Lotic ecosystems traversing mixed land-use landscapes are sources of GHGs to the atmosphere, but their emission strength is uncertain due to longitudinal GHG heterogeneities. In this study, we quantified N2O (as well as CO2 and CH4 concentrations) and N2 concentrations and several water quality parameters along the Rhine river and the Mittelland canal, two critical inland waterways in Germany in the summer of 2023. Our main objectives were to compare N2O concentrations along the two ecosystems and to identify the main drivers responsible for their longitudinal heterogeneities. The results indicated that N2O concentrations in both ecosystems were oversaturated relative to equilibrium concentrations (116 – 782 % saturation), particularly in the Mittelland canal. We also found significant longitudinal variability in % N2O saturation along the mainstems of both lotic ecosystems (CV = 43 – 68 %), with the highest variability in the Mittelland canal, suggesting that single N2O measurements along large lotic ecosystems are not representative of the entire reach. Overall, these significant longitudinal N2O heterogeneities were driven by differences in biogeochemical processes between the two lotic ecosystems. N2O was strongly related to N2 concentrations, with a negative relationship in the Rhine river and a positive relationship in the Mittelland canal. Based on these findings, we concluded that denitrification drives the N2O hotspots in the Canal, while coupled biological N2-fixation and nitrification accounted for N2O hotspots in the Rhine. These findings also highlight the need to include N2 concentration measurements in GHG sampling campaigns, as it has the potential to help better constrain nitrogen cycling in lotic ecosystems.

Abstract Lotic ecosystems transversing mixed land-use landscapes are sources of GHGs to the atmosphere, but their emissions are uncertain due to longitudinal GHG heterogeneities. In this study, we quantified summer CO2, CH4, N2O, and N2 concentrations, 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 along the two ecosystems and to determine the main driving factors responsible for their longitudinal heterogeneities. The results indicated that GHGs in the two ecosystems were up to three orders of magnitude oversaturated relative to equilibrium concentrations, particularly in the Mittelland canal, a hotspot for CH4 and N2O concentrations. We also found significant longitudinal variabilities in % GHG saturations along the mainstems of both ecosystems (CV = 26 – 98 %), with the highest variability recorded for CH4 concentrations in the Mittelland canal, suggesting that single GHG measurements along large lotic ecosystems are unrepresentative of entire reaches. However, these significant longitudinal GHG heterogeneities were driven by divergent drivers between the two lotic ecosystems. Within the Canal, longitudinal CO2 and CH4 hotspots were linked to external inflows of the GHGs from surrounding WWTPs. Contrastingly, harbors and in-situ biogeochemical processes such as methanogenesis and respiration explained CH4 and CO2 hotspots along the Rhine river. In contrast, N2O was strongly linked to N2 concentrations, with a negative relationship in the Rhine river and a positive relationship in the Mittelland canal. Based on these N2 relationships, we hypothesized that denitrification drove N2O hotspots in the Canal, while coupled N-fixation and nitrification accounted for N2O hotspots in the Rhine. This finding stresses the need to include N2 concentration measurements in GHG sampling campaigns, as it has the potential to determine whether nitrogen is fixed through N-fixation or lost through denitrification.

Stream ecosystems are actively involved in the biogeochemical cycling of carbon (C) and nitrogen (N) from terrestrial and aquatic sources. Streams hydrologically connected to peatland soils are suggested to receive significant quantities of particulate, dissolved, and gaseous C and N species, which directly enhance losses of greenhouse gases (GHGs), i.e., carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), and fuel in-stream GHG production. However, riverine GHG concentrations and emissions are highly dynamic due to temporally and spatially variable hydrological, meteorological, and biogeochemical conditions. In this study, we present a complete GHG monitoring system in a peatland stream, which can continuously measure dissolved GHG concentrations and allows to infer gaseous fluxes between the stream and the atmosphere and discuss the results from March 31 to August 25 at variable hydrological conditions during a cool spring and warm summer period. Stream water was continuously pumped into a water-air equilibration chamber, with the equilibrated and actively dried gas phase being measured with two GHG analyzers for CO2 and N2O and CH4 based on Off-Axis Integrated Cavity Output Spectroscopy (OA-ICOS) and Non-Dispersive Infra-Red (NDIR) spectroscopy, respectively. GHG measurements were performed continuously with only shorter measurement interruptions, mostly following a regular maintenance program. The results showed strong dynamics of GHGs with hourly mean concentrations up to 9959.1, 1478.6, and 9.9 parts per million (ppm) and emissions up to 313.89, 1.17, and 0.40 mg C or N m−2h−1 for CO2, CH4, and N2O, respectively. Significantly higher GHG concentrations and emissions were observed shortly after intense precipitation events at increasing stream water levels, contributing 59% to the total GHG budget of 762.2 g m−2 CO2-equivalents (CO2-eq). The GHG data indicated a constantly strong terrestrial signal from peatland pore waters, with high concentrations of dissolved GHGs being flushed into the stream water after precipitation. During drier periods, CO2 and CH4 dynamics were strongly influenced by in-stream metabolism. Continuous and high-frequency GHG data are needed to assess short- and long-term dynamics in stream ecosystems and for improved source partitioning between in-situ and ex-situ production.

