Potential CO2 emissions from defrosting permafrost soils of the Qinghai-Tibet Plateau under different scenarios of climate change in 2050 and 2070

摘要

Permafrost soils store enormous quantities of organic carbon. Especially on the alpine Qinghai-Tibet Plateau, global warming induces strong permafrost thawing, which strengthens the microbial decomposition of organic carbon and the emission of the greenhouse gas carbon dioxide (CO2). Enhanced respiration rates may intensify climate warming in turn, but the magnitude of future CO2 emissions from this data-scarce region in a changing climate remains highly uncertain. Here, we aim at an area-wide estimation of future potential CO2 emissions for the permafrost region on the Qinghai-Tibet Plateau as key region for climate change studies due to its size and sensitiveness. We calculated four potential soil respiration scenarios for 2050 and 2070 each. Using a regression model, results from laboratory experiments and C stock estimations from other studies, we provide an approximation of total potential soil CO2 emissions on a regional scale ranging from 737.90 g CO2 m(-2) 4224.77 g CO2 m(-2) y(-1). Our calculations as first estimate of thawing-induced CO2 emissions (5123 g CO2 m(-2) y(-1)-3002.82 g CO2 m(2) y(-1)) from permafrost soils of the Qinghai-Tibet Plateau under global warming appear to be consistent to measurements of C loss from thawing permafrost soils measured within other studies. Thawing-induced soil CO2 emissions from permafrost soils with a organic C content ranging from 2.42 g degrees C kg(-1) to 425.23 g C kg(-1) increase general soil respiration by at least about one third on average at a temperature of 5 degrees C. Differences between scenarios remain 1% and thawing-induced CO2 emissions generally decrease over time comparing 2015, 2050 and 2070. With this spatial approximation at a regional scale, a first area-wide estimate of potential CO2 emissions for 2050 and 2070 from permafrost soils of the Qinghai-Tibet Plateau is provided. This offers support of assessing potential area-specific greenhouse gas emissions and more differentiated climate change models. (C) 2016 Elsevier B.V. All rights reserved.