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Laurentian Great Lakes phytoplankton and their water quality characteristics, including a diatom-based model for paleoreconstruction of phosphorus.

Reavie ED, Heathcote AJ, Shaw Chraïbi VL - PLoS ONE (2014)

Bottom Line: Further, TP was minimally confounded by other environmental variables, as indicated by the relatively large amount of unique variance in the diatoms explained by TP.We demonstrated the effectiveness of the transfer function by hindcasting TP concentrations using fossil diatom assemblages in a Lake Superior sediment core.The diatom-based transfer function can be used in lake management when retrospective data are needed for tracking long-term degradation, remediation and trajectories.

View Article: PubMed Central - PubMed

Affiliation: Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota Duluth, Duluth, Minnesota, United States of America.

ABSTRACT
Recent shifts in water quality and food web characteristics driven by anthropogenic impacts on the Laurentian Great Lakes warranted an examination of pelagic primary producers as tracers of environmental change. The distributions of the 263 common phytoplankton taxa were related to water quality variables to determine taxon-specific responses that may be useful in indicator models. A detailed checklist of taxa and their environmental optima are provided. Multivariate analyses indicated a strong relationship between total phosphorus (TP) and patterns in the diatom assemblages across the Great Lakes. Of the 118 common diatom taxa, 90 (76%) had a directional response along the TP gradient. We further evaluated a diatom-based transfer function for TP based on the weighted-average abundance of taxa, assuming unimodal distributions along the TP gradient. The r(2) between observed and inferred TP in the training dataset was 0.79. Substantial spatial and environmental autocorrelation within the training set of samples justified the need for further model validation. A randomization procedure indicated that the actual transfer function consistently performed better than functions based on reshuffled environmental data. Further, TP was minimally confounded by other environmental variables, as indicated by the relatively large amount of unique variance in the diatoms explained by TP. We demonstrated the effectiveness of the transfer function by hindcasting TP concentrations using fossil diatom assemblages in a Lake Superior sediment core. Passive, multivariate analysis of the fossil samples against the training set indicated that phosphorus was a strong determinant of historical diatom assemblages, verifying that the transfer function was suited to reconstruct past TP in Lake Superior. Collectively, these results showed that phytoplankton coefficients for water quality can be robust indicators of Great Lakes pelagic condition. The diatom-based transfer function can be used in lake management when retrospective data are needed for tracking long-term degradation, remediation and trajectories.

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Correlation matrix of Great Lakes water quality variables.Correlation matrix of Great Lakes water quality data, using Pearson product-moment correlation coefficients. Ellipses summarize positive or negative correlations, with narrower, darker ellipses indicating stronger correlations. Variable pairs containing an × were not significant (P = 0.05 with Bonferroni correction for multiple comparisons). All variables were transformed as necessary to minimize skew and approximate or achieve normality (Table 1). Scores from the first two axes of a principal components analysis are included to indicate important variables for these gradients.
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pone-0104705-g001: Correlation matrix of Great Lakes water quality variables.Correlation matrix of Great Lakes water quality data, using Pearson product-moment correlation coefficients. Ellipses summarize positive or negative correlations, with narrower, darker ellipses indicating stronger correlations. Variable pairs containing an × were not significant (P = 0.05 with Bonferroni correction for multiple comparisons). All variables were transformed as necessary to minimize skew and approximate or achieve normality (Table 1). Scores from the first two axes of a principal components analysis are included to indicate important variables for these gradients.

Mentions: Algal associations with 11 environmental variables (Table 1), collected simultaneously with phytoplankton, were explored. Additional variables were considered but were redundant (specific conductivity with chloride, beam attenuation with turbidity) or poorly represented in the dataset (dissolved oxygen, irradiance, total nitrogen). Geophysical variables (e.g., depth, latitude, longitude) were not used in multivariate analyses in order to better describe relationships with water quality, although the importance of “lake” as a nominal variable was explored in terms of species specificity. Collection and analysis of environmental data is described in detail in the USEPA (2010) standard operating procedures. Three additional molar ratio variables (N∶P, N∶Si, P∶Si) were calculated from other variables in the list so that they may be used in the evaluation of algal responses across nutrient ratio gradients. Because of substantial correlation among these variables (Figure 1), multivariate approaches were deemed necessary to determine species-environmental relationships.


