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Current estimates of carbon dioxide (CO2) evasion from Arctic lakes are highly uncertain because few studies integrate seasonal variability, specifically evasion during spring ice-melt. We quantified annual CO2 evasion for 14 clear-water Arctic lakes in Northern Sweden through mass balance (ice-melt period) and high-frequency loggers (open-water period). On average, 80% (SD: ± 18) of annual CO2 evasion occurred within 10 d following ice-melt. The contribution of the ice-melt period to annual CO2 evasion was high compared to earlier studies of Arctic lakes (47% ± 32%). Across all lakes, the proportion of ice-melt : annual CO2 evasion was negatively related to the dissolved organic carbon concentration and positively related to the mean depth of the lakes. The results emphasize the need for measurements of CO2 exchange at ice-melt to accurately quantify CO2 evasion from Arctic lakes.

Metabolism is one of the most fundamental ecosystem processes, but the drivers of variation in metabolic rates among lakes dominated by benthic primary producers remain poorly constrained. Here, we report the magnitudes and potential drivers of whole-lake metabolism across 43 Swedish arctic–alpine lakes, based on the free-water diel oxygen technique with sondes deployed during the open-water season near the surface and bottom of the lakes. Gross primary production (GPP) and ecosystem respiration (R) were strongly coupled and ranged from 0.06 to 0.45 mg and 0.05 to 0.43 mg L⁻¹ d⁻¹ among lakes. On average, GPP and R decreased eightfold from relatively shallow to deep lakes (mean depth 0.5–10.9 m) and twofold from concave to convex lakes (mean depth: maximum depth 0.2–0.5). We attribute this to light limitation and shape-specific sensitivity of benthic GPP to disturbance by lake ice. Net ecosystem production (GPP-R) ranged from −0.09 to 0.14 mg L⁻¹ d⁻¹ and switched, on average, from positive to negative towards deeper lakes and lakes richer in dissolved organic carbon (DOC; 0.5–7.4 mg DOC L⁻¹). Uncertainties in metabolism estimates were high (around one and three times mean R and GPP), especially in deep lakes with low insulation and diurnally variable wind speed. Our results confirm the role of DOC in stimulating net heterotrophy and highlight novel effects of lake shape on productivity in benthic-dominated lake ecosystems and its response to changes in lake ice cover.

Aim: Although running waters are getting recognized as important methane sources, large‐scale geographical patterns of microorganisms controlling the net methane balance of streams are still unknown. Here we aim at describing community compositions of methanogenic and methanotrophic microorganisms at large spatial scales and at linking their abundances to potential sediment methane production (PMP) and oxidation rates (PMO).

Location: The study spans across 16 European streams from northern Spain to northern Sweden and from western Ireland to western Bulgaria.

Taxon: Methanogenic archaea and methane‐oxidizing microorganisms.

Methods: To provide a geographical overview of both groups in a single approach, microbial communities and abundances were investigated via 16S rRNA gene sequencing, extracting relevant OTUs based on literature; both groups were quantified via quantitative PCR targeting mcrA and pmoA genes and studied in relation to environmental parameters, sediment PMP and PMO, and land use.

Results: Diversity of methanogenic archaea was higher in warmer streams and of methanotrophic communities in southern sampling sites and in larger streams. Anthropogenically altered, warm and oxygen‐poor streams were dominated by the highly efficient methanogenic families Methanospirillaceae, Methanosarcinaceae and Methanobacteriaceae, but did not harbour any specific methanotrophic organisms. Contrastingly, sediment communities in colder, oxygen‐rich waters with little anthropogenic impact were characterized by methanogenic Methanosaetaceae, Methanocellaceae and Methanoflorentaceae and methanotrophic Methylococcaceae and Cd. Methanoperedens. Representatives of the methanotrophic Crenotrichaceae and Methylococcaceae as well as the methanogenic Methanoregulaceae were characteristic for environments with larger catchment area and higher discharge. PMP increased with increasing abundance of methanogenic archaea, while PMO rates did not show correlations with abundances of methane‐oxidizing bacteria.

Main conclusions: Methanogenic and methanotrophic communities grouping into three habitat types suggest that future climate‐ and land use changes may influence the prevailing microbes involved in the large‐scale stream‐related methane cycle, favouring the growth of highly efficient hydrogenotrophic methane producers. Based on these results, we expect global change effect on PMP rates to especially impact rivers adjacent to anthropogenically disturbed land uses.

