Partitioning NEE from peatland vegetation into autotrophic and heterotrophic components

In ecosystems on organic soils such as peatlands and managed grasslands on peat, understanding the dynamics and controls of peat decomposition in drained soils or accumulation in wetlands is currently a topic of great interest because of their potential contribution to large CO₂ emissions or sustained carbon storage. Net ecosystem carbon exchange fluxes (NEE) measured in such ecosystems are a combination of autotrophic processes, photosynthesis and respiration, in living plant material and heterotrophic respiration from all other organisms including those feeding on decomposing peat. Direct flux measurements from eddy covariance or chambers, however, are unable to distinguish the two co-occurring respiration components.

In this study we assess two approaches to partition measured NEE of peatland ecosystems into respiration components and estimate peat decomposition rates. The traditional approach is to use the assumption that annual heterotrophic respiration equals the difference between NEE and NPP. In managed grasslands on peat soils this implies that annual NEE corrected for harvest removal and manure application represents the annual peat oxidation. The alternative proposed here is based on data at shorter time scales, making use of the information contained in day-to-day variability in fluxes and vegetation activity. We explore the use of correlations between night-time NEE and daily GPP as well as observed changes in NEE following abrupt vegetation changes and management events.

Using multiple site-years of daily NEE measured over a range of managed and natural peatlands in The Netherlands we show that information contained in intra-annual variability carries sufficient information to derive a signal that comes close to heterotrophic respiration and peat decomposition-related carbon loss. The proposed partitioning could be used to understand in more detail the processes responsible for peat decomposition and apply such understanding in emission mitigation management.