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.

The natural abundance of plant and bulk soil N-15 isotopic signatures provides valuable insights into the magnitude of nitrogen cycling and loss processes within terrestrial ecosystems. However, N-15 isotopic signatures are highly variable in space due to natural and anthropogenic factors affecting N cycling processes and losses. To date, most studies on foliar and bulk soil N-15 isotopic signatures have focused on N-limited forest ecosystems at relatively large spatial scales, while similar studies in N-enriched ecosystems at finer spatial scales are lacking. To address this gap and evaluate links between soil N-15 isotopic signatures and ecosystem N cycling and loss processes (plant N uptake, N leaching, and gaseous loss), this study quantified foliar and bulk soil N-15 isotopic signatures, soil physicochemical parameters, gaseous (N2O), and hydrological (NO3) N losses at 80 sites distributed across a heterogeneous landscape (similar to 5.8 km(2)). To account for the spatial-temporal heterogeneity, the measurements were performed in four campaigns (March, June, September 2022, and March 2023) at sites that considered different land uses, soil types, and topography. Results indicated that foliar and bulk soil N-15 isotopic signatures were significantly (P < 0.05) more enriched in arable and grassland ecosystems than forests, suggesting a more open N cycle with significant N cycling and losses due to higher N inputs from fertilizers. Similar to soil inorganic N, N2O fluxes, and NO3 leaching rates, landscape-scale foliar and soil N-15 isotopic signatures varied widely spatially, particularly at grassland and arable land (-3 to 9.0 parts per thousand), with bivariate and multivariate analyses also showing significant relationships between landscape-scale soil N-15 isotopic signatures and the aforementioned parameters (r(2): 0.29 to 0.82). Based on these relationships, our findings suggested that foliar and bulk N-15 isotopic signatures may capture fine-scale areas with persistently high and low environmental N losses (N2O fluxes and NO3 leaching) within a heterogeneous landscape.

Global fluvial ecosystems are important sources of greenhouse gases (CO2, CH4, and N2O) to the atmosphere, but their estimates are plagued by uncertainties due to unaccounted spatio-temporal variabilities in the fluxes. In this study, we tested the potential of modeling these variabilities using several machine learning models (ML) and three different input datasets (remotely sensed vegetation indices, in-situ water quality, and a combination of both) from 20 headwater catchments in Germany that differ in catchment land use and stream size. We also upscaled fluvial GHG fluxes for Germany using the best ML model and explored the role of catchment land use on the GHG spatial-temporal trends. Model performance depended on the choice of ML model, input data and GHG type. Complex decision-tree-based models better predicted GHG concentrations and fluxes than other ML model types (r2 = 0.33 to 0.72). Our upscaled fluxes from catchment scale remotely sensed vegetation indices showed that total annual riverine CO2 equivalent fluxes from 2934 catchments in Germany ranged from 1.7 to 96.4 kg m-2 yr-1 (mean ± SE: 23.2 ± 0.001). The highest fluxes came from urban and intensively cropped catchments, while lower fluxes came from extensively cropped, forestry, and pasture-dominated catchments. Our study demonstrates that spatially and temporally resolved catchment vegetation indices from remotely sensed data in conjunction with machine learning models can be applied to upscale all three GHG concentrations and fluxes from diverse catchments, revealing important spatio-temporal trends associated with catchment land use.

