Variation In Methane Emissions Research Articles

Methane emissions respond to soil temperature in convergent patterns but divergent sensitivities across wetlands along altitude.

Among the global coordinated patterns in soil temperature and methane emission from wetlands, a declining trend of optimal soil temperature for methane emissions from low to high latitudes has been witnessed, while the corresponding trend along the altitudinal gradient has not yet been investigated. We therefore selected two natural wetlands located at contrasting climatic zones from foothill and mountainside of Nepal Himalayas, to test: (1) whether the optimal temperature for methane emissions decreases from low to high altitude, and (2) whether there is a difference in temperature sensitivity of methane emissions from those wetlands. We found significant spatial and temporal variation of methane emissions between the two wetlands and seasons. Soil temperature was the dominant driver for seasonal variation in methane emissions from both wetlands, though its effect was perplexed by the level of standing water, aquatic plants, and dissolved organic carbon, particularly in the deep water area. When integrative comparison was conducted by adding the existing data from wetlands of diverse altitudes, and the latitude-for-altitude effect was taken into account, we found the baseline soil temperatures decrease whilst the altitude rises with respect to a rapid increase in methane emission from all wetlands, however, remarkably higher sensitivity of methane emissions to soil temperature (apparent Q10 ) was found in mid-altitude wetland. We provide the first evidence of an apparent decline in optimal temperature for methane emissions with increasing elevation. These findings suggest a convergent pattern of methane emissions with respect to seasonal temperature shifts from wetlands along altitudinal gradient, while a divergent pattern in temperature sensitivities exhibits a single peak in mid-altitude.

Quantifying methane emissions from Queensland's coal seam gas producing Surat Basin using inventory data and a regional Bayesian inversion

Abstract. Methane (CH4) is a potent greenhouse gas and a key precursor of tropospheric ozone, itself a powerful greenhouse gas and air pollutant. Methane emissions across Queensland's Surat Basin, Australia, result from a mix of activities, including the production and processing of coal seam gas (CSG). We measured methane concentrations over 1.5 years from two monitoring stations established 80 km apart on either side of the main CSG belt located within a study area of 350 km × 350 km. Using an inverse modelling approach coupled with a bottom-up inventory, we quantify methane emissions from this area. The inventory suggests that the total emission is 173.2 × 106 kg CH4 yr−1, with grazing cattle contributing about half of that, cattle feedlots ∼ 25 %, and CSG processing ∼ 8 %. Using the inventory emissions in a forward regional transport model indicates that the above sources are significant contributors to methane at both monitors. However, the model underestimates approximately the highest 15 % of the observed methane concentrations, suggesting underestimated or missing emissions. An efficient regional Bayesian inverse model is developed, incorporating an hourly source–receptor relationship based on a backward-in-time configuration of the forward regional transport model, a posterior sampling scheme, and the hourly methane observations and a derived methane background. The inferred emissions obtained from one of the inverse model setups that uses a Gaussian prior whose averages are identical to the gridded bottom-up inventory emissions across the domain with an uncertainty of 3 % of the averages best describes the observed methane. Having only two stations is not adequate at sampling distant source areas of the study domain, and this necessitates a small prior uncertainty. This inverse setup yields a total emission of (165.8 ± 8.5) × 106 kg CH4 yr−1, slightly smaller than the inventory total. However, in a subdomain covering the CSG development areas, the inferred emissions are (63.6 ± 4.7) × 106 kg CH4 yr−1, 33 % larger than those from the inventory. We also infer seasonal variation of methane emissions and examine its correlation with climatological rainfall in the area.

