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Methane (CH 4 ) strongly contributes to observed global warming. As natural CH 4 emissions mainly originate from wet ecosystems, it is important to unravel how climate change may affect these emissions. This is especially true for ebullition (bubble flux from sediments), a pathway that has long been underestimated but generally dominates emissions. Here we show a remarkably strong relationship between CH 4 ebullition and temperature across a wide range of freshwater ecosystems on different continents using multi-seasonal CH 4 ebullition data from the literature. As these temperature–ebullition relationships may have been affected by seasonal variation in organic matter availability, we also conducted a controlled year-round mesocosm experiment. Here 4 °C warming led to 51% higher total annual CH 4 ebullition, while diffusion was not affected. Our combined findings suggest that global warming will strongly enhance freshwater CH 4 emissions through a disproportional increase in ebullition (6–20% per 1 °C increase), contributing to global warming. The impacts of climate change on natural methane (CH 4 ) emissions via ebullition are unclear. Here, using published and experimental multi-seasonal CH 4 ebullition data, the authors find a strong relationship between CH 4 ebullition and temperature across a wide range of freshwater ecosystems globally.

Lakes and wetlands, common ecosystems of the high northern latitudes, exchange large amounts of the climate-forcing gases methane (CH4) and carbon dioxide (CO2) with the atmosphere. The magnitudes of these fluxes and the processes driving them are still uncertain, particularly for subarctic and Arctic lakes where direct measurements of CH4 and CO2 emissions are often of low temporal resolution and are rarely sustained throughout the entire year. Using the eddy covariance method, we measured surface–atmosphere exchange of CH4 and CO2 during 2.5 years in a thawed fen and a shallow lake of a subarctic peatland complex. Gas exchange at the fen exhibited the expected seasonality of a subarctic wetland with maximum CH4 emissions and CO2 uptake in summer, as well as low but continuous emissions of CH4 and CO2 throughout the snow-covered winter. The seasonality of lake fluxes differed, with maximum CO2 and CH4 flux rates recorded at spring thaw. During the ice-free seasons, we could identify surface CH4 emissions as mostly ebullition events with a seasonal trend in the magnitude of the release, while a net CO2 flux indicated photosynthetic activity. We found correlations between surface CH4 emissions and surface sediment temperature, as well as between diel CO2 uptake and diel solar input. During spring, the breakdown of thermal stratification following ice thaw triggered the degassing of both CH4 and CO2. This spring burst was observed in 2 consecutive years for both gases, with a large inter-annual variability in the magnitude of the CH4 degassing. On the annual scale, spring emissions converted the lake from a small CO2 sink to a CO2 source: 80 % of total annual carbon emissions from the lake were emitted as CO2. The annual total carbon exchange per unit area was highest at the fen, which was an annual sink of carbon with respect to the atmosphere. Continuous respiration during the winter partly counteracted the fen summer sink by accounting for, as both CH4 and CO2, 33 % of annual carbon exchange. Our study shows (1) the importance of overturn periods (spring or fall) for the annual CH4 and CO2 emissions of northern lakes, (2) the significance of lakes as atmospheric carbon sources in subarctic landscapes while fens can be a strong carbon sink, and (3) the potential for ecosystem-scale eddy covariance measurements to improve the understanding of short-term processes driving lake–atmosphere exchange of CH4 and CO2.

Aquatic ecosystems are major sources of greenhouse gases (GHGs). Robust measurements of natural GHG emissions are vital for evaluating regional to global carbon budgets and for assessing climate feedbacks of natural emissions to improve climate models. Diffusive and ebullitive (bubble) transport are two major pathways of gas release from surface waters. To capture the high temporal variability of these fluxes in a well-defined footprint, we designed and built an inexpensive device that includes an easily mobile diffusive flux chamber and a bubble counter all in one. In addition to automatically collecting gas samples for subsequent various analyses in the laboratory, this device also utilized a low-cost carbon dioxide (CO2) sensor (SenseAir, Sweden) and methane (CH4) sensor (Figaro, Japan) to measure GHG fluxes. Each of the devices was equipped with an XBee module to enable local radio communication (DigiMesh network) for time synchronization and data readout at a server controller station on the lakeshore. The software of this server controller was operated on a low-cost computer (Raspberry Pi), which has a 3G connection for remote control and monitor functions from anywhere in the world. This study shows the potential of a low-cost automatic sensor network system for studying GHG fluxes on lakes in remote locations.

