An estimate of the terrestrial carbon budget of Russia using inventory-based, eddy covariance and inversion methods
- 1Department of Earth Sciences, Vrije Universiteit Amsterdam, Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands
- 2International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, 2361 Laxenburg, Austria
- 3IPSL – LSCE, CEA CNRS UVSQ, Centre d'Etudes Orme des Merisiers, 91191 Gif sur Yvette, France
- 4V. N. Sukachev Institute of Forest of SB RAS 660036, Krasnoyarsk, Russia, Akademgorodok, SIF SB RAS and Siberian Federal University, Krasnoyarsk, Russia
- 5Wageningen University, Department of Meteorology and Air Quality, Wageningen, The Netherlands
- 6Institute for Biological Problems of Cryolithozone Siberian Branch of RAS, 677980, 41, Lenina avenue, Yakutsk, Russia
- 7Center for Global Environmental Research, National Institute for Environmental Studies Onogawa 16-2, Tsukuba, Ibaraki 305-8506, Japan
- 8Max Planck Institute for Biogeochemistry, Jena, Germany
Abstract. We determine the net land to atmosphere flux of carbon in Russia, including Ukraine, Belarus and Kazakhstan, using inventory-based, eddy covariance, and inversion methods. Our high boundary estimate is −342 Tg C yr−1 from the eddy covariance method, and this is close to the upper bounds of the inventory-based Land Ecosystem Assessment and inverse models estimates. A lower boundary estimate is provided at −1350 Tg C yr−1 from the inversion models. The average of the three methods is −613.5 Tg C yr−1. The methane emission is estimated separately at 41.4 Tg C yr−1.
These three methods agree well within their respective error bounds. There is thus good consistency between bottom-up and top-down methods. The forests of Russia primarily cause the net atmosphere to land flux (−692 Tg C yr−1 from the LEA. It remains however remarkable that the three methods provide such close estimates (−615, −662, −554 Tg C yr–1) for net biome production (NBP), given the inherent uncertainties in all of the approaches. The lack of recent forest inventories, the few eddy covariance sites and associated uncertainty with upscaling and undersampling of concentrations for the inversions are among the prime causes of the uncertainty. The dynamic global vegetation models (DGVMs) suggest a much lower uptake at −91 Tg C yr−1, and we argue that this is caused by a high estimate of heterotrophic respiration compared to other methods.