Abstract
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 (
14
C) to quantify the release of this “old” SOC as CO
2
or CH
4
to the atmosphere or as dissolved and particulate organic carbon (DOC and POC) to surface waters. We compiled ~1,900
14
C 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 soil
14
C‐CO
2
emissions generally had a modern (post‐1950s) signature, but that well‐drained, oxic soils had increased CO
2
emissions derived from older sources following recent thaw. The age of CO
2
and CH
4
emitted 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 CO
2
, CH
4
, 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 future
14
C studies in the permafrost region.
Key Points
We compiled ~1,900
14
C measurements of CO
2
, CH
4
, DOC, and POC from the northern permafrost region
Old carbon release increases in thawed oxic soils (CO
2
), thermokarst lakes (CH
4
and CO
2
), and headwaters with thermal erosion (DOC and POC)
Simultaneous and year‐long
14
C analyses of CO
2
, CH
4
, DOC, and POC are needed to assess the vulnerability of permafrost carbon across ecosystems
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
flux than Air warming. Soil warming caused rapid permafrost thaw and increased ecosystem respiration (R
), gross primary productivity (GPP), and net summer CO
storage (NEE). Over 7 years R
, 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
, 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
, GPP, and NEE. However R
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
in deeply thawed areas during summer months was balanced by GPP. Summer CO
flux across treatments fit a single quadratic relationship that captured the functional response of CO
flux to thaw, water table depth, and plant biomass. These results demonstrate the importance of indirect thaw effects on CO
flux: plant growth and water table dynamics. Nonsummer R
models estimated that the area was an annual CO
source during all years of observation. Nonsummer CO
loss in warmer, more deeply thawed soils exceeded the increases in summer GPP, and thawed tundra was a net annual CO
source.
Transpiration and stomatal conductance in deciduous needleleaf boreal forests of northern Siberia can be highly sensitive to water stress, permafrost thaw, and atmospheric dryness. Additionally, ...north‐eastern Siberian boreal forests are fire‐driven, and larch (Larix spp.) are the sole tree species. We examined differences in tree water use, stand characteristics, and stomatal responses to environmental drivers between high and low tree density stands that burned 76 years ago in north‐eastern Siberia. Our results provide process‐level insight to climate feedbacks related to boreal forest productivity, water cycles, and permafrost across Arctic regions. The high density stand had shallower permafrost thaw depths and deeper moss layers than the low density stand. Rooting depths and shallow root biomass were similar between stands. Daily transpiration was higher on average in the high‐density stand 0.12 L m−2 day−1 (SE: 0.004) compared with the low density stand 0.10 L m−2 day−1 (SE: 0.001) throughout the abnormally wet summer of 2016. Transpiration rates tended to be similar at both stands during the dry period in 2017 in both stands of 0.10 L m−2 day−1 (SE: 0.002). The timing of precipitation impacted stomatal responses to environmental drivers, and the high density stand was more dependent on antecedent precipitation that occurred over longer periods in the past compared with the low density stand. Post‐fire tree density differences in plant–water relations may lead to different trajectories in plant mortality, water stress, and ecosystem water cycles across Siberian landscapes.
Molybdenum (Mo) is critical for the function of enzymes related to nitrogen cycling. Concentrations of Mo are very low in sandy, acidic soils, and biologically available Mo is only a small fraction ...of the total pool. While several methods have been proposed to measure plant-available Mo, there has not been a recent comprehensive analytical study that compares soil extraction methods as predictors of plant Mo uptake. A suite of five assays total acid microwave digestion, ethylenediamenetetraaacetic acid (EDTA) extraction, Environmental Protection Agency (EPA) protocol 3050B, ammonium oxalate extraction, and pressurized hot water was employed, followed by the determination of soil Mo concentrations via inductively coupled mass spectroscopy. The concentrations of soil Mo determined from these assays and their relationships as predictors of plant Mo concentration were compared. The assays yielded different concentrations of Mo: total digest > EPA > ammonium oxalate ≥ EDTA > pressurized hot water. Legume foliar Mo concentrations were most strongly correlated with ammonium oxalate–extractable Mo from soils, but an oak species showed no relationship with any soil Mo fraction and foliar Mo. Bulk fine roots in the 10- to 30-cm soil horizon were significantly correlated with the ammonium oxalate Mo fraction. There were significant correlations between ammonium oxalate Mo and the oxides of iron (Fe), manganese (Mn), and aluminum (Al). Results suggest that the ammonium oxalate extraction for soil Mo is the best predictor of plant-available Mo for species with high Mo requirements such as legumes and that plant-available Mo tracks strongly with other metal oxides in sandy, acidic soils.
