Heleen A. de Wit | Search USGS

USGS2025

The effects of forest harvesting on total and methylmercury concentrations in surface waters depend on harvest practices and physical site characteristics

Forest harvesting can lead to mercury (Hg) mobilization from soils to aquatic habitats and promote the transformation of inorganic Hg to highly neurotoxic and bioaccumulative methyl-Hg (MeHg). Multiple past studies reveal broad variation of stream water MeHg and total Hg (THg) concentrations responses to forest harvesting, which has confounded messaging to forest and resource managers. To advance beyond divergent and sometimes contradictory findings, we synthesize information for 23 previously studied catchments in North America and Fennoscandia, and compiled a uniform set of soil, landscape, and harvesting properties to identify forest management, riparian, and hillslope factors that influence responses of stream water MeHg and THg concentrations. From this synthesis, we found catchments with high soil moisture and organic soil layers > 100 cm to be at highest risk for disturbance-induced increases in MeHg formation after harvest, but not necessarily affecting concentrations of MeHg in stream waters. Instead, the combination of MeHg formation in soils along with factors that affect mobilization with runoff to streams most influenced how forest harvest affects MeHg concentrations in stream waters.

Environmental Science and Technology↗

USGS2023

Response of lake metabolism to catchment inputs inferred using high-frequency lake and stream data from across the northern hemisphere

In lakes, the rates of gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP) are often controlled by resource availability. Herein, we explore how catchment vs. within lake predictors of metabolism compare using data from 16 lakes spanning 39°N to 64°N, a range of inflowing streams, and trophic status. For each lake, we combined stream loads of dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP) with lake DOC, TN, and TP concentrations and high frequency in situ monitoring of dissolved oxygen. We found that stream load stoichiometry indicated lake stoichiometry for C : N and C : P ( r 2 = 0.74 and r 2 = 0.84, respectively), but not for N : P ( r 2 = 0.04). As we found a strong positive correlation between TN and TP, we only used TP in our statistical models. For the catchment model, GPP and R were best predicted by DOC load, TP load, and load N : P ( R 2 = 0.85 and R 2 = 0.82, respectively). For the lake model, GPP and R were best predicted by TP concentrations ( R 2 = 0.86 and R 2 = 0.67, respectively). The inclusion of N : P in the catchment model, but not the lake model, suggests that both N and P regulate metabolism and that organisms may be responding more strongly to catchment inputs than lake resources. Our models predicted NEP poorly, though it is unclear why. Overall, our work stresses the importance of characterizing lake catchment loads to predict metabolic rates, a result that may be particularly important in catchments experiencing changing hydrologic regimes related to global environmental change.

Limnology & Oceanography↗