Reduced arctic tundra productivity linked with landform and climate change interactions

Dealing with sand in the Arctic city of Nadym

Sand plays an important role in the Arctic urban development as construction material and stable ground. Significance of its studies increases in face of permafrost degradation and coastal erosion and for understanding human capacities to restore natural landscapes after anthropogenic disturbances. This paper examines changing human interactions with sand in the city of Nadym, northwest of Siberia. The study utilizes an interdisciplinary approach which includes remote sensing and GIS analysis, field observations, and interviews with local residents and stakeholders. Analysis of spatial and social characteristics of sand demonstrates different roles of sand as part of the landscape, a resource, and as a mediator in urban and infrastructure development. Understanding the diversity of sand qualities, its uses, and perceptions is relevant for studies of landscape disturbances, resilience, vulnerability, and adaptive capacities of Arctic cities.

No Signs of Long-term Greening Trend in Western Mongolian Grasslands

Trends for increased vegetation greenness based on satellite-derived data have been repeatedly published for the temperate grassland biome (including forest steppes) of eastern Inner Asia since 1982. Although this greening trend has been attenuated or partially reversed by drought in the early twenty-first century, linear increases in the Normalized Difference Vegetation Index (NDVI) or other parameters of vegetation greenness are nevertheless evident when the period since 1982 is regarded. However, the question arises whether these trends are part of a long-term trend driven by climate change, as simultaneously forests in the region show widespread drought-induced growth reductions and mortality outbreaks. Therefore, we hypothesized that the post-1982 greening trend was neither part of a long-term trend nor unprecedented. To test this hypothesis, we analyzed monthly maximum NDVI data from AVHRR time series and correlated these data with standardized tree-ring data of Larix sibirica from two regions of western Mongolia. We used linear regression to model the NDVI from tree-ring anomalies and to reconstruct the NDVI since 1940. These reconstructions show that the availability of satellite-based NDVI data coincidentally began during a dry period of low vegetation greenness in the early 1980s and was followed by a wet phase in the 1990s, producing the linear greening trend. No positive long-term trend in the reconstructed NDVI was observed from 1940 to 2010. This result rules out a recent climate change-driven greening trend for the grasslands and forest steppes of western Mongolia and calls into question its existence for all of eastern Inner Asia.

NDVI changes in the Arctic: Functional significance in the moist acidic tundra of Northern Alaska

The Normalized Difference Vegetation Index (NDVI), derived from reflected visible and infrared radiation, has been critical to understanding change across the Arctic, but relatively few ground truthing efforts have directly linked NDVI to structural and functional properties of Arctic tundra ecosystems. To improve the interpretation of changing NDVI within moist acidic tundra (MAT), a common Arctic ecosystem, we coupled measurements of NDVI, vegetation structure, and CO2 flux in seventy MAT plots, chosen to represent the full range of typical MAT vegetation conditions, over two growing seasons. Light-saturated photosynthesis, ecosystem respiration, and net ecosystem CO2 exchange were well predicted by NDVI, but not by vertically-projected leaf area, our nondestructive proxy for leaf area index (LAI). Further, our data indicate that NDVI in this ecosystem is driven primarily by the biochemical properties of the canopy leaves of the dominant plant functional types, rather than purely the amount of leaf area; NDVI was more strongly correlated with top cover and repeated cover of deciduous shrubs than other plant functional types, a finding supported by our data from separate "monotypic" plots. In these pure stands of a plant functional type, deciduous shrubs exhibited higher NDVI than any other plant functional type. Likewise, leaves from the two most common deciduous shrubs, Betula nana and Salix pulchra, exhibited higher leaf-level NDVI than those from the codominant graminoid, Eriophorum vaginatum. Our findings suggest that recent increases in NDVI in MAT in the North American Arctic are largely driven by expanding deciduous shrub canopies, with substantial implications for MAT ecosystem function, especially net carbon uptake.

Improving ecological insights from dendroecological studies of Arctic shrub dynamics: Research gaps and potential solutions

Rapid climate change has been driving changes in Arctic vegetation in recent decades, with increased shrub dominance in many tundra ecosystems. Dendroecological observations of tundra shrubs can provide insight into current and past growth and recruitment patterns, both key components for understanding and predicting ongoing and future Arctic shrub dynamics. However, generalizing these dynamics is challenging as they are highly scale-dependent and vary among sites, species, and individuals. Here, we provide a perspective on how some of these challenges can be overcome. Based on a targeted literature search of dendrochronological studies from 2005 to 2022, we highlight five research gaps that currently limit dendro-based studies from revealing cross-scale ecological insight into shrub dynamics across the Arctic biome. We further discuss the related research priorities, suggesting that future studies could consider: 1) increasing focus on intra- and interspecific variation, 2) including demographic responses other than radial growth, 3) incorporating drivers, in addition to warming, at different spatial and temporal scales, 4) implementing systematic and unbiased sampling approaches, and 5) investigating the cellular mechanisms behind the observed responses. Focusing on these aspects in dendroecological studies could improve the value of the field for addressing cross-scale and plant community-framed ecological questions. We outline how this could be facilitated through the integration of community-based dendroecology and dendroanatomy with remote sensing approaches. Integrating new technologies and a more multidisciplinary approach in dendroecological research could provide key opportunities to close important knowledge gaps in our understanding of scale-dependencies, as well as intra- and inter-specific variation, in vegetation community dynamics across the Arctic tundra.

