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Tropical Peatlands and the Carbon Cycle

Periodic Reporting for period 1 - TroPeaCC (Tropical Peatlands and the Carbon Cycle)

Reporting period: 2021-02-01 to 2022-07-31

Tropical peatlands are the most carbon-dense ecosystems in the world and they store the equivalent of ~10 years of global anthropogenic CO2 emissions. Despite their importance, crucial questions remain about carbon cycling in tropical peatlands and improving understanding is critical as they are at high risk from climate change and drainage for oil palm cultivation.
TroPeaCC will provide a step-change gain in our understanding of tropical peatland functioning and in projecting their response to climate change.
PI Gallego-Sala will use her unique background that bridges peatland modelling and observations to deliver a novel interdisciplinary approach to tackle four outstanding questions about tropical peatlands:
Q1: What controls the geographical distribution of peatlands in the tropics? TASK1: To assess the tropical peatland extent using a combination of models
Q2: How large is the tropical peatland CO2 sink and what are its main climatic drivers? TASK2: To characterize the drivers of carbon accumulation rates in tropical peatlands using the palaeo-archive.
Q3: How large is the methane flux in tropical peatlands? What are the main controls at the intercontinental scale? TASK3: To determine the main controls on methane fluxes in tropical peatlands, using eddy covariance, chamber-based gas flux measurements, and ground penetrating radar.
Q4: What is the overall carbon balance of tropical peatlands and how will this change in the future? TASK4: To forecast future changes of the extent of tropical peatlands, of the carbon sink and of methane emissions, using the results of Tasks 1-3 to parameterise and evaluate a global dynamic vegetation model that includes tropical peatlands for the first time.
The interdisciplinary approach will lead to a comprehensive understanding of the role of tropical peatlands in the global carbon cycle, allowing their inclusion in earth system models, and informing management decisions to optimise provision of multiple ecosystem services.