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Tundra and boreal ecosystems encompass the northern circumpolar permafrost region and are experiencing rapid environmental change with important implications for the global carbon (C) budget. We analysed multi-decadal time series containing 302 annual estimates of carbon dioxide (CO2) flux across 70 permafrost and non-permafrost ecosystems, and 672 estimates of summer CO2 flux across 181 ecosystems. We find an increase in the annual CO2 sink across non-permafrost ecosystems but not permafrost ecosystems, despite similar increases in summer uptake. Thus, recent non-growing-season CO2 losses have substantially impacted the CO2 balance of permafrost ecosystems. Furthermore, analysis of interannual variability reveals warmer summers amplify the C cycle (increase productivity and respiration) at putatively nitrogen-limited sites and at sites less reliant on summer precipitation for water use. Our findings suggest that water and nutrient availability will be important predictors of the C-cycle response of these ecosystems to future warming.

Permafrost thaw causes the seasonally thawed active layer to deepen, causing the Arctic to shift toward carbon release as soil organic matter becomes susceptible to decomposition. Ground subsidence initiated by ice loss can cause these soils to collapse abruptly, rapidly shifting soil moisture as microtopography changes and also accelerating carbon and nutrient mobilization. The uncertainty of soil moisture trajectories during thaw makes it difficult to predict the role of abrupt thaw in suppressing or exacerbating carbon losses. In this study, we investigated the role of shifting soil moisture conditions on carbon dioxide fluxes during a 13-year permafrost warming experiment that exhibited abrupt thaw. Warming deepened the active layer differentially across treatments, leading to variable rates of subsidence and formation of thermokarst depressions. In turn, differential subsidence caused a gradient of moisture conditions, with some plots becoming consistently inundated with water within thermokarst depressions and others exhibiting generally dry, but more variable soil moisture conditions outside of thermokarst depressions. Experimentally induced permafrost thaw initially drove increasing rates of growing season gross primary productivity (GPP), ecosystem respiration (Reco ), and net ecosystem exchange (NEE) (higher carbon uptake), but the formation of thermokarst depressions began to reverse this trend with a high level of spatial heterogeneity. Plots that subsided at the slowest rate stayed relatively dry and supported higher CO2 fluxes throughout the 13-year experiment, while plots that subsided very rapidly into the center of a thermokarst feature became consistently wet and experienced a rapid decline in growing season GPP, Reco , and NEE (lower carbon uptake or carbon release). These findings indicate that Earth system models, which do not simulate subsidence and often predict drier active layer conditions, likely overestimate net growing season carbon uptake in abruptly thawing landscapes.

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, 10.3334/ORNLDAAC/1934). Copyright:

Recent warming in the Arctic, which has been amplified during the winter1-3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is highly uncertain and has not been well represented by ecosystem models or by empirically-based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1662 Tg C yr-1 from the permafrost region during the winter season (October through April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1032 Tg C yr-1). Extending model predictions to warmer conditions in 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway (RCP) 4.5-and 41% under business-as-usual emissions scenario-RCP 8.5. Our results provide a new baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.

We assess scientific evidence that has emerged since the U.S. Environmental Protection Agency's 2009 Endangerment Finding for six well-mixed greenhouse gases and find that this new evidence lends increased support to the conclusion that these gases pose a danger to public health and welfare. Newly available evidence about a wide range of observed and projected impacts strengthens the association between the risk of some of these impacts and anthropogenic climate change, indicates that some impacts or combinations of impacts have the potential to be more severe than previously understood, and identifies substantial risk of additional impacts through processes and pathways not considered in the Endangerment Finding.

