Impacts of active retrogressive thaw slumps on vegetation, soil, and net ecosystem exchange of carbon dioxide in the Canadian High Arctic
Abstract
Retrogressive thaw slumps (RTS) are permafrost disturbances common on the Fosheim Peninsula, Ellesmere Island, Canada. During the 2013 growing season, three different RTS were studied to investigate the impact on vegetation composition, soil, and growing season net ecosystem exchange (NEE) of CO2 by comparing to the adjacent undisturbed tundra. Eddy covariance and static chamber measurements were used to determine NEE and ecosystem respiration (Re), respectively. Vegetation cover was significantly lower in all active disturbances, relative to the surrounding tundra, and this affected the overall impact of disturbance on CO2 fluxes. Disturbances were characterized by greater Re compared to surrounding undisturbed tundra. Over the mid-growing season (34 days), eddy covariance NEE measurements indicated that there was greater net CO2 uptake in undisturbed versus disturbed tundra. At one site, the undisturbed tundra was a weak net sink (−0.05 ± 0.02 g C m−2 day−1), while the disturbed tundra acted as a weak net source (+0.07 ± 0.04 g C m−2 day−1). At the other site, the NEE of the undisturbed tundra was −0.20 ± 0.03 g C m−2 day−1 (sink), while the disturbed tundra still sequestered CO2, but less than the undisturbed tundra (NEE = −0.05 ± 0.04 g C m−2 day−1). Two of the RTS exhibited average soil temperatures that were greater compared to the surrounding undisturbed tundra. In one case, the opposite effect was observed. All RTS exhibited elevated soil moisture (+14%) and nutrient availability (specifically nitrogen) relative to the undisturbed tundra. We conclude that RTS, although limited in space, have profound environmental impacts by reducing vegetation coverage, increasing wet soil conditions, and altering NEE during the growing season in the High Arctic.
Résumé
Les glissements rétrogressifs dus au dégel (GRD) sont des perturbations du pergélisol courantes sur la péninsule Fosheim de l'île d’Ellesmere, Canada. Pendant la saison de croissance 2013, on a étudié trois GRD différents afin d’examiner l'impact sur la composition de la végétation, le sol et l'échange net d'écosystème (ÉNÉ) de CO2 de la saison de croissance en comparant à la toundra adjacente non perturbée. La covariance des turbulences et des mesures de chambre statique ont servi à déterminer l’ÉNÉ et la respiration de l'écosystème (Ré), respectivement. La couverture de végétation était significativement moindre dans le cas de toutes les perturbations actives, par rapport à la toundra environnante et ceci a eu une influence sur l'impact global de la perturbation sur des flux de CO2. Les perturbations ont été caractérisées par une plus importante Ré comparée à la toundra environnante non perturbée. Au cours de la pleine saison de croissance (34 jours), les mesures de covariance des turbulences et d’ÉNÉ révélaient qu’il y avait une plus importante assimilation nette de CO2 dans la toundra non perturbée comparativement à celle perturbée. À un site, la toundra non perturbée était un puits net faible (−0,05 ± 0,02 g C m–2 jour–1) tandis que la toundra perturbée était une source nette faible (+0,07 ± 0,04 g C m–2 jour–1). À l'autre site, l’ÉNÉ de la toundra non perturbée était −0,20 ± 0,03 g C m–2 jour–1 (puits) tandis que la toundra perturbée séquestrait toujours le CO2, mais moins que la toundra non perturbée (ÉNÉ = −0,05 ± 0,04 g C m–2 jour–1). Deux des GRD ont affiché des températures moyennes de sol qui étaient plus élevées comparées à la toundra environnante non perturbée. Dans un cas, l'effet opposé a été observé. Tous les GRD ont affiché une humidité de sol élevée (14%) et un apport d’éléments nutritifs important (spécifiquement d'azote) par rapport à la toundra non perturbée. Nous concluons que les GRD, bien que sur une surface restreinte, ont des impacts sur l'environnement en réduisant la couverture de végétation, en augmentant des conditions de sol humide, et changent l’ÉNÉ pendant la saison de croissance dans le Haut-Arctique. [Traduit par la Rédaction].
Introduction
Permafrost disturbances are expected to increase in frequency and magnitude with predicted climate change (ACIA 2005; Vincent et al. 2011; Kokelj and Jorgenson 2013; Segal et al. 2016). In the High Arctic, common permafrost disturbances include active layer detachment slides (ALDS) and retrogressive thaw slumps (RTS). RTS occur when ground ice is exposed (including after an ALDS has occurred), soil and vegetation are removed upslope, and the thawed material moves downslope as the ground ice melts (Lantuit and Pollard 2008). RTS remain active until ground ice is depleted or further thaw is prevented by falling blocks of soil and vegetation, which act as insulation (Burn and Friele 1989).
Ecosystem responses to these permafrost disturbances have focused on hydrological impacts (Kokelj and Lewkowicz 1998, 1999; Lamoureux and Lafrenière 2009). In aquatic ecosystems, physical and chemical changes of sediment and water following slumping impact invertebrates, macrophytes, and diatoms, altering composition and abundance (Mesquita et al. 2010; Thienpont et al. 2013; Moquin and Wrona 2015; Chin et al. 2016). The ecological impacts of ALDS have been analyzed at few sites in the High Arctic and changes to the physical environment following a disturbance event have been shown to influence vegetation recovery (Desforges 2000; Cannone et al. 2010; Bosquet 2011; Cassidy 2011). The impacts of RTS on vegetation development have focused on Low Arctic ecosystems (Burn and Friele 1989; Bartleman et al. 2001; Lantz et al. 2009; Cray and Pollard 2015). Thaw slumps modify vegetation communities with changes persisting for centuries (Cray and Pollard 2015).
