scholarly journals Mediterranean rivers: Consequences of water scarcity on benthic algal chlorophyll a content

2016 ◽  
Vol 76 (s1) ◽  
Author(s):  
Elena Piano ◽  
Elisa Falasco ◽  
Francesca Bona
Keyword(s):  
Chlorophyll A ◽  
Green Algae ◽  
Water Scarcity ◽  
Trophic Chain ◽  
Environmental Predictors ◽  
Mediterranean Rivers ◽  
Drought Period ◽  
Ligurian Alps ◽  
Algal Groups ◽  
Chlorophyll A Content

Mediterranean rivers are subjected to strong seasonality with drought during the hot season and extreme flows in autumn-winter. In particular, drought episodes and water scarcity alter the river morphology, with repercussions on primary production and the trophic chain. In this paper, we aimed at analysing the different responses in terms of chlorophyll a content of the three main photosynthetic groups composing stream periphyton, namely diatoms, cyanobacteria and green algae. This work was conducted in the Ligurian Alps (NW-Italy) on five oligotrophic streams (Argentina, Impero, Merula, Quiliano and Vallecrosia), similar in terms of physico-chemical parameters. We measured chlorophyll a content of diatoms, cyanobacteria and green algae by means of an in situ fluorimetric probe (BenthoTorch®). Data were collected from April to October 2014 in: i) impacted sites, where the water scarcity was exacerbated by human pressure; ii) control sites. We applied Generalized Linear Mixed Models to investigate the response of total chlorophyll a and its relative proportions among the three algal groups in relation to the following environmental predictors: water depth, flow velocity, canopy shading, microhabitat isolation, sampling season, dissolved oxygen, temperature, pH, nutrients, and macrophyte coverage.Results showed an opposite response of diatoms and green algae. Diatoms were favoured in the control sites and under moderate flow conditions, while the probability of green algae presence was higher in the impacted sites and during the drought season. Cyanobacteria showed a response similar to green algae, preferring warm, isolated pools typical of the drought period. Diatoms proved to be the most sensitive to drought. More specifically, we found out that percentages of diatoms below 51% with respect to total benthic chlorophyll a indicate high hydrological disturbance. This study provides the first evidence that the proportion of chlorophyll a produced by diatoms can be a suitable indicator for monitoring programs aiming at determining the effects of water scarcity on river ecosystems.

Estimation of Algal Succession in Lake Water Using HPLC Analysis of Pigments

1993 ◽  
Vol 50 (6) ◽  
pp. 1142-1146 ◽  
Author(s):  
Yuko Soma ◽  
Takashi Imaizumi ◽  
Kei-ichi Yagi ◽  
Sei-ichi Kasuga
Keyword(s):  
Seasonal Variation ◽  
Chlorophyll A ◽  
Green Algae ◽  
Lake Water ◽  
Algal Biomass ◽  
Hplc Analysis ◽  
Total Chlorophyll ◽  
Pigment Analysis ◽  
Algal Succession ◽  
Chlorophyll A Content

Seasonal variation in algal biomass in lake water was estimated using HPLC analysis of pigments. Carotenoids/chlorophyll a ratios were determined for cultures of Anabena, Microcystis, green algae, diatoms, and Cryptomonas. The contributions of various algal taxa to the total chlorophyll a content of lake water were calculated using the average carotenoid/chlorophyll a ratios of fingerprint pigments. The pigment analysis reflected the observed trend in the numbers of algae in lake water and proved to be a useful supplementary approach to evaluate algal biomass.

