Exploration of spatial variability in nearshore water quality using the first Great Lakes National Coastal Condition Assessment survey

John R. Kelly; Peder Yurista; Matthew Starry; Jill Scharold; Will Bartsch; Anne Cotter

doi:10.1016/j.jglr.2015.09.007

Exploration of spatial variability in nearshore water quality using the first Great Lakes National Coastal Condition Assessment survey

John R. Kelly, Peder Yurista, Matthew Starry, Jill Scharold, Will Bartsch, Anne Cotter

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

11 Scopus citations

Abstract

A comprehensive approach to assess conditions in the Great Lakes nearshore has been lacking for decades. We conducted a pilot survey in Lake Erie (45 sites) in summer 2009. The US National Coastal Condition Assessment (NCCA) was then conducted across the Great Lakes in summer 2010. The NCCA survey design provided statistically based estimates with defined uncertainty bounds for a variety of ecological indicators. For example, water quality (WQ) was measured (233 sampled sites) in the US nearshore, a resource defined with criteria to include waters to 30. m depth and less than 5. km from shore. A sub-resource of the US nearshore (151 separate sample sites) was defined using geometric criteria along the shoreline to identify small to medium embayment areas. Statistical analyses showed that embayments had higher Total Phosphorus and were more turbid than the open nearshore. We explored spatial variability in WQ results (2009, 2010) through regression analyses at multiple scales (within and across lakes) for nearshore and embayment resources. Empirical modeling identified principal drivers of spatial variability as risk factors for enrichment: water column depth and a landscape disturbance metric representing agricultural intensity as an indicator of watershed nutrient loading. Eutrophic nearshore conditions occurred at the upper end of an associated landscape disturbance gradient across watersheds of the US basin, peaking in Lake Erie. Overall results were consistent with the principles of classical limnology theory and demonstrated that a statistical survey approach can contribute to Great Lakes nearshore assessment and research.

Original language	English (US)
Pages (from-to)	1060-1074
Number of pages	15
Journal	Journal of Great Lakes Research
Volume	41
Issue number	4
DOIs	https://doi.org/10.1016/j.jglr.2015.09.007
State	Published - Dec 1 2015
Externally published	Yes

Bibliographical note

Funding Information:
The US EPA Office of Water, staff from EPA Regions 2, 3, and 5 and the Great Lakes National Program Office (GLNPO), and from the 8 Great Lakes US States conducted the US National Coastal Condition Assessment (NCCA) in summer 2010 as part of a set of National Aquatic Resource Surveys. Funding to conduct the NCCA came from EPA's Office of Water who assists States in the conduct of National Aquatic Resource Surveys, and from enhancements supported by Great Lakes Restoration Initiative (GLRI) funds, thanks to the vision and determination of Gary Gulezian and Paul Horvatin. The development of this Great lakes coastal frame and survey design/analysis has been aided by a strong commitment to include the Great Lakes in the national assessment, over almost a decade, of individuals in the EPA's Office of Research and Development (Tony Olsen and Tom Kinkaid, Western Ecology Division; John Macauley, Gulf Ecology Division; John Kiddon, Atlantic Ecology Division) and Office of Water (Barry Burgan and Greg Colianni). Others in EPA's Office of Water have been instrumental in supporting the Great Lakes development, including Sarah Lehmann, Treda Greyson-Smith, and at Region 5/GLNPO (Paul Horvatin, Mari Nord, Paul Bertram, Elizabeth Hinchey-Malloy). The survey design was done by Tony Olsen and Tom Kincaid, who each assisted with some statistical analyses. Numerous colleagues from the Mid-Continent Ecology Division assisted with fieldwork in 2009, including Jon Van Alstine, Tim Corry, Greg Peterson, Joel Hoffman, Mike Knuth, Sam Miller, David Miller, John Morrice, and summer students Andrew Just, Aisha Beaty, and Emily Bradshaw. We acknowledge especially Glenn Warren and Paul Horvatin (GLNPO) for providing time on the R/V Lake Guardian. Tom Hollenhorst of MED assisted with organizing the GLEI landscape stressor data sets. This manuscript was approved for submission by the US EPA. Thanks to David Bolgrien and JGLR anonymous reviewers for comments that helped clarify presentation. The views expressed in this article are those of the author and do not necessarily reflect the views or policies of the US Environment Protection Agency. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

Publisher Copyright:
© 2015.