Due to the harsh conditions in the High Arctic (low temperatures, short growing season), recovery is predicted to occur more slowly than in the Low Arctic (Svoboda and Henry 1987). The removal of vegetation in the disturbance can reduce albedo by up to 50% (Babb and Bliss 1974). A reduction in albedo and removal of the soil organic layer can increase soil temperatures and deepen the active layer; however, the active layer may also increase due to the disturbance itself (Bliss and Wein 1972; Auerbach et al. 1997; Lantz et al. 2009). An increase in the active layer provides plant roots with more volume in the soil (Bliss and Wein 1972). In addition, the deeper active layer and warmer soil temperatures could result in greater nutrient availability through increased rates of decomposition and mineralization (Lantz et al. 2009). Plants that have deep roots, including species such as Calamagrostis canadensis (bluejoint grass) and Eriophorum angustifolium (tall cotton-grass), are common invaders in some disturbed tundra sites due to their ability to take advantage of extra soil volume and ability to disperse (Chapin and Shaver 1981).
CO2 fluxes between the surface and the atmosphere can be quantified by measuring net ecosystem exchange (NEE), the difference between CO2 emissions due to ecosystem respiration (Re) minus gross primary production. NEE of ecosystems is usually quantified by eddy covariance (EC) (Humphreys and Lafleur 2011; Lafleur et al. 2012; Emmerton et al. 2015) or clear closed chamber systems (Welker et al. 2004). NEE is influenced by temperature, moisture, and light levels, amongst other factors, and differs among plant community types (Baldocchi 2008). During the growing season, tundra ecosystems have generally been found to be CO2 sinks, but can easily shift to CO2 sources due to changes in temperature, moisture, and the water table (Vourlitis et al. 2000; Oberbauer et al. 2007). Chamber studies have found small but steady losses of CO2 during the winter (Welker et al. 2004). At Alexandra Fiord, Ellesmere Island, experimental warming using open top chambers impacted NEE differently based on soil moisture, due to differences in respiration between wet and dry sites (Welker et al. 2004). Across a latitudinal gradient, warming tended to increase respiration, with the greatest increases found in dry ecosystems (Oberbauer et al. 2007). Previous studies examining Arctic NEE have found large interannual variability within and among sites. This variability has been substantial enough to shift the system during the growing season from a CO2 sink to a CO2 source (Griffis and Rouse 2001; Kwon et al. 2006; Merbold et al. 2009). However, there are few measurements of NEE from Arctic tundra sites, especially from the High Arctic, which combined with the inherent variability and the low flux strength in Arctic tundra ecosystems makes it difficult to determine relative NEE across the Arctic and the contribution to regional and global fluxes (Lafleur et al. 2012). Cassidy et al. (2016) simultaneously quantified growing season NEE over an active RTS and its surrounding undisturbed tundra at a High Arctic site. The RTS acted as a net source of carbon, while surrounding undisturbed tundra acted as a net sink.
Vast amounts of carbon are stored in permafrost soils, and Hugelius et al. (2013) estimated that these soils contain 50% of the worldwide belowground organic carbon, with the greatest stores found in yedoma and low Arctic soils. These estimates are likely an underestimation (by up to a factor of 2) due to measurement difficulties and uncertainty regarding carbon storage in cryoturbated soils (Hugelius et al. 2013). Schuur et al. (2008) found that organic carbon that is unfrozen can be released to the atmosphere through microbial respiration. Thus, permafrost disturbance could result in the release of previously frozen carbon from this massive storage reservoir.
In this study, we assessed how the changes that result from permafrost disturbances in the High Arctic influence spatial heterogeneity in CO2 exchange. We focused on changes in vegetation, the unique soil characteristics, and the fluxes of CO2 that are associated with thaw slumps at different stages of recovery. The research objective was to determine the variability of vegetation composition and cover, thaw depth, soil thermal, moisture and nutrient characteristics, and CO2 fluxes among three RTS that varied in time since their formation and adjacent undisturbed tundra.
Materials and methods
Study area
Research was conducted on the Fosheim Peninsula, western Ellesmere Island, Nunavut (79°58ʹ21ʹʹN, 84°17ʹ41ʹʹW, 100 m above sea level). ALDS and thaw slumps are common in the area (Kokelj and Lewkowicz 1998). Multiple sites with RTS were identified during summer 2012 and monitored during summer 2013. The dominant vegetation in the area is characterized as dwarf shrub – graminoid tundra that is found on uniform, weakly alkaline to neutral cryosols (Edlund et al. 1989). The geological substrate is sandstone of the Eureka Sound group (Bell 1996) with marine silts and sands varying in thickness above the bedrock (Robinson and Pollard 1998). The upper limit of marine inundation at the end of the last glaciation is approximately 140 m above sea level (Bell 1996), and limited vegetation is found above this level. This region is an area of ice rich permafrost. Due to the nature of the permafrost and increased summer temperatures and precipitation over the last 20 years, there has been an increase in the occurrence of permafrost disturbances (Lewkowicz and Harris 2005).
Previous research on the Fosheim Peninsula has focused on the initiation, stabilization, and hydrological impacts of ALDS (Kokelj and Lewkowicz 1998, 1999; Lewkowicz 1990, 2007; Robinson 2000; Lewkowicz and Harris 2005); however, limited work has focused on the ecological impacts, especially on vegetation and CO2 fluxes (Desforges 2000; Cannone et al. 2010; Cassidy et al. 2016).
Site selection and description
Three RTS were selected for detailed measurement and analysis, based on vegetation characteristics and the nature of the disturbances (Table 1). Aerial photograph analysis using photographs taken in 1949 show that these sites were not visible on the landscape and indicate that these disturbances formed after 1949. Therefore, these disturbances could be 50+ years old; however, numerous disturbances formed during the particularly warm summers of 1988 and 1998, so they may have occurred during these seasons (Lewkowicz and Harris 2005).
Table 1.
Two of these disturbances were situated on east-facing slopes and are referred to as sites RTS-1 and RTS-2 (Fig. 1) and were selected because they are both part of a larger string of disturbances. EC flux towers were established at RTS-1 and RTS-2 on the periphery of the disturbance (Figs. 2 and 3). Both EC flux towers were located on the northern edge of the RTS; the area north of both towers was undisturbed tundra, while that south was influenced by the RTS and in part by the other disturbances in the vicinity.
Fig. 1.
Fig. 2.
Fig. 3.
