A systematic review of biochar research, with a focus on its stability in situ and its promise as a climate mitigation strategy.

Rewetting fens in agricultural landscapes serves as a method to counteract net emissions of greenhouse gases (GHGs) into the atmosphere. The prevalent assumption is that the rewetted area exhibits uniform behavior; however, peripheral zones of a wetland may experience elevated nutrient levels from the surrounding landscape's drainage, leading to internal gradients of biogeochemical processes within the wetland. This aspect is frequently overlooked in GHG budgets for rewetted fens.In this investigation, we employed an automated GHG flux system (SkyLine) to quantify the annual soil GHG budget at the transition from mineral upland to organic soils in a wet fen, including a partially obstructed drainage ditch. From February 2022 to January 2023, CO2, CH4, and N2O fluxes were automatically measured at 27 plots along a 30-meter transect resulting in over 40.000 fluxes per gas for the site. Spatiotemporal patterns of GHG fluxes were studied alongside measurements of groundwater level, soil moisture, and temperature. Due to the chamber configuration, vegetation was excluded from the measurement plots, allowing for the assessment of net soil GHG exchange.Overall, CO2 and N2O fluxes exhibited similar seasonal trends, indicating comparable climatic and hydrological drivers. CO2 fluxes displayed a distinct seasonal pattern, peaking during the warmest periods. Similarly, N2O fluxes reached maximum values in the summer, however, responding rapidly to fluctuating groundwater caused by precipitation. During these hot moment N2O fluxes increased from close-to-zero to maximum values and reaching minimum again within hours to days. CH4 fluxes were overall below zero with minimal seasonal variability, resulting in a net uptake, though occasional emission spikes occurred. Temporal stability of GHG fluxes across the transect was observed, but flux magnitudes varied significantly between individual plot. Annual soil CO2 effluxes varied sixfold, and annual N2O emissions varied tenfold across the transect.Converted to CO2-equivalents, it became evident that, in the absence of plants, that the GHG budget in the border zone of the fen was dominated by N2O emissions, likely due to the net import of nitrogen with groundwater from upland fields fueling high rates of denitrification in the subsoil. CH4 did not significantly contribute to the GHG budget for the plots on peat but dominated for the ditch due to ebullitions.Our findings show the dynamic nature of GHG fluxes in response to environmental variations in peat soils, emphasizing the impact of fluctuating groundwater. While rewetting may enhance complete denitrification and reduce net N2O, border zones of rewetted wetlands may still experience dynamic hydrology and nutrient inputs. Factors, that collectively promote N2O emissions, particularly during critical, short-lived hot moments. Episodic N2O emissions from this zone can disproportionately influence the magnitude of GHG emission reduction following rewetting.Preliminary results of our net soil GHG budget analysis for this location will be presented, highlighting the necessity for high-frequency flux measurements to elucidate underlying causes of temporal patterns in GHG fluxes and their relationship to biogeochemical, hydrological, and climatic drivers.

<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.

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.

<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 potential carbon neutrality of sustainable viticulture showed through a comprehensive assessment of the greenhouse gas (GHG) budget of wine production

