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Permafrost thaw can alter the soil environment through changes in soil moisture, frequently resulting in soil saturation, a shift to anaerobic decomposition, and changes in the plant community. These changes, along with thawing of previously frozen organic material, can alter the form and magnitude of greenhouse gas production from permafrost ecosystems. We synthesized existing methane (CH4) and carbon dioxide (CO2) production measurements from anaerobic incubations of boreal and tundra soils from the geographic permafrost region to evaluate large-scale controls of anaerobic CO2 and CH4 production and compare the relative importance of landscape-level factors (e.g., vegetation type and landscape position), soil properties (e.g., pH, depth, and soil type), and soil environmental conditions (e.g., temperature and relative water table position). We found fivefold higher maximum CH4 production per gram soil carbon from organic soils than mineral soils. Maximum CH4 production from soils in the active layer (ground that thaws and refreezes annually) was nearly four times that of permafrost per gram soil carbon, and CH4 production per gram soil carbon was two times greater from sites without permafrost than sites with permafrost. Maximum CH4 and median anaerobic CO2 production decreased with depth, while CO2:CH4 production increased with depth. Maximum CH4 production was highest in soils with herbaceous vegetation and soils that were either consistently or periodically inundated. This synthesis identifies the need to consider biome, landscape position, and vascular/moss vegetation types when modeling CH4 production in permafrost ecosystems and suggests the need for longer-term anaerobic incubations to fully capture CH4 dynamics. Our results demonstrate that as climate warms in arctic and boreal regions, rates of anaerobic CO2 and CH4 production will increase, not only as a result of increased temperature, but also from shifts in vegetation and increased ground saturation that will accompany permafrost thaw. [ABSTRACT FROM AUTHOR]

The cycling of trace metals through terrestrial ecosystems is modulated by plant and soil processes. Changes in plant growth and function and soil properties associated with increased atmospheric carbon dioxide (CO2) may therefore also affect the biological storage and stoichiometry of trace metals. We examined CO2 effects on a suite of metal micronutrients and contaminants in forest trees and soils at two free-air CO2 enrichment sites—a loblolly pine forest in North Carolina (Duke) and a sweetgum plantation in Tennessee [Oak Ridge National Laboratory (ORNL)]—and an open-top chamber experiment in a scrub-oak community in Florida [Smithsonian Environmental Research Center (SERC)]. We found that CO2 effects on soil metals were variable across sites; there were significantly higher surface soil metal concentrations with CO2 enrichment at Duke and ORNL ( P < 0.05), but a trend of decreased soil metal concentrations at SERC (non-significant). These impacts on metals may be understood in the context of CO2 effects on soil organic matter (SOM); changes in percent SOM with CO2 enrichment were greatest at Duke (18% increase), followed by ORNL (7% increase), with limited effect at SERC (3% increase). There were significant effects of elevated CO2 on foliar metal concentrations at all sites, but the response of foliar metals to CO2 enrichment varied by metal, among sites, and within sites based on plant species, canopy height, and leaf age. Contrary to expectations, we did not find an overall decline in foliar metal concentrations with CO2 enrichment, and some essential plant metals were greater under elevated CO2 (for example, 28% increase in Mn across species and sites). Our results suggest that elevated CO2 impacts on trace metal biogeochemistry can be understood by accounting for both metal function (or lack thereof) in plants and the soil characteristics of the ecosystem. [ABSTRACT FROM AUTHOR]

