Coastal geomorphic and lake variability in the Laurentian Great Lakes: Implications for a diatom-based monitoring tool

Amy R. Kireta; Euan D Reavie; Nicholas P. Danz; Richard P Axler; Gerald V. Sgro; John C. Kingston; Terry N Brown; Tom Hollenhorst

doi:10.3394/0380-1330(2007)33[136:cgalvi]2.0.co;2

Coastal geomorphic and lake variability in the Laurentian Great Lakes: Implications for a diatom-based monitoring tool

Amy R. Kireta, Euan D Reavie, Nicholas P. Danz, Richard P Axler, Gerald V. Sgro, John C. Kingston, Terry N Brown, Tom Hollenhorst

Natural Resources Research Institute

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

In an evaluation of diatoms as indicators of human disturbance in coastal ecosystems of the Laurentian Great Lakes, we characterized assemblage specificity to lake and habitat type to identify non-anthropogenic factors influencing indicator models. Surface sediment assemblages and environmental variables were collected along the U.S. coastline at 191 sample sites, which were classified by lake and geomorphic type: high-energy (HE), embayment (EB), coastal wetland (CW), riverine wetland (RW), protected wetland (PW), and open water (OP). Diatom inferred (DI) total phosphorus (TP) transfer functions (models) were developed for each lake and geomorphic type. Robust models included: the overall model (RMSEP; r²_jack = 0.65; RMSEP = 0.005), Lake Superior (r²_jack = 0.73; RMSEP = 0.003), Lake Ontario (r²_jack = 0.73; RMSEP = 0.007), PW (r ²_jack = 0.64; RMSEP = 0.003), and EB (r² _jack = 0.64; RMSEP = 0.007). Weaker models, indicating poorer diatom-TP relationships, included: RW (r²_jack = 0.03; RMSEP = 0.005), OP (r²_jack = 0.15; RMSEP = 0.059), and Lake Michigan (r²_jack = 0.38; RMSEP = 0.006). DI TP data were regressed against landscape characteristics to quantify the relationships to adjacent watershed stressors. RW data were further scrutinized as a case study to investigate the suitability of diatom-based approaches in systems with poor diatom-TP relationships. Despite poor performance of the RW model, DI phosphorus data for riverine wetlands, derived from the overall model, were strongly related to watershed characteristics (r² = 0.61), indicating the overall model's ability to integrate stressors from the surrounding watershed in areas where measured phosphorus did not adequately characterize prevailing conditions. This study confirms that physical properties (e.g., lake or habitat type) can influence indicator models; however, weaknesses may be overcome by robust calibration techniques.

Original language	English (US)
Pages (from-to)	136-153
Number of pages	18
Journal	Journal of Great Lakes Research
Volume	33
Issue number	SPEC. ISS. 3
DOIs	https://doi.org/10.3394/0380-1330(2007)33[136:cgalvi]2.0.co;2
State	Published - 2007

Bibliographical note

Funding Information:
This paper is dedicated to the memory of John C. Kingston. We are grateful to the many GLEI and U.S. EPA researchers who were responsible for field sampling and data analysis including J. Hen-neck, instrumental in pilot work and early project logistics, as was J. Reed, J. Ameel who performed much of the water chemistry analyses, and L. Anderson (EPA-MED) who performed the DOC analyses. We thank others at the EPA-MED lab including J. Thompson, and J. Morrice, for constructive discussions and J. Kelly and P. Yurista also for collecting open-water data. Critical project review was provided by R. Kreis, S. Dixit, and E.F. Stoermer, who, along with J. Johansen, provided taxonomic expertise. N.A. Andresen also provided diatom taxonomic expertise and enumeration, as did M. Fer-guson. We are grateful to V. Brady for project coordination and sampling design assistance. We are also grateful for the helpful recommendations to the manuscript provided by two anonymous reviewers and J. Kelly. A special thanks to the numerous students and assistants who dedicated many long days to field collections and sample processing and to Great Lake homeowners who let us use their properties to set up for collections. This research was supported by a grant to G. Niemi from the U.S. EPA’s Science to Achieve Results Estuarine and Great Lakes program through funding to the Great Lakes Environmental Indicators project, U.S. EPA Agreement EPA/R-8286750. This document has not been subjected to the agency’s required peer and policy review and therefore does not necessarily reflect the view of the agency, and no official endorsement should be inferred. This is contribution number 462 of the Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota Duluth.

