Disturbances in North American boreal forest and Arctic tundra: impacts, interactions, and responses

Wildfire is the most well-studied disturbance agent in forests of boreal North America, as fires have substantial impacts on human settlements (Kent 2017), subsistence resources (Nelson et al 2008), and air quality (Trainor et al 2009), in addition to climate (Randerson et al 2006, Potter et al 2020b) and vegetation (Rogers et al 2013, Foster et al 2022). Fires in boreal North America are generally high-intensity crown fires that kill most affected trees and consume substantial belowground carbon stocks, in contrast to those in boreal Eurasia or more temperate ecosystems which include a high fraction of lower-severity surface fires that result in relatively low tree mortality (Stocks and Kaufmann 1997, de Groot et al 2013, Rogers et al 2015). Fire is less common in Arctic tundra but has been increasing in frequency and severity (Hu et al 2015, McCarty et al 2021), especially in the Beringian region (Racine et al 1985, Rocha et al 2012, Masrur et al 2018, Gaglioti et al 2021). Recent increases in boreal and Arctic wildfire activity may indicate fundamental shifts in the causes and impacts of the underlying fire regime, including overwintering fires that smolder during winter months and reappear the following year (Scholten et al 2021, Xu et al 2022), increased occurrence of lightning ignitions (Veraverbeke et al 2017, Chen et al 2021c), and long-term shifts in forest composition following these fires (Baltzer et al 2021, Mack et al 2021). Forest fire records throughout the North American boreal region show an increase in annual burned area and number of large fires since the mid-20th century (Calef et al 2015, Hanes et al 2019, Walker et al 2020b). The majority of projections of future fire regimes suggest increasing fire activity across boreal North America over the 21st century due to climate change (Bachelet et al 2005, Amiro et al 2009, Chen et al 2016, Hope et al 2016, Veraverbeke et al 2017, Wang et al 2020, Phillips et al 2022).

Precursors to fire in boreal ecosystems are well understood—an adequate amount of fuel and fuel dryness are required for fires to ignite and spread, in addition to ignition sources such as lightning strikes and anthropogenic activities (Veraverbeke et al 2017, Archibald et al 2018, Rogers et al 2020). In the boreal zone, fires are generally limited by fuel dryness and ignition sources because the characteristically deep organic and moss layers provide ample fuel. Both species composition and litter moisture are influenced by site drainage conditions, with organic-rich soils dominated by fire-prone and flammable species such as black spruce (Picea mariana). Conversely, Jack pine (Pinus banksiana) and less flammable deciduous species typically occur in well-drained locations with thinner, drier soils (Walker et al 2018, 2020b).

Lightning strikes ignite most fires in the North American ABZ. Lightning ignitions have increased since the mid-20th century due to a warmer and more convective atmosphere (Veraverbeke et al 2017, Chen et al 2021c). More severe fire weather is also prolonging fire seasons and increasing fire intensity and annual area burned. For example, Kasischke et al (2010) found the mean annual area burned in Alaska during the 2000s was 50% greater than any previous decade since the start of the record in 1940, resulting in increased ground-layer combustion and net carbon emissions to the atmosphere (Turetsky et al 2011).

Within the North American boreal region, fires create lasting legacies on vegetation, driving changes in soil characteristics, regeneration patterns, and successional trajectories (Johnstone et al 2010, Gaglioti et al 2021, Mack et al 2021). High-severity forest fires that remove much of the organic layer favor regeneration by deciduous and fast-growing pine species, which may maintain dominance under a warming climate (Johnstone et al 2011). Field data have also suggested that increased warming and fires may be altering the ability of typically resilient black spruce forests to recover following large fires, leading potentially to a tipping point for boreal vegetation—shifting from evergreen to deciduous or non-forested land cover types (Baltzer et al 2021). Alterations to phenological metrics from time series of NDVI and other greenness metrics observed in burned areas in Alaska may also indicate long-term shifts in vegetation cover type and photosynthetic activity at regional scales (Potter 2020a, Madani et al 2021).

In the Arctic tundra, our understanding of the drivers of the wildfire regimes is less thorough, due to a combination of factors including lower fire frequency, remoteness, and limited in-situ observations. It is commonly believed that lightning (Chen et al 2021c, He et al 2022), summer temperature, and precipitation (Hu et al 2015, Vachula et al 2022) are among the primary factors controlling the wildfire regimes in Alaskan tundra. Fire usually favors the recruitment and growth of deciduous shrubs in the tundra. It is therefore an important mechanism for Arctic shrubification (Lantz et al 2010b, Jones et al 2013, Frost et al 2020). Following fire, net ecosystem productivity (NEP) declines because of reduced vegetation productivity and increased ecosystem respiration, with forest ecosystems becoming a carbon source for roughly one to two decades (Amiro et al 2010, Liu et al 2011, Kurz et al 2013). In the tundra, vegetation productivity recovers more quickly, in as little as three years post-fire, though longer term impacts on NEP remain less clear (Gaglioti et al 2021). As vegetation and soils recover, NEP increases up to a maximum and then decreases to a steady state, at which point the ecosystem is again carbon neutral or a carbon sink (Goetz et al 2012, Song et al 2018). Climate change, however, may alter the post-fire NEP response in the future due to species composition shifts, productivity changes, and permafrost thaw (Rocha et al 2012, Gibson et al 2018, Foster et al 2019, Mekonnen et al 2019, Baltzer et al 2021).

Vegetation responses to fire disturbance can be seen in Landsat-derived trajectories of greenness (NDVI) and wetness (NDMI), as showcased in the average across all fire trajectories (n = 32) as well six individual fires (figure 4). The average trajectory shows a rapid decline in normalized NDVI and NDMI immediately following fire, with a moderate recovery rate in the following years (approximately 10 years for NDVI and 15 years for NDMI). Tundra NDVI recovers more rapidly, with NDVI values reaching the pre-disturbance mean within a decade following fire. The NDMI response following fire is more varied for the tundra locations, a pattern which highlights the cascading effects of wildfire on accelerated permafrost thaw and associated changes in soil thermal and moisture regimes, and variability arising from local differences in fire severity and ground ice conditions (Jones et al 2015).

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Large fire databases are crucial for understanding fire precursors, effects, trends, and dynamics in boreal and Arctic ecosystems. In Alaska and Canada, existing fire history databases provide fire perimeter polygons beginning in the 1940s and 1960s, respectively, and are maintained and updated annually. These databases are some of the longest and most complete large-scale historical fire records available anywhere on the planet (Kasischke et al 2002, Stocks et al 2002) and they are foundational datasets for investigating regional impacts of post-fire vegetation succession (Rogers et al 2013, Potter et al 2020b). Despite this, due to the great challenges in mapping wildfires in the high latitudes (e.g. limited availability of Landsat observations during a short growing season and persistent cloud cover; Chen et al 2021a, 2021b), omissions of large wildfire events by these wildfire history records still exist, particularly in the tundra (Jones et al 2013). Moreover, the fire perimeters themselves become less accurate further back in time, and often contain substantial patches of unburned vegetation (Kasischke et al 2002, Walker et al 2018, Potter et al 2020b). Advances in remote sensing tools enable fires and their impacts to be mapped and tracked at increasingly finer spatiotemporal resolutions (Eidenshink et al 2007, Duncan et al 2020, Hall et al 2020). Field data are also crucial for studying fire impacts on carbon stocks and fluxes, vegetation recovery, hydrology, and other ecosystem properties, and a growing number of databases are allowing for meta-analyses of fire impacts (Virkkala et al 2018, Walker et al 2020a, Virkkala et al 2022). However, additional combustion estimates are needed to better understand the interactions between fire weather, fire spread and intensity, and combustion (Walker et al 2020b).

Further data are required to elucidate the interactions between wildfire, vegetation, and permafrost in the context of changing climate (Gibson et al 2018, Treharne et al 2022). Increasing temperatures, changing precipitation, and increases in fire activity will impact vegetation composition and structure, hydrology, and carbon fluxes. Future researchers could utilize a combination of active radar and subsidence data, high spatial and spectral resolution imagery, digital elevation models, and airborne LiDAR and other remote sensing data to observe and analyze these changes. It is also unclear how these changes to vegetation and fuels will interact with future fire regimes. Predicted increases in deciduous fraction and declines in organic layer and other fuels (Foster et al 2019, Mekonnen et al 2019) may lead to decreasing fire frequency and severity, even as fire weather and fuel drying increases (Parks et al 2015). Further, if young stands re-burn following fire, it is unknown how and which species may be able to regenerate as seed banks become depleted and soils become less conducive to seedling establishment (Baltzer et al 2021).

