Author: "Szutu, Daphne" - Searchworks@Jio Institute Digital Library Search Results

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1. Net fluxes of broadband shortwave and photosynthetically active radiation complement NDVI and near infrared reflectance of vegetation to explain gross photosynthesis variability across ecosystems and climate

Author: Mallick, Kanishka, Verfaillie, Joseph, Wang, Tianxin, Ortiz, Ariane Arias, Szutu, Daphne, Yi, Koong, Kang, Yanghui, Shortt, Robert, Hu, Tian, Sulis, Mauro, Szantoi, Zoltan, Boulet, Gilles, Fisher, Joshua B, and Baldocchi, Dennis
Subjects: Earth Sciences, Spectral reflectance, Broadband vegetation index, NIRv, Gross primary productivity, Photosynthetically active radiation, Ecosystem, Climate, Earth sciences, Geological & Geomatics Engineering, Geomatic Engineering, Physical Geography and Environmental Geoscience
Abstract: A significant challenge in global change research is understanding how vegetation interacts with the environment to influence ecosystem gross primary productivity (GPP) through carbon assimilation. One emerging objective is to consistently predict GPP fluctuations worldwide by establishing a robust scaling relationship between GPP measured at flux towers and satellite spectral reflectance data. However, a major hurdle in achieving this goal is the discrepancy in spatial resolution between early satellite measurements and eddy flux measurements. By using a large set of growing season data covering 100 site-years in North and Central America, we explored the potential of transforming incident and reflected shortwave (Rg) and photosynthetically active radiation (PAR) measurements into a broadband normalized difference vegetation index (NDVI) and near-infrared (NIR) reflectance of vegetation (NIRv) which simultaneously explains the GPP variability. We found that the broadband NDVI and NIRv derived from Rg and PAR measurements at the daily time scale were highly correlated with Planet Fusion, Landsat-8/9, and Sentinel-2 narrowband NDVI and NIRv across a wide range of climate and ecological gradients. The differences between satellite and broadband NDVI and NIRv were found to be significantly associated with soil background variations, phenological stages, water stress and signal saturation of broadband NIR reflectance at high biomass. The seasonal variability of broadband NDVI and NIRv remarkably captured the seasonality of vegetation phenology, evaporative fraction, GPP and rainfall in different ecosystems. Although saturation of GPP at high NDVI was evident, a linear relationship between broadband NIRv times incident PAR versus GPP indicated the effectiveness of NIRv-based approach to capture the hidden light use efficiency impacts on GPP. Our study concludes that inexpensive measurement of Rg and PAR components can provide reliable information on NDVI, NIRv, and GPP uninterruptedly. This enhances the sensing capability of flux tower sites without requiring additional spectrometer measurements. The proposed in-situ vegetation indices make a compelling case on using radiation signals for handshaking between ecosystem-scale measurements and remote sensing observables relevant to carbon uptake.
Published: 2024

2. Carbon-sink potential of continuous alfalfa agriculture lowered by short-term nitrous oxide emission events.

Author: Anthony, Tyler L, Szutu, Daphne J, Verfaillie, Joseph G, Baldocchi, Dennis D, and Silver, Whendee L
Abstract: Alfalfa is the most widely grown forage crop worldwide and is thought to be a significant carbon sink due to high productivity, extensive root systems, and nitrogen-fixation. However, these conditions may increase nitrous oxide (N2O) emissions thus lowering the climate change mitigation potential. We used a suite of long-term automated instrumentation and satellite imagery to quantify patterns and drivers of greenhouse gas fluxes in a continuous alfalfa agroecosystem in California. We show that this continuous alfalfa system was a large N2O source (624 ± 28 mg N2O m2 y-1), offsetting the ecosystem carbon (carbon dioxide (CO2) and methane (CH4)) sink by up to 14% annually. Short-term N2O emissions events (i.e., hot moments) accounted for ≤1% of measurements but up to 57% of annual emissions. Seasonal and daily trends in rainfall and irrigation were the primary drivers of hot moments of N2O emissions. Significant coherence between satellite-derived photosynthetic activity and N2O fluxes suggested plant activity was an important driver of background emissions. Combined data show annual N2O emissions can significantly lower the carbon-sink potential of continuous alfalfa agriculture.
Published: 2023

3. Detecting Hot Spots of Methane Flux Using Footprint‐Weighted Flux Maps

Author: Rey‐Sanchez, Camilo, Arias‐Ortiz, Ariane, Kasak, Kuno, Chu, Housen, Szutu, Daphne, Verfaillie, Joseph, and Baldocchi, Dennis
Subjects: Earth Sciences, Geochemistry, methane, hot spots, flux footprint, eddy covariance, wetlands, chambers, Geophysics
Abstract: In this study, we propose a new technique for mapping the spatial heterogeneity in gas exchange around flux towers using flux footprint modeling and focusing on detecting hot spots of methane (CH4) flux. In the first part of the study, we used a CH4 release experiment to evaluate three common flux footprint models: the Hsieh model (Hsieh et al., 2000), the Kljun model (Kljun et al., 2015), and the K & M model (Kormann and Meixner, 2001), finding that the K & M model was the most accurate under these conditions. In the second part of the study, we introduce the Footprint-Weighted Flux Map, a new technique to map spatial heterogeneity in fluxes. Using artificial CH4 release experiments, natural tracer approaches and flux chambers we mapped the spatial flux heterogeneity, and detected and validated a hot spot of CH4 flux in a oligohaline restored marsh. Through chamber measurements during the months of April and May, we found that fluxes at the hot spot were on average as high as 6589 ± 7889 nmol m-2 s-1 whereas background flux from the open water were on average 15.2 ± 7.5 nmol m-2 s-1. This study provides a novel tool to evaluate the spatial heterogeneity of fluxes around eddy-covariance towers and creates important insights for the interpretation of hot spots of CH4 flux, paving the way for future studies aiming to understand subsurface biogeochemical processes and the microbiological conditions that lead to the occurrence of hot spots and hot moments of CH4 flux.
Published: 2022

4. How advection affects the surface energy balance and its closure at an irrigated alfalfa field

Author: Wang, Tianxin, Alfieri, Joseph, Mallick, Kanishka, Arias-Ortiz, Ariane, Anderson, Martha, Fisher, Joshua B., Girotto, Manuela, Szutu, Daphne, Verfaillie, Joseph, and Baldocchi, Dennis
Published: 2024
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5. Restoring wetlands on intensive agricultural lands modifies nitrogen cycling microbial communities and reduces N2O production potential

Author: Kasak, Kuno, Espenberg, Mikk, Anthony, Tyler L, Tringe, Susannah G, Valach, Alex C, Hemes, Kyle S, Silver, Whendee L, Mander, Ülo, Kill, Keit, McNicol, Gavin, Szutu, Daphne, Verfaillie, Joseph, and Baldocchi, Dennis D
Subjects: Climate Change Impacts and Adaptation, Biological Sciences, Ecology, Environmental Sciences, Climate Action, Life on Land, Denitrification, Microbiota, Nitrogen, Nitrogen Cycle, Nitrous Oxide, Soil, Soil Microbiology, Wetlands, Functional genes, Land use change, Land management, Nitrogen fixation, Ammonia oxidation
Abstract: The concentration of nitrous oxide (N2O), an ozone-depleting greenhouse gas, is rapidly increasing in the atmosphere. Most atmospheric N2O originates in terrestrial ecosystems, of which the majority can be attributed to microbial cycling of nitrogen in agricultural soils. Here, 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 N2O 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 N2O. These findings suggest that wetland restoration could be a promising natural climate solution not only for carbon sequestration but also for reduced N2O emissions.
Published: 2021

6. Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Author: Irvin, Jeremy, Zhou, Sharon, McNicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-Chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-Moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Chen, Jiquan, Chu, Housen, Dalmagro, Higo J, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick YF, Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B, Noormets, Asko, Peichl, Matthias, Rey-Sanchez, A Camilo, Richardson, Andrew D, Runkle, Benjamin RK, Schäfer, Karina VR, Sonnentag, Oliver, Stuart-Haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C, Vargas, Rodrigo, Vourlitis, George L, Ward, Eric J, Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma Carmelita R, Billesbach, David P, Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J, Goodrich, Jordan P, Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H, Nemitz, Eiko, Oechel, Walter C, Oikawa, Patricia Y, Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A, Shortt, Robert, Sullivan, Ryan C, Szutu, Daphne J, Tuittila, Eeva-Stiina, Varlagin, Andrej, Verfaillie, Joeseph G, Wille, Christian, Windham-Myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B
Subjects: Earth Sciences, Agricultural, Veterinary and Food Sciences, Biological Sciences, Bioengineering, Networking and Information Technology R&D (NITRD), Machine Learning and Artificial Intelligence, Machine learning, time series, imputation, gap-filling, methane, flux, wetlands, Agricultural and Veterinary Sciences, Meteorology & Atmospheric Sciences, Agricultural, veterinary and food sciences, Biological sciences, Earth sciences
Abstract: 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).
Published: 2021

7. Productive wetlands restored for carbon sequestration quickly become net CO2 sinks with site-level factors driving uptake variability

Author: Valach, Alex C, Kasak, Kuno, Hemes, Kyle S, Anthony, Tyler L, Dronova, Iryna, Taddeo, Sophie, Silver, Whendee L, Szutu, Daphne, Verfaillie, Joseph, and Baldocchi, Dennis D
Subjects: Climate Change Impacts and Adaptation, Biological Sciences, Environmental Sciences, Life on Land, California, Carbon Dioxide, Carbon Sequestration, Climate Change, Ecosystem, Floods, Seasons, Wetlands, General Science & Technology
Abstract: Inundated wetlands can potentially sequester substantial amounts of soil carbon (C) over the long-term because of slow decomposition and high primary productivity, particularly in climates with long growing seasons. Restoring such wetlands may provide one of several effective negative emission technologies to remove atmospheric CO2 and mitigate climate change. However, there remains considerable uncertainty whether these heterogeneous ecotones are consistent net C sinks and to what degree restoration and management methods affect C sequestration. Since wetland C dynamics are largely driven by climate, it is difficult to draw comparisons across regions. With many restored wetlands having different functional outcomes, we need to better understand the importance of site-specific conditions and how they change over time. We report on 21 site-years of C fluxes using eddy covariance measurements from five restored fresh to brackish wetlands in a Mediterranean climate. The wetlands ranged from 3 to 23 years after restoration and showed that several factors related to restoration methods and site conditions altered the magnitude of C sequestration by affecting vegetation cover and structure. Vegetation established within two years of re-flooding but followed different trajectories depending on design aspects, such as bathymetry-determined water levels, planting methods, and soil nutrients. A minimum of 55% vegetation cover was needed to become a net C sink, which most wetlands achieved once vegetation was established. Established wetlands had a high C sequestration efficiency (i.e. the ratio of net to gross ecosystem productivity) comparable to upland ecosystems but varied between years undergoing boom-bust growth cycles and C uptake strength was susceptible to disturbance events. We highlight the large C sequestration potential of productive inundated marshes, aided by restoration design and management targeted to maximise vegetation extent and minimise disturbance. These findings have important implications for wetland restoration, policy, and management practitioners.
Published: 2021