Two sampling transects were established at RTS-1 and RTS-2. The two transects at each RTS were each 60 m in length and were established perpendicular to one another with the EC flux tower located at their intersection on the undisturbed periphery of the RTS (Fig. 2). With this setup, each transect encompassed both undisturbed and disturbed tundra. Plots (5 m × 5 m) were established at 15 m intervals beginning at 15 m from the edge of the disturbance to minimize edge effects. The active centre of these disturbances could not be sampled due to the liquefied slurry of sediment. Increased activity and flows throughout the latter part of the season inundated a segment of one disturbed plot at RTS-2.
A third disturbance, RTS-3, was located on a west-facing slope. A portion of the headwall within this disturbance had been insulated by fallen blocks of soil and vegetation, preventing further thaw, and so was inactive and a revegetated (recovered) zone was selected and compared with the undisturbed surrounding terrain. This zone spanned the northern and southern edges of the current active headwall. The southern recovered region covered an area of 1250 m2 (with a maximum length of 65 m and a maximum width of 35 m), the northern recovered region occupied 835 m2 (maximum length of 45 m and maximum width of 30 m), and both regions accounted for approximately 12% of the total area of disturbance. At RTS-3, undisturbed and disturbed (and recovered) terrain was sampled using four transects, each 50 m. Two transects were established across the disturbance (across the southern and northern recovered areas, at a minimum distance of 10 m from the recovered headwall) and the other two were positioned across the surrounding undisturbed terrain (Fig. 2b). Six plots (5 m × 5 m) were located in each zone (recovered and undisturbed), at a distance of at least 3 m from the current active region and 3 m from the recovered headwall, respectively. Plots were located at distances of 5 m along the transects.
Vegetation sampling
Vegetation was sampled at each plot along transects using a 50 cm × 50 cm quadrat separated into 5 cm squares. Vegetation composition and abundance (cover) were estimated inside five quadrats in each plot: one at the centre of the plot and four times surrounding the plot centre. These quadrats were haphazardly located by blindly throwing a small trowel and placing the quadrat where the trowel fell with the tip of the trowel end in the southeast corner of the quadrat. Percent cover of each vascular plant species and total moss and lichen cover were visually estimated for each species in each quadrat. The same observer made all visual estimates.
Soil characteristics
Thaw depth was measured using a thin metal probe, which was inserted into the ground until the depth of refusal (permafrost) was reached. Thaw depths were measured at the end of the season on 27 July 2013 at each site. At each slump, thaw depth was measured 18 times, while 24 measurements were made outside the slump in the undisturbed tundra.
Soil temperature was measured every minute using Hobo Pendant Temperature/Light Data Loggers (model UA-002-64; Onset Computer Corp., Bourne, Massachusetts) installed at a depth of 5 cm belowground. These sensors were deployed on 2 July 2013 and retrieved on 29 July 2013. A total of 18 loggers were deployed at disturbed (d) and undisturbed (c) plots at RTS-1 and RTS-2 (Nd = 8, Nc = 10). Loggers were positioned in the centre of each plot as shown in Fig. 2 and an additional logger was placed at the EC tower. Four loggers were deployed at RTS-3 (Nd = 2, Nc = 2), with one placed along each transect, in the centre plot.
Soil moisture was measured manually using a calibrated time domain reflectometry (TDR) probe (HydroSenseII Soil Water TDR, Campbell Scientific Inc., Logan, Utah) with 12 cm rods. Soil moisture was recorded at three locations within each plot along each transect and three locations between plots at 10 day intervals throughout the season (Nd = 18, Nc = 18). Additional measurements were taken at both flux towers and 10 m upslope and downslope of the tower (N = 9).
Surface albedo was estimated using a handheld pyranometer (LI200X; Campbell Scientific Inc.), mounted at a height of 1 m to allow for instrumentation to be leveled for all measurements. Measurements were made upwards and downwards during cloud-free conditions on 10 July 2013 (between 10:00 and 14:00) at each plot along the transects.
Soil nutrient availability was measured using ion-exchange membranes (PRS Probes, Western AG, Saskatoon, Saskatchewan). Four cation and four anion membranes (each 17.5 cm2 membrane was mounted in a plastic holder 15 cm × 3 cm × 0.5 cm) were inserted 10 cm into the soil in the centre of each plot. These were deployed on 2 July 2013 and retrieved 26 July 2013 for a 24 day sampling period. At RTS-1 and RTS-2, probes were placed along the transects for a total of Nd = 6 and Nc = 9 sites. At RTS-3, probes were placed in the centre of each plot (Nd = 6 and Nc = 6). Samples were processed during September 2013 at Western AG in Saskatoon using an automated flow injection analysis system and inductively coupled plasma spectrometry.
Portable CO2 efflux chamber system
On 30 June 2013, 28 opaque PVC collars (10 cm diameter, area = 78.5 cm2, depth = 6 cm) were installed at sites RTS-1 (N = 8), RTS-2 (N = 8), and RTS-3 (N = 12) for a total of 14 collars in both disturbed and undisturbed tundra. The collars were inserted 4 cm into the soil to minimally disturb soil and vegetation and they extended 2 cm above the ground surface. Collars were spaced across transects at each plot (Fig. 3). Due to the variability of vegetation cover, collars were placed on both vegetated and unvegetated tundra within the disturbed and undisturbed tundra.
A non-steady-state portable chamber system similar to Jassal et al. (2005) was used to measure ecosystem respiration from each collar using an opaque chamber (Figs. 3a and 3b). The measurement head was a PVC chamber with a volume of 1.4 × 10−3 m3 (height 15.6 cm, diameter 10.7 cm). The chamber head was placed on each collar for 2 min intervals. A foam gasket was used to seal the connection between collar and chamber head. A pump (flow rate 600 cm3 min−1) circulated air from the chamber head into a portable battery-operated infrared gas analyzer (IRGA) (LI-840; LI-COR Inc., Lincoln, Nebraska) and back into the chamber through a closed circuit. The IRGA determined CO2 mixing ratios ([CO2] in ppm) and water vapour concentrations at a temporal resolution of 1 Hz during each run.