Boreal and Arctic regions have warmed up to four times quicker than the rest of the planet since the 1970s. As a result, boreal and tundra ecosystems are experiencing more frequent and higher intensity extreme weather events and disturbances, such as wildfires. Yet limitations in ground and satellite data across the Arctic and boreal regions have challenged efforts to track these disturbances at regional scales. In order to effectively monitor the progression and extent of wildfires in the Arctic-boreal zone, it is essential to determine whether burned area (BA) products are accurate representations of BA. Here, we use 12 different datasets together with MODIS active fire data to determine the total yearly BA and seasonal patterns of fires in Arctic-boreal North America and Russia for the years 2001–2020. We found relatively little variability between the datasets in North America, both in terms of total BA and seasonality, with an average BA of 2.55 ± 1.24 (standard deviation) Mha/year for our analysis period, the majority (ca. 41%) of which occurs in July. In contrast, in Russia, there are large disparities between the products—GFED5 produces over four times more BA than GFED4s in southern Siberia. These disparities occur due to the different methodologies used; dNBR (differenced Normalized Burn Ratio) of short-term composites from Landsat images used alongside hotspot data was the most consistently successful in representing BA. We stress caution using GABAM in these regions, especially for the years 2001–2013, as Landsat-7 ETM+ scan lines are mistaken as burnt patches, increasing errors of commission. On the other hand, we highlight using regional products where possible, such as ABoVE-FED or ABBA in North America, and the Talucci et al. fire perimeter product in Russia, due to their detection of smaller fires which are often missed by global products. [ABSTRACT FROM AUTHOR]

Summary Plant phenology, the timing of recurrent biological events, shows key and complex response to climate warming, with consequences for ecosystem functions and services. A key challenge for predicting plant phenology under future climates is to determine whether the phenological changes will persist with more intensive and long‐term warming. Here, we conducted a meta‐analysis of 103 experimental warming studies around the globe to investigate the responses of four phenophases – leaf‐out, first flowering, last flowering, and leaf coloring. We showed that warming advanced leaf‐out and flowering but delayed leaf coloring across herbaceous and woody plants. As the magnitude of warming increased, the response of most plant phenophases gradually leveled off for herbaceous plants, while phenology responded in proportion to warming in woody plants. We also found that the experimental effects of warming on plant phenology diminished over time across all phenophases. Specifically, the rate of changes in first flowering for herbaceous species, as well as leaf‐out and leaf coloring for woody species, decreased as the experimental duration extended. Together, these results suggest that the real‐world impact of global warming on plant phenology will diminish over time as temperatures continue to increase. [ABSTRACT FROM AUTHOR]

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]

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]

Boreal forests are changing in response to climate, with potentially important feedbacks to regional and global climate through altered carbon cycle and albedo dynamics. These feedback processes will be affected by vegetation changes, and feedback strengths will largely rely on the spatial extent and timing of vegetation change. Satellite remote sensing is widely used to monitor vegetation dynamics, and vegetation indices (VIs) are frequently used to characterize spatial and temporal trends in vegetation productivity. In this study we combine field observations of larch forest cover across a 25 km2 upland landscape in northeastern Siberia with high-resolution satellite observations to determine how the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are related to forest cover. Across 46 forest stands ranging from 0% to 90% larch canopy cover, we find either no change, or declines in NDVI and EVI derived from PlanetScope CubeSat and Landsat data with increasing forest cover. In conjunction with field observations of NDVI, these results indicate that understory vegetation likely exerts a strong influence on vegetation indices in these ecosystems. This suggests that positive decadal trends in NDVI in Siberian larch forests may correspond primarily to increases in understory productivity, or even to declines in forest cover. Consequently, positive NDVI trends may be associated with declines in terrestrial carbon storage and increases in albedo, rather than increases in carbon storage and decreases in albedo that are commonly assumed. Moreover, it is also likely that important ecological changes such as large changes in forest density or variable forest regrowth after fire are not captured by long-term NDVI trends. [ABSTRACT FROM AUTHOR]

