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McNicol, Gavin

Publications and source records attributed to McNicol, Gavin.

Critical needs to close monitoring gaps in pan-tropical wetland CH 4 emissions

Global wetlands are the largest and most uncertain natural source of atmospheric methane (CH 4 ). The FLUXNET-CH 4 synthesis initiative has established a global network of flux tower infrastructure, offering valuable data products and fostering a dedicated community for the measurement and analysis of methane flux data. Existing studies using the FLUXNET-CH 4 Community Product v1.0 have provided invaluable insights into the drivers of ecosystem-to-regional spatial patterns and daily-to-decadal temporal dynamics in temperate, boreal, and Arctic climate regions. However, as the wetland CH 4 monitoring network grows, there is a critical knowledge gap about where new monitoring infrastructure ought to be located to improve understanding of the global wetland CH 4 budget. Here we address this gap with a spatial representativeness analysis at existing and hypothetical observation sites, using 16 process-based wetland biogeochemistry models and machine learning. We find that, in addition to eddy covariance monitoring sites, existing chamber sites are important complements, especially over high latitudes and the tropics. Furthermore, expanding the current monitoring network for wetland CH 4 emissions should prioritize, first, tropical and second, sub-tropical semi-arid wetland regions. Considering those new hypothetical wetland sites from tropical and semi-arid climate zones could significantly improve global estimates of wetland CH 4 emissions and reduce bias by 79% (from 76 to 16 TgCH 4 y -1 ), compared with using solely existing monitoring networks. Our study thus demonstrates an approach for long-term strategic expansion of flux observations.

54 ENVIRONMENTAL SCIENCES↗

Methane fluxes in tidal marshes of the conterminous United States

Abstract Methane (CH 4 ) is a potent greenhouse gas (GHG) with atmospheric concentrations that have nearly tripled since pre‐industrial times. Wetlands account for a large share of global CH 4 emissions, yet the magnitude and factors controlling CH 4 fluxes in tidal wetlands remain uncertain. We synthesized CH 4 flux data from 100 chamber and 9 eddy covariance (EC) sites across tidal marshes in the conterminous United States to assess controlling factors and improve predictions of CH 4 emissions. This effort included creating an open‐source database of chamber‐based GHG fluxes ( https://doi.org/10.25573/serc.14227085 ). Annual fluxes across chamber and EC sites averaged 26 ± 53 g CH 4 m −2 year −1 , with a median of 3.9 g CH 4 m −2 year −1 , and only 25% of sites exceeding 18 g CH 4 m −2 year −1 . The highest fluxes were observed at fresh‐oligohaline sites with daily maximum temperature normals (MATmax) above 25.6°C. These were followed by frequently inundated low and mid‐fresh‐oligohaline marshes with MATmax ≤25.6°C, and mesohaline sites with MATmax >19°C. Quantile regressions of paired chamber CH 4 flux and porewater biogeochemistry revealed that the 90th percentile of fluxes fell below 5 ± 3 nmol m −2 s −1 at sulfate concentrations >4.7 ± 0.6 mM, porewater salinity >21 ± 2 psu, or surface water salinity >15 ± 3 psu. Across sites, salinity was the dominant predictor of annual CH 4 fluxes, while within sites, temperature, gross primary productivity (GPP), and tidal height controlled variability at diel and seasonal scales. At the diel scale, GPP preceded temperature in importance for predicting CH 4 flux changes, while the opposite was observed at the seasonal scale. Water levels influenced the timing and pathway of diel CH 4 fluxes, with pulsed releases of stored CH 4 at low to rising tide. This study provides data and methods to improve tidal marsh CH 4 emission estimates, support blue carbon assessments, and refine national and global GHG inventories.

54 ENVIRONMENTAL SCIENCES↗

Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems

Climate warming is expected to increase global methane (CH 4 ) emissions from wetland ecosystems. Although in situ eddy covariance (EC) measurements at ecosystem scales can potentially detect CH 4 flux changes, most EC systems have only a few years of data collected, so temporal trends in CH 4 remain uncertain. Here, we use established drivers to hindcast changes in CH 4 fluxes (FCH 4 ) since the early 1980s. We trained a machine learning (ML) model on CH 4 flux measurements from 22 [methane-producing sites] in wetland, upland, and lake sites of the FLUXNET-CH 4 database with at least two full years of measurements across temperate and boreal biomes. The gradient boosting decision tree ML model then hindcasted daily FCH 4 over 1981-2018 using meteorological reanalysis data. We found that, mainly driven by rising temperature, half of the sites (n = 11) showed significant increases in annual, seasonal, and extreme FCH 4 , with increases in FCH 4 of ca. 10% or higher found in the fall from 1981–1989 to 2010–2018. The annual trends were driven by increases during summer and fall, particularly at high-CH 4 -emitting fen sites dominated by aerenchymatous plants. We also found that the distribution of days of extremely high FCH 4 (defined according to the 95th percentile of the daily FCH 4 values over a reference period) have become more frequent during the last four decades and currently account for 10–40% of the total seasonal fluxes. The share of extreme FCH 4 days in the total seasonal fluxes was greatest in winter for boreal/taiga sites and in spring for temperate sites, which highlights the increasing importance of the non-growing seasons in annual budgets. Our results shed light on the effects of climate warming on wetlands, which appears to be extending the CH 4 emission seasons and boosting extreme emissions.

