Search

While wetlands are the largest natural source of methane (CH 4 ) to the atmosphere, they represent a large source of uncertainty in the global CH 4 budget due to the complex biogeochemical controls on CH 4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH 4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH 4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH 4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH 4 emissions., (© 2021 John Wiley & Sons Ltd.)

Storm surges can substantially alter the water level and salinity in tidal salt marshes. Little is known about how changes experienced during storm surges affect greenhouse gas emissions (GHG; CO 2 , CH 4 , N 2 O) from tidal salt marsh soils. Understanding how storm surges influence ecosystem processes is critical for evaluating the ecosystem's sensitivity to sea level rise. To explore how hurricane-induced changes in salinity affect GHG emissions, we exposed intact soil mesocosms (0-9 cm depth) from a Mid-Atlantic temperate salt marsh to pulse changes in salinity experienced at the site before, during, and after Hurricane Joaquin in 2015. Soil temperature, oxygen, and water level were kept constant to avoid confounding effects throughout the experiment. Automated measurements (hourly resolution) of soil GHG emissions were recorded in control (i.e., no salinity changes) and treatment mesocosms, and combined with soil pore water chemistry (i.e., SO 4 2- , S 2- , Fe 2+ , TN b , redox potential, pH) to characterize the biogeochemical responses. Using mixed effects models, we found that the role of different biogeochemical processes, such as sulfur cycling, changed throughout the experiment, underscoring the complex nature of GHG emissions in tidal salt marsh soils. Overall, soils subjected to a salinity decrease had greater GHG emissions than control soils, which were maintained at 17 ppt. The treatment soils had a 24% and 23% increase in global warming potential (20- and 100-year scenarios, respectively) indicating that storm surges can produce pulses of GHG emissions. However, both CH 4 and N 2 O emissions returned to baseline values (following hysteresis responses) when initial conditions were reestablished. The results support the fact that tidal salt marshes are resilient ecosystems, as soil GHG emissions recovered relatively quickly from the pulse event., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Tree stems from wetland, floodplain and upland forests can produce and emit methane (CH 4 ). Tree CH 4 stem emissions have high spatial and temporal variability, but there is no consensus on the biophysical mechanisms that drive stem CH 4 production and emissions. Here, we summarize up to 30 opportunities and challenges for stem CH 4 emissions research, which, when addressed, will improve estimates of the magnitudes, patterns and drivers of CH 4 emissions and trace their potential origin. We identified the need: (1) for both long-term, high-frequency measurements of stem CH 4 emissions to understand the fine-scale processes, alongside rapid large-scale measurements designed to understand the variability across individuals, species and ecosystems; (2) to identify microorganisms and biogeochemical pathways associated with CH 4 production; and (3) to develop a mechanistic model including passive and active transport of CH 4 from the soil-tree-atmosphere continuum. Addressing these challenges will help to constrain the magnitudes and patterns of CH 4 emissions, and allow for the integration of pathways and mechanisms of CH 4 production and emissions into process-based models. These advances will facilitate the upscaling of stem CH 4 emissions to the ecosystem level and quantify the role of stem CH 4 emissions for the local to global CH 4 budget., (© 2018 No claim to original US government works New Phytologist © 2018 New Phytologist Trust.)