8. FLUXNET-CH4: a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands

Author: Delwiche, Kyle B, Knox, Sara Helen, Malhotra, Avni, Fluet-Chouinard, Etienne, McNicol, Gavin, Feron, Sarah, Ouyang, Zutao, Papale, Dario, Trotta, Carlo, Canfora, Eleonora, Cheah, You-Wei, Christianson, Danielle, Alberto, Ma Carmelita R, Alekseychik, Pavel, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Billesbach, David P, Bohrer, Gil, Bracho, Rosvel, Buchmann, Nina, Campbell, David I, Celis, Gerardo, Chen, Jiquan, Chen, Weinan, Chu, Housen, Dalmagro, Higo J, Dengel, Sigrid, Desai, Ankur R, Detto, Matteo, Dolman, Han, Eichelmann, Elke, Euskirchen, Eugenie, Famulari, Daniela, Fuchs, Kathrin, Goeckede, Mathias, Gogo, Sébastien, Gondwe, Mangaliso J, Goodrich, Jordan P, Gottschalk, Pia, Graham, Scott L, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S, Hirano, Takashi, Hollinger, David, Hörtnagl, Lukas, Iwata, Hiroki, Jacotot, Adrien, Jurasinski, Gerald, Kang, Minseok, Kasak, Kuno, King, John, Klatt, Janina, Koebsch, Franziska, Krauss, Ken W, Lai, Derrick YF, Lohila, Annalea, Mammarella, Ivan, Marchesini, Luca Belelli, Manca, Giovanni, Matthes, Jaclyn Hatala, Maximov, Trofim, Merbold, Lutz, Mitra, Bhaskar, Morin, Timothy H, Nemitz, Eiko, Nilsson, Mats B, Niu, Shuli, Oechel, Walter C, Oikawa, Patricia Y, Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Reba, Michele L, Richardson, Andrew D, Riley, William, Runkle, Benjamin RK, Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sanchez, Camilo Rey, Schuur, Edward A, Schäfer, Karina VR, Sonnentag, Oliver, Sparks, Jed P, Stuart-Haëntjens, Ellen, Sturtevant, Cove, Sullivan, Ryan C, Szutu, Daphne J, Thom, Jonathan E, Torn, Margaret S, Tuittila, Eeva-Stiina, Turner, Jessica, Ueyama, Masahito, Valach, Alex C, Vargas, Rodrigo, Varlagin, Andrej, and Vazquez-Lule, Alma
Subjects: Earth Sciences, Atmospheric Sciences, Climate Action, Geochemistry, Physical Geography and Environmental Geoscience, Atmospheric sciences, Geoinformatics, Physical geography and environmental geoscience
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 20g g€¯S to 20g g€¯N) the spring onset of elevated CH4 emissions starts 3g€¯d earlier, and the CH4 emission season lasts 4g€¯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 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.
Published: 2021

9. COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

Author: Bond‐Lamberty, Ben, Christianson, Danielle S, Malhotra, Avni, Pennington, Stephanie C, Sihi, Debjani, AghaKouchak, Amir, Anjileli, Hassan, Arain, M Altaf, Armesto, Juan J, Ashraf, Samaneh, Ataka, Mioko, Baldocchi, Dennis, Black, Thomas Andrew, Buchmann, Nina, Carbone, Mariah S, Chang, Shih‐Chieh, Crill, Patrick, Curtis, Peter S, Davidson, Eric A, Desai, Ankur R, Drake, John E, El‐Madany, Tarek S, Gavazzi, Michael, Görres, Carolyn‐Monika, Gough, Christopher M, Goulden, Michael, Gregg, Jillian, del Arroyo, Omar Gutiérrez, He, Jin‐Sheng, Hirano, Takashi, Hopple, Anya, Hughes, Holly, Järveoja, Järvi, Jassal, Rachhpal, Jian, Jinshi, Kan, Haiming, Kaye, Jason, Kominami, Yuji, Liang, Naishen, Lipson, David, Macdonald, Catriona A, Maseyk, Kadmiel, Mathes, Kayla, Mauritz, Marguerite, Mayes, Melanie A, McNulty, Steve, Miao, Guofang, Migliavacca, Mirco, Miller, Scott, Miniat, Chelcy F, Nietz, Jennifer G, Nilsson, Mats B, Noormets, Asko, Norouzi, Hamidreza, O’Connell, Christine S, Osborne, Bruce, Oyonarte, Cecilio, Pang, Zhuo, Peichl, Matthias, Pendall, Elise, Perez‐Quezada, Jorge F, Phillips, Claire L, Phillips, Richard P, Raich, James W, Renchon, Alexandre A, Ruehr, Nadine K, Sánchez‐Cañete, Enrique P, Saunders, Matthew, Savage, Kathleen E, Schrumpf, Marion, Scott, Russell L, Seibt, Ulli, Silver, Whendee L, Sun, Wu, Szutu, Daphne, Takagi, Kentaro, Takagi, Masahiro, Teramoto, Munemasa, Tjoelker, Mark G, Trumbore, Susan, Ueyama, Masahito, Vargas, Rodrigo, Varner, Ruth K, Verfaillie, Joseph, Vogel, Christoph, Wang, Jinsong, Winston, Greg, Wood, Tana E, Wu, Juying, Wutzler, Thomas, Zeng, Jiye, Zha, Tianshan, Zhang, Quan, and Zou, Junliang
Subjects: Climate Change Impacts and Adaptation, Environmental Sciences, 2.6 Resources and infrastructure (aetiology), Climate Action, Atmosphere, Carbon Dioxide, Ecosystem, Greenhouse Gases, Methane, Nitrous Oxide, Reproducibility of Results, Respiration, Soil, carbon dioxide, greenhouse gases, methane, open data, open science, soil respiration, Biological Sciences, Ecology, Biological sciences, Earth sciences, Environmental sciences
Abstract: 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.
Published: 2020

10. Handily measuring sensible and latent heat exchanges at a bargain: A test of the variance-Bowen ratio approach

Author: Wang, Tianxin, Verfaillie, Joseph, Szutu, Daphne, and Baldocchi, Dennis
Published: 2023
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11. Assessing the carbon and climate benefit of restoring degraded agricultural peat soils to managed wetlands

Author: Hemes, Kyle S, Chamberlain, Samuel D, Eichelmann, Elke, Anthony, Tyler, Valach, Amy, Kasak, Kuno, Szutu, Daphne, Verfaillie, Joe, Silver, Whendee L, and Baldocchi, Dennis D
Subjects: Earth Sciences, Agricultural, Veterinary and Food Sciences, Biological Sciences, Climate Action, Life on Land, Greenhouse gas, Peat soil, Wetland restoration, Methane, Carbon dioxide, Sequestration, Agricultural and Veterinary Sciences, Meteorology & Atmospheric Sciences, Agricultural, veterinary and food sciences, Biological sciences, Earth sciences
Abstract: Restoring degraded peat soils presents an attractive, but largely untested, climate change mitigation approach. Drained peat soils used for agriculture can be large greenhouse gas sources. By restoring subsided peat soils to managed, impounded wetlands, significant agricultural emissions are avoided, and soil carbon can be sequestered and protected. Here, we synthesize 36 site-years of continuous carbon dioxide and methane flux data from a mesonetwork of eddy covariance towers in the Sacramento-San Joaquin Delta in California, USA to compute carbon and greenhouse gas budgets for drained agricultural land uses and compare these to restored deltaic wetlands. We found that restored wetlands effectively sequestered carbon and halted soil carbon loss associated with drained agricultural land uses. Depending on the age and disturbance regime of the restored wetland, many land use conversions from agriculture to restored wetland resulted in emission reductions over a 100-year timescale. With a simple model of radiative forcing and atmospheric lifetimes, we showed that restored wetlands do not begin to accrue greenhouse gas benefits until nearly a half century, and become net sinks from the atmosphere after a century. Due to substantial interannual variability and uncertainty about the multi-decadal successional trajectory of managed, restored wetlands, ongoing ecosystem flux measurements are critical for understanding the long-term impacts of wetland restoration for climate change mitigation.
Published: 2019

12. Matching high resolution satellite data and flux tower footprints improves their agreement in photosynthesis estimates

Author: Kong, Juwon, Ryu, Youngryel, Liu, Jiangong, Dechant, Benjamin, Rey-Sanchez, Camilo, Shortt, Robert, Szutu, Daphne, Verfaillie, Joe, Houborg, Rasmus, and Baldocchi, Dennis D.
Published: 2022
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13. Soil properties and sediment accretion modulate methane fluxes from restored wetlands

Author: Chamberlain, Samuel D, Anthony, Tyler L, Silver, Whendee L, Eichelmann, Elke, Hemes, Kyle S, Oikawa, Patricia Y, Sturtevant, Cove, Szutu, Daphne J, Verfaillie, Joseph G, and Baldocchi, Dennis D
Subjects: Climate Change Impacts and Adaptation, Environmental Sciences, California, Carbon, Carbon Dioxide, Conservation of Natural Resources, Geologic Sediments, Methane, Soil, Wetlands, alternative electron acceptor, carbon flux, eddy covariance, greenhouse gas balance, information theory, peatland, redox, Sacramento-San Joaquin Delta, Biological Sciences, Ecology, Biological sciences, Earth sciences, Environmental sciences
Abstract: Wetlands are the largest source of methane (CH4 ) globally, yet our understanding of how process-level controls scale to ecosystem fluxes remains limited. It is particularly uncertain how variable soil properties influence ecosystem CH4 emissions on annual time scales. We measured ecosystem carbon dioxide (CO2 ) and CH4 fluxes by eddy covariance from two wetlands recently restored on peat and alluvium soils within the Sacramento-San Joaquin Delta of California. Annual CH4 fluxes from the alluvium wetland were significantly lower than the peat site for multiple years following restoration, but these differences were not explained by variation in dominant climate drivers or productivity across wetlands. Soil iron (Fe) concentrations were significantly higher in alluvium soils, and alluvium CH4 fluxes were decoupled from plant processes compared with the peat site, as expected when Fe reduction inhibits CH4 production in the rhizosphere. Soil carbon content and CO2 uptake rates did not vary across wetlands and, thus, could also be ruled out as drivers of initial CH4 flux differences. Differences in wetland CH4 fluxes across soil types were transient; alluvium wetland fluxes were similar to peat wetland fluxes 3 years after restoration. Changing alluvium CH4 emissions with time could not be explained by an empirical model based on dominant CH4 flux biophysical drivers, suggesting that other factors, not measured by our eddy covariance towers, were responsible for these changes. Recently accreted alluvium soils were less acidic and contained more reduced Fe compared with the pre-restoration parent soils, suggesting that CH4 emissions increased as conditions became more favorable to methanogenesis within wetland sediments. This study suggests that alluvium soil properties, likely Fe content, are capable of inhibiting ecosystem-scale wetland CH4 flux, but these effects appear to be transient without continued input of alluvium to wetland sediments.
Published: 2018

