In order to quantify C transport and emission and main environmental factors controlling the C cycle in Siberian rivers, we investigated the largest tributary of the Ob River, the Ket River basin, by measuring spatial and seasonal variations in carbon CO2 and CH4 concentrations and emissions together with hydrochemical analyses. The obtained results are useful for large-scale modeling of C emission and export fluxes from permafrost-free boreal rivers of an underrepresented region of the world.
In order to quantify riverine carbon (C) exchange with the atmosphere in permafrost regions, we report a first assessment of CO2 and CH4 concentration and fluxes of the largest permafrost-affected river, the Lena River, during the peak of spring flow. The results allowed identification of environmental factors controlling GHG concentrations and emission in the Lena River watershed; this new knowledge can be used for foreseeing future changes in C balance in permafrost-affected Arctic rivers.
Maurizio Santoro, Oliver Cartus, Nuno Carvalhais, Danaë M. A. Rozendaal, Valerio Avitabile, Arnan Araza, Sytze de Bruin, Martin Herold, Shaun Quegan, Pedro Rodríguez-Veiga, Heiko Balzter, João Carreiras, Dmitry Schepaschenko, Mikhail Korets, Masanobu Shimada, Takuya Itoh, Álvaro Moreno Martínez, Jura Cavlovic, Roberto Cazzolla Gatti, Polyanna da Conceição Bispo, Nasheta Dewnath, Nicolas Labrière, Jingjing Liang, Jeremy Lindsell, Edward T. A. Mitchard, Alexandra Morel, Ana Maria Pacheco Pascagaza, Casey M. Ryan, Ferry Slik, Gaia Vaglio Laurin, Hans Verbeeck, Arief Wijaya, and Simon Willcock
Forests play a crucial role in Earth’s carbon cycle. To understand the carbon cycle better, we generated a global dataset of forest above-ground biomass, i.e. carbon stocks, from satellite data of 2010. This dataset provides a comprehensive and detailed portrait of the distribution of carbon in forests, although for dense forests in the tropics values are somewhat underestimated. This dataset will have a considerable impact on climate, carbon, and socio-economic modelling schemes.