From a societal perspective, the increasing frequency of large fires, and necessary increased investments in fire-fighting activities at the wildland-urban interface, will strain the existing fire management budgets and governance structures (Rogers et al 2020). More studies are needed linking the influence of management on fire regimes, both historically and in the future, to quantify these relationships and make predictions for the efficacy and costs of fire management efforts (Calef et al 2015, Melvin et al 2017b, Phillips et al 2022).

Biotic disturbances, such as fungal pathogens (e.g. root rots and needle rusts) and insect outbreaks (e.g. bark beetles and defoliators/leaf miners) can cause extensive tree mortality during outbreaks (Holsten et al 2008, Kautz et al 2016). Fungal pathogens often kill individuals slowly by disrupting water and nutrient transport (Holsten et al 1985) and reducing growth. In contrast, episodic insect outbreaks can cause major growth reductions and spatially widespread tree mortality over a few years, at times eclipsing that due to fire. For example, annual forest volume lost due to productivity reduction and mortality from pests and pathogens in Canada was estimated to be 106 million m³ yr⁻¹ between 1982 and 1987, which was three times that lost annually to fire and 70% of volume harvested in Canada nationally during that period (Hall and Moody 1994, Malmstrom and Raffa 2000, Volney and Fleming 2000, Price et al 2013). In the 1990s in Alaska, insects cumulatively damaged 1.6–2 million hectares of forest, which was 30% more area than burned during that period (Malmstrom and Raffa 2000).

Bark beetles, such as the mountain pine beetle (Dendroctonus ponderosae) and spruce beetle (Dendroctonus rufipennis), kill host trees outright by feeding on the cambium and phloem (figures 5(a) and (c)) and disrupting water transport (Malmstrom and Raffa 2000, Bentz et al 2010). These beetles attack trees through 'mass attacks' of many beetles, attracted via massing pheromones released by the beetles (Raffa et al 2008). Bark beetle populations typically exist at relatively low levels, punctuated by occurrences of high, epidemic levels due to climate-, disturbance-, or forest structure-related triggers (DeRose et al 2013, Seidl et al 2016). Young, healthy trees can often defend against low levels of attacking beetles by exuding resin and allelochemicals. However, stressed trees and those experiencing a large number of attacking beetles are more likely to succumb to infestation (DeRose and Long 2012). Thus, conditions that lead to vegetation stress, such as drought, often lead to outbreak events (Sherriff et al 2011, Seidl et al 2016).

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Defoliators and leaf miners feed on the leaves and needles of host plants. In the North American ABZ, these guilds include, for instance, eastern and western spruce budworms (Choristoneura spp.), Jack pine budworm (Choristoneura pinus), aspen leaf miner (Phyllocnistis populliella) (figure 6(a)), and large aspen tortrix (Choristoneura conflictana). Outbreaks of these defoliators and miners cause significant tree growth reduction and potentially tree mortality. Removal or damage to needles and leaves disrupts water transport and interferes with photosynthesis, which can kill trees directly or cause physiological stress that predisposes them to death from other factors, such as drought (Malmstrom and Raffa 2000). Recovery from major defoliation and mining depends on the extent of damage and the amount of carbon reserves held in other tissues (Boyd et al 2021). Deciduous species generally are more able to re-foliate from leaf damage than evergreen species, even in the same year as defoliation (Krause and Raffa 1996, Holsten et al 2008). Evergreen species, however, often have a high rate of mortality following successive years of intense defoliation, potentially leading to species composition shifts post-outbreak.

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The most common pathogens in the North American ABZ include root rot (e.g. Inonotus tomentosus), heart rot fungi (e.g. Fomitopsis pinicola), and needle rusts (e.g. Chrysomyxa ledicola; figure 6(c)) (Armstrong and Ives 1995, Holsten et al 2008). These pathogens can cause hydraulic impairment by damaging vascular systems, reduce productivity through impacts on needles and leaves, and ultimately lead to plant mortality. Recently, an outbreak of the novel aspen running canker (Neodothiopora populina) caused widespread mortality of quaking aspen (Populus tremuloides) in interior Alaska (figure 6(b)). Aspen mortality from these infections was exacerbated by ongoing drought as well as an outbreak of aspen leaf miner (Ruess et al 2021).

While pathogens frequently affect a wide range of species, insects are often species- or genus-specific in their host requirements (Armstrong and Ives 1995, Holsten et al 2008). Hosts that are larger, older, or stressed are generally more susceptible to bark beetles. Thus, areas with high numbers of susceptible hosts are most vulnerable to insect outbreak, with mature, host-dominated stands being the most susceptible (Raffa et al 2008, Chapman et al 2012, DeRose et al 2013, Hart et al 2015). These homogenous stands provide a high quality habitat for insects, allowing for self-sustaining populations and sources of large-scale outbreaks (Malmstrom and Raffa 2000, Seidl et al 2016). The relatively low biodiversity in ABZ forests thus makes them particularly vulnerable to insect and pathogen outbreaks (Jactel et al 2005, Campbell et al 2008, Senf et al 2017a). Increasing temperatures and drought are thus generally expected to increase the impacts of insects and pathogens in the North American ABZ.

Insect and pathogen outbreak dynamics are affected and compounded by climate and weather by influencing the range and population size of insects and pathogens and altering the vulnerability of plants. For example, warming temperatures can reduce wintertime mortality and accelerate population growth of insects like the spruce beetle (Raffa et al 2008, Bentz et al 2010, Gray et al 2013). Spruce beetles usually have a two-year (semivoltine) life cycle, but warmer conditions can accelerate larval growth, causing a shift to a one-year (univoltine) life cycle (Hansen et al 2011). More beetles with univoltine life cycles drives faster population growth and more severe outbreaks, such as occurred with the expansion of bark beetle outbreaks in British Columbia in the 1970s and 1980s (Bentz et al 2010). Host plants also interact with climate through host stress levels. Drought predisposes trees to disease and infestation (Raffa et al 2008, McKenzie et al 2009, Boyd et al 2021, Ruess et al 2021), and can be a secondary cause of mortality following defoliation stress (Malmstrom and Raffa 2000). Climate change is predicted to result in range expansion of insect species (de la Giroday et al 2012) and increases in outbreak severity and frequency (Raffa et al 2008). In Alaska, drought, high vapor pressure deficit, and high temperatures are key contributors to mortality linked with aspen leaf miner and aspen canker (Boyd et al 2021, Ruess et al 2021).

Because bark beetles tend to affect one or only a few host tree species and preferentially attack larger trees, their outbreaks often result in a shift towards smaller size classes and non-host species (Veblen et al 1991, Campbell and Antos 2015, Zeppenfeld et al 2015). Productivity often increases in these subsequent stands as non-infested trees are released from suppression (Campbell et al 2019). In more homogenous stands, species composition can shift towards early successional species after an outbreak. These impacts can be seen in trajectories of NDVI and NDMI before and during outbreaks (figure 7). Defoliators also tend to impact one or a few species—the eastern spruce budworm (C. fumiferana) mostly infests balsam fir (Abies balsamea) and white spruce (Picea glauca), and infestation-caused mortality often leads to release of seedlings and saplings of host species (Boulanger and Arsenault 2004). Changes in NDVI are generally subtle as outbreaks build, sometimes asynchronously, within individual trees (figure 5(b)), and are usually only visible in moderate-resolution satellites when large areas are impacted (DeRose and Long 2012). This subtle NDVI pattern (figure 7) is especially characteristic of spruce beetle outbreaks, which do not exhibit a characteristic 'red-stage' attack as do pine species infested with mountain pine beetle (Coops et al 2006). However, NDMI often does decline (figure 7), due to decreases in transpiration and increases in foliar water stress during and following bark beetle outbreaks (Foster et al 2017). In contrast, trajectories of NDVI and NDMI during and following spruce budworm infestation in the Northwest Territories (figure 8) have a clearer signal, with some variability across the individual sites, highlighting the impact of infestation severity on the spectral signal. Sites which have a lower infestation severity (e.g. percent defoliation) will have a more subtle signal than sites which had more complete defoliation from spruce budworm infestation (Senf et al 2016). The response of NDVI to aspen running canker is also clear, with limited recovery following the drop in NDVI due to infestation (figure 8). NDMI response is less clear, with some decline following infestation.

