Modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (Paraná River , Brazil)
The need for prediction is widely recognized in limnology. In this study, data from 25 lakes of the Upper Paraná River floodplain were used to build models to predict chlorophyll-a and dissolved oxygen concentrations. Akaike's information criterion (AIC) was used as a criterion for model select...
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doaj-c3f36c34899b43f4a104f15befe24f7f2020-11-24T23:23:53ZengInstituto Internacional de EcologiaBrazilian Journal of Biology1678-4375692 suppl49150010.1590/S1519-69842009000300005S1519-69842009000300005Modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (Paraná River , Brazil)RRA. Rocha0SM. Thomaz1P. Carvalho2LC. Gomes3Universidade Estadual de MaringáUniversidade Estadual de MaringáUniversidade Estadual de MaringáUniversidade Estadual de MaringáThe need for prediction is widely recognized in limnology. In this study, data from 25 lakes of the Upper Paraná River floodplain were used to build models to predict chlorophyll-a and dissolved oxygen concentrations. Akaike's information criterion (AIC) was used as a criterion for model selection. Models were validated with independent data obtained in the same lakes in 2001. Predictor variables that significantly explained chlorophyll-a concentration were pH, electrical conductivity, total seston (positive correlation) and nitrate (negative correlation). This model explained 52% of chlorophyll variability. Variables that significantly explained dissolved oxygen concentration were pH, lake area and nitrate (all positive correlations); water temperature and electrical conductivity were negatively correlated with oxygen. This model explained 54% of oxygen variability. Validation with independent data showed that both models had the potential to predict algal biomass and dissolved oxygen concentration in these lakes. These findings suggest that multiple regression models are valuable and practical tools for understanding the dynamics of ecosystems and that predictive limnology may still be considered a powerful approach in aquatic ecology.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842009000300005&lng=en&tlng=enmodelchlorophyll-aoxygenfloodplain lakes |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
RRA. Rocha SM. Thomaz P. Carvalho LC. Gomes |
spellingShingle |
RRA. Rocha SM. Thomaz P. Carvalho LC. Gomes Modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (Paraná River , Brazil) Brazilian Journal of Biology model chlorophyll-a oxygen floodplain lakes |
author_facet |
RRA. Rocha SM. Thomaz P. Carvalho LC. Gomes |
author_sort |
RRA. Rocha |
title |
Modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (Paraná River , Brazil) |
title_short |
Modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (Paraná River , Brazil) |
title_full |
Modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (Paraná River , Brazil) |
title_fullStr |
Modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (Paraná River , Brazil) |
title_full_unstemmed |
Modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (Paraná River , Brazil) |
title_sort |
modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (paraná river , brazil) |
publisher |
Instituto Internacional de Ecologia |
series |
Brazilian Journal of Biology |
issn |
1678-4375 |
description |
The need for prediction is widely recognized in limnology. In this study, data from 25 lakes of the Upper Paraná River floodplain were used to build models to predict chlorophyll-a and dissolved oxygen concentrations. Akaike's information criterion (AIC) was used as a criterion for model selection. Models were validated with independent data obtained in the same lakes in 2001. Predictor variables that significantly explained chlorophyll-a concentration were pH, electrical conductivity, total seston (positive correlation) and nitrate (negative correlation). This model explained 52% of chlorophyll variability. Variables that significantly explained dissolved oxygen concentration were pH, lake area and nitrate (all positive correlations); water temperature and electrical conductivity were negatively correlated with oxygen. This model explained 54% of oxygen variability. Validation with independent data showed that both models had the potential to predict algal biomass and dissolved oxygen concentration in these lakes. These findings suggest that multiple regression models are valuable and practical tools for understanding the dynamics of ecosystems and that predictive limnology may still be considered a powerful approach in aquatic ecology. |
topic |
model chlorophyll-a oxygen floodplain lakes |
url |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842009000300005&lng=en&tlng=en |
work_keys_str_mv |
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1725563018609164288 |