected the species richness in a positive way, while, pasture share had a negative effect. Indicators of hydrological alteration were found to be the best predictors for the differences in functional richness. This integrated model framework was found to be suitable for analysis of complex environmental conditions in river basin management. A key message would be the significance of forest area preservation and ecohydrological restoration in maintaining both phytoplankton richness and their functional role in river ecosystems.
鉴于淡水生物多样性面临着诸多威胁，我们需要能够确定河流中存在的多种胁迫因素中，哪些因素对驱动变化最为重要。浮游植物是水生生态系统的关键组成部分，其丰度、物种丰富度和功能丰富度是生态系统健康的重要指标。在本研究中，空间变量、理化条件、水流变化和土地利用模式被视为来自低地农村流域的联合胁迫因素。应用了一种将生态水文学模型与机器学习相结合的建模方法。结果表明，土地利用和水流状况，而不是养分，对解释浮游植物群落差异最为重要。特别是水体面积百分比和中等级别居住市区面积是推动该农村流域浮游植物丰度上升的关键因素。森林和牧场面积的比例是控制物种丰富度变化的主要因素。在这种情况下，落叶林覆盖对物种丰富度有积极影响，而牧场比例则有负面影响。水文变化指标被发现是功能丰富度差异的最佳预测指标。该综合模型框架被证明适用于分析流域管理中复杂的环境条件。一个关键信息是森林面积保护和生态水文学恢复对于维持浮游植物丰富度及其在河流生态系统中的功能作用的重要性。
