Environmentally stratified sampling design for the development of Great Lakes environmental indicators

Nicholas P. Danz; Ronald R. Regal; Gerald J Niemi; Valerie J Brady; Tom Hollenhorst; Lucinda B Johnson; George E Host; Joann M. Hanowski; Carol A. Johnston; Terry N Brown; John Kingston; John R Kelly

doi:10.1007/s10661-005-1594-8

Environmentally stratified sampling design for the development of Great Lakes environmental indicators

Nicholas P. Danz, Ronald R. Regal, Gerald J Niemi, Valerie J Brady, Tom Hollenhorst, Lucinda B Johnson, George E Host, Joann M. Hanowski, Carol A. Johnston, Terry N Brown, John Kingston, John R Kelly

Natural Resources Research Institute

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

108 Scopus citations

Abstract

Understanding the relationship between human disturbance and ecological response is essential to the process of indicator development. For large-scale observational studies, sites should be selected across gradients of anthropogenic stress, but such gradients are often unknown for a population of sites prior to site selection. Stress data available from public sources can be used in a geographic information system (GIS) to partially characterize environmental conditions for large geographic areas without visiting the sites. We divided the U.S. Great Lakes coastal region into 762 units consisting of a shoreline reach and drainage-shed and then summarized over 200 environmental variables in seven categories for the units using a GIS. Redundancy within the categories of environmental variables was reduced using principal components analysis. Environmental strata were generated from cluster analysis using principal component scores as input. To protect against site selection bias, sites were selected in random order from clusters. The site selection process allowed us to exclude sites that were inaccessible and was shown to successfully distribute sites across the range of environmental variation in our GIS data. This design has broad applicability when the goal is to develop ecological indicators using observational data from large-scale surveys.

Original language	English (US)
Pages (from-to)	41-65
Number of pages	25
Journal	Environmental Monitoring and Assessment
Volume	102
Issue number	1-3
DOIs	https://doi.org/10.1007/s10661-005-1594-8
State	Published - Mar 2005

Bibliographical note

Funding Information:
We are grateful to Connie Host, Paul Meysembourg, Jim Sales, and Gerry Sjerven for assistance in compiling GIS data. Two anonymous referees provided valuable comments on an earlier draft. This research was supported by a grant from the U.S. Environmental Protection Agency’s Science to Achieve Results (STAR) Estuarine and Great Lakes (EaGLe) program through funding to the Great Lakes Environmental Indicators (GLEI) 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 views of the Agency, and no official endorsement should be inferred. This is contribution number 360 of the Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota Duluth.

Keywords

Anthropogenic stress
Ecological indicators
GIS
Great Lakes
Human disturbance gradient
Sampling design

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Danz, N. P., Regal, R. R., Niemi, G. J., Brady, V. J., Hollenhorst, T., Johnson, L. B., Host, G. E., Hanowski, J. M., Johnston, C. A., Brown, T. N., Kingston, J., & Kelly, J. R. (2005). Environmentally stratified sampling design for the development of Great Lakes environmental indicators. Environmental Monitoring and Assessment, 102(1-3), 41-65. https://doi.org/10.1007/s10661-005-1594-8

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abstract = "Understanding the relationship between human disturbance and ecological response is essential to the process of indicator development. For large-scale observational studies, sites should be selected across gradients of anthropogenic stress, but such gradients are often unknown for a population of sites prior to site selection. Stress data available from public sources can be used in a geographic information system (GIS) to partially characterize environmental conditions for large geographic areas without visiting the sites. We divided the U.S. Great Lakes coastal region into 762 units consisting of a shoreline reach and drainage-shed and then summarized over 200 environmental variables in seven categories for the units using a GIS. Redundancy within the categories of environmental variables was reduced using principal components analysis. Environmental strata were generated from cluster analysis using principal component scores as input. To protect against site selection bias, sites were selected in random order from clusters. The site selection process allowed us to exclude sites that were inaccessible and was shown to successfully distribute sites across the range of environmental variation in our GIS data. This design has broad applicability when the goal is to develop ecological indicators using observational data from large-scale surveys.",

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note = "Funding Information: We are grateful to Connie Host, Paul Meysembourg, Jim Sales, and Gerry Sjerven for assistance in compiling GIS data. Two anonymous referees provided valuable comments on an earlier draft. This research was supported by a grant from the U.S. Environmental Protection Agency{\textquoteright}s Science to Achieve Results (STAR) Estuarine and Great Lakes (EaGLe) program through funding to the Great Lakes Environmental Indicators (GLEI) 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 views of the Agency, and no official endorsement should be inferred. This is contribution number 360 of the Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota Duluth.",

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AU - Niemi, Gerald J

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AU - Hollenhorst, Tom

AU - Johnson, Lucinda B

AU - Host, George E

AU - Hanowski, Joann M.

AU - Johnston, Carol A.

AU - Brown, Terry N

AU - Kingston, John

AU - Kelly, John R

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Environmentally stratified sampling design for the development of Great Lakes environmental indicators

Abstract

Bibliographical note

Keywords

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