Kd(PAR) and a Depth Based Model to Estimate the Height of Submerged Aquatic Vegetation in an Oligotrophic Reservoir: A Case Study at Nova Avanhandava

Submerged aquatic vegetation (SAV) carry out important biological functions in freshwater systems, however, uncontrolled growth can lead to many negative ecologic and economic impacts. Radiation availability is the primary limiting factor for SAV and it is a function of water transparency measured by Kd(PAR) (downwelling attenuation coefficient of Photosynthetically Active Radiation) and depth. The aim of this study was to develop a Kd(PAR) and depth based model to estimate the height of submerged aquatic vegetation in a tropical oligotrophic reservoir. This work proposed a new graphical model to represent the SAV height in relation to Kd(PAR) and depth. Based on the visual analysis of the model, it was possible to establish a set of Boolean rules to classify the SAV height and identify regions where SAV can grow with greater or lesser vigor. Kd(PAR) was estimated using a model based on satellite data. Overall, the occurrence and height of SAV were directly influenced by the Kd(PAR), depending on the depth. This study highlights the importance of optical parameters in examining the occurrence and status of SAV in Brazilian Reservoirs. It was concluded that the digital model and its graphical representation overcomes the limitations found by other researchers to understand the SAV behavior in relation to those independent variables: depth and Kd(PAR)

Estimating the Optical Properties of Inorganic Matter-Dominated Oligo-to-Mesotrophic Inland Waters

Many studies over the years have focused on bio-optical modeling of inland waters to monitor water quality. However, those studies have been conducted mainly in eutrophic and hyper-eutrophic environments dominated by phytoplankton. With the launch of the Ocean and Land Colour Instrument (OLCI)/Sentinel-3A in 2016, a range of bands became available including the 709 nm band recommended for scaling up these bio-optical models for productive inland waters. It was found that one category of existing bio-optical models, the quasi-analytical algorithms (QAAs), when applied to colored dissolved organic matter (CDOM) and detritus-dominated waters, produce large errors. Even after shifting the reference wavelength to 709 nm, the recently re-parameterized QAA versions could not accurately retrieve the inherent optical properties (IOPs) in waterbodies dominated by inorganic matter. In this study, three existing versions of QAA were implemented and proved inefficient for the study site. Therefore, several changes were incorporated into the QAA, starting with the re-parameterization of the empirical steps related to the total absorption coefficient retrieval. The re-parameterized QAA, QAAOMW showed a significant improvement in the mean absolute percentage error (MAPE). MAPE decreased from 58.05% for existing open ocean QAA (QAALv5) to 16.35% for QAAOMW. Considerable improvement was also observed in the estimation of the absorption coefficient of CDOM and detritus from a MAPE of 91.05% for QAALv5 to 18.87% for QAAOMW. The retrieval of the absorption coefficient of phytoplankton ( a ϕ ) using the native form of QAA proved to be inaccurate for the oligo-to-mesotrophic waterbody due to the low a ϕ returning negative predictions. Therefore, a novel approach based on the normalized a ϕ was adopted to maintain the spectral shape and retrieve positive values, resulting in an improvement of 119% in QAAOMW. Further tuning and scale-up of QAAOMW to OLCI bands will aid in monitoring water resources and associated watershed processes

Monosodium Glutamate (MSG) renders alkalinizing properties and Its urinary metabolic markers of MSG consumption in rats

Monosodium glutamate (MSG) is widely used as a flavor enhancer and its effects on human health are still debated. We aimed to investigate whether MSG can act as alkalinizing agent in murine models and if its metabolites are biomarkers of MSG consumption. For this purpose, adult male Wistar rats were given water added with 1 g% MSG or three types of control water, including sodium chloride (NaCl) and sodium bicarbonate (NaHCO3). At 14 days, urinary pH, electrolytes, urinary metabolites and ion-exchanger gene expression were determined. The results revealed that MSG-treated rats had significantly more alkaline urine and higher levels of urinary sodium and bicarbonate similar to NaHCO3 controls. These changes correlated with a lower expression of ion-exchanger genes, namely, CAII, NBC1, and AE1, which are involved in bicarbonate kidney reabsorption. The urinary metabolic profiles also revealed similar patterns for the MSG and NaHCO3 groups. In conclusion, MSG exhibits similar properties to NaHCO3, an alkalinizing agent, with regard to inducing alkaline urine, reducing bicarbonate kidney reabsorption, and generating a specific urinary metabolic pattern. We believe that these observations will be useful to further study the MSG effects in humans