Respiration (Re) was calculated from Δ[CO2]/Δt (linear regression over 2 min, discarding the first 10 s):
(1)
where ρ is the molar density of air (mol m−3) calculated from measured air temperature, D̅ is dilution considering [H2O], Δ[CO2dry]/Δt is the rate of change of CO2 mixing ratio over time (μmol mol−1 s−1), and V and A are chamber volume and area, respectively. Measurements were made on two days during the season (17 and 27 July 2013) and were taken between 10:00 and 16:00 on each day to minimize diurnal changes in light and temperature.
EC measurement of NEE
We used an EC tower and wind directional partitioning to measure NEE from disturbed and undisturbed tundra. Two towers were located at RTS-1 and RTS-2, and each tower was established 2 m from the edge of the disturbance (and 50 and 60 m away from the headwall, respectively). Both EC systems were mounted on tripods at and ran continuously from 26 and 27 June 2013, respectively, until 29 July 2013 (Fig. 3). Each system included an ultrasonic anemometer (CSAT-3; Campbell Scientific Inc.) and a co-located open-path IRGA (LI-7500; LI-COR Inc.) (installed tilted by 30°), both established at 1.75 m, a temperature and humidity sensor (HMP; Campbell Scientific Inc.) at 1.3 m, a net radiometer (NR Lite; Kipp & Zonen B.V., Delft, The Netherlands) at 1.2 m, and a quantum sensor (SQ-110; Apogee Instruments Inc., Logan, Utah) at 1.2 m. Ultrasonic anemometers were sampled at 60 Hz and data output was stored at 10 Hz. The IRGA was sampled at 10 Hz, and all data were stored on a data logger (CR1000; Campbell Scientific Inc., Edmonton, Alberta). Both towers were placed with the IRGA and sonic anemometer parallel to the slump edge to avoid any flow distortion effects from preferred wind sectors associated with flow past the sensors and the head wall of the slump (data were removed in sectors with flow distortion). Partitioning based on wind direction allowed measurement of fluxes from disturbed and undisturbed tundra. Friction velocity (u*) thresholds of 0.10 m s−1 were applied to remove data under low-turbulence conditions. Both IRGAs were tiled 30° from the vertical to minimize issues with sensor heating and reduce pooling of moisture on the windows. All IRGAs (EC tower and portable chamber) were calibrated prior to the field season using a two-point calibration in the laboratory against standards from the Greenhouse Gas Measurement Laboratory (GGML), Meteorological Service of Canada (using a zero gas and span gas of known mixing ratio).
Flux data processing
Molar fluxes of CO2 (Fc in μmol m−2 s−1) were computed in EddyPro (V5.1.1; LI-COR Inc.) with a missing sampling allowance of 30%. Fc was calculated over a 30 min averaging interval using double rotation for tilt correction, block average detrending, time lag detection, and Webb–Pearman–Leuning corrections (Webb et al. 1980). Data quality controls based on the flagging system proposed by Mauder and Foken (2004) were used and data categorized as level 2 were discarded. Corrections were applied for both low- and high-pass filtering effects according to Moncrieff et al. (1997, 2004). At low temperatures, measurements from upright (vertically mounted) open-path LI-7500 CO2 sensors have been shown to overestimate uptake rates of CO2 (Burba et al. 2008). To minimize this error, an LI-7500 head was mounted tilted from the vertical by 30°. As measurements were made during the warmest month of the year, with mean temperatures of 8 °C and a range of 0.5–17 °C, and with tilted IRGA installation, heating issues have been shown to be minimal under most conditions (see Cassidy et al. (2016) supplement for a detailed justification for not performing corrections on flux data). However, as potential issues have been associated with this sensor when fluxes are measured at lower temperatures, caution should be taken when transferring this methodology to shoulder seasons or when interpreting values measured at lower temperatures.
When winds were parallel to the edge of the disturbance, the source terrain could not be separated as disturbed or undisturbed, calculated NEE (Fc) values were not reliable, and fluxes from these sectors were discarded (46% of data). Fluxes with a difference greater than 5 standard deviations from the daily average of the 30 min values (of the same day) were removed. We averaged half hour NEE data into hourly fluxes. If one of the half hour values was not available and from the same segment (disturbed/undisturbed), the hourly value was then based on the single 30 min flux measurement. We filled remaining hourly gaps using the following methods: (1) gaps of less than 2 h from the same segment were filled using linear interpolation and (2) gaps greater than 2 h were filled using aggregate averaging over a rolling 5 day window selecting the same time of day and same segment. The data set was comprised of 90% original data and 10% gap-filled data, as 173 of the 1723 data points were modeled.
Statistical analysis
All statistical analysis was completed using the R programming language (version 3.1.2) (R Core Team 2016) to analyze differences between sites (RTS-1, RTS-2, and RTS-3) and the impact of disturbance (two zones: disturbed and undisturbed). To determine differences in community composition of vegetation among sites and between disturbed and undisturbed tundra (zone), we used nonmetric multidimensional scaling, a multivariate ordination technique based on Bray–Curtis distance matrices derived from percent cover data. A two-dimensional ordination displayed the least stress and was repeated 100 times to reach the best solution (Legendre and Legendre 1998). ANOSIM was used to test for differences among groups using the vegan package (Oksanen et al. 2012).
Indicator species analysis was used to determine species characteristic of each zone and site. Indicator species analysis calculates an indicator value (IVij) for species i in group j based on relative abundance (specificity: (Aij), and relative frequency (fidelity: Bij):
(2)
(3)
(4)
where x̅ij is the mean cover of species i within group j, Σjx̅i is the sum of mean cover of species i in all groups, nij is the number of samples in group j occupied by species i, and nj is the total number of samples in group j (McCune and Grace 2002). IVij ranges between 0 and 100 and strong indicators are those with IVij > 25.
Total cover was calculated as the sum of percent cover of live green material in each plot. Differences in environmental variables (total vegetation cover, soil moisture, thaw depth, soil temperatures) and CO2 fluxes were tested using two-way ANOVA (site × zone) with Bonferroni correction. Data were transformed to meet normality assumptions, when necessary. Post hoc Tukey tests were used to conduct pairwise comparisons. Soil nutrient availability data were analyzed with a nonparametric Kruskal–Wallis test to determine the effect of site (RTS-1, RTS-2, and RTS-3) and zone (disturbed, undisturbed).
