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Vegetation has recolonized the Arctic numerous times throughout the Holocene. The most recent retreat of glaciers on Baffin Island, Nunavut, has been since the Little Ice Age, due to anthropogenic warming. Retreating cold-based ice often uncovers ancient vegetation. Recently exposed plants can tell us about past plant communities and colonization rates, important information for parameterizing vegetation feedback in climate models. Here, we provide complete descriptions of vegetation communities recently exposed by two retreating ice caps on Baffin Island and compare them with modern vegetation in the surrounding areas. We found that the ancient vegetation was similar to current vegetation, meaning that the current vegetation had not significantly changed during the past several hundred years. Colonization of bare ground was evident and differed depending on the substrate (rock versus finer substrates), with saxicolous lichens colonizing rocks and acrocarpous mosses and liverworts colonizing areas with finer substrates. The mature communities differed at the two sites, mostly because of a warmer climate at the southern site. Vegetation colonization, especially of light-colored rocks, reduces albedo, but the process can take hundreds of years. Changes in plant community composition are likely to continue for thousands of years due to climate change and the arrival of new species. 

Vegetation has recolonized the Arctic numerous times throughout the Holocene. The most recent retreat of glaciers on Baffin Island, Nunavut, has been since the Little Ice Age, due to anthropogenic warming. Retreating cold-based ice often uncovers ancient vegetation. Recently exposed plants can tell us about past plant communities and colonization rates, important information for parameterizing vegetation feedback in climate models. Here, we provide complete descriptions of vegetation communities recently exposed by two retreating ice caps on Baffin Island and compare them with modern vegetation in the surrounding areas. We found that the ancient vegetation was similar to current vegetation, meaning that the current vegetation had not significantly changed during the past several hundred years. Colonization of bare ground was evident and differed depending on the substrate (rock versus finer substrates), with saxicolous lichens colonizing rocks and acrocarpous mosses and liverworts colonizing areas with finer substrates. The mature communities differed at the two sites, mostly because of a warmer climate at the southern site. Vegetation colonization, especially of light-colored rocks, reduces albedo, but the process can take hundreds of years. Changes in plant community composition are likely to continue for thousands of years due to climate change and the arrival of new species. 

The Arctic is warming faster than anywhere else on Earth, placing tundra ecosystems at the forefront of global climate change. Plant biomass is a fundamental ecosystem attribute that is sensitive to changes in climate, closely tied to ecological function, and crucial for constraining ecosystem carbon dynamics. However, the amount, functional composition, and distribution of plant biomass are only coarsely quantified across the Arctic. Therefore, we developed the first moderate resolution (30 m) maps of live aboveground plant biomass (g m− 2) and woody plant dominance (%) for the Arctic tundra biome, including the mountainous Oro Arctic. We modeled biomass for the year 2020 using a new synthesis dataset of field biomass harvest measurements, Landsat satellite seasonal synthetic composites, ancillary geospatial data, and machine learning models. Additionally, we quantified pixel-wise uncertainty in biomass predictions using Monte Carlo simulations and validated the models using a robust, spatially blocked and nested cross-validation procedure. Observed plant and woody plant biomass values ranged from 0 to ~6000 g m− 2 (mean ≈350 g m− 2), while predicted values ranged from 0 to ~4000 g m− 2 (mean ≈275 g m− 2), resulting in model validation root-mean-squared-error (RMSE) ≈400 g m− 2 and R2 ≈ 0.6. Our maps not only capture large-scale patterns of plant biomass and woody plant dominance across the Arctic that are linked to climatic variation (e.g., thawing degree days), but also illustrate how fine-scale patterns are shaped by local surface hydrology, topography, and past disturbance. By providing data on plant biomass across Arctic tundra ecosystems at the highest resolution to date, our maps can significantly advance research and inform decision-making on topics ranging from Arctic vegetation monitoring and wildlife conservation to carbon accounting and land surface modeling 

Abstract. 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: https://doi.org/10.3334/ORNLDAAC/2177). 

We studied processes of ice-wedge degradation and stabilization at three sites adjacent to road infrastructure in the Prudhoe Bay Oilfield, Alaska, USA. We examined climatic, environmental, and subsurface conditions and evaluated vulnerability of ice wedges to thermokarst in undisturbed and road-affected areas. Vulnerability of ice wedges strongly depends on the structure and thickness of soil layers above ice wedges, including the active, transient, and intermediate layers. In comparison with the undisturbed area, sites adjacent to the roads had smaller average thicknesses of the protective intermediate layer (4 cm vs. 9 cm), and this layer was absent above almost 60% of ice wedges (vs. ∼45% in undisturbed areas). Despite the strong influence of infrastructure, ice-wedge degradation is a reversible process. Deepening of troughs during ice-wedge degradation leads to a substantial increase in mean annual ground temperatures but not in thaw depths. Thus, stabilization of ice wedges in the areas of cold continuous permafrost can occur despite accumulation of snow and water in the troughs. Although thermokarst is usually more severe in flooded areas, higher plant productivity, more litter, and mineral material (including road dust) accumulating in the troughs contribute to formation of the intermediate layer, which protects ice wedges from further melting. 

