Fluxes of carbon dioxide, methane and nitrous oxide in two contrastive fringing zones of coastal lagoon, Lake Nakaumi, Japan

Abstract. Arctic terrestrial greenhouse gas (GHG) fluxes of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) play an important role in the global GHG budget. However, these GHG fluxes are rarely studied simultaneously, and our understanding of the conditions controlling them across spatial gradients is limited. Here, we explore the magnitudes and drivers of GHG fluxes across fine-scale terrestrial gradients during the peak growing season (July) in sub-Arctic Finland. We measured chamber-derived GHG fluxes and soil temperature, soil moisture, soil organic carbon and nitrogen stocks, soil pH, soil carbon-to-nitrogen (C/N) ratio, soil dissolved organic carbon content, vascular plant biomass, and vegetation type from 101 plots scattered across a heterogeneous tundra landscape (5 km2). We used these field data together with high-resolution remote sensing data to develop machine learning models for predicting (i.e., upscaling) daytime GHG fluxes across the landscape at 2 m resolution. Our results show that this region was on average a daytime net GHG sink during the growing season. Although our results suggest that this sink was driven by CO2 uptake, it also revealed small but widespread CH4 uptake in upland vegetation types, almost surpassing the high wetland CH4 emissions at the landscape scale. Average N2O fluxes were negligible. CO2 fluxes were controlled primarily by annual average soil temperature and biomass (both increase net sink) and vegetation type, CH4 fluxes by soil moisture (increases net emissions) and vegetation type, and N2O fluxes by soil C/N (lower C/N increases net source). These results demonstrate the potential of high spatial resolution modeling of GHG fluxes in the Arctic. They also reveal the dominant role of CO2 fluxes across the tundra landscape but suggest that CH4 uptake in dry upland soils might play a significant role in the regional GHG budget.

Coastal salt marshes play an important role in mitigating global warming by removing atmospheric carbon at a high rate. We investigated the environmental controls and emergent scaling of major greenhouse gas (GHG) fluxes such as carbon dioxide (CO2) and methane (CH4) in coastal salt marshes by conducting data analytics and empirical modeling. The underlying hypothesis is that the salt marsh GHG fluxes follow emergent scaling relationships with their environmental drivers, leading to parsimonious predictive models. CO2 and CH4 fluxes, photosynthetically active radiation (PAR), air and soil temperatures, well water level, soil moisture, and porewater pH and salinity were measured during May–October 2013 from four marshes in Waquoit Bay and adjacent estuaries, MA, USA. The salt marshes exhibited high CO2 uptake and low CH4 emission, which did not significantly vary with the nitrogen loading gradient (5–126 kg · ha−1 · year−1) among the salt marshes. Soil temperature was the strongest driver of both fluxes, representing 2 and 4–5 times higher influence than PAR and salinity, respectively. Well water level, soil moisture, and pH did not have a predictive control on the GHG fluxes, although both fluxes were significantly higher during high tides than low tides. The results were leveraged to develop emergent power law‐based parsimonious scaling models to accurately predict the salt marsh GHG fluxes from PAR, soil temperature, and salinity (Nash‐Sutcliffe Efficiency = 0.80–0.91). The scaling models are available as a user‐friendly Excel spreadsheet named Coastal Wetland GHG Model to explore scenarios of GHG fluxes in tidal marshes under a changing climate and environment.

One of the goals of urban ecology is to link community structure to ecosystem function in urban habitats. Pollution-tolerant wetland invertebrates have been shown to enhance greenhouse gas (GHG) flux in controlled laboratory experiments, suggesting that they may influence urban wetland roles as sources or sinks of GHG. However, it is unclear if their effects can be detected in highly variable conditions in a field setting. Here we use an extensive data set on carbon dioxide (CO2 ), methane (CH4 ), and nitrous oxide (N2 O) flux in sediment cores (n=103) collected from 10 urban wetlands in Melbourne, Australia during summer and winter in order to test for invertebrate enhancement of GHG flux. We detected significant multiplicative enhancement effects of temperature, sediment carbon content, and invertebrate density on CH4 and CO2 flux. Each doubling in density of oligochaete worms or large benthic invertebrates (oligochaete worms and midge larvae) corresponded to ~42% and ~15% increases in average CH4 and CO2 flux, respectively. However, despite exceptionally high densities, invertebrates did not appear to enhance N2 O flux. This was likely due to fairly high organic carbon content in sediments (range 2.1-12.6%), and relatively low nitrate availability (median 1.96μmol/L NO3- -N), which highlights the context-dependent nature of community structural effects on ecosystem function. The invertebrates enhancing GHG flux in this study are ubiquitous, and frequently dominate faunal communities in impaired aquatic ecosystems. Therefore, invertebrate effects on CO2 and CH4 flux may be common in wetlands impacted by urbanization, and urban wetlands may make greater contributions to the total GHG budgets of cities if the negative impacts of urbanization on wetlands are left unchecked.