Results
Micrometeorological conditions
Minimal differences in micrometeorological conditions were found between the two flux tower locations and so the data were combined to describe the conditions throughout the season (Fig. 4). Air temperatures (Fig. 4a) rose steadily throughout the season and reached a peak on DOY 197 (16 July 2013) before decreasing after day of year (DOY) 205 (24 July 2013); over the season, average air temperatures were 7.9 °C at RTS-1 and 8.6 °C at RTS-2. Vapour pressure deficit also rose, albeit at a more modest rate, with a maximum deficit on DOY 197–198 (16–17 July 2013) before decreasing at the end of the sampling season consistent with air temperature decreases (Fig. 4d). Photosynthetically active radiation (PAR) and net radiation displayed consistent diurnal fluctuations throughout the season (Figs. 4b and 4c).
Fig. 4.
Vegetation
Significant differences were found in plant community composition among the sites (Fig. 5). ANOSIM indicated differences in composition based on site and disturbance status (ANOSIM: R = 0.4312, p = 0.001, based on 999 permutations). Pairwise comparisons at each site also indicate compositional differences (Table 2).
Fig. 5.
Table 2.
Indicator species analysis (Table 3) supported the differences in composition among the sites and between zones (disturbed and undisturbed tundra) as shown using NMDS and ANOSIM. Undisturbed tundra was characterized as dwarf shrub graminoid tundra, with shrubs Salix arctica (Arctic willow) and Dryas integrifolia (mountain avens) found at these sites. Disturbed areas were dominated by rhizomatous grasses and sedges. At RTS-1, undisturbed tundra was characterized by Dryas integrifolia and Carex nardina; however, in adjacent disturbed tundra, vegetation cover was characterized by grasses, Poa glauca (glaucous bluegrass) and Alopecurus magellanicus (alpine foxtail). At RTS-2, undisturbed tundra was characterized by Salix arctica and moss; however, no unique vegetation was characteristic within the disturbance at RTS-2, which was largely unvegetated. At RTS-3, undisturbed tundra was characterized by Salix arctica, Dryas integrifolia, Puccinellia spp. (alkali grass), and lichen. The stabilized slump at RTS-3 was largely colonized by Carex aquatilis (aquatic sedge) and Alopecurus magellanicus. Common species were found at multiple sites, including Dryas integrifolia at RTS-1 and RTS-3 and Salix arctica at RTS-2 and RTS-3; however, differences were found in the overall community composition. Disturbed tundra was characterized by species able to recover and recolonize quickly and tolerate site conditions present in RTS.
Table 3.
Total cover (Fig. 6a) was not significantly different between disturbed and undisturbed tundra (F(1,878) = 2.52, p = 0.12); however, differences in cover were found between all sites (F(2,10534) = 15.08, p < 0.001). The interaction between zone (disturbed and undisturbed tundra) and site (RTS-1, RTS-2, and RTS-3) was significant (F(2,9574) = 13.71, p < 0.001), as total cover was lower within the disturbance at RTS-1 and RTS-2. However, this difference in cover was only significant at RTS-2, while at RTS-3, the reverse pattern was found, with significantly greater cover characterizing disturbed terrain. The lack of overall significance in the difference in total cover between disturbed and undisturbed tundra is based on stabilization of RTS-3 and the active nature of RTS-1 and RTS-2.
Fig. 6.
Soil thermal regime
Maximum thaw depth ranged from 50 to 81 cm. Overall, when maximum thaw depth was compared, no differences were found between disturbed and undisturbed tundra (F(1,36) = 2.10, p = 0.16) (Fig. 6b). However, there were significant differences in thaw depths among sites (F(2,36) = 7.59, p < 0.01) (Table 4), with the greatest depths found at RTS-2 (depth 72 ± 1 cm). There was also a significant interaction between disturbed and undisturbed tundra and site (F(2,36) = 6.00, p < 0.01). Spatial variability in thaw depths was evident across sites, as undisturbed tundra at RTS-2 had a significantly deeper active layer (depth 72 ± 1 cm) than the undisturbed terrain at RTS-1 (depth 58 ± 2 cm) and RTS-3 (depth 60 ± 1 cm). Thaw depths in the disturbances were slightly greater at RTS-1 (depth 71 ± 3 cm) and RTS-3 (depth 61 ± 3 cm) and slightly shallower at RTS-2 (depth 68 ± 5 cm), but these differences were not significant.
Table 4.
Soil temperatures at the 5 cm depth over the growing season were impacted by disturbance (F(1,14286) = 251.9, p < 0.001) (Table 4), as greater soil temperatures were found within disturbed soils at RTS-1 and RTS-2 (9.31 ± 0.1 and 8.6 ± 0.1 °C, respectively) when compared to adjacent undisturbed soils (7.2 ± 0.1 and 8.3 ± 0.1 °C, respectively). At RTS-3, lower temperatures were found in the disturbed (6.5 ± 0.1 °C) than in the undisturbed soils (8.2 ± 0.1 °C). This divergence in the direction of soil temperatures in active and stabilized slumps is shown in Fig. 7. Soils temperatures were significantly different among sites (F(2,14286) = 140.7, p < 0.001), with the coolest soil temperatures found at RTS-3 and the overall warmest temperatures at RTS-2.
Fig. 7.
Soil moisture regime
Soil moisture was greater (38.5% ± 0.9%) in the disturbed tundra than in the undisturbed terrain (24.0% ± 0.6%) at all three sites F(1,370) = 218.5, p < 0.01) (Fig. 6c). There was a significant interaction between site and disturbance (F(2,370) = 19.8, p < 0.01), as soil moisture measured within disturbed soils at RTS-3 was greater than in RTS-2; however, RTS-1 was not significantly different from RTS-2 or RTS-3. Undisturbed soils in RTS-1 and RTS-2 had similar soil moisture levels, and these undisturbed soil moisture values were greater than those in undisturbed tundra at RTS-3.
