Phytoplankton characterization in a tropical tidal river impacted by a megacity: the case of the Saigon River (Southern Vietnam)

Abstract

The spatiotemporal variation of phytoplankton and their relationship with environmental variables were analysed in the Saigon River -a tropical river in Southern Vietnam. Two longitudinal pro les were conducted during dry and rainy season at 18 sampling sites covering more than 60 km long in the river.Besides, a bi-weekly monitoring conducted upstream, urban area (Ho Chi Minh City -HCMC) and downstream of Saigon River was organized from December 2016 to November 2017. The major phytoplankton were diatoms (e.g. Cyclotella cf. meneghiniana, Leptocylindrus danicus, Aulacoseira granulata), cyanobacteria (Microcystis spp., Raphidiopsis raciborskii, Pseudanabaena sp) and euglenoids (Trachelomonas volvocina). Commonly freshwater phytoplankton species and sometimes brackish water species were dominant during the monitoring. Phytoplankton abundances in dry season were much higher than in rainy season (> 100 times) which was explained by a shorter riverine water residence time and higher ushing capacity during the dry season. There was a clear separation of phytoplankton abundance between the urban area and the remaining area of Saigon River because of polluted urban emissions of HCMC. Redundancy analysis shows that the environmental variables (TOC, Nitrogen, pH, salinity, Mo, Mn) were the driving factors related to the dominance of L. danicus and Cyclotella cf. meneghiniana in the upstream river and urban section of Saigon River. The dominance of cyanobacterium Microcystis spp in the downstream of Saigon River was related to higher salinity, Mg, Cu concentrations and lower concentrations of nutrients, Mn, Co, Mo. The dominance of potentially toxic cyanobacteria in Saigon River possess health risk to local residents especially upon the increasing temperature context and nutrient loading into the river in the next decades.

Remotely sensed-based analysis about climatic and landscape change effects on phytoplankton bloom in Barra Bonita Reservoir (São Paulo State, Brazil)

“…Such behavior corroborates the findings of Lehman et al 81 . and Nguyen et al 82 . According to the authors, phytoplankton biomass is higher during the dry season than the wet season due to a better combination of water transparency, light, and nutrient.…”

“…42,45,79 Low precipitation that increases the euphotic zone due to the lower input of suspended matter is a probable cause of high primary production in BBHR in the dry season. 80 Such behavior corroborates the findings of Lehman et al 81 and Nguyen et al 82 According to the authors, phytoplankton biomass is higher during the dry season than the wet season due to a better combination of water transparency, light, and nutrient. In the current context of climate changes, the extreme drought events may amplify the occurrence of phytoplankton bloom, intensify the eutrophication process, and negatively influence the biodiversity and quality of freshwater ecosystems.…”

Phytoplankton Communities’ Response to Thermal Stratification and Changing Environmental Conditions in a Deep-Water Reservoir: Stochastic and Deterministic Processes

“…The absorption rate of NH 4 + -N by phytoplankton was greater than that of NO --N. When phytoplankton absorb and utilize NO --N, they need to consume energy to use NO 3 − reductase and NO 2 − reductase to reduce NO --N to NH 4 + -N, synthesize amino acids under the action of glutamyl ammonia synthetase, and, finally, synthesize cells through photosynthesis [69]. Additionally, phytoplankton could produce a large amount of organic matter through photosynthesis, which increases the COD Mn [70]. Therefore, a series of interactions contributed to the significant correlation between dominant phytoplankton species abundance and NH 4 + -N and COD Mn .…”

Innovative Design of Urban Domestic Waste Reverse Logistics Network from the Perspective of Ecological Civilization a Case Study of Hefei, China

“…This paper designs the fitness of the algorithm with the objective function of maximizing the product revenue of the recycling center and minimizing the operation cost of reverse logistics, which can more effectively weigh the optimization degree of individuals in the hybrid algorithm. In process of PSO algorithm and GA algorithm, set the fitness function as [36]: (22) Where: Z is the reverse logistics operation cost; W is the income of the recycling center.…”