14. Net fluxes of broadband shortwave and photosynthetically active radiation complement NDVI and near infrared reflectance of vegetation to explain gross photosynthesis variability across ecosystems and climate

Author: Mallick, Kanishka, primary, Verfaillie, Joseph, additional, Wang, Tianxin, additional, Ortiz, Ariane Arias, additional, Szutu, Daphne, additional, Yi, Koong, additional, Kang, Yanghui, additional, Shortt, Robert, additional, Hu, Tian, additional, Sulis, Mauro, additional, Szantoi, Zoltan, additional, Boulet, Gilles, additional, Fisher, Joshua B., additional, and Baldocchi, Dennis, additional
Published: 2024
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15. Effect of Drought-Induced Salinization on Wetland Methane Emissions, Gross Ecosystem Productivity, and Their Interactions

Author: Chamberlain, Samuel D., Hemes, Kyle S., Eichelmann, Elke, Szutu, Daphne J., Verfaillie, Joseph G., and Baldocchi, Dennis D.
Published: 2020

16. Assessing the carbon and climate benefit of restoring degraded agricultural peat soils to managed wetlands

Author: Hemes, Kyle S., Chamberlain, Samuel D., Eichelmann, Elke, Anthony, Tyler, Valach, Amy, Kasak, Kuno, Szutu, Daphne, Verfaillie, Joe, Silver, Whendee L., and Baldocchi, Dennis D.
Published: 2019
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17. Water Scarcity in Semi-Arid California Compromises Perennial Alfalfa's High Yield and Carbon Sinking Potentials

Author: Wang, Tianxin, primary, Baldocchi, Dennis, additional, Mallick, Kanishka, additional, Verfaillie, Joseph, additional, and Szutu, Daphne, additional
Published: 2024
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18. How Advection Affects the Surface Energy Balance and Plays a Role in its Closure at an Irrigated Alfalfa Field

Author: Wang, Tianxin, primary, Alfieri, Joseph, additional, Mallick, Kanishka, additional, Arias Ortiz, Ariane, additional, Anderson, Martha C., additional, Fisher, Joshua B., additional, Girotto, Manuela, additional, Szutu, Daphne, additional, Verfaillie, Joseph, additional, and Baldocchi, Dennis, additional
Published: 2023
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19. Detecting Hot Spots of Methane Flux Using Footprint-Weighted Flux Maps.

Author: Rey-Sanchez, Camilo, Rey-Sanchez, Camilo, Arias-Ortiz, Ariane, Kasak, Kuno, Chu, Housen, Szutu, Daphne, Verfaillie, Joseph, Baldocchi, Dennis, Rey-Sanchez, Camilo, Rey-Sanchez, Camilo, Arias-Ortiz, Ariane, Kasak, Kuno, Chu, Housen, Szutu, Daphne, Verfaillie, Joseph, and Baldocchi, Dennis
Abstract: In this study, we propose a new technique for mapping the spatial heterogeneity in gas exchange around flux towers using flux footprint modeling and focusing on detecting hot spots of methane (CH4) flux. In the first part of the study, we used a CH4 release experiment to evaluate three common flux footprint models: the Hsieh model (Hsieh et al., 2000), the Kljun model (Kljun et al., 2015), and the K & M model (Kormann and Meixner, 2001), finding that the K & M model was the most accurate under these conditions. In the second part of the study, we introduce the Footprint-Weighted Flux Map, a new technique to map spatial heterogeneity in fluxes. Using artificial CH4 release experiments, natural tracer approaches and flux chambers we mapped the spatial flux heterogeneity, and detected and validated a hot spot of CH4 flux in a oligohaline restored marsh. Through chamber measurements during the months of April and May, we found that fluxes at the hot spot were on average as high as 6589 ± 7889 nmol m-2 s-1 whereas background flux from the open water were on average 15.2 ± 7.5 nmol m-2 s-1. This study provides a novel tool to evaluate the spatial heterogeneity of fluxes around eddy-covariance towers and creates important insights for the interpretation of hot spots of CH4 flux, paving the way for future studies aiming to understand subsurface biogeochemical processes and the microbiological conditions that lead to the occurrence of hot spots and hot moments of CH4 flux.
Published: 2022

20. Matching high resolution satellite data and flux tower footprints improves their agreement in photosynthesis estimates

Author: Kong, Juwon, primary, Ryu, Youngryel, additional, Liu, Jiangong, additional, Dechant, Benjamin, additional, Rey-Sanchez, Camilo, additional, Shortt, Robert, additional, Szutu, Daphne, additional, Verfaillie, Joe, additional, Houborg, Rasmus, additional, and Baldocchi, Dennis, additional
Published: 2022
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21. Biogeochemical drivers of soil N2O, CH4, and CO2 emissions from alfalfa using long-term continuous measurements

Author: Anthony, Tyler, primary, Verfaillie, Joseph, additional, Szutu, Daphne, additional, Baldocchi, Dennis, additional, and Silver, Whendee, additional
Published: 2021
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22. Restoring wetlands on intensive agricultural lands modifies nitrogen cycling microbial communities and reduces N2O production potential

Author: Kasak, Kuno, primary, Espenberg, Mikk, additional, Anthony, Tyler L., additional, Tringe, Susannah G., additional, Valach, Alex C., additional, Hemes, Kyle S., additional, Silver, Whendee L., additional, Mander, Ülo, additional, Kill, Keit, additional, McNicol, Gavin, additional, Szutu, Daphne, additional, Verfaillie, Joseph, additional, and Baldocchi, Dennis D., additional
Published: 2021
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23. A novel approach to partitioning evapotranspiration into evaporation and transpiration in flooded ecosystems

Author: Eichelmann, Elke, primary, Mantoani, Mauricio C., additional, Chamberlain, Samuel D., additional, Hemes, Kyle S., additional, Oikawa, Patricia Y., additional, Szutu, Daphne, additional, Valach, Alex, additional, Verfaillie, Joseph, additional, and Baldocchi, Dennis D., additional
Published: 2021
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24. FLUXNET-CH4 : a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands

Author: Delwiche, Kyle B., Knox, Sara Helen, Malhotra, Avni, Fluet-Chouinard, Etienne, McNicol, Gavin, Feron, Sarah, Ouyang, Zutao, Papale, Dario, Trotta, Carlo, Canfora, Eleonora, Cheah, You Wei, Christianson, Danielle, Alberto, Ma Carmelita R., Alekseychik, Pavel, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Billesbach, David P., Bohrer, Gil, Bracho, Rosvel, Buchmann, Nina, Campbell, David I., Celis, Gerardo, Chen, Jiquan, Chen, Weinan, Chu, Housen, Dalmagro, Higo J., Dengel, Sigrid, Desai, Ankur R., Detto, Matteo, Dolman, Han, Eichelmann, Elke, Euskirchen, Eugenie, Famulari, Daniela, Fuchs, Kathrin, Goeckede, Mathias, Gogo, Sébastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Graham, Scott L., Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Hollinger, David, Hörtnagl, Lukas, Iwata, Hiroki, Jacotot, Adrien, Jurasinski, Gerald, Kang, Minseok, Kasak, Kuno, King, John, Klatt, Janina, Koebsch, Franziska, Krauss, Ken W., Lai, Derrick Y.F., Lohila, Annalea, Mammarella, Ivan, Belelli Marchesini, Luca, Manca, Giovanni, Matthes, Jaclyn Hatala, Maximov, Trofim, Merbold, Lutz, Mitra, Bhaskar, Morin, Timothy H., Nemitz, Eiko, Nilsson, Mats B., Niu, Shuli, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Riley, William, Runkle, Benjamin R.K., Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sanchez, Camilo Rey, Schuur, Edward A., Schäfer, Karina V.R., Sonnentag, Oliver, Sparks, Jed P., Stuart-Haëntjens, Ellen, Sturtevant, Cove, Sullivan, Ryan C., Szutu, Daphne J., Thom, Jonathan E., Torn, Margaret S., Tuittila, Eeva Stiina, Turner, Jessica, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Varlagin, Andrej, Vazquez-Lule, Alma, Verfaillie, Joseph G., Vesala, Timo, Vourlitis, George L., Ward, Eric J., Wille, Christian, Wohlfahrt, Georg, Wong, Guan Xhuan, Zhang, Zhen, Zona, Donatella, Windham-Myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B., Institute for Atmospheric and Earth System Research (INAR), Micrometeorology and biogeochemical cycles, Viikki Plant Science Centre (ViPS), Ecosystem processes (INAR Forest Sciences), Earth Sciences, and Earth and Climate
Subjects: 1171 Geosciences, Earth sciences, SDG 17 - Partnerships for the Goals, Physical Geography, ddc:550, 114 Physical sciences, 1172 Environmental sciences, Atmospheric Sciences
Abstract: Methane (CH$_{4}$) emissions from natural landscapes constitute roughly half of global CH$_{4}$ 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 CH$_{4}$ flux are ideal for constraining ecosystem-scale CH$_{4}$ emissions due to quasi-continuous and high-temporal-resolution CH$_{4}$ 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-CH$_{4}$ Version 1.0, the first open-source global dataset of CH$_{4}$ 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 CH$_{4}$ 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-CH$_{4}$ representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH$_{4}$ Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH$_{4}$ emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH$_{4}$ 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 CH$_{4}$ emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20° S to 20° N) the spring onset of elevated CH$_{4}$ emissions starts 3 d earlier, and the CH$_{4}$ emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH$_{4}$ emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH$_{4}$ emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH$_{4}$ emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH$_{4}$ emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH$_{4}$ modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH$_{4}$ peak). FLUXNET-CH$_{4}$ is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH$_{4}$ 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-CH$_{4}$ 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.
Published: 2021
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25. Carbon Flux Trajectories and Site Conditions from Restored Impounded Marshes in the Sacramento‐San Joaquin Delta