Coupled soil oxygen and greenhouse gas dynamics under variable hydrology

Land-use change in tropical peatlands substantially impacts peat emissions of methane (CH4) and nitrous oxide (N2O) in addition to emissions of carbon dioxide (CO2). However, assessments of full peat greenhouse gas (GHG) budgets are scarce and CH4 and N2O contributions remain highly uncertain. The objective of our research was to assess changes in peat GHG flux and budget associated with peat swamp forest disturbance and conversion to oil palm plantation and to evaluate drivers of variation in trace gas fluxes. Over a period of one and a half year, we monitored monthly CH4 and N2O fluxes together with environmental variables in three undrained peat swamp forests and three oil palm plantations on peat in Central Kalimantan. The forests included two primary forests and one 30-year-old secondary forest. We calculated the peat GHG budget in both ecosystems using soil respiration and litterfall rates measured concurrently with CH4 and N2O fluxes, site-specific soil respiration partitioning ratios, and literature-based values of root inputs and dissolved organic carbon export. Peat CH4 fluxes (kg CH4 ha−1 year−1) were insignificant in oil palm (0.3 ± 0.4) while emissions in forest were high (14.0 ± 2.8), and larger in wet than in dry months. N2O emissions (kg N2O ha−1 year−1) were highly variable spatially and temporally and similar across land-uses (5.0 ± 3.9 and 5.2 ± 3.7 in oil palm and forest). Temporal variation of CH4 was controlled by water table level and soil water-filled pore space in forest and oil palm, respectively. Monthly fluctuations of N2O were linked to water table level in forest. The peat GHG budget (Mg CO2 equivalent ha−1 year−1) in oil palm (31.7 ± 8.6) was nearly eight times the budget in forest (4.0 ± 4.8) owing mainly to decreased peat C inputs and increased peat C outputs. The GHG budget was also ten times higher in the secondary forest (10.2 ± 4.5) than in the primary forests (0.9 ± 3.9) on the account of a larger peat C budget and N2O emission rate. In oil palm 96% of emissions were released as CO2 whereas in forest CH4 and N2O together contributed 65% to the budget. Our study highlights the disastrous atmospheric impact associated with forest degradation and conversion to oil palm in tropical peatlands and stresses the need to investigate GHG fluxes in disturbed undrained lands.

Grassland ecosystems play an essential role in climate regulation through carbon (C) storage in plant and soil. But, anthropogenic practices such as livestock grazing, grazing related excreta nitrogen (N) deposition, and manure/fertilizer N application have the potential to reduce the effectiveness of grassland C sink through increased nitrous oxide (N2O) and methane (CH4) emissions. Although the effect of anthropogenic activities on net greenhouse gas (GHG) fluxes in grassland ecosystems have been investigated at local to regional scales, estimates of net GHG balance at the global scale remains uncertain. With the data-model framework integrating empirical estimates of livestock CH4 emissions with process-based modeling estimates of land CO2, N2O and CH4 fluxes, we examined the overall global warming potential (GWP) of grassland ecosystems during 1961–2010. We then quantified the grassland-specific and regional variations to identify hotspots of GHG fluxes. Our results show that, over a 100-year time horizon, grassland ecosystems sequestered a cumulative total of 113.9 Pg CO2-eq in plant and soil, but then released 91.9 Pg CO2-eq to the atmosphere, offsetting 81% of the net CO2 sink. We also found large grassland-specific variations in net GHG fluxes, with pasturelands acting as a small GHG source of 1.52 ± 143 Tg CO2-eq yr−1 (mean ± 1.0 s.d.) and rangelands a strong GHG sink (−442 ± 266 Tg CO2-eq yr−1) during 1961–2010. Regionally, Europe acted as a GHG source of 23 ± 10 Tg CO2-eq yr−1, while other regions (i.e. Africa, Southern Asia) were strong GHG sinks during 2001–2010. Our study highlights the importance of considering regional and grassland-specific differences in GHG fluxes for guiding future management and climate mitigation strategies in global grasslands.

To evaluate the effect of vegetation change on greenhouse gas (GHG) budget from a wetland ecosystem, the CO2, CH4 and N2O budgets from whole area (21.5 ha) of the Bibai Wetland, where dwarf bamboo (Sasa) or Ilex has invaded into original Sphagnum dominated vegetation, located in Hokkaido, Japan were estimated. The original Sphagnum-dominated vegetation was changed from a sink to a source of CO2 by invasion of short-Sasa (50 cm &gt; height), while the invasion of tall-Sasa (50 cm &lt; height &lt; 150 cm) or Ilex increased CO2 uptake. Annual CH4 emission was decreased by the invasion of Sasa or Ilex. The annual N2O emission was slightly increased by invasion of Ilex only. These GHG budgets were correlated with the environmental factors related to the water table depth. The distribution of vegetation and environmental factors was estimated from satellite image bands, and the GHG budget of the entire wetland was estimated. The whole wetland area was considered to be a sink for GHG (−113 Mg CO2-eq y−1) and CO2 uptake by tall-Sasa occupied 71% of the GHG budget. The vegetation change due to the lowering of the water table depth currently increases the rate of carbon accumulation in the ecosystem by about 5 times.