Keywords

Assessment
Embayments
Great Lakes
Nearshore
Phosphorus
Watersheds

UN SDGs

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

Access

10.1016/j.jglr.2015.09.007

OpenUrl availability

Full text

Cite this

@article{42a72124692146eb89a851618a860f18,

title = "Exploration of spatial variability in nearshore water quality using the first Great Lakes National Coastal Condition Assessment survey",

abstract = "A comprehensive approach to assess conditions in the Great Lakes nearshore has been lacking for decades. We conducted a pilot survey in Lake Erie (45 sites) in summer 2009. The US National Coastal Condition Assessment (NCCA) was then conducted across the Great Lakes in summer 2010. The NCCA survey design provided statistically based estimates with defined uncertainty bounds for a variety of ecological indicators. For example, water quality (WQ) was measured (233 sampled sites) in the US nearshore, a resource defined with criteria to include waters to 30. m depth and less than 5. km from shore. A sub-resource of the US nearshore (151 separate sample sites) was defined using geometric criteria along the shoreline to identify small to medium embayment areas. Statistical analyses showed that embayments had higher Total Phosphorus and were more turbid than the open nearshore. We explored spatial variability in WQ results (2009, 2010) through regression analyses at multiple scales (within and across lakes) for nearshore and embayment resources. Empirical modeling identified principal drivers of spatial variability as risk factors for enrichment: water column depth and a landscape disturbance metric representing agricultural intensity as an indicator of watershed nutrient loading. Eutrophic nearshore conditions occurred at the upper end of an associated landscape disturbance gradient across watersheds of the US basin, peaking in Lake Erie. Overall results were consistent with the principles of classical limnology theory and demonstrated that a statistical survey approach can contribute to Great Lakes nearshore assessment and research.",

keywords = "Assessment, Embayments, Great Lakes, Nearshore, Phosphorus, Watersheds",

author = "Kelly, {John R.} and Peder Yurista and Matthew Starry and Jill Scharold and Will Bartsch and Anne Cotter",

note = "Funding Information: The US EPA Office of Water, staff from EPA Regions 2, 3, and 5 and the Great Lakes National Program Office (GLNPO), and from the 8 Great Lakes US States conducted the US National Coastal Condition Assessment (NCCA) in summer 2010 as part of a set of National Aquatic Resource Surveys. Funding to conduct the NCCA came from EPA's Office of Water who assists States in the conduct of National Aquatic Resource Surveys, and from enhancements supported by Great Lakes Restoration Initiative (GLRI) funds, thanks to the vision and determination of Gary Gulezian and Paul Horvatin. The development of this Great lakes coastal frame and survey design/analysis has been aided by a strong commitment to include the Great Lakes in the national assessment, over almost a decade, of individuals in the EPA's Office of Research and Development (Tony Olsen and Tom Kinkaid, Western Ecology Division; John Macauley, Gulf Ecology Division; John Kiddon, Atlantic Ecology Division) and Office of Water (Barry Burgan and Greg Colianni). Others in EPA's Office of Water have been instrumental in supporting the Great Lakes development, including Sarah Lehmann, Treda Greyson-Smith, and at Region 5/GLNPO (Paul Horvatin, Mari Nord, Paul Bertram, Elizabeth Hinchey-Malloy). The survey design was done by Tony Olsen and Tom Kincaid, who each assisted with some statistical analyses. Numerous colleagues from the Mid-Continent Ecology Division assisted with fieldwork in 2009, including Jon Van Alstine, Tim Corry, Greg Peterson, Joel Hoffman, Mike Knuth, Sam Miller, David Miller, John Morrice, and summer students Andrew Just, Aisha Beaty, and Emily Bradshaw. We acknowledge especially Glenn Warren and Paul Horvatin (GLNPO) for providing time on the R/V Lake Guardian. Tom Hollenhorst of MED assisted with organizing the GLEI landscape stressor data sets. This manuscript was approved for submission by the US EPA. Thanks to David Bolgrien and JGLR anonymous reviewers for comments that helped clarify presentation. The views expressed in this article are those of the author and do not necessarily reflect the views or policies of the US Environment Protection Agency. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. Publisher Copyright: {\textcopyright} 2015.",

year = "2015",

month = dec,

day = "1",

doi = "10.1016/j.jglr.2015.09.007",

language = "English (US)",

volume = "41",

pages = "1060--1074",

journal = "Journal of Great Lakes Research",

issn = "0380-1330",

publisher = "International Association of Great Lakes Research",

number = "4",

}

TY - JOUR

T1 - Exploration of spatial variability in nearshore water quality using the first Great Lakes National Coastal Condition Assessment survey

AU - Kelly, John R.