Water flow controls the spatial variability of methane emissions in a northern valley fen ecosystem

Abstract. Northern peatlands are projected to be crucial in future atmospheric methane (CH4) budgets and have a positive feedback on global warming. Fens receive nutrients from catchments via inflowing water and are more sensitive than bogs to variations in their ecohydrology. Yet, due to a lack of data detailing the impacts of moving water on microhabitats and CH4 fluxes in fens, large uncertainties remain with respect to predicting CH4 emissions from these sites under climate changes. We measured CH4 fluxes with manual chambers over three growing seasons (2017–2019) at a northern boreal fen. To address the spatial variation at the site where a stream flows through the long and narrow valley fen, we established sample plots at varying distances from the stream. To link the variations in CH4 emissions to environmental controls, we quantified water levels, peat temperature, dissolved oxygen concentration, vegetation composition, and leaf area index in combination with flux measurements during the growing season in 2019. We found that due to the flowing water, there was a higher water level, cooler peat temperatures, and more oxygen in the peat close to the stream, which also had the highest total leaf area and gross primary production (GPP) values but the lowest CH4 emissions. CH4 emissions were highest at an intermediate distance from the stream where the oxygen concentration in the surface peat was low but GPP was still high. Further from the stream, the conditions were drier and produced low CH4 emissions. Our results emphasize the key role of ecohydrology in CH4 dynamics in fens and, for the first time, show how a stream controls CH4 emissions in a flow-through fen. As valley fens are common peatland ecosystems from the Arctic to the temperate zones, future projections of global CH4 budgets need to take flowing water features into account.

Changes in the methane emissions and hard coal output in the Brzeszcze mine (the Upper Silesian Coal Basin, Poland)

The paper presents the variability of methane emissions in mining excavations in the Brzeszcze mine (Poland) against the background of hard coal output, geological and mining factors. The geological structure of the Upper Silesian Coal Basin (USCB) is very diverse. The Brzeszcze coal deposit is located close to the large and permeable Jawiszowice fault which increases the methane hazard during mining activities performed close to this fault. The overall decrease in hard coal output (1988–2018) has coincided with a rapid increase in methane emissions (1997–2018). Throughout the study period, hard coal output decreased threefold from 3.9 to 1.2 million Mg annually. Coal extraction in high methane content beds (e.g. 510, 405/1, 364, 352) increases the total methane (CH4) emission into mining excavations, aggravating the methane hazard due to the high explosiveness of the gas. To protect miners, coal workings need to be continuously ventilated, taking the harmful gas out of the mine (ventilation air methane emission) or methane needs to be captured by underground methane systems (degassing). Every year, over 34 million m3 of CH4 is captured by the drainage systems and over 70 million m3 CH4 (average) is discharged through ventilation shafts into the atmosphere. The presence of the large, permeable regional dislocation, the Jawiszowice fault zone, shaped the methane concentration in the fault vicinity, when the highest methane emissions during coal mining was studied.

A heat diffusion multilayer network approach for the identification of functional biomarkers in rumen methane emissions.

A better understanding of rumen microbial interactions is crucial for the study of rumen metabolism and methane emissions. Metagenomics-based methods can explore the relationship between microbial genes and metabolites to clarify the effect of microbial function on the host phenotype. This study investigated the rumen microbial mechanisms of methane metabolism in cattle by combining metagenomic data and network-based methods. Based on the relative abundance of 1461 rumen microbial genes and the main volatile fatty acids (VFAs), a multilayer heterogeneous network was constructed, and the functional modules associated with metabolite-microbial genes were obtained by heat diffusion algorithm. The PLS model by integrating data from VFAs and microbial genes explained 72.98% variation of methane emissions. Compared with single-layer networks, more previously reported biomarkers of methane prediction can be captured by the multilayer network. More biomarkers with the rank of top 20 topological centralities were from the PLS models of diffusion subsets. The heat diffusion algorithm is different from the strategy used by the microbial metabolic system to understand methane phenotype. It inferred 24 novel biomarkers that were preferentially affected by changes in specific VFAs. Results showed that the heat diffusion multilayer network approach improved the understanding of the microbial patterns of VFAs affecting methane emissions which represented by the functional microbial genes.

