Nine years (2003–2011) of carbon dioxide (CO2) flux were measured at a black spruce forest in interior Alaska using the eddy covariance method. Seasonal and interannual variations in the gross ...primary productivity (GPP) and ecosystem respiration (RE) were associated primarily with air temperature: warmer conditions enhanced GPP and RE. Meanwhile, interannual variation in annual CO2 balance was controlled predominantly by RE, and not GPP. During these 9 years of measurement, the annual CO2 balance shifted from a CO2 sink to a CO2 source, with a 9‐year average near zero. The increase in autumn RE was associated with autumn warming and was mostly attributed to a shift in the annual CO2 balance. The increase in autumn air temperature (0.22 °C yr−1) during the 9 years of study was 15 times greater than the long‐term warming trend between 1905 and 2011 (0.015 °C yr−1) due to decadal climate oscillation. This result indicates that most of the shifts in observed CO2 fluxes were associated with decadal climate variability. Because the natural climate varies in a cycle of 10–30 years, a long‐term study covering at least one full cycle of decadal climate oscillation is important to quantify the CO2 balance and its interaction with the climate.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
•A simple CH4 model constrained by observed data with a Bayesian method was developed.•CH4 flux based on the eddy covariance method was partitioned in a cool temperate bog.•Ebullition and ...plant-mediated transport are important pathways.•The anoxic deep layer contributed more to the CH4 flux than the oxic surface layer.•Long-term data are indispensable for better constraining models.
The responses of CH4 fluxes to environmental drivers are known to be complex in wetlands and are not easily interpreted due to their nonlinear nature. To better understand the observed CH4 flux, we developed a method to partition this flux into CH4 production, oxidation, and three transport pathways. Based on a Bayesian method with six-year eddy covariance measurements from a cool temperate bog in northern Japan, we estimated the parameters of a simple two-layer model, which considered the processes in surface oxic and deep anoxic layers. The constrained model explained 87% of the variation in the observed CH4 flux at the daily to seasonal timescales. The model estimated that 64% of CH4 was transported by ebullition compared with 36% by plant-mediated transport during snow-free periods. The model predicted that CH4 was mostly emitted from the deep anoxic layer rather than from the surface layer. The model explained 56% of the interannual variations in the annual CH4 flux, which was mostly controlled by CH4 production. Posterior distributions of the parameters depended on the data coverage that constrained the model, strongly indicating that long-term data are indispensable for constraining process models. Even when using the six-year data, all parameters were not well constrained probably because the data did not contain enough information to constrain the processes. Thus, the method must be tested in various wetlands with additional long-term data to evaluate its applicability and limitations.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
To evaluate CO2 emissions in urban areas and their temporal and spatial variability, continuous measurements of CO2 fluxes were conducted using the eddy covariance method at three locations in Sakai, ...Osaka, Japan. Based on the flux footprint at the measurement sites, CO2 fluxes from the three sites were partitioned into five datasets representing a dense urban center, a moderately urban area, a suburb, an urban park, and a rural area. A distinct biological uptake of CO2 was observed in the suburb, urban park, and rural areas in the daytime, whereas high emissions were observed in the dense and moderate urban areas in the daytime. Weekday CO2 emissions in the dense urban center and suburban area were approximately 50 % greater than emissions during weekends and holidays, but the other landscapes did not exhibit a clear weekly cycle. Seasonal variations in the urban park, rural area, and suburban area were influenced by photosynthetic uptake, exhibiting the lowest daily emissions or even uptake during the summer months. In contrast, the dense and moderately urban areas emitted CO2 in all seasons. CO2 emissions in the urban areas were high in the winter and summer months, and they significantly increased with the increase in air temperature in the summer and the decrease in air temperature in the winter. Irrespective of the land cover type, all urban landscapes measured in this study acted as net annual CO2 sources, with emissions ranging from 0.5 to 4.9 kg C m−2 yr−1. The magnitude of the annual CO2 emissions was negatively correlated with the green fraction; areas with a smaller green fraction had higher annual CO2 emissions. Upscaled flux estimated based on the green fraction indicated that the emissions for the entire city were 3.3 kg C m−2 yr−1, which is equivalent to 0.5 Tg C yr−1 or 1.8 Mt CO2 yr−1, based on the area of the city (149.81 km2). A network of eddy covariance measurements is useful for characterizing the spatial and temporal variations in net CO2 fluxes from urban areas. Multiple methods would be required to evaluate the rationale behind the fluxes and overcome the limitations in the future.