The average (±SE) albedo measured on 10 July 2013 at RTS-1 was 0.18 ± 0.00 in undisturbed tundra and 0.15 ± 0.01 in the disturbance. At RTS-2, undisturbed tundra had a slightly greater albedo (0.19 ± 0.01) than at RTS-1, while albedo in the disturbed portion of this site (RTS-2) (0.21 ± 0.01) was notably greater than at RTS-1. With all measurements combined, average albedo was very similar between the undisturbed tundra (0.18 ± 0.004) and the disturbed tundra (0.18 ± 0.01). Albedo was not measured at RTS-3.
Nutrient availability
Summary values of nutrient availabilities as measured using ion-exchange membranes are presented in Table 5. Total nitrogen was greater in disturbed soils, and differences in total nitrogen were driven by NO3−-N, which was also higher in the disturbances. Availability of NH4 did not differ between disturbed and undisturbed tundra (Table 6). Site variability was apparent in differences in the concentrations of K+ and NO3−, with greater availability of both ions found at RTS-1 and RTS-2 compared to RTS-3. Concentrations of micronutrients including SO42−, boron, Cu+, Fe2+, and Mg2+ were greater in disturbed soils. In addition, higher concentrations of Cu+ were found in disturbed soils at RTS-2 and RTS-3 but not RTS-1.
Table 5.
Table 6.
Ecosystem respiration
Ecosystem respiration (Re) measured over the growing season (Fig. 6d) was greater in disturbed zones (0.47 ± 0.09 µmol m−2 s−1) than in undisturbed zones (0.27 ± 0.06 µmol m−2 s−1), and these fluxes were significantly different (F(1,44) = 4.17, p = 0.05). When individual sites where examined, differential responses in respiration were found. At RTS-2 and RTS-3, greater respiration was found in disturbed zones (0.84 ± 0.43 and 0.52 ± 0.08 µmol m−2 s−1, respectively) compared to undisturbed zones (0.43 ± 0.15 and 0.25 ± 0.09 µmol m−2 s−1, respectively). This differed from RTS-1, as respiration from undisturbed tundra (0.21 ± 0.07 µmol m−2 s−1) was similar to respiration from disturbed tundra (0.20 ± 0.05 µmol m−2 s−1). Spatial variability in respiration was greater within the disturbed zone of RTS-2, while variability was similar in both zones at RTS-1 and RTS-3. Maximum respiration values were twice as large in disturbed areas (1.89 µmol m−2 s−1 found at RTS-2) compared to undisturbed areas (0.96 µmol m−2 s−1). When respiration was compared between all sites and zones, differences in respiration were found between sites (F(2,44) = 4.49, p = 0.02). Correlations among ecosystem respiration and ecosystem variables are presented in Table 7.
Table 7.
NEE
When EC-measured NEE was separated by wind direction (Table 8), undisturbed areas (wind from the north) at both sites were a net sink of CO2 (Fig. 8). At RTS-1, the undisturbed tundra sequestered an average of 0.19 ± 0.03 µmol CO2 m−2 s−1 over the measurement period, while the disturbed tundra sequestered only 25% of this amount at RTS-1 (0.05 ± 0.04 µmol m−2 s−1) (Fig. 9). At RTS-2, the undisturbed tundra sequestered 0.05 ± 0.02 µmol CO2 m−2 s−1, while the disturbed tundra released 0.07 ± 0.04 µmol m−2 s−1 over the measurement period. Variability in fluxes in undisturbed tundra was evident between these two sites, as the CO2 sequestered in undisturbed tundra at RTS-2 was similar to that sequestered by the disturbed tundra at RTS-1. Comparison of fluxes showed the influence of disturbance, as NEE from disturbed areas (NEEd = 0.00 ± 0.03 µmol m−2 s−1) differed significantly from NEE in undisturbed areas (NEEc = −0.13 ± 0.02 µmol m−2 s−1) (F(1,697) = 11.22, p < 0.0001). Site was also a significant factor, as fluxes differed between RTS-1 and RTS-2 (F(1,697) = 11.85, p < 0.0001). Tukey tests showed significant differences in NEE from undisturbed tundra at RTS-1 and all other locations and zones.
Table 8.
Fig. 8.
Fig. 9.
At each site, the relationship between air temperature and NEE was also explored. Linear regressions were calculated to predict NEE based on temperature and disturbance classification and their interaction at each EC tower. At RTS-1, a negative relationship was found between temperature and NEE (F(1,421) = 6.42, p = 0.01); however, disturbance classification (F(1,421) = 3.47, p = 0.06) and the interaction between disturbance and temperature (F(1,421) = 1.35, p = 0.24) did not significantly improve the model. At RTS-2, we also found a negative relationship (F(1,272) = 14.65, p < 0.01) between temperature and fluxes. There was a significant interaction between disturbance and temperature (F(1,272) = 5.23, p < 0.05), improving the model; however, disturbance alone did not (F(1,272) = 2.98, p = 0.08). When air temperatures were compared over the sampling period, significant differences were found between temperatures during situations when wind came from the disturbed and undisturbed sector at each site (Table 8). Average air temperatures at RTS-1 and RTS-2 were significantly different with wind direction. When wind came from the disturbed sectors, air temperatures were on average 6.5 ± 0.3 °C and 8.8 ± 0.4 °C at RTS-1 and RTS-2, respectively. Average air temperature was higher during situations when wind came from the undisturbed sectors (9.6 ± 0.3 °C and 10.5 ± 0.3 °C for RTS-1 and RTS-2, respectively). As air temperatures were different between situations that were sampled as disturbed and undisturbed tundra at each site, a conditional sampling by weighting bin averaged measurements based on air temperature was conducted (Fig. 9). Results indicated a significant effect of location, as fluxes differed between RTS-1 and RTS-2 (F(1,34) = 6.31, p < 0.05); however, CO2 fluxes from disturbed tundra were not statistically significantly different from fluxes from undisturbed tundra (F(1,34) = 1.84, p = 0.18).