On the Question of the Chlorophyll a Content of the Photosystem II Reaction Center

1994 ◽  
Vol 98 (31) ◽  
pp. 7725-7735 ◽  
Author(s):  
H.-C. Chang ◽  
R. Jankowiak ◽  
N. R. S. Reddy ◽  
C. F. Yocum ◽  
R. Picorel ◽  
...  
Keyword(s):  
Photosystem Ii ◽  
Chlorophyll A ◽  
Reaction Center ◽  
Chlorophyll A Content

scholarly journals Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae and Turbidity

2018 ◽  
Vol 15 (9) ◽  
pp. 1881 ◽  
Author(s):  
Sina Keller ◽  
Philipp Maier ◽  
Felix Riese ◽  
Stefan Norra ◽  
Andreas Holbach ◽  
...  
Keyword(s):  
Machine Learning ◽  
Water Quality ◽  
Chlorophyll A ◽  
Green Algae ◽  
Hyperspectral Data ◽  
Coefficient Of Determination ◽  
Inland Waters ◽  
Learning Approaches ◽  
River Elbe ◽  
Regression Framework

Inland waters are of great importance for scientists as well as authorities since they are essential ecosystems and well known for their biodiversity. When monitoring their respective water quality, in situ measurements of water quality parameters are spatially limited, costly and time-consuming. In this paper, we propose a combination of hyperspectral data and machine learning methods to estimate and therefore to monitor different parameters for water quality. In contrast to commonly-applied techniques such as band ratios, this approach is data-driven and does not rely on any domain knowledge. We focus on CDOM, chlorophyll a and turbidity as well as the concentrations of the two algae types, diatoms and green algae. In order to investigate the potential of our proposal, we rely on measured data, which we sampled with three different sensors on the river Elbe in Germany from 24 June–12 July 2017. The measurement setup with two probe sensors and a hyperspectral sensor is described in detail. To estimate the five mentioned variables, we present an appropriate regression framework involving ten machine learning models and two preprocessing methods. This allows the regression performance of each model and variable to be evaluated. The best performing model for each variable results in a coefficient of determination R 2 in the range of 89.9% to 94.6%. That clearly reveals the potential of the machine learning approaches with hyperspectral data. In further investigations, we focus on the generalization of the regression framework to prepare its application to different types of inland waters.

Extraction and quantification of chlorophyll a from freshwater green algae

1998 ◽  
Vol 32 (7) ◽  
pp. 2220-2223 ◽  
Author(s):  
David Simon ◽  
Stuart Helliwell
Keyword(s):  
Chlorophyll A ◽  
Green Algae

scholarly journals The Epiphytic FernElaphoglossum luridum(Fée) Christ. (Dryopteridaceae) from Central and South America: Morphological and Physiological Responses to Water Stress

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Bruno Degaspari Minardi ◽  
Ana Paula Lorenzen Voytena ◽  
Marisa Santos ◽  
Áurea Maria Randi
Keyword(s):  
Water Stress ◽  
Water Deficit ◽  
Chlorophyll A ◽  
Tca Cycle ◽  
Photosynthetic Parameters ◽  
Relative Water ◽  
Physiological Studies ◽  
Cycle Regulation ◽  
Epiphytic Fern ◽  
Chlorophyll A Content

Elaphoglossum luridum(Fée) Christ. (Dryopteridaceae) is an epiphytic fern of the Atlantic Forest (Brazil). Anatomical and physiological studies were conducted to understand how this plant responds to water stress. TheE. luridumfrond is coriaceus and succulent, presenting trichomes, relatively thick cuticle, and sinuous cell walls in both abaxial and adaxial epidermis. Three treatments were analyzed: control, water deficit, and abscisic acid (ABA). Physiological studies were conducted through analysis of relative water content (RWC), photosynthetic pigments, chlorophyll a fluorescence, and malate content. No changes in RWC were observed among treatments; however, significant decreases in chlorophyll a content and photosynthetic parameters, including optimal irradiance (Iopt) and maximum electron transport rate (ETRmax), were determined by rapid light curves (RLC). No evidence of crassulacean acid metabolism (CAM) pathway was observed inE. luridumin response to either water deficit or exogenous application of ABA. On the other hand, malate content decreased in theE. luridumfrond after ABA treatment, seeming to downregulate malate metabolism at night, possibly through tricarboxylic acid (TCA) cycle regulation.

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