Keywords

Diatoms
Great Lakes environmental indicators
Habitat
Nearshore
Phosphorus
Transfer functions

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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abstract = "In an evaluation of diatoms as indicators of human disturbance in coastal ecosystems of the Laurentian Great Lakes, we characterized assemblage specificity to lake and habitat type to identify non-anthropogenic factors influencing indicator models. Surface sediment assemblages and environmental variables were collected along the U.S. coastline at 191 sample sites, which were classified by lake and geomorphic type: high-energy (HE), embayment (EB), coastal wetland (CW), riverine wetland (RW), protected wetland (PW), and open water (OP). Diatom inferred (DI) total phosphorus (TP) transfer functions (models) were developed for each lake and geomorphic type. Robust models included: the overall model (RMSEP; r2jack = 0.65; RMSEP = 0.005), Lake Superior (r2jack = 0.73; RMSEP = 0.003), Lake Ontario (r2jack = 0.73; RMSEP = 0.007), PW (r 2jack = 0.64; RMSEP = 0.003), and EB (r2 jack = 0.64; RMSEP = 0.007). Weaker models, indicating poorer diatom-TP relationships, included: RW (r2jack = 0.03; RMSEP = 0.005), OP (r2jack = 0.15; RMSEP = 0.059), and Lake Michigan (r2jack = 0.38; RMSEP = 0.006). DI TP data were regressed against landscape characteristics to quantify the relationships to adjacent watershed stressors. RW data were further scrutinized as a case study to investigate the suitability of diatom-based approaches in systems with poor diatom-TP relationships. Despite poor performance of the RW model, DI phosphorus data for riverine wetlands, derived from the overall model, were strongly related to watershed characteristics (r2 = 0.61), indicating the overall model's ability to integrate stressors from the surrounding watershed in areas where measured phosphorus did not adequately characterize prevailing conditions. This study confirms that physical properties (e.g., lake or habitat type) can influence indicator models; however, weaknesses may be overcome by robust calibration techniques.",

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note = "Funding Information: This paper is dedicated to the memory of John C. Kingston. We are grateful to the many GLEI and U.S. EPA researchers who were responsible for field sampling and data analysis including J. Hen-neck, instrumental in pilot work and early project logistics, as was J. Reed, J. Ameel who performed much of the water chemistry analyses, and L. Anderson (EPA-MED) who performed the DOC analyses. We thank others at the EPA-MED lab including J. Thompson, and J. Morrice, for constructive discussions and J. Kelly and P. Yurista also for collecting open-water data. Critical project review was provided by R. Kreis, S. Dixit, and E.F. Stoermer, who, along with J. Johansen, provided taxonomic expertise. N.A. Andresen also provided diatom taxonomic expertise and enumeration, as did M. Fer-guson. We are grateful to V. Brady for project coordination and sampling design assistance. We are also grateful for the helpful recommendations to the manuscript provided by two anonymous reviewers and J. Kelly. A special thanks to the numerous students and assistants who dedicated many long days to field collections and sample processing and to Great Lake homeowners who let us use their properties to set up for collections. This research was supported by a grant to G. Niemi from the U.S. EPA{\textquoteright}s Science to Achieve Results Estuarine and Great Lakes program through funding to the Great Lakes Environmental Indicators project, U.S. EPA Agreement EPA/R-8286750. This document has not been subjected to the agency{\textquoteright}s required peer and policy review and therefore does not necessarily reflect the view of the agency, and no official endorsement should be inferred. This is contribution number 462 of the Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota Duluth.",

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N1 - Funding Information: This paper is dedicated to the memory of John C. Kingston. We are grateful to the many GLEI and U.S. EPA researchers who were responsible for field sampling and data analysis including J. Hen-neck, instrumental in pilot work and early project logistics, as was J. Reed, J. Ameel who performed much of the water chemistry analyses, and L. Anderson (EPA-MED) who performed the DOC analyses. We thank others at the EPA-MED lab including J. Thompson, and J. Morrice, for constructive discussions and J. Kelly and P. Yurista also for collecting open-water data. Critical project review was provided by R. Kreis, S. Dixit, and E.F. Stoermer, who, along with J. Johansen, provided taxonomic expertise. N.A. Andresen also provided diatom taxonomic expertise and enumeration, as did M. Fer-guson. We are grateful to V. Brady for project coordination and sampling design assistance. We are also grateful for the helpful recommendations to the manuscript provided by two anonymous reviewers and J. Kelly. A special thanks to the numerous students and assistants who dedicated many long days to field collections and sample processing and to Great Lake homeowners who let us use their properties to set up for collections. This research was supported by a grant to G. Niemi from the U.S. EPA’s Science to Achieve Results Estuarine and Great Lakes program through funding to the Great Lakes Environmental Indicators project, U.S. EPA Agreement EPA/R-8286750. This document has not been subjected to the agency’s required peer and policy review and therefore does not necessarily reflect the view of the agency, and no official endorsement should be inferred. This is contribution number 462 of the Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota Duluth.