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Past insect outbreaks are often identified through dendrochronology and pollen records (Anderson et al 2010, Sherriff et al 2011). However, these are limited to specific locations, usually where an outbreak is known, resulting in biases in our understanding of their extent and occurrence. Aerial detection surveys that produce polygons of infestation extent and severity are valuable for determining the regional and national impacts of forest pests. However, these polygons are often at a coarse spatial scale with potentially low positional accuracy (Wulder et al 2006, Hall et al 2016). Detection of recent or ongoing outbreaks using moderate resolution satellite sensors is possible, especially for large, severe outbreaks (Meddens and Hicke 2014, Hall et al 2016, Senf et al 2016, 2017a). Specialized methods are generally required for each insect type (e.g. bark beetles vs. defoliators). Foliar color changes of conifers infested with bark beetles often progress from green, sometimes to red, and to gray as needles lose moisture and are ultimately shed from the tree. The red and gray stages are easily detectable in multispectral imagery (Coops et al 2006), however the green stage is more subtle, making early detection difficult (DeRose et al 2011). Despite this difficulty, some studies have had success in using the water-sensitive shortwave infrared wavelengths to detect early moisture stress from green-stage infestations (Foster et al 2017).

Accurate and temporally and spatially consistent datasets of infestation/infection status and extent across jurisdictions are crucial for determining the extent and severity of past and ongoing outbreaks, and for predicting future outbreaks (Kautz et al 2016, Senf et al 2017b). Such large-scale datasets would also aid in generalizing detection methods across wider regions and disturbance agents. Because some major limitations to detecting insect and pathogen disturbance from remotely sensed data include accurately discriminating between these disturbances and other vegetation stressors, due to the exhibition of similar spectral signals (Senf et al 2017b), field observations of infestation status that are coincident with remote sensing observations will assist in developing more accurate algorithms for multi-stage detection efforts (Cessna et al 2021). Increased availability of different types of remote sensing data, particularly hyperspectral and radar imagery, have the potential to identify changes in forest moisture related to insect and pathogen outbreaks at regional scales and with high spatial detail.

Studies have shown that insects and pathogens are expanding their ranges poleward with increasing temperatures, increasing the area of forest vulnerable to outbreak (de la Giroday et al 2012, Pureswaran et al 2018). Insects are also beginning to infest novel host species (NRC 2018), and it is unclear how such host species will respond. Such range expansion highlights the need for increased detection and monitoring of outbreaks, as well as the need for predictions of future infestation vulnerability.

Permafrost soils often exhibit warped or broken soil horizons that result from cryoturbation, the frost-based movements of seasonally frozen materials (Bockheim and Tarnocai 1998). Cryoturbation can also create distinctive surficial disturbance features that generate fine-scale spatial heterogeneity in ground conditions and serve as foci for ecological change (Walker et al 2011, Frost et al 2013, Aalto et al 2017). Frost circles are a common form of patterned ground. They occur as approximately circular patches (∼0.5–3 m diameter) of mineral soil that often form geometric mosaics of vegetated and unvegetated microsites at uniform spacing of ∼1–3 m (figure 1(c)).

Frost circles are common in permafrost regions, particularly where surface organic material is lacking and the soil profile is dominated by fine-textured silt or clay (Bockheim et al 1998, Peterson and Krantz 2003). The intensity of cryoturbation is strongly affected by soil moisture, soil texture, changes in seasonal temperature, and snow cover (Daanen et al 2007, Aalto et al 2017). In general, climate warming and increased snow cover dampen cryoturbation by reducing differential frost-heave. Climate warming can also dampen cryoturbation indirectly by promoting vegetation colonization, which stabilizes the soil and results in organic matter accumulation on cryoturbated soils. Species that are fast-growing and/or tolerant of ground surface disturbances are best able to colonize cryoturbated surfaces (Kade et al 2005, Sutton et al 2006, Frost et al 2013). Once cryoturbation is reduced or no longer occurring, the increase in biomass is abrupt and persistent; however, cryoturbation can be renewed if vegetation and organic material are removed by other disturbances (chiefly wildfire).

Cryoturbation can have nonlinear responses to climate change with respect to vegetation cover and biomass, which can be detected in multi-decadal NDVI time series (Frost et al 2014). Furthermore, cryoturbation has distinctive spatiotemporal properties as a disturbance agent, because features usually occur as a multitude of 1–3 m microsites within a broad landscape mosaic, and the disturbance acts annually and is not episodic. At our case study locations, both NDVI and NDMI increased over the 30 year Landsat record (figure 9). With respect to NDVI, the warming climate could allow vegetation to colonize previously bare frost circles in cryoturbated landscapes, which would reduce further cryoturbation (Frost et al 2013). The NDVI increase could additionally reflect a general background greening (i.e. vegetation increase) of the landscape, as only a fraction is cryoturbated, and the remainder can have nearly complete vegetation cover. For NDMI, the increase in moisture is likely in part due to the moisture content of the colonizing vegetation, but also increased soil moisture beneath the vegetation cover (figure 9).

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Polygonal ground, encompassing mosaics of ice-wedge polygons (∼5–15 m wide) formed by contraction cracking followed by annual cycles of thawing and refreezing, is widespread and conspicuous in permafrost landscapes (Liljedahl et al 2016). Wedge-shaped masses of ice underlie the edges of each polygon (figure 10). Ice-wedge degradation occurs when the uppermost portions of ice wedges thaw, which triggers local ground subsidence, ponding, and persistent changes to vegetation and hydrologic connectivity across the landscape (figure 10). Ice-wedge degradation often results in substantial micro-topographic changes, such as the transition from low-centered to high-centered polygonal landforms.

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Polygonal ground is most common in tundra with continuous permafrost, especially areas with fine-textured soils, and patterned landscapes can cover areas as large tens of square kilometers or larger (Lachenbruch 1962). However, ice wedges are also common in discontinuous permafrost regions well into the boreal forest (Kokelj et al 2014, Swanson 2016). Extreme warm and wet summers initiate ice-wedge degradation (Jorgenson et al 2006, 2015, Liljedahl et al 2016). Long periods of time (i.e. millennia) without additional disturbances are required to develop large ice wedges, so the terrain affected by ice-wedge degradation has historically supported 'climax' vegetation communities—usually tussock tundra or needleleaf woodlands in boreal forest settings (Billings and Peterson 1980).

Local and regional variability in the timing and extent of ice-wedge degradation arises from differences in surficial materials and ground-ice content, disturbance history (natural and anthropogenic), regional climate gradients, and regional differences in the timing and magnitude of recent extreme warm summers (Raynolds et al 2014, Kanevskiy et al 2017, Frost et al 2018a, Farquharson et al 2019). This variability in ice-wedge degradation contributes to variability in patterns of tundra vegetation change (e.g. tundra greening or browning). Once thaw begins, the resultant subsidence forms small, flooded pits and troughs along the polygon margins. These pits and troughs pock-mark the landscape, kill existing vegetation that is adapted to mesic conditions (i.e. a mechanism for tundra browning) (Lara et al 2018), and support the colonization of hydrophytic vegetation (e.g. wetland sedges and mosses). Secondary impacts can affect large areas because the generation of pits and troughs creates new hydrologic flowpaths that alter soil hydrology and the distribution of surface water (Koch et al 2018). Over time (usually a matter of years to a decade), most pits and troughs become colonized by wetland vegetation, and surface water extent declines due to the development of an organic mat (i.e. a mechanism for tundra greening) (Wolter et al 2016).

Successional processes after ice-wedge degradation could explain in part the increasing NDVI trajectories in ice-wedge polygon landscapes (figure 11). However, this increase is likely also being driven by a general background greening of the tundra landscape in response to climate warming (Berner et al 2020, Myers-Smith et al 2020), as the affected microsites comprise only a fraction of the broader polygonal landscape. The distribution of NDVI dynamics includes numerous pixels with strong 'browning' signals, probably due to extensive ice wedge degradation and increasing surface water (Jorgenson et al 2022). The increasing NDMI (figure 11) over time in these landscapes is likely being driven by the increasing surface water due to the development of pits and troughs.

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Climate-induced thawing of permafrost-affected hillslopes can trigger a variety of abrupt and gradual disturbances involving the mass movement of soils, collectively termed 'cryogenic landslides.' These landslides can result in losses of vegetation, followed by the development of successional vegetation on re-transported materials. Different forms of cryogenic landslides vary with respect to their spatial extent and temporal characteristics, and thus the pattern and rate of ecological succession after disturbance. These subtypes include (a) active-layer detachments, (b) frozen debris lobes, and (c) retrogressive thaw slumps.

Active-layer detachment slides are relatively small, local slope failures that develop after warm, wet summers, such that saturated active-layer soils slide abruptly over the permafrost table (Leibman 1995, Ermokhina and Myalo 2012, Verdonen et al 2020). Future climate warming and associated permafrost degradation, as well as increases in triggers such as extreme warm summer periods, increases in rainfall, and forest fires, could increase their frequency (Lewkowicz and Harris 2005). Frozen debris lobes are slow-moving, lobate permafrost features consisting of soil, rock, organic material, and ice that move down permafrost-affected slopes via shear along their bases (Darrow et al 2015, 2016, Simpson et al 2016). The distribution and dynamics of frozen debris lobes are comparatively poorly known.

Retrogressive thaw slumps are thermokarst slope disturbances that contribute large volumes of materials downslope to lakes, drainage networks, and coastal zones (Burn and Lewkowicz 1990, Lantuit and Pollard 2008). Initiation of retrogressive thaw slumps depends on local geomorphological conditions and meteorology. Fluvial erosion along riverbanks or coastal zones can initiate slope failures, promoted by extended warm and wet conditions (Burn and Lewkowicz 1990). Following an initial slope failure, exposure of ice-rich permafrost enables thaw slump development, which can persist for many years while the areal size of the thaw slumps can expand to tens of hectares. For example, the thaw slump shown in figures 12(b) and (c) expanded from 0.63 ha immediately after the detachment failure in 2016 to 1.04 hectares three years later (Turner et al 2021).

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The frequency and size of retrogressive thaw slumps can be highly variable within and among landscapes. The largest thaw slumps in North America have been observed in the Richardson Mountains and Peel Plateau regions, NWT, Canada (Lacelle et al 2015). This region, which includes the Mackenzie Delta, has experienced an increase in occurrences of thaw slumps in response to wet summer conditions (Lantz and Kokelj 2008, Kokelj et al 2015). Zwieback et al (2018) also found an increase in thaw slumps on the Tuktoyaktuk Peninsula, northwest of the Mackenzie Delta, Canada, and the Bykovsky Peninsula, Russia, associated with available energy and late-season rainfall. Many coastal areas have seen an increase in thaw slump activity, including Banks Island (Lewkowicz and Way 2019). Interactions with marine environments, including thermo-abrasion from waves and ice, can have a strong influence on thaw slump activity along coastlines (Günther et al 2013).

Cryogenic landslides impact terrestrial and aquatic ecosystems and atmospheric feedbacks. Within lake and river aquatic environments, biogeochemical cycling can be impacted by the liberated sediment and solutes, which are typically rich in nutrients and ions. However, the downstream impacts, on nutrient concentrations, for example, can be highly variable (Frey and McClelland 2009, Harms et al 2014, Lafrenière et al 2017, Mu et al 2017) and depend on local geomorphic conditions including relief, ice content, permafrost extent, and parent material (Tank et al 2020). These complex relations present uncertainties for associated impacts on local and downstream ecology. Vegetation can efficiently colonize stabilized areas of cryogenic landslides (Turner et al 2021). Habitat characteristics associated with landslide age and vegetation composition also have an influence on wildlife (Cray and Pollard 2019). Atmospheric impacts include climate change feedbacks that stem from microbial decomposition of parent material and subsequent emission of greenhouse gasses (CO₂ and CH₄; Schuur et al 2015, Turetsky et al 2020, Miner et al 2022).

Thermokarst lakes are formed when permafrost degradation results in subsidence of the land, which subsequently fills with water. These features are abundant across ice-rich permafrost terrain and are highly sensitive to climate conditions (Jones et al 2022). Though thermokarst lakes may remain stable for centuries, the shorelines are highly susceptible to erosion and expansion, the rate of which can be strongly influenced by dominant fetch and shoreline ground-ice content as well as climate (Roy-Léveillée and Burn 2010). When shoreline expansion progresses into low-lying areas or invades the boundaries of other thermokarst lakes, they can drain and experience near-complete water loss within days. Additional mechanisms that trigger drainage events can include drainage across an ice-wedge network, headward erosion along adjacent streams or coastal boundaries, and bank overflow when established outflow channels are blocked by snow and ice (Mackay 1981, 1988, Brewer et al 1993, Marsh and Neumann 2001, Hinkel et al 2007, Wolfe and Turner 2008, Jones and Arp 2015). Drainage can also occur incrementally through partial tapping by a stream and the development of open talik systems beneath the lake (Yoshikawa and Hinzman 2003).

Thermokarst lake drainage events represent drastic landscape transitions. Newly exposed lacustrine deposits serve as seedbeds for colonizing vegetation and can quickly develop continuous vegetation cover (e.g. Eriophorum russeolum, Carex aquatilis, and Senecio congestus) within the first few years following drainage depending on local conditions (Ovenden 1986, Mackay and Burn 2002, Shur and Jorgenson 2007, Lantz 2017). For example, willow (Salix spp.) encroached within 30.8% of the former 12 km² lakebed of Zelma Lake in Old Crow Flats, Yukon (Turner et al 2022). After a lake drainage event, the aquatic environment of the remaining water body can become highly dynamic for several years following drainage as biogeochemical properties are strongly influenced by weather and pluvial runoff across the exposed lakebed (Tondu et al 2017). Lake water biogeochemical properties stabilize as shrubs encroach, which enhances snowpack depth and snowmelt input (Turner et al 2022). The increasing NDVI in our lake drainage case study trajectories (figure 13) suggests encroachment of shrub vegetation. NDMI likely does not change because encroaching vegetation at these point locations are inundated with water.

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Catchment hydrologic and vegetation characteristics typically do not return to pre-drainage conditions (Bandara et al 2020) and can thus exert long-term influence on carbon cycling. Drained lake basins can effectively sequester atmospheric carbon as peat accumulates (Fuchs et al 2019), though peat and carbon accumulation may eventually decrease (Bockheim et al 2004, Jones et al 2012, Fuchs et al 2019). Drained lake basins can remain dry for millennia (Hinkel et al 2003, Shur and Jorgenson 2007), and succession and ground-ice development may lead to variable species composition depending on local conditions.

Changes in the frequency of thermokarst lake drainage events have been highly variable among permafrost landscapes in Alaska (Jones et al 2011, Swanson 2019, Nitze et al 2020, Jones et al 2020a) and northwestern Canada (Lantz and Turner 2015). However, increasing temperatures and rainfall and associated increase in energy fluxes to permafrost will likely increase the vulnerability of thermokarst lakes to drainage (Turetsky et al 2020). In addition, lake drainage can be accompanied by the formation or expansion of other water bodies as observed in Siberia (Karlsson et al 2012, Polishchuk et al 2015, Nitze et al 2020), Alaska (Chen et al 2014), and the Tuktoyaktuk Peninsula (Marsh et al 2009, Olthof et al 2015). While the overall surface water area has remained stable in many of these regions, the spatial redistribution of water bodies suggests that these lake-rich landscapes are in a state of climate-driven transition (Rowland et al 2010, Pastick et al 2019). Ongoing research and monitoring will build our understanding of the short and long-term consequences for ecology, hydrology, and carbon cycling.

Broadly, the study of permafrost-related disturbances would benefit from remote sensing studies which leverage higher-resolution sensors. Many of these disturbances at the individual scale can be quite small (e.g. frost circles, <3 m in diameter), and thus medium resolution satellites such as Landsat or Sentinel may miss small-scale changes in surface geology and vegetation driven by thermokarst processes. Additionally, more studies are needed to understand vegetation colonization and succession on newly available land created by permafrost-related disturbances.

Although frost circles are common across the entire Arctic climate gradient, the small size of individual features makes them difficult to detect, even in imagery with submeter spatial resolution. As a result, their distribution has not been mapped or constrained except at local scales. Such mapping of cryoturbated surfaces would be highly desirable, especially in the Low Arctic, where they are at risk of becoming less active (Aalto et al 2017). At present, areas that support dense frost circles can only be predicted based on coarse-scale maps of surficial geology and generalized soil texture. Whereas individual features may be challenging to identify, it may be possible to distinguish cryoturbated landscapes based on landscape-scale average spatial features.