UNLABELLED: Wetlands cover a small portion of the world, but have disproportionate influence on global carbon (C) sequestration, carbon dioxide and methane emissions, and aquatic C fluxes. However, the underlying biogeochemical processes that affect wetland C pools and fluxes are complex and dynamic, making measurements of wetland C challenging. Over decades of research, many observational, experimental, and analytical approaches have been developed to understand and quantify pools and fluxes of wetland C. Sampling approaches range in their representation of wetland C from short to long timeframes and local to landscape spatial scales. This review summarizes common and cutting-edge methodological approaches for quantifying wetland C pools and fluxes. We first define each of the major C pools and fluxes and provide rationale for their importance to wetland C dynamics. For each approach, we clarify what component of wetland C is measured and its spatial and temporal representativeness and constraints. We describe practical considerations for each approach, such as where and when an approach is typically used, who can conduct the measurements (expertise, training requirements), and how approaches are conducted, including considerations on equipment complexity and costs. Finally, we review key covariates and ancillary measurements that enhance the interpretation of findings and facilitate model development. The protocols that we describe to measure soil, water, vegetation, and gases are also relevant for related disciplines such as ecology. Improved quality and consistency of data collection and reporting across studies will help reduce global uncertainties and develop management strategies to use wetlands as nature-based climate solutions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13157-023-01722-2.

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil-to-atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS ), is one of the largest carbon fluxes in the Earth system. An increasing number of high-frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open-source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long-term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS , the database design accommodates other soil-atmosphere measurements (e.g. ecosystem respiration, chamber-measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.

Methane dynamics within salt marshes are complex because vegetation types, temperature, oscillating water levels, and changes in salinity and redox conditions influence CH4 production, consumption, oxidation, and emissions. These non‐linear and complex interactions among variables affect the traditionally expected functional relationships and present challenges for interpreting and developing process‐based models. We employed empirical dynamic modeling (EDM) and convergent cross mapping (CCM) as a novel approach for characterizing seasonal/multiday and diurnal CH4 dynamics by inferring causal variables, lags, and interconnections among multiple biophysical variables within a temperate salt marsh using 5 years of eddy covariance data. EDM/CCM is a nonparametric approach capable of quantifying the coupling between variables while determining time scales where variable interactions are the most relevant. We found that gross primary productivity, tidal creek dissolved oxygen, and temperature were important for seasonal/multiday dynamics (rho = 0.73–0.80), while water level was most important for diurnal dynamics during both the growing and dormancy phenoperiods (rho = 0.72 and 0.56, respectively). Lags for the top‐ranked variables (i.e., gross primary productivity, dissolved oxygen, temperature, water level) occurred between 1 and 5 weeks at the seasonal scale and 1–24 hr at the diurnal scale. The EDM had high prediction capabilities for intra‐/inter‐seasonal patterns and annual CH4 sums but had limitations in representing large, infrequent fluxes. Results highlight the importance of non‐linearity, drivers, lag times, and interconnections among multiple biophysical variables that regulate CH4 fluxes in tidal wetlands. This research introduces a novel approach to examining CH4 fluxes, which will aid in evaluating current paradigms in wetlands and other ecosystems. Plain Language Summary: The movement of methane gas in salt marshes is complex and influenced by various factors such as plant types, temperature, water level, and changes in water salinity and oxygen levels. These factors interact in complex ways, making predicting the outcome of methane production and movement difficult. We applied a new method of studying methane dynamics using Empirical Dynamic Modeling and Convergent Cross Mapping. After analyzing 5 years of ecosystem‐scale measurements of methane fluxes, we show that the amount of oxygen in the water, the temperature, and the amount of light received by plants are crucial for understanding regulating methane fluxes within days and across seasons. The interconnections among these variables are complex, and methane fluxes may have delayed responses (i.e., lag times), highlighting the importance of these interactions. This research improves our comprehension of how environmental factors interact to affect methane fluxes in wetlands. Key Points: Methane dynamics in salt marshes are complex and influenced by multiple variablesEmpirical dynamic modeling and convergent cross mapping are novel approaches to characterizing CH4 dynamicsResults highlight drivers, non‐linearities, lag times, and interconnections among multiple biophysical variables for CH4 dynamics [ABSTRACT FROM AUTHOR]