Laurentian Great Lakes phytoplankton and their water quality characteristics, including a diatom-based model for paleoreconstruction of phosphorus.

Reavie ED, Heathcote AJ, Shaw Chraïbi VL - PLoS ONE (2014)

Correlation matrix of Great Lakes water quality variables.Correlation matrix of Great Lakes water quality data, using Pearson product-moment correlation coefficients. Ellipses summarize positive or negative correlations, with narrower, darker ellipses indicating stronger correlations. Variable pairs containing an × were not significant (P = 0.05 with Bonferroni correction for multiple comparisons). All variables were transformed as necessary to minimize skew and approximate or achieve normality (Table 1). Scores from the first two axes of a principal components analysis are included to indicate important variables for these gradients.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4126776&req=5

pone-0104705-g001: Correlation matrix of Great Lakes water quality variables.Correlation matrix of Great Lakes water quality data, using Pearson product-moment correlation coefficients. Ellipses summarize positive or negative correlations, with narrower, darker ellipses indicating stronger correlations. Variable pairs containing an × were not significant (P = 0.05 with Bonferroni correction for multiple comparisons). All variables were transformed as necessary to minimize skew and approximate or achieve normality (Table 1). Scores from the first two axes of a principal components analysis are included to indicate important variables for these gradients.
Mentions: Algal associations with 11 environmental variables (Table 1), collected simultaneously with phytoplankton, were explored. Additional variables were considered but were redundant (specific conductivity with chloride, beam attenuation with turbidity) or poorly represented in the dataset (dissolved oxygen, irradiance, total nitrogen). Geophysical variables (e.g., depth, latitude, longitude) were not used in multivariate analyses in order to better describe relationships with water quality, although the importance of “lake” as a nominal variable was explored in terms of species specificity. Collection and analysis of environmental data is described in detail in the USEPA (2010) standard operating procedures. Three additional molar ratio variables (N∶P, N∶Si, P∶Si) were calculated from other variables in the list so that they may be used in the evaluation of algal responses across nutrient ratio gradients. Because of substantial correlation among these variables (Figure 1), multivariate approaches were deemed necessary to determine species-environmental relationships.

Bottom Line: Further, TP was minimally confounded by other environmental variables, as indicated by the relatively large amount of unique variance in the diatoms explained by TP.We demonstrated the effectiveness of the transfer function by hindcasting TP concentrations using fossil diatom assemblages in a Lake Superior sediment core.The diatom-based transfer function can be used in lake management when retrospective data are needed for tracking long-term degradation, remediation and trajectories.

View Article: PubMed Central - PubMed

Affiliation: Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota Duluth, Duluth, Minnesota, United States of America.

ABSTRACT
Recent shifts in water quality and food web characteristics driven by anthropogenic impacts on the Laurentian Great Lakes warranted an examination of pelagic primary producers as tracers of environmental change. The distributions of the 263 common phytoplankton taxa were related to water quality variables to determine taxon-specific responses that may be useful in indicator models. A detailed checklist of taxa and their environmental optima are provided. Multivariate analyses indicated a strong relationship between total phosphorus (TP) and patterns in the diatom assemblages across the Great Lakes. Of the 118 common diatom taxa, 90 (76%) had a directional response along the TP gradient. We further evaluated a diatom-based transfer function for TP based on the weighted-average abundance of taxa, assuming unimodal distributions along the TP gradient. The r(2) between observed and inferred TP in the training dataset was 0.79. Substantial spatial and environmental autocorrelation within the training set of samples justified the need for further model validation. A randomization procedure indicated that the actual transfer function consistently performed better than functions based on reshuffled environmental data. Further, TP was minimally confounded by other environmental variables, as indicated by the relatively large amount of unique variance in the diatoms explained by TP. We demonstrated the effectiveness of the transfer function by hindcasting TP concentrations using fossil diatom assemblages in a Lake Superior sediment core. Passive, multivariate analysis of the fossil samples against the training set indicated that phosphorus was a strong determinant of historical diatom assemblages, verifying that the transfer function was suited to reconstruct past TP in Lake Superior. Collectively, these results showed that phytoplankton coefficients for water quality can be robust indicators of Great Lakes pelagic condition. The diatom-based transfer function can be used in lake management when retrospective data are needed for tracking long-term degradation, remediation and trajectories.

Show MeSH
Related in: MedlinePlus