Cross-scale regulation of seasonal microclimate by vegetation and snow in the Arctic tundra

Climate warming is inducing widespread vegetation changes in Arctic tundra ecosystems, with the potential to alter carbon and nutrient dynamics between vegetation and soils. Yet, we lack a detailed understanding of how variation in vegetation and topography influences fine-scale temperatures ("microclimate") that mediate these dynamics, and at what resolution vegetation needs to be sampled to capture these effects. We monitored microclimate at 90 plots across a tundra landscape in western Greenland. Our stratified random study design covered gradients of topography and vegetation, while nested plots (0.8-100 m² ) enabled comparison across different sampling resolutions. We used Bayesian mixed-effect models to quantify the direct influence of plot-level topography, moisture and vegetation on soil, near-surface and canopy-level temperatures (-6, 2, and 15 cm). During the growing season, colder soils were predicted by shrub cover (-0.24°C per 10% increase), bryophyte cover (-0.35°C per 10% increase), and vegetation height (-0.17°C per 1 cm increase). The same three factors also predicted the magnitude of differences between soil and above-ground temperatures, indicating warmer soils at low cover/height, but colder soils under closed/taller canopies. These findings were consistent across plot sizes, suggesting that spatial predictions of microclimate may be possible at the operational scales of satellite products. During winter, snow cover (+0.75°C per 10 snow-covered days) was the key predictor of soil microclimate. Topography and moisture explained little variation in the measured temperatures. Our results not only underline the close connection of vegetation and snow with microclimate in the Arctic tundra but also point to the need for more studies disentangling their complex interplay across tundra environments and seasons. Future shifts in vegetation cover and height will likely mediate the impact of atmospheric warming on the tundra soil environment, with potential implications for below-ground organisms and ecosystem functioning.

Shrubification along Pipeline Corridors in Permafrost Regions

Pipeline corridors have been rapidly increasing in length and density because of the ever growing demand for crude oil and natural gas resources in hydrocarbon-rich permafrost regions. Pipeline engineering activities have significant implications for the permafrost environment in cold regions. Along these pipeline corridors, the shrubification in the right-of-way (ROW) has been extensively observed during vegetation recovery. However, the hydrothermal mechanisms of this ROW shrubification have seldom been studied and thus remain poorly understood. This paper reviews more than 112 articles mainly published from 2000 to 2022 and focuses on the hydrothermal mechanisms of shrubification associated with environmental changes induced by the rapidly degrading permafrost from pipeline construction and around the operating pipelines under a warming climate. First, the shrubification from pipeline construction and operation and the ensuing vegetation clearance are featured. Then, key permafrost-related ROW shrubification mechanisms (e.g., from the perspectives of warmer soil, soil moisture, soil type, soil nutrients, topography and landscapes, and snow cover) are discussed. Other key influencing factors on these hydrothermal and other mechanisms are hierarchically documented as well. In the end, future research priorities are identified and proposed. We call for prioritizing more systematic and in-depth investigations and surveys, laboratory testing, long-term field monitoring, and numerical modeling studies of the ROW shrubification along oil and gas pipelines in permafrost regions, such as in boreal and arctic zones, as well as in alpine and high-plateau regions. This review can improve our understanding of shrubification mechanisms under pipeline disturbances and climate changes and help to better manage the ecological environment along pipeline corridors in permafrost regions.

From Intra-plant to Regional Scale: June Temperatures and Regional Climates Directly and Indirectly Control Betula nana Growth in Arctic Alaska

Tundra shrubs reflect climate sensitivities in their growth-ring widths, yet tissue-specific shrub chronologies are poorly studied. Further, the relative importance of regional climate patterns that exert mesoscale precipitation and temperature influences on tundra shrub growth has been explored in only a few Arctic locations. Here, we investigate Betula nana growth-ring chronologies from adjacent dry heath and moist tussock tundra habitats in arctic Alaska in relation to local and regional climate. Mean shrub and five tissue-specific ring width chronologies were analyzed using serial sectioning of above- and below-ground shrub organs, resulting in 30 shrubs per site with 161 and 104 cross sections from dry and moist tundra, respectively. Betula nana growth-ring widths in both habitats were primarily related to June air temperature (1989–2014). The strongest relationships with air temperature were found for ‘Branch2’ chronologies (dry site: r = 0.78, June 16, DOY = 167; moist site: r = 0.75, June 9, DOY = 160). Additionally, below-ground chronologies (‘Root’ and ‘Root2’) from the moist site were positively correlated with daily mean air temperatures in the previous late-June (‘Root2’ chronology: r = 0.57, pDOY = 173). Most tissue-specific chronologies exhibited the strongest correlations with daily mean air temperature during the period between 8 and 20 June. Structural equation modeling indicated that shrub growth is indirectly linked to regional Arctic and Pacific Decadal Oscillation (AO and PDO) climate indices through their relation to summer sea ice extent and air temperature. Strong dependence of Betula nana growth on early growing season temperature indicates a highly coordinated allocation of resources to tissue growth, which might increase its competitive advantage over other shrub species under a rapidly changing Arctic climate.

Increased Arctic NO3− Availability as a Hydrogeomorphic Consequence of Permafrost Degradation and Landscape Drying

Climate-driven permafrost thaw alters the strongly coupled carbon and nitrogen cycles within the Arctic tundra, influencing the availability of limiting nutrients including nitrate (NO3−). Researchers have identified two primary mechanisms that increase nitrogen and NO3− availability within permafrost soils: (1) the ‘frozen feast’, where previously frozen organic material becomes available as it thaws, and (2) ‘shrubification’, where expansion of nitrogen-fixing shrubs promotes increased soil nitrogen. Through the synthesis of original and previously published observational data, and the application of multiple geospatial approaches, this study investigates and highlights a third mechanism that increases NO3− availability: the hydrogeomorphic evolution of polygonal permafrost landscapes. Permafrost thaw drives changes in microtopography, increasing the drainage of topographic highs, thus increasing oxic conditions that promote NO3− production and accumulation. We extrapolate relationships between NO3− and soil moisture in elevated topographic features within our study area and the broader Alaskan Coastal Plain and investigate potential changes in NO3− availability in response to possible hydrogeomorphic evolution scenarios of permafrost landscapes. These approximations indicate that such changes could increase Arctic tundra NO3− availability by ~250–1000%. Thus, hydrogeomorphic changes that accompany continued permafrost degradation in polygonal permafrost landscapes will substantially increase soil pore water NO3− availability and boost future fertilization and productivity in the Arctic.

Earlier snowmelt may lead to late season declines in plant productivity and carbon sequestration in Arctic tundra ecosystems

Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO2 later in the season.

Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities

As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near Utqiaġvik to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.

Biophysical Determinants of Shifting Tundra Vegetation Productivity in the Beaufort Delta Region of Canada

Temperature increases across the circumpolar north have driven rapid increases in vegetation productivity, often described as ‘greening’. These changes have been widespread, but spatial variation in their pattern and magnitude suggests that biophysical factors also influence the response of tundra vegetation to climate warming. In this study, we used field sampling of soils and vegetation and random forests modeling to identify the determinants of trends in Landsat-derived Enhanced Vegetation Index, a surrogate for productivity, in the Beaufort Delta region of Canada between 1984 and 2016. This region has experienced notable change, with over 71% of the Tuktoyaktuk Coastlands and over 66% of the Yukon North Slope exhibiting statistically significant greening. Using both classification and regression random forests analyses, we show that increases in productivity have been more widespread and rapid at low-to-moderate elevations and in areas dominated by till blanket and glaciofluvial deposits, suggesting that nutrient and moisture availability mediate the impact of climate warming on tundra vegetation. Rapid greening in shrub-dominated vegetation types and observed increases in the cover of low and tall shrub cover (4.8% and 6.0%) also indicate that regional changes have been driven by shifts in the abundance of these functional groups. Our findings demonstrate the utility of random forests models for identifying regional drivers of tundra vegetation change. To obtain additional fine-grained insights on drivers of increased tundra productivity, we recommend future research combine spatially comprehensive time series satellite data (as used herein) with samples of high spatial resolution imagery and integrated field investigations.

Arctic Tundra Land Cover Classification on the Beaufort Coast Using the Kennaugh Element Framework on Dual-Polarimetric TerraSAR-X Imagery

Arctic tundra landscapes are highly complex and are rapidly changing due to the warming climate. Datasets that document the spatial and temporal variability of the landscape are needed to monitor the rapid changes. Synthetic Aperture Radar (SAR) imagery is specifically suitable for monitoring the Arctic, as SAR, unlike optical remote sensing, can provide time series regardless of weather and illumination conditions. This study examines the potential of seasonal backscatter mechanisms in Arctic tundra environments for improving land cover classification purposes by using a time series of HH/HV TerraSAR-X (TSX) imagery. A Random Forest (RF) classification was applied on multi-temporal Sigma Nought intensity and multi-temporal Kennaugh matrix element data. The backscatter analysis revealed clear differences in the polarimetric response of water, soil, and vegetation, while backscatter signal variations within different vegetation classes were more nuanced. The RF models showed that land cover classes could be distinguished with 92.4% accuracy for the Kennaugh element data, compared to 57.7% accuracy for the Sigma Nought intensity data. Texture predictors, while improving the classification accuracy on the one hand, degraded the spatial resolution of the land cover product. The Kennaugh elements derived from TSX winter acquisitions were most important for the RF model, followed by the Kennaugh elements derived from summer and autumn acquisitions. The results of this study demonstrate that multi-temporal Kennaugh elements derived from dual-polarized X-band imagery are a powerful tool for Arctic tundra land cover mapping.

Urbanization Affects Soil Microbiome Profile Distribution in the Russian Arctic Region

Urbanization in the Arctic results in considerable and still poorly known environmental consequences. The effect of urbanization on soil microbiome-an ecosystem component highly sensitive to anthropogenic disturbance-remains overlooked for the Arctic region. The research compared chemical and microbial properties of the natural Podzol soils and urban soils of Murmansk-the largest Arctic city. Particular attention was given to the profile distribution, which is almost completely ignored by most microbial studies. Soil microbiome was investigated by the quantitative indicators based on fluorescence microscopy (microbial biomass) and PCR real-time methods (amount of rRNA genes copies of archaea, bacteria, and fungi). The principal changes in urban soils' properties compared to the natural references included a shift in pH and an increase in C and nutrients' contents, especially remarkable for the subsoil. The numbers of rRNA genes copies of archaea, bacteria, and fungi in urban topsoils (10⁶-10¹⁰, 10⁹-10¹⁰, and 10⁷-10⁹, respectively) were lower than in Podzol; however, the opposite pattern was shown for the subsoil. Similarly, the total microbial biomass in urban topsoils (0.55-0.75 mg g^-1) was lower compared to the 1.02 mg g^-1 in Podzols, while urban subsoil microbial biomass was 2-2.5 times higher than in the natural conditions. Both for urban and natural soils and throughout the profiles, fungi were dominated by mycelium forms; however, the ratios of mycelium-spores were lower, and the amount of thin mycelium was higher in urban soils than in natural Podzols. Urbanization in the Arctic altered soil morphological and chemical properties and created a new niche for microbial development in urban subsoils; its contribution to biodiversity and nutrient cycling promises to become increasingly important under projected climate change.

Vegetation grows more luxuriantly in Arctic permafrost drained lake basins

As Arctic warming, permafrost thawing, and thermokarst development intensify, increasing evidence suggests that the frequency and magnitude of thermokarst lake drainage events are increasing. Presently, we lack a quantitative understanding of vegetation dynamics in drained lake basins, which is necessary to assess the extent to which plant growth in thawing ecosystems will offset the carbon released from permafrost. In this study, continuous satellite observations were used to detect thermokarst lake drainage events in northern Alaska over the past 20 years, and an advanced temporal segmentation and change detection algorithm allowed us to determine the year of drainage for each lake. Quantitative analysis showed that the greenness (normalized difference vegetation index [NDVI]) of tundra vegetation growing on wet and nutrient-rich lake sediments increased approximately 10 times faster than that of the peripheral vegetation. It takes approximately 5 years (4-6 years for the 25%-75% range) for the drainage lake area to reach the greenness level of the peripheral vegetation. Eventually, the NDVI values of the drained lake basins were 0.15 (or 25%) higher than those of the surrounding areas. In addition, we found less lush vegetation in the floodplain drained lake basins, possibly due to water logging. We further explored the key environmental drivers affecting vegetation dynamics in and around the drained lake basins. The results showed that our multivariate regression model well simulated the growth dynamics of the drainage lake ecosystem ( Radj2=.73 , p < .001) and peripheral vegetation ( Radj2=.68 , p < .001). Among climate variables, moisture variables were more influential than temperature variables, indicating that vegetation growth in this area is susceptible to water stress. Our study provides valuable information for better modeling of vegetation dynamics in thermokarst lake areas and provides new insights into Arctic greening and carbon balance studies as thermokarst lake drainage intensifies.

