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Final Report Summary - PERCCOM (Permafrost Carbon Cycle Observations and Modeling across multiple spatiotemporal scales)

The motivation for the conducted research was rooted in the fact that the current state and future evolution of Arctic permafrost, particularly its interactions with the atmosphere, are among the largest uncertainties in our understanding of the Earth’s climate system. The Arctic is one of the most susceptible regions on Earth to climate change, and altered climate conditions may have enormous consequences for the sustainability of its natural environment. Interactions between permafrost, climate, hydrology, and ecology have the potential to cause dramatic changes, via mechanisms that are currently poorly monitored and therefore highly unpredictable.

The primary objective of the PerCCOM project was therefore to analyze the spatial and temporal variability of the surface-atmosphere exchange fluxes of carbon and energy in permafrost ecosystems across scales. Moreover, in combination with the assessment of ecosystem characteristics and changes therein, we targeted to identify the dominant control factors for these processes, and gain new insight into mechanisms that determine the current and future states of the Arctic carbon and energy cycles. To address these questions, new observational programs needed to be established to monitor permafrost ecosystems in Northeast Siberia, and results needed to be assimilated into bottom-up biogeochemical models as well as top-down atmospheric inverse modeling schemes.

Regarding the observational infrastructure, two new observation sites were established in the Chersky region in Northeastern Siberia within the context of the PerCCOM project. First, at the Ambolikha site (68.61°N, 161.34°E) that is situated on a floodplain of the Kolyma river approximately 15km south of Chersky, we installed a paired experiment focusing on the effects of long-term hydrological disturbance on ecosystem structure and carbon and energy budgets of a permafrost tussock tundra. Within a tundra patch that is drained since 2004 and a nearby undisturbed control area, we established eddy-covariance towers, soil chamber transects and small scale monitoring with soils and vegetation, and fluxes were monitored continuously starting summer 2013, continuing to date. At a second site, Ambarchik Bay (69.63°N, 162.30°E), which is situated approximately 100km North of Chersky at the Arctic Ocean coast, in summer 2014 we installed a tall tower to monitor well-calibrated atmospheric mixing ratios of CH4, CO2 and H2O. This facility allows observing air masses that carry information on regional to pan-Arctic biogeochemical processes, and therefore constrain large-scale budgets.

At the microscale (a few meters), we found very pronounced gradients in carbon and energy flux rates between microsites monitored through the soil chamber technique. Besides soil water status, also vegetation community structure and soil thermal regime were identified as the dominant influence factors that determine spatiotemporal variability in CH4, CO2 and energy flux rates. Continuous monitoring of surface-atmosphere exchange fluxes with eddy-covariance systems, which integrate over distances of several 100s of meters (mesoscale), revealed that long-term drainage turned this site from a moderate sink for CO2 carbon (uptake of ~50g CO2-C m-2 yr-1) to about carbon neutral, while CH4 emissions (control: ~7g CH4-C m-2 yr-1) was reduced to 50% after the disturbance. Energy fluxes showed a shift from latent towards sensible heat fluxes. All these shifts were the result of a drying out of shallow soil layers (down to 30cm below surface) during summer, shifts in vegetation from wetland grasses towards more shrubby species, and corresponding complex changes in soil temperatures linked to thermal conductivity and heat capacity. Overall, at the Ambolikha site drainage reduced thaw depth, thus stabilized deeper soil layers and prevented the degradation of old permafrost carbon pools. At the macroscale (100s to 1000s km), a direct comparison with comparable observation sites in the Lena River delta in Northwest Siberia indicated very similar CO2-budgets during summertime when comparing floodplain sites, while CH4 budgets were systematically different.

With respect to temporal variability in flux rates, our experiments demonstrated that even though fluxes are highest during the growing seasons, neglect of fluxes during the Arctic winter would lead to systematic biases in annual flux budgets: For CO2, about 50% of the summertime carbon uptake is lost through respiration during the colder seasons, while for CH4 about 30% of methane emissions are added while soils are (partly) frozen. Interannual variability in flux rates was pronounced particularly for CO2 fluxes, and also for CH4 fluxes from the control section of our site, while CH4 fluxes from the drained areas were largely constant throughout the years. We identified conditions during the late growing season (mostly August) as the most important influence on interannual variability in flux budgets. A methodological review of eddy covariance flux measurements indicated that Arctic CH4 observations are prone to biases linked to the intermittent nature of CH4 flux outbursts at nighttime, while a systematic review of quality control measured during Arctic winter helped to improve overall data quality.

Modeling activities were distributed across three major categories. First, data-driven upscaling of Siberian eddy-covariance flux datasets from five sites revealed a solid terrestrial sink for CO2 carbon embedded within a highly structured permafrost landscape. Second, the land-surface model JSBACH was extended by a process-based methane module, and tested against observational datasets from Chersky and other sites. These studies revealed the need to resolve fine-scale landscape characteristics in high resolution to avoid aggregation errors in simulated carbon budgets. Third, we developed a data assimilation system based on geostatistical inverse modeling to constrain regional scale carbon budgets in the Arctic, and dominant processes controlling them. All of these modeling approaches, particularly the last element, are still being refined at the time of writing, so results are in part preliminary to date.

Concluding, the new observational infrastructure that was installed in the context of PerCCOM closed a crucial gap in the undersampled Siberian permafrost regions. Our first-of-its-kind long-term permafrost experiment yielded novel understanding of the role of sustained changes in water levels on carbon cycling and energy budgets in tundra ecosystems. The new mechanistic insights of factors controlling surface-atmosphere exchange fluxes, and the net effect of drainage on permafrost stability, will facilitate higher accuracy in forecasts targeting the fate of permafrost carbon pools under future climate change. The new modules in the land surface model JSBACH are groundbreaking regarding a process-based representation of permafrost carbon-climate change feedbacks, and will lead to a more realistic representation of permafrost landscapes in global scale Earth System models. Finally, in combination with the new data stream from Ambarchik the ongoing research on atmospheric inverse modeling will provide a novel data-driven constraint on regional carbon budgets in the Arctic, and thus better constrain the role of key regions like the East Siberian Arctic Shelf in the global climate system.

PerCCOM research did not include any economical objectives. Our data streams and process-based insights into permafrost carbon cycling and general ecology will benefit the Arctic research community, and in particular the modeling community that aims at improving our capabilities for prognostic simulations of Arctic feedbacks to global climate change. Taken together, PerCCOM results will contribute to inform decisionmakers and the general public towards developing suitable adaptation and mitigation measures against climate change.

Reported by

MAX PLANCK GESELLSCHAFT ZUR FOERDERUNG DER WISSENSCHAFTEN E.V.
Germany

Subjects

Life Sciences
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