To obtain an accurate understanding of carbon dioxide (CO2) and methane (CH4) emissions from urban areas, it is important to estimate their spatial variations because the heterogeneous nature of ...urban land use results in different emissions patterns. We measured CH4 and CO2 fluxes from two urban landscapes in Japan with the eddy covariance method and evaluated the spatial distributions of fluxes by combining flux footprint analysis and mobile measurements of gas concentrations. CH4 hotspots were identified at sewage plants, oil refineries, and natural gas facilities in the urban center. The fluxes (60 ± 65 nmol m−2 s−1) affected by hotspots were higher than those in the suburban and residential areas (22 ± 30 nmol m−2 s−1). High CH4 concentrations of up to 5130 ppb from the hotspots were also observed in the mobile measurements. The measured fluxes showed that the study area generally acted as a CH4 source irrespective of the presence of hotspots. The mobile measurements suggested several CH4 sources: gas leaks from natural gas networks, sewage pipes, gas-powered air conditioners, and moats. The CO2 fluxes were larger in commercial and industrial areas than residential and suburb areas, and fluxes from vegetated areas were nearly CO2-neutral in the daytime.
•Daytime CH4 and CO2 fluxes were measured using the eddy covariance method.•The spatial variations in the fluxes were visualized with the footprint analysis.•Mobile measurements of CH4 and CO2 concentrations were conducted.•Sewage plants, oil refineries, and natural gas facilities could be CH4 hotspots.•Natural gas leaks, sewage pipes, and air conditioners were potential CH4 sources.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Upland forests are thought to be methane (CH4) sinks due to oxidation by methanotrophs in aerobic soils. However, CH4 budget for upland forests are not well quantified at the ecosystem scale, when ...possible CH4 sources, such as small wet areas, exists in the ecosystem. Here, we quantified CH4 fluxes in a cool-temperate larch plantation based on four-year continuous measurements using the hyperbolic relaxed eddy accumulation (HREA) method and dynamic closed chambers with a laser-based analyzer. After filling data gaps for half-hourly data using machine-learning-based regressions, we found that the forest acted as a net CH4 source at the canopy scale: 30 ± 11 mg CH4 m−2 yr−1 in 2014, 56 ± 8 mg CH4 m−2 yr−1 in 2015, 154 ± 5 mg CH4 m−2 yr−1 in 2016, and 132 ± 6 mg CH4 m−2 yr−1 in 2017. Hotspot emissions from the edge of the pond could strongly contribute to the canopy-scale emissions. The magnitude of the hotspot emissions was 10–100 times greater than the order of the canopy-scale and chamber-based CH4 fluxes at the dry soils. The high temperatures with wet conditions stimulated the hotspot emissions, and thus induced canopy-scale CH4 emissions in the summer. Understanding and modeling the dynamics of hotspot emissions are important for quantifying CH4 budgets of upland forests. Micrometeorological measurements at various forests are required for revisiting CH4 budget of upland forests.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are ...increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.
We synthesized eddy covariance and chamber measurements of annual and growing season carbon dioxide (CO2) fluxes from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites. We used statistical models to predict terrestrial ecosystem CO2 fluxes across the region over 1990–2015. Average annual net ecosystem CO2 sink strength was generally strong in the boreal biome but decreased with increasing latitude towards the tundra which was nearly neutral. Uncertainties remained high, but our results suggest that the high‐latitude region was on average an annual terrestrial ecosystem CO2 sink.
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•Four-year and nine-year measurements of CO2 flux at two burned forests at Alaska.•13 years after fire, the ecosystem become CO2 sink.•Recovery of GPP was explained by an increase in LAI.•Anomalous ...weathers increased the CO2 emissions rather than uptake.•Regional post-fire CO2 emissions was one third to fourth of the direct CO2 emissions.
Fire is the major disturbance in North American boreal forests, and is thought to be the most important process that determines the carbon balance in North American boreal forests. This study conducted four years of tower flux measurements in a burned ecosystem from one to four years after a fire, and nine years of measurements in a young regeneration from five to 13 years after a fire in interior Alaska. The fire scar acted as a source of 248 g C m−2 yr-1 one year after the fire, and the annual CO2 emissions continuously decreased until seven years after the fire. At the final year of the study period, 13 years after the fire, the older forest became a CO2 sink. During the 13 years after the fires, the total post-fire emissions were 767 g C m−2 across both sites. Gross primary productivity (GPP) and ecosystem respiration (RE) recovered to those of mature black spruce forests 10 years after the fire. The successional recovery of GPP was mostly explained by the recovery of the leaf area index (LAI). Anomalous weather, such as a cold spring, hot summer, and high summer rainfall, increased the CO2 emissions rather than the uptake. In interior Alaska, the post-fire CO2 emissions (35–48 Tg C) were estimated to be approximately one third to fourth of the direct CO2 emissions (156 Tg C) by combustions from 1998 to 2017, which indicates that post-fire emissions are important to the regional CO2 balance. The forest successional trajectory at young age still contains large uncertainties due to lack of data, and thus adding new data improves our understanding of the post-fire CO2 balance.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•CH4 fluxes were observed by chambers in an upland forest soil over seven years.•Modules for CH4 uptake were calibrated by the observed data with a Bayesian method.•After calibrating two parameters, ...the modules reproduced the observed fluxes well.•Future CH4 fluxes were predicted to increase with rising CH4 concentrations.•The modules contained high uncertainty levels in future predictions even after the calibration.