Greenhouse gas emissions from headwater streams are linked to multiple sources influenced by terrestrial land use and hydrology, yet partitioning these sources at catchment scales remains highly unexplored. To address this gap, we sampled year-long stable water isotopes (δ18O and δ2H) from 17 headwater streams differing in catchment agricultural areas. We calculated mean residence times (MRT) and young water fractions (YWF) based on the seasonality of δ18O signals and linked these hydrological measures to catchment characteristics, mean annual water physico-chemical variables, and GHG % saturations. The MRT and the YWF ranged from 0.25 to 4.77 years and 3 to 53%, respectively. The MRT of stream water was significantly negatively correlated with stream slope (r2 = 0.58) but showed no relationship with the catchment area. Streams in agriculture-dominated catchments were annual hotspots of GHG oversaturation, which we attributed to precipitation-driven terrestrial inputs of dissolved GHGs for streams with shorter MRTs and nutrients and GHG inflows from groundwater for streams with longer MRTs. Based on our findings, future research should also consider water mean residence time estimates as indicators of integrated hydrological processes linking discharge and land use effects on annual GHG dynamics in headwater streams.

Anthropogenic activities increase the contributions of inland waters to global greenhouse gas (GHG; CO2, CH4, and N2O) budgets, yet the mechanisms driving these increases are still not well constrained. In this study, we quantified year-long GHG concentrations and fluxes, as well as water physico-chemical variables from 23 streams, three ditches, and two wastewater inflow sites across five catchments in Germany contrasted by land use. Using mixed-effects models, we determined the overall impact of land use and seasonality on the intra-annual variabilities of these parameters. We found that land use was more significant than seasonality in controlling the intra-annual variability of GHG concentrations and fluxes. Agricultural land use and wastewater inflows in settlement areas resulted in elevated riverine CO2, CH4, and N2O emissions, as substrate inputs by these sources appeared to favor in situ GHG production processes. Dissolved GHG inputs directly from agricultural runoff and waste-water inputs also contributed substantially to the annual emissions from these sites. Drainage ditches were hotspots for CO2 and CH4 fluxes due to high dissolved organic matter concentrations, which appeared to favor in situ production via respiration and methanogensis. Overall, the annual emission from anthropogenic-influenced streams and rivers in CO2-equivalents was up to 20 times higher (~71 kg CO2 m-2 yr-1) than from natural streams (~3 kg CO2 m-2 yr-1). Future studies aiming to estimate the contribution of riverine systems to GHG emissions should therefore focus on anthropogenically perturbed streams, as their GHG emission are much more variable in space and time.

Upscaling chamber measurements of soil greenhouse gas (GHG) fluxes from point scale to landscape scale remain challenging due to the high variability in the fluxes in space and time. This study measured GHG fluxes and soil parameters at selected point locations (n=268), thereby implementing a stratified sampling approach on a mixed-land-use landscape (∼5.8 km2). Based on these field-based measurements and remotely sensed data on landscape and vegetation properties, we used random forest (RF) models to predict GHG fluxes at a landscape scale (1 m resolution) in summer and autumn. The RF models, combining field-measured soil parameters and remotely sensed data, outperformed those with field-measured predictors or remotely sensed data alone. Available satellite data products from Sentinel-2 on vegetation cover and water content played a more significant role than those attributes derived from a digital elevation model, possibly due to their ability to capture both spatial and seasonal changes in the ecosystem parameters within the landscape. Similar seasonal patterns of higher soil/ecosystem respiration (SR/ER–CO2) and nitrous oxide (N2O) fluxes in summer and higher methane (CH4) uptake in autumn were observed in both the measured and predicted landscape fluxes. Based on the upscaled fluxes, we also assessed the contribution of hot spots to the total landscape fluxes. The identified emission hot spots occupied a small landscape area (7 % to 16 %) but accounted for up to 42 % of the landscape GHG fluxes. Our study showed that combining remotely sensed data with chamber measurements and soil properties is a promising approach for identifying spatial patterns and hot spots of GHG fluxes across heterogeneous landscapes. Such information may be used to inform targeted mitigation strategies at the landscape scale.