There are numerous unknowns regarding the dynamics of ice-wedge degradation and potential re-stabilization, and the extent to which they are occurring. Ice wedges are generally insulated by a mat of vegetation and accumulating snow in the winter, and it is still unclear what weather conditions induce ice wedge melting and what might drive heterogeneity in degradation among ice wedges. It is also unclear what factors drive vegetation succession following ice-wedge degradation and the development of surface water ponds and troughs. One factor could be the availability of nutrients such as nitrogen and phosphorus (Beermann et al 2015, Herndon et al 2020), however only a few studies have attempted to address changes in nutrient concentrations following ice-wedge degradation (Norby et al 2019). Finally, the rates of accumulation of organic matter in degraded ice wedges and their potential for stabilization are still poorly understood. Field studies of ice wedge dynamics utilize space-for-time substitution, examining ice wedges at different stages of degradation (Jorgenson et al accepted) as opposed to assessing the dynamics of individual ice wedges over time.

There has been substantial progress on our capacity to gauge the extent of ice-wedge degradation utilizing high-resolution remote sensing and machine learning techniques (Witharana et al 2020, 2021). Whereas these studies and associated applications can map ice-wedge polygon networks across extensive areas of land, and even potentially estimate the fraction of land that contains ice wedges versus polygon centers, there is still work to be done to distinguish among the different stages of degradation.

There have been many studies that have documented the detection of cryogenic landslides (e.g. Barnhart and Crosby 2013, Balser et al 2014, Swanson and Nolan 2018), however, detection of the frequency of relatively small landslides may be difficult using medium resolution imagery (e.g. Landsat). Thus, large-scale mapping of these disturbances is difficult because the size of individual thaw slumps can be characteristically different depending on the region, and because high-resolution imagery at large scales is both cost prohibitive and difficult to work with.

Lake drainage events and associated impacts are complex and require additional research, especially where drainage frequency is increasing. Our ability to identify where and when thermokarst lake drainage will occur in the future must be refined. Existing data archives (e.g. Landsat 5–8, Sentinel-2) provide resources needed for identifying locations of past drainage and associated changes in land cover of larger lakes. While many studies have successfully utilized products from these sensors, the availability of scenes can be limited for any given year according to the timing of cloud-free conditions and the spatial resolution may not be adequate for detection of small-scale surface area change (e.g. <30 m resolution) or for smaller water bodies. Broader coverage of high-resolution (optical, radar and elevation) products will improve these analyses and enhance detection of landscape responses to drainage and geomorphological characteristics (e.g. the proximity of lakes to low-lying areas) that make lakes vulnerable to drainage.

Forest harvest activities are major disturbances in Canadian forests (Gauthier et al 2015), with 35%–40% of the Canadian boreal forest under industrial harvest and management (Burton et al 2003, Venier et al 2014). Industrial-scale forest management and economic activity have been an important component of the southern and eastern Canadian boreal forest since the 1800's (Venier et al 2014). For example, the Canadian forest products industry harvested over 710 000 hectares (∼143 million m³) of forest in 2020 (National Forestry Database 2020). In these higher productivity and more easily accessible southern and eastern regions, coniferous evergreen species (e.g. spruce, fir and pine) and aspen dominate the landscape and are utilized for lumber, pulp, and paper (Burton et al 2003, Venier et al 2014). In comparison, timber harvest is less extensive in the Alaskan boreal forest (Potapov et al 2008), where managed forests are generally concentrated in areas with high-value sawtimber species, adequate road access, and proximity to milling facilities—mostly in southeastern Alaska (Morimoto and Juday 2018) and episodically within the interior.

Clear-cutting is the most common silvicultural method used in the boreal forest (Haggstrom and Kelleyhouse 1996, Burton et al 2003, Cyr et al 2009). It was initially justified as an adequate replication of stand-replacing natural wildfire (Bergeron et al 2002); however, post-treatment belowground conditions (e.g. soil depth, nutrient content) can substantially differ from those following wildfire (Simard et al 2001), ultimately impacting post-disturbance successional trajectories in unique ways (Nguyen-Xuan et al 2000). Additionally, the coarse woody debris left after wildfire generates habitat for songbirds and other species, but is largely absent from post-harvest landscapes (Morissette et al 2002). Finally, post-treatment planting can increase regrowth compared to post-fire regrowth (Dieleman et al 2020). This is evident in the NDVI and NDMI time series for our logging case studies (figure 14), which in general show a faster initial recovery than those for fire (figure 4), and aligns with prior research (White et al 2017). However, it should be noted that other work has found the opposite result wherein post-fire forests recover slightly more quickly than harvested areas (Bartels et al 2016).

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Traditional clear-cutting results in even-aged forest stands, as all trees are either harvested or disturbed due to harvesting activity, with only a small fraction left to stand as a seed source. Consequently, intensively managed landscapes often yield an even distribution of tree ages across the managed area, with no or few stands older than the harvest rotation time (Bergeron et al 2002). When the rotation time is shorter than the fire frequency, the resulting stands will be less diverse in terms of stand structure and species composition than stands that grow for longer periods and allow tree replacement or fires to kill a population of trees. Long fire intervals (e.g. 200+ years) allow for shifts in canopy dominance and forest age structure as a result of forest successional processes (Bergeron et al 2002). Thus, biodiversity concerns for highly managed areas have arisen, particularly in southern and eastern Canada (Boucher et al 2009, Venier et al 2014).

While clear-cut or group selection harvests predominate areas with high value stands or in areas where managers are attempting to mimic fire, approaches such as partial harvest and individual tree selection in mixed or deciduous stands often allow for individuals with a range of ages to coexist and the promotion of certain forest types (Gauthier et al 2009). Such harvesting practices can help increase diverse forest structural attributes, particularly in stands that are even-aged following prior harvest practices (Bose et al 2015). Comparatively, selective harvest is less impactful on total stand biomass than even-aged selection or fire, and thus has a more nuanced signal from remotely sensed data. Notably, many selective harvest practices, particularly those which promote specific species or are considered variable retention that retain structural elements of the stand, have been examined for impacts on avian (Schieck et al 2000), vertebrate (Vanderwel et al 2009), understory plant (Macdonald and Fenniak 2007), and beetle (Wu et al 2020) communities. While group selection and clear-cutting are most common throughout the boreal forests of the North American ABZ, harvest for the purpose of maintaining biodiversity or transitioning forest types for fire management (Astrup et al 2018) also occurs throughout the region. These different harvesting techniques and the degree to which outcomes can vary from technique to technique are an important component of the impact of forest management on boreal vegetation and soils, and warrants further study, especially in the context of ongoing shifts in climate and fire regimes that impact regeneration patterns.

Oil and gas well production in the North American ABZ can be traced back a century to the still-active Norman Wells drilled in the 1920s in the Northwest Territories (Bone and Mahnic 1984). In British Columbia, the first commercial gas well was drilled along the Peace River in 1947 and the first discovery of oil in Alaska occurred in 1957. The density of wells in the ABZ is typically less than 1 km⁻², however some locations can be as dense as 3 km⁻² or higher (Warrack et al 2021).

Over its long history, oil and gas exploration and the associated production technology, practices, and regulations have evolved (King and King 2013, Kang et al 2016). Depending on the type of well (e.g. conventional oil, unconventional gas), intent of the well (e.g. production, exploration, injection), geology (including depth and formation properties), and other factors, the resulting disturbance to the surrounding vegetation can be highly variable in terms of size, shape, and form, with the area of influence ranging from tens to hundreds of square meters. The disturbance also varies temporally throughout the life cycle of the well from site preparation to plug and abandonment (Burnham et al 2012, Allen et al 2013).

For both exploratory and development (or production) wells, well site preparation includes constructing a well pad and access roads. The lengths of new access roads for well sites in the Wayne National Forest in Ohio are 8–30 km (USFS 2004), but the lengths of new access roads needed in the ABZ may be much longer (Pasher et al 2013, Wilkinson et al 2021). The well pad involves clearing land so that the drill rigs can be brought in. Wells meant for producing oil and gas are first cased with steel piping and cemented, and then the inside of the innermost casing is connected with the host rock containing oil and/or gas. These activities remove vegetation, degrade soils, result in loss of seed and bud stores (Pickell et al 2015), and lead to overall biodiversity and habitat loss (McDaniel and Borton 2002, Butt et al 2013, Northrup and Wittemyer 2013). Due to the impacts of well production on soil nutrients, hydrology, and seed sources, regeneration on well sites is slower than that following fire or forest harvest (Osko and MacFarlane 2001). Forest succession and regrowth and overall landscape recovery can thus take decades following oil and gas activity (Powers et al 2015, Chowdhury et al 2017). NDVI and NDMI responses to oil and gas wells (figure 15) show a clear decline in both vegetation moisture and greenness, with recovery lasting longer than ten years.