Remote Sensing-Based Statistical Approach for Defining Drained Lake Basins in a Continuous Permafrost Region, North Slope of Alaska

Lake formation and drainage are pervasive phenomena in permafrost regions. Drained lake basins (DLBs) are often the most common landforms in lowland permafrost regions in the Arctic (50% to 75% of the landscape). However, detailed assessments of DLB distribution and abundance are limited. In this study, we present a novel and scalable remote sensing-based approach to identifying DLBs in lowland permafrost regions, using the North Slope of Alaska as a case study. We validated this first North Slope-wide DLB data product against several previously published sub-regional scale datasets and manually classified points. The study area covered >71,000 km2, including a >39,000 km2 area not previously covered in existing DLB datasets. Our approach used Landsat-8 multispectral imagery and ArcticDEM data to derive a pixel-by-pixel statistical assessment of likelihood of DLB occurrence in sub-regions with different permafrost and periglacial landscape conditions, as well as to quantify aerial coverage of DLBs on the North Slope of Alaska. The results were consistent with previously published regional DLB datasets (up to 87% agreement) and showed high agreement with manually classified random points (64.4–95.5% for DLB and 83.2–95.4% for non-DLB areas). Validation of the remote sensing-based statistical approach on the North Slope of Alaska indicated that it may be possible to extend this methodology to conduct a comprehensive assessment of DLBs in pan-Arctic lowland permafrost regions. Better resolution of the spatial distribution of DLBs in lowland permafrost regions is important for quantitative studies on landscape diversity, wildlife habitat, permafrost, hydrology, geotechnical conditions, and high-latitude carbon cycling.

Trends in Satellite Earth Observation for Permafrost Related Analyses—A Review

Climate change and associated Arctic amplification cause a degradation of permafrost which in turn has major implications for the environment. The potential turnover of frozen ground from a carbon sink to a carbon source, eroding coastlines, landslides, amplified surface deformation and endangerment of human infrastructure are some of the consequences connected with thawing permafrost. Satellite remote sensing is hereby a powerful tool to identify and monitor these features and processes on a spatially explicit, cheap, operational, long-term basis and up to circum-Arctic scale. By filtering after a selection of relevant keywords, a total of 325 articles from 30 international journals published during the last two decades were analyzed based on study location, spatio-temporal resolution of applied remote sensing data, platform, sensor combination and studied environmental focus for a comprehensive overview of past achievements, current efforts, together with future challenges and opportunities. The temporal development of publication frequency, utilized platforms/sensors and the addressed environmental topic is thereby highlighted. The total number of publications more than doubled since 2015. Distinct geographical study hot spots were revealed, while at the same time large portions of the continuous permafrost zone are still only sparsely covered by satellite remote sensing investigations. Moreover, studies related to Arctic greenhouse gas emissions in the context of permafrost degradation appear heavily underrepresented. New tools (e.g., Google Earth Engine (GEE)), methodologies (e.g., deep learning or data fusion etc.) and satellite data (e.g., the Methane Remote Sensing LiDAR Mission (Merlin) and the Sentinel-fleet) will thereby enable future studies to further investigate the distribution of permafrost, its thermal state and its implications on the environment such as thermokarst features and greenhouse gas emission rates on increasingly larger spatial and temporal scales.

Periglacial Lake Origin Influences the Likelihood of Lake Drainage in Northern Alaska

Nearly 25% of all lakes on earth are located at high latitudes. These lakes are formed by a combination of thermokarst, glacial, and geological processes. Evidence suggests that the origin of periglacial lake formation may be an important factor controlling the likelihood of lakes to drain. However, geospatial data regarding the spatial distribution of these dominant Arctic and subarctic lakes are limited or do not exist. Here, we use lake-specific morphological properties using the Arctic Digital Elevation Model (DEM) and Landsat imagery to develop a Thermokarst lake Settlement Index (TSI), which was used in combination with available geospatial datasets of glacier history and yedoma permafrost extent to classify Arctic and subarctic lakes into Thermokarst (non-yedoma), Yedoma, Glacial, and Maar lakes, respectively. This lake origin dataset was used to evaluate the influence of lake origin on drainage between 1985 and 2019 in northern Alaska. The lake origin map and lake drainage datasets were synthesized using five-year seamless Landsat ETM+ and OLI image composites. Nearly 35,000 lakes and their properties were characterized from Landsat mosaics using an object-based image analysis. Results indicate that the pattern of lake drainage varied by lake origin, and the proportion of lakes that completely drained (i.e., >60% area loss) between 1985 and 2019 in Thermokarst (non-yedoma), Yedoma, Glacial, and Maar lakes were 12.1, 9.5, 8.7, and 0.0%, respectively. The lakes most vulnerable to draining were small thermokarst (non-yedoma) lakes (12.7%) and large yedoma lakes (12.5%), while the most resilient were large and medium-sized glacial lakes (4.9 and 4.1%) and Maar lakes (0.0%). This analysis provides a simple remote sensing approach to estimate the spatial distribution of dominant lake origins across variable physiography and surficial geology, useful for discriminating between vulnerable versus resilient Arctic and subarctic lakes that are likely to change in warmer and wetter climates.

