Using 3D modeling and remote sensing capabilities for a better understanding of spatio-temporal heterogeneities of phytoplankton abundance in large lakes

Lake biological parameters show important spatio-temporal heterogeneities. This is why explaining the spatial patchiness of phytoplankton abundance has been a recurrent ecological issue and is an essential prerequisite for objectively assessing, protecting and restoring freshwater ecosystems. The drivers of these heterogeneities can be identified by modeling their dynamics. This approach is useful for theoretical and applied limnology. In this study, a 3D hydrodynamic model of Lake Geneva (France/Switzerland) was created. It is based on the Delft3D suite software and includes the main tributary (Rhône River) and two-dimensional high-resolution meteorological forcing. It provides 3D maps of water temperature and current velocities with a 1?h time step on a 1?km horizontal grid size and with a vertical resolution of 1?m near the surface to 7?m at the bottom of the lake. The dynamics and the drivers of phytoplankton heterogeneities were assessed by combining the outputs of the model and chlorophyll-a concentration (Chl-a) data from MERIS satellite images between 2008 and 2012. Results highlight physical mechanisms responsible for the occurrence of seasonal hot-spots in phytoplankton abundance in the lake. At the beginning of spring, Chl-a heterogeneities are usually caused by an earlier onset of phytoplankton growth in the shallowest and more sheltered areas; spatial differences in the timing of phytoplankton growth can be explained by spatial variability in thermal stratification dynamics. In summer, transient and locally higher phytoplankton abundances are observed in relation to the impact of basin-scale upwelling.     

A mercury transport and fate model (LM2-Mercury) for mass budget assessment of mercury cycling in Lake Michigan

LM2-Mercury, a mercury mass balance model, was developed to simulate and evaluate the transport, fate, and biogeochemical transformations of mercury in Lake Michigan. The model simulates total suspended and resuspendable solids (TSRS), dissolved organic carbon (DOC), and total, elemental, divalent, and methylmercury as state variables. Simplified processes among the mercury state variables including net methylation, net reduction of divalent mercury, and reductive demethylation are incorporated in the model. Volatilization of elemental mercury as a kinetic (phase transfer) process and partitioning of total, divalent, and methylmercury as a set of instantaneous equilibrium processes were also simulated. The model was calibrated to data collected in 1994 and 1995 and corroborated by comparing model output generated from a long-term model hindcast to total mercury measured in high quality sediment profiles. Model hindcast predictions of total mercury in the water column were within estimates of total mercury calculated from observed lake trout bioaccumulation factors. Using the model, a mass budget assessment of mercury cycling in the lake was conducted. Atmospheric deposition, including wet and dry (particle) deposition and absorption of gaseous divalent mercury, was the dominant source of total mercury to the lake, followed by sediment resuspension, and then tributary loads. The major loss mechanism of total mercury from the water was associated with the settling of solids, followed by net volatilization. Methylmercury loading associated with wet deposition was the dominant source to the lake, followed by tributary loadings, and in situ net methylation.