To understand the carbon and energy exchange between the lake surface and the atmosphere, direct measurements of latent, sensible heat, and CO₂ fluxes were taken using the eddy covariance (EC) technique in Western Lake Erie during October 2011 to September 2013. We found that the latent heat flux (LE) had a marked one‐peak seasonal change in both years that differed from the diurnal course and lacked a sinusoidal dynamic common in terrestrial ecosystems. Daily mean LE was 4.8 ± 0.1 and 4.3 ± 0.2 MJ m⁻² d⁻¹ in Year 1 and Year 2, respectively. The sensible heat flux (H) remained much lower than the LE, with a daily mean of 0.9 ± 0.1 and 1.1 ± 0.1 MJ m⁻² d⁻¹ in Year 1 and Year 2, respectively. As a result, the Bowen ratio was <1 during most of the 2 year period, with the lowest summer value at 0.14. The vapor pressure deficit explained 35% of the variation in half hourly LE, while the temperature difference between the water surface and air explained 65% of the variation in half hourly H. Western Lake Erie acted as a small carbon sink holding −19.0 ± 5.4 and −40.2 ± 13.3 g C m⁻² in the first and second summers (May–September) but as an annual source of 77.7 ± 18.6 and 49.5 ± 17.9 g C m⁻² yr⁻¹ in Year 1 and Year 2, respectively. The CO₂ flux ( ) rate varied from −0.45 g C m⁻² d⁻¹ to 0.98 g C m⁻² d⁻¹. Similar to LE, had noticeable diurnal changes during the months that had high chlorophyll a months but not during other months. A significantly negative correlation (P < 0.05) was found between and chlorophyll a on monthly fluxes. Three gap‐filling methods, including marginal distribution sampling, mean diurnal variation, and monthly mean, were quantitatively assessed, yielding an uncertainty of 4%, 6%, and 10% in LE, H, and , respectively.

In recent years, the increased intensity and duration of droughts have dramatically altered the structure and function of grassland ecosystems, which have been forced to adapt to this change in climate. Combinations of global change drivers such as elevated atmospheric CO₂ concentration, warming, nitrogen (N) deposition, grazing, and land-use change have influenced the impact that droughts have on grassland C cycling. This influence, to some extent, can modify the relationship between droughts and grassland carbon (C) cycling in the multi-factor world. Unfortunately, prior reviews have been primarily anecdotal from the 1930s to the 2010s. We investigated the current state of the study on the interactive impacts of multiple factors under drought scenarios in grassland C cycling and provided scientific advice for dealing with droughts and managing grassland C cycling in a multi-factor world. Currently, adequate information is not available on the interaction between droughts and global change drivers, which would advance our understanding of grassland C cycling responses. It was determined that future experiments and models should specifically test how droughts regulate grassland C cycling under global changes. Previous multi-factor experiments of current and future global change conditions have studied various drought scenarios poorly, including changes in precipitation frequency and amplitude, timing, and interactions with other global change drivers. Multi-factor experiments have contributed to quantifying these potential changes and have provided important information on how water affects ecosystem processes under global change. There is an urgent need to establish a systematic framework that can assess ecosystem dynamic responses to droughts under current and future global change and human activity, with a focus on the combined effects of droughts, global change drivers, and the corresponding hierarchical responses of an ecosystem.

Lakes are important components for regulating carbon cycling within landscapes. Most lakes are regarded as CO₂ sources to the atmosphere, except for a few eutrophic ones. Algal blooms are common phenomena in many eutrophic lakes and can cause many environmental stresses, yet their effects on the net exchange of CO₂ (F_CO2) at large spatial scales have not been adequately addressed. We integrated remote sensing and Eddy Covariance (EC) technologies to investigate the effects that algal blooms have on F_CO2 in the western basin of Lake Erie—a large lake infamous for these blooms. Three years of long-term EC data (2012–2014) at two sites were analyzed. We found that at both sites: (1) daily F_CO2 significantly correlated with daily temperature, light, and wind speed during the algal bloom periods; (2) monthly F_CO2 was negatively correlated with chlorophyll-a concentration; and (3) the year with larger algal blooms was always associated with lower carbon emissions. We concluded that large algal blooms could reduce carbon emissions in the western basin of Lake Erie. However, considering the complexity of processes within large lakes, the weak relationship we found, and the potential uncertainties that remain in our estimations of F_CO2 and chlorophyll-a, we argue that additional data and analyses are needed to validate our conclusion and examine the underlying regulatory mechanisms.