Fluxes of greenhouse gases at two different aquaculture ponds in the coastal zone of southeastern China

Plants regulate greenhouse gas (GHG) fluxes in wetland ecosystems, but the mechanisms of plant removal and plant species that contribute to GHG emissions remain unclear. In this study, the fluxes of carbon dioxide (CO2) and nitrous oxide (N2O) were measured using the static chamber method from an island forest dominated by two different species, namely Betula platyphylla (BP) and Larix gmelinii (LG), in a marsh wetland in the Great Xing'an Mountains. Four sub-plots were established in this study: (1) bare soil after removing vegetation under BP (SBP); (2) bare soil after removing vegetation under LG (SLG); (3) soil with vegetation under BP (VSBP); and (4) soil with vegetation under LG (VSLG). Additionally, the contributions of the dark respiration from plant aerial parts under BP (VBP) and LG (VLG) to GHG fluxes were calculated. We found that the substantial spatial variability of CO2 fluxes ranged from -25.32 ± 15.45 to 187.20 ± 74.76 mg m-2 h-1 during the study period. The CO2 fluxes decreased in the order of SBP > VSLG > VSBP > SLG > VLG > VBP, indicating that vegetation species had a great impact on CO2 emissions. Particularly, the absence of vegetation promoted CO2 emission in both BP and LG. Additionally, CO2 fluxes showed dramatically seasonal variations, with high CO2 fluxes in late spring (May) and summer (June, July, and August), but low fluxes in late summer (August) and early autumn (September). Soil temperatures at 0-20 cm depth were better predictors of CO2 fluxes than deeper soil temperatures. N2O fluxes were varied in different treatments with the highest N2O fluxes in SLG and the lowest N2O fluxes in VBP. Meanwhile, no significant correlation was found between N2O fluxes and air or soil temperatures. Temporally, negative N2O fluxes were observed from June to October, indicating that soil N2O fluxes were reduced and emitted as N2, which was the terminal step of the microbial denitrification process. Most of the study sites were CO2 sources during the warm season and CO2 sinks in the cold season. Thus, soil temperature plays an important role in CO2 fluxes. We also found that the CO2 flux was positively related to pH in a 10 cm soil layer and positively related to moisture content (MC) in a 50 cm soil layer in VSBP and VSLG. However, the CO2 flux was negatively related to pH in a 30 cm soil layer in SBP and SLG. Our findings highlight the effects of vegetation removal on GHG fluxes, and aid in the scientific management of wetland plants.

Under the umbrella of international and European Union climate policies and agreements aimed at achieving climate neutrality and thus reducing greenhouse gas (GHG) emissions from drained organic soils (including the Paris agreement, the European Green Deal and the Nature Restoration Law), it is urgently necessary to estimate GHG fluxes from former peat extraction fields to provide measurement-based recommendations for further management of these areas. In addition, there is lack of quantitative estimates of contribution of peatland plant cultivation, including berries, to total GHG emissions and climate change mitigation. Here, we compared carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes from nutrient-poor organic soils (Histosols) in former peat extraction fields currently used for cranberry (Vaccinium macrocarpon) and highbush blueberry (Vaccinium corymbosum) plantations, active peat extraction fields and pristine raised bogs. GHG flux measurements were conducted over two years using a manual chamber technique at 16 study sites (at least three sites of each land-use type) across 11 different raised bogs in the hemiboreal vegetation region of Europe (in Latvia). Across the studied land-use types, mean annual net CO2 fluxes, calculated as the difference between the annual soil heterotrophic respiration and the annual C input into soil with plant litter, ranged from near zero (-0.07 ± 0.68 t CO2-C ha-1 y-1) in the pristine raised bogs to 1.56 ± 0.19 t CO2-C ha-1 y-1 in active peat extraction fields. Furthermore, net CO2 fluxes had the largest contribution to total GHG emissions in both active peat extraction fields and berry plantations. The lowest annual CH4 fluxes were observed in cranberry plantations (6.65 ± 1.77 kg CH4-C ha-1 yr-1), while the highest were in pristine raised bogs (128.0 ± 27.5 kg CH4-C ha-1 yr-1), where CH4 fluxes accounted for the largest share of total GHG emissions. Annual N2O fluxes did not exceed 0.65 ± 0.33 kg N2O-N ha-1 yr-1 (in highbush blueberry plantations) and made a relatively low contribution to total GHG emissions compared to net CO2 and CH4 fluxes. Across the studied land-use types, the highest total GHG fluxes (the sum of annual net CO2, CH4 and N2O fluxes considering global warming potential values for a 100-year time horizon) were observed in active peat extraction fields (6.23 t CO2 eq. ha-1 yr-1), while the lowest were in cranberry plantations (1.50 t CO2 eq. ha-1 yr-1).Acknowledgments: The research was conducted within the scope of the European Commission LIFE Climate Action Programme Project “Peatland restoration for greenhouse gas emission reduction and carbon sequestration in the Baltic Sea region” (LIFE21 - CCM - LV - LIFE PeatCarbon, Project number: 101074396).