Large uncertainties exist in carbon (C)-climate feedback in permafrost regions, partly due to an insufficient understanding of warming effects on nutrient availabilities and their subsequent impacts on vegetation C sequestration. Although a warming climate may promote a substantial release of soil C to the atmosphere, a warming-induced increase in soil nutrient availability may enhance plant productivity, thus offsetting C loss from microbial respiration. Here, we present evidence that the positive temperature effect on carbon dioxide ( CO2) fluxes may be weakened by reduced plant nitrogen (N) and phosphorous (P) concentrations in a Tibetan permafrost ecosystem. Although experimental warming initially enhanced ecosystem CO2 uptake, the increased rate disappeared after the period of peak plant growth during the early growing season, even though soil moisture was not a limiting factor in this swamp meadow ecosystem. We observed that warming did not significantly affect soil extractable N or P during the period of peak growth, but decreased both N and P concentrations in the leaves of dominant plant species, likely caused by accelerated plant senescence in the warmed plots. The attenuated warming effect on CO2 assimilation during the late growing season was associated with lowered leaf N and P concentrations. These findings suggest that warming-mediated nutrient changes may not always benefit ecosystem C uptake in permafrost regions, making our ability to predict the C balance in these warming-sensitive ecosystems more challenging than previously thought. [ABSTRACT FROM AUTHOR]

The distribution of contaminant elements within ecosystems is an environmental concern because of these elements' potential toxicity to animals and plants and their ability to hinder microbial ecosystem services. As with nutrients, contaminants are cycled within and through ecosystems. Elevated atmospheric CO2 generally increases plant productivity and alters nutrient element cycling, but whether CO2 causes similar effects on the cycling of contaminant elements is unknown. Here we show that 11 years of experimental CO2 enrichment in a sandy soil with low organic matter content causes plants to accumulate contaminants in plant biomass, with declines in the extractable contaminant element pools in surface soils. These results indicate that CO2 alters the distribution of contaminant elements in ecosystems, with plant element accumulation and declining soil availability both likely explained by the CO2 stimulation of plant biomass. Our results highlight the interdependence of element cycles and the importance of taking a broad view of the periodic table when the effects of global environmental change on ecosystem biogeochemistry are considered. [ABSTRACT FROM AUTHOR]

Carbon cycle perturbations in high-latitude ecosystems associated with rapid warming can have implications for the global climate. Belowground biomass is an important component of the carbon cycle in these ecosystems, with, on average, significantly more vegetation biomass belowground than aboveground. Large quantities of dead root biomass are also in these ecosystems owing to slow decomposition rates. Current understanding of how live and dead root biomass carbon pools vary across high-latitude ecosystems and the environmental conditions associated with this variation is limited due to the labor- and time-intensive nature of data collection. To that end, we examined patterns and factors (abiotic and biotic) associated with the variation in live and dead fine root biomass (FRB) and FRB carbon (C), nitrogen (N) and phosphorus concentrations for 23 sites across a latitudinal gradient in Alaska, spanning both boreal forest and tundra biomes. We found no difference in the live or dead FRB variables between these biomes, despite large differences in predominant vegetation types, except for significantly higher live FRB C:N ratios in boreal sites. Soil C:N ratio, moisture, and temperature, along with moss cover, explained a substantial portion of the dead:live FRB ratio variability across sites. We find all these factors have negative relationships with dead FRB, while having positive or no relationship with live FRB. This work demonstrates that FRB does not necessarily correlate with aboveground vegetation characteristics, and it highlights the need for finer-scale measurements of abiotic and biotic factors to understand FRB landscape variability now and into the future. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Northern lakes are a source of greenhouse gases to the atmosphere and contribute substantially to the global carbon budget. However, the sources of methane (CH4) to northern lakes are poorly constrained limiting our ability to the assess impacts of future Arctic change. Here we present measurements of the natural groundwater tracer, radon, and CH4 in a shallow lake on the Yukon-Kuskokwim Delta, AK and quantify groundwater discharge rates and fluxes of groundwater-derived CH4. We found that groundwater was significantly enriched (2000%) in radon and CH4 relative to lake water. Using a mass balance approach, we calculated average groundwater fluxes of 1.2 ± 0.6 and 4.3 ± 2.0 cm day−1, respectively as conservative and upper limit estimates. Groundwater CH4 fluxes were 7—24 mmol m−2 day−1 and significantly exceeded diffusive air–water CH4 fluxes (1.3–2.3 mmol m−2 day−1) from the lake to the atmosphere, suggesting that groundwater is an important source of CH4 to Arctic lakes and may drive observed CH4 emissions. Isotopic signatures of CH4 were depleted in groundwaters, consistent with microbial production. Higher methane concentrations in groundwater compared to other high latitude lakes were likely the source of the comparatively higher CH4 diffusive fluxes, as compared to those reported previously in high latitude lakes. These findings indicate that deltaic lakes across warmer permafrost regions may act as important hotspots for CH4 release across Arctic landscapes. [ABSTRACT FROM AUTHOR]

