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While wetlands are the largest natural source of methane (CH4) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi‐site synthesis of how predictors of CH4 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 CH4. 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 CH4 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 CH4 emissions.

Methane flux (FCH4) measurements using the eddy covariance technique have increased over the past decade. FCH4 measurements commonly include data gaps, as is the case with CO2 and energy fluxes. However, gap‐filling FCH4 data are more challenging than other fluxes due to its unique characteristics including multidriver dependency, variabilities across multiple timescales, nonstationarity, spatial heterogeneity of flux footprints, and lagged influence of biophysical drivers. Some researchers have applied a marginal distribution sampling (MDS) algorithm, a standard gap‐filling method for other fluxes, to FCH4 datasets, and others have applied artificial neural networks (ANN) to resolve the challenging characteristics of FCH4. However, there is still no consensus regarding FCH4 gap‐filling methods due to limited comparative research. We are not aware of the applications of machine learning (ML) algorithms beyond ANN to FCH4 datasets. Here, we compare the performance of MDS and three ML algorithms (ANN, random forest [RF], and support vector machine [SVM]) using multiple combinations of ancillary variables. In addition, we applied principal component analysis (PCA) as an input to the algorithms to address multidriver dependency of FCH4 and reduce the internal complexity of the algorithmic structures. We applied this approach to five benchmark FCH4 datasets from both natural and managed systems located in temperate and tropical wetlands and rice paddies. Results indicate that PCA improved the performance of MDS compared to traditional inputs. ML algorithms performed better when using all available biophysical variables compared to using PCA‐derived inputs. Overall, RF was found to outperform other techniques for all sites. We found gap‐filling uncertainty is much larger than measurement uncertainty in accumulated CH4 budget. Therefore, the approach used for FCH4 gap filling can have important implications for characterizing annual ecosystem‐scale methane budgets, the accuracy of which is important for evaluating natural and managed systems and their interactions with global change processes.

Abstract. Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

Carbon dioxide (CO2) emissions to the atmosphere from running waters are estimated to be four times larger than the total carbon (C) flux to the oceans. However, these fluxes remain poorly constrained because of substantial temporal variability in dissolved CO2 concentrations. Using a global compilation of high frequency CO2 measurements, we demonstrate that nocturnal CO2 emissions are consistently larger, by an average of 27% (0.9 g C m -2 d -1 ), than those estimated from diurnal concentrations alone. Canopy shading is the principal control on observed diel (24 hr) variation, suggesting this nocturnal increase arises from daytime fixation of dissolved inorganic C by photosynthesis. Because contemporary global estimates of CO2 emissions to the atmosphere from running waters (0.65 -1.8 Pg C yr -1 ) rely primarily on discrete measurements of dissolved CO2 obtained during the day, they substantially underpredict the magnitude of this important flux. Accounting for night-time CO2 elevates global estimates of emissions from running waters to the atmosphere by 0.20-0.55 Pg C yr -1 .Carbon dioxide (CO2) emission from inland waters to the atmosphere is a major flux in the global carbon (C) cycle, and four-fold larger than the lateral C export to oceans 1 . Streams and rivers are hotspots for this flux, accounting for ~85% of inland water CO2 emissions despite covering <20% of the freshwater surface area 2 . Despite this importance, the magnitude of global CO2 emissions from streams and rivers remains highly uncertain with estimates revised upwards over the past decade from 0.6 to 3.48 Pg C yr -1 (3,4) . Changes to this estimate follow improvements in the spatial resolution for upscaling emissions 2,5 , as well as new studies from previously underrepresented areas such as the Congo 6 , Amazon 7 , and global mountains 8 . Further refinements have emerged from considering temporal variability in CO2 emission rates 9 . However, despite recent studies showing dramatic day-night changes in stream and river water CO2 concentrations 10-14 the significance of systematic sub-daily variation on overall CO2 emissions remains unexplored.Diurnal cycles in solar radiation impose a well-known periodicity on stream biogeochemical processes, creating diel (i.e., 24-hr period lengths) patterns for many solutes and gases, including nutrients, dissolved organic matter, and dissolved oxygen (O2) 15 . Indeed, diel variation in O2 arising from photosynthetic activity is the signal from which whole-system metabolic fluxes are estimated 16 . Photosynthetic production of O2 is stoichiometrically linked to the day-time assimilation of dissolved inorganic carbon (principally bicarbonate and dissolved CO2), lowering CO2 concentrations during the day. The resulting diel variation, with higher night-time CO2 concentrations when respiration reactions dominate, implies increased emissions at night. Despite the obvious connection between photosynthesis and CO2 consumption, the implications for total aquatic CO2 emissions has been neglected, most likely ...