Northern post-glacial lakes are significant, increasing sources of atmospheric carbon through ebullition (bubbling) of microbially-produced methane (CH 4 ) from sediments. Ebullitive CH 4 flux correlates strongly with temperature, reflecting that solar radiation drives emissions. However, here we show that the slope of the temperature-CH 4 flux relationship differs spatially across two post-glacial lakes in Sweden. We compared these CH 4 emission patterns with sediment microbial (metagenomic and amplicon), isotopic, and geochemical data. The temperature-associated increase in CH 4 emissions was greater in lake middles—where methanogens were more abundant—than edges, and sediment communities were distinct between edges and middles. Microbial abundances, including those of CH 4 -cycling microorganisms and syntrophs, were predictive of porewater CH 4 concentrations. Results suggest that deeper lake regions, which currently emit less CH 4 than shallower edges, could add substantially to CH 4 emissions in a warmer Arctic and that CH 4 emission predictions may be improved by accounting for spatial variations in sediment microbiota. Arctic lakes are strong and increasing sources of atmospheric methane, but extreme conditions and limited observations hinder robust understanding. Here the authors show that microbes in the middle of Arctic lakes have elevated methane producing potential, and are poised to release even more in the future.

Lakes are sources of the greenhouse gas methane. A synthesis of measurements of methane emissions reveals that lakes and ponds above 50 °N emit 16.5 Tg methane annually, and emissions may increase by 20 to 50% with longer ice-free seasons. Lakes and ponds represent one of the largest natural sources of the greenhouse gas methane. By surface area, almost half of these waters are located in the boreal region and northwards. A synthesis of measurements of methane emissions from 733 lakes and ponds north of ∼50° N, combined with new inventories of inland waters, reveals that emissions from these high latitudes amount to around 16.5 Tg CH 4 yr −1 (12.4 Tg CH 4 -C yr −1 ). This estimate — from lakes and ponds alone — is equivalent to roughly two-thirds of the inverse model calculation of all natural methane sources in the region. Thermokarst water bodies have received attention for their high emission rates, but we find that post-glacial lakes are a larger regional source due to their larger areal extent. Water body depth, sediment type and ecoclimatic region are also important in explaining variation in methane fluxes. Depending on whether warming and permafrost thaw cause expansion or contraction of lake and pond areal coverage, we estimate that annual water body emissions will increase by 20–54% before the end of the century if ice-free seasons are extended by 20 days. We conclude that lakes and ponds are a dominant methane source at high northern latitudes.

Lakes and reservoirs contribute to regional carbon budgets via significant emissions of climate forcing trace gases. Here, for improved modelling, we use 8 years of floating chamber measurements from three small, shallow subarctic lakes (2010–2017, n=1306) to separate the contribution of physical and biogeochemical processes to the turbulence-driven, diffusion-limited flux of methane (CH4) on daily to multi-year timescales. Correlative data include surface water concentration measurements (2009–2017, n=606), total water column storage (2010–2017,n=237), and in situ meteorological observations. We used the last to compute near-surface turbulence based on similarity scaling and then applied the surface renewal model to compute gas transfer velocities. Chamber fluxes averaged 6.9±0.3 mg CH4 m-2 d-1 and gas transfer velocities (k600) averaged 4.0±0.1 cm h-1. Chamber-derived gas transfer velocities tracked the power-law wind speed relation of the model. Coefficients for the model and dissipation rates depended on shear production of turbulence, atmospheric stability, and exposure to wind. Fluxes increased with wind speed until daily average values exceeded 6.5 m s-1, at which point emissions were suppressed due to rapid water column degassing reducing the water–air concentration gradient. Arrhenius-type temperature functions of the CH4 flux (Ea′=0.90±0.14 eV) were robust (R2≥0.93, p<0.01) and also applied to the surface CH4 concentration (Ea′=0.88±0.09 eV). These results imply that emissions were strongly coupled to production and supply to the water column. Spectral analysis indicated that on timescales shorter than a month, emissions were driven by wind shear whereas on longer timescales variations in water temperature governed the flux. Long-term monitoring efforts are essential to identify distinct functional relations that govern flux variability on timescales of weather and climate change.

Lakes and reservoirs contribute to regional carbon budgets via significant emissions of climate forcing trace gases. Here, for improved modelling, we use 8 years of floating chamber measurements from three small, shallow subarctic lakes (2010-2017, n=1306) to separate the contribution of physical and biogeochemical processes to the turbulence-driven, diffusion-limited flux of methane (CH.sub.4) on daily to multi-year timescales. Correlative data include surface water concentration measurements (2009-2017, n=606), total water column storage (2010-2017, n=237), and in situ meteorological observations. We used the last to compute near-surface turbulence based on similarity scaling and then applied the surface renewal model to compute gas transfer velocities. Chamber fluxes averaged 6.9±0.3 mg CH.sub.4  m.sup.-2  d.sup.-1 and gas transfer velocities (k.sub.600) averaged 4.0±0.1 cm h.sup.-1 . Chamber-derived gas transfer velocities tracked the power-law wind speed relation of the model. Coefficients for the model and dissipation rates depended on shear production of turbulence, atmospheric stability, and exposure to wind. Fluxes increased with wind speed until daily average values exceeded 6.5 m s.sup.-1, at which point emissions were suppressed due to rapid water column degassing reducing the water-air concentration gradient. Arrhenius-type temperature functions of the CH.sub.4 flux (Ea'=0.90±0.14 eV) were robust (R.sup.2 â¥0.93, p0.01) and also applied to the surface CH.sub.4 concentration (Ea'=0.88±0.09 eV). These results imply that emissions were strongly coupled to production and supply to the water column. Spectral analysis indicated that on timescales shorter than a month, emissions were driven by wind shear whereas on longer timescales variations in water temperature governed the flux. Long-term monitoring efforts are essential to identify distinct functional relations that govern flux variability on timescales of weather and climate change.