The Shrinking Resource Base of Pastoralism: Saami Reindeer Husbandry in a Climate of Change

The productive performance of large ungulates in extensive pastoral grazing systems is modulated simultaneously by the effects of climate change and human intervention independent of climate change. The latter includes the expansion of private, civil and military activity and infrastructure and the erosion of land rights. We used Saami reindeer husbandry in Norway as a model in which to examine trends in, and to compare the influence of, both effects on a pastoral grazing system. Downscaled projections of mean annual temperature over the principal winter pasture area (Finnmarksvidda) closely matched empirical observations across 34 years to 2018. The area, therefore, is not only warming but seems likely to continue to do so. Warming notwithstanding, 50-year (1969–2018) records of local weather (temperature, precipitation and characteristics of the snowpack) demonstrate considerable annual and decadal variation which also seems likely to continue and alternately to amplify and to counter net warming. Warming, moreover, has both positive and negative effects on ecosystem services that influence reindeer. The effects of climate change on reindeer pastoralism are evidently neither temporally nor spatially uniform, nor indeed is the role of climate change as a driver of change in pastoralism even clear. The effects of human intervention on the system, by contrast, are clear and largely negative. Gradual liberalization of grazing rights from the 18th Century has been countered by extensive loss of reindeer pasture. Access to ~50% of traditional winter pasture was lost in the 19th Century owing to the closure of international borders to the passage of herders and their reindeer. Subsequent to this the area of undisturbed pasture within Norway has decreased by 71%. Loss of pasture due to piecemeal development of infrastructure and to administrative encroachment that erodes herders' freedom of action on the land that remains to them, are the principal threats to reindeer husbandry in Norway today. These tangible effects far exceed the putative effects of current climate change on the system. The situation confronting Saami reindeer pastoralism is not unique: loss of pasture and administrative, economic, legal and social constraints bedevil extensive pastoral grazing systems across the globe.

Untargeted Exometabolomics Provides a Powerful Approach to Investigate Biogeochemical Hotspots with Vegetation and Polygon Type in Arctic Tundra Soils

Rising temperatures in the Arctic have led to the thawing of tundra soils, which is rapidly changing terrain, hydrology, and plant and microbial communities, causing hotspots of biogeochemical activity across the landscape. Despite this, little is known about how nutrient-rich low molecular weight dissolved organic matter (LMW DOM) varies within and across tundra ecosystems. Using a high-resolution nano-liquid chromatography-mass spectrometry (LC/MS) approach, we characterized the composition and availability of LMW DOM from high-centered polygons (HCP) and low-centered polygons (LCP) with Eriophorum angustifolium or Carex aquatilis as the dominant vegetation. Over 3000 unique features (i.e., discrete mass/charge ions) were detected; 521 were identified as differentially abundant between polygonal types and 217 were putatively annotated using high mass accuracy MS data. While polygon type was a strong predictor of LMW DOM composition and availability, vegetation and soil depth were also important drivers. Extensive evidence was found for enhanced microbial processing at the LCP sites, which were dominated by Carex plant species. We detected significant differences between polygon types with varying aboveground landscape features or properties, and hotspots of biogeochemical activity, indicating LMW DOM, as quantified by untargeted exometabolomics, provides a window into the dynamic complex interactions between landscape topography, vegetation, and organic matter cycling in Arctic polygonal tundra soils.

Divergence of Arctic shrub growth associated with sea ice decline

Arctic sea ice extent (SIE) is declining at an accelerating rate with a wide range of ecological consequences. However, determining sea ice effects on tundra vegetation remains a challenge. In this study, we examined the universality or lack thereof in tundra shrub growth responses to changes in SIE and summer climate across the Pan-Arctic, taking advantage of 23 tundra shrub-ring chronologies from 19 widely distributed sites (56°N to 83°N). We show a clear divergence in shrub growth responses to SIE that began in the mid-1990s, with 39% of the chronologies showing declines and 57% showing increases in radial growth (decreasers and increasers, respectively). Structural equation models revealed that declining SIE was associated with rising air temperature and precipitation for increasers and with increasingly dry conditions for decreasers. Decreasers tended to be from areas of the Arctic with lower summer precipitation and their growth decline was related to decreases in the standardized precipitation evapotranspiration index. Our findings suggest that moisture limitation, associated with declining SIE, might inhibit the positive effects of warming on shrub growth over a considerable part of the terrestrial Arctic, thereby complicating predictions of vegetation change and future tundra productivity.

Assessment of Spatio-Temporal Landscape Changes from VHR Images in Three Different Permafrost Areas in the Western Russian Arctic

Our study highlights the usefulness of very high resolution (VHR) images to detect various types of disturbances over permafrost areas using three example regions in different permafrost zones. The study focuses on detecting subtle changes in land cover classes, thermokarst water bodies, river dynamics, retrogressive thaw slumps (RTS) and infrastructure in the Yamal Peninsula, Urengoy and Pechora regions. Very high-resolution optical imagery (sub-meter) derived from WorldView, QuickBird and GeoEye in conjunction with declassified Corona images were involved in the analyses. The comparison of very high-resolution images acquired in 2003/2004 and 2016/2017 indicates a pronounced increase in the extent of tundra and a slight increase of land covered by water. The number of water bodies increased in all three regions, especially in discontinuous permafrost, where 14.86% of new lakes and ponds were initiated between 2003 and 2017. The analysis of the evolution of two river channels in Yamal and Urengoy indicates the dominance of erosion during the last two decades. An increase of both rivers’ lengths and a significant widening of the river channels were also observed. The number and total surface of RTS in the Yamal Peninsula strongly increased between 2004 and 2016. A mean annual headwall retreat rate of 1.86 m/year was calculated. Extensive networks of infrastructure occurred in the Yamal Peninsula in the last two decades, stimulating the initiation of new thermokarst features. The significant warming and seasonal variations of the hydrologic cycle, in particular, increased snow water equivalent acted in favor of deepening of the active layer; thus, an increasing number of thermokarst lake formations.

