Evaluation of geographic, geomorphic and human influences on Great Lakes wetland indicators: A multi-assemblage approach

J. C. Brazner; N. P. Danz; G. J. Niemi; R. R. Regal; A. S. Trebitz; R. W. Howe; J. M. Hanowski; L. B. Johnson; J. J.H. Ciborowski; C. A. Johnston; E. D. Reavie; V. J. Brady; G. V. Sgro

doi:10.1016/j.ecolind.2006.07.001

Evaluation of geographic, geomorphic and human influences on Great Lakes wetland indicators: A multi-assemblage approach

J. C. Brazner, N. P. Danz, G. J. Niemi, R. R. Regal, A. S. Trebitz, R. W. Howe, J. M. Hanowski, L. B. Johnson, J. J.H. Ciborowski, C. A. Johnston, E. D. Reavie, V. J. Brady, G. V. Sgro

Natural Resources Research Institute

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93 Scopus citations

Abstract

Developing effective indicators of ecological condition requires calibration to determine the geographic range and ecosystem type appropriate for each indicator. Here, we demonstrate an approach for evaluating the relative influence of geography, geomorphology and human disturbance on patterns of variation in biotic indicators derived from multiple assemblages for ecosystems that span broad spatial scales. To accomplish this, we collected abundance information on six biotic assemblages (birds, fish, amphibians, aquatic macroinvertebrates, wetland vegetation, and diatoms) from over 450 locations along U.S. shorelines throughout each of the Great Lakes during 2002-2004. Sixty-six candidate taxon- and function-based indicators analyzed using hierarchical variance partitioning revealed that geographic (lake) rather than geomorphic factors (wetland type) had the greatest influence on the proportion of variance explained across all indicators, and that a significant portion of the variance was also related to response to human disturbance. Wetland vegetation, fish and bird indicators were the most, and macroinvertebrates the least, responsive to human disturbance. Proportion of rock bass, Carex lasiocarpa, and stephanodiscoid diatoms, as well as the presence of spring peepers and the number of insectivorous birds were among the indicators that responded most strongly to a human disturbance index, suggesting they have good potential as indicators of Great Lakes coastal wetland condition. Ecoprovince, wetland type, and indicator type (taxa vs function based) explained relatively little variance. Variance patterns for macroinvertebrates and birds were least concordant with those of other assemblages, while diatoms and amphibians, and fish and wetland vegetation were the most concordant assemblage pairs. Our results strongly suggest it will not be possible to develop effective indicators of Great Lakes coastal wetland condition without accounting for differences among lakes and their important interactions. This is one of the first attempts to show how ecological indicators of human disturbance vary over a broad spatial scale in wetlands.

Original language	English (US)
Pages (from-to)	610-635
Number of pages	26
Journal	Ecological Indicators
Volume	7
Issue number	3
DOIs	https://doi.org/10.1016/j.ecolind.2006.07.001
State	Published - Jul 2007

Bibliographical note

Funding Information:
We are especially grateful to Terry Brown and Tom Hollenhorst for their database and geographic information expertise. Thanks also to M. Aho, M. Alexander, N. Andresen, K. Bailey, J. Baillargeon, B. Bedford, Y. Bhagat, A. Boers, M. Bourdaghs, D. Breneman, J. Carlson, A. Cotter, S. Cronk, R. Daw, R. Eedy, M. Ferguson, C. Foley, C. Frieswyk, J. Gathman, I. Grigorovich, R. Hell, J. Holland, C. Host, T. Jicha, J. Johansen, C. Johnson, M. Kang, J. Kaser, J. Kingston, A. Kireta, L. Ladwig, J. Lind, A. Ly, P. Meysembourg, J. Morrice, M. Pearson, G. Peterson, A. Peterson, M. Sierszen, G. Sjerven, E. Stoermer, D. Tanner, D. Taylor, J. Thompson, M. Tulbure, L. Vaccaro, D. Watters, J. Wiklund, and J. Zedler for their assistance with field work, data compilation, and laboratory analysis. 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 article was also supported by funding from the National Space and Aeronautics Administration (NAG5-11262). Additional financial support provided by the National Science Foundation/EPSCoR Grant No. 0091948 and by the State of South Dakota. 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 385 of the Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota, Duluth.