The Polaris Project, a National Science Foundation-funded program at the Woodwell Climate Research Center, aims to comprehensively address minority participation in climate and Arctic science research. The project implemented design principles to recruit, motivate, and retain African Americans, Hispanics, Native Americans or Alaskan Natives, and women through immersive, field research experiences. The project included undergraduate and graduate students from environmental science, ecology, hydrology, biology, forestry, and geology. Ninety-five percent of participants identified as African American, Hispanic, Native American or Alaskan Native, and/or female. Critical participant outcomes included development of interdisciplinary research projects, involvement in self-efficacy and advocacy experiences, and increased awareness and discussion of Arctic research careers. All outcomes contributed to the Polaris Project's role as a model climate science research program.

Ecosystems at high latitudes are changing rapidly in response to climate change. To understand changes in carbon fluxes across seasonal to multi‐decadal timescales, long‐term in situ measurements from eddy covariance networks are needed. However, there are large spatiotemporal gaps in the high‐latitude eddy covariance network. Here we used the relative extrapolation error index in machine learning‐based upscaled gross primary production as a measure of network representativeness and as the basis for a network optimization. We show that the relative extrapolation error index has steadily decreased from 2001 to 2020, suggesting diminishing upscaling errors. In experiments where we limit site activity by either setting a maximum duration or by ending measurements at a fixed time those errors increase significantly, in some cases setting the network status back more than a decade. Our experiments also show that with equal site activity across different theoretical network setups, a more spread out design with shorter‐term measurements functions better in terms of larger‐scale representativeness than a network with fewer long‐term towers. We developed a method to select optimized site additions for a network extension, which blends an objective modeling approach with expert knowledge. This method greatly outperforms an unguided network extension and can compensate for suboptimal human choices. For the Canadian Arctic we show several optimization scenarios and find that especially the Canadian high Arctic and north east tundra benefit greatly from addition sites. Overall, it is important to keep sites active and where possible make the extra investment to survey new strategic locations. Plain Language Summary: The Arctic is one of earth's regions most severely affected by climate change as ice sheets melt and permafrost thaws. This permafrost is rich in carbon which will be released in time. How fast and in which form this carbon is released is highly uncertain. Release as methane would, for example, cause greater global warming in the near future than if it were released as carbon dioxide. It is therefore important to properly measure this carbon release so society can properly prepare for its effects. But as the Arctic is remote and has extreme conditions, there are not so many measuring stations and they might not cover all essential regions. We investigate how well this network represents the Arctic, and where there might be gaps both in space and time. We find that it is essential to keep currently active sites running since if we were to stop measurements our ability to predict this carbon release would not only stagnate but rapidly decline. We developed a method to identify regions that are underrepresented and by incorporating expert knowledge and a new optimization algorithm we can find ideal locations to expand the monitoring network, to better prepare for the future. Key Points: The network of high‐latitude eddy covariance sites has expanded over time, still, sites should remain active and new remote locations addedWhen sites are discontinued, upscaling model skill declines over time, and more quickly in large networksNetwork optimization methods as shown here are a valuable tool to ensure a representative network design [ABSTRACT FROM AUTHOR]

Climate warming can result in both abiotic (e.g., permafrost thaw) and biotic (e.g., microbial functional genes) changes in Arctic tundra. Recent research has incorporated dynamic permafrost thaw in Earth system models (ESMs) and indicates that Arctic tundra could be a significant future carbon (C) source due to the enhanced decomposition of thawed deep soil C. However, warming-induced biotic changes may influence biologically related parameters and the consequent projections in ESMs. How model parameters associated with biotic responses will change under warming and to what extent these changes affect projected C budgets have not been carefully examined. In this study, we synthesized six data sets over 5 years from a soil warming experiment at the Eight Mile Lake, Alaska, into the Terrestrial ECOsystem (TECO) model with a probabilistic inversion approach. The TECO model used multiple soil layers to track dynamics of thawed soil under different treatments. Our results show that warming increased light use efficiency of vegetation photosynthesis but decreased baseline (i.e., environment-corrected) turnover rates of SOC in both the fast and slow pools in comparison with those under control. Moreover, the parameter changes generally amplified over time, suggesting processes of gradual physiological acclimation and functional gene shifts of both plants and microbes. The TECO model predicted that field warming from 2009 to 2013 resulted in cumulative C losses of 224 or 87 g/m2 , respectively, without or with changes in those parameters. Thus, warming-induced parameter changes reduced predicted soil C loss by 61%. Our study suggests that it is critical to incorporate biotic changes in ESMs to improve the model performance in predicting C dynamics in permafrost regions.