Lotic ecosystems are sources of greenhouse gases (GHGs) to the atmosphere, but their emissions are uncertain due to longitudinal GHG heterogeneities associated with point source pollution from anthropogenic activities. In this study, we quantified summer concentrations and fluxes of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and dinitrogen (N2), as well as several water quality parameters along the Rhine River and the Mittelland Canal, two critical inland waterways in Germany. Our main objectives were to compare GHG concentrations and fluxes along the two ecosystems and to determine the main driving factors responsible for their longitudinal GHG heterogeneities. The results indicated that the two ecosystems were sources of GHG fluxes to the atmosphere, with the Mittelland Canal being a hotspot for CH4 and N2O fluxes. We also found significant longitudinal GHG flux discontinuities along the mainstems of both ecosystems, which were mainly driven by divergent drivers. Along the Mittelland Canal, peak CO2 and CH4 fluxes coincided with point pollution sources such as a joining river tributary or the presence of harbors, while harbors and in-situ biogeochemical processes such as methanogenesis and respiration mainly explained CH4 and CO2 hotspots along the Rhine River. In contrast to CO2 and CH4 fluxes, N2O longitudinal trends along the two lotic ecosystems were better predicted by in-situ parameters such as chlorophyll-a concentrations and N2 fluxes. Based on a positive relationship with N2 fluxes, we hypothesized that in-situ denitrification was driving N2O hotspots in the Canal, while a negative relationship with N2 in the Rhine River suggested that coupled biological N2 fixation and nitrification accounted for N2O hotspots. These findings stress the need to include N2 flux estimates in GHG studies, as it can potentially improve our understanding of whether nitrogen is fixed through N2 fixation or lost through denitrification.

Forest soils are recognized as sources and sinks of greenhouse gases (GHG) (CO2, CH4, N2O), but there are limited data quantifying the magnitude of GHG fluxes at the soil-atmosphere interface across a range of landscape hydrogeomorphic conditions. In our study, GHG fluxes were measured in a forested watershed across a range of hydrogeomorphic locations (wetlands, hillslopes, riparian zones, etc) and evaluated in relation to temperature, antecedent flow conditions, and stream chemistry to help develop strategies to scale GHG emissions from the point scale to the watershed scale. Mean study period CO2 fluxes (0.61 to 2.89 gCm-2d-1) were positive at all sites, with larger fluxes occurring in well-drained soils. Negative fluxes (CH4 sinks) were found at the hillslope and lowland sites, while the wetland was a large source of CH4 emissions at the watershed scale. Mean CH4 fluxes ranged from -2.53 to 330.34 mgCm-2d-1. Nitrous oxide fluxes were low relative to other GHG fluxes (in terms of CO2 equivalent) and ranged between -0.72 to 0.70 mgNm-2d-1. Although carbon dioxide fluxes were positively correlated to soil temperature at all locations, CH4 and N2O fluxes were not significantly related to temperature, antecedent flow conditions, or stream chemistry at the watershed scale. However, strong differences in CO2 and CH4 fluxes related to landscape geomorphology were observed, and exceeded the magnitude of seasonal variations for CO2 and CH4 fluxes, suggesting that landscape hydrogeomorphology was likely a stronger predictor of GHG fluxes at the watershed scale than temperature and stream chemistry variables, at least within the confine of one watershed. In lieu of statistical approaches relying on environmental variables to predict GHG fluxes at the watershed scale, geomorphological approaches, potentially coupled with seasonal comparisons of GHG fluxes in each land class, might therefore be a promising research avenue to provide solid watershed wide estimates of GHG fluxes.

