Predicting Phytoplankton Growth and Dynamics in Relation to Physico-chemical Characteristics of Water Body

Abstract

In recent times, frequency and severity of algal blooms has increased significantly. To control their expansion, it is essential to identify the factors responsible for blooming of waters. Nutrient overenrichment (mainly due to anthropogenic activities) and environmental factors (including the climate change) are considered the major catalyst for onset, proliferation, and development of blooms. A eutrophic subtropical water reservoir (Durgakund Pond, Varanasi) was sampled for 2 years (2000)(2001)(2002), and data were obtained on various physico-chemical factors such as temperature, dissolved oxygen, pH, phosphorus (PO 4 − and other P forms), nitrogen (NO 3 − , NO 2 − , and NH + 4 ), chloride, iron, and phytoplankton biomass in terms of chlorophyll a, total protein, and carbohydrate content. Linear regression models that developed indicated that phosphorous, nitrogen, and iron had maximal impact on phytoplankton growth. Physical factors, though vital, had an indirect effect in facilitating the interaction among various nutrients and their availability.

Simultaneous bioelectrochemical degradation of algae sludge and energy recovery in microbial fuel cells

“…The steady-state of the current lasted longer for A-AS, demonstrating that more substrate was available for electricity generation. The maximum power density was 226 mW m 22 for MFCs using R-AS at a current density of 0.6 A m 22 , and 311 mW m 22 for MFCs using A-AS at a current density of 0.86 A m 22 . The corresponding OCV was 709 mV (R-AS) and 763 mV (A-AS) (Fig.…”

“…8 The anode was ammonia gas-treated graphite brushes (4 cm in diameter 6 4 cm in length; fiber: T700-12 K, Toray Industries Co., Ltd.). 14 The cathode was carbon cloth (5 cm 6 5 cm) coated with 0.5 mg cm 22 of Pt (20 wt% Pt/ C, JM). The electrodes were connected to a 1 kV external resistor with copper wire.…”

“…16 The current in the circuit was determined by monitoring the voltage drop across a resistor (1 kV) using a data acquisition system (2700, Keithley Instruments Inc., USA) every 10 min. Power density, P (mW m 22 ), was obtained according to P = IV/ A, where A (m 2 ) is the projected surface area of the cathode (25 cm 2 ). The maximum power density was determined by varying the external resistance (between 50 V and 100 KV).…”

Support Vector Regression Model of Chlorophyll-<i>a</i> during Spring Algal Bloom in Xiangxi Bay of Three Gorges Reservoir, China

“…The concentration of chlorophyll-a in aquatic system depends on a number of variables including nutrients, light, temperature, physicochemical properties of the water mass [8] as well as interactions between these physical, chemical and biological compartments of the system. There are many study methods to the relationship between chlorophyll-a and environmental factors such as stepwise multiple linear regression (MLR) analysis [9][10][11][12] and artificial neural network (ANN) [13,14]. But the algal bloom is the multivariate interaction and nonlinear process.…”

Spatial and temporal variability of stable isotopes and biological parameters for the Danube River in Serbia

“…Component 2 captured 20% of the data's total variance and exhibits moderate positive loadings for a specific site (0.67) with TSS, VS, BOD, dominated by Cha (0.82), and a high-negative loading for o-P(−0.81). This component could be conditionally named the 'biological' factor since the phytoplankton biomass growth, measured by planktonic algal Cha, depends on the availability of phosphorus in the form of orthophosphate in a water body[35]. The third component covered 21% of the total variance and had high positive loadings (0.71-0.87) for EC, TH, and Ca and a high negative loading (−0.88) for temperature.…”