Accurate quantification of landscape soil greenhouse gas (GHG) exchange from chamber measurements is challenging due to the high spatial‐temporal variability of fluxes, which results in large uncertainties in upscaled regional and global flux estimates. We quantified landscape‐scale (6 km 2 in central Germany) soil/ecosystem respiration (SR/ER‐CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) fluxes at stratified sites with contrasting landscape characteristics using the fast‐box chamber technique. We assessed the influence of land use (forest, arable, and grassland), seasonality (spring, summer, and autumn), soil types, and slope on the fluxes. We also evaluated the number of chamber measurement locations required to estimate landscape fluxes within globally significant uncertainty thresholds. The GHG fluxes were strongly influenced by seasonality and land use rather than soil type and slope. The number of chamber measurement locations required for robust landscape‐scale flux estimates depended on the magnitude of fluxes, which varied with season, land use, and GHG type. Significant N 2 O‐N flux uncertainties greater than the global mean flux (0.67 kg ha −1 yr −1 ) occurred if landscape measurements were done at <4 and <22 chamber locations (per km 2 ) in forest and arable ecosystems, respectively, in summer. For CO 2 and CH 4 fluxes, uncertainties greater than the global median CO 2 ‐C flux (7,500 kg ha −1 yr −1 ) and the global mean forest CH 4 ‐C uptake rate (2.81 kg ha −1 yr −1 ) occurred at <2 forest and <6 arable chamber locations. This finding suggests that more chamber measurement locations are required to assess landscape‐scale N 2 O fluxes than CO 2 and CH 4, based on these GHG‐specific uncertainty thresholds.

Greenhouse gas fluxes (CO2, CH4, and N2O) from African streams and rivers are under‐represented in global datasets, resulting in uncertainties in their contributions to regional and global budgets. We conducted year‐long sampling of 59 sites in a nested‐catchment design in the Mara River, Kenya in which fluxes were quantified and their underlying controls assessed. We estimated annual basin‐scale greenhouse gas emissions from measured in‐stream gas concentrations, modeled gas transfer velocities, and determined the sensitivity of up‐scaling to discharge. Based on the total annual CO2‐equivalent emissions calculated from global warming potentials (GWP), the Mara basin was a net greenhouse gas source (294 ± 35 Gg CO2 eq yr−1). Lower‐order streams (1–3) contributed 81% of the total fluxes, and higher stream orders (4–8) contributed 19%. Cropland‐draining streams also exhibited higher fluxes compared to forested streams. Seasonality in stream discharge affected stream widths (and stream area) and gas exchange rates, strongly influencing the basin‐wide annual flux, which was 10 times higher during the high and medium discharge periods than the low discharge period. The basin‐wide estimate was underestimated by up to 36% if discharge was ignored, and up to 37% for lower stream orders. Future research should therefore include seasonality in stream surface areas in upscaling procedures to better constrain basin‐wide fluxes. Given that agricultural activities are a major factor increasing riverine greenhouse gas fluxes in the study region, increased conversion of forests and agricultural intensification has the possibility of increasing the contribution of the African continent to global greenhouse gas sources.

Populations of rodents such as common vole (Microtus arvalis) can develop impressive soil bioturbation activities in grasslands. These burrowing and nesting activities highly impact soil physicochemical properties as well as vegetation coverage and diversity. Managed grasslands in livestock production regions receive significant amounts of slurry, commonly at high loads at the beginning of the vegetation period. However, nothing is known how the combination of vole bioturbation and slurry application may affect the fluxes of C and N trace gases from grasslands. Here we report on an in-situ experiment and supporting laboratory incubations carried out during the period March to May 2020 comparing C (CH4, CO2) and N (N2O, NO, NH3) trace gas fluxes from Lolium perenne and Trifolium repens dominated montane grasslands with and without vole bioturbation and with and without slurry application, whereby, with regard to the latter, we further differentiated between acidified and non-acidified slurry. Vole bioturbation significantly (p < 0.05) increased soil NO and NH3 emissions, while N2O fluxes were only significantly (p < 0.05) enhanced in vole affected grassland patches following slurry application (+17%). Effects of vole bioturbation on CH4 fluxes were non-significant, while slurry application significantly reduced CH4 uptake. Compared to applications of non-acidified slurry, application of acidified slurry significantly (p < 0.05) reduced NH3 volatilization by approx. 38% and 50%, for vole and non-vole affected grassland patches, respectively. A significant effect of acidified slurry application on soil NO emissions was only observed for vole affected grassland patches. Significant (p < 0.05) reductions in aboveground net primary productivity and reduced plant N uptake are likely the main mechanisms explaining the stimulation of gaseous N losses following slurry application. Long-term measurements are needed to better understand effects of vole bioturbation on grassland soil C and N cycling and ecosystem GHG balance.