In the last few decades, temperatures in the Arctic have increased twice as much as the rest of the globe. As permafrost thaws in response to this warming, large amounts of soil organic matter may become vulnerable to decomposition. Microbial decomposition will release carbon (C) from permafrost soils, however, warmer conditions could also lead to enhanced plant growth and C uptake. Field and modeling studies show high uncertainty in soil and plant responses to climate change but there have been few studies that reconcile field and model data to understand differences and reduce uncertainty. Here, we evaluate gross primary productivity (GPP), ecosystem respiration (Reco), and net ecosystem C exchange (NEE) from eight years of experimental soil warming in moist acidic tundra against equivalent fluxes from the Community Land Model during simulations parameterized to reflect the field conditions associated with this manipulative field experiment. Over the eight-year experimental period, soil temperatures and thaw depths increased with warming in field observations and model simulations. However, the field and model results do not agree on warming effects on water table depth; warming created wetter soils in the field and drier soils in the models. In the field, initial increases in growing season GPP, Reco, and NEE to experimentally-induced permafrost thaw created a higher C sink capacity in the first years followed by a stronger C source in years six through eight. In contrast, both models predicted linear increases in GPP, Reco, and NEE with warming. The divergence of model results from field experiments reveals the role subsidence, hydrology, and nutrient cycling play in influencing the C flux responses to permafrost thaw, a complexity that the models are not structurally able to predict, and highlight challenges associated with projecting C cycle dynamics across the Arctic.

Rapid Arctic warming is expected to increase global greenhouse gas concentrations as permafrost thaw exposes immense stores of frozen carbon (C) to microbial decomposition. Permafrost thaw also stimulates plant growth, which could offset C loss. Using data from 7 years of experimental Air and Soil warming in moist acidic tundra, we show that Soil warming had a much stronger effect on CO2 flux than Air warming. Soil warming caused rapid permafrost thaw and increased ecosystem respiration (Reco ), gross primary productivity (GPP), and net summer CO2 storage (NEE). Over 7 years Reco , GPP, and NEE also increased in Control (i.e., ambient plots), but this change could be explained by slow thaw in Control areas. In the initial stages of thaw, Reco , GPP, and NEE increased linearly with thaw across all treatments, despite different rates of thaw. As thaw in Soil warming continued to increase linearly, ground surface subsidence created saturated microsites and suppressed Reco , GPP, and NEE. However Reco and GPP remained high in areas with large Eriophorum vaginatum biomass. In general NEE increased with thaw, but was more strongly correlated with plant biomass than thaw, indicating that higher Reco in deeply thawed areas during summer months was balanced by GPP. Summer CO2 flux across treatments fit a single quadratic relationship that captured the functional response of CO2 flux to thaw, water table depth, and plant biomass. These results demonstrate the importance of indirect thaw effects on CO2 flux: plant growth and water table dynamics. Nonsummer Reco models estimated that the area was an annual CO2 source during all years of observation. Nonsummer CO2 loss in warmer, more deeply thawed soils exceeded the increases in summer GPP, and thawed tundra was a net annual CO2 source.