AU - Yurista, Peder

AU - Starry, Matthew

AU - Scharold, Jill

AU - Bartsch, Will

AU - Cotter, Anne

N1 - Funding Information: The US EPA Office of Water, staff from EPA Regions 2, 3, and 5 and the Great Lakes National Program Office (GLNPO), and from the 8 Great Lakes US States conducted the US National Coastal Condition Assessment (NCCA) in summer 2010 as part of a set of National Aquatic Resource Surveys. Funding to conduct the NCCA came from EPA's Office of Water who assists States in the conduct of National Aquatic Resource Surveys, and from enhancements supported by Great Lakes Restoration Initiative (GLRI) funds, thanks to the vision and determination of Gary Gulezian and Paul Horvatin. The development of this Great lakes coastal frame and survey design/analysis has been aided by a strong commitment to include the Great Lakes in the national assessment, over almost a decade, of individuals in the EPA's Office of Research and Development (Tony Olsen and Tom Kinkaid, Western Ecology Division; John Macauley, Gulf Ecology Division; John Kiddon, Atlantic Ecology Division) and Office of Water (Barry Burgan and Greg Colianni). Others in EPA's Office of Water have been instrumental in supporting the Great Lakes development, including Sarah Lehmann, Treda Greyson-Smith, and at Region 5/GLNPO (Paul Horvatin, Mari Nord, Paul Bertram, Elizabeth Hinchey-Malloy). The survey design was done by Tony Olsen and Tom Kincaid, who each assisted with some statistical analyses. Numerous colleagues from the Mid-Continent Ecology Division assisted with fieldwork in 2009, including Jon Van Alstine, Tim Corry, Greg Peterson, Joel Hoffman, Mike Knuth, Sam Miller, David Miller, John Morrice, and summer students Andrew Just, Aisha Beaty, and Emily Bradshaw. We acknowledge especially Glenn Warren and Paul Horvatin (GLNPO) for providing time on the R/V Lake Guardian. Tom Hollenhorst of MED assisted with organizing the GLEI landscape stressor data sets. This manuscript was approved for submission by the US EPA. Thanks to David Bolgrien and JGLR anonymous reviewers for comments that helped clarify presentation. The views expressed in this article are those of the author and do not necessarily reflect the views or policies of the US Environment Protection Agency. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. Publisher Copyright: © 2015.

PY - 2015/12/1

Y1 - 2015/12/1

N2 - A comprehensive approach to assess conditions in the Great Lakes nearshore has been lacking for decades. We conducted a pilot survey in Lake Erie (45 sites) in summer 2009. The US National Coastal Condition Assessment (NCCA) was then conducted across the Great Lakes in summer 2010. The NCCA survey design provided statistically based estimates with defined uncertainty bounds for a variety of ecological indicators. For example, water quality (WQ) was measured (233 sampled sites) in the US nearshore, a resource defined with criteria to include waters to 30. m depth and less than 5. km from shore. A sub-resource of the US nearshore (151 separate sample sites) was defined using geometric criteria along the shoreline to identify small to medium embayment areas. Statistical analyses showed that embayments had higher Total Phosphorus and were more turbid than the open nearshore. We explored spatial variability in WQ results (2009, 2010) through regression analyses at multiple scales (within and across lakes) for nearshore and embayment resources. Empirical modeling identified principal drivers of spatial variability as risk factors for enrichment: water column depth and a landscape disturbance metric representing agricultural intensity as an indicator of watershed nutrient loading. Eutrophic nearshore conditions occurred at the upper end of an associated landscape disturbance gradient across watersheds of the US basin, peaking in Lake Erie. Overall results were consistent with the principles of classical limnology theory and demonstrated that a statistical survey approach can contribute to Great Lakes nearshore assessment and research.

AB - A comprehensive approach to assess conditions in the Great Lakes nearshore has been lacking for decades. We conducted a pilot survey in Lake Erie (45 sites) in summer 2009. The US National Coastal Condition Assessment (NCCA) was then conducted across the Great Lakes in summer 2010. The NCCA survey design provided statistically based estimates with defined uncertainty bounds for a variety of ecological indicators. For example, water quality (WQ) was measured (233 sampled sites) in the US nearshore, a resource defined with criteria to include waters to 30. m depth and less than 5. km from shore. A sub-resource of the US nearshore (151 separate sample sites) was defined using geometric criteria along the shoreline to identify small to medium embayment areas. Statistical analyses showed that embayments had higher Total Phosphorus and were more turbid than the open nearshore. We explored spatial variability in WQ results (2009, 2010) through regression analyses at multiple scales (within and across lakes) for nearshore and embayment resources. Empirical modeling identified principal drivers of spatial variability as risk factors for enrichment: water column depth and a landscape disturbance metric representing agricultural intensity as an indicator of watershed nutrient loading. Eutrophic nearshore conditions occurred at the upper end of an associated landscape disturbance gradient across watersheds of the US basin, peaking in Lake Erie. Overall results were consistent with the principles of classical limnology theory and demonstrated that a statistical survey approach can contribute to Great Lakes nearshore assessment and research.

KW - Assessment

KW - Embayments

KW - Great Lakes

KW - Nearshore

KW - Phosphorus

KW - Watersheds

UR - http://www.scopus.com/inward/record.url?scp=84955340301&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84955340301&partnerID=8YFLogxK

U2 - 10.1016/j.jglr.2015.09.007

DO - 10.1016/j.jglr.2015.09.007

M3 - Article

AN - SCOPUS:84955340301

SN - 0380-1330

VL - 41

SP - 1060

EP - 1074

JO - Journal of Great Lakes Research

JF - Journal of Great Lakes Research

IS - 4

ER -

Exploration of spatial variability in nearshore water quality using the first Great Lakes National Coastal Condition Assessment survey

Abstract

Bibliographical note

Keywords

UN SDGs

Access

OpenUrl availability

Other files and links

Fingerprint

Cite this