The role of snow cover affecting boreal-arctic soil freeze–thaw and carbon dynamics

Northern Hemisphere permafrost affected land areas contain about twice as much carbon as the global atmosphere. This vast carbon pool is vulnerable to accelerated losses through mobilization and decomposition under projected global warming. Satellite data records spanning the past 3 decades indicate widespread reductions (~ 0.8–1.3 days decade−1) in the mean annual snow cover extent and frozen-season duration across the pan-Arctic domain, coincident with regional climate warming trends. How the soil carbon pool responds to these changes will have a large impact on regional and global climate. Here, we developed a coupled terrestrial carbon and hydrology model framework with a detailed 1-D soil heat transfer representation to investigate the sensitivity of soil organic carbon stocks and soil decomposition to climate warming and changes in snow cover conditions in the pan-Arctic region over the past 3 decades (1982–2010). Our results indicate widespread soil active layer deepening across the pan-Arctic, with a mean decadal trend of 6.6 ± 12.0 (SD) cm, corresponding to widespread warming. Warming promotes vegetation growth and soil heterotrophic respiration particularly within surface soil layers (≤ 0.2 m). The model simulations also show that seasonal snow cover has a large impact on soil temperatures, whereby increases in snow cover promote deeper (≥ 0.5 m) soil layer warming and soil respiration, while inhibiting soil decomposition from surface (≤ 0.2 m) soil layers, especially in colder climate zones (mean annual T ≤ −10 °C). Our results demonstrate the important control of snow cover on northern soil freeze–thaw and soil carbon decomposition processes and the necessity of considering both warming and a change in precipitation and snow cover regimes in characterizing permafrost soil carbon dynamics

Changes in growing season duration and productivity of northern vegetation inferred from long-term remote sensing data

Monitoring and understanding climate-induced changes in the boreal and arctic vegetation is critical to aid in prognosticating their future. Weused a 33 year (1982-2014) long record of satellite observations to robustly assess changes in metrics of growing season (onset: SOS, end: EOS and length: LOS) and seasonal total gross primary productivity. Particular attention was paid to evaluating the accuracy of these metrics by comparing them to multiple independent direct and indirect growing season and productivity measures. These comparisons reveal that the derived metrics capture the spatio-temporal variations and trends with acceptable significance level (generally p < 0.05). We find that LOS has lengthened by 2.60 d dec(-1) (p < 0.05) due to an earlier onset of SOS (-1.61 d dec(-1), p < 0.05) and a delayed EOS (0.67 d dec(-1), p < 0.1) at the circumpolar scale over the past three decades. Relatively greater rates of changes in growing season were observed in Eurasia (EA) and in boreal regions than in North America (NA) and the arctic regions. However, this tendency of earlier SOS and delayed EOS was prominent only during the earlier part of the data record (1982-1999). During the later part (2000-2014), this tendency was reversed, i.e. delayed SOS and earlier EOS. As for seasonal total productivity, we find that 42.0% of northern vegetation shows a statistically significant (p < 0.1) greening trend over the last three decades. This greening translates to a 20.9% gain in productivity since 1982. In contrast, only 2.5% of northern vegetation shows browning, or a 1.2% loss of productivity. These trends in productivity were continuous through the period of record, unlike changes in growing season metrics. Similarly, we find relatively greater increasing rates of productivity in EA and in arctic regions than in NA and the boreal regions. These results highlight spatially and temporally varying vegetation dynamics and are reflective of biome-specific responses of northern vegetation during last three decades

Synergies Among Environmental Science Research and Monitoring Networks: A Research Agenda

Many research and monitoring networks in recent decades have provided publicly available data documenting environmental and ecological change, but little is known about the status of efforts to synthesize this information across networks. We convened a working group to assess ongoing and potential cross-network synthesis research and outline opportunities and challenges for the future, focusing on the US-based research network (the US Long-Term Ecological Research network, LTER) and monitoring network (the National Ecological Observatory Network, NEON). LTER-NEON cross-network research synergies arise from the potentials for LTER measurements, experiments, models, and observational studies to provide context and mechanisms for interpreting NEON data, and for NEON measurements to provide standardization and broad scale coverage that complement LTER studies. Initial cross-network syntheses at co-located sites in the LTER and NEON networks are addressing six broad topics: how long-term vegetation change influences C fluxes; how detailed remotely sensed data reveal vegetation structure and function; aquatic-terrestrial connections of nutrient cycling; ecosystem response to soil biogeochemistry and microbial processes; population and species responses to environmental change; and disturbance, stability and resilience. This initial study offers exciting potentials for expanded cross-network syntheses involving multiple long-term ecosystem processes at regional or continental scales. These potential syntheses could provide a pathway for the broader scientific community, beyond LTER and NEON, to engage in cross-network science. These examples also apply to many other research and monitoring networks in the US and globally, and can guide scientists and research administrators in promoting broad-scale research that supports resource management and environmental policy

Carbon Fluxes and Microbial Activities From Boreal Peatlands Experiencing Permafrost Thaw

