127 citations as recorded by crossref.

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33. Effects of temperature and pH on archaeal membrane lipid distributions in freshwater wetlands J. Blewett et al. 10.1016/j.orggeochem.2020.104080
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56. Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems X. Xu et al. 10.5194/bg-13-3735-2016
57. Genome-centric view of carbon processing in thawing permafrost B. Woodcroft et al. 10.1038/s41586-018-0338-1
58. Challenges Regionalizing Methane Emissions Using Aquatic Environments in the Amazon Basin as Examples J. Melack et al. 10.3389/fenvs.2022.866082
59. Ensemble estimates of global wetland methane emissions over 2000–2020 Z. Zhang et al. 10.5194/bg-22-305-2025
60. 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
61. 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
62. Surface water inundation in the boreal-Arctic: potential impacts on regional methane emissions J. Watts et al. 10.1088/1748-9326/9/7/075001
63. Evaluation of wetland methane emissions across North America using atmospheric data and inverse modeling S. Miller et al. 10.5194/bg-13-1329-2016
64. The Global Methane Budget 2000–2017 M. Saunois et al. 10.5194/essd-12-1561-2020
65. Spatiotemporal Assessment of GHG Emissions and Nutrient Sequestration Linked to Agronutrient Runoff in Global Wetlands C. Pasut et al. 10.1029/2020GB006816
66. Simulated Hydrological Dynamics and Coupled Iron Redox Cycling Impact Methane Production in an Arctic Soil B. Sulman et al. 10.1029/2021JG006662
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68. Modeling strategies and data needs for representing coastal wetland vegetation in land surface models S. LaFond‐Hudson & B. Sulman 10.1111/nph.18760
69. Detecting, Extracting, and Monitoring Surface Water From Space Using Optical Sensors: A Review C. Huang et al. 10.1029/2018RG000598
70. Humid Subtropical Forests Constitute a Net Methane Source: A Catchment‐Scale Study L. Yu et al. 10.1029/2019JG005210
71. Causality guided machine learning model on wetland CH4 emissions across global wetlands K. Yuan et al. 10.1016/j.agrformet.2022.109115
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74. 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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76. Disentangling methane and carbon dioxide sources and transport across the Russian Arctic from aircraft measurements C. Narbaud et al. 10.5194/acp-23-2293-2023
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81. Inverse modelling of European CH4 emissions during 2006–2012 using different inverse models and reassessed atmospheric observations P. Bergamaschi et al. 10.5194/acp-18-901-2018
82. Multi-source global wetland maps combining surface water imagery and groundwater constraints A. Tootchi et al. 10.5194/essd-11-189-2019
83. 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
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87. The Importance of Spatial Resolution in the Modeling of Methane Emissions from Natural Wetlands Y. Albuhaisi et al. 10.3390/rs15112840
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96. The Characteristics of Soil Microbial Community Structure, Soil Microbial Respiration and their Influencing Factors of Three Vegetation Types in Alpine Wetland Ecosystem Y. Wang et al. 10.1007/s13157-024-01862-z
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