Author: Valach, Alex C., primary, Kasak, Kuno, additional, Hemes, Kyle S., additional, Szutu, Daphne, additional, Verfaillie, Joe, additional, and Baldocchi, Dennis D., additional
Published: 2021
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26. Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Author: Irvin, Jeremy, primary, Zhou, Sharon, additional, McNicol, Gavin, additional, Lu, Fred, additional, Liu, Vincent, additional, Fluet-Chouinard, Etienne, additional, Ouyang, Zutao, additional, Knox, Sara Helen, additional, Lucas-Moffat, Antje, additional, Trotta, Carlo, additional, Papale, Dario, additional, Vitale, Domenico, additional, Mammarella, Ivan, additional, Alekseychik, Pavel, additional, Aurela, Mika, additional, Avati, Anand, additional, Baldocchi, Dennis, additional, Bansal, Sheel, additional, Bohrer, Gil, additional, Campbell, David I, additional, Chen, Jiquan, additional, Chu, Housen, additional, Dalmagro, Higo J, additional, Delwiche, Kyle B, additional, Desai, Ankur R, additional, Euskirchen, Eugenie, additional, Feron, Sarah, additional, Goeckede, Mathias, additional, Heimann, Martin, additional, Helbig, Manuel, additional, Helfter, Carole, additional, Hemes, Kyle S, additional, Hirano, Takashi, additional, Iwata, Hiroki, additional, Jurasinski, Gerald, additional, Kalhori, Aram, additional, Kondrich, Andrew, additional, Lai, Derrick YF, additional, Lohila, Annalea, additional, Malhotra, Avni, additional, Merbold, Lutz, additional, Mitra, Bhaskar, additional, Ng, Andrew, additional, Nilsson, Mats B, additional, Noormets, Asko, additional, Peichl, Matthias, additional, Rey-Sanchez, A. Camilo, additional, Richardson, Andrew D, additional, Runkle, Benjamin RK, additional, Schäfer, Karina VR, additional, Sonnentag, Oliver, additional, Stuart-Haëntjens, Ellen, additional, Sturtevant, Cove, additional, Ueyama, Masahito, additional, Valach, Alex C, additional, Vargas, Rodrigo, additional, Vourlitis, George L, additional, Ward, Eric J, additional, Wong, Guan Xhuan, additional, Zona, Donatella, additional, Alberto, Ma. Carmelita R, additional, Billesbach, David P, additional, Celis, Gerardo, additional, Dolman, Han, additional, Friborg, Thomas, additional, Fuchs, Kathrin, additional, Gogo, Sébastien, additional, Gondwe, Mangaliso J, additional, Goodrich, Jordan P, additional, Gottschalk, Pia, additional, Hörtnagl, Lukas, additional, Jacotot, Adrien, additional, Koebsch, Franziska, additional, Kasak, Kuno, additional, Maier, Regine, additional, Morin, Timothy H, additional, Nemitz, Eiko, additional, Oechel, Walter C, additional, Oikawa, Patricia Y, additional, Ono, Keisuke, additional, Sachs, Torsten, additional, Sakabe, Ayaka, additional, Schuur, Edward A, additional, Shortt, Robert, additional, Sullivan, Ryan C, additional, Szutu, Daphne J, additional, Tuittila, Eeva-Stiina, additional, Varlagin, Andrej, additional, Verfaillie, Joeseph G, additional, Wille, Christian, additional, Windham-Myers, Lisamarie, additional, Poulter, Benjamin, additional, and Jackson, Robert B, additional
Published: 2021
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27. Assessing effects of native forest restoration on soil moisture dynamics and potential aquifer recharge, Auwahi, Maui

Author: Perkins, Kim S., Nimmo, John R., Medeiros, Arthur C., Szutu, Daphne J., and von Allmen, Erica
Published: 2014
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28. FLUXNET-CH4: a global, multi-ecosystem datasetand analysis of methane seasonalityfrom freshwater wetlands

Author: Knox, Sara, Alberto, Ma, Matthes, Jaclyn, Sanchez, Camilo, Wong, Guan, Delwiche, Kyle, Knox, Sara Helen, Malhotra, Avni, Fluet-Chouinard, Etienne, McNicol, Gavin, Feron, Sarah, Ouyang, Zutao, Papale, Dario, Trotta, Carlo, Canfora, Eleonora, Cheah, You-Wei, Christianson, Danielle, Alberto, Ma. Carmelita R., Alekseychik, Pavel, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Billesbach, David, Bohrer, Gil, Bracho, Rosvel, Buchmann, Nina, Campbell, David, Celis, Gerardo, Chen, Jiquan, Chen, Weinan, Chu, Housen, Dalmagro, Higo, Dengel, Sigrid, Desai, Ankur, Detto, Matteo, Dolman, Han, Eichelmann, Elke, Euskirchen, Eugenie, Famulari, Daniela, Fuchs, Kathrin, Goeckede, Mathias, Gogo, Sébastien, Gondwe, Mangaliso, Goodrich, Jordan, Gottschalk, Pia, Graham, Scott, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle, Hirano, Takashi, Hollinger, David, Hörtnagl, Lukas, Iwata, Hiroki, Jacotot, Adrien, Jurasinski, Gerald, Kang, Minseok, Kasak, Kuno, King, John, Klatt, Janina, Koebsch, Franziska, Krauss, Ken, Lai, Derrick, Lohila, Annalea, Mammarella, Ivan, Belelli Marchesini, Luca, Manca, Giovanni, Matthes, Jaclyn Hatala, Maximov, Trofim, Merbold, Lutz, Mitra, Bhaskar, Morin, Timothy, Nemitz, Eiko, Nilsson, Mats, Niu, Shuli, Oechel, Walter, Oikawa, Patricia, Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Reba, Michele, Richardson, Andrew, Riley, William, Runkle, Benjamin, Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sanchez, Camilo Rey, Schuur, Edward, Schäfer, Karina, Sonnentag, Oliver, Sparks, Jed, Stuart-Haëntjens, Ellen, Sturtevant, Cove, Sullivan, Ryan, Szutu, Daphne, Thom, Jonathan, Torn, Margaret, Tuittila, Eeva-Stiina, Turner, Jessica, Ueyama, Masahito, Valach, Alex, Vargas, Rodrigo, Varlagin, Andrej, Vazquez-Lule, Alma, Verfaillie, Joseph, Vesala, Timo, Vourlitis, George, Ward, Eric, Wille, Christian, Wohlfahrt, Georg, Wong, Guan Xhuan, Zhang, Zhen, Zona, Donatella, Windham-Myers, Lisamarie, Poulter, Benjamin, Jackson, Robert, Institut des Sciences de la Terre d'Orléans - UMR7327 (ISTO), Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Biogéosystèmes Continentaux - UMR7327, and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC)
Subjects: [SDU]Sciences of the Universe [physics], [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment
Abstract: International audience; 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.
Published: 2021
Full Text: View/download PDF

29. Gap-filling eddy covariance methane fluxes:Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Author: Irvin, Jeremy, Zhou, Sharon, Mcnicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Chen, Jiquan, Chu, Housen, Dalmagro, Higo J, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Yf, Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B, Noormets, Asko, Peichl, Matthias, Rey-sanchez, A. Camilo, Richardson, Andrew D, Runkle, Benjamin Rk, Schäfer, Karina Vr, Sonnentag, Oliver, Stuart-haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C, Vargas, Rodrigo, Vourlitis, George L, Ward, Eric J, Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R, Billesbach, David P, Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J, Goodrich, Jordan P, Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H, Nemitz, Eiko, Oechel, Walter C, Oikawa, Patricia Y, Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A, Shortt, Robert, Sullivan, Ryan C, Szutu, Daphne J, Tuittila, Eeva-stiina, Varlagin, Andrej, Verfaillie, Joeseph G, Wille, Christian, Windham-myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B, Irvin, Jeremy, Zhou, Sharon, Mcnicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Chen, Jiquan, Chu, Housen, Dalmagro, Higo J, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Yf, Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B, Noormets, Asko, Peichl, Matthias, Rey-sanchez, A. Camilo, Richardson, Andrew D, Runkle, Benjamin Rk, Schäfer, Karina Vr, Sonnentag, Oliver, Stuart-haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C, Vargas, Rodrigo, Vourlitis, George L, Ward, Eric J, Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R, Billesbach, David P, Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J, Goodrich, Jordan P, Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H, Nemitz, Eiko, Oechel, Walter C, Oikawa, Patricia Y, Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A, Shortt, Robert, Sullivan, Ryan C, Szutu, Daphne J, Tuittila, Eeva-stiina, Varlagin, Andrej, Verfaillie, Joeseph G, Wille, Christian, Windham-myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B
Abstract: 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 impro
Published: 2021

30. Evaluation of Atmospheric Boundary Layer Height From Wind Profiling Radar and Slab Models and Its Responses to Seasonality of Land Cover, Subsidence, and Advection

Author: Rey‐Sanchez, Camilo, primary, Wharton, Sonia, additional, Vilà‐Guerau de Arellano, Jordi, additional, Paw U, Kyaw Tha, additional, Hemes, Kyle S., additional, Fuentes, Jose D., additional, Osuna, Jessica, additional, Szutu, Daphne, additional, Ribeiro, João Vinicius, additional, Verfaillie, Joseph, additional, and Baldocchi, Dennis, additional
Published: 2021
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31. Managing hydrology can reduce methane emissions of high-emitting freshwater marshes by half making them present-day net greenhouse gas sinks

Author: Valach, Alex, primary, Eichelmann, Elke, additional, Hemes, Kyle, additional, Kasak, Kuno, additional, Knox, Sara, additional, Oikawa, Patty, additional, Szutu, Daphne, additional, Verfaillie, Joseph, additional, and Baldocchi, Dennis, additional
Published: 2021
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32. FLUXNET-CH4: A global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands

Author: Delwiche, Kyle B., primary, Knox, Sara Helen, additional, Malhotra, Avni, additional, Fluet-Chouinard, Etienne, additional, McNicol, Gavin, additional, Feron, Sarah, additional, Ouyang, Zutao, additional, Papale, Dario, additional, Trotta, Carlo, additional, Canfora, Eleonora, additional, Cheah, You-Wei, additional, Christianson, Danielle, additional, Alberto, M. Carmelita R., additional, Alekseychik, Pavel, additional, Aurela, Mika, additional, Baldocchi, Dennis, additional, Bansal, Sheel, additional, Billesbach, David P., additional, Bohrer, Gil, additional, Bracho, Rosvel, additional, Buchmann, Nina, additional, Campbell, David I., additional, Celis, Gerardo, additional, Chen, Jiquan, additional, Chen, Weinan, additional, Chu, Housen, additional, Dalmagro, Higo J., additional, Dengel, Sigrid, additional, Desai, Ankur R., additional, Detto, Matteo, additional, Dolman, Han, additional, Eichelmann, Elke, additional, Euskirchen, Eugenie, additional, Famulari, Daniela, additional, Friborg, Thomas, additional, Fuchs, Kathrin, additional, Goeckede, Mathias, additional, Gogo, Sébastien, additional, Gondwe, Mangaliso J., additional, Goodrich, Jordan P., additional, Gottschalk, Pia, additional, Graham, Scott L., additional, Heimann, Martin, additional, Helbig, Manuel, additional, Helfter, Carole, additional, Hemes, Kyle S., additional, Hirano, Takashi, additional, Hollinger, David, additional, Hörtnagl, Lukas, additional, Iwata, Hiroki, additional, Jacotot, Adrien, additional, Jansen, Joachim, additional, Jurasinski, Gerald, additional, Kang, Minseok, additional, Kasak, Kuno, additional, King, John, additional, Klatt, Janina, additional, Koebsch, Franziska, additional, Krauss, Ken W., additional, Lai, Derrick Y. F., additional, Mammarella, Ivan, additional, Manca, Giovanni, additional, Marchesini, Luca Belelli, additional, Matthes, Jaclyn Hatala, additional, Maximon, Trofim, additional, Merbold, Lutz, additional, Mitra, Bhaskar, additional, Morin, Timothy H., additional, Nemitz, Eiko, additional, Nilsson, Mats B., additional, Niu, Shuli, additional, Oechel, Walter C., additional, Oikawa, Patricia Y., additional, Ono, Keisuke, additional, Peichl, Matthias, additional, Peltola, Olli, additional, Reba, Michele L., additional, Richardson, Andrew D., additional, Riley, William, additional, Runkle, Benjamin R. K., additional, Ryu, Youngryel, additional, Sachs, Torsten, additional, Sakabe, Ayaka, additional, Sanchez, Camilo Rey, additional, Schuur, Edward A., additional, Schäfer, Karina V. R., additional, Sonnentag, Oliver, additional, Sparks, Jed P., additional, Stuart-Haëntjens, Ellen, additional, Sturtevant, Cove, additional, Sullivan, Ryan C., additional, Szutu, Daphne J., additional, Thom, Jonathan E., additional, Torn, Margaret S., additional, Tuittila, Eeva-Stiina, additional, Turner, Jessica, additional, Ueyama, Masahito, additional, Valach, Alex C., additional, Vargas, Rodrigo, additional, Varlagin, Andrej, additional, Vazquez-Lule, Alma, additional, Verfaillie, Joseph G., additional, Vesala, Timo, additional, Vourlitis, George L., additional, Ward, Eric J., additional, Wille, Christian, additional, Wohlfahrt, Georg, additional, Wong, Guan Xhuan, additional, Zhang, Zhen, additional, Zona, Donatella, additional, Windham-Myers, Lisamarie, additional, Poulter, Benjamin, additional, and Jackson, Robert B., additional
Published: 2021
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33. Outgoing Near‐Infrared Radiation From Vegetation Scales With Canopy Photosynthesis Across a Spectrum of Function, Structure, Physiological Capacity, and Weather

Author: Baldocchi, Dennis D., primary, Ryu, Youngryel, additional, Dechant, Benjamin, additional, Eichelmann, Elke, additional, Hemes, Kyle, additional, Ma, Siyan, additional, Sanchez, Camilo Rey, additional, Shortt, Robert, additional, Szutu, Daphne, additional, Valach, Alex, additional, Verfaillie, Joe, additional, Badgley, Grayson, additional, Zeng, Yelu, additional, and Berry, Joseph A., additional
Published: 2020
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34. Variability of nitrogen-cycle microbial communities determined by the age of restored wetlands

Author: Kasak, Kuno, primary, Anthony, Tyler, additional, Valach, Alex, additional, Hemes, Kyle, additional, Kill, Keit, additional, Silver, Whendee, additional, Mander, Ülo, additional, Szutu, Daphne, additional, Verfaillie, Joseph, additional, and Baldocchi, Dennis, additional
Published: 2020
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35. A novel approach to partitioning evapotranspiration into evaporation and transpiration in flooded ecosystems.

Author: Eichelmann, Elke, Mantoani, Mauricio C., Chamberlain, Samuel D., Hemes, Kyle S., Oikawa, Patricia Y., Szutu, Daphne, Valach, Alex, Verfaillie, Joseph, and Baldocchi, Dennis D.
Subjects: ARTIFICIAL neural networks, EVAPOTRANSPIRATION, HYDROLOGIC cycle, FRICTION velocity, VAPOR pressure, ATMOSPHERIC temperature, HABITAT partitioning (Ecology)
Abstract: Reliable partitioning of micrometeorologically measured evapotranspiration (ET) into evaporation (E) and transpiration (T) would greatly enhance our understanding of the water cycle and its response to climate change related shifts in local‐to‐regional climate conditions and rising global levels of vapor pressure deficit (VPD). While some methods on ET partitioning have been developed, their underlying assumptions make them difficult to apply more generally, especially in sites with large contributions of E. Here, we report a novel ET partitioning method using artificial neural networks (ANNs) in combination with a range of environmental input variables to predict daytime E from nighttime ET measurements. The study uses eddy covariance data from four restored wetlands in the Sacramento‐San Joaquin Delta, California, USA, as well as leaf‐level T data for validation. The four wetlands vary in their vegetation make‐up and structure, representing a range of ET conditions. The ANNs were built with increasing complexity by adding the input variable that resulted in the next highest average value of model testing R2 across all sites. The order of variable inclusion (and importance) was: VPD > gap‐filled sensible heat flux (H_gf) > air temperature (Tair) > friction velocity (u∗) > other variables. The model using VPD, H_gf, Tair, and u∗ showed the best performance during validation with independent data and had a mean testing R2 value of 0.853 (averaged across all sites, range from 0.728 to 0.910). In comparison to other methods, our ANN method generated T/ET partitioning results which were more consistent with CO2 exchange data especially for more heterogeneous sites with large E contributions. Our method improves the understanding of T/ET partitioning. While it may be particularly suited to flooded ecosystems, it can also improve T/ET partitioning in other systems, increasing our knowledge of the global water cycle and ecosystem functioning. [ABSTRACT FROM AUTHOR]
Published: 2022
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36. COSORE: A community database for continuous soil respiration and other soil-atmosphere greenhouse gas flux data

Author: Bond-Lamberty, Ben, Christianson, Danielle S., Malhotra, Avni, Pennington, Stephanie C., Sihi, Debjani, AghaKouchak, Amir, Anjileli, Hassan, Arain, M. Altaf, Armesto, Juan J., Ashraf, Samaneh, Ataka, Mioko, Baldocchi, Dennis, Black, Thomas Andrew, Buchmann, Nina, Carbone, Mariah S., Chang, Shih-Chieh, Crill, Patrick, Curtis, Peter S., Davidson, Eric A., Desai, Ankur R., Drake, John E., El-Madany, Tarek S., Gavazzi, Michael, Gorres, Carolyn-Monika, Gough, Christopher M., Goulden, Michael, Gregg, Jillian, del Arroyo, Omar Gutierrez, He, Jin-Sheng, Hirano, Takashi, Hopple, Anya, Hughes, Holly, Järveoja, Järvi, Jassal, Rachhpal, Jian, Jinshi, Kan, Haiming, Kaye, Jason, Kominami, Yuji, Liang, Naishen, Lipson, David, Macdonald, Catriona A., Maseyk, Kadmiel, Mathes, Kayla, Mauritz, Marguerite, Mayes, Melanie A., McNulty, Steve, Miao, Guofang, Migliavacca, Mirco, Miller, Scott, Miniat, Chelcy F., Nietz, Jennifer G., Nilsson, Mats, Noormets, Asko, Norouzi, Hamidreza, O'Connell, Christine S., Osborne, Bruce, Oyonarte, Cecilio, Pang, Zhuo, Peichl, Matthias, Pendall, Elise, Perez-Quezada, Jorge F., Phillips, Claire L., Raich, James W., Renchon, Alexandre A., Ruehr, Nadine K., Sanchez-Canete, Enrique P., Saunders, Matthew, Savage, Kathleen E., Schrumpf, Marion, Scott, Russell L., Seibt, Ulli, Silver, Whendee L., Sun, Wu, Szutu, Daphne, Takagi, Kentaro, Teramoto, Munemasa, Tjoelker, Mark G., Trumbore, Susan, Ueyama, Masahito, Vargas, Rodrigo, Varner, Ruth K., Verfaillie, Joseph, Vogel, Christoph, Wang, Jinsong, Winston, Greg, Wood, Tana E., Wu, Juying, Wutzler, Thomas, Zeng, Jiye, Zha, Tianshan, Zhang, Quan, and Zou, Junliang
Subjects: Climate Research
Abstract: 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 CO(2)flux, commonly though imprecisely termed soil respiration (R-S), is one of the largest carbon fluxes in the Earth system. An increasing number of high-frequencyR(S)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 measuredR(S), 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.
Published: 2020

37. Effect of Drought-Induced Salinization on Wetland Methane Emissions, Gross Ecosystem Productivity, and Their Interactions

Author: Chamberlain, Samuel D., primary, Hemes, Kyle S., additional, Eichelmann, Elke, additional, Szutu, Daphne J., additional, Verfaillie, Joseph G., additional, and Baldocchi, Dennis D., additional
Published: 2019
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38. Productive wetlands restored for carbon sequestration quickly become net CO2 sinks with site-level factors driving uptake variability.