During 2010-2013, we investigated the effects of stump harvesting on greenhouse gas (GHG) fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) with the flux-gradient technique at four experimental plots in a hemiboreal forest in Sweden. All plots were clear-cut and soil scarified and two of the plots were additionally stump harvested. The two clear-cut plots served as control plots. Due to differences in topography, we had one wetter and one drier plot of each treatment. All plots exhibited substantial emissions of GHGs and we noted significant effects of wetness on CO2, CH4 and N2O fluxes within treatments and significant effects of stump harvesting on CO2 and N2O fluxes at the dry plots. The CO2 emissions were lower at the dry stump harvested plot than at the dry control, but when estimated emissions from the removed stumps were added, total CO2 emissions were higher at the stump harvested plot, indicating a small enhancement of soil respiration. In addition, we noted significant emissions of N2O at this plot. At the wet plots, CO2 emissions were higher at the stump harvested plot, also suggesting a treatment effect but differences in wetness and vegetation cover at these plots make this effect more uncertain. At the wet plots, we noted sustained periods (weeks to months) of net N2O uptake. During the year with simultaneous measurements of the abovementioned GHGs, GHG budgets were 1.224×103 and 1.442×103 gm-2 of CO2-equivalents at the wet and dry stump harvested plots, respectively, and 1.070×103 and 1.696×103 gm-2 of CO2-equivalents at the wet and dry control plots, respectively. CO2 fluxes dominated GHG budgets at all plots but N2O contributed with 17% at the dry stump harvested plot. For the full period 2010-2013, total carbon (CO2+CH4) budgets were 4.301×103 and 4.114×103 g m-2 of CO2-eqvivalents at the wet and dry stump harvest plots, respectively and 4.107×103 and 5.274×103 gm-2 of CO2-equivalents at the wet and dry control plots, respectively. Our results support recent studies suggesting that stump harvesting does not result in substantial increase in CO2 emissions but uncertainties regarding GHG fluxes (especially N2O) remain and more long-term measurements are needed before robust conclusions can be drawn.

National greenhouse gas (GHG) budget, including CO2, CH4 and N2O has increasingly become a topic of concern in international climate governance. China is paying increasing attention to reducing GHG emissions and increasing land sinks to effectively mitigate climate change. Accurate estimates of GHG fluxes are crucial for monitoring progress toward mitigating GHG emissions in China. This study used comprehensive methods, including emission factor methods, process-based models, atmospheric inversions, and data-driven models, to estimate the long-term trends of GHG sources and sinks from all anthropogenic and natural sectors in China's mainland during 2000–2023, and produced an up-to-date China GHG Budget dataset (CNGHG). The total gross emissions of the three GHGs show a 3-fold increase from 5.0 (95% CI: 4.9–5.1) Gt CO2-eq yr−1 (in 2000) to 14.3 (95% CI: 13.8–14.8) Gt CO2-eq yr−1 (in 2023). CO2 emissions represented 81.8% of the GHG emissions in 2023, while 12.7% and 5.5% were for CH4 and N2O, respectively. As the largest CO2 source, the energy sector contributed 87.4% CO2 emissions. In contrast, the agriculture, forestry and other land use sector was the largest sector of CH4 and N2O, representing 50.1% and 66.3% emissions, respectively. Moreover, China's terrestrial ecosystems serve as a net CO2 sink (1.0 Gt CO2 yr−1, 95% CI: 0.2–1.9 Gt CO2 yr−1) during 2012 to 2021, equivalent to an average of 14.3% of fossil CO2 emissions. Our GHG emission estimates showed a general consistency with national GHG inventories, with gridded and sector-specific estimates of GHG fluxes over China, providing the basis for curtailing GHG emissions for each region and sector.