Evaluating temporal controls on greenhouse gas (GHG) fluxes in an Arctic tundra environment: An entropy-based approach

The invasions of the alien species such as Spartina alterniflora along the northern Jiangsu coastlines have posed a threat to biodiversity and the ecosystem function. Yet, limited attention has been given to their potential influence on greenhouse gas (GHG) emissions, including the diurnal variations of GHG fluxes that are fundamental in estimating the carbon and nitrogen budget. In this study, we examined the diurnal variation in fluxes of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) from a S. alterniflora intertidal flat in June, October, and December of 2013 and April of 2014 representing the summer, autumn, winter, and spring seasons, respectively. We found that the average CH4 fluxes on the diurnal scale were positive during the growing season while negative otherwise. The tidal flat of S. alterniflora acted as a source of CH4 in summer (June) and a combination of source and sink in other seasons. We observed higher diurnal variations in the CO2 and N2O fluxes during the growing season (1 536.5 mg CO2 m–2 h–1 and 25.6 μg N2O m–2 h–1) compared with those measured in the non-growing season (379.1 mg CO2 m–2 h–1 and 16.5 μg N2O m–2 h–1). The mean fluxes of CH4 were higher at night than that in the daytime during all the seasons but October. The diurnal variation in the fluxes of CO2 in June and N2O in December fluctuated more than that in October and April. However, two peak curves in October and April were observed for the diurnal changes in CO2 and N2O fluxes (prominent peaks were found in the morning of October and in the afternoon of April, respectively). The highest diurnal variation in the N2O fluxes took place at 15:00 (86.4 μg N2O m–2 h–1) in June with an unimodal distribution. Water logging in October increased the emission of CO2 (especially at nighttime), yet decreased N2O and CH4 emissions to a different degree on the daily scale because of the restrained diffusion rates of the gases. The seasonal and diurnal variations of CH4 and CO2 fluxes did not correlate to the air and soil temperatures, whereas the seasonal and diurnal variation of the fluxes of N2O in June exhibited a significant correlation with air temperature. When N2O and CH4 fluxes were converted to CO2-e equivalents, the emissions of N2O had a remarkable potential to impact the global warming. The mean daily flux (MF) and total daily flux (TDF) were higher in the growing season, nevertheless, the MF and TDF of CO2 were higher in October and those of CH4 and N2O were higher in June. In spite of the difference in the optimal sampling times throughout the observation period, our results obtained have implications for sampling and scaling strategies in estimating the GHG fluxes in coastal saline wetlands.

<strong class="journal-contentHeaderColor">Abstract.</strong> Arctic terrestrial greenhouse gas (GHG) fluxes of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) play an important role in the global GHG budget. However, these GHG fluxes are rarely studied simultaneously, and our understanding of the conditions controlling them across spatial gradients is limited. Here, we explore the magnitudes and drivers of GHG fluxes across fine-scale terrestrial gradients during the peak growing season (July) in sub-Arctic Finland. We measured chamber-derived GHG fluxes and soil temperature, soil moisture, soil organic carbon and nitrogen stocks, soil pH, soil carbon-to-nitrogen (C/N) ratio, soil dissolved organic carbon content, vascular plant biomass, and vegetation type from 101 plots scattered across a heterogeneous tundra landscape (5 km²). We used these field data together with high-resolution remote sensing data to develop machine learning models to predict (i.e., upscale) daytime GHG fluxes across the landscape at 2-m resolution. Our results show that this region was on average a daytime net GHG sink during the growing season. Although our results suggest that this sink was driven by CO₂ uptake, it also revealed small but widespread CH₄ uptake in upland vegetation types, shifting this region to an average net CH₄sink at the landscape scale during growing season, despite the presence of high-emitting wetlands. Average N₂O fluxes were negligible. CO₂ fluxes were controlled primarily by annual average soil temperature and biomass (both increase net sink) and vegetation type, CH₄ fluxes by soil moisture (increases net emissions) and vegetation type, and N₂O fluxes by soil C/N (lower C/N increases net source). These results demonstrate the potential of high spatial resolution modelling of GHG fluxes in the Arctic. They also reveal the dominant role of CO₂ fluxes across the tundra landscape, but suggest that CH₄ uptake might play a significant role in the regional GHG budget.

