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The physical and chemical changes that accompany permafrost thaw directly influence the microbial communities that mediate the decomposition of formerly frozen organic matter, leading to uncertainty in permafrost–climate feedbacks. Although changes to microbial metabolism and community structure are documented following thaw, the generality of post‐thaw assembly patterns across permafrost soils of the world remains uncertain, limiting our ability to predict biogeochemistry and microbial community responses to climate change. Based on our review of the Arctic microbiome, permafrost microbiology, and community ecology, we propose thatAssembly Theoryprovides a framework to better understand thaw‐mediated microbiome changes and the implications for community function and climate feedbacks. This framework posits that the prevalence of deterministic or stochastic processes indicates whether the community is well‐suited to thrive in changing environmental conditions. We predict that on a short timescale and following high‐disturbance thaw (e.g., thermokarst), stochasticity dominates post‐thaw microbiome assembly, suggesting that functional predictions will be aided by detailed information about the microbiome. At a longer timescale and lower‐intensity disturbance (e.g., active layer deepening), deterministic processes likely dominate, making environmental parameters sufficient for predicting function. We propose that the contribution of stochastic and deterministic processes to post‐thaw microbiome assembly depends on the characteristics of the thaw disturbance, as well as characteristics of the microbial community, such as the ecological and phylogenetic breadth of functional guilds, their functional redundancy, and biotic interactions. These propagate across space and time, potentially providing a means for predicting the microbial forcing of greenhouse gas feedbacks to global climate change.

 

Earth system models (ESMs) have been rapidly developed in recent decades to advance our understanding of climate change‐carbon cycle feedback. However, those models are massive in coding, require expensive computational resources, and have difficulty in diagnosing their performance. It is highly desirable to develop ESMs with modularity and effective diagnostics. Toward these goals, we implemented a matrix approach to the Community Land Model version 5 (CLM5) to represent carbon and nitrogen cycles. Specifically, we reorganized 18 balance equations each for carbon and nitrogen cycles among the 18 vegetation pools in the original CLM5 into two matrix equations. Similarly, 140 balance equations each for carbon and nitrogen cycles among the 140 soil pools were reorganized into two additional matrix equations. The vegetation carbon and nitrogen matrix equations are connected to soil matrix equations via litterfall. The matrix equations fully reproduce simulations of carbon and nitrogen dynamics by the original model. The computational cost for forwarding simulation of the CLM5 matrix model was 26% more expensive than the original model, largely due to calculation of additional diagnostic variables, but the spin‐up computational cost was significantly saved. We showed a case study on modeled soil carbon storage under two forcing data sets to illustrate the diagnostic capability that the matrix approach uniquely offers to understand simulation results of global carbon and nitrogen dynamics. The successful implementation of the matrix approach to CLM5, one of the most complex land models, demonstrates that most, if not all, the biogeochemical models can be reorganized into the matrix form to gain high modularity, effective diagnostics, and accelerated spin‐up.

 

The magnitude of future emissions of greenhouse gases from the northern permafrost region depends crucially on the mineralization of soil organic carbon (SOC) that has accumulated over millennia in these perennially frozen soils. Many recent studies have used radiocarbon (¹⁴C) to quantify the release of this “old” SOC as CO₂or CH₄to the atmosphere or as dissolved and particulate organic carbon (DOC and POC) to surface waters. We compiled ~1,900¹⁴C measurements from 51 sites in the northern permafrost region to assess the vulnerability of thawing SOC in tundra, forest, peatland, lake, and river ecosystems. We found that growing season soil¹⁴C‐CO₂emissions generally had a modern (post‐1950s) signature, but that well‐drained, oxic soils had increased CO₂emissions derived from older sources following recent thaw. The age of CO₂and CH₄emitted from lakes depended primarily on the age and quantity of SOC in sediments and on the mode of emission, and indicated substantial losses of previously frozen SOC from actively expanding thermokarst lakes. Increased fluvial export of aged DOC and POC occurred from sites where permafrost thaw caused soil thermal erosion. There was limited evidence supporting release of previously frozen SOC as CO₂, CH₄, and DOC from thawing peatlands with anoxic soils. This synthesis thus suggests widespread but not universal release of permafrost SOC following thaw. We show that different definitions of “old” sources among studies hamper the comparison of vulnerability of permafrost SOC across ecosystems and disturbances. We also highlight opportunities for future¹⁴C studies in the permafrost region.

 

Abstract Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm −2 ) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types. 

