Modelling the impacts of land use change on carbon dynamics in tropical peatlands using the tropical holocene peat model (HPMTrop)

Tropical peatlands store approximately 14-19% of the world’s peat carbon, with estimates ranging from 50-90 GtC. Southeast Asia contains the largest proportion of tropical peatland with an estimated 56% of the tropical peatland area and 77% of the tropical peat C store. These peatlands have functioned as a globally significant carbon sink for millennia. However they are now being deforested, degraded and converted to other land uses at extremely high rates, switching their function from carbon sink to source. In addition, land use change causes losses of other critical ecosystem services, functions, and biodiversity. The carbon dynamics of tropical peatlands are largely under-studied compared to temperate and boreal peatlands. Comprehensive field studies are scarce, particularly at the ecological time scales required to assess process rates and long-term trends. Therefore, it is informative to use modelling approaches to ascertain long-term carbon dynamics beyond scales of practical observation. Here we use the Tropical Holocene Peat Model (HPMTrop) to assess the impact of land use change on carbon storage in a hypothetical tropical peat system over decadal time scales. HPMTrop is a processbased dynamic carbon model parameterized and calibrated from existing field data from Southeast Asia. We present peat carbon losses caused by typical trajectories of peatland conversion, and the potential rebalance of the carbon cycle and restored carbon sequestration under possible peatland rewetting and rehabilitation scenarios. Results indicate that although emissions from converted peatlands can be reduced, or even reversed, restoration of carbon stocks lost due to conversion is impossible at practical time scales; for example steady C accumulation over hundreds to thousands of years would be necessary to replenish carbon stocks lost over just one rotation of industrial oil palm cultivation, a dominant driver of land use change in the region