Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions.
Kuang-Yu ChangWilliam J RileySara H KnoxRobert B JacksonGavin McNicolBenjamin PoulterMika AurelaDennis D BaldocchiSheel BansalGil BohrerDavid I CampbellAlessandro CescattiHousen ChuKyle B DelwicheAnkur R DesaiEugénie S EuskirchenThomas FriborgMathias GöckedeManuel HelbigKyle S HemesTakashi HiranoHiroki IwataMinseok KangTrevor F KeenanKen W KraussAnnalea K LohilaIvan MammarellaBhaskar MitraAkira MiyataMats B NilssonAsko NoormetsWalter C OechelDario PapaleMatthias PeichlMichele L RebaJanne RinneBenjamin R K RunkleYoungryel RyuTorsten SachsKarina V R SchäferHans Peter SchmidNarasinha J ShurpaliOliver SonnentagAngela C I TangMargaret S TornCarlo TrottaEeva Stiina TuittilaMasahito UeyamaRodrigo VargasTimo VesalaLisamarie Windham-MyersZhen ZhangDonatella ZonaPublished in: Nature communications (2021)
Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] 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.