Lakes and reservoirs contribute to regional carbon budgets via significant emissions of climate forcing trace gases. Here, for improved modelling, we use 8 years of floating chamber measurements from three small, shallow subarctic lakes (2010–2017, n=1306) to separate the contribution of physical and biogeochemical processes to the turbulence-driven, diffusion-limited flux of methane (CH4) on daily to multi-year timescales. Correlative data include surface water concentration measurements (2009–2017, n=606), total water column storage (2010–2017, n=237), and in situ meteorological observations. We used the last to compute near-surface turbulence based on similarity scaling and then applied the surface renewal model to compute gas transfer velocities. Chamber fluxes averaged 6.9±0.3 mg CH4 m−2 d−1 and gas transfer velocities (k600) averaged 4.0±0.1 cm h−1. Chamber-derived gas transfer velocities tracked the power-law wind speed relation of the model. Coefficients for the model and dissipation rates depended on shear production of turbulence, atmospheric stability, and exposure to wind. Fluxes increased with wind speed until daily average values exceeded 6.5 m s−1, at which point emissions were suppressed due to rapid water column degassing reducing the water–air concentration gradient. Arrhenius-type temperature functions of the CH4 flux (Ea′=0.90±0.14 eV) were robust (R2≥0.93, p<0.01) and also applied to the surface CH4 concentration (Ea′=0.88±0.09 eV). These results imply that emissions were strongly coupled to production and supply to the water column. Spectral analysis indicated that on timescales shorter than a month, emissions were driven by wind shear whereas on longer timescales variations in water temperature governed the flux. Long-term monitoring efforts are essential to identify distinct functional relations that govern flux variability on timescales of weather and climate change.

Aquatic ecosystems are major sources of greenhouse gases (GHGs). Robust measurements of natural GHG emissions are vital for evaluating regional to global carbon budgets and for assessing climate feedbacks of natural emissions to improve climate models. Diffusive and ebullitive (bubble) transport are two major pathways of gas release from surface waters. To capture the high temporal variability of these fluxes in a well-defined footprint, we designed and built an inexpensive device that includes an easily mobile diffusive flux chamber and a bubble counter all in one. In addition to automatically collecting gas samples for subsequent various analyses in the laboratory, this device also utilized a low-cost carbon dioxide (CO2) sensor (SenseAir, Sweden) and methane (CH4) sensor (Figaro, Japan) to measure GHG fluxes. Each of the devices was equipped with an XBee module to enable local radio communication (DigiMesh network) for time synchronization and data readout at a server controller station on the lakeshore. The software of this server controller was operated on a lowcost computer (Raspberry Pi), which has a 3G connection for remote control and monitor functions from anywhere in the world. This study shows the potential of a low-cost automatic sensor network system for studying GHG fluxes on lakes in remote locations.

Lakes and reservoirs are important emitters of climate forcing trace gases. Various environmental drivers of the flux, such as temperature and wind speed, have been identified, but their relative importance remains poorly understood. Here we use an extensive field dataset to disentangle physical and biogeochemical controls on the turbulence-driven diffusive flux of methane (CH4) on daily to multi-year timescales. We compare 8 years of floating chamber fluxes from three small, shallow subarctic lakes (2010–2017,  n  = 1306) with fluxes computed using 9 years of surface water concentration measurements (2009–2017,  n  = 606) and a small-eddy surface renewal model informed by in situ meteorological observations. Chamber fluxes averaged 6.9 ± 0.3 mg m−2 d−1 and gas transfer velocities ( k 600) from the chamber-calibrated surface renewal model averaged 4.0 ± 0.1 cm h−1. We find robust ( R 2 ≥ 0.93,  p  < 0.01) Arrhenius-type temperature functions of the CH4 flux ( E a' = 0.90 ± 0.14 eV) and of the surface CH4 concentration ( E a' = 0.88 ± 0.09 eV). Chamber derived gas transfer velocities tracked the power-law wind speed relation of the model ( k  ∝  u 3/4). While the flux increased with wind speed, during storm events ( U 10 ≥ 6.5 m s−1) emissions were reduced by rapid water column degassing. Spectral analysis revealed that on timescales shorter than a month emissions were driven by wind shear, but on longer timescales variations in water temperature governed the flux, suggesting emissions were strongly coupled to production. Our findings suggest that accurate short- and long term projections of lake CH4 emissions can be based on distinct weather- and climate controlled drivers of the flux.