Algal Pigment Estimation Models to Assess Bloom Toxicity in a South American Lake

In this study, we build an empirical model to estimate pigments in the South American Lake Villarrica. We use data from Dirección General de Aguas de Chile during the period of 1989–2024 to analyze the behavior of limnological parameters and trophic condition in the lake. Four seasonal linear regres...

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Veröffentlicht in:Water (Basel) 2024-12, Vol.16 (24), p.3708
Hauptverfasser: Rodríguez-López, Lien, Bustos Usta, David Francisco, Bravo Alvarez, Lisandra, Duran-Llacer, Iongel, Bourrel, Luc, Frappart, Frederic, Cardenas, Rolando, Urrutia, Roberto
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container_issue 24
container_start_page 3708
container_title Water (Basel)
container_volume 16
creator Rodríguez-López, Lien
Bustos Usta, David Francisco
Bravo Alvarez, Lisandra
Duran-Llacer, Iongel
Bourrel, Luc
Frappart, Frederic
Cardenas, Rolando
Urrutia, Roberto
description In this study, we build an empirical model to estimate pigments in the South American Lake Villarrica. We use data from Dirección General de Aguas de Chile during the period of 1989–2024 to analyze the behavior of limnological parameters and trophic condition in the lake. Four seasonal linear regression models were developed by us, using a set of water quality variables that explain the values of phycocyanin pigment in Lake Villarrica. In the first case, we related chlorophyll-a (Chl-a) to phycocyanin, expecting to find a direct relationship between both variables, but this was not fulfilled for all seasons of the year. In the second case, in addition to Chl-a, we included water temperature, since this parameter has a great influence on the algal photosynthesis process, and we obtained better results. We discovered a typical seasonal variability given by temperature fluctuations in Lake Villarrica, where in the spring, summer, and autumn seasons, conditions are favorable for algal blooms, while in winter, the natural seasonal conditions do not allow increases in algal productivity. For a third case, we included the turbidity variable along with the variables mentioned above and the statistical performance metrics of the models improved significantly, obtaining R2 values of up to 0.90 in the case of the model for the fall season and a mean squared error (MSE) of 0.04 µg/L. In the last case used, we added the variable dissolved organic matter (MOD), and the models showed a slight improvement in their performance. These models may be applicable to other lakes with harmful algal blooms in order to alert the community to the potential toxicity of these events.
doi_str_mv 10.3390/w16243708
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We use data from Dirección General de Aguas de Chile during the period of 1989–2024 to analyze the behavior of limnological parameters and trophic condition in the lake. Four seasonal linear regression models were developed by us, using a set of water quality variables that explain the values of phycocyanin pigment in Lake Villarrica. In the first case, we related chlorophyll-a (Chl-a) to phycocyanin, expecting to find a direct relationship between both variables, but this was not fulfilled for all seasons of the year. In the second case, in addition to Chl-a, we included water temperature, since this parameter has a great influence on the algal photosynthesis process, and we obtained better results. We discovered a typical seasonal variability given by temperature fluctuations in Lake Villarrica, where in the spring, summer, and autumn seasons, conditions are favorable for algal blooms, while in winter, the natural seasonal conditions do not allow increases in algal productivity. For a third case, we included the turbidity variable along with the variables mentioned above and the statistical performance metrics of the models improved significantly, obtaining R2 values of up to 0.90 in the case of the model for the fall season and a mean squared error (MSE) of 0.04 µg/L. In the last case used, we added the variable dissolved organic matter (MOD), and the models showed a slight improvement in their performance. These models may be applicable to other lakes with harmful algal blooms in order to alert the community to the potential toxicity of these events.</description><identifier>ISSN: 2073-4441</identifier><identifier>EISSN: 2073-4441</identifier><identifier>DOI: 10.3390/w16243708</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Algae ; Aquatic ecosystems ; Chlorophyll ; Comparative analysis ; Data integrity ; Distribution ; Environmental aspects ; Environmental Sciences ; Identification and classification ; Lakes ; Linear models (Statistics) ; Linear regression models ; Measurement ; Pigments ; Plant pigments ; Testing ; Variables ; Vegetation ; Water bloom ; Water quality ; Water temperature</subject><ispartof>Water (Basel), 2024-12, Vol.16 (24), p.3708</ispartof><rights>COPYRIGHT 2024 MDPI AG</rights><rights>2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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We use data from Dirección General de Aguas de Chile during the period of 1989–2024 to analyze the behavior of limnological parameters and trophic condition in the lake. Four seasonal linear regression models were developed by us, using a set of water quality variables that explain the values of phycocyanin pigment in Lake Villarrica. In the first case, we related chlorophyll-a (Chl-a) to phycocyanin, expecting to find a direct relationship between both variables, but this was not fulfilled for all seasons of the year. In the second case, in addition to Chl-a, we included water temperature, since this parameter has a great influence on the algal photosynthesis process, and we obtained better results. We discovered a typical seasonal variability given by temperature fluctuations in Lake Villarrica, where in the spring, summer, and autumn seasons, conditions are favorable for algal blooms, while in winter, the natural seasonal conditions do not allow increases in algal productivity. 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source MDPI - Multidisciplinary Digital Publishing Institute; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
subjects Algae
Aquatic ecosystems
Chlorophyll
Comparative analysis
Data integrity
Distribution
Environmental aspects
Environmental Sciences
Identification and classification
Lakes
Linear models (Statistics)
Linear regression models
Measurement
Pigments
Plant pigments
Testing
Variables
Vegetation
Water bloom
Water quality
Water temperature
title Algal Pigment Estimation Models to Assess Bloom Toxicity in a South American Lake
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