Environmental predictors of phytoplankton chlorophyll-a in Great Lakes coastal wetlands

Abstract

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.