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The production life of a well is highly variable, with some wells remaining in production for decades and others being abandoned after only a few years. Nevertheless, all wells are eventually abandoned and, according to modern regulations, must be plugged and the well site restored (Kang et al 2019). In Alberta and British Columbia, site restoration involves removing surface infrastructure and re-vegetating the land to pre-development conditions (Kang et al 2021). However, some wells have not been plugged and abandoned according to these regulations and have not had the surface restored.

The largest anthropogenic disturbance across much of boreal and Arctic North America are seismic lines (Jorgensen et al 2010, Strack et al 2019), which are long linear clearings cut across forests and wetlands for oil and gas exploration (figures 1(d) and 16(a), (b)). Seismic exploration for underground sources of oil and natural gas involves drilling a series of holes 6–20 m deep along the lines and analyzing the reflection of sound waves generated from either explosives detonated at the site or truck-mounted surface vibrators (EMR 2006). Originally, these lines (previously known as legacy or 2D lines) were cleared using heavy machinery to cut through heavily forested areas (Dabros et al 2018), creating lines up to 10 m wide. Individual length varies but combined create a vast network; Strack et al (2019) estimated 345 000 km of seismic lines crossing peatlands in Alberta alone. This type of clearing results in the complete removal of the aboveground woody vegetation (Filicetti et al 2019) and significant soil and peat compaction, causing the water table to be much closer to the ground surface (Davidson et al 2020b). These changes in soil characteristics and hydrological conditions can alter understory vegetation composition, including shifts from feather moss-shrub dominated understories to complete cover by sedges (e.g. Carex aquatilis) in fen peatlands, or sphagnum moss (Sphagnum spp.) in bog peatlands (Deane et al 2020, Davidson et al 2021). In recent decades, there has been a move towards a method called 'low-impact' seismic lines, created using lighter-weight machinery and by hand and allowing for minimal disturbance to the ground-surface (Dabros et al 2018). These lines are narrower (1–5 m) than legacy lines but they are far more abundant on the landscape, creating a dense grid-like network of disturbances and can still create substantial changes to both tree cover (van Rensen et al 2015) and understory vegetation communities (Davidson et al 2021).

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Although the creation of some seismic lines occurred almost 40–50 years ago, tree recovery and regeneration in many of these locations is slow and often fails. For example, Lee and Boutin (2006) estimated that after 35 years, approximately 65% of seismic lines crossing forests in Canada's boreal plains remained free of woody vegetation. Yet, our mechanistic understanding of how seismic testing influences vegetation recovery is limited. For example, in wetland locations, mechanical flattening of localized topography can result in a water table closer to the ground surface, leading to unfavorable conditions for black spruce (Picea mariana) seedlings to regenerate (Lee and Boutin 2006, Caners and Lieffers 2014). Furthermore, the post-disturbance understory vegetation communities, often dominated by hydrophilic species such as sedges and sphagnum mosses, may outcompete slow growing tree saplings (Davidson et al 2020b). In addition to the initial disturbance, continued use of these linear features for hunting, recreational sports, and further resource extraction activities can hinder tree recovery (van Rensen et al 2015). This poor recovery can be seen in our Landsat case studies of vegetation response to seismic lines (figure 16). There is a substantial drop in NDVI and NDMI at both upland and peatland seismic line sites following disturbance given trees are actively removed, and NDMI recovery is slow.

Recent progress has been made to identify and map annual forest disturbance from logging across the North American ABZ based on the Landsat data archive spanning 1984–2014 (Zhang et al 2022). Between 1987 and 2012, 10.8% of the Alaska and western Canada experienced disturbance, with 1.4% attributed to logging. However, state and provincial forestry records are still an essential data source for understanding the scale and impact of logging and validating satellite detection of forest management, especially for lower-impact forestry practices that may be challenging for remote sensing approaches to detect. Such long-term data (e.g. polygons dating back to the 1960s, and GeoPDFs dating back to the 1800s in Saskatchewan, Canada) are crucial for studies of the impact of forest management on the North American boreal forest. However, many of these records are difficult to obtain. Similarly, data and records of seismic lines are not readily available across all Canadian provinces.

There are limited studies on land disturbances caused by oil and gas well production and exploration with only a few recent studies that are based in the contiguous U.S. (Raynolds et al 2014, Nallur et al 2020, Chomphosy et al 2021). Though databases with information on wells (i.e. intent, type, age, etc) are developed and maintained by numerous state, provincial, and territorial governments as well as the U.S. Bureau of Land Management for wells on federal lands, they can be incomplete (e.g. completely missing wells or incomplete information on well depth and age, etc). Nevertheless, these databases have been compiled for Canada and the U.S. to understand oil and gas well distribution, methane emissions, and other environmental impacts (Kang et al 2021, Williams et al 2021). Commercial databases are also available (e.g. GeoScout), however, they are not likely to contain information on the size of well pads and land disturbances. There is research on using machine learning and high-resolution imagery to detect active oil and gas well pads, which may provide data on well pad sizes and shapes (Bartsch et al 2020). Overall, there is a need for improved oil and gas well databases and information on well pads to understand the full extent of impacts.

Rain-on-snow events, or more broadly wet surface snow conditions (Pan et al 2018), are driven by a range of physical processes, though most often are caused by wintertime rain events that result in a wet snow surface (Singh et al 2000). Wet snow conditions can cause flooding and paludification in ABZ ecosystems, accelerate permafrost thawing, and decrease vegetation productivity (Rennert et al 2009, Bjerke et al 2014, Jeong and Sishama 2018). In mountainous regions rain-on-snow can destabilize the snowpack and trigger avalanches (Conway and Benedict 1994).

Most notably, re-freezing of melted snow creates ice barriers between the soil surface and the snowpack, making it difficult for ungulates such as caribou (Rangifer tarandus) and musk oxen (Ovibos moschatus) to forage for lichen during the winter (Putkonen et al 2009, Rennert et al 2009). These water and ice layers also facilitate the growth of toxic fungi, which can spoil lichens, further lowering wintertime food sources for ungulates, increasing foraging efforts and negatively impacting fat and protein reserves. In some cases, this can lead to movement of herds outside of their normal ranges, or even starvation and death, as occurred in 2003 on Banks Island, Canada (Putkonen et al 2009), when a severe rain-on-snow event resulted in the death of ∼20 000 musk oxen, reducing the island's population by 25%.

Along with direct impacts of rain-on-snow on vegetation freezing and flooding damage (Bjerke et al 2015), such severe impacts on ABZ ungulates can have cascading impacts on vegetation, predators, and the human populations that depend on the herds (Sokolov et al 2016, Serreze et al 2021). A significant decline in ungulates in one region can potentially release that vegetation from grazing and trampling pressure, whereas a movement of ungulates into a new area driven by rain-on-snow may cause significant vegetation damage (Vors and Boyce 2009).

Occurrence of rain-on-snow events depends on several factors, including air temperature, precipitation type, and extent and thickness of the snowpack (McCabe et al 2007, Freudiger et al 2014). Increases in energy flux to the snow surface, either through increasing temperature or increases in latent heat from rainwater, cause snowmelt as well as subsequent disruption of the insulative effect of the snowpack on the soil through increased liquid water content and increased energy flux to the soil (Rennert et al 2009, Kim et al 2015, Pan et al 2018). While an individual rain-on-snow event is generally short-lived—on the order of days—the subsequent impacts on soil hydrologic and thermal conditions can last months. The frequency of rain-on-snow is predicted to increase in the future in the ABZ due to rising temperatures (Ye et al 2008, Jeong and Sishama 2018, Pan et al 2018), with potential cascading impacts on hydrology, thermal conditions, ecosystem function, and ecosystem services.

Heat waves and extreme drought can damage ABZ vegetation, lower productivity, and cause vegetation mortality (Hogg et al 2008, Allen et al 2010, Michaelian et al 2011). Heat waves can occur both during the growing season and in winter, with differing impacts on vegetation. Wintertime heat waves occur when temperatures rise above freezing for several days (Phoenix and Lee 2004, Bokhorst et al 2011). As a result, snow melts across large regions (Bokhorst et al 2008, 2009), initiating spring-like physiological responses in plants such as de-hardening and loss of frost tolerance, increases in photosynthesis, and bud swelling (Crawford 2008, Bokhorst et al 2010). Once temperatures return to freezing or below, plants are exposed to extreme cold due to reduction of snow's insulating capacity and buds can be damaged by frost (Bokhorst et al 2008, Girardin et al 2022). When the warming event is accompanied by little or no soil thaw, plant damage can be worsened by plant transpiration in frozen soil, leading to cavitation and desiccation of leaves, i.e. 'frost drought' (Bokhorst et al 2008, Bjerke et al 2017, Comeau et al 2019). This plant damage can decrease productivity and lead to mortality. For example, an experimental manipulation study of a sub-Arctic heathland found a 50% reduction in gross primary production (GPP) after multiple extreme winter warming events (Bokhorst et al 2011). Such extreme warming events are predicted to increase in the future as temperatures rise (Meehl and Tebaldi 2004). In Utqiagvik, Alaska, the number of winter days with maximum temperatures above freezing has steadily increased since 1960, and several record-high days occurred in 2020 (as compared to the previous 20 years) (figure 17). Such temperature anomalies will continue to impact ABZ vegetation, potentially leading to plant damage and decreased productivity if wintertime extremes continue to increase (Richardson et al 2018).