Abstract: 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. [ABSTRACT FROM AUTHOR]

• Trained high-accuracy deep neural networks to map retrogressive thaw slumps (RTS). • Tested the impact of negative data in training RTS segmentation models. • Evaluated the impact of 'within-class' and 'between-class' variances on RTS models. • Developed a Lightweight workflow for training deep learning RTS segmentation models. • Developed an effective RTS data fusion method for multi-source satellite imageries. Retrogressive thaw slumps (RTS) are thermokarst features in ice-rich hillslope permafrost terrain, and their occurrence in the warming Arctic is increasingly frequent and has caused dynamic changes to the landscape. RTS can significantly impact permafrost stability and generate substantial carbon emissions. Understanding the spatial and temporal distribution of RTS is a critical step to understanding and modelling greenhouse gas emissions from permafrost thaw. Mapping RTS using conventional Earth observation approaches is challenging due to the highly dynamic nature and often small scale of RTS in the Arctic. In this study, we trained deep neural network models to map RTS across several landscapes in Siberia and Canada. Convolutional neural networks were trained with 965 RTS features, where 509 were from the Yamal and Gydan peninsulas in Siberia, and 456 from six other pan-Arctic regions including Canada and Northeastern Siberia. We further tested the impact of negative data on the model performance. We used 4-m Maxar commercial imagery as the base map, 10-m NDVI derived from Sentinel-2 and 2-m elevation data from the ArcticDEM as model inputs and applied image augmentation techniques to enhance training. The best-performing model reached a validation Intersection over Union (IoU) score of 0.74 and a test IoU score of 0.71. Compared to past efforts to map RTS features, this represents one of the best-performing models and generalises well for mapping RTS in different permafrost regions, representing a critical step towards pan-Arctic deployment. The predicted RTS matched very well with the ground truth labels visually. We also tested how model performance varied across different regional contexts. The result shows an overall positive impact on the model performance when data from different regions were incorporated into the training. We propose this method as an effective, accurate and computationally undemanding approach for RTS mapping. [ABSTRACT FROM AUTHOR]

Increasing wildfire activity at high northern latitudes has the potential to mobilize large amounts of terrestrial mercury (Hg). However, understanding implications for Hg cycling and ecosystems is hindered by sparse research on peatland wildfire Hg emissions. In this study, we used measurements of soil organic carbon (SOC) and Hg, burn depth, and environmental indices derived from satellite remote sensing to develop machine learning models for predicting Hg emissions from major wildfires in the permafrost peatland of the Yukon-Kuskokwim Delta (YKD) in southwestern Alaska. Wildfire Hg emissions during summer 2015─estimated as the product of Hg:SOC (0.38 ± 0.17 ng Hg g C 1- ), predicted SOC stores (mean [5th-95th] = 9.1 [5.3-11.2] kg C m -2 ), and burn depth (11.3 [8.2-13.9] cm)─were 556 [164-1138] kg Hg or approximately 6% of Hg emissions from wildfire activity >60°N. Modeling estimates suggest that wildfire nearly doubled summertime Hg deposition within 10 km, despite advection of more than 75% of total emissions beyond Alaska. YKD areal emissions combined with remote sensing estimates of burned area suggest that wildfire Hg emissions from northern peatlands (25.4 [14.9-33.6] Mg y -1 ) are an important component of the northern Hg budget. Additional research is needed to refine these estimates and understand the implications for Arctic and global Hg cycling.

Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m -2 ) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic., (© 2024. The Author(s).)

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 (R eco ), 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 CO 2 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, R eco , 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., (© 2023 John Wiley & Sons Ltd.)

Warming of northern high latitude regions (NHL, > 50 °N) has increased both photosynthesis and respiration which results in considerable uncertainty regarding the net carbon dioxide (CO 2 ) balance of NHL ecosystems. Using estimates constrained from atmospheric observations from 1980 to 2017, we find that the increasing trends of net CO 2 uptake in the early-growing season are of similar magnitude across the tree cover gradient in the NHL. However, the trend of respiratory CO 2 loss during late-growing season increases significantly with increasing tree cover, offsetting a larger fraction of photosynthetic CO 2 uptake, and thus resulting in a slower rate of increasing annual net CO 2 uptake in areas with higher tree cover, especially in central and southern boreal forest regions. The magnitude of this seasonal compensation effect explains the difference in net CO 2 uptake trends along the NHL vegetation- permafrost gradient. Such seasonal compensation dynamics are not captured by dynamic global vegetation models, which simulate weaker respiration control on carbon exchange during the late-growing season, and thus calls into question projections of increasing net CO 2 uptake as high latitude ecosystems respond to warming climate conditions., (© 2022. The Author(s).)

Advancing phenology is one of the most visible effects of climate change on plant communities, and has been especially pronounced in temperature-limited tundra ecosystems. However, phenological responses have been shown to differ greatly between species, with some species shifting phenology more than others. We analysed a database of 42,689 tundra plant phenological observations to show that warmer temperatures are leading to a contraction of community-level flowering seasons in tundra ecosystems due to a greater advancement in the flowering times of late-flowering species than early-flowering species. Shorter flowering seasons with a changing climate have the potential to alter trophic interactions in tundra ecosystems. Interestingly, these findings differ from those of warmer ecosystems, where early-flowering species have been found to be more sensitive to temperature change, suggesting that community-level phenological responses to warming can vary greatly between biomes.

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 CO 2 flux than Air warming. Soil warming caused rapid permafrost thaw and increased ecosystem respiration (R eco ), gross primary productivity (GPP), and net summer CO 2 storage (NEE). Over 7 years R eco , 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, R eco , 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 R eco , GPP, and NEE. However R eco 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 R eco in deeply thawed areas during summer months was balanced by GPP. Summer CO 2 flux across treatments fit a single quadratic relationship that captured the functional response of CO 2 flux to thaw, water table depth, and plant biomass. These results demonstrate the importance of indirect thaw effects on CO 2 flux: plant growth and water table dynamics. Nonsummer R eco models estimated that the area was an annual CO 2 source during all years of observation. Nonsummer CO 2 loss in warmer, more deeply thawed soils exceeded the increases in summer GPP, and thawed tundra was a net annual CO 2 source., (© 2017 John Wiley & Sons Ltd.)

The distribution of contaminant elements within ecosystems is an environmental concern because of these elements' potential toxicity to animals and plants and their ability to hinder microbial ecosystem services. As with nutrients, contaminants are cycled within and through ecosystems. Elevated atmospheric CO2 generally increases plant productivity and alters nutrient element cycling, but whether CO2 causes similar effects on the cycling of contaminant elements is unknown. Here we show that 11 years of experimental CO2 enrichment in a sandy soil with low organic matter content causes plants to accumulate contaminants in plant biomass, with declines in the extractable contaminant element pools in surface soils. These results indicate that CO2 alters the distribution of contaminant elements in ecosystems, with plant element accumulation and declining soil availability both likely explained by the CO2 stimulation of plant biomass. Our results highlight the interdependence of element cycles and the importance of taking a broad view of the periodic table when the effects of global environmental change on ecosystem biogeochemistry are considered.