Temporal and spatial variations in methane emissions from the littoral zone of a shallow mid-latitude lake with steady methane bubble emission areas

Temporal and spatial variations in methane (CH4) emissions from the littoral zone of a shallow mid-latitude lake, Lake Suwa, were examined using the eddy covariance technique. The observation data were supplemented with dissolved CH4 measurement and incubation experiments of lake sediment and water. This lake had areas with steady bubble CH4 emissions, shaping the spatial variation in CH4 flux with strong spot emissions. In the other areas, CH4 was emitted via diffusion and episodic ebullition. CH4 emissions from this area had a clear seasonal variation, reflecting temperature variations, with a maximum monthly mean emission of 0.39 µmolm−2s−1 in August. The higher emission in summer was due to higher CH4 production in the sediment and the resulting higher dissolved CH4 concentration in the surface water. The steady bubble CH4 emission was seasonally controlled by the total hydrostatic pressure, with higher emission under lower pressure, suggesting regulation of the amount of bubbles emitted from the lake bottom by pressure. Isotope analysis revealed that this CH4 was produced biologically. This natural gas seepage was estimated to emit 1.9 Mg of CH4 annually. Compared with other eddy covariance studies over inland waters, CH4 emissions from Lake Suwa may be large for the latitude. This may be related to eutrophication, which enhances CH4 production.

Spatial and temporal variability of methane emissions from cascading reservoirs in the Upper Mekong River

Reservoirs are an important source of atmospheric methane (CH4), a potent greenhouse gas. The Mekong, one of the largest Asian rivers, has been heavily dammed and can be a potential hotspot for CH4 emissions. While low diffusive CH4 flux was previously reported from cascading reservoirs in the Upper Mekong, the contribution of ebullition (bubbling) remained unexplored. To better constrain the magnitude and drivers of ebullition from these reservoirs, automated bubble traps were deployed in four reservoirs, allowing for continuous measurement of the ebullitive flux with high temporal resolution for a period of six months. To characterize the spatial variability of CH4 fluxes mediated by ebullition and diffusion, whole-reservoir surveys were conducted using a scientific echo sounder for bubble observations together with a gas equilibrator for mapping dissolved CH4 concentration in surface water from which diffusive fluxes were estimated. Potential production and anaerobic oxidation rates of CH4 were estimated in laboratory incubations of sediment cores collected near the bubble trap deployment sites. The CH4 production potential in sediments increased strongly along the reservoir cascade, with mostly minor reduction by anaerobic oxidation. Surface CH4 fluxes, in contrast, showed high spatial variability in both ebullitive and diffusive pathways (ranging 0.05–44 and 1.8–6.4 mg m−2 d−1, respectively, among all reservoirs). Ebullitive fluxes were about one order of magnitude higher than diffusive fluxes and remained significant at sites as deep as 30–45 m. The repeated spatial pattern of ebullition (higher fluxes at the dam area than in upstream sections) suggests the possible control of emission rates by sediment transport and deposition.

Diel variability of methane emissions from lakes

Lakes are considered the second largest natural source of atmospheric methane (CH4). However, current estimates are still uncertain and do not account for diel variability of CH4 emissions. In this study, we performed high-resolution measurements of CH4 flux from several lakes, using an automated and sensor-based flux measurement approach (in total 4,580 measurements), and demonstrated a clear and consistent diel lake CH4 flux pattern during stratification and mixing periods. The maximum of CH4 flux were always noted between 10:00 and 16:00, whereas lower CH4 fluxes typically occurred during the nighttime (00:00-04:00). Regardless of the lake, CH4 emissions were on an average 2.4 higher during the day compared to the nighttime. Fluxes were higher during daytime on nearly 80% of the days. Accordingly, estimates and extrapolations based on daytime measurements only most likely result in overestimated fluxes, and consideration of diel variability is critical to properly assess the total lake CH4 flux, representing a key component of the global CH4 budget. Hence, based on a combination of our data and additional literature information considering diel variability across latitudes, we discuss ways to derive a diel variability correction factor for previous measurements made during daytime only.

