Nitrate (NO₃^-) removal from aquatic ecosystems involves several microbially mediated processes, including denitrification, dissimilatory nitrate reduction to ammonium (DNRA), and anaerobic ammonium oxidation (anammox), controlled by slight changes in environmental gradients. In addition, some of these processes (i.e. denitrification) may involve the production of undesirable compounds such as nitrous oxide (N₂O), an important greenhouse gas. Saline lakes are prone to the accumulation of anthropogenic contaminants, making them highly vulnerable environments to NO₃^- pollution. The aim of this paper was to investigate the effect of light and oxygen on the different NO₃^- removal pathways under highly saline conditions. For this purpose, mesocosm experiments were performed using lacustrine, undisturbed, organic-rich sediments from the Pétrola Lake (Spain), a highly saline waterbody subject to anthropogenic NO₃^- pollution. The revised ¹⁵N-isotope pairing technique (¹⁵N-IPT) was used to determine NO₃^- sink processes. Our results demonstrate for the first time the coexistence of denitrification, DNRA, and anammox processes in a highly saline lake, and how their contribution was determined by environmental conditions (oxygen and light). DNRA, and especially denitrification to N₂O, were the dominant nitrogen (N) removal pathways when oxygen and/or light were present (up to 82%). In contrast, anoxia and darkness promoted NO₃^- reduction by DNRA (52%), combined with N loss by anammox (28%). Our results highlight the role of coupled DNRA-anammox, which has not yet been investigated in lacustrine sediments. We conclude that anoxia and darkness favored DNRA and anammox processes over denitrification and therefore to restrict N₂O emissions to the atmosphere.

Boreal lakes are the most abundant lakes on Earth. Changes in acid rain deposition, climate, and catchment land use have increased lateral fluxes of terrestrial dissolved organic matter (DOM), resulting in a widespread browning of boreal freshwaters. This browning affects the aqueous communities and ecosystem processes, and boost emissions of the greenhouse gases (GHG) CH₄, CO₂, and N₂O. In this study, we predicted biotic saturation of GHGs in boreal lakes by using a set of chemical, hydrological, climate, and land use parameters. For this purpose, concentrations of GHGs and nutrients (organic C, -P, and -N) were determined in surface water samples from 73 lakes in south-eastern Norway covering wide ranges in DOM and nutrient concentrations, as well as catchment properties and land use. The spatial variation in saturation of each GHG is related to explanatory variables. Catchment characteristics (hydrological and climate parameters) such as lake size and summer precipitation, as well as NDVI, were key determinants when fitting GAM models for CH₄ and CO₂ saturation (explaining 71 and 54%, respectively), while summer precipitation and land use data were the best predictors for the N₂O saturation, explaining almost 50% of deviance. Our results suggest that lake size, precipitation, and terrestrial primary production in the watershed control the saturation of GHG in boreal lakes. These predictions based on the 73-lake dataset was validated against an independent dataset from 46 lakes in the same region. Together, this provides an improved understanding of drivers and spatial variation in GHG saturation in boreal lakes across wide gradients of lake and catchment properties. The assessment highlights the need to incorporate multiple explanatory parameters in prediction models of GHGs for extrapolation across the boreal biome.