Rapid climate warming at northern high latitudes is driving geomorphic changes across the permafrost zone. In the Yamal and Gydan peninsulas in western Siberia, subterranean accumulation of methane ...beneath or within ice-rich permafrost can create mounds at the land surface. Once over-pressurized by methane, these mounds can explode and eject frozen ground, forming a gas emission crater (GEC). While GECs pose a hazard to human populations and infrastructure, only a small number have been identified in the Yamal and Gydan peninsulas, where the regional distribution and frequency of GECs and other types of land surface change are relatively unconstrained. To understand the distribution of landscape change within 327,000 km2 of the Yamal-Gydan region, we developed a semi-automated multivariate change detection algorithm using satellite-derived surface reflectance, elevation, and water extent in the Google Earth Engine cloud computing platform. We found that 5% of the landscape changed from 1984 to 2017. The algorithm detected all seven GECs reported in the scientific literature and three new GEC-like features, and further revealed that retrogressive thaw slumps were more abundant than GECs. Our methodology can be refined to detect and better understand diverse types of land surface change and potentially mitigate risks across the northern permafrost zone.
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.
In post‐fire Siberian larch forests, where tree density can vary within a burn perimeter, shrubs constitute a substantial portion of the vegetation canopy. Leaf area index (LAI), defined as the ...one‐sided total green leaf area per unit ground surface area, is useful for characterizing variation in plant canopies. We estimated LAI with allometry for trees and tall shrubs (>0.5 and <1.5 m) across 26 sites with varying tree stem density (0.05–3.3 stems/m2) and canopy cover (4.6%–76.9%) in a uniformly‐aged mature Siberian larch forest that regenerated following a fire ∼75 years ago. We investigated relationships between tree density, tree LAI, and tall shrub LAI, and between LAI and satellite observations of Normalized Difference and Enhanced Vegetation Indices (NDVI and EVI). Across the density gradient, tree LAI increases with increasing tree density, while tall shrub LAI decreases, exhibiting no patterns in combined tree‐shrub LAI. We also found significant positive relationships between tall shrub LAI and NDVI/EVI from PlanetScope and Landsat imagery. These findings suggest that tall shrubs compensate for lower tree LAI in tree canopy gaps, forming a canopy with contiguous combined tree‐shrub LAI across the density gradient. Our findings suggest that NDVI and EVI are more sensitive to variation in tall shrub canopies than variation in tree canopies or combined tree‐shrub canopies in these ecosystems. The results improve our understanding of the relationships between forest density and tree and shrub leaf area and have implications for interpreting spatial variability in LAI, NDVI, and EVI in Siberian boreal forests.
Plain Language Summary
After wildfires burn forests in northeast Siberia, they often grow back unevenly, with some sections containing many more trees than others. Sections with more trees have a higher capacity to take up carbon and higher rates of energy production, which has important implications for climate change. To investigate how vegetation varies across sections of a forest which burned in 1940, we estimated the separate and combined contributions of trees and tall shrubs (>0.5 and <1.5 m) in high, medium, and low density sections using tree and shrub stem diameter measurements. We estimated the canopy vegetation in each section of forest by calculating the total area of leaves in the section and dividing it by the total ground area, producing the leaf area index (LAI). In sections with less dense tree cover, tall shrubs made up for lower tree leaf area, and the combined leaf area of trees and tall shrubs was consistent across the sections of different tree density. We also compared our leaf area measurements with measures of vegetation productivity produced from satellite imagery, finding that the satellite measures were correlated with tall shrub LAI, but not with tree LAI or combined LAI from trees and shrubs.
Key Points
Tall shrubs compensate for lower tree leaf area in low density larch forests
Combined leaf area of trees and tall shrubs is consistent across a range of forest tree densities
Satellite‐derived v
egetation indices are more closely linked to shrub LAI than tree LAI or combined tree‐shr LAI
Future warming of the Arctic not only threatens to destabilize the enormous pool of organic carbon accumulated in permafrost soils but may also mobilize elements such as calcium (Ca) or silicon (Si). ...While for Greenlandic soils, it was recently shown that both elements may have a strong effect on carbon dioxide (CO
2
) production with Ca strongly decreasing and Si increasing CO
2
production, little is known about the effects of Si and Ca on carbon cycle processes in soils from Siberia, the Canadian Shield, or Alaska. In this study, we incubated five different soils (rich organic soil from the Canadian Shield and from Siberia (one from the top and one from the deeper soil layer) and one acidic and one non-acidic soil from Alaska) for 6 months under both drained and waterlogged conditions and at different Ca and amorphous Si (ASi) concentrations. Our results show a strong decrease in soil CO
2
production for all soils under both drained and waterlogged conditions with increasing Ca concentrations. The ASi effect was not clear across the different soils used, with soil CO
2
production increasing, decreasing, or not being significantly affected depending on the soil type and if the soils were initially drained or waterlogged. We found no methane production in any of the soils regardless of treatment. Taking into account the predicted change in Si and Ca availability under a future warmer Arctic climate, the associated fertilization effects would imply potentially lower greenhouse gas production from Siberia and slightly increased greenhouse gas emissions from the Canadian Shield. Including Ca as a controlling factor for Arctic soil CO
2
production rates may, therefore, reduces uncertainties in modeling future scenarios on how Arctic regions may respond to climate change.
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.
•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.
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