Sources of seasonal wetland methane emissions in permafrost regions of the Qinghai-Tibet Plateau

In this study, systematic soil methane cycle geochemical monitoring was carried out in a typical gas hydrate region in the Qinghai-Tibet Plateau. Soil gas samples were collected for hydrocarbon components and carbon isotope analysis. Meanwhile, soil-methane fluxes from the upper active layer (20–30 cm) were monitored during six months of one year. The results of this research provide evidence of a new source of methane emission from wetland soils in permafrost regions: gas hydrate release. Sites with large methane emissions were found using flux monitoring, the characteristics of thermogenic methane were identified using carbon isotope tracing, and the relationship between emission by soils and effusion from gas hydrates was determined through correlation analyses of soil-adsorbed hydrocarbons. Seasonal variation of methane emissions are also discussed by considering the emission of bacterial methane, thermogenic methane, and the absorption of methane from the soil active layer. These comprehensive findings provide valuable information for carbon cycle research of wetlands in permafrost regions.

Bayesian modeling reveals host genetics associated with rumen microbiota jointly influence methane emission in dairy cows

Reducing methane emissions from livestock production is of great importance for the sustainable management of the Earth’s environment. Rumen microbiota play an important role in producing biogenic methane. However, knowledge of how host genetics influences variation in ruminal microbiota and their joint effects on methane emission is limited. We analyzed data from 750 dairy cows, using a Bayesian model to simultaneously assess the impact of host genetics and microbiota on host methane emission. We estimated that host genetics and microbiota explained 24% and 7%, respectively, of variation in host methane levels. In this Bayesian model, one bacterial genus explained up to 1.6% of the total microbiota variance. Further analysis was performed by a mixed linear model to estimate variance explained by host genomics in abundances of microbial genera and operational taxonomic units (OTU). Highest estimates were observed for a bacterial OTU with 33%, for an archaeal OTU with 26%, and for a microbial genus with 41% heritability. However, after multiple testing correction for the number of genera and OTUs modeled, none of the effects remained significant. We also used a mixed linear model to test effects of individual host genetic markers on microbial genera and OTUs. In this analysis, genetic markers inside host genes ABS4 and DNAJC10 were found associated with microbiota composition. We show that a Bayesian model can be utilized to model complex structure and relationship between microbiota simultaneously and their interaction with host genetics on methane emission. The host genome explains a significant fraction of between-individual variation in microbial abundance. Individual microbial taxonomic groups each only explain a small amount of variation in methane emissions. The identification of genes and genetic markers suggests that it is possible to design strategies for breeding cows with desired microbiota composition associated with phenotypes.

Identification of Complex Rumen Microbiome Interaction Within Diverse Functional Niches as Mechanisms Affecting the Variation of Methane Emissions in Bovine.

A network analysis including relative abundances of all ruminal microbial genera (archaea, bacteria, fungi, and protists) and their genes was performed to improve our understanding of how the interactions within the ruminal microbiome affects methane emissions (CH4). Metagenomics and CH4 data were available from 63 bovines of a two-breed rotational cross, offered two basal diets. Co-abundance network analysis revealed 10 clusters of functional niches. The most abundant hydrogenotrophic Methanobacteriales with key microbial genes involved in methanogenesis occupied a different functional niche (i.e., “methanogenesis” cluster) than methylotrophic Methanomassiliicoccales (Candidatus Methanomethylophylus) and acetogens (Blautia). Fungi and protists clustered together and other plant fiber degraders like Fibrobacter occupied a seperate cluster. A Partial Least Squares analysis approach to predict CH4 variation in each cluster showed the methanogenesis cluster had the best prediction ability (57.3%). However, the most important explanatory variables in this cluster were genes involved in complex carbohydrate degradation, metabolism of sugars and amino acids and Candidatus Azobacteroides carrying nitrogen fixation genes, but not methanogenic archaea and their genes. The cluster containing Fibrobacter, isolated from other microorganisms, was positively associated with CH4 and explained 49.8% of its variability, showing fermentative advantages compared to other bacteria and fungi in providing substrates (e.g., formate) for methanogenesis. In other clusters, genes with enhancing effect on CH4 were related to lactate and butyrate (Butyrivibrio and Pseudobutyrivibrio) production and simple amino acids metabolism. In comparison, ruminal genes negatively related to CH4 were involved in carbohydrate degradation via lactate and succinate and synthesis of more complex amino acids by γ-Proteobacteria. When analyzing low- and high-methane emitters data in separate networks, competition between methanogens in the methanogenesis cluster was uncovered by a broader diversity of methanogens involved in the three methanogenesis pathways and larger interactions within and between communities in low compared to high emitters. Generally, our results suggest that differences in CH4 are mainly explained by other microbial communities and their activities rather than being only methanogens-driven. Our study provides insight into the interactions of the rumen microbial communities and their genes by uncovering functional niches affecting CH4, which will benefit the development of efficient CH4 mitigation strategies.