Rapid Arctic environmental change affects the entire Earth system as thawing permafrost ecosystems release greenhouse gases to the atmosphere. Understanding how much permafrost carbon will be released, over what time frame, and what the relative emissions of carbon dioxide and methane will be is key for understanding the impact on global climate. In addition, the response of vegetation in a warming climate has the potential to offset at least some of the accelerating feedback to the climate from permafrost carbon. Temperature, organic carbon, and ground ice are key regulators for determining the impact of permafrost ecosystems on the global carbon cycle. Together, these encompass services of permafrost relevant to global society as well as to the people living in the region and help to determine the landscape-level response of this region to a changing climate. 

Climate change is an existential threat to the vast global permafrost domain. The diverse human cultures, ecological communities, and biogeochemical cycles of this tenth of the planet depend on the persistence of frozen conditions. The complexity, immensity, and remoteness of permafrost ecosystems make it difficult to grasp how quickly things are changing and what can be done about it. Here, we summarize terrestrial and marine changes in the permafrost domain with an eye toward global policy. While many questions remain, we know that continued fossil fuel burning is incompatible with the continued existence of the permafrost domain as we know it. If we fail to protect permafrost ecosystems, the consequences for human rights, biosphere integrity, and global climate will be severe. The policy implications are clear: the faster we reduce human emissions and draw down atmospheric CO 2 , the more of the permafrost domain we can save. Emissions reduction targets must be strengthened and accompanied by support for local peoples to protect intact ecological communities and natural carbon sinks within the permafrost domain. Some proposed geoengineering interventions such as solar shading, surface albedo modification, and vegetation manipulations are unproven and may exacerbate environmental injustice without providing lasting protection. Conversely, astounding advances in renewable energy have reopened viable pathways to halve human greenhouse gas emissions by 2030 and effectively stop them well before 2050. We call on leaders, corporations, researchers, and citizens everywhere to acknowledge the global importance of the permafrost domain and work towards climate restoration and empowerment of Indigenous and immigrant communities in these regions. 

Abstract. Large changes in the Arctic carbon balance are expectedas warming linked to climate change threatens to destabilize ancientpermafrost carbon stocks. The eddy covariance (EC) method is an establishedtechnique to quantify net losses and gains of carbon between the biosphereand atmosphere at high spatiotemporal resolution. Over the past decades, agrowing network of terrestrial EC tower sites has been established acrossthe Arctic, but a comprehensive assessment of the network'srepresentativeness within the heterogeneous Arctic region is still lacking.This creates additional uncertainties when integrating flux data acrosssites, for example when upscaling fluxes to constrain pan-Arctic carbonbudgets and changes therein. This study provides an inventory of Arctic (here > = 60∘ N)EC sites, which has also been made available online(https://cosima.nceas.ucsb.edu/carbon-flux-sites/, last access: 25 January 2022). Our database currentlycomprises 120 EC sites, but only 83 are listed as active, and just 25 ofthese active sites remain operational throughout the winter. To map therepresentativeness of this EC network, we evaluated the similarity betweenenvironmental conditions observed at the tower locations and those withinthe larger Arctic study domain based on 18 bioclimatic and edaphicvariables. This allows us to assess a general level of similarity betweenecosystem conditions within the domain, while not necessarily reflectingchanges in greenhouse gas flux rates directly. We define two metrics basedon this representativeness score: one that measures whether a location isrepresented by an EC tower with similar characteristics (ER1) and a secondfor which we assess if a minimum level of representation for statisticallyrigorous extrapolation is met (ER4). We find that while half of the domainis represented by at least one tower, only a third has enough towers insimilar locations to allow reliable extrapolation. When we consider methanemeasurements or year-round (including wintertime) measurements, the valuesdrop to about 1/5 and 1/10 of the domain, respectively. With themajority of sites located in Fennoscandia and Alaska, these regions wereassigned the highest level of network representativeness, while large partsof Siberia and patches of Canada were classified as underrepresented.Across the Arctic, mountainous regions were particularly poorly representedby the current EC observation network. We tested three different strategies to identify new site locations orupgrades of existing sites that optimally enhance the representativeness ofthe current EC network. While 15 new sites can improve therepresentativeness of the pan-Arctic network by 20 %, upgrading as fewas 10 existing sites to capture methane fluxes or remain active duringwintertime can improve their respective ER1 network coverage by 28 % to 33 %. This targeted network improvement could be shown to be clearlysuperior to an unguided selection of new sites, therefore leading tosubstantial improvements in network coverage based on relatively smallinvestments. 

Abstract. Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).