54 ENVIRONMENTAL SCIENCES↗

CROCUS Urban Fluxes of CO₂, H₂O, and Turbulence at University of Illinois Chicago

As of May 12, 2026 this dataset is currently being versioned to include data up to April 2026. Once the versioning process is complete, new data files will be available for access. The dataset metadata will also be updated to reflect the data availability of the new data being versioned. This dataset was collected at the UIC Plant Research Laboratory in Chicago, Illinois, as part of the Community Research on Climate and Urban Science (CROCUS) Urban Integrated Field Laboratory (UIFL) project, led by Argonne National Laboratory. The site provides continuous atmospheric flux measurements, focusing on CO₂, H₂O, and heat and momentum transport in an urban setting. The data is processed at 30 minutes interval using the Eddy Covariance method and includes quality control and diagnostic data generated by EddyPro software. The data is stored in the netCDF files following CF conventions. The UIC Plant Research Laboratory is located near major highways and urban infrastructure, including buildings and parking areas. The surrounding landscape consists of a mix of turf, plants, trees, and impervious surfaces such as concrete and asphalt, making it ideal for studying urban at for studies on urban sustainability, air quality, and the effects of urbanization on atmospheric processes on urban climate dynamics, air quality, and surface-atmosphere exchanges within the city of Chicago. This dataset is funded by the U.S. Department of Energy’s Office of Science, Biological and Environmental Research (BER) program.

54 ENVIRONMENTAL SCIENCES↗

CROCUS High-Frequency Measurements of CO₂, H₂O, Wind, and Temperature at University of Illinois Chicago

As of April 9, 2026: this dataset is currently being versioned to include data up to March 31, 2026. Once the versioning process is complete, new data files will be available for access. The dataset metadata will also be updated to reflect the data availability of the new data being versioned. Raw atmospheric measurements collected at the University of Illinois Chicago (UIC) as part of the Community Research on Climate and Urban Science (CROCUS) project. The data includes high-frequency measurements of carbon dioxide (CO₂) concentration, water vapor (H₂O) concentration, wind speed (U, V, W components), temperature, and atmospheric pressure. These raw data are recorded by the LI-7500DS Open Path CO₂/H₂O Analyzer and a sonic anemometer at a 10 Hz acquisition frequency, providing the necessary inputs for calculating fluxes of CO₂, H₂O, heat, and momentum. In addition to gas concentration measurements, the dataset includes diagnostic information from the instruments, including absorptance, sample and reference signals, and diagnostic values. The data were collected to study urban atmospheric conditions and contribute to flux calculations for urban climate research. These measurements form the basis for calculating 30-minute average fluxes of key atmospheric variables using the eddy covariance method. This dataset provides critical raw input data for researchers interested in atmospheric fluxes, urban air quality, and the interaction between the urban environment and atmospheric processes. The data is part of the U.S. Department of Energy’s Biological and Environmental Research (BER) program, under the CROCUS Urban Integrated Field Laboratory (UIFL) project.

54 ENVIRONMENTAL SCIENCES↗

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET-CH 4 Sites Using Wavelet Analyses

Process-based land surface models are important tools for estimating global wetland methane (CH 4 ) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH 4 fluxes (FCH 4 ) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15 days); (b) most of the models can capture the CH 4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH 4 production). Our evaluation suggests the need to accurately replicate FCH 4 variability, especially at short time scales, in future wetland CH 4 model developments.

58 GEOSCIENCES↗

Upscaling Wetland Methane Emissions From the FLUXNET–CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison

Wetlands are responsible for 20%–31% of global methane (CH 4 ) emissions and account for a large source of uncertainty in the global CH 4 budget. Data-driven upscaling of CH 4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH 4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH 4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH 4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ~0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH 4 emissions of 146 ± 43 TgCH 4 y –1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH 4 y –1 ) and overlaps with top-down atmospheric inversion models (155–200 TgCH 4 y –1 ). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH 4 fluxes has the potential to produce realistic extra-tropical wetland CH 4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions.

54 ENVIRONMENTAL SCIENCES↗

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions

Abstract Wetlands are the largest natural source of methane (CH 4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH 4 , but interpreting its spatiotemporal variations is challenging due to the co‐occurrence of CH 4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data‐model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data‐constrained model—iPEACE—reasonably reproduced CH 4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH 4 production appeared to be the most important process, followed by oxidation in explaining inter‐site variations in CH 4 emissions. Based on a sensitivity analysis, CH 4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant‐mediated transport appeared to be the major pathway for CH 4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH 4 production and CH 4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH 4 production, plant‐mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH 4 emissions across biomes. These processes and associated parameters for CH 4 emissions among and within the wetlands provide useful insights for interpreting observed net CH 4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH 4 fluxes.