Author: Valach, Alex C., Kasak, Kuno, Hemes, Kyle S., Anthony, Tyler L., Dronova, Iryna, Taddeo, Sophie, Silver, Whendee L., Szutu, Daphne, Verfaillie, Joseph, and Baldocchi, Dennis D.
Subjects: WETLAND restoration, CARBON sequestration, WETLANDS, WETLAND soils, MEDITERRANEAN climate, WATER levels, GROWING season
Abstract: Inundated wetlands can potentially sequester substantial amounts of soil carbon (C) over the long-term because of slow decomposition and high primary productivity, particularly in climates with long growing seasons. Restoring such wetlands may provide one of several effective negative emission technologies to remove atmospheric CO2 and mitigate climate change. However, there remains considerable uncertainty whether these heterogeneous ecotones are consistent net C sinks and to what degree restoration and management methods affect C sequestration. Since wetland C dynamics are largely driven by climate, it is difficult to draw comparisons across regions. With many restored wetlands having different functional outcomes, we need to better understand the importance of site-specific conditions and how they change over time. We report on 21 site-years of C fluxes using eddy covariance measurements from five restored fresh to brackish wetlands in a Mediterranean climate. The wetlands ranged from 3 to 23 years after restoration and showed that several factors related to restoration methods and site conditions altered the magnitude of C sequestration by affecting vegetation cover and structure. Vegetation established within two years of re-flooding but followed different trajectories depending on design aspects, such as bathymetry-determined water levels, planting methods, and soil nutrients. A minimum of 55% vegetation cover was needed to become a net C sink, which most wetlands achieved once vegetation was established. Established wetlands had a high C sequestration efficiency (i.e. the ratio of net to gross ecosystem productivity) comparable to upland ecosystems but varied between years undergoing boom-bust growth cycles and C uptake strength was susceptible to disturbance events. We highlight the large C sequestration potential of productive inundated marshes, aided by restoration design and management targeted to maximise vegetation extent and minimise disturbance. These findings have important implications for wetland restoration, policy, and management practitioners. [ABSTRACT FROM AUTHOR]
Published: 2021
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39. A Unique Combination of Aerodynamic and Surface Properties Contribute to Surface Cooling in Restored Wetlands of the Sacramento‐San Joaquin Delta, California

Author: Hemes, Kyle S., primary, Eichelmann, Elke, additional, Chamberlain, Samuel D., additional, Knox, Sara H., additional, Oikawa, Patricia Y., additional, Sturtevant, Cove, additional, Verfaillie, Joseph, additional, Szutu, Daphne, additional, and Baldocchi, Dennis D., additional
Published: 2018
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40. SAGEEP 2017 papers with only a paragraph abstract

Author: Dickey, Kira, primary, Finn, Carol, additional, Holbrook, W. Steven, additional, Bedrosian, Paul, additional, Auken, Esben, additional, Pedersen, Jesper, additional, Carr, Bradley, additional, Sims, Ken, additional, Lowenstern, Jacob, additional, Hurwitz, Shaul, additional, Munday, Timothy, additional, Davis, Aaron, additional, Soerensen, Camilla, additional, Abraham, Jared, additional, Kalinski, Michael, additional, Miyamoto, Kit, additional, Cameron, Kathleen, additional, Cannia, James, additional, Asch, Ted, additional, Ball, Lyndsay, additional, Cromwell, Geoffrey, additional, Buesch, David, additional, Miller, David, additional, Densmore, Jill, additional, Bach, Torben, additional, Pallesen, Tom Martlev, additional, Jacobsen, Rikke, additional, Triumf, Carl-Axel, additional, Persson, Lena, additional, Dahlqvist, Peter, additional, Hansen, Thomas Mejer, additional, Gulbrandsen, Mats Lundh, additional, Mulè, Shane, additional, Smiarowski, Adam, additional, Smith, David, additional, Hudson, Mark, additional, Legault, Jean, additional, Plastow, Geoffrey, additional, Eadie, Timothy, additional, Prikhodko, Alexander, additional, Tishin, Pavel, additional, Brown, Bill, additional, Oliver, James, additional, Dahlin, Torleif, additional, North, Ryan, additional, Silverstein, Jay, additional, Thompson, Robert, additional, Momayez, Moe, additional, Heath, Gail, additional, Bauman, Paul, additional, McClymont, Alastair, additional, Freund, Richard, additional, Seligman, Jon, additional, Jol, Harry, additional, Reeder, Philip, additional, Beam, Erika, additional, Mitchell, Kevin, additional, Crowder, Robert, additional, Phillips, Stephanie, additional, Johnson, Carole, additional, Robbins, Gary, additional, Lane, John, additional, Culig, Mike, additional, Davis, Nathan, additional, Paine, Jeffrey, additional, Collins, Edward, additional, Black, Andrew, additional, Nielson, Travis, additional, Bradford, John, additional, Flinchum, Brady, additional, Grana, Dario, additional, Zhang, Ye, additional, Parsekian, Andrew, additional, Richter, Daniel, additional, Harmon, Ryan, additional, Szutu, Daphne, additional, Randell, Jackie, additional, Barnard, Holly, additional, Singha, Kamini, additional, Kotikian, Maneh, additional, Paige, Ginger, additional, Carey, Austin, additional, Khalil, Mohamed, additional, Orubu, Akpofure, additional, Speece, Marvin, additional, Seyfried, Mark, additional, Glas, Robin, additional, Lautz, Laura, additional, McKenzie, Jeffrey, additional, Moucha, Robert, additional, Mark, Bryan, additional, Andersen, Theis Raaschou, additional, Schaefer, Kevin, additional, Chen, Albert, additional, Jafarov, Elchin, additional, Ludwig, Sarah, additional, Liu, Lin, additional, Michaelides, Roger, additional, Natali, Sue, additional, Panda, Santosh, additional, Schaefer, Sean, additional, Minsley, Burke, additional, Pastick, Neal, additional, Wylie, Bruce, additional, Kass, M. Andy, additional, Creighton, Andrea, additional, Jones, Benjamin, additional, Babcock, Esther, additional, Bondurant, Allen, additional, Arp, Christopher, additional, Ajo-Franklin, Jonathan, additional, Lindsey, Nathaniel, additional, Dou, Shan, additional, Wagner, Anna, additional, Bjella, Kevin, additional, Daley, Thomas, additional, Freifeld, Barry, additional, Ulrich, Craig, additional, Gelvin, Arthur, additional, Ekblaw, Ian, additional, Martin, Eileen, additional, Kuroda, Seiichiro, additional, Mohammadi, Mohammad, additional, Hickey, Craig, additional, Hayashi, Koichi, additional, Lorenzo, Juan, additional, Craig, Mitchell, additional, Morrison, Martial, additional, Delisser, Terrance, additional, Parkman, Kevin, additional, Stephens, Isaac, additional, Robbins, Bryant, additional, Mundell, John, additional, Brumbaugh, Ryan, additional, Kunkel, Forrest, additional, Hon, Kevin, additional, Cox, Jason, additional, Munsey, Jeffrey, additional, LeFebvre, Jeanne, additional, Carnevale, Mario, additional, Decker, Kathryn, additional, Karaoulis, Marios, additional, de kleine, marco, additional, Robbins, Austin, additional, Plattner, Alain, additional, Guenther, Thomas, additional, LaBrecque, Douglas, additional, Brigham, Russell, additional, LaBrecque, Daniel, additional, Robinson, Judy, additional, Slater, Lee, additional, Nguyen, Dung, additional, Smith, Nathan, additional, Kessouri, Pauline, additional, Buckman, Christopher, additional, Mankowski, Len, additional, Ngui, Yin Jeh, additional, Lin, Chih-Ping, additional, Lin, Chun-Hung, additional, Groom, Ross, additional, Lei, Yang, additional, Sheehan, Jacob, additional, Dornfest, Robin, additional, Sirles, Phil, additional, Kolawole, Folarin, additional, Atekwana, Estella, additional, Laó-Dávila, Daniel, additional, Abdelsalam, Mohamed, additional, Ivey, Toni, additional, Chindandali, Patrick, additional, Salima, Jalf, additional, Kalindekafe, Leonard, additional, Ismail, Ahmed, additional, Sickbert, Tim, additional, Pickens, Cullen, additional, Beckendorff, David, additional, Mayle, Micah, additional, Ngalamo, Jeannot, additional, Nyalugwe, Victor, additional, Aghayan, Afshin, additional, Monarco, Dominic, additional, Pfeiffer, Jim, additional, Haramy, Khamis, additional, Kidanu, Shishay, additional, Torgashov, Evgeniy, additional, Anderson, Neil, additional, Land, Lewis, additional, Laymon, Doug, additional, Wise, Matthew, additional, Hallman, David, additional, Cook, Jeffrey, additional, Steelman, Colby, additional, Capes, Donovan, additional, Pehme, Peeter, additional, Kennedy, Celia, additional, Parker, Beth, additional, Ikard, Scott, additional, Payne, Jason, additional, Teeple, Andrew, additional, Banta, Ryan, additional, Stanton, Gregory, additional, Ward, Adam, additional, Gooseff, Michael, additional, McKenna, Thomas, additional, Nyquist, Jonathan, additional, Toran, Laura, additional, O'Neill, Paul, additional, Devlin, Kelly, additional, Claes, Niels, additional, Walvoord, Michelle, additional, Day-Lewis, Frederick, additional, Jepsen, Steven, additional, Rover, Jennifer, additional, Voss, Clifford, additional, Briggs, Martin, additional, Kulongoski, Justin, additional, Adams, Josip, additional, Holmquist-Johnson, Christopher, additional, Hanson, Leanne, additional, Struckhoff, Matthew, additional, Kropidlowski, Stefan, additional, Doll, William, additional, Muller, Edward, additional, Oliver, Mark, additional, Francke, Jan, additional, Danforth, Myles, additional, Stanford, Charles, additional, Everett, Mark, additional, Bowling, Roy, additional, Laya, Juan Carlos, additional, deSmet, Timothy, additional, Grote, Katherine, additional, Hajiani, Payman, additional, Sammy, Somaria, additional, Stewart, Robert, additional, Fletcher, Andrew, additional, Hussey, Sean, additional, Hrencher, Braden, additional, Campbell, Nathan, additional, Aneke, Christian, additional, Harding, Jordan K., additional, Klazinga, Dylan, additional, Cahill, Aaron, additional, Endres, Tony, additional, Kennedy, Jeff, additional, Travis, Rebecca, additional, Norton, Stuart, additional, Ham, Brian, additional, Federico, Ric, additional, Lund, Anders, additional, Ntarlagiannis, Dimitrios, additional, Bekins, Barbara, additional, Cozzarelli, Isabelle, additional, Liu, Hsing-Chang, additional, Pettifer, Geoff, additional, Richards, Garth, additional, Jenke, Graham, additional, Lester, Neil, additional, Cherry, John, additional, Jalinoos, Frank, additional, Sauck, William, additional, Qian, Rongyi, additional, Chandarana, Upasna, additional, Morelli, Gianfranco, additional, Tayyab, Haroon, additional, An, Zhiyuan, additional, Fage, Isaac, additional, Best, Melvyn, additional, Ryan, Shawn, additional, Cote, Chad, additional, Chen, Rujun, additional, Yao, Hongchun, additional, Shen, Ruijie, additional, Zhao, Xuefeng, additional, Sun, Shaoqin, additional, Yin, Qian, additional, Krahenbuhl, Richard, additional, Li, Yaoguo, additional, Wagner, Sean, additional, Crook, Nigel, additional, Cubbage, Brian, additional, Rucker, Dale, additional, Anand, Vivek, additional, Hein, Annette, additional, Larsen, Jakob Juul, additional, Dlugosch, Raphael, additional, Müller-Petke, Mike, additional, Kirkland, Catherine, additional, Phillips, Adrienne, additional, Grunewald, Elliot, additional, Walsh, David, additional, Codd, Sarah, additional, Irons, Trevor, additional, Heath, Jason, additional, McPherson, Brian, additional, Ampomah, William, additional, Rose-Coss, Dylan, additional, Walsh, Dave, additional, Keating, Kristina, additional, Gazo, Nikolas, additional, Smith, Richard, additional, Grombacher, Denys, additional, Chapa, E. Michael, additional, Obert, Arnd, additional, Fukushima, Eiichi, additional, Altobelli, Stephen, additional, Conradi, Mark, additional, Nedwed, Timothy, additional, Palandro, David, additional, Thomann, Hans, additional, Sowko, Nicholas, additional, Song, Seo Young, additional, Jang, Hangilro, additional, Kim, Bitnarae, additional, Nam, Myung Jin, additional, Vales, David, additional, Kozlowski, Andres, additional, Bird, Brian, additional, Keller, Austin, additional, Milinic, Bojan, additional, Moriarty, Sarah, additional, Richardson, Ashley, additional, Sherrod, Laura, additional, Jang, Hannuree, additional, Avci, Emine, additional, Yuksel, Fethi Ahmet, additional, Avci, Kerim, additional, Gorucu, Mahmut Ziya, additional, Donmez, Sevket, additional, Sabunis, Kivanc, additional, Saito, Hirotaka, additional, Iwasaki, Toshiki, additional, Tobe, Yukio, additional, Nagai, Nobuhito, additional, James, Stephanie, additional, Screaton, Elizabeth, additional, Russo, Raymond, additional, Panning, Mark, additional, Alamooti, Moones, additional, Aydin, Adnan, additional, Domenzain, Diego, additional, Mead, Jodie, additional, Vignoli, Giulio, additional, Jørgensen, Flemming, additional, Zaremba, Nicholas, additional, Smith, Christopher, additional, Nelson, Paul, additional, and Newlander, Khori, additional
Published: 2017
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41. Quantifying the influence of deep soil moisture on ecosystem albedo: The role of vegetation

