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Climate change is increasing the frequency and intensity of thermokarst, but the influences of regional climate and physiography remain poorly understood. Retrogressive thaw slumping is one of the most dynamic forms of thermokarst and affects many areas of glaciated terrain across northwestern Canada. In this study, we used airphotos and satellite imagery to investigate the influence of climate and landscape factors on thaw slump dynamics. We assessed slump size, density, and growth rates in four regions of ice-rich terrain with contrasting climate and physiographic conditions: the Jesse Moraine, the Tuktoyaktuk Coastlands, the Bluenose Moraine, and the Peel Plateau. Observed increases in: (1) the area impacted by slumps (+2 to +407%), (2) average slump sizes (+0.31 to +1.82 ha), and (3) slump growth rates (+169 to +465 m2 yr−1) showed that thermokarst activity is rapidly accelerating in ice-rich morainal landscapes in the western Canadian Arctic, where slumping has become a dominant driver of geomorphic change. Differences in slump characteristics among regions indicate that slump development is strongly influenced by topography, ground ice conditions, and Quaternary history. Observed increases in slump activity occurred in conjunction with increases in air temperature and precipitation, but variation in slump activity among the four regions suggests that increased precipitation has been an important driver of change. Our observation that the most rapid intensification of slump activity occurred in the coldest environment (the Jesse Moraine on Banks Island) indicates that ice-cored landscapes in cold permafrost environments are highly vulnerable to climate change.

Ice-wedge networks underlie polygonal terrain and comprise the most widespread form of massive ground ice in continuous permafrost. Here, we show that climate-driven thaw of hilltop ice-wedge networks is rapidly transforming uplands across Banks Island in the Canadian Arctic Archipelago. Change detection using high-resolution WorldView images and historical air photos, coupled with 32-year Landsat reflectance trends, indicate broad-scale increases in ponding from ice-wedge thaw on hilltops, which has significantly affected at least 1500 km2 of Banks Island and over 3.5% of the total upland area. Trajectories of change associated with this upland ice-wedge thermokarst include increased micro-relief, development of high-centred polygons, and, in areas of poor drainage, ponding and potential initiation of thaw lakes. Millennia of cooling climate have favoured ice-wedge growth, and an absence of ecosystem disturbance combined with surface denudation by solifluction has produced high Arctic uplands and slopes underlain by ice-wedge networks truncated at the permafrost table. The thin veneer of thermally-conductive mineral soils strongly links Arctic upland active-layer responses to summer warming. For these reasons, widespread and intense ice-wedge thermokarst on Arctic hilltops and slopes contrast more muted responses to warming reported in low and subarctic environments. Increasing field evidence of thermokarst highlights the inherent climate sensitivity of the Arctic permafrost terrain and the need for integrated approaches to monitor change and investigate the cascade of environmental consequences.

Strong evidence for a pan-Arctic expansion of upright shrubs comes from analysis of satellite imagery, historical photographs, vegetation plots, and growth rings. However, there are still uncertainties related to local-scale patterns of shrub growth, resulting interactions among vegetation functional groups, and the relative roles of disturbance and climate as drivers of observed change. Here, we present evidence that widespread and rapid shrub expansion and lichen declines over a 15,000 km² area of the western Canadian Arctic have been driven by regional increases in temperature. Using 30 m resolution Landsat satellite imagery and high resolution repeat color-infrared aerial photographs, we show that 85% of the land surface has a positive 1985-2011 trend (P < 0.05) in NDVI, making this one of the most intensely greening regions in the Arctic. Strong positive trends (> 0.03 NDVI/decade) occurred consistently across all landscape positions and most vegetation types. Comparison of 208, 1:2,000 scale vertical air photo pairs from 1980 and 2013 clearly shows that this greening was driven by increased canopy cover of erect dwarf and tall shrubs, with declines in terricolous lichen cover. Disturbances caused by wildfires, exploratory gas wells, and drained lakes all produced strong, yet localized increases in NDVI due to shrub growth. Our analysis also shows that a 4°C winter temperature increase over the past 30 years, leading to warmer soils and enhanced nutrient mineralization provides the best explanation for observed vegetation change. These observations thus provide early corroboration for modeling studies predicting large-scale vegetation shifts in low-Arctic ecosystems from climate change.

The reality confronting ecosystem managers today is one of heterogeneous, rapidly transforming landscapes, particularly in the areas more affected by urban and agricultural development. A landscape management framework that incorporates all systems, across the spectrum of degrees of alteration, provides a fuller set of options for how and when to intervene, uses limited resources more effectively, and increases the chances of achieving management goals. That many ecosystems have departed so substantially from their historical trajectory that they defy conventional restoration is not in dispute. Acknowledging novel ecosystems need not constitute a threat to existing policy and management approaches. Rather, the development of an integrated approach to management interventions can provide options that are in tune with the current reality of rapid ecosystem change.

Anthropogenic climate change has driven an increase in the frequency, size, and severity of fires at high latitudes. Recent research shows that increasing fire severity in the subarctic is altering the trajectories of forest succession, but to date, research on the effect of fire severity on tundra succession has been limited. In this study, we investigated short-term recovery of shrub tundra communities following fire in the Tuktoyaktuk Coastal Plain and Anderson River Plain ecoregions of the Northwest Territories. To understand the effects of fire severity, we documented vegetation and permafrost recovery within moderately burned, severely burned, and unburned portions of six tundra fires that burned in 2012. We found that vegetation structure at moderately and severely burnt sites recovered rapidly toward pre-fire levels, but that differences in community composition, characterized by a decrease in shrub and lichen cover as well as an increase in abundance of ruderals and graminoids, persisted at severely burned sites. The persistence of thermal changes and increased thaw depth indicate that while biotic recovery can occur promptly, severe fire may have long-term impacts on belowground conditions.

