122 citations as recorded by crossref.

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23. Methane emissions from global rice fields: Magnitude, spatiotemporal patterns, and environmental controls B. Zhang et al. 10.1002/2016GB005381
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47. Characteristics and effect factors of CH4 emissions in single-family treatment wetlands J. Hu et al. 10.1016/j.ecoleng.2022.106793
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53. Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications B. Ringeval et al. 10.5194/bg-11-1519-2014
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55. Genome-centric view of carbon processing in thawing permafrost B. Woodcroft et al. 10.1038/s41586-018-0338-1
56. Challenges Regionalizing Methane Emissions Using Aquatic Environments in the Amazon Basin as Examples J. Melack et al. 10.3389/fenvs.2022.866082
57. Simulated plant-mediated oxygen input has strong impacts on fine-scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands Y. Zhou et al. 10.1007/s10533-024-01145-z
58. A global‐scale analysis of water storage dynamics of inland wetlands: Quantifying the impacts of human water use and man‐made reservoirs as well as the unavoidable and avoidable impacts of climate change P. Döll et al. 10.1002/eco.2175
59. Surface water inundation in the boreal-Arctic: potential impacts on regional methane emissions J. Watts et al. 10.1088/1748-9326/9/7/075001
60. Evaluation of wetland methane emissions across North America using atmospheric data and inverse modeling S. Miller et al. 10.5194/bg-13-1329-2016
61. The Global Methane Budget 2000–2017 M. Saunois et al. 10.5194/essd-12-1561-2020
62. Spatiotemporal Assessment of GHG Emissions and Nutrient Sequestration Linked to Agronutrient Runoff in Global Wetlands C. Pasut et al. 10.1029/2020GB006816
63. Simulated Hydrological Dynamics and Coupled Iron Redox Cycling Impact Methane Production in an Arctic Soil B. Sulman et al. 10.1029/2021JG006662
64. An observation-constrained assessment of the climate sensitivity and future trajectories of wetland methane emissions E. Koffi et al. 10.1126/sciadv.aay4444
65. Modeling strategies and data needs for representing coastal wetland vegetation in land surface models S. LaFond‐Hudson & B. Sulman 10.1111/nph.18760
66. Detecting, Extracting, and Monitoring Surface Water From Space Using Optical Sensors: A Review C. Huang et al. 10.1029/2018RG000598
67. Humid Subtropical Forests Constitute a Net Methane Source: A Catchment‐Scale Study L. Yu et al. 10.1029/2019JG005210
68. Causality guided machine learning model on wetland CH4 emissions across global wetlands K. Yuan et al. 10.1016/j.agrformet.2022.109115
69. Adding stable carbon isotopes improves model representation of the role of microbial communities in peatland methane cycling J. Deng et al. 10.1002/2016MS000817
70. Extending a land-surface model with <i>Sphagnum</i> moss to simulate responses of a northern temperate bog to whole ecosystem warming and elevated CO<sub>2</sub> X. Shi et al. 10.5194/bg-18-467-2021
71. Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH4, and CO2 emissions T. Lippmann et al. 10.5194/gmd-16-6773-2023
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74. Greenhouse gas fluxes from Alaska's North Slope inferred from the Airborne Carbon Measurements campaign (ACME-V) J. Tadić et al. 10.1016/j.atmosenv.2021.118239
75. NGRIP CH<sub>4</sub> concentration from 120 to 10 kyr before present and its relation to a δ<sup>15</sup>N temperature reconstruction from the same ice core M. Baumgartner et al. 10.5194/cp-10-903-2014
76. DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands B. Stocker et al. 10.5194/gmd-7-3089-2014
77. The global methane budget 2000–2012 M. Saunois et al. 10.5194/essd-8-697-2016
78. Inverse modelling of European CH<sub>4</sub> emissions during 2006–2012 using different inverse models and reassessed atmospheric observations P. Bergamaschi et al. 10.5194/acp-18-901-2018
79. Multi-source global wetland maps combining surface water imagery and groundwater constraints A. Tootchi et al. 10.5194/essd-11-189-2019
80. Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands J. Irvin et al. 10.1016/j.agrformet.2021.108528
81. WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia T. Bohn et al. 10.5194/bg-12-3321-2015
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83. Estimating global natural wetland methane emissions using process modelling: spatio‐temporal patterns and contributions to atmospheric methane fluctuations Q. Zhu et al. 10.1111/geb.12307
84. The Importance of Spatial Resolution in the Modeling of Methane Emissions from Natural Wetlands Y. Albuhaisi et al. 10.3390/rs15112840
85. Stable atmospheric methane in the 2000s: key-role of emissions from natural wetlands I. Pison et al. 10.5194/acp-13-11609-2013
86. The impact of spatially varying wetland source signatures on the atmospheric variability ofδD-CH4 A. Stell et al. 10.1098/rsta.2020.0442
87. Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions S. Ma et al. 10.1029/2021AV000408
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108. Large-Scale Marsh Loss Reconstructed from Satellite Data in the Small Sanjiang Plain since 1965: Process, Pattern and Driving Force F. Yan 10.3390/s20041036
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