Author: Sanchez-Mejia, Zulia Mayari, primary, Papuga, Shirley Anne, additional, Swetish, Jessica Blaine, additional, van Leeuwen, Willem Jan Dirk, additional, Szutu, Daphne, additional, and Hartfield, Kyle, additional
Published: 2014
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42. COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

Author: Bond‐Lamberty, Ben, Christianson, Danielle S., Malhotra, Avni, Pennington, Stephanie C., Sihi, Debjani, AghaKouchak, Amir, Anjileli, Hassan, Altaf Arain, M., Armesto, Juan J., Ashraf, Samaneh, Ataka, Mioko, Baldocchi, Dennis, Andrew Black, Thomas, Buchmann, Nina, Carbone, Mariah S., Chang, Shih‐Chieh, Crill, Patrick, Curtis, Peter S., Davidson, Eric A., Desai, Ankur R., Drake, John E., El‐Madany, Tarek S., Gavazzi, Michael, Görres, Carolyn‐Monika, Gough, Christopher M., Goulden, Michael, Gregg, Jillian, Gutiérrez Del Arroyo, Omar, He, Jin‐Sheng, Hirano, Takashi, Hopple, Anya, Hughes, Holly, Järveoja, Järvi, Jassal, Rachhpal, Jian, Jinshi, Kan, Haiming, Kaye, Jason, Kominami, Yuji, Liang, Naishen, Lipson, David, Macdonald, Catriona A., Maseyk, Kadmiel, Mathes, Kayla, Mauritz, Marguerite, Mayes, Melanie A., McNulty, Steve, Miao, Guofang, Migliavacca, Mirco, Miller, Scott, Miniat, Chelcy F., Nietz, Jennifer G., Nilsson, Mats B., Noormets, Asko, Norouzi, Hamidreza, O’Connell, Christine S., Osborne, Bruce, Oyonarte, Cecilio, Pang, Zhuo, Peichl, Matthias, Pendall, Elise, Perez‐Quezada, Jorge F., Phillips, Claire L., Phillips, Richard P., Raich, James W., Renchon, Alexandre A., Ruehr, Nadine K., Sánchez‐Cañete, Enrique P., Saunders, Matthew, Savage, Kathleen E., Schrumpf, Marion, Scott, Russell L., Seibt, Ulli, Silver, Whendee L., Sun, Wu, Szutu, Daphne, Takagi, Kentaro, Takagi, Masahiro, Teramoto, Munemasa, Tjoelker, Mark G., Trumbore, Susan, Ueyama, Masahito, Vargas, Rodrigo, Varner, Ruth K., Verfaillie, Joseph, Vogel, Christoph, Wang, Jinsong, Winston, Greg, Wood, Tana E., Wu, Juying, Wutzler, Thomas, Zeng, Jiye, Zha, Tianshan, Zhang, Quan, and Zou, Junliang
Subjects: 13. Climate action, 15. Life on land
Abstract: 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 CO$_{2}$ flux, commonly though imprecisely termed soil respiration (R$_{S}$), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency R$_{S}$ 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 R$_{S}$, 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.

43. COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

Author: Bond-Lamberty, Ben, Christianson, Danielle S., Malhotra, Avni, Pennington, Stephanie C., Sihi, Debjani, AghaKouchak, Amir, Anjileli, Hassan, Altaf Arain, Muhammad, Armesto, Juan J., Ashraf, Samaneh, Ataka, Mioko, Baldocchi, Dennis D., Andrew Black, Thomas, Buchmann, Nina, Carbone, Mariah S., Chang, Shihchieh, Crill, Patrick, Curtis, Peter S., Davidson, Eric A., Desai, Ankur R., Drake, John E., El-Madany, Tarek S., Gavazzi, Michael J., Görres, Carolyn M., Gough, Christopher, Goulden, Michael L., Gregg, Jillian W., Gutiérrez del Arroyo, Omar, He, Jin-Sheng, Hirano, Takashi, Hopple, Anya M., Hughes, Holly, Järveoja, Järvi, Jassal, Rachhpal, Jian, Jinshi, Kan, Haiming, Kaye, Jason P., Kominami, Yuji, Liang, Naishen, Lipson, David A., Macdonald, Catriona A., Maseyk, Kadmiel S., Mathes, Kayla C., Mauritz, Marguerite, Mayes, Melanie A., McNulty, Steven, Miao, Guofang, Migliavacca, Mirco, Miller, Scott D., Miniat, Chelcy F., Nietz, Jennifer, Nilsson, Mats, Noormets, Asko, Norouzi, Hamid, O’Connell, Christine S., Osborne, Bruce, Oyonarte, Cecilio, Pang, Zhuo, Peichl, Matthias, Pendall, Elise G., Perez-Quezada, Jorge F., Phillips, Claire L., Phillips, Richard P., Raich, James W., Renchon, Alexandre, Ruehr, Nadine K., Sánchez-Cañete, Enrique P., Saunders, Matthew, Savage, Kathleen, Schrumpf, Marion, Scott, Russell L., Seibt, Ulli, Silver, Whendee L., Sun, Wu, Szutu, Daphne J., Takagi, Kentaro, Takagi, Masahiro, Teramoto, Munemasa, Tjoelker, Mark G., Trumbore, Susan E., Ueyama, Masahito, Vargas, Rodrigo, Varner, Ruth K., Verfaillie, Joseph, Vogel, Christoph S., Wang, Jinsong, Winston, Gregory, Wood, Tana E., Wu, Juying, Wutzler, Thomas, Zeng, Jiye, Zha, Tianshan, Zhang, Quan, and Zou, Junliang
Subjects: 13. Climate action, methane, 11. Sustainability, greenhouse gases, open science, carbon dioxide, open data, 15. Life on land, soil respiration
Abstract: 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., Global Change Biology, 26 (12), ISSN:1354-1013, ISSN:1365-2486

44. FLUXNET-CH$_{4}$: a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands

Author: Delwiche, Kyle B., Knox, Sara Helen, Malhotra, Avni, Fluet-Chouinard, Etienne, McNicol, Gavin, Feron, Sarah, Ouyang, Zutao, Papale, Dario, Trotta, Carlo, Canfora, Eleonora, Cheah, You-Wei, Christianson, Danielle, Alberto, Ma. Carmelita R., Alekseychik, Pavel, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Billesbach, David P., Bohrer, Gil, Bracho, Rosvel, Buchmann, Nina, Campbell, David I., Celis, Gerardo, Chen, Jiquan, Chen, Weinan, Chu, Housen, Dalmagro, Higo J., Dengel, Sigrid, Desai, Ankur R., Detto, Matteo, Dolman, Han, Eichelmann, Elke, Euskirchen, Eugenie, Famulari, Daniela, Fuchs, Kathrin, Goeckede, Mathias, Gogo, S��bastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Graham, Scott L., Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Hollinger, David, H��rtnagl, Lukas, Iwata, Hiroki, Jacotot, Adrien, Jurasinski, Gerald, Kang, Minseok, Kasak, Kuno, King, John, Klatt, Janina, Koebsch, Franziska, Krauss, Ken W., Lai, Derrick Y. F., Lohila, Annalea, Mammarella, Ivan, Belelli Marchesini, Luca, Manca, Giovanni, Matthes, Jaclyn Hatala, Maximov, Trofim, Merbold, Lutz, Mitra, Bhaskar, Morin, Timothy H., Nemitz, Eiko, Nilsson, Mats B., Niu, Shuli, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Riley, William, Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sanchez, Camilo Rey, Schuur, Edward A., Sch��fer, Karina V. R., Sonnentag, Oliver, Sparks, Jed P., Stuart-Ha��ntjens, Ellen, Sturtevant, Cove, Sullivan, Ryan C., Szutu, Daphne J., Thom, Jonathan E., Torn, Margaret S., Tuittila, Eeva-Stiina, Turner, Jessica, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Varlagin, Andrej, Vazquez-Lule, Alma, Verfaillie, Joseph G., Vesala, Timo, Vourlitis, George L., Ward, Eric J., Wille, Christian, Wohlfahrt, Georg, Wong, Guan Xhuan, Zhang, Zhen, Zona, Donatella, Windham-Myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B.
Subjects: 13. Climate action, 15. Life on land, 6. Clean water
Abstract: Methane (CH$_{4}$) emissions from natural landscapes constitute roughly half of global CH$_{4}$ 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 CH$_{4}$ flux are ideal for constraining ecosystem-scale CH$_{4}$ emissions due to quasi-continuous and high-temporal-resolution CH$_{4}$ 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-CH$_{4}$ Version 1.0, the first open-source global dataset of CH$_{4}$ 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 CH$_{4}$ 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-CH$_{4}$ representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH$_{4}$ Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH$_{4}$ emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH$_{4}$ 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 CH$_{4}$ emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20�� S to 20�� N) the spring onset of elevated CH$_{4}$ emissions starts 3 d earlier, and the CH$_{4}$ emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH$_{4}$ emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH$_{4}$ emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH$_{4}$ emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH$_{4}$ emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH$_{4}$ modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH$_{4}$ peak). FLUXNET-CH$_{4}$ is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH$_{4}$ 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-CH$_{4}$ 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.

45. COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

Author: Bond‐Lamberty, Ben, Christianson, Danielle S., Malhotra, Avni, Pennington, Stephanie C., Sihi, Debjani, AghaKouchak, Amir, Anjileli, Hassan, Altaf Arain, M., Armesto, Juan J., Ashraf, Samaneh, Ataka, Mioko, Baldocchi, Dennis, Andrew Black, Thomas, Buchmann, Nina, Carbone, Mariah S., Chang, Shih‐Chieh, Crill, Patrick, Curtis, Peter S., Davidson, Eric A., Desai, Ankur R., Drake, John E., El‐Madany, Tarek S., Gavazzi, Michael, Görres, Carolyn‐Monika, Gough, Christopher M., Goulden, Michael, Gregg, Jillian, Gutiérrez del Arroyo, Omar, He, Jin‐Sheng, Hirano, Takashi, Hopple, Anya, Hughes, Holly, Järveoja, Järvi, Jassal, Rachhpal, Jian, Jinshi, Kan, Haiming, Kaye, Jason, Kominami, Yuji, Liang, Naishen, Lipson, David, Macdonald, Catriona A., Maseyk, Kadmiel, Mathes, Kayla, Mauritz, Marguerite, Mayes, Melanie A., McNulty, Steve, Miao, Guofang, Migliavacca, Mirco, Miller, Scott, Miniat, Chelcy F., Nietz, Jennifer G., Nilsson, Mats B., Noormets, Asko, Norouzi, Hamidreza, O’Connell, Christine S., Osborne, Bruce, Oyonarte, Cecilio, Pang, Zhuo, Peichl, Matthias, Pendall, Elise, Perez‐Quezada, Jorge F., Phillips, Claire L., Phillips, Richard P., Raich, James W., Renchon, Alexandre A., Ruehr, Nadine K., Sánchez‐Cañete, Enrique P., Saunders, Matthew, Savage, Kathleen E., Schrumpf, Marion, Scott, Russell L., Seibt, Ulli, Silver, Whendee L., Sun, Wu, Szutu, Daphne, Takagi, Kentaro, Takagi, Masahiro, Teramoto, Munemasa, Tjoelker, Mark G., Trumbore, Susan, Ueyama, Masahito, Vargas, Rodrigo, Varner, Ruth K., Verfaillie, Joseph, Vogel, Christoph, Wang, Jinsong, Winston, Greg, Wood, Tana E., Wu, Juying, Wutzler, Thomas, Zeng, Jiye, Zha, Tianshan, Zhang, Quan, Zou, Junliang, Bond‐Lamberty, Ben, Christianson, Danielle S., Malhotra, Avni, Pennington, Stephanie C., Sihi, Debjani, AghaKouchak, Amir, Anjileli, Hassan, Altaf Arain, M., Armesto, Juan J., Ashraf, Samaneh, Ataka, Mioko, Baldocchi, Dennis, Andrew Black, Thomas, Buchmann, Nina, Carbone, Mariah S., Chang, Shih‐Chieh, Crill, Patrick, Curtis, Peter S., Davidson, Eric A., Desai, Ankur R., Drake, John E., El‐Madany, Tarek S., Gavazzi, Michael, Görres, Carolyn‐Monika, Gough, Christopher M., Goulden, Michael, Gregg, Jillian, Gutiérrez del Arroyo, Omar, He, Jin‐Sheng, Hirano, Takashi, Hopple, Anya, Hughes, Holly, Järveoja, Järvi, Jassal, Rachhpal, Jian, Jinshi, Kan, Haiming, Kaye, Jason, Kominami, Yuji, Liang, Naishen, Lipson, David, Macdonald, Catriona A., Maseyk, Kadmiel, Mathes, Kayla, Mauritz, Marguerite, Mayes, Melanie A., McNulty, Steve, Miao, Guofang, Migliavacca, Mirco, Miller, Scott, Miniat, Chelcy F., Nietz, Jennifer G., Nilsson, Mats B., Noormets, Asko, Norouzi, Hamidreza, O’Connell, Christine S., Osborne, Bruce, Oyonarte, Cecilio, Pang, Zhuo, Peichl, Matthias, Pendall, Elise, Perez‐Quezada, Jorge F., Phillips, Claire L., Phillips, Richard P., Raich, James W., Renchon, Alexandre A., Ruehr, Nadine K., Sánchez‐Cañete, Enrique P., Saunders, Matthew, Savage, Kathleen E., Schrumpf, Marion, Scott, Russell L., Seibt, Ulli, Silver, Whendee L., Sun, Wu, Szutu, Daphne, Takagi, Kentaro, Takagi, Masahiro, Teramoto, Munemasa, Tjoelker, Mark G., Trumbore, Susan, Ueyama, Masahito, Vargas, Rodrigo, Varner, Ruth K., Verfaillie, Joseph, Vogel, Christoph, Wang, Jinsong, Winston, Greg, Wood, Tana E., Wu, Juying, Wutzler, Thomas, Zeng, Jiye, Zha, Tianshan, Zhang, Quan, and Zou, Junliang
Abstract: 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.

46. COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

Author: Bond‐Lamberty, Ben, Christianson, Danielle S., Malhotra, Avni, Pennington, Stephanie C., Sihi, Debjani, AghaKouchak, Amir, Anjileli, Hassan, Altaf Arain, M., Armesto, Juan J., Ashraf, Samaneh, Ataka, Mioko, Baldocchi, Dennis, Andrew Black, Thomas, Buchmann, Nina, Carbone, Mariah S., Chang, Shih‐Chieh, Crill, Patrick, Curtis, Peter S., Davidson, Eric A., Desai, Ankur R., Drake, John E., El‐Madany, Tarek S., Gavazzi, Michael, Görres, Carolyn‐Monika, Gough, Christopher M., Goulden, Michael, Gregg, Jillian, Gutiérrez del Arroyo, Omar, He, Jin‐Sheng, Hirano, Takashi, Hopple, Anya, Hughes, Holly, Järveoja, Järvi, Jassal, Rachhpal, Jian, Jinshi, Kan, Haiming, Kaye, Jason, Kominami, Yuji, Liang, Naishen, Lipson, David, Macdonald, Catriona A., Maseyk, Kadmiel, Mathes, Kayla, Mauritz, Marguerite, Mayes, Melanie A., McNulty, Steve, Miao, Guofang, Migliavacca, Mirco, Miller, Scott, Miniat, Chelcy F., Nietz, Jennifer G., Nilsson, Mats B., Noormets, Asko, Norouzi, Hamidreza, O’Connell, Christine S., Osborne, Bruce, Oyonarte, Cecilio, Pang, Zhuo, Peichl, Matthias, Pendall, Elise, Perez‐Quezada, Jorge F., Phillips, Claire L., Phillips, Richard P., Raich, James W., Renchon, Alexandre A., Ruehr, Nadine K., Sánchez‐Cañete, Enrique P., Saunders, Matthew, Savage, Kathleen E., Schrumpf, Marion, Scott, Russell L., Seibt, Ulli, Silver, Whendee L., Sun, Wu, Szutu, Daphne, Takagi, Kentaro, Takagi, Masahiro, Teramoto, Munemasa, Tjoelker, Mark G., Trumbore, Susan, Ueyama, Masahito, Vargas, Rodrigo, Varner, Ruth K., Verfaillie, Joseph, Vogel, Christoph, Wang, Jinsong, Winston, Greg, Wood, Tana E., Wu, Juying, Wutzler, Thomas, Zeng, Jiye, Zha, Tianshan, Zhang, Quan, Zou, Junliang, Bond‐Lamberty, Ben, Christianson, Danielle S., Malhotra, Avni, Pennington, Stephanie C., Sihi, Debjani, AghaKouchak, Amir, Anjileli, Hassan, Altaf Arain, M., Armesto, Juan J., Ashraf, Samaneh, Ataka, Mioko, Baldocchi, Dennis, Andrew Black, Thomas, Buchmann, Nina, Carbone, Mariah S., Chang, Shih‐Chieh, Crill, Patrick, Curtis, Peter S., Davidson, Eric A., Desai, Ankur R., Drake, John E., El‐Madany, Tarek S., Gavazzi, Michael, Görres, Carolyn‐Monika, Gough, Christopher M., Goulden, Michael, Gregg, Jillian, Gutiérrez del Arroyo, Omar, He, Jin‐Sheng, Hirano, Takashi, Hopple, Anya, Hughes, Holly, Järveoja, Järvi, Jassal, Rachhpal, Jian, Jinshi, Kan, Haiming, Kaye, Jason, Kominami, Yuji, Liang, Naishen, Lipson, David, Macdonald, Catriona A., Maseyk, Kadmiel, Mathes, Kayla, Mauritz, Marguerite, Mayes, Melanie A., McNulty, Steve, Miao, Guofang, Migliavacca, Mirco, Miller, Scott, Miniat, Chelcy F., Nietz, Jennifer G., Nilsson, Mats B., Noormets, Asko, Norouzi, Hamidreza, O’Connell, Christine S., Osborne, Bruce, Oyonarte, Cecilio, Pang, Zhuo, Peichl, Matthias, Pendall, Elise, Perez‐Quezada, Jorge F., Phillips, Claire L., Phillips, Richard P., Raich, James W., Renchon, Alexandre A., Ruehr, Nadine K., Sánchez‐Cañete, Enrique P., Saunders, Matthew, Savage, Kathleen E., Schrumpf, Marion, Scott, Russell L., Seibt, Ulli, Silver, Whendee L., Sun, Wu, Szutu, Daphne, Takagi, Kentaro, Takagi, Masahiro, Teramoto, Munemasa, Tjoelker, Mark G., Trumbore, Susan, Ueyama, Masahito, Vargas, Rodrigo, Varner, Ruth K., Verfaillie, Joseph, Vogel, Christoph, Wang, Jinsong, Winston, Greg, Wood, Tana E., Wu, Juying, Wutzler, Thomas, Zeng, Jiye, Zha, Tianshan, Zhang, Quan, and Zou, Junliang
Abstract: 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.

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

Author: Kasak K, Espenberg M, Anthony TL, Tringe SG, Valach AC, Hemes KS, Silver WL, Mander Ü, Kill K, McNicol G, Szutu D, Verfaillie J, and Baldocchi DD
Subjects: Denitrification, Nitrogen, Nitrogen Cycle, Nitrous Oxide analysis, Soil, Soil Microbiology, Microbiota, Wetlands
Abstract: 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, 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., (Copyright © 2021 Elsevier Ltd. All rights reserved.)
Published: 2021
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