Application of the best available science to improve quantification of greenhouse gas (GHG) emissions at regional and national scales is key to climate action. Here, we present a two‐decade (2000–2019) GHG (CO2, CH4, and N2O) budget for Mexico derived from multiple products. Data from the National GHG Inventory, global observations, and the scientific literature were compared to identify knowledge gaps on GHG flux dynamics and discrepancies among estimates. Total mean annual GHG emissions were estimated at 695–910 TgCO2‐eq year−1 over these two decades, with 70% of the emissions attributable to CO2, 23% to CH4, and 5% to N2O (2% to other gases). When divided by sectors, we found agreement across emission estimates from various sources for fossil fuels, cattle, agriculture, and waste for all GHGs. However, considerable discrepancies were identified in the fluxes from terrestrial ecosystems. The disagreement was particularly large for the land CO2 sink, where net biome production estimations from the national inventory were double those from any other observational product. Extensive knowledge gaps exist, mainly related to aquatic systems (e.g., outgassing in rivers) and the lateral fluxes (e.g., wood trade). In addition, limited information is available on CH4 emissions from wetlands and soil CH4 consumption. We expect these results to guide future research to reduce estimation uncertainties and fill the information gaps across Mexico. Plain Language Summary: Mexico represents the 13th global emitter of greenhouse gases (GHGs) and the second among Latin American countries, releasing roughly 485 million tons of CO2, six million tons of CH4 (equivalent to 160 million tons of CO2), and 0.1 million tons of N2O (equivalent to 35 million tons of CO2). However, large uncertainties prevail in the estimation of several components of each flux; thus, the application of the best available science to account for and improve these estimations is essential for sound mitigation policies. Here, we used multiple available products (national inventories, satellites, flux towers, dynamic global vegetation models, inversion models, and other data sources) to advance our understanding of the GHG budget of Mexico over the last 20 years. We found that fluxes from fossil fuel combustion (including energy production, transportation, industry, etc.), agriculture, livestock, and waste management agree remarkably well across products. In contrast, we documented large differences among products for land‐based fluxes (e.g., CO2 capture) and scant available information on aquatic ecosystems (e.g., CH4 emission from wetlands) and on lateral fluxes (e.g., emissions from trade). We expect these results to help in guiding future measuring efforts and policies to mitigate GHG emissions from Mexico. Key Points: A greenhouse gas (GHG) budget for Mexico was calculated based on multiple products. We estimated fluxes for CO2, CH4, and N2O over the 2000–2019 periodTotal GHG emissions were 695 TgCO2‐eq year−1 in the national inventory and as much as a mean 910 TgCO2‐eq year−1 across productsGHG fluxes agreed well across products for emissions, but large discrepancies exist for the land CO2 and CH4 sinks [ABSTRACT FROM AUTHOR]

Copyright of Global Change Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Quantifying the role of soils in nature-based solutions require accurate estimates of soil greenhouse gas (GHG) fluxes. Technological advances allow to simultaneously measure multiple GHGs and now is possible to provide complete GHG budgets from soils (i.e., CO2, CH4 and N2O fluxes). We propose that there is a conflict between the convenience of simultaneously measuring multiple soil GHG fluxes at fixed time intervals (e.g., once, or twice per month) and the intrinsic temporal variability and patterns of different GHG fluxes. Information derived from fixed time intervals -as is commonly done during manual field campaigns- had limitations to reproduce statistical properties, temporal dependence, annual budgets, and associated uncertainty, when compared with information derived from continuous measurements (i.e., automated hourly measurements) for all soil GHG fluxes. We present a novel approach (i.e., temporal univariate Latin Hypercube sampling) that can be applied to optimize monitoring efforts of GHG fluxes across time. We suggest that multiple GHG fluxes should not be simultaneously measured at few fixed time intervals (especially once a month), but an optimized sampling approach can be used to reduce bias and uncertainty. These results have implications for assessing GHG fluxes from soils and consequently reduce uncertainty on the role of soils in nature-based solutions. [ABSTRACT FROM AUTHOR]

