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Methane (CH₄) is a potent greenhouse gas and its concentrations have tripled in the atmosphere since the industrial revolution. There is evidence that global warming has increased CH₄emissions from freshwater ecosystems^1,2, providing positive feedback to the global climate. Yet for rivers and streams, the controls and the magnitude of CH₄emissions remain highly uncertain^3,4. Here we report a spatially explicit global estimate of CH₄emissions from running waters, accounting for 27.9 (16.7–39.7) Tg CH₄ per year and roughly equal in magnitude to those of other freshwater systems^5,6. Riverine CH₄emissions are not strongly temperature dependent, with low average activation energy (E_M = 0.14 eV) compared with that of lakes and wetlands (E_M = 0.96 eV)¹. By contrast, global patterns of emissions are characterized by large fluxes in high- and low-latitude settings as well as in human-dominated environments. These patterns are explained by edaphic and climate features that are linked to anoxia in and near fluvial habitats, including a high supply of organic matter and water saturation in hydrologically connected soils. Our results highlight the importance of land–water connections in regulating CH₄supply to running waters, which is vulnerable not only to direct human modifications but also to several climate change responses on land.

 

Abstract. Despite their small spatial extent, fluvial ecosystems play a significant role in processing and transporting carbon in aquatic networks, which results in substantial emission of methane (CH4) into the atmosphere. For this reason, considerable effort has been put into identifying patterns and drivers of CH4 concentrations in streams and rivers and estimating fluxes to the atmosphere across broad spatial scales. However, progress toward these ends has been slow because of pronounced spatial and temporal variability of lotic CH4 concentrations and fluxes and by limited data availability across diverse habitats and physicochemical conditions. To address these challenges, we present a comprehensive database of CH4 concentrations and fluxes for fluvial ecosystems along with broadly relevant and concurrent physical and chemical data. The Global River Methane Database (GriMeDB; https://doi.org/10.6073/pasta/f48cdb77282598052349e969920356ef, Stanley et al., 2023) includes 24 024 records of CH4 concentration and 8205 flux measurements from 5029 unique sites derived from publications, reports, data repositories, unpublished data sets, and other outlets that became available between 1973 and 2021. Flux observations are reported as diffusive, ebullitive, and total CH4 fluxes, and GriMeDB also includes 17 655 and 8409 concurrent measurements of concentrations and 4444 and 1521 fluxes for carbon dioxide (CO2) and nitrous oxide (N2O), respectively. Most observations are date-specific (i.e., not site averages), and many are supported by data for 1 or more of 12 physicochemical variables and 6 site variables. Site variables include codes to characterize marginal channel types (e.g., springs, ditches) and/or the presence of human disturbance (e.g., point source inputs, upstream dams). Overall, observations in GRiMeDB encompass the broad range of the climatic, biological, and physical conditions that occur among world river basins, although some geographic gaps remain (arid regions, tropical regions, high-latitude and high-altitude systems). The global median CH4 concentration (0.20 µmol L−1) and diffusive flux (0.44 mmolm-2d-1) in GRiMeDB are lower than estimates from prior site-averaged compilations, although ranges (0 to 456 µmol L−1 and −136 to 4057 mmolm-2d-1) and standard deviations (10.69 and 86.4) are greater for this larger and more temporally resolved database. Available flux data are dominated by diffusive measurements despite the recognized importance of ebullitive and plant-mediated CH4 fluxes. Nonetheless, GriMeDB provides a comprehensive and cohesive resource for examining relationships between CH4 and environmental drivers, estimating the contribution of fluvial ecosystems to CH4 emissions, and contextualizing site-based investigations.

 

The Global River Methane Database (GriMeDB) is a compilation of measurements of CH4 concentrations and fluxes for flowing water environments derived from publications, reports, data repositories, and other outlets between 1973 and 2021. Assembly of GRiMeDB was motivated by the goal of having a centralized, standardized resource to facilitate further studies of CH4 pattern and process in flowing water systems, upscaling efforts, and identification of tendencies in when, where, and how CH4 has been sampled in streams and rivers across the world. Thus, CH4 data are supported by concurrent observations (as available) of aquatic CO2, N2O, temperature, conductivity, pH, dissolved oxygen, nitrogen, phosphorus, organic carbon, and discharge, along with site data (latitude, longitude, elevation, and [as available]: stream order, elevation, channel slope, catchment size, and codes for distinct or disturbed channel types). GRiMeDB includes over 24,000 records of CH4 concentration and greater than 8,000 flux measurements from over 5,000 unique sites, most of which are resolved to the daily time scale. 