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N2 - In an evaluation of diatoms as indicators of human disturbance in coastal ecosystems of the Laurentian Great Lakes, we characterized assemblage specificity to lake and habitat type to identify non-anthropogenic factors influencing indicator models. Surface sediment assemblages and environmental variables were collected along the U.S. coastline at 191 sample sites, which were classified by lake and geomorphic type: high-energy (HE), embayment (EB), coastal wetland (CW), riverine wetland (RW), protected wetland (PW), and open water (OP). Diatom inferred (DI) total phosphorus (TP) transfer functions (models) were developed for each lake and geomorphic type. Robust models included: the overall model (RMSEP; r2jack = 0.65; RMSEP = 0.005), Lake Superior (r2jack = 0.73; RMSEP = 0.003), Lake Ontario (r2jack = 0.73; RMSEP = 0.007), PW (r 2jack = 0.64; RMSEP = 0.003), and EB (r2 jack = 0.64; RMSEP = 0.007). Weaker models, indicating poorer diatom-TP relationships, included: RW (r2jack = 0.03; RMSEP = 0.005), OP (r2jack = 0.15; RMSEP = 0.059), and Lake Michigan (r2jack = 0.38; RMSEP = 0.006). DI TP data were regressed against landscape characteristics to quantify the relationships to adjacent watershed stressors. RW data were further scrutinized as a case study to investigate the suitability of diatom-based approaches in systems with poor diatom-TP relationships. Despite poor performance of the RW model, DI phosphorus data for riverine wetlands, derived from the overall model, were strongly related to watershed characteristics (r2 = 0.61), indicating the overall model's ability to integrate stressors from the surrounding watershed in areas where measured phosphorus did not adequately characterize prevailing conditions. This study confirms that physical properties (e.g., lake or habitat type) can influence indicator models; however, weaknesses may be overcome by robust calibration techniques.

AB - In an evaluation of diatoms as indicators of human disturbance in coastal ecosystems of the Laurentian Great Lakes, we characterized assemblage specificity to lake and habitat type to identify non-anthropogenic factors influencing indicator models. Surface sediment assemblages and environmental variables were collected along the U.S. coastline at 191 sample sites, which were classified by lake and geomorphic type: high-energy (HE), embayment (EB), coastal wetland (CW), riverine wetland (RW), protected wetland (PW), and open water (OP). Diatom inferred (DI) total phosphorus (TP) transfer functions (models) were developed for each lake and geomorphic type. Robust models included: the overall model (RMSEP; r2jack = 0.65; RMSEP = 0.005), Lake Superior (r2jack = 0.73; RMSEP = 0.003), Lake Ontario (r2jack = 0.73; RMSEP = 0.007), PW (r 2jack = 0.64; RMSEP = 0.003), and EB (r2 jack = 0.64; RMSEP = 0.007). Weaker models, indicating poorer diatom-TP relationships, included: RW (r2jack = 0.03; RMSEP = 0.005), OP (r2jack = 0.15; RMSEP = 0.059), and Lake Michigan (r2jack = 0.38; RMSEP = 0.006). DI TP data were regressed against landscape characteristics to quantify the relationships to adjacent watershed stressors. RW data were further scrutinized as a case study to investigate the suitability of diatom-based approaches in systems with poor diatom-TP relationships. Despite poor performance of the RW model, DI phosphorus data for riverine wetlands, derived from the overall model, were strongly related to watershed characteristics (r2 = 0.61), indicating the overall model's ability to integrate stressors from the surrounding watershed in areas where measured phosphorus did not adequately characterize prevailing conditions. This study confirms that physical properties (e.g., lake or habitat type) can influence indicator models; however, weaknesses may be overcome by robust calibration techniques.

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Coastal geomorphic and lake variability in the Laurentian Great Lakes: Implications for a diatom-based monitoring tool

Abstract

Bibliographical note

Keywords

UN SDGs

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