Tidal wetlands are comprised of complex interdependent pathways where measurements of carbon exchange are often scale dependent. Common data collection methods (i.e., chambers and eddy covariance) are inherently constrained to different spatial and temporal scales which could generate biased information for applications of carbon accounting, identifying functional relationships and predicting future responses to climate change. Consequently, it is needed to systematically evaluate measurements derived from multiple approaches to identify differences and how techniques complement each other to reconcile interpretations. To accomplish this, we tested ecosystem‐scale eddy covariance with plot‐scale chamber measurements within a temperate salt marsh. We found good agreement (R2 = 0.71–0.95) when comparing measurements of CH4 emissions and CO2 exchange but this agreement was dependent upon canopy phenology with discrepancies mainly arising during senescence and dormancy phenophases. The environmental drivers for CH4 and CO2 fluxes were mostly preserved across different measurement techniques, but the number of drivers increases while their individual strength decreases at the ecosystem scale. Empirical upscaling models parameterized with chamber measurements overestimated annual net ecosystem exchange (NEE; 108%) and gross primary production (GPP; 12%) while underestimating ecosystem respiration (Reco; 14%) and CH4 emissions (69%) compared to eddy covariance measurements. Our results suggest that the environmental complexity of CH4 and CO2 fluxes in salt marshes may be underestimated by chamber‐based measurements, and highlights how different techniques are complementary while considering limitations at each level of measurement. Plain Language Summary: Tidal wetlands are important landscape features which play a significant role in regional carbon cycling between land, ocean and the atmosphere. These ecosystems are very productive, with high rates of photosynthesis during the growing season, but they also emit methane and carbon dioxide which can offset carbon gains. Therefore, it is important to accurately measure and understand what factors regulate carbon cycling processes to better characterize how these systems function, calculate carbon budgets and help predict possible reposes to climate change. We compare several common measurement techniques including chamber and eddy covariance which incorporate information across different scales to evaluate the level of agreement and how these techniques can be combined to increase our understanding of ecosystem functionality. We found that techniques agree well when comparing time‐matched measurement windows but different plant development stages across the ecosystem likely impacted agreement during autumn and early winter. We found that primary factors regulating fluxes were similar across techniques but when considering data collected over more hours of the day with eddy covariance, additional factors were identified indicating measurements from chambers which are limited in both coverage across space and time may present an oversimplified view within tidal wetlands. Key Points: Plot‐level and eddy covariance measurements had good overall agreement, but the strength of agreement was dependent upon plant phenologyThe relevance and influence of environmental drivers varied for all fluxes across different techniquesModels parameterized with plot‐level data overestimated ecosystem‐scale net ecosystem exchange but underestimated CO2 and CH4 emissions [ABSTRACT FROM AUTHOR]

Coastal salt marshes store large amounts of carbon but the magnitude and patterns of greenhouse gas (GHG; i.e., carbon dioxide (CO2) and methane (CH4)) fluxes are unclear. Information about GHG fluxes from these ecosystems comes from studies of sediments or at the ecosystem‐scale (eddy covariance) but fluxes from tidal creeks are unknown. We measured GHG concentrations in water, water quality, meteorological parameters, sediment CO2 efflux, ecosystem‐scale GHG fluxes, and plant phenology; all at half‐hour intervals over 1 year. Manual creek GHG flux measurements were used to calculate gas transfer velocity (k) and parameterize a model of water‐to‐atmosphere GHG fluxes. The creek was a source of GHGs to the atmosphere where tidal patterns controlled diel variability. Dissolved oxygen and wind speed were negatively correlated with creek CH4 efflux. Despite lacking a seasonal pattern, creek CO2 efflux was correlated with drivers such as turbidity across phenological phases. Overall, nighttime creek CO2 efflux (3.6 ± 0.63 μmol/m2/s) was at least 2 times higher than nighttime marsh sediment CO2 efflux (1.5 ± 1.23 μmol/m2/s). Creek CH4 efflux (17.5 ± 6.9 nmol/m2/s) was 4 times lower than ecosystem‐scale CH4 fluxes (68.1 ± 52.3 nmol/m2/s) across the year. These results suggest that tidal creeks are potential hotspots for CO2 emissions and could contribute to lateral transport of CH4 to the coastal ocean due to supersaturation of CH4 (>6,000 μmol/mol) in water. This study provides insights for modeling GHG efflux from tidal creeks and suggests that changes in tide stage overshadow water temperature in determining magnitudes of fluxes. Key Points: A tidal creek was a hotspot for CO2 efflux compared to the surrounding wetlandChanges in tide stage, not water temperature variability, regulated diel creek CO2 and CH4 effluxThe relative influence of nontidal drivers of creek CO2 and CH4 efflux varied by plant phenological phases [ABSTRACT FROM AUTHOR]

