Modelling past, present and future peatland carbon accumulation across the pan-Arctic region

• Published in: Biogeosciences
• Main Authors: Chaudhary, Nitin, Miller, Paul A., Smith, Benjamin
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus GmbH 2017
• Subjects: Climate Research; Geosciences; Multidisciplinary; Arctic; Climate change; permafrost; Alaska; Siberia
• Online Access: https://lup.lub.lu.se/record/d821c649-5b6d-488c-9717-030e5cfaba8c; https://doi.org/10.5194/bg-14-4023-2017

Most northern peatlands developed during the Holocene, sequestering large amounts of carbon in terrestrial ecosystems. However, recent syntheses have highlighted the gaps in our understanding of peatland carbon accumulation. Assessments of the long-Term carbon accumulation rate and possible warming-driven changes in these accumulation rates can therefore benefit from process-based modelling studies. We employed an individual-based dynamic global ecosystem model with dynamic peatland and permafrost functionalities and patch-based vegetation dynamics to quantify long-Term carbon accumulation rates and to assess the effects of historical and projected climate change on peatland carbon balances across the pan-Arctic region. Our results are broadly consistent with published regional and global carbon accumulation estimates. A majority of modelled peatland sites in Scandinavia, Europe, Russia and central and eastern Canada change from carbon sinks through the Holocene to potential carbon sources in the coming century. In contrast, the carbon sink capacity of modelled sites in Siberia, far eastern Russia, Alaska and western and northern Canada was predicted to increase in the coming century. The greatest changes were evident in eastern Siberia, north-western Canada and in Alaska, where peat production hampered by permafrost and low productivity due the cold climate in these regions in the past was simulated to increase greatly due to warming, a wetter climate and higher CO2 levels by the year 2100. In contrast, our model predicts that sites that are expected to experience reduced precipitation rates and are currently permafrost free will lose more carbon in the future.