Ueyama, Masahito↗

Causality guided machine learning model on wetland CH 4 emissions across global wetlands

Wetland CH 4 emissions are among the most uncertain components of the global CH 4 budget. The complex nature of wetland CH 4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH 4 emissions. In this study, we used the flux measurements of CH 4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH 4 emissions at sub-seasonal scale. We found that soil temperature is the dominant factor for CH 4 emissions in all studied wetland types. Ecosystem respiration (CO 2 ) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH 4 emissions differed by up to a factor of 4 under a +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH 4 emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH 4 emissions within earth system land models.

54 ENVIRONMENTAL SCIENCES↗

Restoring wetlands on intensive agricultural lands modifies nitrogen cycling microbial communities and reduces N 2 O production potential

The concentration of nitrous oxide (N 2 O), an ozone-depleting greenhouse gas, is rapidly increasing in the atmosphere. Most atmospheric N 2 O originates in terrestrial ecosystems, of which the majority can be attributed to microbial cycling of nitrogen in agricultural soils. Here, in this study, we demonstrate how the abundance of nitrogen cycling genes vary across intensively managed agricultural fields and adjacent restored wetlands in the Sacramento-San Joaquin Delta in California, USA. We found that the abundances of nirS and nirK genes were highest at the intensively managed organic-rich cornfield and significantly outnumber any other gene abundances, suggesting very high N 2 O production potential. The quantity of nitrogen transforming genes, particularly those responsible for denitrification, nitrification and DNRA, were highest in the agricultural sites, whereas nitrogen fixation and ANAMMOX was strongly associated with the wetland sites. Although the abundance of nosZ genes was also high at the agricultural sites, the ratio of nosZ genes to nir genes was significantly higher in wetland sites indicating that these sites could act as a sink of N 2 O. These findings suggest that wetland restoration could be a promising natural climate solution not only for carbon sequestration but also for reduced N 2 O emissions.

59 BASIC BIOLOGICAL SCIENCES↗

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales

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. In this work 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.

59 BASIC BIOLOGICAL SCIENCES↗

Climate-Mediated Changes to Linked Terrestrial and Marine Ecosystems across the Northeast Pacific Coastal Temperate Rainforest Margin

Coastal margins are important areas of materials flux that link terrestrial and marine ecosystems. Consequently, climate-mediated changes to coastal terrestrial ecosystems and hydrologic regimes have high potential to influence nearshore ocean chemistry and food web dynamics. Research from tightly coupled, high-flux coastal ecosystems can advance understanding of terrestrial–marine links and climate sensitivities more generally. In the present article, we use the northeast Pacific coastal temperate rainforest as a model system to evaluate such links. We focus on key above- and belowground production and hydrological transport processes that control the land-to-ocean flow of materials and their influence on nearshore marine ecosystems. We evaluate how these connections may be altered by global climate change and we identify knowledge gaps in our understanding of the source, transport, and fate of terrestrial materials along this coastal margin. Finally, we propose five priority research themes in this region that are relevant for understanding coastal ecosystem links more broadly.

temperate rainforest, coastal margin, climate chan↗

FLUXNET-CH4 Synthesis Activity: Objectives, Observations, and Future Directions

This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from −0.2 ± 0.02 g C m(exp -2) yr(exp -1) for an upland forest site to 114.9 ± 13.4 g C m(exp -2) yr(exp -1) for an estuarine freshwater marsh, with fluxes exceeding 40 g C m(exp -2) yr(exp -1) at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH4 estimates due to gap-filling and random errors were on average ±1.6 g C m(exp -2) yr(exp -1) at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH4 flux database, the controls on ecosystem CH4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH4 emissions.

Knox, Sara H.↗

Where old meets new: An ecosystem study of methanogenesis in a reflooded agricultural peatland

Reflooding formerly drained peatlands has been proposed as a means to reduce losses of organic matter and sequester soil carbon for climate change mitigation, but a renewal of high methane emissions has been reported for these ecosystems, offsetting mitigation potential. Our ability to interpret observed methane fluxes in reflooded peatlands and make predictions about future flux trends is limited due to a lack of detailed studies of methanogenic processes. In this study we investigate methanogenesis in a reflooded agricultural peatland in the Sacramento Delta, California. Furthermore, we use the stable-and radio-carbon isotopic signatures of wetland sediment methane, ecosystem-scale eddy covariance flux observations, and laboratory incubation experiments, to identify which carbon sources and methanogenic production pathways fuel methanogenesis and how these processes are affected by vegetation and seasonality. We found that the old peat contribution to annual methane emissions was large (~30%) compared to intact wetlands, indicating a biogeochemical legacy of drainage. However, fresh carbon and the acetoclastic pathway still accounted for the majority of methanogenesis throughout the year. Although temperature sensitivities for bulk peat methanogenesis were similar between open-water (Q 10 = 2.1) and vegetated (Q 10 = 2.3) soils, methane production from both fresh and old carbon sources showed pronounced seasonality in vegetated zones. We conclude that high methane emissions in restored wetlands constitute a biogeochemical trade-off with contemporary carbon uptake, given that methane efflux is fueled primarily by fresh carbon inputs.

54 ENVIRONMENTAL SCIENCES↗