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Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores
This study aimed to identify the key factors influencing the phytoplankton development in four lakes on the island of São Miguel (Azores). We used a multivariate analysis of biological parameters (phytoplankton), physicochemical parameters, and meteorological data. Data were collected between 2003 and 2018 in the volcanic Lakes of Sete Cidades (Green and Blue), Fogo, and Furnas. The ecosystems of these bodies of water are increasingly vulnerable to anthropogenic activities (increasing human pressure) as well as to changing climate patterns. This analysis is the first exploratory approach to this dataset to explore trends and patterns of evolution from a multivariate perspective. This approach is also intended to improve understanding of the conditions that favor the emergence of different Cyanobacterial divisions. For this purpose, several statistical and chemometric methods were used, such as analysis of variance (ANOVA) and principal component analysis (PCA). Multivariate models combining biological and meteorological data focused from 2010 to 2012. The results from the PCA models showed that the abundance of Bacillariophyta, Dinophyta, and Cryptophyta phyla are correlated and appear to be influenced by high levels of precipitation, evaporation, and wind speed. On the other hand, the Cyanophyta, Chlorophyta, and Chrysophyta phyla appear to be more correlated with high values of air temperature, water temperature, and radiation. Also, the Euglenophyta phylum appears to be associated with low levels of precipitation, evaporation and wind speed, and high temperatures. Finally, we can conclude that these lakes have endured physicochemical parameters over the past 15 years, meaning that the measures adopted to monitor and protect the lakes are effective.
Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores
This study aimed to identify the key factors influencing the phytoplankton development in four lakes on the island of São Miguel (Azores). We used a multivariate analysis of biological parameters (phytoplankton), physicochemical parameters, and meteorological data. Data were collected between 2003 and 2018 in the volcanic Lakes of Sete Cidades (Green and Blue), Fogo, and Furnas. The ecosystems of these bodies of water are increasingly vulnerable to anthropogenic activities (increasing human pressure) as well as to changing climate patterns. This analysis is the first exploratory approach to this dataset to explore trends and patterns of evolution from a multivariate perspective. This approach is also intended to improve understanding of the conditions that favor the emergence of different Cyanobacterial divisions. For this purpose, several statistical and chemometric methods were used, such as analysis of variance (ANOVA) and principal component analysis (PCA). Multivariate models combining biological and meteorological data focused from 2010 to 2012. The results from the PCA models showed that the abundance of Bacillariophyta, Dinophyta, and Cryptophyta phyla are correlated and appear to be influenced by high levels of precipitation, evaporation, and wind speed. On the other hand, the Cyanophyta, Chlorophyta, and Chrysophyta phyla appear to be more correlated with high values of air temperature, water temperature, and radiation. Also, the Euglenophyta phylum appears to be associated with low levels of precipitation, evaporation and wind speed, and high temperatures. Finally, we can conclude that these lakes have endured physicochemical parameters over the past 15 years, meaning that the measures adopted to monitor and protect the lakes are effective.
Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores
João Lopes (author) / Afonso Silva Pinto (author) / Telmo Eleutério (author) / Maria Gabriela Meirelles (author) / Helena Cristina Vasconcelos (author)
2022
Article (Journal)
Electronic Resource
Unknown
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