Hiatus of wetland methane emissions associated with recent La Niña episodes in the Asian monsoon region

The variability of methane emissions from wetlands in the tropics and northern temperate regions can explain more than 70% of the interannual variation in global wetland methane emissions, which are largely driven by climate variability. We use climate reanalysis, remote sensing wetland area dataset and simulations from 11 land models contributing to Global Methane Budget to investigate the interannual variation and anomalies of wetland methane emissions in the Asian Monsoon region. Methane emissions in this region steadily increased over 2000–2012. However, abnormally low methane emissions were found in equatorial fully humid (Af), warm temperate winter dry (Cw), and warm temperate fully humid (Cf) Asian Monsoon climate sub-regions in 2008, 2009 and 2011, respectively. These spatially-shifting low emissions occurred simultaneously with observed wetland area shrinkage due to abnormally low precipitation. Interannual variability of wetland methane emissions in Asian Monsoon region are primarily driven by South Asian Monsoon system. However, the abnormally low emissions are related to strong La Nina events, and its accompanying effect of weakened East Asian Monsoon system and eastward Western Pacific subtropical high, which drives the shifting pattern of rainfall, and thus the spatial pattern of methane emission anomalies.

НЕОПРЕДЕЛЕННОСТЬ ЕСТЕСТВЕННЫХ ЭМИССИЙ МЕТАНА ИЗ ВЛАЖНЫХ ЭКОСИСТЕМ ВЫСОКИХ ШИРОТ

Current estimates of methane emissions from high latitude wetlands have significant intermodel variations, one reason for which may be internal atmospheric circulation variability. This paper analyzes the impact of internal atmospheric variability on variations in methane emissions from the Hudson Bay Lowland (HBL) area. The ensemble of numerical experiments with a joint model of the methane cycle and heat and moisture transport in soil was performed. An ensemble of 45 realizations of the multi-year data of meteorological variables at the land surface, calculated by the ECHAM5 for different initial and identical boundary conditions for a 34-year period (from 1.01.1979 to 31.12.2012) was specified as space-distributed input data. Necessary physical characteristics of the soil were calculated in the module of heat and moisture transport, supplemented with an interactive scheme for calculating the area of the model cell occupied by the wetlands. Wetlands are estimated to occupy 8–20 % (with 11.4 % ensemble mean) of HBL region area. The ensemble average of annual emissions for HBL over the estimated period equals 6.1 TgCH4/yr with – 0.1 TgCH4/yr trend. The obtained uncertainty associated with climate noise equals 32 % for average annual emissions, and 31–38 % for individual months. It is shown that a significant contribution to the high uncertainty of methane emissions is made by the climatically determined variability of the wetland area.

Reasons and patterns of spatio-temporal variability of methane emission from the Mozhaysk reservoir in summer period

Anthropogenic reservoirs are not only sources of clean energy, flow regulators, recreational and food resources, but also sources of greenhouse gases such as methane. The studies presented in this work, done on a well-studied low-flowing valley reservoir mainly in the summer, when the greatest variability of methane fluxes was observe. Depending on synoptic conditions, the temporal variability of methane fluxes varies greatly. Methane fluxes increase during the summer period and huge methane emissions observed before the autumn mixing stage. Emissions can occur during the destruction of temperature stratification, as a result of stormy weather. With such emissions, methane fluxes into the atmosphere can reach about 20 mgC*m-2*d-1, which is higher than the emission during convection. Revealing the patterns of spatio-temporal distribution of methane fluxes will help to determine the contribution of water bodies (in particular reservoirs) to the total methane budget of the atmosphere more accurately.

