Integrating time-series and spatial surveys to assess annual, lake-wide emissions of carbon dioxide and methane from a eutrophic lake

Lakes are important regulators of global carbon cycling and conduits of greenhouse gases to the atmosphere; however, most efflux estimates for individual lakes are based on extrapolations from a limited number of locations. Within-lake variability in carbon dioxide (CO2) and methane (CH4) arises from differences in water sources, physical mixing, and biogeochemical transformations; all of which can vary at multiple temporal and spatial scales. We mapped surface water concentrations of CO2 and CH4 weekly across Lake Mendota (a 39.9 km2 eutrophic lake in Wisconsin, USA) spanning the majority of the 2016 ice-free season (249 days). Combining these maps with a spatially explicit gas transfer velocity (k) model, we estimated the diffusive exchange of both gases with the atmosphere taking into account both spatial and temporal heterogeneity. The cumulative efflux of CO2 (85.3 Mmol) and CH4 (9.47 Mmol) was positive, indicating that on the annual scale Lake Mendota was a net-source of both gases to the atmosphere. Although our model included variability in k, flux patterns reflected the patterns in gas concentrations. During the stratified period, CO2 was generally undersaturated throughout the pelagic zone due to high primary production and differed near river inlets and shorelines. The lake was routinely extremely supersaturated with CH4 with elevated concentrations in expansive littoral areas. During fall mixis, concentrations of both gases increased and became more variable across the lake surface, and their spatial arrangement changed reflecting hypolimentic mixing. In this system, samples collected from the lake center reasonably well-represented the lake-wide mean CO2 concentration, but they poorly represented CH4. While metabolic processes driving CO2 varied across the lake surface, pelagic phytoplankton contributed extensively to overall primary production, which acted at the lake-wide scale. Additionally Lake Mendota's high alkalinity may have masked the metabolic imprint on CO2 patterns. In contrast, heterogeneous CH4 transformations and transport lead to remarkable variation in CH4 across the lake surface that was dynamic through time. Thus, extrapolations from a limited number of locations or timepoints may not adequately describe lake-wide CH4 dynamics.