Abstract
Wetland methane (CH4) emissions ({F}_{{{CH}}_{4}}) are important in global carbon budgets and climate change assessments. Currently, {F}_{{{CH}}_{4}} projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent {F}_{{{CH}}_{4}} temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that {F}_{{{CH}}_{4}} are often controlled by factors beyond temperature. Here, we evaluate the relationship between {F}_{{{CH}}_{4}} and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between {F}_{{{CH}}_{4}} and temperature, suggesting larger {F}_{{{CH}}_{4}} sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.
Highlights
Wetland methane (CH4) emissions (FCH4 ) are important in global carbon budgets and climate change assessments
We show that consistent intra-seasonal changes in emergent dependencies of FCH4 were derived with Tair and the global FLUXNET-CH4 and soil (Tsoil) measurements at the sites where both measurements were available
As an example of seasonal hysteresis, we examined daily estimates obtained from measurements taken at the Bibai Mire in Northern
Summary
A case study of positive seasonal CH4 emission hysteresis. As an example of seasonal hysteresis, we examined daily estimates obtained from measurements taken at the Bibai Mire in Northern. In terms of the magnitude of seasonal FCH4 hysteresis, intra-seasonal changes in emergent FCH4 -Tair dependence vary substantially among site-years within each ecosystem type (Fig. 3), despite being predominantly positive (Fig. 2). Results derived from our random-forest model confirm the importance of ecosystem-site variability in regulating ahys and thereby FCH4 predicted by the hybrid model in each part of the frost-free season (Supplemental Fig. 16). -Tair FCH4 dependence (i.e., the top that row in Fig. 4a), the resulting FCH4 predictions substantially underestimate the range of FCH4 measured across wetland and rice paddy sites (Fig. 5a) This generic Tair sensitivity of FCH4 flattens the high temporal and spatial variability[10,11] that strongly controls the timing and magnitude of FCH4 , reinforcing the need. Such efforts are imperative because the FCH4 prediction error can increase substantially with increased FCH4 , especially for the relatively simple parameterization that only represents a generic Tair sensitivity of FCH4 (Fig. 5c)
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