Keeping up with the math: Advancing the ecological foundation of the Great Lakes Cladophora Model

The nearshore waters of the Laurentian Great Lakes have historically suffered from beach fouling and clogged water intakes due to proliferation of the native, filamentous green alga Cladophora. A resurgence in nuisance growth of the alga has led to a demand for an improved model platform to better guide management. The Great Lakes Cladophora model (GLCM v3) predicts algal biomass (g dry matter m-2) and stored phosphorus content (P as % of dry matter) based on simulations forced by time series of incident light (I), water temperature (T) and water column soluble reactive phosphorus concentration (SRP, mu gP L-1). A particular strength of the GLCM v3 is its foundation in ecologically sound biokinetic mechanisms, supported by field and laboratory measurements. These measurements, advancing the credibility and reliability of the biokinetic framework, include improved characterization of the growth and respiration responses to light and temperature, addition of a self-shading algorithm replacing an overly deterministic carrying capacity term, a new treatment of phosphorus uptake based on radioisotope experiments, additional observational support for Droop-based simulation of growth as a function of stored P, and implementation of a new physiologically and physically driven sloughing function. Uncertainty associated with processes collectively termed environmental friction (the I, T, and P growth forcing functions) is reduced, leaving the model sensitive to the maximum specific growth rate and the coefficient for extinction of photosynthetically active radiation through the algal mat. The model was performance tested by multi-lake (Erie, Huron, Ontario, and Michigan) calibration employing a common set of biophysical coefficients. This common set of calibration coefficients provides enhanced corroboration that GLCM v3 is suitable for examining the phosphorus-Cladophora dynamic across the Great Lakes. In particular, it greatly strengthens the model's efficacy for establishing a phosphorus standard to maintain levels of algal biomass below those constituting a nuisance condition, as per the Great Lakes Water Quality Agreement of 2012. In addition, the model structure can be applied to other lakes experiencing problems with attached filamentous algae.

Automated summary

This study develops an improved model platform for predicting the biomass and phosphorus content of green algae in the Great Lakes region. The model's reliability and applicability are verified through calibration using a common set of coefficients. This model is of great importance for guiding management practices and maintaining water quality standards to prevent algal proliferation.