Quantifying the impact of emission outbursts and non-stationary flow on eddy-covariance CH<sub>4</sub> flux measurements using wavelet techniques

Abstract. Methane flux measurements by the eddy-covariance technique are subject to large uncertainties, particularly linked to the partly highly intermittent nature of methane emissions. Outbursts of high methane emissions, termed event fluxes, hold the potential to introduce systematic biases into derived methane budgets, since under such conditions the assumption of stationarity of the flow is violated. In this study, we investigate the net impact of this effect by comparing eddy-covariance fluxes against a wavelet-derived reference that is not negatively influenced by non-stationarity. Our results demonstrate that methane emission events influenced 3 %–4 % of the flux measurements and did not lead to systematic biases in methane budgets for the analyzed summer season; however, the presence of events substantially increased uncertainties in short-term flux rates. The wavelet results provided an excellent reference to evaluate the performance of three different gap-filling approaches for eddy-covariance methane fluxes, and we show that none of them could reproduce the range of observed flux rates. The integrated performance of the gap-filling methods for the longer-term dataset varied between the two eddy-covariance towers involved in this study, and we show that gap-filling remains a large source of uncertainty linked to limited insights into the mechanisms governing the short-term variability in methane emissions. With the capability for broadening our observational methane flux database to a wider range of conditions, including the direct resolution of short-term variability on the order of minutes, wavelet-derived fluxes hold the potential to generate new insight into methane exchange processes with the atmosphere and therefore also improve our understanding of the underlying processes.

Multi-scale temporal variation in methane emission from an alpine peatland on the Eastern Qinghai-Tibetan Plateau and associated environmental controls

Most previous studies on methane (CH4) emissions from peatlands have focused on the boreal, subarctic, and tropical regions. Little is known about CH4 emissions from the alpine peatlands that are widely distributed in the eastern Qinghai-Tibetan Plateau (QTP), which are sensitive to climate change and human disturbance. To assess the magnitudes of daily and seasonal variations in CH4 flux in this area, and to identify the influential environmental factors, an eddy covariance (EC) tower with a LI-7700 open-path CH4 analyzer was established on Hongyuan Peatland. Total annual CH4 emission was 46.8 g CH4 m-2 in 2014, with emissions in the non-growing season accounting for 25% of the annual total. From May to September 2014, diurnal variation in CH4 emissions was observed, with CH4 fluxes varying between 0.15 and 0.25 μmol m-2 s-1. In contrast, during all other periods of 2014, no diurnal variation was observed, and CH4 flux varied below 0.05 μmol m-2 s-1. A clear seasonal pattern in CH4 exchange with small surges in CH4 emission appeared in soil thawing and freezing seasons. Wavelet analysis was applied to the continuous CH4 flux time series to explore temporal variation in ecosystem CH4 exchange during the growing season. On daily timescales, changes in CH4 flux are in phase with changes in air temperature, and influenced by friction velocity and vapor pressure deficit (VPD). On weekly-to-monthly timescales, soil temperature can explain most of the variation in CH4 exchange. Though CH4 fluxes had no apparent correlation with water table level, fluxes were significantly (R2 = 0.86) correlated with soil temperature measured at -25 cm depth, close to the water table level throughout the growing season, suggesting a synergistic effect of water table level and soil temperature on methane emission. This study highlights the need for continuous eddy covariance measurements and time series analysis approaches to adequately describe temporal variability in ecosystem CH4 exchange.

