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AbstractThe recent rise in atmospheric methane (CH4) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom‐up (BU) process‐based biogeochemical models and top‐down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi‐model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH4 emission estimates and model performance. We find that using better‐performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU‐ and TD‐based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year−1) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter‐site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site‐specific and ecosystem‐specific variabilities inferred from observations.

The contribution of particular hydrogen bonds to the stability of a protein fold can be investigated experimentally as well as computationally by the construction of protein mutants which lack particular hydrogen-bond donors or acceptors with a subsequent determination of their structural stability. However, the comparison of experimental data with computational results is not straightforward. One of the difficulties is related to the representation of the unfolded state conformation.A series of molecular dynamics simulations of the 34-residue WW domain of protein Pin1 and 20 amide-to-ester mutants started from the X-ray crystal structure and the NMR solution structure are analysed in terms of backbone-backbone hydrogen bonding and differences in free enthalpies of folding in order to provide a structural interpretation of the experimental data available.The contribution of the different β-sheet hydrogen bonds to the relative stability of the mutants with respect to wild type cannot be directly inferred from experimental thermal denaturation temperatures or free enthalpies of chaotrope denaturation for the different mutants, because some β-sheet hydrogen bonds show sizeable variation in occurrence between the different mutants.A proper representation of unfolded state conformations appears to be essential for an adequate description of relative stabilities of protein mutants.The simulations may be used to link the structural Boltzmann ensembles to relative free enthalpies of folding between mutants and wild-type protein and show that unfolded conformations have to be treated with a sufficient level of detail in free energy calculations of protein stability. This article is part of a Special Issue entitled Recent developments of molecular dynamics.