Globally, inland waters emit over 2 Pg of carbon per year as carbon dioxide, of which the majority originates from streams and rivers. Despite the global significance of fluvial carbon dioxide emissions, little is known about their diel dynamics. Here we present a large-scale assessment of day- and night-time carbon dioxide fluxes at the water-air interface across 34 European streams. We directly measured fluxes four times between October 2016 and July 2017 using drifting chambers. Median fluxes are 1.4 and 2.1mmolm(-2) h(-1) at midday and midnight, respectively, with night fluxes exceeding those during the day by 39%. We attribute diel carbon dioxide flux variability mainly to changes in the water partial pressure of carbon dioxide. However, no consistent drivers could be identified across sites. Our findings highlight widespread day-night changes in fluvial carbon dioxide fluxes and suggest that the time of day greatly influences measured carbon dioxide fluxes across European streams. Diel patterns can greatly impact total stream carbon dioxide emissions, with 39% greater carbon dioxide flux during the night-time relative to the day-time, according to a study of 34 streams across Europe.

Oxygen depletion in lake bottom waters has adverse impacts on ecosystem health including decreased water quality from release of nutrients and reduced substances from sediments, and the reduction of fish growth and reproduction. Depletion occurs when oxygen is consumed during decomposition of organic matter, and oxygen replenishment is limited by water column stratification. Arctic–alpine lakes are often well mixed and oxygenated, but rapid climate change in these regions is an important driver of shifts in catchment vegetation that could affect the mixing and oxygen dynamics of lakes. Here, we analyze high-resolution time series of dissolved oxygen concentration and temperature profiles in 40 Swedish arctic–alpine lakes across the tree line ecotone. The lakes stratified for 1−125 days, and during stratification, near-bottom dissolved oxygen concentrations changed by −0.20 to +0.15 mg L−1 day−1, resulting in final concentrations of 1.1−15.5 mg L−1 at the end of the longest stratification period. Structural equation modeling revealed that lakes with taller shoreline vegetation relative to lake area had higher dissolved organic carbon concentrations and oxygen consumption rates, but also lower wind speeds and longer stratification periods, and ultimately, lower near-bottom dissolved oxygen concentrations. We use an index of shoreline canopy height and lake area to predict variations among our study lakes in near-bottom dissolved oxygen concentrations at the end of the longest stratification period (R2 = 0.41). Upscaling this relationship to 8392 Swedish arctic–alpine lakes revealed that near-bottom dissolved oxygen concentrations drop below 3, 5, and 7 mg L−1 in 15%, 32%, and 53% of the lakes and that this proportion is sensitive (5%−22%, 13%−45%, and 29%−69%) to hypothetical tree line shifts observed in the past century or reconstructed for the Holocene (±200 m elevation; ±0.5° latitude). Assuming space-for-time substitution, we predict that tree line advance will decrease near-bottom dissolved oxygen concentrations in many arctic–alpine lakes.

Estimating air-water gas transfer velocities (k) is integral to understand biogeochemical and ecological processes in aquatic systems. In lakes, k is commonly predicted using wind-based empirical models, however, their predictive performance under conditions that differ from their original calibration remains largely unassessed. Here, we collected 2222 published k estimates derived from various methods in 46 globally distributed lakes to (1) evaluate the predictions of a selection of six available wind-speed based k models for lakes and (2) explore and develop new empirical models to predict k over global lakes. We found that selected k models generally performed poorly in predicting k in lakes. Model predictions were more accurate than simply assuming a mean k in only 2-39% of all lakes, however, we could not identify with confidence the specific conditions in which some models outperformed others. We developed new wind-based models in which additional variables describing the spatial coverage of k estimates and the lake size and shape had a significant effect on the wind speed-k relationship. Although these new models did not fit the global dataset significantly better than previous k models, they generate overall less biased predictions for global lakes. We further provide explicit estimates of prediction errors that integrate methodological and lake-specific uncertainties. Our results highlight the potential limits when using wind-based models to predict k across lakes and urge scientists to properly account for prediction errors, or measure k directly in the field whenever possible.

