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Gu, Baohua

Publications and source records attributed to Gu, Baohua.

38 records · Page 3

Mercury methylation potential in a sand dune on Lake Michigan's eastern shoreline

Lake Michigan hosts the largest freshwater sand dune system in the world and is economically important for the fishery industry and tourism. Due to industrial pollution and atmospheric mercury (Hg) deposition, toxic levels of methylmercury (MeHg) have been found in the Lake biota, but little information is known regarding MeHg sources and Hg methylation potential in the shoreline sand dunes. In this study, we conducted anaerobic incubation experiments with beach sands collected from Ludington, Michigan, and examined the effects of organic carbon substrate addition, inorganic nitrogen, and mineral magnetite on Hg methylation. Despite nutrient poor and low-organic carbon conditions, appreciable Hg methylation activity coupled with carbon degradation was observed in the sands. Addition of acetate as a carbon source substantially increased MeHg production from 2 to 380 ng/kg sediment while acetate was rapidly degraded in the first 19 days of incubation. Ammonium addition showed little influence on carbon degradation or Hg methylation, whereas iron oxide addition (~1% dry weight) significantly inhibited both carbon degradation and MeHg production (by up to 90%), highlighting strongly coupled interactions between microbes, carbon substrates, and minerals. This research demonstrates the potential of microbial Hg methylation in the sand dunes, which may play a role in MeHg input and bioaccumulation in the Lake Michigan ecosystem.

54 ENVIRONMENTAL SCIENCES↗

Mechanistic Modeling of Microtopographic Impacts on CO 2 and CH 4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM-Microbe Model

Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO 2 and CH 4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO 2 and CH 4 fluxes across seven landscape types in Utqia&#289vik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO 2 and CH 4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH 4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO 2 + H 2 ) is the most important factor determining CH 4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH 4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH 4 fluxes. The model underestimated the EC-measured CH 4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH 4 flux. The strong microtopographic impacts on CO 2 and CH 4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape.

54 ENVIRONMENTAL SCIENCES↗