This dataset was collected to document the changing plant community, and associated environmental factors, as warming climate conditions accelerate permafrost thaw in northern peatland environments. Due to the insulative properties of dry, surface peat layers, discontinuous permafrost is preferentially found in peatlands, termed peat plateaux, where the volumetric expansion of ice-rich permafrost has resulted in a raised, dry ground surface dominated by lichens and, often, stunted black spruce forests. As ground temperatures warm, and the ice-rich permafrost thaws, the ground surface sinks to, or below, the water table, and these peat plateau environments change dramatically from black spruce and lichen-dominated peat plateaux to treeless moss- and sedge-dominated collapse scar environments. Data are from a set of 17 sites distributed along a latitudinal gradient in the Mackenzie Valley of Northwestern Canada. At each site, a transect of five to nine contiguous 1x1m quadrats was sampled, spanning the transition from peat plateau to collapse scar environments and, thus, capturing the zone of active permafrost thaw within peat plateaux as they transition to collapse scars. Fourteen of these sites were sampled at two time periods: 2007 and 2008 (T1: time 1), and 2017 and 2018 (T2: time 2) enabling an assessment of 10-year changes (9 years for one site). This dataset includes quadrat-level measurements of plant community composition (percent cover by species), frost depth, water table depth, peat depth, soil moisture, and canopy cover. Site level measurements consist of maximum peat depth, along with pH and electrical conductivity of collapse scar water samples, as well as the annual rate of lateral permafrost thaw. We also include basic site location parameters, as well as several climatic parameters, interpolated for each site using BioSIM software.

Please note that these methods have been adapted from those in the accompanying paper. Please see the accompanying paper in the Journal of Ecology for full context. 

Field Sampling

In the summers (late June to early September) of 2007 and 2008 (T1: time 1), 16 sites were selected along a latitudinal gradient in the Mackenzie Valley and a single transect was established at each site, perpendicular to the boundary of a collapse scar feature. Each transect was located on an independent peat plateau and consisted of a series of five to nine contiguous 1- x 1- m vegetation quadrats extending from the peat plateau to the collapse scar proper. The transect length (and, thus, the number of quadrats) depended on the distance needed to span this transition such that the transect extended from one or two quadrats into the peat plateau beyond the ‘collapsing slope’ to a point in the collapse scar where vegetation became more consistent and typical of that found in central portions of the collapse scar. Fourteen of these sites were resampled in the summers of 2017 and 2018 (T2: time 2) enabling an assessment of 10-year changes (9 years for one site). At one site the transect was resampled, although it could not be precisely relocated; a second was partially consumed by a wildfire in 2014 so was not resampled. Two new transects were established in T2. A metal rod (peat probe) was used to characterize the depth to permafrost at least every 100 cm along the transect at both time periods, with the lateral extent of permafrost determined to the nearest 10 cm. During the first measurement (T1), the peat probe was also used to assess peat depth at transect locations where permafrost was not present. Also, at T1, composite surface water samples were collected from three shallow pits dug in the central portions of each collapse scar. Water samples were frozen for transportation to the laboratory, subsequently thawed, and analyzed for pH and electrical conductivity using a Mettler Toledo multi-parameter meter (Mettler Toledo, Mississauga, Canada) with conductivity measurements standardized to 25°C. At T2, depth to the water table was assessed to the nearest 5 cm every 100 cm along each transect using a syringe to pull water from a piece of 0.5 cm diameter tubing marked at 5cm intervals. Also at T2, a Fieldscout TDR 100 soil moisture metre (Spectrum Technologies, Inc., Aurora, USA) was used to measure volumetric soil water content to a 12 cm depth as an average of three readings, from the approximate midpoint of three sides of each vegetation quadrat. Canopy closure was assessed in both time periods with the use of a concave spherical densitometer held at 1.3 m above each vegetation quadrat.

Also at both time periods, within each quadrat, all vascular plants, bryophytes, and ground lichens were identified to species and cover was visually estimated to the nearest percent with cover values of 0.5% and + (< 0.5% cover) also recorded. For quantitative analyses, + was interpreted as a cover value of 0.05%. Species concepts and nomenclature largely follow those outlined in the Flora of North America for mosses (Flora of North America Editorial Committee, 2007; 2014), and vascular plants (Flora of North America Editorial Committee, 1993+). For families for which Flora of North America volumes have not yet been completed, vascular species concepts follow Porsild and Cody (1980) and Cody (2000), all updated according to VASCAN for the most current nomenclature (Brouillet et al., 2010+).  Liverwort species concepts generally follow Schuster (1966-1992) and Paton (1999), while those of lichens follow Brodo et al. (2001), Goward (1999), and Goward et al. (1994), updated to the most current taxonomy according to Stotler and Crandall-Stotler (2017) and Esslinger (2021), respectively.  One exception is the lichen genus of Cladina (the classic “reindeer lichen” species) which current taxonomy places within Cladonia (Esslinger, 2021; Ahti and DePriest, 2001).  Due to clear functional and morphological distinctions between the species groups, we maintain the older distinction of Cladina as a separate genus (Ahti 1984). 