Keywords

Amphibians
Aquatic macroinvertebrates
Biogeography
Biotic assemblages
Birds
Diatoms
Ecological condition indicators
Fish
Geomorphology
Great Lakes coastal wetlands
Hierarchical variance partitioning
Wetland vegetation

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Brazner, J. C., Danz, N. P., Niemi, G. J., Regal, R. R., Trebitz, A. S., Howe, R. W., Hanowski, J. M., Johnson, L. B., Ciborowski, J. J. H., Johnston, C. A., Reavie, E. D., Brady, V. J., & Sgro, G. V. (2007). Evaluation of geographic, geomorphic and human influences on Great Lakes wetland indicators: A multi-assemblage approach. Ecological Indicators, 7(3), 610-635. https://doi.org/10.1016/j.ecolind.2006.07.001

Brazner, JC, Danz, NP, Niemi, GJ, Regal, RR, Trebitz, AS, Howe, RW, Hanowski, JM, Johnson, LB, Ciborowski, JJH, Johnston, CA, Reavie, ED , Brady, VJ & Sgro, GV 2007, 'Evaluation of geographic, geomorphic and human influences on Great Lakes wetland indicators: A multi-assemblage approach', Ecological Indicators, vol. 7, no. 3, pp. 610-635. https://doi.org/10.1016/j.ecolind.2006.07.001

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title = "Evaluation of geographic, geomorphic and human influences on Great Lakes wetland indicators: A multi-assemblage approach",

abstract = "Developing effective indicators of ecological condition requires calibration to determine the geographic range and ecosystem type appropriate for each indicator. Here, we demonstrate an approach for evaluating the relative influence of geography, geomorphology and human disturbance on patterns of variation in biotic indicators derived from multiple assemblages for ecosystems that span broad spatial scales. To accomplish this, we collected abundance information on six biotic assemblages (birds, fish, amphibians, aquatic macroinvertebrates, wetland vegetation, and diatoms) from over 450 locations along U.S. shorelines throughout each of the Great Lakes during 2002-2004. Sixty-six candidate taxon- and function-based indicators analyzed using hierarchical variance partitioning revealed that geographic (lake) rather than geomorphic factors (wetland type) had the greatest influence on the proportion of variance explained across all indicators, and that a significant portion of the variance was also related to response to human disturbance. Wetland vegetation, fish and bird indicators were the most, and macroinvertebrates the least, responsive to human disturbance. Proportion of rock bass, Carex lasiocarpa, and stephanodiscoid diatoms, as well as the presence of spring peepers and the number of insectivorous birds were among the indicators that responded most strongly to a human disturbance index, suggesting they have good potential as indicators of Great Lakes coastal wetland condition. Ecoprovince, wetland type, and indicator type (taxa vs function based) explained relatively little variance. Variance patterns for macroinvertebrates and birds were least concordant with those of other assemblages, while diatoms and amphibians, and fish and wetland vegetation were the most concordant assemblage pairs. Our results strongly suggest it will not be possible to develop effective indicators of Great Lakes coastal wetland condition without accounting for differences among lakes and their important interactions. This is one of the first attempts to show how ecological indicators of human disturbance vary over a broad spatial scale in wetlands.",

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note = "Funding Information: We are especially grateful to Terry Brown and Tom Hollenhorst for their database and geographic information expertise. Thanks also to M. Aho, M. Alexander, N. Andresen, K. Bailey, J. Baillargeon, B. Bedford, Y. Bhagat, A. Boers, M. Bourdaghs, D. Breneman, J. Carlson, A. Cotter, S. Cronk, R. Daw, R. Eedy, M. Ferguson, C. Foley, C. Frieswyk, J. Gathman, I. Grigorovich, R. Hell, J. Holland, C. Host, T. Jicha, J. Johansen, C. Johnson, M. Kang, J. Kaser, J. Kingston, A. Kireta, L. Ladwig, J. Lind, A. Ly, P. Meysembourg, J. Morrice, M. Pearson, G. Peterson, A. Peterson, M. Sierszen, G. Sjerven, E. Stoermer, D. Tanner, D. Taylor, J. Thompson, M. Tulbure, L. Vaccaro, D. Watters, J. Wiklund, and J. Zedler for their assistance with field work, data compilation, and laboratory analysis. 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 article was also supported by funding from the National Space and Aeronautics Administration (NAG5-11262). Additional financial support provided by the National Science Foundation/EPSCoR Grant No. 0091948 and by the State of South Dakota. 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 385 of the Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota, Duluth. ",

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doi = "10.1016/j.ecolind.2006.07.001",

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T2 - A multi-assemblage approach

AU - Brazner, J. C.

AU - Danz, N. P.

AU - Niemi, G. J.

AU - Regal, R. R.

AU - Trebitz, A. S.

AU - Howe, R. W.

AU - Hanowski, J. M.

AU - Johnson, L. B.

AU - Ciborowski, J. J.H.

AU - Johnston, C. A.

AU - Reavie, E. D.

AU - Brady, V. J.

AU - Sgro, G. V.

