Simulating carbon accumulation and loss in the central Congo peatlands.

Peatlands of the central Congo Basin have accumulated carbon over millennia. They currently store some 29 billion tonnes of carbon in peat. However, our understanding of the controls on peat carbon accumulation and loss and the vulnerability of this stored carbon to climate change is in its infancy. Here we present a new model of tropical peatland development, DigiBog_Congo, that we use to simulate peat carbon accumulation and loss in a rain-fed interfluvial peatland that began forming ~20,000 calendar years Before Present (cal. yr BP, where 'present' is 1950 CE). Overall, the simulated age-depth curve is in good agreement with palaeoenvironmental reconstructions derived from a peat core at the same location as our model simulation. We find two key controls on long-term peat accumulation: water at the peat surface (surface wetness) and the very slow anoxic decay of recalcitrant material. Our main simulation shows that between the Late Glacial and early Holocene there were several multidecadal periods where net peat and carbon gain alternated with net loss. Later, a climatic dry phase beginning ~5200 cal. yr BP caused the peatland to become a long-term carbon source from ~3975 to 900 cal. yr BP. Peat as old as ~7000 cal. yr BP was decomposed before the peatland's surface became wetter again, suggesting that changes in rainfall alone were sufficient to cause a catastrophic loss of peat carbon lasting thousands of years. During this time, 6.4 m of the column of peat was lost, resulting in 57% of the simulated carbon stock being released. Our study provides an approach to understanding the future impact of climate change and potential land-use change on this vulnerable store of carbon.

Hydroclimatic vulnerability of peat carbon in the central Congo Basin.

The forested swamps of the central Congo Basin store approximately 30 billion metric tonnes of carbon in peat1,2. Little is known about the vulnerability of these carbon stocks. Here we investigate this vulnerability using peat cores from a large interfluvial basin in the Republic of the Congo and palaeoenvironmental methods. We find that peat accumulation began at least at 17,500 calibrated years before present (cal. yr BP; taken as AD 1950). Our data show that the peat that accumulated between around 7,500 to around 2,000 cal. yr BP is much more decomposed compared with older and younger peat. Hydrogen isotopes of plant waxes indicate a drying trend, starting at approximately 5,000 cal. yr BP and culminating at approximately 2,000 cal. yr BP, coeval with a decline in dominant swamp forest taxa. The data imply that the drying climate probably resulted in a regional drop in the water table, which triggered peat decomposition, including the loss of peat carbon accumulated prior to the onset of the drier conditions. After approximately 2,000 cal. yr BP, our data show that the drying trend ceased, hydrologic conditions stabilized and peat accumulation resumed. This reversible accumulation-loss-accumulation pattern is consistent with other peat cores across the region, indicating that the carbon stocks of the central Congo peatlands may lie close to a climatically driven drought threshold. Further research should quantify the combination of peatland threshold behaviour and droughts driven by anthropogenic carbon emissions that may trigger this positive carbon cycle feedback in the Earth system.

A cautionary tale about using the apparent carbon accumulation rate (aCAR) obtained from peat cores.

The carbon (C) accumulation histories of peatlands are of great interest to scientists, land users and policy makers. Because peatlands contain more than 500 billion tonnes of C, an understanding of the fate of this dynamic store, when subjected to the pressures of land use or climate change, is an important part of climate-change mitigation strategies. Information from peat cores is often used to recreate a peatland's C accumulation history from recent decades to past millennia, so that comparisons between past and current rates can be made. However, these present day observations of peatlands' past C accumulation rates (known as the apparent rate of C accumulation - aCAR) are usually different from the actual uptake or loss of C that occurred at the time (the true C balance). Here we use a simple peatland model and a more detailed ecosystem model to illustrate why aCAR should not be used to compare past and current C accumulation rates. Instead, we propose that data from peat cores are used with existing or new C balance models to produce reliable estimates of how peatland C function has changed over time.

Misinterpreting carbon accumulation rates in records from near-surface peat.

Peatlands are globally important stores of carbon (C) that contain a record of how their rates of C accumulation have changed over time. Recently, near-surface peat has been used to assess the effect of current land use practices on C accumulation rates in peatlands. However, the notion that accumulation rates in recently formed peat can be compared to those from older, deeper, peat is mistaken - continued decomposition means that the majority of newly added material will not become part of the long-term C store. Palaeoecologists have known for some time that high apparent C accumulation rates in recently formed peat are an artefact and take steps to account for it. Here we show, using a model, how the artefact arises. We also demonstrate that increased C accumulation rates in near-surface peat cannot be used to infer that a peatland as a whole is accumulating more C - in fact the reverse can be true because deep peat can be modified by events hundreds of years after it was formed. Our findings highlight that care is needed when evaluating recent C addition to peatlands especially because these interpretations could be wrongly used to inform land use policy and decisions.

Spatial models with covariates improve estimates of peat depth in blanket peatlands.

Peatlands are spatially heterogeneous ecosystems that develop due to a complex set of autogenic physical and biogeochemical processes and allogenic factors such as the climate and topography. They are significant stocks of global soil carbon, and therefore predicting the depth of peatlands is an important part of establishing an accurate assessment of their magnitude. Yet there have been few attempts to account for both internal and external processes when predicting the depth of peatlands. Using blanket peatlands in Great Britain as a case study, we compare a linear and geostatistical (spatial) model and several sets of covariates applicable for peatlands around the world that have developed over hilly or undulating terrain. We hypothesized that the spatial model would act as a proxy for the autogenic processes in peatlands that can mediate the accumulation of peat on plateaus or shallow slopes. Our findings show that the spatial model performs better than the linear model in all cases-root mean square errors (RMSE) are lower, and 95% prediction intervals are narrower. In support of our hypothesis, the spatial model also better predicts the deeper areas of peat, and we show that its predictive performance in areas of deep peat is dependent on depth observations being spatially autocorrelated. Where they are not, the spatial model performs only slightly better than the linear model. As a result, we recommend that practitioners carrying out depth surveys fully account for the variation of topographic features in prediction locations, and that sampling approach adopted enables observations to be spatially autocorrelated.