Local-scale Arctic tundra heterogeneity affects regional-scale carbon dynamics

In northern Alaska nearly 65% of the terrestrial surface is composed of polygonal ground, where geomorphic tundra landforms disproportionately influence carbon and nutrient cycling over fine spatial scales. Process-based biogeochemical models used for local to Pan-Arctic projections of ecological responses to climate change typically operate at coarse-scales (1km2-0.5°) at which fine-scale (<1km2) tundra heterogeneity is often aggregated to the dominant land cover unit. Here, we evaluate the importance of tundra heterogeneity for representing soil carbon dynamics at fine to coarse spatial scales. We leveraged the legacy of data collected near Utqiaġvik, Alaska between 1973 and 2016 for model initiation, parameterization, and validation. Simulation uncertainty increased with a reduced representation of tundra heterogeneity and coarsening of spatial scale. Hierarchical cluster analysis of an ensemble of 21st-century simulations reveals that a minimum of two tundra landforms (dry and wet) and a maximum of 4km2 spatial scale is necessary for minimizing uncertainties (<10%) in regional to Pan-Arctic modeling applications.

Lake Drainage in Permafrost Regions Produces Variable Plant Communities of High Biomass and Productivity

Climate warming, increased precipitation, and permafrost thaw in the Arctic are accompanied by an increase in the frequency of full or partial drainage of thermokarst lakes. After lake drainage, highly productive plant communities on nutrient-rich sediments may develop, thus increasing the influencing greening trends of Arctic tundra. However, the magnitude and extent of this process remain poorly understood. Here we characterized plant succession and productivity along a chronosequence of eight drained thermokarst lakes (khasyreys), located in the low-Arctic tundra of the Western Siberian Lowland (WSL), the largest permafrost peatland in the world. Based on a combination of satellite imagery, archive mapping, and radiocarbon dating, we distinguished early (<50 years), mid (50–200 years), and late (200–2000 years) ecosystem stages depending on the age of drainage. In 48 sites within the different aged khasyreys, we measured plant phytomass and productivity, satellite-derived NDVImax, species composition, soil chemistry including nutrients, and plant elementary composition. The annual aboveground net primary productivity of the early and mid khasyrey ranged from 1134 and 660 g·m⁻²·y⁻¹, which is two to nine times higher than that of the surrounding tundra. Late stages exhibited three to five times lower plant productivity and these ecosystems were distinctly different from early and mid-stages in terms of peat thickness and pools of soil nitrogen and potassium. We conclude that the main driving factor of the vegetation succession in the khasyreys is the accumulation of peat and the permafrost aggradation. The soil nutrient depletion occurs simultaneously with a decrease in the thickness of the active layer and an increase in the thickness of the peat. The early and mid khasyreys may provide a substantial contribution to the observed greening of the WSL low-Arctic tundra.

A continental scale spatial investigation of lake sediment organic compositions using sedimentomics

Sedimentomics is a new method used to investigate carbon cycling in sediment organic matter. This untargeted method, based on metabolomics workflows, was used to investigate the molecular composition of sediment organic matter across northern Canada (Nunavut and Northwest Territories). Unique "lake districts" were defined using unsupervised clustering based on changes in sediment organic carbon compositions across space. Supervised machine learning analyses were used to compare the "lake districts" to commonly used regional classification systems like the treeline, ecozones, and/or georegions. Treeline was the best model to explain the compositional variance of sediment organic carbon from lakes across Canada, closely followed by the georegions model. A novel sediment metaphenomics analysis was also applied to determine how well environmental constraints explain the variation of sediment organic matter composition across a continent. We determined that sedimentomics is more informative than traditional measurements (such as total organic carbon) and can be integrated with other "omics" techniques.

Vascular plants of Victoria Island (Northwest Territories and Nunavut, Canada): a specimen-based study of an Arctic flora

Victoria Island in Canada's western Arctic is the eighth largest island in the world and the second largest in Canada. Here, we report the results of a floristic study of vascular plant diversity of Victoria Island. The study is based on a specimen-based dataset comprising 7031 unique collections from the island, including some 2870 new collections gathered between 2008 and 2019 by the authors and nearly 1000 specimens variously gathered by N. Polunin (in 1947), M. Oldenburg (1940s-1950s) and S. Edlund (1980s) that, until recently, were part of the unprocessed backlog of the National Herbarium of Canada and unavailable to researchers. Results are presented in an annotated checklist, including keys and distribution maps for all taxa, citation of specimens, comments on taxonomy, distribution and the history of documentation of taxa across the island, and photographs for a subset of taxa. The vascular plant flora of Victoria Island comprises 38 families, 108 genera, 272 species, and 17 additional taxa. Of the 289 taxa known on the island, 237 are recorded from the Northwest Territories portion of the island and 277 from the Nunavut part. Thirty-nine taxa are known on the island from a single collection, seven from two collections and three from three collections. Twenty-one taxa in eight families are newly recorded for the flora of Victoria Island: Artemisia tilesii, Senecio lugens, Taraxacum scopulorum (Asteraceae); Crucihimalaya bursifolia, Draba fladnizensis, D. juvenilis, D. pilosa, D. simmonsii (Brassicaceae); Carex bigelowii subsp. bigelowii, Eriophorum russeolum subsp. albidum (Cyperaceae); Anthoxanthum monticola subsp. monticola, Bromus pumpellianus, Deschampsia cespitosa subsp. cespitosa, D. sukatschewii, Festuca rubra subsp. rubra, Lolium perenne, Poa pratensis subsp. pratensis (Poaceae); Stuckenia filiformis (Potamogetonaceae); Potentilla × prostrata (Rosaceae); Galium aparine (Rubiaceae); and Salix ovalifolia var. ovalifolia (Salicaceae). Eight of these are new to the flora of the Canadian Arctic Archipelago: Senecio lugens, Draba juvenilis, D. pilosa, Anthoxanthum monticola subsp. monticola, Bromus pumpellianus, Deschampsia cespitosa subsp. cespitosa, Poa pratensis subsp. pratensis and Salix ovalifolia var. ovalifolia. One of these, Galium aparine, is newly recorded for the flora of Nunavut. Four first records for Victoria Island are introduced plants discovered in Cambridge Bay in 2017: three grasses (Festuca rubra subsp. rubra, Lolium perenne, and Poa pratensis subsp. pratensis) and Galium aparine. One taxon, Juncus arcticus subsp. arcticus, is newly recorded from the Northwest Territories. Of the general areas on Victoria Island that have been botanically explored the most, the greatest diversity of vascular plants is recorded in Ulukhaktok (194 taxa) and the next most diverse area is Cambridge Bay (183 taxa). The floristic data presented here represent a new baseline on which continued exploration of the vascular flora of Victoria Island - particularly the numerous areas of the island that remain unexplored or poorly explored botanically - will build.

