Thawing permafrost as a nitrogen fertiliser: implications for climate feedbacks

• Published in: Nitrogen
• Main Authors: Burke, Eleanor, Chadburn, Sarah, Huntingford, Chris
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI 2022
• Subjects: Agriculture and Soil Science; Meteorology and Climatology; Arctic; Jules; Climate change; permafrost
• Online Access: http://nora.nerc.ac.uk/id/eprint/532933/; https://nora.nerc.ac.uk/id/eprint/532933/1/N532933JA.pdf; https://doi.org/10.3390/nitrogen3020023

Studies for the northern high latitudes suggest that, in the near term, increased vegetation uptake may offset permafrost carbon losses, but over longer time periods, permafrost carbon decomposition causes a net loss of carbon. Here, we assess the impact of a coupled carbon and nitrogen cycle on the simulations of these carbon fluxes. We present results from JULES-IMOGEN—a global land surface model coupled to an intermediate complexity climate model with vertically resolved soil biogeochemistry. We quantify the impact of nitrogen fertilisation from thawing permafrost on the carbon cycle and compare it with the loss of permafrost carbon. Projections show that the additional fertilisation reduces the high latitude vegetation nitrogen limitation and causes an overall increase in vegetation carbon uptake. This is a few Petagrams of carbon (Pg C) by year 2100, increasing to up to 40 Pg C by year 2300 for the RCP8.5 concentration scenario and adds around 50% to the projected overall increase in vegetation carbon in that region. This nitrogen fertilisation results in a negative (stabilising) feedback on the global mean temperature, which could be equivalent in magnitude to the positive (destabilising) temperature feedback from the loss of permafrost carbon. This balance depends on the future scenario and initial permafrost carbon. JULES-IMOGEN describes one representation of the changes in Arctic carbon and nitrogen cycling in response to climate change. However there are uncertainties in the modelling framework, model parameterisation and missing processes which, when assessed, will provide a more complete picture of the balance between stabilising and destabilising feedbacks.