Greenhouse gas (GHG) emission estimates from tropical African rivers are underrepresented in global datasets, resulting in uncertainties in their contributions to global emissions. To better constrain the contribution of rivers and streams to GHG emissions from tropical landscapes and to determine possible underlying controlling processes, we implemented a monthly synoptic sampling program from January 2019 – December 2019, in which CO2, CH4 and N2O concentrations and fluxes, along with water quality and sediment parameters were measured from 60 river sites in the upper and middle catchments of the Mara River in Kenya (~8450 km2). Consistent with previous studies, Mara basin streams and rivers were mostly sources of GHGs, and were comparable to previous studies in tropical and temperate regions. Based on CO2 equivalents, CO2 accounted for >60% of the emissions, while CH4 and N2O (<35%) were minor contributors. There were higher mean values of CO2 and N2O fluxes in streams draining croplands (92±9 CO2 mmol m-2 d-1 and 14±2 N2O µmol m-2 d-1) compared to those draining forested areas (45±5 CO2 mmol m-2 d-1 and 3±0.6 N2O µmol m-2 d-1). CH4 fluxes showed no significant variation with land use. CO2 and CH4 concentrations had a negative correlation with dissolved oxygen (DO) and a positive correlation with dissolved organic carbon (DOC) and fine benthic organic matter (FBOM), while N2O was positively correlated to nitrate (NO3-N) and negatively correlated to DO. Based on the significant relationships of all three gases with DO and their substrates, we inferred that GHG concentrations were mainly controlled by in-stream biogeochemical processes - i.e. methanogenesis for CH4, net heterotrophy for CO2 and coupled nitrification-denitrification for N2O. Changes in discharge, driven by precipitation events, significantly accounted for the seasonal variation in GHGs concentration and flux, with clear differences between the driest months (March and April) and the wettest (October-December). During low-discharge periods, streams were characterized by lower DO, lower nitrate NO3-N, higher DOC, and higher FBOM concentrations compared to the wet season. This resulted in significantly higher CH4 and CO2 concentrations, which could be attributed to increased in-stream production through the aforementioned processes as a result of increased water residence times. In contrast, N2O concentrations in the dry season were lower than in the wet season, indicating that due to low DO and NO3-N concentrations, produced N2O may have been further reduced to N2 during denitrification. However, as fluxes are a function of both concentration and the discharge-related gas transfer velocity (k), all GHG’s exhibited higher fluxes in the wet season compared to the dry season. Mean monthly CO2 and N2O concentrations also responded positively to discharge, suggesting that terrestrial inputs could also account for higher fluxes during the wet season. In future studies, we therefore plan to incorporate process measurements (e.g. nitrification, denitrification and ecosystem metabolism) across seasons in conjunction with measurements of GHG fluxes and environmental parameters. This will allow to a) elucidate the importance of in-stream production versus terrestrial inputs as controls of fluxes of GHGs and to b) attribute observed fluxes to specific biogeochemical processes.

Anthropogenic activities have led to increases in nitrous oxide (N 2 O) emissions from river systems, but there are large uncertainties in estimates due to lack of data in tropical rivers and rapid increase in human activity. We assessed the effects of land use and river size on N 2 O flux and concentration in 46 stream sites in the Mara River, Kenya, during the transition from the wet (short rains) to dry season, November 2017 to January 2018. Flux estimates were similar to other studies in tropical and temperate systems, but in contrast to other studies, land use was more related to N 2 O concentration and flux than stream size. Agricultural stream sites had the highest fluxes (26.38 ± 5.37 N 2 O‐N μg·m –2 ·hr –1 ) compared to both forest and livestock sites (5.66 ± 1.38 N 2 O‐N μg·m –2 ·hr –1 and 6.95 ± 2.96 N 2 O‐N μg·m –2 ·hr –1 , respectively). N 2 O concentrations in forest and agriculture streams were positively correlated to stream carbon dioxide (CO 2 ‐C (aq) ) but showed a negative correlation with dissolved organic carbon, and the dissolved organic carbon:dissolved inorganic nitrogen ratio. N 2 O concentration in the livestock sites had a negative relationship with CO 2 ‐C (aq) and a higher number of negative fluxes. We concluded that in‐stream chemoautotrophic nitrification was likely the main biogeochemical process driving N 2 O production in agricultural and forest streams, whereas complete denitrification led to the consumption of N 2 O in the livestock stream sites. These results point to the need to better understand the relative importance of nitrification and denitrification in different habitats in producing N 2 O and for process‐based studies.