Identifying historical and future potential lake drainage events on the western Arctic coastal plain of Alaska

Arctic lakes located in permafrost regions are susceptible to catastrophic drainage. In this study, we reconstructed historical lake drainage events on the western Arctic Coastal Plain of Alaska between 1955 and 2017 using USGS topographic maps, historical aerial photography (1955), and Landsat Imagery (ca. 1975, ca. 2000, and annually since 2000). We identified 98 lakes larger than 10 ha that partially (>25% of area) or completely drained during the 62-year period. Decadal-scale lake drainage rates progressively declined from 2.0 lakes/yr (1955-1975), to 1.6 lakes/yr (1975-2000), and to 1.2 lakes/yr (2000-2017) in the ~30,000-km2 study area. Detailed Landsat trend analysis between 2000 and 2017 identified two years, 2004 and 2006, with a cluster (five or more) of lake drainages probably associated with bank overtopping or headward erosion. To identify future potential lake drainages, we combined the historical lake drainage observations with a geospatial dataset describing lake elevation, hydrologic connectivity, and adjacent lake margin topographic gradients developed with a 5-m-resolution digital surface model. We identified ~1900 lakes likely to be prone to drainage in the future. Of the 20 lakes that drained in the most recent study period, 85% were identified in this future lake drainage potential dataset. Our assessment of historical lake drainage magnitude, mechanisms and pathways, and identification of potential future lake drainages provides insights into how arctic lowland landscapes may change and evolve in the coming decades to centuries.

NDVI Changes Show Warming Increases the Length of the Green Season at Tundra Communities in Northern Alaska: A Fine-Scale Analysis

A warming Arctic has been associated with increases in aboveground plant biomass, specifically shrubs, and changes in vegetation cover. However, the magnitude and direction of changes in NDVI have not been consistent across different tundra types. Here we examine the responsiveness of fine-scale NDVI values to experimental warming at eight sites in northern Alaska, United States. Warming in our eight sites ranged in duration from 2‑23 seasons. Dry, wet and moist tundra communities were monitored for canopy surface temperatures and NDVI in ambient and experimentally-warmed plots at near-daily frequencies during the summer of 2017 to assess the impact of the warming treatment on the magnitude and timing of greening. Experimental warming increased canopy-level surface temperatures across all sites (+0.47 to +3.14˚C), with the strongest warming effect occurring during June and July and for the southernmost sites. Green-up was accelerated by warming at six sites, and autumn senescence was delayed at five sites. Warming increased the magnitude of peak NDVI values at five sites, decreased it at one site, and at two sites it did not change. Warming resulted in earlier peak NDVI at three sites and no significant change in the other sites. Shrub and graminoid cover was positively correlated with the magnitude of peak NDVI (r=0.37 to 0.60) while cryptogam influence was mixed. The magnitude and timing of peak NDVI showed considerable variability across sites. Warming extended the duration of the summer green season at most sites due to accelerated greening in the spring and delayed senescence in the autumn. We show that in a warmer Arctic (as simulated by our experiment) the timing and total period of carbon gain may change. Our results suggest these changes are dependent on community composition and abundance of specific growth forms and therefore will likely impact net primary productivity and trophic interactions.

Alder Distribution and Expansion Across a Tundra Hillslope: Implications for Local N Cycling

Increases in the availability of nitrogen (N) may have consequences for plant growth and nutrient cycling in N-limited tundra plant communities. We investigated the impact alder (Alnus viridis spp. fruticosa), an N-fixing deciduous shrub, has on tundra N cycling at a hillslope located on Alaska's Seward Peninsula. We quantified N fixation using 15N2 incubations within two distinct alder communities at this site: alder shrublands located on well-drained, rocky outcroppings in the uplands and alder savannas located in water tracks along the moist toeslope of the hill. Annual N fixation rates in alder shrublands were 1.95 ± 0.68 g N m-2 year-1, leading to elevated N levels in adjacent soils and plants. Alder savannas had lower N fixation rates (0.53 ± 0.19 g N m-2 year-1), perhaps due to low phosphorus availability and poor drainage in these highly organic soil profiles underlain by permafrost. In addition to supporting higher rates of N fixation, tall-statured alder shrublands had different foliar traits than relatively short-statured alder in savannas, providing an opportunity to link N fixation to remotely-sensed variables. We were able to generate a map of the alder shrubland distribution at this site using a multi-sensor fusion approach. The change in alder shrubland distribution through time was also determined from historic aerial and satellite imagery. Analysis of historic imagery showed that the area of alder shrublands at this site has increased by 40% from 1956 to 2014. We estimate this increase in alder shrublands was associated with a 22% increase in N fixation. Our results suggest that expansion of alder shrublands has the potential to substantially alter N cycling, increase plant productivity, and redistribute C storage in upland tundra regions. An improved understanding of the consequences of N fixation within N-limited tundra plant communities will therefore be crucial for predicting the biogeochemistry of these warming ecosystems.

Patterns of Arctic Tundra Greenness Based on Spatially Downscaled Solar-Induced Fluorescence

A general greening trend in the Arctic tundra biome has been indicated by satellite remote sensing data over recent decades. However, since 2011, there have been signs of browning trends in many parts of the region. Previous research on tundra greenness across the Arctic region has relied on the satellite-derived normalized difference vegetation index (NDVI). In this research, we initially used spatially downscaled solar-induced fluorescence (SIF) data to analyze the spatiotemporal variation of Arctic tundra greenness (2007–2013). The results derived from the SIF data were also compared with those from two NDVIs (the Global Inventory Modeling and Mapping Studies NDVI3g and MOD13Q1 NDVI), and the eddy-covariance (EC) observed gross primary production (GPP). It was found that most parts of the Arctic tundra below 75° N were browning (–0.0098 mW/m2/sr/nm/year, where sr is steradian and nm is nanometer) using SIF, whereas spatially and temporally heterogeneous trends (greening or browning) were obtained based on the two NDVI products. This research has further demonstrated that SIF data can provide an alternative direct proxy for Arctic tundra greenness.