Metabolic stoichiometry predicts that dissolved oxygen (O₂) and carbon dioxide (CO₂) in aquatic ecosystems should covary inversely; however, field observations often diverge from theoretical expectations. Here, we propose a suite of metrics describing this O₂ and CO₂ decoupling and introduce a conceptual framework for interpreting these metrics within aquatic ecosystems. Within this framework, we interpret cross‐system patterns of high‐frequency O₂ and CO₂ measurements in 11 northern lakes and extract emergent insights into the metabolic behavior and the simultaneous roles of chemical and physical forcing in shaping ecosystem processes. This approach leverages the power of high‐frequency paired O₂–CO₂ measurements, and yields a novel, integrative aquatic system typology which can also be applicable more broadly to streams and rivers, wetlands and marine systems.

Carbon dioxide (CO2) concentrations in lakes vary strongly over time. This variability is rarely captured by environmental monitoring but is crucial for accurately assessing the magnitude of lake CO2 emissions. However, it is unknown to what extent temporal variability needs to be captured to understand important drivers of lake carbon cycling such as climate and land management. We used environmental monitoring data of Swedish forest lakes collected in autumn (n = 439) and throughout the whole open water season (n = 22) from a wet and a dry year to assess temporal variability in effects of climate and forestry on CO2 concentrations across lakes. Effects differed depending on the season and year sampled. According to cross-lake comparisons based on autumn data, CO2 concentrations increased with annual mean air temperature (dry year) or catchment forest productivity (wet year) but were not related to colored dissolved organic matter concentrations. In contrast, open water-season averaged CO2 concentrations were similar across temperature and productivity gradients but increased with colored dissolved organic matter. These contradictions resulted from scale mismatches in input data, lead to weak explanatory power (R-2 = 9-32%), and were consistent across published data from 79 temperate, boreal, and arctic lakes. In a global survey of 144 published studies, we identified a trade-off between temporal and spatial coverage of CO2 sampling. This trade-off clearly determines which conclusions are drawn from landscape-scale CO(2 )assessments. Accurate evaluations of the effects of climate and land management require spatially and temporally representative data that can be provided by emerging sensor technologies and forms of collaborative sampling.

Air–water gas exchange velocities (k) are critical components of many biogeochemical and ecological process studies in aquatic systems. However, their high spatiotemporal variability is difficult to capture with traditional methods, especially in turbulent flow. Here, we investigate the potential of sound spectral analysis to infer k in running waters, based on the rationale that both turbulence and entrained bubbles drive gas exchange and cause a characteristic sound. We explored the relationship between k and sound spectral properties using laboratory experiments and field observations under a wide range of turbulence and bubble conditions. We estimated k using flux chamber measurements of CO₂ exchange and recorded sound above and below the water surface by microphones and hydrophones, respectively. We found a strong influence of turbulence and bubbles on sound pressure levels (SPLs) at octave bands of 31.5 Hz and 1000 Hz, respectively. The difference in SPLs at these bands and background noise bands showed a linear correlation with k both in the laboratory (R² = 0.93–0.99) and in the field (median R² = 0.42–0.90). Underwater sound indices outperformed aerial sound indices in general, and indices based on hydraulic parameters in particular, in turbulent and bubbly surface flow. The results highlight the unique potential of acoustic techniques to predict k, isolate mechanisms, and improve the spatiotemporal coverage of k estimates in bubbly flow.

In seasonally ice‐covered lakes, carbon dioxide (CO₂) and methane (CH₄) emission at ice‐off can account for a significant fraction of the annual budget. Yet knowledge of the mechanisms controlling below lake‐ice carbon (C) dynamics and subsequent CO₂ and CH₄ emissions at ice‐off is limited. To understand the control of below ice C dynamics, and C emissions in spring, we measured spatial variation in CO₂, CH₄, and dissolved inorganic and organic carbon from ice‐on to ice‐off, in a small boreal lake during a winter with sporadic melting events. Winter melt events were associated with decreased surface water DOC in the forest‐dominated basin and increased surface water CH₄ in the mire‐dominated basin. At the whole‐lake scale, CH₄ accumulated below ice throughout the winter, whereas CO₂ accumulation was greatest in early winter. Mass‐balance estimates suggest that, in addition to the CO₂ and CH₄ accumulated during winter, external inputs of CO₂ and CH₄ and internal processing during ice‐melt could represent significant sources of C gas emissions during ice‐off. Moreover, internal processing of CO₂ and CH₄ worked in opposition, with production of CO₂ and oxidation of CH₄ dominating at ice‐off. These findings have important implications for how small boreal lakes will respond to warmer winters in the future; increased winter melt events will likely increase external inputs below ice and thus alter the extent and timing of CO₂ and CH₄ emissions to the atmosphere at ice‐off.