Nitrate removal, communities of denitrifiers and adverse effects in different carbon substrates for use in denitrification beds

Denitrification beds are containers filled with wood by-products that serve as a carbon and energy source to denitrifiers, which reduce nitrate (NO₃⁻) from point source discharges into non-reactive dinitrogen (N₂) gas. This study investigates a range of alternative carbon sources and determines rates, mechanisms and factors controlling NO₃⁻ removal, denitrifying bacterial community, and the adverse effects of these substrates. Experimental barrels (0.2 m³) filled with either maize cobs, wheat straw, green waste, sawdust, pine woodchips or eucalyptus woodchips were incubated at 16.8 °C or 27.1 °C (outlet temperature), and received NO₃⁻enriched water (14.38 mg N L⁻¹and 17.15 mg N L⁻¹). After 2.5 years of incubation measurements were made of NO₃⁻–N removal rates, in vitro denitrification rates (DR), factors limiting denitrification (carbon and nitrate availability, dissolved oxygen, temperature, pH, and concentrations of NO₃⁻, nitrite and ammonia), copy number of nitrite reductase (nirS and nirK) and nitrous oxide reductase (nosZ) genes, and greenhouse gas production (dissolved nitrous oxide (N₂O) and methane), and carbon (TOC) loss. Microbial denitrification was the main mechanism for NO₃⁻–N removal. Nitrate–N removal rates ranged from 1.3 (pine woodchips) to 6.2 g N m⁻³ d⁻¹ (maize cobs), and were predominantly limited by C availability and temperature (Q₁₀ = 1.2) when NO₃⁻–N outlet concentrations remained above 1 mg L⁻¹. The NO₃⁻–N removal rate did not depend directly on substrate type, but on the quantity of microbially available carbon, which differed between carbon sources. The abundance of denitrifying genes (nirS, nirK and nosZ) was similar in replicate barrels under cold incubation, but varied substantially under warm incubation, and between substrates. Warm incubation enhanced growth of nirS containing bacteria and bacteria that lacked the nosZ gene, potentially explaining the greater N2O emission in warmer environments. Maize cob substrate had the highest NO₃⁻–N removal rate, but adverse effects include TOC release, dissolved N₂O release and substantial carbon consumption by non-denitrifiers. Woodchips removed less than half of NO₃⁻ removed by maize cobs, but provided ideal conditions for denitrifying bacteria, and adverse effects were not observed. Therefore we recommend the combination of maize cobs and woodchips to enhance NO₃⁻ removal while minimizing adverse effects in denitrification beds

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 39oN to 64oN, 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 (r2 = 0.74 and r2 = 0.84, respectively), but not for N : P (r2 = 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 (R2 = 0.85 and R2 = 0.82, respectively). For the lake model, GPP and R were best predicted by TP concentrations (R2 = 0.86 and R2 = 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

Global patterns and drivers of ecosystem functioning in rivers and riparian zones

Abstract River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth’s biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented “next-generation biomonitoring” by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale