| 1. |
- Chang, Kuang Yu, et al.
(författare)
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Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates
- 2023
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Ingår i: Global Change Biology. - 1354-1013. ; 29:15, s. 4298-4312
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 2. |
- Fluet-Chouinard, Etienne, et al.
(författare)
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Extensive global wetland loss over the past three centuries
- 2023
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 614:7947, s. 281-286
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Tidskriftsartikel (refereegranskat)abstract
- Wetlands have long been drained for human use, thereby strongly affecting greenhouse gas fluxes, flood control, nutrient cycling and biodiversity1,2. Nevertheless, the global extent of natural wetland loss remains remarkably uncertain3. Here, we reconstruct the spatial distribution and timing of wetland loss through conversion to seven human land uses between 1700 and 2020, by combining national and subnational records of drainage and conversion with land-use maps and simulated wetland extents. We estimate that 3.4 million km2 (confidence interval 2.9–3.8) of inland wetlands have been lost since 1700, primarily for conversion to croplands. This net loss of 21% (confidence interval 16–23%) of global wetland area is lower than that suggested previously by extrapolations of data disproportionately from high-loss regions. Wetland loss has been concentrated in Europe, the United States and China, and rapidly expanded during the mid-twentieth century. Our reconstruction elucidates the timing and land-use drivers of global wetland losses, providing an improved historical baseline to guide assessment of wetland loss impact on Earth system processes, conservation planning to protect remaining wetlands and prioritization of sites for wetland restoration4.
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| 3. |
- Zhang, Zhen, et al.
(författare)
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Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET-CH4 Sites Using Wavelet Analyses
- 2023
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Ingår i: Journal of Geophysical Research: Biogeosciences. - 2169-8953. ; 128:11
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Tidskriftsartikel (refereegranskat)abstract
- Process-based land surface models are important tools for estimating global wetland methane (CH4) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH4 fluxes (FCH4) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15 days); (b) most of the models can capture the CH4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH4 production). Our evaluation suggests the need to accurately replicate FCH4 variability, especially at short time scales, in future wetland CH4 model developments.
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