Large carbon cycle sensitivities to climate across a permafrost thaw gradient in subarctic Sweden

Abstract

Abstract. Permafrost peatlands store large amounts of carbon potentially vulnerable to decomposition. However, the fate of that carbon in a changing climate remains uncertain in models due to complex interactions among hydrological, biogeochemical, microbial, and plant processes. In this study, we estimated effects of climate forcing biases present in global climate reanalysis products on carbon cycle predictions at a thawing permafrost peatland in subarctic Sweden. The analysis was conducted with a comprehensive biogeochemical model (ecosys) across a permafrost thaw gradient encompassing intact permafrost palsa with an ice core and a shallow active layer, partly thawed bog with a deeper active layer and a variable water table, and fen with a water table close to the surface, each with distinct vegetation and microbiota. Using in situ observations to correct local cold and wet biases found in the Global Soil Wetness Project Phase 3 (GSWP3) climate reanalysis forcing, we demonstrate good model performance by comparing predicted and observed carbon dioxide (CO2) and methane (CH4) exchanges, thaw depth, and water table depth. The simulations driven by the bias-corrected climate suggest that the three peatland types currently accumulate carbon from the atmosphere, although the bog and fen sites can have annual positive radiative forcing impacts due to their higher CH4 emissions. Our simulations indicate that projected precipitation increases could accelerate CH4 emissions from the palsa area, even without further degradation of palsa permafrost. The GSWP3 cold and wet biases for this site significantly alter simulation results and lead to erroneous active layer depth (ALD) and carbon budget estimates. Biases in simulated CO2 and CH4 exchanges from biased climate forcing are as large as those among the thaw stages themselves at a landscape scale across the examined permafrost thaw gradient. Future studies should thus not only focus on changes in carbon budget associated with morphological changes in thawing permafrost, but also recognize the effects of climate forcing uncertainty on carbon cycling.

Methane Production Pathway Regulated Proximally by Substrate Availability and Distally by Temperature in a High‐Latitude Mire Complex

“…Global Soil Wetness Project Phase 3 (GSWP3) is an ongoing modeling activity that provides global gridded meteorological forcing (0.5°× 0.5°resolution) and investigates changes in energy, water, and carbon cycles throughout the 20th and 21st centuries (Kim, 2017). The GSWP3 reanalysis dataset is based on the 20th Century Reanalysis (Compo et al, 2011), and its spatial and temporal resolutions are finer than many other existing climate reanalysis datasets (Chang et al, 2019). A more detailed description of the GSWP can be found in Dirmeyer (2011) and van den Hurk et al (2016).…”

“…In this study, we extracted the 3-hourly GSWP3 meteorological conditions at the Stordalen Mire from 1901 to 2013, and bias-corrected the time series using the monthly mean biases calculated in this period based on the correction method described in Chang et al (2019). Chang et al (2019). Three distinct habitats are present at the Mire: intact permafrost palsa with a shallow active layer, partly thawed bog with a deeper active layer and a variable water table, and fen with a water table near or above the peat surface.…”

“…However, estimated rates of permafrost soil carbon loss are strongly dependent on model physical and biological parameterizations that are currently very uncertain (McGuire et al, 2016. High-latitude carbon cycling is sensitive to ecosystem properties (e.g., soil moisture, soil temperature, water table position, permafrost thaw stage, microbial community, and vegetation composition), climate forcing (e.g., air temperature and precipitation), and their spatiotemporal variability (Chang et al, 2019;Malhotra & Roulet, 2015;McCalley et al, 2014;Olefeldt et al, 2013). In addition, the global radiative energy budget is sensitive to the form of permafrost soil carbon loss because the global warming potential of CH 4 is estimated to be 84 and 28 times stronger than that of CO 2 over 20 and 100 year periods, respectively (Myhre et al, 2013).…”

The IsoGenie database: an interdisciplinary data management solution for ecosystems biology and environmental research

“…1B). By integrating these myriad types of datasets, the project has characterized how thaw-induced changes in hydrology and vegetation (Malmer et al, 2005;Johansson et al, 2006;Bäckstrand et al, 2010;Palace et al, 2018) drive changes in organic matter (Hodgkins et al, 2014(Hodgkins et al, , 2016Wilson et al, 2017;Wilson & Tfaily, 2018) and microbial and viral communities (Mondav et al, 2014;Trubl et al, 2016Trubl et al, , 2018Trubl et al, , 2019Singleton et al, 2018;Emerson et al, 2018;Woodcroft et al, 2018;Martinez et al, 2019;Wilson et al, 2019;Roux et al, 2019), giving rise to changes in carbon gas emissions (Wik et al, 2013(Wik et al, , 2018Hodgkins et al, 2014Hodgkins et al, , 2015McCalley et al, 2014;Burke et al, 2019;Perryman et al, 2020), and collectively these insights are allowing improvements in predictive models (Deng et al, 2014(Deng et al, , 2017Chang et al, 2019aChang et al, , 2019bWilson et al, 2019).…”

“…The IsoGenieDB leverages the inherent relationships within the data (e.g., commonalities in sampling location or measurement technique) to build the basic structure of the database. In the IsoGenieDB, most of the nodes are organized hierarchically based on Ecosys model input data, code, and outputs X Chang et al (2019aChang et al ( , 2019b Notes:…”