Discussion and conclusion
Landscape mosaics were evident on the Fosheim Peninsula as a result of permafrost disturbances. Site characteristics that result from morphological modifications following retrogressive thaw slumping are dependent on initial site characteristics. These permafrost disturbances increase spatial heterogeneity at the fine and landscape scale. At our study location, three disturbances were compared to their respective undisturbed tundra in the surrounding area. Each site was characterized by different combinations of plant species, possibly due to the initial site conditions. We found vegetation differences across the three disturbances, which were likely the result of differences in soil moisture and are supported by a positive correlation between these variables: the newly disturbed tundra in RTS-1 was characterized by the grass Poa glauca, while the recovered tundra at RTS-3 had wet soil conditions and was dominated by Carex aquatilis. The greater soil moisture at RTS-3 was due to the re-exposure of ground ice that had begun to melt and the continued flow of meltwater, which allowed moisture-dependent species to colonize, including Carex aquatilis (Chapin et al. 1992). Increases in soil moisture were also present at the other two sites, and field observations suggest that differences were influenced by the quantity of meltwater provided by ground ice thaw at the headwall in addition to flow patterns present in the disturbance. The dynamic nature of these flow patterns can greatly modify vegetation composition during recovery. Bartleman et al. (2001) found that recovery trajectories in the Low Arctic (Mayo, Yukon) were altered by the depletion of ground ice and resulting lack of flow, which resulted in moisture-rich areas that were dominated by Equisetum spp. (horsetail) and drier areas of the slump that were characterized by Salix spp.
Additionally, thaw depths were impacted by disturbance. Differences in thaw depth at our study sites corresponded to reduced albedo. Lower albedo at RTS-1 resulted in greater absorption of solar radiation and a deeper thaw layer, while greater albedo corresponded to a shallower thaw layer at RTS-2. We found negative correlations between vegetation cover and thaw depth, likely in response to greater soil moisture in shallower active layers (and resulting in a slight negative correlation between soil moisture and thaw depth). Thaw depths are also impacted by winter snow accumulation, soil texture, organic layer development, and soil moisture, amongst other factors. At sites impacted by vehicle disturbance, Emers et al. (1995) found both increases and decreases in active layer depth associated with disturbed tundra, with shallower depth associated with insulating vegetation and complete removal of vegetation resulting in deeper depths. We found increased soil temperatures within disturbed soils at RTS-1 and RTS-2. However, at RTS-3, greater soil temperatures were found in the undisturbed terrain, which were likely a result of the increased shading by the greater vegetation cover in the recovering disturbance at this site. Less vegetation was found on the undisturbed surrounding terrain; thus, albedo was likely greater in the disturbance. The ground thermal regime can be altered by these permafrost disturbances for more than a century (Burn and Friele 1989), which contributes to the vegetation differences in and out of the disturbances.
Plant nutrient availability may be elevated by permafrost thaw, as soluble materials in the frozen ground may be released with ground ice melt associated with disturbance. Lantz et al. (2009) found increased plant available nitrate, sulfate, and calcium concentrations in RTS in the Low Arctic. Increased concentrations of various soil nutrients (including K+, Ca2+, Mg2+, Cl−, SO42−, and PO33−) have been found in soils impacted by cryogenic landslides on the Yamal Peninsula, Russia, and greater nutrient availability resulted in increased productivity of Salix spp. (Ukraintseva and Leibman 2000; Ukraintseva 2008). Ukraintseva (2008) also noted increases in soil fertility associated with increases in nitrogen and potassium availability in disturbed soils. At our study site, enhanced nutrient concentrations were found within disturbed terrain; however, we also found high variation within and among sites. Although elevated nutrient concentrations are found within disturbed areas, runoff from disturbances removes material released from thawing permafrost. The fluvial impacts following permafrost disturbance include pulses in sediment transport and increases in discharge and turbidity (Lamoureux and Lafrenière 2009; Kokelj et al. 2015).
On the Fosheim Peninsula, salt efflorescence accumulations have been found at sites located below the glacial marine limit and are largely related to disturbance, as dissolved solids that were previously trapped in frozen sediments were released and redistributed downslope (Kokelj and Lewkowicz 1999). Efflorescences were found within scar floors of the RTS sites and downstream from disturbances. Large concentrations of Na+ and salts in the active layer and runoff could negatively affect plant growth and revegetation of disturbed terrain, increasing the duration of modified drainage and enhancing erosion and may continue to alter the terrestrial system for 30 years or more (Kokelj and Lewkowicz 1999).
Ecosystem respiration (Re) was greater in disturbed soils than in surrounding tundra, and these patterns were consistent with measurements from other permafrost disturbances (Beamish et al. 2014; Cassidy et al. 2016). However, we found differential responses of Re based on site, as disturbed tundra was characterized by greater Re at sites RTS-2 and RTS-3, while undisturbed and disturbed tundra at RTS-1 had similar Re rates. Disturbed tundra that has undergone some revegetation, such as the recovered site at RTS-3, may also have larger gross primary production, which would offset increases in Re at these sites. Re was found to be positively correlated with thaw depth and weakly negatively correlated with soil moisture.
Loss of old carbon from permafrost has been associated with disturbance. Schuur et al. (2008) found a positive relationship between ecosystem respiration and old carbon release associated with permafrost thawing. On the Fosheim Peninsula, old carbon may be released due to permafrost disturbances, which may be responsible for increases in respiration in disturbed areas relative to undisturbed tundra at some sites; however, these increases were not significant at all sites.
Our NEE measurements are comparable to those at other High Arctic locations (specifically Lake Hazen, Ellesmere Island, and Cape Bounty, Melville Island), with uptake values that ranged between 0.2 and 2.2 g C m−2 day−1 (Lafleur et al. 2012). Despite the small magnitude of these fluxes, the impact of disturbance was evident. Although both disturbed and undisturbed tundra at RTS-1 sequestered a minimal quantity of CO2, the undisturbed tundra sequestered nearly four times the CO2 of the disturbed tundra. In addition, at RTS-2, the undisturbed terrain sequestered CO2 throughout the season whereas the disturbed tundra emitted CO2 to the atmosphere. The NEE of the undisturbed tundra at RTS-1 was substantially greater than at RTS-2, which was likely due to greater vegetation cover at this site. This indicates that the initial conditions of undisturbed tundra, such as vegetation composition and cover, influence the resulting carbon exchange of disturbed tundra through vegetation colonization and recovery within the disturbance.