Cajander larch (Larix cajanderi Mayr.) forests of the Siberian Arctic are experiencing increased wildfire activity in conjunction with climate warming. These shifts could affect postfire variation in the density and arrangement of trees and understory plant communities. To better understand how understory plant composition, abundance, and diversity vary with tree density, we surveyed understory plant communities and stand characteristics (e.g., canopy cover, active layer depth, and soil organic layer depth) within 25 stands representing a density gradient of similarly-aged larch trees that established following a 1940 fire near Cherskiy, Russia. Understory plant diversity and mean total plant abundance decreased with increased canopy cover. Canopy cover was also the most important variable affecting individual species' abundances. In general, tall shrubs (e.g., Betula nana subsp. exilis) were more abundant in low-density stands with high light availability, and mosses (e.g., Sanionia spp.) were more abundant in high-density stands with low light availability. These results provide evidence that postfire variation in tree recruitment affects understory plant community composition and diversity as stands mature. Therefore, projected increases in wildfire activity in the Siberian Arctic could have cascading impacts on forest structure and composition in both overstory and understory plant communities. Key words: Cajander larch, Larix cajanderi, Betula nana subsp. exilis, wildfire, disturbance. Les forets de meleze cajander (Larix cajanderi Mayr.) de l'Arctique siberien connaissent une augmentation de l'activite des feux de foret conjointement avec le rechauffement climatique. Ces changements pourraient avoir un impact sur la variation apres feu de la densite et de la composition des arbres ainsi que des communautes vegetales du sous-bois. Dans le but de mieux comprendre de quelle facon la composition, l'abondance et la diversite des plantes de sous-bois varient en fonction de la densite des arbres, nous avons inventorie les communautes vegetales du sous-bois et les caracteristiques du peuplement (par example, couvert forestier, profondeur de la strate active et profondeur de l'horizon organique du sol) dans 25 peuplements representant un gradient de densite de melezes d'age similaire qui se sont etablis a la suite de l'incendie de 1940 pres de Cherskiy, en Russie. La diversite des plantes de sous-bois et l'abondance totale moyenne des plantes diminuaient avec l'augmentation du couvert forestier, lequel etait aussi la plus importante variable ayant un impact sur l'abondance des especes prises individuellement. En general, les grands arbustes (p. ex., Betula nana subsp. exilis) etaient plus abondants dans les peuplements avec une faible densite et une grande disponibilite de lumiere, et les mousses (p. ex., Sanionia spp.) etaient plus abondantes dans les peuplements avec une densite elevee et une faible disponibilite de lumiere. Ces resultats fournissent la preuve que la variation apres feu dans le recrutement des arbres a un impact sur la composition et la diversite de la communaute vegetale du sous-bois a mesure que les peuplements deviennent matures. Par consequent, les augmentations prevues de l'activite des feux de foret dans l'Arctique siberien pourraient avoir des repercussions en cascade sur la structure et la composition de la foret parmi les communautes vegetales du sous-bois et de l'etage dominant. [Traduit par la Redaction] Mots-cles : meleze cajander, Larix cajanderi, Betula nana subsp. exilis, feu de foret, perturbation., Introduction Rapid rates of global change make boreal forests particularly susceptible to forest loss and (or) transition to novel forest conditions (Johnstone et al. 2010; Scheffer et al. 2012). Boreal [...]

Studies in recent decades have shown strong evidence of physical and biological changes in the Arctic tundra, largely in response to rapid rates of warming. Given the important implications of these changes for ecosystem services, hydrology, surface energy balance, carbon budgets, and climate feedbacks, research on the trends and patterns of these changes is becoming increasingly important and can help better constrain estimates of local, regional, and global impacts as well as inform mitigation and adaptation strategies. Despite this great need, scientific understanding of tundra ecology and change remains limited, largely due to the inaccessibility of this region and less intensive studies compared to other terrestrial biomes. A synthesis of existing datasets from past field studies can make field data more accessible and open up possibilities for collaborative research as well as for investigating and informing future studies. Here, we synthesize field datasets of vegetation and active-layer properties from the Alaskan tundra, one of the most well-studied tundra regions. Given the potentially increasing intensive fire regimes in the tundra, fire history and severity attributes have been added to data points where available. The resulting database is a resource that future investigators can employ to analyze spatial and temporal patterns in soil, vegetation, and fire disturbance-related environmental variables across the Alaskan tundra. This database, titled the Synthesized Alaskan Tundra Field Database (SATFiD), can be accessed at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for Biogeochemical Dynamics (Chen et al., 2023: 10.3334/ORNLDAAC/2177). [ABSTRACT FROM AUTHOR]