Model Simulation and Prediction of Decadal Mountain Permafrost Distribution Based on Remote Sensing Data in the Qilian Mountains from the 1990s to the 2040s

Based on the results of remote sensing data interpretation, this paper aims to simulate and predict the mountain permafrost distribution changes affected by the mean decadal air temperature (MDAT), from the 1990s to the 2040s, in the Qilian Mountains. A bench-mark map is visually interpreted to acquire a mountain permafrost distribution from the 1990s, based on remote sensing images. Through comparison and estimation, a logistical regression model (LRM) is constructed using the bench-mark map, topographic and land coverage factors and MDAT data from the 1990s. MDAT data from the 2010s to the 2040s are predicted according to survey data from meteorological stations. Using the LRM, MDAT data and the factors, the probabilities (p) of decadal mountain permafrost distribution from the 1990s to the 2040s are simulated and predicted. According to the p value, the permafrost distribution statuses are classified as ‘permafrost probable’ (p > 0.7), ‘permafrost possible’ (0.7 ≥ p ≥ 0.3) and ‘permafrost improbable’ (p < 0.3). From the 1990s to the 2040s, the ‘permafrost probable’ type mainly degrades to that of ‘permafrost possible’, with the total area degenerating from 73.5 × 103 km2 to 66.5 × 103 km2. The ‘permafrost possible’ type mainly degrades to that of ‘permafrost impossible’, with a degradation area of 6.5 × 103 km2, which accounts for 21.3% of the total area. Meanwhile, the accuracy of the simulation results can reach about 90%, which was determined by the validation of the simulation results for the 1990s, 2000s and 2010s based on remote sensing data interpretation results. This research provides a way of understanding the mountain permafrost distribution changes affected by the rising air temperature rising over a long time, and can be used in studies of other mountains with similar topographic and climatic conditions.

Bird population changes reconstructed from isotopic signals of peat developed in a nutrient enriched tundra

Five peat sequences were studied to identify the time the little auk Alle alle colonies originated in the Hornsund area (Spitsbergen). Elemental and stable isotope analysis of nitrogen and carbon was applied as markers for bird activity. The peat sequences were dated with ²¹⁰Pb and radiocarbon methods. The results showed that peat development related to seabird activity is significantly older (at least 300 years old) in localities closer to the fjord's mouth (west) than those located deeper in the fjord (east), which are ~100 years old. Isotopic signals indicated that bird activity in the western localities decreased simultaneously with the growth of the eastern colonies. Colonization by birds of new localities correlated with the termination of the Little Ice Age and the meaningful decrease in the glacier area of the region. Hence, we suggest that the availability of new localities for nesting in talus cones, nival moraines and lateral moraines on gentle mountain slopes with south-eastern exposition attracted the little auk due to better thermal conditions, isolation from strong westerly winds and better protection from predation by gull Larus hyperboreus. The expansion of little auks to the new localities was fast (20-30 yrs), and there are no records of changes in bird impacts on the tundra environment after 1920.

Regional Patterns and Asynchronous Onset of Ice-Wedge Degradation since the Mid-20th Century in Arctic Alaska

Ice-wedge polygons are widespread and conspicuous surficial expressions of ground-ice in permafrost landscapes. Thawing of ice wedges triggers differential ground subsidence, local ponding, and persistent changes to vegetation and hydrologic connectivity across the landscape. Here we characterize spatio-temporal patterns of ice-wedge degradation since circa 1950 across environmental gradients on Alaska’s North Slope. We used a spectral thresholding approach validated by field observations to map flooded thaw pits in high-resolution images from circa 1950, 1982, and 2012 for 11 study areas (1577–4460 ha). The total area of flooded pits increased since 1950 at 8 of 11 study areas (median change +3.6 ha; 130.3%). There were strong regional differences in the timing and extent of degradation; flooded pits were already extensive by 1950 on the Chukchi coastal plain (alluvial-marine deposits) and subsequent changes there indicate pit stabilization. Degradation began more recently on the central Beaufort coastal plain (eolian sand) and Arctic foothills (yedoma). Our results indicate that ice-wedge degradation in northern Alaska cannot be explained by late-20th century warmth alone. Likely mechanisms for asynchronous onset include landscape-scale differences in surficial materials and ground-ice content, regional climate gradients from west (maritime) to east (continental), and regional differences in the timing and magnitude of extreme warm summers after the Little Ice Age.

Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska

Arctic tundra landscapes are composed of a complex mosaic of patterned ground features, varying in soil moisture, vegetation composition, and surface hydrology over small spatial scales (10–100 m). The importance of microtopography and associated geomorphic landforms in influencing ecosystem structure and function is well founded, however, spatial data products describing local to regional scale distribution of patterned ground or polygonal tundra geomorphology are largely unavailable. Thus, our understanding of local impacts on regional scale processes (e.g., carbon dynamics) may be limited. We produced two key spatiotemporal datasets spanning the Arctic Coastal Plain of northern Alaska (~60,000 km²) to evaluate climate-geomorphological controls on arctic tundra productivity change, using (1) a novel 30 m classification of polygonal tundra geomorphology and (2) decadal-trends in surface greenness using the Landsat archive (1999–2014). These datasets can be easily integrated and adapted in an array of local to regional applications such as (1) upscaling plot-level measurements (e.g., carbon/energy fluxes), (2) mapping of soils, vegetation, or permafrost, and/or (3) initializing ecosystem biogeochemistry, hydrology, and/or habitat modeling.