Forest soils are an important component of CO2 and CH4 fluxes at the global scale, but the magnitude of these fluxes varies greatly in space and time within a landscape. Understanding the spatial and temporal distributions of these fluxes across complex landscapes remains a major challenge for researchers and land managers alike. We investigated the spatiotemporal variability of soil-atmosphere CO2 and CH4 fluxes and the relationships of these fluxes to chemical and physical soil properties distributed across a topographically-heterogeneous landscape. Soil CO2 and CH4 fluxes were measured along with soil temperature, moisture, bulk density, texture, carbon, sorption capacity, and dissolved organic matter quality over 2 years along hillslope transects spanning valley bottom, transition zone, and upland landscape positions in a temperate forest watershed. Transition zone soil CO2 efflux was 54-160% higher than low-lying valley bottoms, and 15-54% higher than uplands. Net seasonal CH4 uptake was 58-150% higher in transition zone soils than in uplands, while valley bottoms were occasionally large net sources (up to 19 nmol CH4 m−2 s−1). Soil CO2 efflux and net CH4 uptake were both positively associated with seasonal temperature, and were highest in soils with relatively high carbon and clay content, and relatively low bulk density, moisture, and sorption capacity. We concluded that: (1) transition zone soils act as landscape hotspots for net CH4 uptake in addition to CO2 efflux, and (2) that this spatial distribution is more consistent across seasons for net CH4 uptake than for CO2 efflux. [ABSTRACT FROM AUTHOR]

Incorporation of silica-rich rice husk residue into flooded paddy soil decreases arsenic uptake by rice. However, the impact of this practice on soil greenhouse gas (GHG) emissions and elemental cycling is unresolved particularly as amended soils experience recurrent flooding and drying cycles. We evaluated the impact of pre-incubated silica-rich rice residue incorporation to soils on pore water chemistry and soil GHG fluxes (i.e., CO 2 , CH 4 , N 2 O) over a flooding and drying cycle typical of flooded rice cultivation. Soils pre-incubated with rice husk had 4-fold higher pore water Si than control and 2-fold higher than soils pre-incubated with rice straw, whereas the pore water As and Fe concentrations in soils amended with pre-incubated straw and husk were unexpectedly similar (maximum ~ 0.85 μM and ~ 450 μM levels, respectively). Pre-incubation of residues did not affect Si but did affect the pore water levels of As and Fe compared to previous studies using fresh residues where straw amended soils had higher As and Fe in pore water. The global warming potential (GWP) of soil GHG emissions decreased in the order straw (612 ± 76 g CO 2 -eq m − 2 ) > husk (367 ± 42 g CO 2 -eq m − 2 ) > ashed husk = ashed straw (251 ± 26 and 278 ± 28 g CO 2 -eq m − 2 ) > control (186 ± 23 g CO 2 -eq m − 2 ). The GWP increase due to pre-incubated straw amendment was due to: a) larger N 2 O fluxes during re-flooding; b) smaller contributions from larger CH 4 fluxes during flooded periods; and c) higher CH 4 and CO 2 fluxes at the onset of drainage. In contrast, the GWP of the husk amendment was dominated by CO 2 and CH 4 emissions during flooded and drainage periods, while ashed amendments increased CO 2 emissions particularly during drainage. This experiment shows that ashed residues and husk addition minimizes GWP of flooded soils and enhances pore water Si compared to straw addition even after pre-incubation. [ABSTRACT FROM AUTHOR]