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During the growing season, heat waves and severe droughts (either from increased temperatures or decreased precipitation) can lead to water deficits that increase vegetation stress, lower productivity, and can cause widespread mortality under severe conditions (figure 18(a); Hogg et al 2008, Allen et al 2010, Michaelian et al 2011, Peng et al 2011, Girardin et al 2021, Refsland and Cushman 2021). Such drought stress disrupts plant cell membrane function and can lead to xylem cavitation, with susceptibility to cavitation increasing with canopy height and varying by plant species due to differences in stomatal regulation (Allen et al 2010, McDowell and Allen 2015). Species-specific differences in drought response can alter stand structure and species composition if previously dominant species die off and are replaced by more drought-tolerant ones (Anderegg et al 2012). Drought can also cause regeneration failure and conversion of forests to woodland or grassland, particularly if compounded by other disturbances like fire (Whitman et al 2019, Baltzer et al 2021). Such drought and heat wave events can also trigger disease and insect outbreaks within already stressed vegetation (Raffa et al 2008, Boyd et al 2021, Ruess et al 2021). The impact of drought on vegetation greenness and moisture can be seen in a case study in the Northwest Territories for a drought that occurred in 2018 (figure 18(c)). Both NDVI and NDMI drop immediately following the drought, with slow recovery in vegetation moisture and more moderate recovery in NDVI.

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Severe droughts and heat wave events are increasing within the North American ABZ, particularly in the southern boreal zone (Michaelian et al 2011, Perkins-Kirkpatrick and Lewis 2020, Berner and Goetz 2022). An extreme drought in 2001–2002 in southwestern Canada resulted in a severe aspen mortality event, with 45 Mt of biomass lost, resembling the carbon impacts from a severe wildfire (Michaelian et al 2011). Drought and heat wave events impact water quality, nutrient availability, and biogeochemistry (Houle et al 2016, Tiwari et al 2018) They also have the capacity to feed back to climate change through loss of carbon stocks and subsequent emissions from decomposition (Michaelian et al 2011, Ma et al 2012), as well as changes to energy and water cycling due to changes in surface roughness, transpiration rates, and latent heat fluxes (Bonan 2008).

Windthrow, or tree blowdown events from high wind, are important disturbance agents within the North American boreal zone that act primarily at the stand-scale (Ruel 2000, Bouchard et al 2009). While extreme wind events resulting in stand-replacement are rare in the boreal zone, partial windthrow where some individuals survive is more common, with return intervals ranging from 40 to 450 years in eastern Canada (Ruel 2000, De Grandpré et al 2018).

Damage to trees depends on individual tree and stand factors, including tree size, species, canopy position, and previous stem damage, as well as soil depth and moisture, stand density, fragmentation, and angle with respect to wind direction (Peterson 2004). Tree size and species are the most reliable predictor of windthrow survival—some tree species are more 'wind firm' than others, and damage susceptibility increases with increasing tree size (Peterson 2004, Rich et al 2007). Because of the differential impact of partial windthrow on tree size and species, these events can cause shifts in the species composition and stand structure of impacted stands (Veblen et al 2001, Girard et al 2014). Windthrow can also act as a trigger for subsequent bark beetle outbreaks, as beetle populations are able to colonize and grow within downed stems (Wichmann and Ravn 2001).

Some of the main challenges of studying extreme weather events like rain-on-snow, winter warming, and windthrow include the sparsity of weather stations in northern regions, the lack of routinely deployed weather equipment (Putkonen et al 2009), and the unpredictable occurrence of events such as severe blowdown (Bouchard et al 2009). Detection of rain-on-snow events with satellite measurements is possible using radar, microwave, and multispectral imagery (Serreze et al 2000, Bartsch et al 2010, Pan et al 2018). Accurate detection of windthrow depends on the spatial resolution of remotely sensed measurements compared to the scale of the blowdown (Schwarz et al 2003). An enhanced monitoring network of weather conditions and snowpack, such as those present in the SNOTEL network (Schaefer and Paetzold 2001) would help better characterize and identify the occurrence of these events.

With respect to extreme drought and heat waves, while the physiological mechanisms underlying plant drought response and vulnerability are well established and emerging remote sensing techniques offer promise (Rogers et al 2018), it is still difficult to predict which individuals will die from such drought stress (Trugman et al 2021). Critical needs include further understanding of plant physiological and site characteristics that influence drought exposure and susceptibility and better information about how biotic agents interact with drought to cause plant mortality (Trugman et al 2021).

Despite their relatively small footprint in ABZ landscapes, riparian zones are disproportionately important for ecological disturbance (Scrimgeour et al 1994), hydrological processes (Ploum et al 2021), biogeochemical cycling (Blackburn et al 2017), species diversity (Johansson et al 1996, Andersson et al 2000, Johnson and Almlöf 2016), and wildlife (Tape et al 2016, Cooke and Tauzer 2020). In recent decades, substantial hydrologic changes have been observed on ABZ rivers, including changes to seasonal flow-regimes (Peterson 2002, McClelland et al 2006, Smith et al 2007, Rawlins et al 2010, Holmes et al 2021), groundwater relations (Okkonen et al 2010), river-ice breakup (Prowse and Beltaos 2002, Beltaos et al 2006), biogeochemistry and water quality (Tiwari et al 2022), and beaver colonization (Tape et al 2018, 2022). In addition, there have been widespread changes observed in permafrost extent both on floodplains and within their catchments (St. Jacques and Sauchyn 2009, Jones and Rinehart 2010, Quinton et al 2011, Tananaev and Lotsari 2022). It has been hypothesized that these processes will lead to a reduction in the areal extent of active floodplains in ABZ landscapes due to increased river channelization, smaller peak flows, and reduced riparian disturbance intensity (Ström et al 2011, 2012, Nilsson et al 2013, Jansson et al 2019).

Streams and rivers in the ABZ are strongly influenced by geology and topographic relief as well as hydroclimate, ice cover, and the permafrost regime (Ashmore and Church 2001, Rokaya et al 2018), with high variability in river morphology (Nilsson et al 2015). Streamflow rates can range from slow-moving tundra streams to large flowing rivers that span Arctic-boreal ecotones (e.g. the Mackenzie and Yukon rivers) (Nilsson et al 2015). Riparian ecosystems are especially dynamic because they experience frequent erosion, flooding, and sedimentation (Wiens 2002). Channel migration and flooding can be seen as similar to fire disturbance, both creating short-term destruction to vegetation with the capacity for regeneration following the event (Rood et al 2007). Channel migration in particular can 'reset' vegetation succession at any successional stage through floodplain erosion and simultaneous sedimentation and creation of new land for vegetation establishment (Walker and Chapin 1986, Viereck et al 1993, Van Cleve et al 1996, Helm and Collins 1997, Lininger et al 2017).

In addition to channel migration, ice-jam flooding is also an important disturbance in ABZ riparian zones. Ice-jams occur when ice floes in rivers are impeded by stationary ice covers, bridges, islands, or river width constrictions, leading to flooding (Rokaya et al 2018). Ice-jam flooding can occur during any river ice freeze-up or breakup period but are most common during the spring breakup period (Beltaos and Prowse 2009, Rokaya et al 2018). Ice-jam flooding causes significant economic and structural damage, and can result in loss of human life, made more prevalent by their unpredictable nature (Massie et al 2002, Mahabir et al 2008, Rokaya et al 2018). These floods also disrupt aquatic and riparian habitat through decreased fish habitat, and damage to and even removal of vegetation adjacent to the stream (Lind et al 2014, Lindenschmidt et al 2016). Ice-jam flooding also exerts a strong influence on the water balance of lakes within river floodplains and deltas, and the floodwaters supply sediment, nutrients, and contaminants. These processes have been investigated in the Slave River and Peace-Athabasca Deltas where floodwaters replenish nearby basins and offset evaporative water loss (e.g. Brock et al 2009, Wolfe et al 2012) while also increasing concentrations of suspended sediment (and turbidity of the lake water), major nutrients, and contaminants such as polycyclic aromatic compounds and metals (Hall et al 2012, Wiklund et al 2012, Elmes et al 2016, MacDonald et al 2016, Kay et al 2020). Reductions in the frequency of flooding leave lakes across these landscapes at risk of drying (Wolfe et al 2012). Sustainable management of ice-jam flooding thus includes balancing both the detrimental and beneficial aspects of these events on socio-economic and ecological systems (Das et al 2018).

