Identifying the main drivers of change of phytoplankton community structure and gross primary productivity in a river-lake system
Identifying the main drivers of change of phytoplankton community structure and gross primary productivity in a river-lake system
复制标题
DOI：
10.1016/j.jhydrol.2020.124633
复制
发表时间：
2020-04-01
影响因子：
6.4
通讯作者：
Lu, Yao
中科院分区：
文献类型：
--
作者：
Jia, Junjie;Gao, Yang;Lu, Yao
河流湖泊系统的管理受到现有模型适用性的限制，这些模型描述了环境因素和浮游植物群落特征之间的关系，但很少包括对藻类动态的共同和间接影响。在这项研究中，我们假设光，水，温度，pH值和营养盐的相互作用，包括直接和间接的影响，是影响浮游植物动态的潜在因素。我们确定这些是主要的驱动因素，浮游植物群落结构和生产的河流湖泊系统，通过使用三种不同的模型的基础上偏最小二乘结构方程建模方法。我们的结果表明，这些模型对各种环境因子对浮游植物特征的总体解释力达到了60%以上，包括间接和直接影响。特别是，光照、pH、营养盐含量和比例共同控制着浮游植物的动态特征，而不是单一的营养盐，但光照是浮游植物群落特征的主要驱动力。控制水下光照条件和氮磷污染负荷，可以有效调控水华，提高生产力，促进生态平衡，减少水体污染。研究结果为水资源管理和污染控制提供了科学理论依据。
The management of river-lake systems is hindered by limitations in the applicability of existing models that describe the relationship between environmental factors and phytoplankton community characteristics but rarely include common and indirect effects on algae dynamics. In this study, we assumed that the interaction of light, water, temperature, pH, and nutrients, including direct and indirect effects, are the potential factors affecting phytoplankton dynamics. We determined which of these are the main drivers of phytoplankton community structure and production in a river-lake system by using three different models based on the partial least squares structural equation modeling method. Our results indicated that the models achieved more than 60% of the overall explanatory power of various environmental factors on phytoplankton characteristics, including indirect and direct effects. In particular, light, pH, and nutrient content and ratios commonly control phytoplankton dynamic characteristics rather than a single nutrient, but light is the main driving force of phytoplankton community characteristics. Controlling the underwater light conditions, and nitrogen and phosphorus pollution load could effectively regulate algal blooms, increase productivity, promote ecological balance, and reduce water pollution. Our findings provide a scientific and theoretical basis for water resource management and pollution control.