Critical needs to close monitoring gaps in pan-tropical wetland CH 4 emissions

Global wetlands are the largest and most uncertain natural source of atmospheric methane (CH 4 ). The FLUXNET-CH 4 synthesis initiative has established a global network of flux tower infrastructure, offering valuable data products and fostering a dedicated community for the measurement and analysis of methane flux data. Existing studies using the FLUXNET-CH 4 Community Product v1.0 have provided invaluable insights into the drivers of ecosystem-to-regional spatial patterns and daily-to-decadal temporal dynamics in temperate, boreal, and Arctic climate regions. However, as the wetland CH 4 monitoring network grows, there is a critical knowledge gap about where new monitoring infrastructure ought to be located to improve understanding of the global wetland CH 4 budget. Here we address this gap with a spatial representativeness analysis at existing and hypothetical observation sites, using 16 process-based wetland biogeochemistry models and machine learning. We find that, in addition to eddy covariance monitoring sites, existing chamber sites are important complements, especially over high latitudes and the tropics. Furthermore, expanding the current monitoring network for wetland CH 4 emissions should prioritize, first, tropical and second, sub-tropical semi-arid wetland regions. Considering those new hypothetical wetland sites from tropical and semi-arid climate zones could significantly improve global estimates of wetland CH 4 emissions and reduce bias by 79% (from 76 to 16 TgCH 4 y −1 ), compared with using solely existing monitoring networks. Our study thus demonstrates an approach for long-term strategic expansion of flux observations

Arid · Biogeochemistry · Biome · Ecoregion · Ecosystem · Eddy covariance · FluxNet · Permafrost · Tropics · Wetland · Atmospheric and Environmental Gas Dynamics · Climate variability and models · Environmental Science · Science and Climate Studies · Ecology

• Advancements and opportunities to improve bottom–up estimates of global wetland methane emissions

  Open Access•Qing Zhu, Daniel J Jacob et al.•Environmental Research Letters•2025

  Añadir item

• The Global Methane Budget 2000–2017

  Open Access•Marielle Saunois, Ann R Stavert et al.•Earth System Science Data•2020

  Añadir item

• Machine learning models inaccurately predict current and future high-latitude C balances

  Open Access•Ian Shirley, Z A Mekonnen et al.•Environmental Research Letters•2022

  Añadir item