Upland soils are thought to be a sink of CH4, the second most important anthropogenic greenhouse gas, owing to oxidation by methanotrophs. To better understand CH4 fluxes in upland forests, we quasi-continuously measured CH4 fluxes using an automated closed chamber system over seven years on a larch plantation in a volcanic soil in Japan. We hypothesized that the long-term data sufficiently can calibrate modules for CH4 fluxes, and aimed to predict future pathways of CH4 uptake and their uncertainties in the forest. Based on the observations, a thinning of the overstory only marginally influenced the CH4 fluxes measured by the chambers. Using the data with a Bayesian method, we calibrated four modules for CH4 fluxes in forest soils, which were embedded in the process-based ecosystem model VISIT. The modules well reproduced the observed seasonality, annual budgets, and interannual variability in the CH4 fluxes after calibrating the following parameters: the diffusion coefficient or base CH4 oxidation rate constant and temperature sensitivity. The CH4 fluxes were predicted to increase in the future under the RCP8.5 scenario but to decrease under the RCP 2.6 scenario. The contrasting trajectory was caused by rising and decreasing CH4 concentrations under the RCP 8.5 and 2.6 scenarios, respectively. Furthermore, the magnitudes of the future changes in the fluxes differed in each module because the responses to the changes in the CH4 concentrations were inconsistent among the modules. The observed CH4 fluxes increased with increasing atmospheric CH4 concentration (4.95 mg CH4 m−2 d−1 ppm−1), which was greater in magnitude than those in the modules. Considering the uncertainties in the modules and potential confounding effects in the observations, we conclude that further understanding the responses of CH4 uptake to rising CH4 concentrations is required.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
While wetlands are the largest natural source of methane (CH4) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on ...CH4 dynamics. Here we present, to our knowledge, the first multi‐site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet‐based multi‐resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat‐dominated sites, with drops in PA coinciding with synchronous releases of CH4. At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1‐ to 4‐h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.
We used multiple statistical approaches to assess the importance of environmental predictors and lags on methane fluxes across 23 freshwater wetland eddy covariance sites and multiple time scales. Temperature and water levels were dominant predictors of methane flux at the seasonal scale (average 5–17 day lag between change in predictor and change in methane flux), atmospheric pressure was another key predictor at the multiday scale, and methane fluxes varied near‐synchronously with latent heat flux, vapor pressure deficit and photosynthesis diurnally. This work helps to better understand predictors and timing of methane exchange, inform models, and constrain wetland methane emissions.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
High-latitude warming has stimulated CO2 and CH4 emissions from permafrost peatland. This study evaluated growing season CH4 and CO2 emissions from a forest floor of a lowland black spruce forest on ...permafrost in interior Alaska using automated-closed chambers, anaerobic incubation of peat soils and next-generation sequencing. The CH4 emissions from May to October were 723 ± 432 mg C m−2 and 829 ± 628 mg C m−2 from the two Carex wet plots, 124 ± 76 mg C m−2 from the Sphagnum moss plot, and 11 mg C m−2 from the lichen plot (± denotes standard deviation of different years). The CH4 emissions in the peak season showed diurnal variations with a single peak around noon or double peaks depending on the plots. The CH4 emissions were an order of magnitude lower than those for other northern wetlands, possibly because deep, cold peats regulated CH4 production and oxidation at the dry aerobic surface layer. Low water table positions strongly inhibited CH4 emissions in 2018, suggesting the importance of dissolved CH4 pool at the bottom of the active layer. The future trajectory of CH4 emissions could substantially change with water conditions, deep soil temperatures, and sedge compositions.
•CH4 emissions were low in a lowland spruce forest on permafrost, interior Alaska.•Deep cold peats were estimated to play a dominant role in CH4 production.•CH4 emissions were higher in plots dominated by Carex than by moss and lichen.•Interannual variation in CH4 flux was large depending on the water table position.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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