Climate warming has significant impacts on permafrost, infrastructure and soil organic carbon at the northern high latitudes. These impacts are mainly driven by changes in soil temperature (TS). Snow insulation can cause significant differences between TS and air temperature (TA), and our understanding about this effect through space and time is currently limited. In this study, we compiled soil and air temperature observations (measured at about 0.2 m depth and 2 m height, respectively) at 588 sites from climate stations and boreholes across the northern high latitudes. Analysis of this circumpolar dataset demonstrates the large offset between mean TS and TA in the low arctic and northern boreal regions. The offset decreases both northward and southward due to changes in snow conditions. Correlation analysis shows that the coupling between annual TS and TA is weaker, and the response of annual TS to changes in TA is smaller in boreal regions than in the arctic and the northern temperate regions. Consequently, the inter-annual variation and the increasing trends of annual TS are smaller than that of TA in boreal regions. The systematic and significant differences in the relationship between TS and TA across the circumpolar north is important for understanding and assessing the impacts of climate change and for reconstruction of historical climate based on ground temperature profiles for the northern high latitudes.

Plot-scale field measurements are necessary to monitor changes to tundra vegetation, which has a small stature and high spatial heterogeneity, while satellite remote sensing can be used to track coarser changes over larger regions. In this study, we explored the potential of unmanned aerial vehicle (UAV) photographic surveys to map low-Arctic vegetation at an intermediate scale. A multicopter was used to capture highly overlapping, subcentimetre photographs over a 2 ha site near Tuktoyaktuk, Northwest Territories. Images were processed into ultradense 3D point clouds and 1 cm resolution orthomosaics and vegetation height models using Structure-from-Motion (SfM) methods. Shrub vegetation heights measured on the ground were accurately represented using SfM point cloud data (r 2 = 0.96, SE = 8 cm, n = 31) and a combination of spectral and height predictor variables yielded an 11-class classification with 82% overall accuracy. Differencing repeat UAV surveys before and after manually trimming shrub patches showed that vegetation height decreases in trimmed areas (− 6.5 cm, SD = 21 cm). Based on these findings, we conclude that UAV photogrammetry provides a promising, cost-efficient method for high-resolution mapping and monitoring of tundra vegetation that can be used to bridge the gap between plot and satellite remote sensing measurements.

Replicability of Digital Terrain Models (DTMs) and Canopy Height Models (CHMs) derived from drone photogrammetry is important to understand the extent to which time-series are exposed to methodological noise and conceal real environmental changes. Root mean square error (RMSE) distribution metrics (median/IQR) were used as indicators of replicability across seven drone survey setups, three dense matching scales, and 13 ground point filters in a challenging shrubland environment (total of 273 DTMs and CHMs). We conclude that methodological effects have considerable potential to negatively affect replicability. A power-law relationship between point cloud density and dense matching resolution suggested that important dense matching resolution thresholds exist beyond which replicability degrades considerably. For our Arctic study area, replicability of DTMs (median ± 0.1 m RMSE Vegetated Vertical Accuracy) and CHMs (within ±0.05 m of true site-level heights) is most likely when source imagery is collected with ≤1.5 cm spatial resolution and side-lap of >80%, and if classified point clouds are generated using full-scale dense matching and Triangular Irregular Network filtering. Negative biases for maximum shrub height estimates increased from 4–9% to 14–50% with coarser imagery. We advocate for increased attention to drone-derived model replicability to separate real environmental changes from noise during a period of rapid ecological and geomorphic change.

Deep learning has been used for mapping retrogressive thaw slumps and other periglacial landforms but its application is still limited to local study areas. To understand the accuracy, efficiency, and transferability of a deep learning model (i.e., DeepLabv3+) when applied to large areas or multiple regions, we conducted several experiments using training data from three different regions across the Canadian Arctic. To overcome the main challenge of transferability, we used a generative adversarial network (GAN) called CycleGAN to produce new training data in an attempt to improve transferability. The results show that (1) data augmentation can improve the accuracy of the deep learning model but does not guarantee transferability, (2) it is necessary to choose a good combination of hyper-parameters (e.g., backbones and learning rate) to achieve an optimal trade-off between accuracy and efficiency, and (3) a GAN can significantly improve the transferability if the variation between source and target is dominated by color or general texture. Our results suggest that future mapping of retrogressive thaw slumps should prioritize the collection of training data from regions where a GAN cannot improve the transferability.

The distribution and composition of Arctic vegetation are expected to shift with ongoing climate change. Global models generally predict northward shifts in high‐latitude ecotones, and analysis of remote sensing data shows widespread greening and changes in vegetation structure across the circumpolar Arctic. However, there are still uncertainties related to the timing of these shifts and variation among different plant functional types. In this paper, we investigate disequilibrium dynamics of green alder and white spruce in the Tuktoyaktuk Coastal Plain, NWT. We used high‐resolution air photographs captured in the 1970s and 2000s to quantify changes in the distribution and abundance of alder and spruce near their northern limits. We found increases in alder and spruce stem density over time, but no change in their range limits, indicating that both species are affected by leading‐edge disequilibrium. Low stand density and temperature limitation of reproduction along the northern margin likely contributed to observed disequilibrium in both species. We also observed the greatest change in species occupancy within a burned area, suggesting that the increased frequency of fire will play a significant role in the timing and magnitude of near‐term vegetation change.