Quantifying the biophysical impacts of management on river and stream ecosystems is an important issue that requires understanding of ecological, hydrological and geomorphological processes. We conducted a year-long ecogeomorphological experiment to determine sedimentation and carbon cycling differences between run-of-river (ROR) dams in a 200 year old impounded floodplain and a floodplain that was formerly impounded > 65 years ago. Our study shows that ROR dams do not necessarily enhance floodplain sedimentation or carbon storage, but promote brief periods of sediment CH 4 flux (up to 2.91 nmol CH 4 m − 2 s − 1 ) to the atmosphere. Removal of a ROR dam may result in channel widening, and removal by lateral transport (i.e., erosion) of nearly 14 MgC per floodplain. We did not find significant differences in mean sediment CO 2 fluxes or temperature sensitivity (Q 10 = 2.1 ± 0.4) of CO 2 efflux among floodplains. All floodplains were likely an annual net source of sediment CO 2 flux (annual mean of 2.12 ± 0.974 μmol CO 2 m − 2 s − 1 ) to the atmosphere, and a sink for atmospheric CH 4 (annual mean of − 0.221 ± 0.163 nmol CH 4 m − 2 s − 1 ). We provide a conceptual model on the management consequences on ROR dam structures for floodplain sedimentation/erosion, and sediment carbon cycling. [ABSTRACT FROM AUTHOR]

Highlights • Soil flux predictions closely matched observations across seasons. • We used a machine learning approach to upscale soil fluxes and estimate uncertainty. • Temperature was positively related to CO 2 efflux and CH 4 uptake. • CH 4 fluxes had bi-directional responses to seasonal precipitation patterns. Abstract Upscaling soil-atmosphere greenhouse gas (GHG) fluxes across complex landscapes is a major challenge for environmental scientists and land managers. This study employs a quantile-based digital soil mapping approach for estimating the spatially continuous distributions (2 m spatial resolution) and uncertainties of seasonal mean mid-day soil CO 2 and CH 4 fluxes. This framework was parameterized using manual chamber measurements collected over two years within a temperate forested headwater watershed. Model accuracy was highest for early (r2 = 0.61) and late summer (r2 = 0.64) for CO 2 and CH 4 fluxes. Model uncertainty was generally lower for predicted CO 2 fluxes than CH 4 fluxes. Within the study area, predicted seasonal mean CO 2 fluxes ranged from 0.17 to 0.58 μmol m−2 s−1 in winter, and 1.4 to 5.1 μmol m−2 s−1 in early summer. Predicted CH 4 fluxes across the study area ranged from −0.52 to 0.02 nmol m−2 s−1 in winter, and −2.1 to 0.61 nmol m−2 s−1 in early and late summer. The models estimated a per hectare net GHG potential ranging from 0.44 to 4.7 kg CO 2 eq. hr−1 in winter and early summer, with an estimated 0.4 to 1.5% of emissions offset by CH 4 uptake. Flux predictions fell within ranges reported in other temperate forest systems. Soil CO 2 fluxes were more sensitive to seasonal temperature changes than CH 4 fluxes, with significant temperature relationships for soil CO 2 emissions and CH 4 uptake in pixels with high slope angles. In contrast, soil CH 4 fluxes from flat low-lying areas near the stream network within the watershed were significantly correlated to seasonal precipitation. This study identified key challenges for modeling high spatial resolution soil CO 2 and CH 4 fluxes, and suggests a larger spatial heterogeneity and complexity of underlying processes that govern CH 4 fluxes. [ABSTRACT FROM AUTHOR]