Permafrost thaw in northern ecosystems may cause large quantities of carbon (C) to move from soil to atmospheric pools. Because soil microbial communities play a critical role in regulating C fluxes from soils, we examined microbial activity and greenhouse gas production soon after permafrost thaw and ground collapse (into collapse‐scar bogs), relative to the permafrost plateau or older thaw features. Using multiple field and laboratory‐based assays at a field site in interior Alaska, we show that the youngest collapse‐scar bog had the highest CH4 production potential from soil incubations, and, based upon temporal changes in porewater concentrations and 13C‐CH4 and 13C‐CO2, had greater summer in situ rates of respiration, methanogenesis, and surface CH4 oxidation. These patterns could be explained by greater C and N availability in the young bog, while alternative terminal electron accepting processes did not play a significant role. Field diffusive CH4 fluxes from the young bog were 4.1 times greater in the shoulder season and 1.7–7.2 times greater in winter relative to older bogs, but not during summer. Greater relative CH4 flux rates in the shoulder season and winter could be due to reduced CH4 oxidation relative to summer, magnifying the importance of differences in production. Both the permafrost plateau and collapse‐scar bogs were sources of C to the atmosphere due in large part to winter C fluxes. In collapse scar bogs, winter is a critical period when differences in thermokarst age translates to differences in surface fluxes. Plain Language Summary Permafrost thaw is occurring in Alaska which may result in a positive feedback to climate warming, due to the release of greenhouse gases such as CO2 and CH4 from soils. Here we examined greenhouse gas production along a gradient of “time since thaw,” hypothesizing that fluxes and microbial activities would be highest soon after thaw, and then decline. We observed highest rates of microbial activities, particularly methanogenesis, soon after thaw, coinciding with less decomposed organic matter and higher concentrations of dissolved carbon and nitrogen in soil, possibly of permafrost origin. However, field fluxes were higher in the young thaw site, compared to the older sites, in winter and not summer, a phenomenon that is currently not well understood

Warming response of peatland CO2 sink is sensitive to seasonality in warming trends

Peatlands have acted as net CO2 sinks over millennia, exerting a global climate cooling effect. Rapid warming at northern latitudes, where peatlands are abundant, can disturb their CO2 sink function. Here we show that sensitivity of peatland net CO2 exchange to warming changes in sign and magnitude across seasons, resulting in complex net CO2 sink responses. We use multiannual net CO2 exchange observations from 20 northern peatlands to show that warmer early summers are linked to increased net CO2 uptake, while warmer late summers lead to decreased net CO2 uptake. Thus, net CO2 sinks of peatlands in regions experiencing early summer warming, such as central Siberia, are more likely to persist under warmer climate conditions than are those in other regions. Our results will be useful to improve the design of future warming experiments and to better interpret large-scale trends in peatland net CO2 uptake over the coming few decades.Peatlands have historically acted as a carbon sink, but it is unclear how climate warming will affect this. The response of peatland carbon uptake to warming depends on the timing of summer warming; early warming leads to increased CO2 uptake and later warming to decreased uptake

Reanalysis in Earth System Science: Towards Terrestrial Ecosystem Reanalysis

A reanalysis is a physically consistent set of optimally merged simulated model states and historical observational data, using data assimilation. High computational costs for modelled processes and assimilation algorithms has led to Earth system specific reanalysis products for the atmosphere, the ocean and the land separately. Recent developments include the advanced uncertainty quantification and the generation of biogeochemical reanalysis for land and ocean. Here, we review atmospheric and oceanic reanalyses, and more in detail biogeochemical ocean and terrestrial reanalyses. In particular, we identify land surface, hydrologic and carbon cycle reanalyses which are nowadays produced in targeted projects for very specific purposes. Although a future joint reanalysis of land surface, hydrologic and carbon processes represents an analysis of important ecosystem variables, biotic ecosystem variables are assimilated only to a very limited extent. Continuous data sets of ecosystem variables are needed to explore biotic-abiotic interactions and the response of ecosystems to global change. Based on the review of existing achievements, we identify five major steps required to develop terrestrial ecosystem reanalysis to deliver continuous data streams on ecosystem dynamics

A multi-scale comparison of modeled and observed seasonal methane emissions in northern wetlands

Wetlands are the largest global natural methane (CH4) source, and emissions between 50 and 70° N latitude contribute 10–30% to this source. Predictive capability of land models for northern wetland CH4 emissions is still low due to limited site measurements, strong spatial and temporal variability in emissions, and complex hydrological and biogeochemical dynamics. To explore this issue, we compare wetland CH4 emission predictions from the Community Land Model 4.5 (CLM4.5-BGC) with siteto regional-scale observations. A comparison of the CH4 fluxes with eddy flux data highlighted needed changes to the model’s estimate of aerenchyma area, which we implemented and tested. The model modification substantially reduced biases in CH4 emissions when compared with CarbonTracker CH4 predictions. CLM4.5 CH4 emission predictions agree well with growing season (May–September) CarbonTracker Alaskan regional-level CH4 predictions and sitelevel observations. However, CLM4.5 underestimated CH4 emissions in the cold season (October–April). The monthly atmospheric CH4 mole fraction enhancements due to wetland emissions are also assessed using the Weather Research and Forecasting-Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) model coupled with daily emissions from CLM4.5 and compared with aircraft CH4 mole fraction measurements from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) campaign. Both the tower and aircraft analyses confirm the underestimate of cold-season CH4 emissions by CLM4.5. The greatest uncertainties in predicting the seasonal CH4 cycle are from the wetland extent, coldseason CH4 production and CH4 transport processes. We recommend more cold-season experimental studies in highlatitude systems, which could improve the understanding and parameterization of ecosystem structure and function during this period. Predicted CH4 emissions remain uncertain, but we show here that benchmarking against observations across spatial scales can inform model structural and parameter improvements