The 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.

Significant and rapid changes in nutrient turnover and budget have occurred over the past century (Li & Bowman, 2001;Vitousek et al., 1997). Temperature, precipitation, soil weathering, microbial activity, and nutrient runoff control carbon (C), nitrogen (N), and sulfur (S) availability and their turnover rates in wetlands (Matias et al., 2011;Whitehead, 2000). However, these dynamics have largely been overlooked in global-scale assessments, even though wetlands contribute globally between 25% and 30% of CH 4 emissions

Wetlands represent the most significant natural greenhouse gas (GHG) source and their annual emissions tightly depend on climatic and anthropogenic factors. Biogeochemical processes occurring in wetlands are still poorly described by mechanistic models and hence their dynamic response to environmental changes are weakly predicted. We investigated wetland GHG emissions, relevant electron acceptors and donors concentrations, and microbial composition resulting from changes in temperature, CH 4 plant uptake efficiency, and SO 2− 4 deposition using a mechanistic biogeochemical model (here called BAMS3) that integrates the carbon (C), nitrogen (N), and sulfur (S) cycles. Parameters constraining the coupled C-N-S cycles were retrieved from controlled experiments and were validated against independent field data of CH 4 emissions, and CH 4 (aq) and SO 2− 4 concentration profiles in a wetland in southern Michigan, USA (Shannon & White, 1994, http://hdl.handle.net/102.100.100/236252? index=1). We found that +1.75 • C increase in temperature leads to 22% and 30% increment in CH 4 and N 2 O emissions, respectively. A decrease in the CH 4 plant uptake efficiency causes the prevalent CH 4 emission pathway to become diffusion mediated and resulted in 50% increase in the daily average CH 4 emissions. Finally, a decreasing SO 2− 4 deposition rate can increase CH 4 emissions up to 5%. We conclude that the increasing GHG emissions from wetlands is a result of both environmental and anthropogenic causes rather than global warming alone. An increase in model complexity does not necessary improve the estimation of GHG emissions but it aids interpretation of intermediate processes to a greater detail. Plain Language SummaryWetlands are the largest natural source of greenhouse gasses; hence, climate change and human development have become a major concern for the conservation of these ecosystems. In this study, we explore the effect of rising temperature, plants community, and changes in nutrient input rate on the emission rate and quality in a wetland. The assessment was conducted using a mechanistic model that accounts for carbon, nitrogen, and sulfur cycles on test scenarios. The model was initially tested on field data of a wetland in southern Michigan, and then used for scenarios predictions. Results suggest that increasing the average soil temperature leads to a substantial increase in greenhouse gas emissions; in particular, methane emissions increase by 22%. Methane emissions are also affected by the plant composition, which controls the main emission pathway; small composition changes can induce high emissions variations. Finally, we showed how a change in atmospheric sulfate deposition to wetlands can control the methane emissions. We conclude that modeling coupled chemical, biological, and physical processes helped to describe wetland nutrients dynamics under both climate change and anthropogenic factors.

Australian ecosystems, particularly wetlands, are facing new and extreme threats due to climate change, land use, and other human interventions. However, more fundamental knowledge is required to understand how nutrient turnover in wetlands is affected. In this study, we deployed a mechanistic biogeochemical model of carbon (C), nitrogen (N), and sulfur (S) cycles at 0.25∘× 0.25∘ spatial resolution across wetlands in Australia. Our modeling was used to assess nutrient inputs to soil, elemental nutrient fluxes across the soil organic and mineral pools, and greenhouse gas (GHG) emissions in different climatic areas. In the decade 2008–2017, we estimated an average annual emission of 5.12 Tg-CH4, 90.89 Tg-CO2, and 2.34 × 10−2 Tg-N2O. Temperate wetlands in Australia have three times more N2O emissions than tropical wetlands as a result of fertilization, despite similar total area extension. Tasmania wetlands have the highest areal GHG emission rates. C fluxes in soil depend strongly on hydroclimatic factors; they are mainly controlled by anaerobic respiration in temperate and tropical regions and by aerobic respiration in arid regions. In contrast, N and S fluxes are mostly governed by plant uptake regardless of the region and season. The new knowledge from this study may help design conservation and adaptation plans to climate change and better protect the Australian wetland ecosystem.