Wetlands are important sources of methane (CH4) and sinks of carbon dioxide (CO2). However, little is known about CH4 and CO2 fluxes and dynamics of seasonally flooded tropical forests of South America in relation to local carbon (C) balances and atmospheric exchange. We measured net ecosystem fluxes of CH4 and CO2 in the Pantanal over 2014–2017 using tower‐based eddy covariance along with C measurements in soil, biomass and water. Our data indicate that seasonally flooded tropical forests are potentially large sinks for CO2 but strong sources of CH4, particularly during inundation when reducing conditions in soils increase CH4 production and limit CO2 release. During inundation when soils were anaerobic, the flooded forest emitted 0.11 ± 0.002 g CH4‐C m−2 d−1 and absorbed 1.6 ± 0.2 g CO2‐C m−2 d−1 (mean ± 95% confidence interval for the entire study period). Following the recession of floodwaters, soils rapidly became aerobic and CH4 emissions decreased significantly (0.002 ± 0.001 g CH4‐C m−2 d−1) but remained a net source, while the net CO2 flux flipped from being a net sink during anaerobic periods to acting as a source during aerobic periods. CH4 fluxes were 50 times higher in the wet season; DOC was a minor component in the net ecosystem carbon balance. Daily fluxes of CO2 and CH4 were similar in all years for each season, but annual net fluxes varied primarily in relation to flood duration. While the ecosystem was a net C sink on an annual basis (absorbing 218 g C m−2 (as CH4‐C + CO2‐C) in anaerobic phases and emitting 76 g C m−2in aerobic phases), high CH4 effluxes during the anaerobic flooded phase and modest CH4 effluxes during the aerobic phase indicate that seasonally flooded tropical forests can be a net source of radiative forcings on an annual basis, thus acting as an amplifying feedback on global warming.

All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. Variations in Stand Structure and Diversity along a Soil Fertility Gradient in a Brazilian Savanna (Cerrado) in Southern Mato Grosso Forest, Range & Wildland Soils B razilian savanna, locally known as cerrado, covers approximately 20 to 25% of the total land cover of Brazil and is the second largest vegetation type following Amazonian forest (Furley and Ratter, 1988). Cerrado is composed of distinctive physiognomies that vary as a function of height, cover, and/ or density of trees (Goodland, 1971; Eiten, 1972; Furley and Ratter, 1988). The factors that affect the physiognomy and distribution of cerrado remain a subject of debate; however, seasonal variation in rainfall, soil fertility and drainage, and fire are considered the most important (Eiten, 1972; Furley and Ratter, 1988; Lopes and Cox, 1977). In terms of soil properties, variations in soil texture, water holding capacity, and chemical properties, such as pH and Al 3+ concentration, have been found to be important variables affecting cerrado physiognomy and tree species distribution (Lopes and Cox, 1977; Furley and Ratter, 1988; de Souza et al., 2007; de Assis et al., 2011). Nutrient limitation has been implicated as a primary factor inhibiting the development of forests in tropical savanna, and across large-scale fertility gradients, an increase in soil fertility can lead to an increase in the production of woody vegetation, and the density and cover of trees (Goodland and Pollard, 1973; Lopes

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