Permafrost soils currently store approximately 1672 Pg of carbon (C), but as high latitudes warm, this temperature-protected C reservoir will become vulnerable to higher rates of decomposition. In recent decades, air temperatures in the high latitudes have warmed more than any other region globally, particularly during the winter. Over the coming century, the arctic winter is also expected to experience the most warming of any region or season, yet it is notably understudied. Here we present nonsummer season (NSS) CO2 flux data from the Carbon in Permafrost Experimental Heating Research project, an ecosystem warming experiment of moist acidic tussock tundra in interior Alaska. Our goals were to quantify the relationship between environmental variables and winter CO2 production, account for subnivean photosynthesis and late fall plant C uptake in our estimate of NSS CO2 exchange, constrain NSS CO2 loss estimates using multiple methods of measuring winter CO2 flux, and quantify the effect of winter soil warming on total NSS CO2 balance. We measured CO2 flux using four methods: two chamber techniques (the snow pit method and one where a chamber is left under the snow for the entire season), eddy covariance, and soda lime adsorption, and found that NSS CO2 loss varied up to fourfold, depending on the method used. CO2 production was dependent on soil temperature and day of season but atmospheric pressure and air temperature were also important in explaining CO2 diffusion out of the soil. Warming stimulated both ecosystem respiration and productivity during the NSS and increased overall CO2 loss during this period by 14% (this effect varied by year, ranging from 7 to 24%). When combined with the summertime CO2 fluxes from the same site, our results suggest that this subarctic tundra ecosystem is shifting away from its historical function as a C sink to a C source.

Wetlands are the largest natural source of methane (CH4) emissions globally. Northern wetlands (>45° N), accounting for 42 % of global wetland area, are increasingly vulnerable to carbon loss, especially as CH4 emissions may accelerate under intensified high-latitude warming. However, the magnitude and spatial patterns of high-latitude CH4 emissions remain relatively uncertain. Here we present estimates of daily CH4 fluxes obtained using a new machine learning-based wetland CH4 upscaling framework (WetCH4) that applies the most complete database of eddy covariance (EC) observations available to date, and satellite remote sensing informed observations of environmental conditions at 10-km resolution. The most important predictor variables included near-surface soil temperatures (top 40 cm), vegetation reflectance, and soil moisture. Our results, modeled from 138 site-years across 26 sites, had relatively strong predictive skill with a mean R2 of 0.46 and 0.62 and a mean absolute error (MAE) of 23 nmol m-2 s-1 and 21 nmol m-2 s-1 for daily and monthly fluxes, respectively. Based on the model results, we estimated an annual average of 20.8 ±2.1 Tg CH4 yr-1 for the northern wetland region (2016–2022) and total budgets ranged from 13.7–44.1 Tg CH4 yr-1, depending on wetland map extents. Although 86 % of the estimated CH4 budget occurred during the May–October period, a considerable amount (1.4 ±0.2 Tg CH4) occurred during winter. Regionally, the West Siberian wetlands accounted for a majority (51 %) of the interannual variation in domain CH4 emissions. Significant issues with data coverage remain, with only 23 % of the sites observing year-round and most of the data from 11 wetland sites in Alaska and 10 bog/fen sites in Canada and Fennoscandia, and in general, Western Siberian Lowlands are underrepresented by EC CH4 sites. Our results provide high spatiotemporal information on the wetland emissions in the high-latitude carbon cycle and possible responses to climate change. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling. The dataset can be found at https://doi.org/10.5281/zenodo.10802154 (Ying et al., 2024). [ABSTRACT FROM AUTHOR]