<strong class="journal-contentHeaderColor">Abstract.</strong> Arctic terrestrial greenhouse gas (GHG) fluxes of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) play an important role in the global GHG budget. However, these GHG fluxes are rarely studied simultaneously, and our understanding of the conditions controlling them across spatial gradients is limited. Here, we explore the magnitudes and drivers of GHG fluxes across fine-scale terrestrial gradients during the peak growing season (July) in sub-Arctic Finland. We measured chamber-derived GHG fluxes and soil temperature, soil moisture, soil organic carbon and nitrogen stocks, soil pH, soil carbon-to-nitrogen (C/N) ratio, soil dissolved organic carbon content, vascular plant biomass, and vegetation type from 101 plots scattered across a heterogeneous tundra landscape (5 km²). We used these field data together with high-resolution remote sensing data to develop machine learning models to predict (i.e., upscale) daytime GHG fluxes across the landscape at 2-m resolution. Our results show that this region was on average a daytime net GHG sink during the growing season. Although our results suggest that this sink was driven by CO₂ uptake, it also revealed small but widespread CH₄ uptake in upland vegetation types, shifting this region to an average net CH₄sink at the landscape scale during growing season, despite the presence of high-emitting wetlands. Average N₂O fluxes were negligible. CO₂ fluxes were controlled primarily by annual average soil temperature and biomass (both increase net sink) and vegetation type, CH₄ fluxes by soil moisture (increases net emissions) and vegetation type, and N₂O fluxes by soil C/N (lower C/N increases net source). These results demonstrate the potential of high spatial resolution modelling of GHG fluxes in the Arctic. They also reveal the dominant role of CO₂ fluxes across the tundra landscape, but suggest that CH₄ uptake might play a significant role in the regional GHG budget.

<strong class="journal-contentHeaderColor">Abstract.</strong> Arctic terrestrial greenhouse gas (GHG) fluxes of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) play an important role in the global GHG budget. However, these GHG fluxes are rarely studied simultaneously, and our understanding of the conditions controlling them across spatial gradients is limited. Here, we explore the magnitudes and drivers of GHG fluxes across fine-scale terrestrial gradients during the peak growing season (July) in sub-Arctic Finland. We measured chamber-derived GHG fluxes and soil temperature, soil moisture, soil organic carbon and nitrogen stocks, soil pH, soil carbon-to-nitrogen (C/N) ratio, soil dissolved organic carbon content, vascular plant biomass, and vegetation type from 101 plots scattered across a heterogeneous tundra landscape (5 km²). We used these field data together with high-resolution remote sensing data to develop machine learning models to predict (i.e., upscale) daytime GHG fluxes across the landscape at 2-m resolution. Our results show that this region was on average a daytime net GHG sink during the growing season. Although our results suggest that this sink was driven by CO₂ uptake, it also revealed small but widespread CH₄ uptake in upland vegetation types, shifting this region to an average net CH₄sink at the landscape scale during growing season, despite the presence of high-emitting wetlands. Average N₂O fluxes were negligible. CO₂ fluxes were controlled primarily by annual average soil temperature and biomass (both increase net sink) and vegetation type, CH₄ fluxes by soil moisture (increases net emissions) and vegetation type, and N₂O fluxes by soil C/N (lower C/N increases net source). These results demonstrate the potential of high spatial resolution modelling of GHG fluxes in the Arctic. They also reveal the dominant role of CO₂ fluxes across the tundra landscape, but suggest that CH₄ uptake might play a significant role in the regional GHG budget.

<strong class="journal-contentHeaderColor">Abstract.</strong> Arctic terrestrial greenhouse gas (GHG) fluxes of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) play an important role in the global GHG budget. However, these GHG fluxes are rarely studied simultaneously, and our understanding of the conditions controlling them across spatial gradients is limited. Here, we explore the magnitudes and drivers of GHG fluxes across fine-scale terrestrial gradients during the peak growing season (July) in sub-Arctic Finland. We measured chamber-derived GHG fluxes and soil temperature, soil moisture, soil organic carbon and nitrogen stocks, soil pH, soil carbon-to-nitrogen (C/N) ratio, soil dissolved organic carbon content, vascular plant biomass, and vegetation type from 101 plots scattered across a heterogeneous tundra landscape (5 km²). We used these field data together with high-resolution remote sensing data to develop machine learning models to predict (i.e., upscale) daytime GHG fluxes across the landscape at 2-m resolution. Our results show that this region was on average a daytime net GHG sink during the growing season. Although our results suggest that this sink was driven by CO₂ uptake, it also revealed small but widespread CH₄ uptake in upland vegetation types, shifting this region to an average net CH₄sink at the landscape scale during growing season, despite the presence of high-emitting wetlands. Average N₂O fluxes were negligible. CO₂ fluxes were controlled primarily by annual average soil temperature and biomass (both increase net sink) and vegetation type, CH₄ fluxes by soil moisture (increases net emissions) and vegetation type, and N₂O fluxes by soil C/N (lower C/N increases net source). These results demonstrate the potential of high spatial resolution modelling of GHG fluxes in the Arctic. They also reveal the dominant role of CO₂ fluxes across the tundra landscape, but suggest that CH₄ uptake might play a significant role in the regional GHG budget.

The impact of permafrost on carbon dioxide and methane fluxes in Siberia: A meta-analysis