Methane occurrence, emissions and hazards in the Upper Silesian Coal Basin, Poland

The paper presents the variability of methane emissions into mining excavations and the atmosphere in the Upper Silesian Coal Basin (USCB) (Poland) against the background of natural and mining factors. Emissions of methane from exploited coal seams have become a serious problem in the USCB due to the growing methane hazard in coal mines and emissions of methane into the atmosphere. In the mid-nineties 753 million m3 of methane was emitted annually from the USCB mines. Despite a significant drop in coal production over the next 20 years, methane emissions have not decreased sharply; on the contrary, in recent years they have begun to grow, and, in 2016, reached the level of 933 million m3 per year. This represents an increase of 180 million m3 per year since the mid-nineties. One of the important reasons for this phenomenon is the constantly increasing depth of coal exploitation, which in many mines now exceeds 1000 m; this is the depth corresponding to the deep methane zone, where the volume of accumulated methane in the coal seams is particularly high. Factors influencing the volume of methane emissions in relation to mine workings can be divided roughly into two groups: natural (geological) and anthropogenic (mining-related). Natural factors include methane content in coal seams, gas pressure, the presence of free gas in fault zones, related fissures and porous sandstone, the migration of methane through faults and fissures, and the presence of a continuous and impermeable Miocene overburden. Mining factors include the depth of exploitation and the concentration of coal production as expressed in terms of the length, height, and advance of walls. The interdependence of these factors means that, despite the decline in coal production, methane emissions, both total and specific, are increasing. This problem cannot be neglected, especially since it may grow worse in future. One measure to prevent the growth of methane emissions and the associated hazard may be the intensification of mine methane drainage and the economic use of captured mining gas, which is already done in the USCB.

日本海側積雪寒冷地の稲わら施用水田におけるメタン発生量の年次変動と中干し期間の延長によるメタン発生量の低減効果 第1報 同一試験地における17年間21事例のメタン発生量の年次変動に及ぼす気温，土壌Ehの影響

日本海側積雪寒冷地の稲わら施用水田におけるメタン発生量の年次変動と中干し期間の延長によるメタン発生量の低減効果 第1報 同一試験地における17年間21事例のメタン発生量の年次変動に及ぼす気温，土壌Ehの影響

日本海側積雪寒冷地の稲わら施用水田におけるメタン発生量の年次変動と中干し期間の延長によるメタン発生量の低減効果 第2報 中干し期間の延長によるメタン発生量の低減効果と水稲生育への影響

日本海側積雪寒冷地の稲わら施用水田におけるメタン発生量の年次変動と中干し期間の延長によるメタン発生量の低減効果 第2報 中干し期間の延長によるメタン発生量の低減効果と水稲生育への影響

Wetland methane emissions dominated by plant‐mediated fluxes: Contrasting emissions pathways and seasons within a shallow freshwater subtropical wetland

AbstractWetlands represent the largest natural source of methane; however, very few studies have simultaneously quantified the three main atmospheric flux pathways (i.e., diffusive, ebullition, and plant‐mediated). Unlike better‐studied northern hemisphere systems, many Australian subtropical wetlands undergo extreme wet/dry oscillations, which may strongly impact methane dynamics. We assessed diurnal methane emissions of multiple pathways during three distinct seasonal events within an Australian freshwater wetland. Six‐fold higher methane emissions occurred during summer compared to autumn floods (which followed an extensive dry‐period) and winter/cool conditions. Over three seasons, diffusion represented the highest average areal fluxes (25.9 ± 73.2 mmol m−2 d−1) but were within range of fluxes through water lily aerenchyma (20.8 ± 41.5 mmol m−2 d−1). Average ebullition rates were 5.5 ± 9.7 mmol m−2 d−1. Water column CH4 displayed high spatiotemporal variability, ranging from 55.0 to 253.5 μmol L−1. Time series δ13C–CH4 isotope measurements revealed an oxidation fraction of ~ 15% at night‐time and ~ 36% during day‐time, and night‐time diffusive fluxes were consistently ~ three‐fold higher than day‐time fluxes. By aggregating seasons and weighting for changes in lily coverage, plant‐mediated fluxes accounted for ~ 59% of the annual methane emissions, whereas ebullition and diffusion each accounted for ~ 20%. The up‐scaled annual area‐weighted wetland methane flux (combined pathways) was 27.3 ± 36.7 mmol m−2 d−1. We contend that water lilies (Nymphaea sp.) are the significant carbon source, mediator, and conduit for methane fluxes in this system, and the extremely large seasonal variability of methane emissions reflect dynamic redox oscillations driven by oscillating wet and dry conditions.