Opposing seasonal temperature dependencies of CO₂ and CH₄ emissions from wetlands

Abstract

Wetlands are critically important to global climate change because of their role in modulating the release of atmospheric greenhouse gases (GHGs) carbon dioxide (CO2) and methane (CH4). Temperature plays a crucial role in wetland GHG emissions, while the general pattern for seasonal temperature dependencies of wetland CO2 and CH4 emissions is poorly understood. Here we show opposite seasonal temperature dependencies of CO2 and CH4 emissions by using 36,663 daily observations of simultaneous measurements of ecosystem‐scale CO2 and CH4 emissions in 42 widely distributed wetlands from the FLUXNET‐CH4 database. Specifically, the temperature dependence of CO2 emissions decreased with increasing monthly mean temperature, but the opposite was true for that of CH4 emissions. Neglecting seasonal temperature dependencies may overestimate wetland CO2 and CH4 emissions compared to the use of a year‐based static and consistent temperature dependence parameter when only considering temperature effects. Our findings highlight the importance of incorporating the remarkable seasonality in temperature dependence into process‐based biogeochemical models to predict feedbacks of wetland GHG emissions to climate warming.

Including Methane Emissions from Agricultural Ponds in National Greenhouse Gas Inventories

“…Also, in the absence of data, E m was estimated using larger systems, such as lakes and reservoirs, as described in Malerba et al This approach is likely conservative for agricultural ponds. Freshwater systems of comparable sizes to agricultural ponds often record values around 1 eV, , whereas larger freshwater systems have lower values around 0.4–0.6. , Increasing the temperature sensitivity of our model would increase the total emissions. For example, increasing E m from 0.4 to 1 eV would increase our predicted methane emissions from agricultural ponds by 44% (from 41 to 59 kt CH 4 year –1 ).…”

“…Freshwater systems of comparable sizes to agricultural ponds often record values around 1 eV, 33 , 34 whereas larger freshwater systems have lower values around 0.4–0.6. 35 , 36 Increasing the temperature sensitivity of our model would increase the total emissions. For example, increasing E m from 0.4 to 1 eV would increase our predicted methane emissions from agricultural ponds by 44% (from 41 to 59 kt CH 4 year –1 ).…”

Significant Daily CO2 Source–Sink Interchange in an Urbanizing Lake in Southwest China

“…Moreover, the average daytime pCO 2 was 707 ± 642 µatm (n = 44), which was significantly elevated compared to typical atmospheric CO 2 levels (i.e., 380-420 µatm; [17,18,53]). This observation indicated that the biological productivity at a depth of 1.0 m exceeded the dissolution of water CO 2 , with the potential for CO 2 to be released into the atmosphere [10,54]. Thus, to some extent, it can be considered that this lake becomes a 'source' of CO 2 during the day.…”