Extensive regions in the permafrost zone are projected to become climatically unsuitable to sustain permafrost peatlands over the next century, suggesting transformations in these landscapes that can leave large amounts of permafrost carbon vulnerable to post-thaw decomposition. We present three years of eddy covariance measurements of CH4 and CO2 fluxes from the degrading permafrost peatland Iskoras in Northern Norway, which we disaggregate into separate fluxes of palsa, pond, and fen areas using information provided by the dynamic flux footprint in a novel ensemble-based Bayesian deep neural network framework. The three-year mean CO2-equivalent flux is estimated to be 106 gCO2 m-2 yr-1 for palsas, 1780 gCO2 m-2 yr-1 for ponds, and -31 gCO2 m-2 yr-1 for fens, indicating that possible palsa degradation to thermokarst ponds would strengthen the local greenhouse gas forcing by a factor of about 17, while transformation into fens would slightly reduce the current local greenhouse gas forcing.

Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep-water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed Anoxia Begets Anoxia (ABA) feedback. Lakes in the dataset span a broad range of surface area (1–126,909 ha), maximum depth (6–370 m), and morphometry, with a median time series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyll-a concentrations, and oxygen demand across the 656-lake dataset. Likewise, we found further support for these relationships by analyzing time series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake-specific characteristics: for example, we found that surface phosphorus concentrations were more positively associated with chlorophyll-a in high-phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world.

Five decades of monitoring data (1974-2022) at the acidified, acid-sensitive forested catchment of Langtjern in southern Norway document strong chemical recovery and browning of surface water, related to changes in sulfur (S) deposition. We used the process-oriented model MAGIC to simulate water chemistry from 1860 to 2100 using historical and projected deposition and climate. New in MAGIC is i) a solubility control of dissolved organic carbon (DOC) from S deposition, which allows inclusion of the changing role of organic acids in chemical recovery, and ii) climate-dependency of weathering rates. MAGIC successfully described measured chemical recovery and browning, and the change towards organic acid dominated acidification status. Hindcasts of pH suggested lower preindustrial pH than previously modelled with MAGIC, simulated without sulfate-dependency of DOC solubility. Climate scenarios indicated substantially wetter climate, leading to increased base cation losses and slight reacidification of the surface waters. A sensitivity analysis of weathering rates revealed that a doubling of weathering rates is needed to reach pre-industrial ANC in 2100, given that S deposition is expected to be reduced to a minimum. We conclude that impacts of climate change are most likely to lead to slight reacidification of surface waters, and that enhanced weathering rates could partly compensate this trend.

The complexity of organic matter (OM) degradation mechanisms represents a significant challenge for developing biogeochemical models to quantify the role of aquatic sediments in the climate system. The common representation of OM by carbohydrates formulated as CHO in models comes with the assumption that its degradation by fermentation produces equimolar amounts of methane (CH) and dissolved inorganic carbon (DIC). To test the validity of this assumption, we modeled using reaction-transport equations vertical profiles of the concentration and isotopic composition (δC) of CH and DIC in the top 25 cm of the sediment column from two lake basins, one whose hypolimnion is perennially oxygenated and one with seasonal anoxia. Our results reveal that methanogenesis only occurs via hydrogenotrophy in both basins. Furthermore, we calculate, from CH and DIC production rates associated with methanogenesis, that the fermenting OM has an average carbon oxidation state (COS) below −0.9. Modeling solute porewater profiles reported in the literature for four other seasonally anoxic lake basins also yields negative COS values. Collectively, the mean (±SD) COS value of −1.4 ± 0.3 for all the seasonally anoxic sites is much lower than the value of zero expected from carbohydrates fermentation. We conclude that carbohydrates do not adequately represent the fermenting OM and that the COS should be included in the formulation of OM fermentation in models applied to lake sediments. This study highlights the need to better characterize the labile OM undergoing mineralization to interpret present-day greenhouse gases cycling and predict its alteration under environmental changes.