N1 - Funding Information: We are especially grateful to Terry Brown and Tom Hollenhorst for their database and geographic information expertise. Thanks also to M. Aho, M. Alexander, N. Andresen, K. Bailey, J. Baillargeon, B. Bedford, Y. Bhagat, A. Boers, M. Bourdaghs, D. Breneman, J. Carlson, A. Cotter, S. Cronk, R. Daw, R. Eedy, M. Ferguson, C. Foley, C. Frieswyk, J. Gathman, I. Grigorovich, R. Hell, J. Holland, C. Host, T. Jicha, J. Johansen, C. Johnson, M. Kang, J. Kaser, J. Kingston, A. Kireta, L. Ladwig, J. Lind, A. Ly, P. Meysembourg, J. Morrice, M. Pearson, G. Peterson, A. Peterson, M. Sierszen, G. Sjerven, E. Stoermer, D. Tanner, D. Taylor, J. Thompson, M. Tulbure, L. Vaccaro, D. Watters, J. Wiklund, and J. Zedler for their assistance with field work, data compilation, and laboratory analysis. 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 article was also supported by funding from the National Space and Aeronautics Administration (NAG5-11262). Additional financial support provided by the National Science Foundation/EPSCoR Grant No. 0091948 and by the State of South Dakota. 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 385 of the Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota, Duluth.

PY - 2007/7

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N2 - Developing effective indicators of ecological condition requires calibration to determine the geographic range and ecosystem type appropriate for each indicator. Here, we demonstrate an approach for evaluating the relative influence of geography, geomorphology and human disturbance on patterns of variation in biotic indicators derived from multiple assemblages for ecosystems that span broad spatial scales. To accomplish this, we collected abundance information on six biotic assemblages (birds, fish, amphibians, aquatic macroinvertebrates, wetland vegetation, and diatoms) from over 450 locations along U.S. shorelines throughout each of the Great Lakes during 2002-2004. Sixty-six candidate taxon- and function-based indicators analyzed using hierarchical variance partitioning revealed that geographic (lake) rather than geomorphic factors (wetland type) had the greatest influence on the proportion of variance explained across all indicators, and that a significant portion of the variance was also related to response to human disturbance. Wetland vegetation, fish and bird indicators were the most, and macroinvertebrates the least, responsive to human disturbance. Proportion of rock bass, Carex lasiocarpa, and stephanodiscoid diatoms, as well as the presence of spring peepers and the number of insectivorous birds were among the indicators that responded most strongly to a human disturbance index, suggesting they have good potential as indicators of Great Lakes coastal wetland condition. Ecoprovince, wetland type, and indicator type (taxa vs function based) explained relatively little variance. Variance patterns for macroinvertebrates and birds were least concordant with those of other assemblages, while diatoms and amphibians, and fish and wetland vegetation were the most concordant assemblage pairs. Our results strongly suggest it will not be possible to develop effective indicators of Great Lakes coastal wetland condition without accounting for differences among lakes and their important interactions. This is one of the first attempts to show how ecological indicators of human disturbance vary over a broad spatial scale in wetlands.

AB - Developing effective indicators of ecological condition requires calibration to determine the geographic range and ecosystem type appropriate for each indicator. Here, we demonstrate an approach for evaluating the relative influence of geography, geomorphology and human disturbance on patterns of variation in biotic indicators derived from multiple assemblages for ecosystems that span broad spatial scales. To accomplish this, we collected abundance information on six biotic assemblages (birds, fish, amphibians, aquatic macroinvertebrates, wetland vegetation, and diatoms) from over 450 locations along U.S. shorelines throughout each of the Great Lakes during 2002-2004. Sixty-six candidate taxon- and function-based indicators analyzed using hierarchical variance partitioning revealed that geographic (lake) rather than geomorphic factors (wetland type) had the greatest influence on the proportion of variance explained across all indicators, and that a significant portion of the variance was also related to response to human disturbance. Wetland vegetation, fish and bird indicators were the most, and macroinvertebrates the least, responsive to human disturbance. Proportion of rock bass, Carex lasiocarpa, and stephanodiscoid diatoms, as well as the presence of spring peepers and the number of insectivorous birds were among the indicators that responded most strongly to a human disturbance index, suggesting they have good potential as indicators of Great Lakes coastal wetland condition. Ecoprovince, wetland type, and indicator type (taxa vs function based) explained relatively little variance. Variance patterns for macroinvertebrates and birds were least concordant with those of other assemblages, while diatoms and amphibians, and fish and wetland vegetation were the most concordant assemblage pairs. Our results strongly suggest it will not be possible to develop effective indicators of Great Lakes coastal wetland condition without accounting for differences among lakes and their important interactions. This is one of the first attempts to show how ecological indicators of human disturbance vary over a broad spatial scale in wetlands.

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KW - Aquatic macroinvertebrates

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KW - Biotic assemblages

KW - Birds

KW - Diatoms

KW - Ecological condition indicators

KW - Fish

KW - Geomorphology

KW - Great Lakes coastal wetlands

KW - Hierarchical variance partitioning

KW - Wetland vegetation

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Evaluation of geographic, geomorphic and human influences on Great Lakes wetland indicators: A multi-assemblage approach

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Bibliographical note

Keywords

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