TY - JOUR
T1 - Environmental predictors of phytoplankton chlorophyll-a in Great Lakes coastal wetlands
AU - Gentine, Joseph A.
AU - Conard, Whitney M.
AU - O'Reilly, Katherine E.
AU - Cooper, Matthew J.
AU - Fiorino, Giuseppe E.
AU - Harrison, Anna M.
AU - Hein, Marina
AU - Moerke, Ashley H.
AU - Ruetz, Carl R.
AU - Uzarski, Donald G.
AU - Lamberti, Gary A.
N1 - Funding Information:
The data used in this manuscript were collected by scientists and their research teams from 11 U.S. and Canadian universities, three U.S. and Canadian government agencies, and one environmental engineering and science firm as part of the Great Lakes Coastal Wetland Monitoring Program. The U.S. project team consists of scientists from the Institute for Great Lakes Research at Central Michigan, the Natural Resources Research Institute (NRRI) at the University of Minnesota Duluth, the Annis Water Resources Institute (AWRI) at Grand Valley State University, the Burke Center for Freshwater Innovation at Northland College, the University of Notre Dame, Lake Superior State University, State University of New York-College at Brockport, the University of Wisconsin at Green Bay, River Falls, and Superior, and Oregon State University, as well as resource management officials from the Michigan Department of Environmental Quality and the United States Environmental Protection Agency (USEPA), and a data-management professional from LimnoTech (this is contribution number 168 of the CMU IGLR). The Canadian project team consists of scientists from the University of Windsor, Environment and Climate Change Canada, and Bird Studies Canada. Funding was provided by the USEPA Great Lakes National Program Office, grant numbers GL-00E00612-0, 00E01567 as part of the Great Lakes Restoration Initiative. Although this research is partly funded by the USEPA, it has not been subjected to the agency's required peer and policy review, and thus, does not necessarily reflect their views. We thank all personnel involved in collecting data that were included in this analysis. We also thank Mike Brueseke and Sarah Klepinger from the University of Notre Dame for analyzing chlorophyll-a samples.
Funding Information:
The data used in this manuscript were collected by scientists and their research teams from 11 U.S. and Canadian universities, three U.S. and Canadian government agencies, and one environmental engineering and science firm as part of the Great Lakes Coastal Wetland Monitoring Program. The U.S. project team consists of scientists from the Institute for Great Lakes Research at Central Michigan, the Natural Resources Research Institute (NRRI) at the University of Minnesota Duluth , the Annis Water Resources Institute (AWRI) at Grand Valley State University, the Burke Center for Freshwater Innovation at Northland College, the University of Notre Dame, Lake Superior State University, State University of New York-College at Brockport, the University of Wisconsin at Green Bay, River Falls, and Superior, and Oregon State University, as well as resource management officials from the Michigan Department of Environmental Quality and the United States Environmental Protection Agency (USEPA), and a data-management professional from LimnoTech (this is contribution number 168 of the CMU IGLR ). The Canadian project team consists of scientists from the University of Windsor, Environment and Climate Change Canada, and Bird Studies Canada. Funding was provided by the USEPA Great Lakes National Program Office, grant numbers GL-00E00612-0 , 00E01567 as part of the Great Lakes Restoration Initiative. Although this research is partly funded by the USEPA, it has not been subjected to the agency’s required peer and policy review, and thus, does not necessarily reflect their views. We thank all personnel involved in collecting data that were included in this analysis. We also thank Mike Brueseke and Sarah Klepinger from the University of Notre Dame for analyzing chlorophyll-a samples.
Publisher Copyright:
© 2022 International Association for Great Lakes Research
PY - 2022
Y1 - 2022
N2 - Coastal wetlands of the Laurentian Great Lakes are diverse and productive ecosystems that provide many ecosystem services, but are threatened by anthropogenic factors, including nutrient input, land-use change, invasive species, and climate change. In this study, we examined one component of wetland ecosystem structure – phytoplankton biomass – using the proxy metric of water column chlorophyll-a measured in 514 coastal wetlands across all five Great Lakes as part of the Great Lakes Coastal Wetland Monitoring Program. Mean chlorophyll-a concentrations increased from north-to-south from Lake Superior to Lake Erie, but concentrations varied among sites within lakes. To predict chlorophyll-a concentrations, we developed two random forest models for each lake – one using variables that may directly relate to phytoplankton biomass (“proximate” variables; e.g., dissolved nutrients, temperature, pH) and another using variables with potentially indirect effects on phytoplankton growth (“distal” variables; e.g., land use, fetch). Proximate and distal variable models explained 16–43% and 19–48% of variation in chlorophyll-a, respectively, with models developed for lakes Erie and Michigan having the highest amount of explanatory power and models developed for lakes Ontario, Superior, and Huron having the lowest. Land-use variables were important distal predictors of chlorophyll-a concentrations across all lakes. We found multiple proximate predictors of chlorophyll-a, but there was little consistency among lakes, suggesting that, while chlorophyll-a may be broadly influenced by distal factors such as land use, individual lakes and wetlands have unique characteristics that affect chlorophyll-a concentrations. Our results highlight the importance of responsible land-use planning and watershed-level management for protecting coastal wetlands.
AB - Coastal wetlands of the Laurentian Great Lakes are diverse and productive ecosystems that provide many ecosystem services, but are threatened by anthropogenic factors, including nutrient input, land-use change, invasive species, and climate change. In this study, we examined one component of wetland ecosystem structure – phytoplankton biomass – using the proxy metric of water column chlorophyll-a measured in 514 coastal wetlands across all five Great Lakes as part of the Great Lakes Coastal Wetland Monitoring Program. Mean chlorophyll-a concentrations increased from north-to-south from Lake Superior to Lake Erie, but concentrations varied among sites within lakes. To predict chlorophyll-a concentrations, we developed two random forest models for each lake – one using variables that may directly relate to phytoplankton biomass (“proximate” variables; e.g., dissolved nutrients, temperature, pH) and another using variables with potentially indirect effects on phytoplankton growth (“distal” variables; e.g., land use, fetch). Proximate and distal variable models explained 16–43% and 19–48% of variation in chlorophyll-a, respectively, with models developed for lakes Erie and Michigan having the highest amount of explanatory power and models developed for lakes Ontario, Superior, and Huron having the lowest. Land-use variables were important distal predictors of chlorophyll-a concentrations across all lakes. We found multiple proximate predictors of chlorophyll-a, but there was little consistency among lakes, suggesting that, while chlorophyll-a may be broadly influenced by distal factors such as land use, individual lakes and wetlands have unique characteristics that affect chlorophyll-a concentrations. Our results highlight the importance of responsible land-use planning and watershed-level management for protecting coastal wetlands.
KW - Chlorophyll-a
KW - Coastal wetlands
KW - Great Lakes
KW - Land use
KW - Random forest
KW - Water quality
UR - http://www.scopus.com/inward/record.url?scp=85129918217&partnerID=8YFLogxK
U2 - 10.1016/j.jglr.2022.04.015
DO - 10.1016/j.jglr.2022.04.015
M3 - Article
AN - SCOPUS:85129918217
JO - Journal of Great Lakes Research
JF - Journal of Great Lakes Research
SN - 0380-1330
ER -