&amp;lt;p&amp;gt;Nationwide data comparisons show that greenhouse gas (GHG) budgets vary not only due to land-use and water table but seem to reflect biogeographical regions. Therefore, the KliMoBay project pursues two main objectives pertaining to GHG: (1) collating all archival GHG data available for Bavarian peatlands to derive regional emission factors and as a foundation for spatial and temporal modelling of GHG budgets in different land-use and peatland types, and (2) closing gaps identified in step (1) via new eddy covariance and chamber-based GHG flux measurements in 2020 and 2021.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;br&amp;gt;The Bavarian GHG peatland dataset currently consists of 163 annual budgets from 76 treatments in seven peatland regions. For our empirical modelling approach carbon dioxide and methane data for different land-use types are regressed against the mean annual water table. Due to its high variability no such dependence could be found for nitrous oxide; hence a land-use specific mean value is used instead.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;br&amp;gt;Data gaps identified in Bavaria that were chosen for GHG measurements within the project are peatland forests (both natural and managed) on the one hand, and deeply drained grassland peat soils along with the transition period during rewetting measures in differently managed grassland peat soils on the other hand. For peatland forests we continued GHG flux analyses at two existing eddy covariance towers (one near-natural, one drained but left to natural succession after a windbreak in 2015). For grassland peat soils we compare two pre-Alpine locations with different drainage depths and management intensities with rewetting measures implemented at the deeply drained site in the fall of 2020.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;br&amp;gt;First results suggest that out of all land-use categories only the near-natural forested peatland location is a persistent GHG sink. Both, using peatlands as arable land and high-intensity grassland management practices lead to very high GHG emissions; partly because these peatlands tend to be drained more deeply. However, comparing budgets from grassland peat soils managed with different intensities at the same drainage level shows that changed management practices can reduce carbon dioxide emissions by up to 500 g CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;-C m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; yr&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt;. The drained peatland forest left to natural succession is still a GHG source five years after clear-cutting. Given that current tendencies continue, it is expected to show carbon uptake on an annual basis in the near future though. Comparing the 2020 and 2021 GHG measurements for grassland peat soils within the project clearly shows a heterogeneity between the different management practices. Yet, despite the rewetting measures at the deeply drained location and a higher water table at both locations as a result of distinctly different weather conditions in the two years, there seems to be surprisingly little inter-annual variability in the GHG fluxes. We are currently still working on explaining these results by further studying auxiliary variables recorded at the measurement locations.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;br&amp;gt;KliMoBay is funded by the Bavarian State Ministry of Environment and Consumer Protection through the European Regional Development Fund.&amp;lt;/p&amp;gt;

Freshwater wetlands can contribute significantly to the global carbon budget as a net source or sink of the major greenhouse gas (GHG) fluxes such as carbon dioxide (FCO2) and methane (FCH4). The amount of GHG fluxes in the freshwater wetlands is highly variable and depends on a range of environmental drivers. These wetlands are commonly hypothesized to be net sinks (i.e., burial) of FCO2 and net sources (emission) of FCH4 at the monthly to annual scales. Understanding the environmental controls on the wetland GHG fluxes is essential for an accurate estimation of the global GHG budget, which is often used as a pivotal measure to reduce GHG emissions and enhance carbon sequestration. In this study, we analyzed FLUXNET data from 38 freshwater wetlands located across the globe to investigate the relationships of monthly-scale GHG fluxes with various climatic and ecohydrological drivers. Data analytics with multivariate pattern recognition techniques—including principal component analysis, factor analysis, and partial least squares regression— were performed to identify and quantify the dominant controls of wetland FCO2 and FCH4 fluxes. The environmental controls on the GHG fluxes in freshwater wetlands were found to highly vary based on the climatic zones. In the tropical (i.e., mega thermal) zone, the GHG fluxes were overall primarily controlled by photosynthetically active radiation (PAR), soil temperature (TS), wind speed (WS), friction velocity (USTAR), and vapor pressure deficit (VPD). However, the latent heat flux (LE) and VPD, alongside PAR, TS, and USTAR, exhibited the dominant controls on the GHG fluxes in the dry (or arid) zone wetlands. Both GHG fluxes in wetlands of the temperate (or mesothermal) zone were mainly controlled by water table depth (WL), TS, and LE. Surprisingly, PAR did not appear to be a strong driver of the monthly averaged fluxes in the temperate wetlands. In contrast, PAR, LE, TS, WS, and USTAR were the primary controlling factors of the GHG fluxes in wetlands representing continental (or microthermal) climates. However, in wetlands of the polar (alpine) region, sensible heat flux (H) had a strong linkage with the GHG fluxes, alongside the controls of PAR, TS, WS, VPD and USTAR. These findings and new knowledge can help inform wetland management and conservation strategies, particularly in the context of climate and land cover changes. Effective management and conservation of wetlands can help reduce GHG emissions, thereby contributing to the mitigation efforts on global warming.