Data processing

Environmental variables

Because of the challenge of measuring relevant abiotic variables across the disparate conditions present along the gradient from peat plateau to collapse scar environments, several environmental variables were modified to allow for more complete datasets. In particular, the depth to the water table was adjusted (WTD_adj) to account for situations when the water table was not detected via the siphon system. In all but one case these missing values were in locations directly overlying permafrost and the WTD_adj was set to the frost depth where the water table was presumably present but frozen. At one other location, on a relatively dry hummock where the water table was deeper than the 45 cm siphon assembly, the water table was assigned an estimated value of 50 cm to complete the dataset. In cases where permafrost was not present in the collapse scar, frost depth (FD_adj) was standardized to 200 cm, well beyond the deepest permafrost detected in these transects (139 cm). We recognize that permafrost is likely absent from many of these locations but we cannot rule out its presence at depths below the peat/mineral interface (165 – 500 cm). Fundamentally, FD_adj is a pseudo-quantitative variable with values of 200 cm indicating an absence of near-surface permafrost.

Peat depth was measured only at T1 and could not be measured in quadrats with permafrost. Since the permafrost table restricts the rooting zone and any hydrochemical interactions with the underlying mineral soil, peat depths were considered to have limited ecological relevance for quadrats with permafrost; thus, quadrats having permafrost present in both T1 and T2 were assigned a value of zero for peat depth. When peat depth measurements were available for a quadrat in T1, that value was also used for T2. For those quadrats where permafrost thawed between T1 and T2 and, thus, lacked measurements from T1, peat depths were assigned for T2 based on the mean peat depth of other quadrats in the transect. We feel this is justified as peat depth is a relatively coarsely measured value with limited small-scale variability and, within a transect, peat depth values displayed a mean range of 50 ± 12 cm (SE). Maximum peat depth (PD_max) for each transect was also used as a site-level variable. Probe depth (probed) was the maximum depth the probe reached before reaching either frost or mineral soil and is, thus, effectively, a composite of the unadjusted frost depth and the peat depth.

The variable “distance from collapse” (dfc) characterized quadrats in terms of their position relative to the location of permafrost collapse. The point along each quadrat where peat plateau permafrost was last detected was set to a distance of dfc = 0 and the centre point of each quadrat from this “point of collapse” was calculated such that distances farther into the collapse scar was positive and distances farther into the peat plateau were negative. The mean annual lateral rate of permafrost thaw for each transect was calculated as the difference between the distance of maximum permafrost extent at T1 versus T2, divided by the sampling interval (9 or 10 years).

Diversity metrics

Shannon diversity (H’), Simpson’s diversity index (1-D), Pielou’s evenness (J), and species richness (S) were calculated for each quadrat using the vegan package (Oksanen et al., 2022) of R, version 4.2.1 (R Core Team, 2022). Species richness and abundance (% cover) were also calculated for several structural groups and key genera (vascular species, bryophytes, mosses, liverworts, lichens, trees, shrubs, forbs, graminoids, Sphagnum, Carex, Eriophorum, Cladina).

Climate variables

Since climate stations in northern Canada are very scarce, we used climate data interpolated from the nearest measurement locations using BioSIM software (Régnière et al., 2014). The algorithm used inverse distance square-weighted interpolation of data from the eight closest weather stations to each study site, correcting for differences in latitude and elevation between the weather stations and the study sites. Four climatic variables were used: the mean annual temperature (MAT), the mean annual precipitation (MAP), mean annual snowfall (MAS) and the mean length of the growing season (GS); each of these was calculated for three time periods: 1950-2018 (the maximum length of time we have reasonably consistent climate records in the major NWT climate stations); 1978-2007 (the 30-years preceding T1); and 1988-2017 (the 30 years preceding T2). The 30-year time frame was used to avoid short-term trends and reflect longer-term climate conditions, as is the standard reporting procedure for climate normals, recommended by the World Meteorological Organization (WMO 2022). Changes in climate conditions (ΔMAT, ΔMAP, ΔMAS, and ΔGS) were quantified through subtraction of 1978-2007 means from those of 1988-2017. Growing season was defined as the number of days between the last 3 consecutive days with frost (minimum daily temperature (T_min) < 0) in the spring and the first 3 consecutive days with frost (T_min < 0) in the autumn. Mean seasonal values, and 10-year changes, of temperature, precipitation, and snowfall were also calculated over the same time periods where seasons were considered to be spring (March, April, May), summer (June, July, August), autumn (September, October, November), and winter (December of the previous year, January, February).

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