Beavers are important ecosystem engineers in the North American ABZ through their dam-building and hydrologic engineering of rivers, streams, sloughs, and lakes. Previously considered only a sub-Arctic species, recent observations show beaver colonization into low arctic tundra regions of Alaska and Canada in recent decades (Tape et al 2018, Jones et al 2020b, 2022) due to climate-change driven landscape change as well as population recovery from historical over-trapping (Tape et al 2018). Beaver dams trap water on the landscape, turning streams and sloughs into connected ponds, widening riparian zones and altering groundwater flow (Westbrook et al 2006, Tape et al 2022). Jones et al (2020b) found that beavers preferentially targeted thermokarst landforms in their dam-building activities within the Baldwin Peninsula, Alaska, accounting for 60% of the increase in surface water in the region between 2002 and 2019. Increases in surface and groundwater due to beaver dams transfers additional heat to the ground and thaws permafrost surrounding and beneath beaver ponds (Tape et al 2022). In permafrost-affected regions, beavers have the capacity to initiate and affect lake formation and drainage, ice-wedge degradation, cryogenic landslides, and other thermokarst events (Jones et al 2018, 2021). These physical changes to waterways and the surrounding permafrost effectively create warmer patches of mixed aquatic and terrestrial ecosystems that likely act as oases.

Given the role of climate and extreme events on floodplains, spatiotemporal properties of disturbance, succession, and floodplain evolution are likely to be influenced by recent climatic warming at high latitudes, leading to important changes in the structure and function of riparian ecosystems in the ABZ. However, most ecosystem change studies to date have focused on upland and lowland ecosystems, whereas the observational record for riparian zones is comparatively sparse. There is thus substantial uncertainty concerning recent changes and future trajectories on floodplains across gradients of climate, stream order, catchment size, and floodplain morphology. For example, the pace of vegetation succession may increase in a warming climate due to longer, more productive growing seasons and changes in permafrost properties on or near riparian zones, particularly in forest-tundra ecotones (Wilmking and Juday 2005, Kharuk et al 2006, Beck et al 2011), while altered flow-regimes may influence the frequency and intensity of disturbance regimes. In Alaska, several studies have documented conspicuous, long-term increases in the extent and canopy height of tall shrublands in subarctic and Arctic riparian zones (Tape et al 2011, Brodie et al 2019, Liljedahl et al 2020). Understanding the interactions between biological and physical processes in the context of climate warning is important for assessing long-term impacts of continued warming on ABZ floodplains.

Beaver activity may be an important disturbance within permafrost regions, potentially causing widespread changes to the hydrologic and biotic environment, and initiating permafrost degradation (Tape et al 2022). Current research is exploring how these newly constructed oases affect carbon cycling, aquatic and terrestrial biodiversity, fish, and other ecosystem attributes. Further investigation is needed to understand the spatial extent and implications of beaver activity within the North American and circumpolar ABZ (Tape et al 2022).

Mammalian herbivores like moose (Alces alces), caribou (Rangifer tarandus), and snowshoe and arctic hares (Lepus americanus, L. arcticus) impact ABZ ecosystems through coupled herbivore-vegetation feedbacks. For example, selective foraging, trampling, and inputs of excreta, urine, and decomposing carcasses can directly alter plant community composition or indirectly affect ecosystem properties through changes to soil characteristics and nutrient cycling (Olofsson et al 2004, Väisänen et al 2014, Schmitz et al 2018, Leroux et al 2020). These species are also a crucial subsistence resource for indigenous communities (Rexstad and Kielland 2006). Caribou in particular occur in high abundance across much of the North American ABZ, numbering in the millions, and are one of the Arctic's most ecologically, culturally, and economically important species (Hummel and Ray 2008, Parlee et al 2018, Gagnon et al 2020). These large herbivores also make some of the longest terrestrial animal migrations in the world, with some herds traveling over 1000 km from boreal wintering grounds to Arctic tundra breeding grounds (Gurarie et al 2019, Joly et al 2019). During calving and migratory periods, caribou herds aggregate in dense groups and can alter landscapes as they pass through, impacting vegetation cover and structure, soils, and ecosystem carbon storage (Olofsson and Post 2018).

The distribution and intensity of caribou impacts are driven primarily by grazing and trampling associated with fluctuations in population sizes, which occur on a multi-decadal basis (Gunn 2003, Vors and Boyce 2009, Joly et al 2011). These fluctuations are influenced by snow conditions and forage availability (Post and Forchhammer 2002, Gunn 2003, Joly et al 2011). A meta-analysis of caribou impacts on vegetation cover across the Eurasian and North American ABZ showed a clear negative effect on lichen (Bernes et al 2015). Because lichens are slow to recover from disturbance, this impact is both acute and long-lasting (Suominen and Olofsson 2000, Joly et al 2009, Macander et al 2020). Reductions in lichens in turn drive density-dependent feedbacks on caribou, causing population declines and influencing population cycles (Manseau et al 1996, Gunn 2003). Impacts of caribou trampling and grazing on vegetation can also include transitions to graminoid dominated communities (van der Wal 2006), and constraints on deciduous shrub expansion (Olofsson et al 2009, Christie et al 2015, Bråthen et al 2017) or treeline advance (Munier et al 2010, Bryant et al 2014). Caribou impacts are most pronounced in arctic environments where population densities are highest. In the boreal zone, low caribou density likely minimizes impacts.

In contrast, herbivores like hares and moose in the boreal forest can shift the age distribution of the foraged species towards younger age classes (Butler 2003, Kielland et al 2006). Selective feeding can also shift species composition. For example, moose herbivory can cause a shift from palatable deciduous species towards unpalatable evergreen species (Pastor et al 1988, Kielland et al 2006). Recent work suggests that moose alter their behavior to favor dense canopy areas during increased summer temperatures, suggesting shifts in areas vulnerable to browsing under warmer conditions (Jennewein et al 2020). Whereas moose generally avoid evergreen species like white spruce (Picea glauca), snowshoe hares browse heavily on white spruce seedlings, especially during periods of high hare abundance (Rexstad and Kielland 2006, Angell and Kielland 2009, Sharam and Turkington 2009, Hollingsworth et al 2010). Snowshoe hare populations in Alaska and Canada exhibit cyclic dynamics, driven by predator population size and herbivore-vegetation feedbacks (Krebs et al 2018). During peaks that occur about every ten years, snowshoe hare browsing can alter vegetation composition and plant chemical defenses (Fox and Bryant 1984), suppress the succession of white spruce (Olnes and Kielland 2016), and curb treeline advance (Olnes et al 2018).

Most studies of herbivore impacts on vegetation use exclosures to assess what happens when herbivores are removed from a system. However, responses of vegetation to increasing vs. decreasing grazing pressure are not equal (Olofsson 2006). For example, studies that examine the impact of increasing caribou herd size (typically observational) often report stronger impacts than experiments that exclude caribou and examine the impact of decreasing herd size (typically manipulative) (Olofsson 2006). Geographic disparities in research can also influence conclusions. For example, studies of caribou impacts on vegetation primarily come from Fennoscandia (Soininen et al 2021). This raises issues of transferability of results because ecological conditions are different. Most caribou in Fennoscandia are managed in domesticated or semi-domesticated herds that often occur at higher densities than wild herds in North America (Bernes et al 2015).

Results from remote sensing and modeling studies which attempt to capture the relationship between caribou population density and vegetation productivity have produced mixed results, with some studies reporting significant negative relationships (Rickbeil et al 2015, Yu et al 2017, Campeau et al 2019) and others reporting weak or non-significant relationships (Fauchald et al 2017). Recent work by Davidson et al (2020a) provides and extensive collection of animal tracking datasets that can be used to analyze climate-driven variation in animal movement and foraging activity. As remote sensing technologies improve, increasing spectral and spatial resolution of satellite imagery might bolster the ability to quantify herbivore impacts across space and time.