Characteristics of Phytoplankton Community Structure and Indication to Water Quality in the Lake in Agricultural Areas

Abstract

In recent years, lakes’ water quality and quantity have been affected and damaged by agricultural activities. The sensitivity of phytoplankton to the hydrological environment can effectively indicate the health of the aquatic ecosystem and the change in water quality. Understanding the changes of phytoplankton communities in lakes contaminated by agriculture may contribute to determining the directions of protection of these water bodies and provide reference cases for wider research. It is found that there are 146 species, 63 genera, and 8 phyla of phytoplankton, including 57 species of Bacillariophyta, 46 species of Chlorophyta, 17 species of Cyanobacteria and Euglenophyta. The total abundance was changed successively with Bacillariophyta (75% in June), Cyanobacteria (50% in July–August), and Chlorophyta (75% in September–October). The total biomass decreased continuously over time. The biomass of Chlorophyta is highest in October (67.4%), and diatoms contribute the most biomass in other months (76.5%). The Redundancy analysis indicated that the main environmental factors affecting phytoplankton’s dynamic change are total salt, water temperature, total phosphorus, and 5-day biochemical oxygen demand. The phytoplankton can be divided into 21 functional groups. The MP group has the highest frequency, mainly distributed in the frequently stirred and turbid shallow water. Representative functional groups indicate the high degree of eutrophication and nutrient-rich conditions and the good associated environment for phytoplankton and slow water flow rate. With the seasonal change of agricultural irrigation and drainage, the water quality of Xinmiao Lake began to deteriorate from medium pollution in July and reached serious pollution in October finally. Furthermore, this research discovered that the risk of cyanobacteria bloom is high in summer, primarily when thermal stratification occurs. This study provides necessary information for understanding and predicting the changes of the phytoplankton community caused by the increase of nutrients, human disturbance, and temperature conditions in eutrophic lakes in agricultural areas.

[RETRACTED] Short-term dynamics and growth parameters of cyanobacteria and microcystins in freshwater from the Sidi-Yacoub dam, North-east of Algeria

“…The dominance of cyanophyte species agrees with results obtained by other researchers from reservoirs located in Algeria and a neighboring country with close climatic conditions as in Marocco. Among these climatic conditions is the temperature which is considered the most important determinant of cyanobacteria growth and metabolism of microcystins (Lv et al 2014;Xue et al 2016;Pham et al 2017;Preece et al 2017;Huang et al 2022).…”

Effects of Sampling Time and Depth on Phytoplankton Metrics in Agricultural Irrigation Ponds

“…Since eutrophication increases the phytoplankton biomass that can be supported during an algal bloom [15] various metrics related to the amount of phytoplankton growth have been established as indicators of the overall water quality and trophic status in both fresh and marine aquatic environments [16][17][18][19]. Approaches to quantifying the presence of phytoplankton can be divided into two groups: cell abundance and photosynthetic pigment concentrations.…”

Water physicochemical characterization and phytoplankton diversity of arid region in Meggarine Lake, Ouargla, Algeria

“…Water quality is one of the factors that should be evaluated in coastal ecosystems since decreased water purity could be catastrophic for marine life (Riani et al 2014). Following Huang et al (2022), agricultural production activities have recently impacted and damaged the quantity and purity of the water in lakes. The health of the aquatic ecosystem and changes in water quality can be successfully detected by the phytoplankton's sensitivity to the hydrological environment.…”

“…Due to the great temporal and geographical heterogeneity of phytoplankton and environmental variables, their interactions are frequently complex and difficult to understand. For example, aspects of the lake, such as nutrition, light, temperature, etc., control the growth of algae (Huang et al 2022). Therefore, for this reason, the present work aimed to characterize the physicochemical parameters and identify the collected microalgae of Meggarine Lake.…”