When meteorological conditions were compared during times when fluxes were measured from disturbed and undisturbed wind sectors over the measurement period, significant differences were found (including air temperature and vapour pressure deficit). As we were unable to measure CO2 fluxes from both disturbed and undisturbed tundra simultaneously, our flux comparisons are dependent on wind directions. The magnitude of the estimated impact of disturbance may be influenced by the seasonality of CO2 fluxes. Cooler temperatures and greater wind speeds characterized times when fluxes were measured from disturbed tundra at both RTS-1 and RTS-2. As such, fluxes from these areas were found to be smaller than those measured during times when wind came from the undisturbed tundra sector, which were characterized by warmer temperatures during our measurement period. We used conditional sampling to address biases of meteorological conditions associated with fluxes from disturbed and undisturbed tundra. We posit disturbance had some effect on NEE, which is supported by our chamber measurements and the findings of Cassidy et al. (2016).
NEE measurements from High Arctic sites are generally smaller than those from Low Arctic sites (Lafleur et al. 2012). If disturbances occur in areas that sequester the most CO2 in a landscape, the effect on the landscape CO2 balance will be greater than in areas with lower initial sequestration. In the Low Arctic, very large slumps could have large impacts on the CO2 balance of landscapes, as this region is carbon rich and has higher fluxes (Lafleur et al. 2012). The lower CO2 fluxes measured and the smaller amounts of carbon in the soils of the High Arctic indicate that the impacts of disturbances here will not have the same magnitude of effects on regional carbon balance or the atmosphere as in the Low Arctic. Understanding the spatial variation in thermokarst will be critical to understanding the magnitude of their effects on the climate system.
Based on the data presented here, we draw the following conclusions: (1) initial site conditions influence the impacts of permafrost disturbance on ecosystem structure and function, (2) differences between the three sites for many variables were greater than the impacts of disturbance within one site, and (3) RTS impact NEE. Heterogeneity in conditions and responses was amplified by disturbance, resulting in unique combinations of vegetation communities, site characteristics, and carbon fluxes.
The establishment of flux towers at two locations allowed us to determine the variability in the impacts of permafrost disturbances on CO2 fluxes simultaneously throughout the season and examine the role of heterogeneity on NEE. However, as fluxes were dependent on wind direction, only either disturbed or undisturbed tundra could be measured at each site at any one time.
As the magnitude and frequency of disturbance are predicted to increase with increasing temperatures and precipitation, it becomes important to determine the impacts of disturbance at the plot scale but also at the landscape scale. Understanding both scales will help us predict the potential ecosystem changes that may result from modified disturbance regimes in the Arctic.
Acknowledgements
Funding for this study was provided by grants to G.H.R.H. from the Natural Sciences and Engineering Research Council of Canada (NSERC) (NSERC Frontier Discovery Program ADAPT) and ArcticNet and to A.E.C. from the Northern Scientific Training Program, Polar Knowledge Canada. Selected instrumentation was funded by grants to A.C. from NSERC and the Canadian Foundation for Innovation (CFI). We thank the Polar Continental Shelf Program for logistical support. Jason Paul assisted in the field and Rick Ketler assisted with equipment testing and calibration prior to fieldwork. Thank you to Drs. Vincent St. Louis (University of Alberta) and Andrew Black (The University of British Columbia) for providing additional equipment and scientific guidance.
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Arctic Science
Volume 3 • Number 2 • June 2017
Pages: 179 - 202
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Received: 17 August 2016
Accepted: 13 February 2017
Accepted manuscript online: 13 February 2017
Version of record online: 13 February 2017
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This article is part of a Special issue entitled “Arctic permafrost systems”.
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This article is open access. This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/deed.en_GB
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What does permafrost thaw mean for future Arctic ecosystems?
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Alison E. Cassidy, Andreas Christen, and Greg H.R. Henry. 2017. Impacts of active retrogressive thaw slumps on vegetation, soil, and net ecosystem exchange of carbon dioxide in the Canadian High Arctic. Arctic Science.
3(2): 179-202. https://doi.org/10.1139/as-2016-0034
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9. Assessing multi-hazard susceptibility to cryospheric hazards: Lesson learnt from an Alaskan example
10. Carbon loss and emissions within a permafrost collapse chronosequence
11. Recognition of thaw slumps based on machine learning and UAVs: A case study in the Qilian Mountains, northeastern Qinghai-Tibet Plateau
12. Landforms and degradation pattern of the Batagay thaw slump, Northeastern Siberia
13. Multi-hazard susceptibility mapping of cryospheric hazards in a high-Arctic environment: Svalbard Archipelago
14. Freeze-thaw induced landslides on grasslands in cold regions
15. Landslides: An emerging model for ecosystem and soil chronosequence research
16. Accuracy, Efficiency, and Transferability of a Deep Learning Model for Mapping Retrogressive Thaw Slumps across the Canadian Arctic
17. Global permafrost simulation and prediction from 2010 to 2100 under different climate scenarios
18. Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr
19. Accelerated mobilization of organic carbon from retrogressive thaw slumps on the northern Taymyr Peninsula
20. Automatically quantifying evolution of retrogressive thaw slumps in Beiluhe (Tibetan Plateau) from multi-temporal CubeSat images
21. Preliminary assessment of thaw slump hazard to Arctic cultural heritage in Nordenskiöld Land, Svalbard
22. Interannual Variability of Summer Net Ecosystem CO
2
Exchange in High Arctic Tundra
23. Extreme event impacts on CO
2
fluxes across a range of high latitude, shrub-dominated ecosystems
24. Acceleration of thaw slump during 1997–2017 in the Qilian Mountains of the northern Qinghai-Tibetan plateau
25. Using deep learning to map retrogressive thaw slumps in the Beiluhe region (Tibetan Plateau) from CubeSat images
26. Extremes of summer climate trigger thousands of thermokarst landslides in a High Arctic environment
27. Automated detection of thermoerosion in permafrost ecosystems using temporally dense Landsat image stacks
28. Ecological Response to Permafrost Thaw and Consequences for Local and Global Ecosystem Services
29. Arctic permafrost landscapes in transition: towards an integrated Earth system approach1