Environmental impact assessments for new Arctic infrastructure do not adequately consider the likely long-term cumulative effects of climate change and infrastructure to landforms and vegetation in areas with ice-rich permafrost, due in part to lack of long-term environmental studies that monitor changes after the infrastructure is built. This case study examines long-term (1949–2020) climate- and road-related changes in a network of ice-wedge polygons, Prudhoe Bay Oilfield, Alaska. We studied four trajectories of change along a heavily traveled road and a relatively remote site. During 20 years prior to the oilfield development, the climate and landscapes changed very little. During 50 years after development, climate-related changes included increased numbers of thermokarst ponds, changes to ice-wedge-polygon morphology, snow distribution, thaw depths, dominant vegetation types, and shrub abundance. Road dust strongly affected plant-community structure and composition, particularly small forbs, mosses, and lichens. Flooding increased permafrost degradation, polygon center-trough elevation contrasts, and vegetation productivity. It was not possible to isolate infrastructure impacts from climate impacts, but the combined datasets provide unique insights into the rate and extent of ecological disturbances associated with infrastructure-affected landscapes under decades of climate warming. We conclude with recommendations for future cumulative impact assessments in areas with ice-rich permafrost. 

This dataset provides estimates of live, oven-dried aboveground biomass of all plants (tree, shrub, graminoid, forb, bryophyte) and all woody plants (tree, shrub) at 30-meter resolution across the Arctic tundra biome. Estimates of woody plant dominance are also provided as: (woody plant biomass / plant biomass) * 100. Plant biomass and woody plant biomass were estimated for each pixel (grams per square meter [g / m2]) using field harvest data for calibration/validation along with modeled seasonal surface reflectance data derived using Landsat satellite imagery and the Continuous Change Detection and Classification algorithm, and other supplementary predictors related to topography, region (e.g. bioclimate zone, ecosystem type), land cover, and derivative spectral products. Modeling was performed in a two-stage process using random forest models. First, biomass presence/absence was predicted using probability forests. Then, biomass quantity was predicted using regression forests. The model outputs were combined to produce final biomass estimates. Pixel uncertainty was assessed using Monte Carlo iterations. Field and remote sensing data were permuted during each iteration and the median (50th percentile, p500) predictions for each pixel were considered best estimates. In addition, this dataset provides the lower (2.5th percentile, p025) and upper (97.5th percentile, p975) bounds of a 95% uncertainty interval. Estimates of woody plant dominance are not modeled directly, but rather derived from plant biomass and woody plant biomass best estimates. The Pan Arctic domain includes both the Polar Arctic, defined using bioclimate zone data from the Circumpolar Arctic Vegetation Mapping Project (CAVM; Walker et al., 2005), and the Oro Arctic (treeless alpine tundra at high latitudes outside the Polar Arctic), defined using tundra ecoregions from the RESOLVE ecoregions dataset (Dinerstein et al., 2017) and treeline data from CAVM (CAVM Team, 2003). The mapped products focus on Arctic tundra vegetation biomass, but the coarse delineation of this biome meant some forested areas were included within the study domain. Therefore, this dataset also provides a tree mask product that can be used to mask out areas with canopy height ≥ 5 meters. This mask helps reduce, but does not eliminate entirely, areas of dense tree cover within the domain. Users should be cautious of predictions in forested areas as the models used to predict biomass were not well constrained in these areas. This dataset includes 132 files: 128 cloud-optimized GeoTIFFs, 2 tables in comma-separated values (CSV) format, 1 vector polygon in Shapefile format, and one figure in JPEG format. Raster data is provided in the WGS 84 / North Pole LAEA Bering Sea projection (EPSG:3571) at 30 meter (m) resolution. Raster data are tiled with letters representing rows and numbers representing columns, but note that some tiles do not contain unmasked pixels. We included all tiles nonetheless to maintain consistency. Tiling information can be found in the ‘metadata’ directory as a figure (JPEG) or shapefile. 

Abstract This study applies an indicators framework to investigate climate drivers of tundra vegetation trends and variability over the 1982–2019 period. Previously known indicators relevant for tundra productivity (summer warmth index (SWI), coastal spring sea-ice (SI) area, coastal summer open-water (OW)) and three additional indicators (continentality, summer precipitation, and the Arctic Dipole (AD): second mode of sea level pressure variability) are analyzed with maximum annual Normalized Difference Vegetation Index (MaxNDVI) and the sum of summer bi-weekly (time-integrated) NDVI (TI-NDVI) from the Advanced Very High Resolution Radiometer time-series. Climatological mean, trends, and correlations between variables are presented. Changes in SI continue to drive variations in the other indicators. As spring SI has decreased, summer OW, summer warmth, MaxNDVI, and TI-NDVI have increased. However, the initial very strong upward trends in previous studies for MaxNDVI and TI-NDVI are weakening and becoming spatially and temporally more variable as the ice retreats from the coastal areas. TI-NDVI has declined over the last decade particularly over High Arctic regions and southwest Alaska. The continentality index (CI) (maximum minus minimum monthly temperatures) is decreasing across the tundra, more so over North America than Eurasia. The relationship has weakened between SI and SWI and TI-NDVI, as the maritime influence of OW has increased along with total precipitation. The winter AD is correlated in Eurasia with spring SI, summer OW, MaxNDVI, TI-NDVI, the CI and total summer precipitation. This winter connection to tundra emphasizes the role of SI in driving the summer indicators. The winter (DJF) AD drives SI variations which in turn shape summer OW, the atmospheric SWI and NDVI anomalies. The winter and spring indicators represent potential predictors of tundra vegetation productivity a season or two in advance of the growing season.