The Global River Methane Database (GriMeDB) is a compilation of measurements of CH4 concentrations and fluxes for flowing water environments derived from publications, reports, data repositories, and other outlets between 1973 and 2021. Assembly of GRiMeDB was motivated by the goal of having a centralized, standardized resource to facilitate further studies of CH4 pattern and process in flowing water systems, upscaling efforts, and identification of tendencies in when, where, and how CH4 has been sampled in streams and rivers across the world. Thus, CH4 data are supported by concurrent observations (as available) of aquatic CO2, N2O, temperature, conductivity, pH, dissolved oxygen, nitrogen, phosphorus, organic carbon, and discharge, along with site data (latitude, longitude, elevation, and [as available]: stream order, elevation, channel slope, catchment size, and codes for distinct or disturbed channel types). GRiMeDB includes over 24,000 records of CH4 concentration and greater than 8,000 flux measurements from over 5,000 unique sites, most of which are resolved to the daily time scale. 

Lakes emit globally significant amounts of carbon dioxide (CO₂) to the atmosphere, but quantifying these rates for individual lakes is extremely challenging. The exchange of CO₂across the air‐water interface is driven by physical, chemical, and biological processes in both the lake and the atmosphere that vary at multiple spatial and temporal scales. None of the methods we use to estimate CO₂flux fully capture this heterogeneous gas exchange. Here, we compared concurrent CO₂flux estimates from a single lake based on commonly used methods. These include floating chambers (FCs), eddy covariance (EC), and two concentration gradient‐based methods labeled fixed (F‐pCO₂) and spatial (S‐pCO₂). At the end of summer, cumulative carbon fluxes were similar between EC, F‐pCO₂, and S‐pCO₂ methods (−4, −4, and −9.5 gC m⁻²), while methods diverged in directionality of fluxes during the fall turnover period (−50, 43, and 38 gC m⁻²). Collectively, these results highlight the discrepancies among methods and the need to acknowledge the uncertainty when using any of them to approximate this heterogeneous flux.

 

The extent to which terrestrial organic matter supports aquatic consumers remains uncertain because factors regulating resource flows are poorly understood. We sampled 12 lakes throughout the Sierra Nevada (California, USA) spanning large gradients in elevation and size to evaluate how watershed attributes and lake morphometry influence resource flows to lake carbon pools and zooplankton. We found that the size and composition of carbon pools in lakes were often more strongly determined by watershed or lake features rather than by elevational position. Using three different tracers of resource origin (δ¹³C, Δ¹⁴C, C:N ratio), we found terrestrial contributions to most lake resource pools (dissolved organic carbon, particulate organic matter (POM), sediments) and pelagic consumers (zooplankton) were more strongly related to local‐scale watershed features such as vegetation cover or watershed area: lake area rather than to elevation. Landscape patterns in multiple tracers indicated consistent contribution of within‐lake C sources to bulk resource pools across elevations (POM, sediments, zooplankton). δ¹³C‐enrichment of lake C pools and overlap with δ¹³C of terrestrial resources can arise due to reduced fractionation of¹³C by phytoplankton under CO₂limitation, therefore we recommend careful consideration of potential environmental drivers when interpreting among‐lake patterns in δ¹³C. Our findings emphasize the importance of local‐scale variation in mediating terrestrial contributions to lake food webs.

 

Lakes are conduits of greenhouse gases to the atmosphere; however, most efflux estimates for individual lakes are based on extrapolations from a limited number of locations. Within‐lake variability in carbon dioxide (CO₂) and methane (CH₄) arises from differences in water sources, mixing, atmospheric exchange, and biogeochemical transformations, all of which vary across multiple temporal and spatial scales. We asked, how variable are CO₂and CH₄across the surface of a single lake, how do spatial patterns change seasonally, and how well does the typical sampling location represent the entire lake surface? During the 2016 ice‐free period, we mapped surface water concentrations of CO₂and CH₄approximately weekly in Lake Mendota (USA) and modeled diffusive gas exchange. During stratification, CO₂was generally lower than atmospheric saturation (mean 19.81 μM) and relatively homogenous (mean coefficient of variation 0.12), whereas CH₄was routinely extremely supersaturated (mean 0.29 μM) with greater spatial heterogeneity (mean coefficient of variation 0.65). During fall mixis, concentrations of both gases increased and became more spatially variable, but their spatial arrangements differed. In this system, samples collected from the lake center reasonably well represented the spatially weighted mean CO₂concentration but overestimated annual CO₂efflux by 21%. For CH₄, the lake center underestimated annual diffusive efflux by only 8.6% but poorly represented lakewide concentrations and fluxes on any given day. Upscaling from a single site to the whole lake requires consideration of spatial variation to assess lakewide carbon dynamics due to heterogeneity in within‐lake processing, transport to the lake surface, and exchange with the atmosphere.