Data from: Rate of permafrost thaw and associated plant community dynamics in peatlands of northwestern Canada
Data files
Apr 23, 2024 version files 216.89 KB
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community.csv
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env_quadrat.csv
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env_transect.csv
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README.md
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species.csv
Abstract
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.
README: Rate of permafrost thaw and associated plant community dynamics in peatlands of northwestern Canada
https://doi.org/10.5061/dryad.g4f4qrfz5
Description of the data and file structure
Detailed data collection and processing methods can be found in the associated paper (Errington et al. in press) and in the Dryad metadata. Further contextual information regarding the broader Mackenzie Valley Permanent Monitoring Plot Network, including site-level and forest mensuration plot data can be found in Errington et al. (2018, 2020).
This submission contains 4 .csv files:
- “env_transect.csv” contains site/ transect level environmental variables,
- “env_quadrat.csv” contains quadrat-level environmental and vegetation summary variables,
- “community.csv” contains quadrat-level plant community composition, and
- “species.csv” contains species information.
Missing data is coded as “na”. Field names and contents are clarified below:
Table 1: Explanation and description of fields included in “env_transect.csv”
Field | Description |
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site | site name, consistent with the naming scheme of the Mackenzie Valley Permanent Monitoring Plot Network (Errington et al. 2018, 2020) |
transect | within site transect identifier |
pfzone | Permafrost Zone (Heginbottom et al. 1995) where C = Continuous; ED = Extensive Discontinuous; SD = Sporadic Discontinuous |
ecoclim | Ecoclimatic Region (Ecosystem Classification Group 2007, 2010) where MB = Mid-boreal; HB = High Boreal; LS = Low Subarctic |
lat | latitude (decimal degrees) |
long | longitude (decimal degrees) |
yr-est | year transect established |
yr-rem | year transect remeasured |
expansion | distance (cm) between the lateral extent of permafrost from the establishment year to the remeasurement year; positive values indicate a regression of permafrost into the peat plateau while positive values indicate expansion of permafrost into the collapse scar. |
annualexp | mean annual movement of the lateral permafrost extent (cm yr-1); positive values indicate a regression of permafrost into the peat plateau while positive values indicate expansion of permafrost into the collapse scar. |
compare | y = suitable for remeasurement comparison; n = not suitable for remeasurement comparison; fire = burned in 2014 forest fire |
pH | pH of collapse scar surface water |
cond | electrical conductivity of collapse scar surface water (μS) |
pdmax | maximum peat depth as measured along the transect (cm) |
MAT | mean annual temperature (deg C) 1950-2018 |
MAP | mean annual precipitation (mm) 1950-2018 |
MAS | mean annual snowfall (mm water equivalent) 1950-2018 |
GS | growing season length (days) 1950-2018 |
MAT-T1 | mean annual temperature (deg C) 1978-2007 |
MAP-T1 | mean annual precipitation (mm) 1978-2007 |
MAS-T1 | mean annual snowfall (mm water equivalent) 1978-2007 |
GS-T1 | growing season length (days) 1978-2007 |
MAT-T2 | mean annual temperature (deg C) 1988-2017 |
MAP-T2 | mean annual precipitation (mm) 1988-2017 |
MAS-T2 | mean annual snowfall (mm water equivalent) 1988-2017 |
GS-T2 | growing season length (days) 1988-2017 |
MATdif | change in mean annual temperature (deg C) T2 (1988-2017) - T1 (1978-2007) |
MAPdif | change in mean annual precipitation (mm) T2 (1988-2017) - T1 (1978-2007) |
MASdif | change in mean annual snowfall (mm water equivalent) T2 (1988-2017) - T1 (1978-2007) |
GSdif | change in growing season length (days) T2 (1988-2017) - T1 (1978-2007) |
MATsp | mean annual spring (March, April, May) temperature (deg C) 1950-2018 |
MAPsp | mean annual spring (March, April, May) precipitation (mm) 1950-2018 |
MASsp | mean annual spring (March, April, May) snowfall (mm water equivalent) 1950-2018 |
MATsum | mean annual summer (June, July, August) temperature (deg C) 1950-2018 |
MAPsum | mean annual summer (June, July, August) precipitation (mm) 1950-2018 |
MASsum | mean annual summer (June, July, August) snowfall (mm water equivalent) 1950-2018 |
MATf | mean annual autumn (September, October, November) temperature (deg C) 1950-2018 |
MAPf | mean annual autumn (September, October, November) precipitation (mm) 1950-2018 |
MASf | mean annual autumn (September, October, November) snowfall (mm water equivalent) 1950-2018 |
MATw | mean annual winter (December, January, February) temperature (deg C) 1950-2018 |
MAPw | mean annual winter (December, January, February) precipitation (mm) 1950-2018 |
MASw | mean annual winter (December, January, February) snowfall (mm water equivalent) 1950-2018 |
MATw1 | mean annual winter (December, January, February) temperature (deg C) 1978-2007 |
MAPw1 | mean annual winter (December, January, February) precipitation (mm) 1978-2007 |
MASw1 | mean annual winter (December, January, February) snowfall (mm water equivalent) 1978-2007 |
MATsp1 | mean annual spring (March, April, May) temperature (deg C) 1978-2007 |
MAPsp1 | mean annual spring (March, April, May) precipitation (mm) 1978-2007 |
MASsp1 | mean annual spring (March, April, May) snowfall (mm water equivalent) 1978-2007 |
MATsum1 | mean annual summer (June, July, August) temperature (deg C) 1978-2007 |
MAPsum1 | mean annual summer (June, July, August) precipitation (mm) 1978-2007 |
MASsum1 | mean annual summer (June, July, August) snowfall (mm water equivalent) 1978-2007 |
MATf1 | mean annual autumn (September, October, November) temperature (deg C) 1978-2007 |
MAPf1 | mean annual autumn (September, October, November) precipitation (mm) 1978-2007 |
MASf1 | mean annual autumn (September, October, November) snowfall (mm water equivalent) 1978-2007 |
MATw2 | mean annual winter (December, January, February) temperature (deg C) 1988-2017 |
MAPw2 | mean annual winter (December, January, February) precipitation (mm) 1988-2017 |
MASw2 | mean annual winter (December, January, February) snowfall (mm water equivalent) 1988-2017 |
MATsp2 | mean annual spring (March, April, May) temperature (deg C) 1988-2017 |
MAPsp2 | mean annual spring (March, April, May) precipitation (mm) 1988-2017 |
MASsp2 | mean annual spring (March, April, May) snowfall (mm water equivalent) 1988-2017 |
MATsum2 | mean annual summer (June, July, August) temperature (deg C) 1988-2017 |
MAPsum2 | mean annual summer (June, July, August) precipitation (mm) 1988-2017 |
MASsum2 | mean annual summer (June, July, August) snowfall (mm water equivalent) 1988-2017 |
MATf2 | mean annual autumn (September, October, November) temperature (deg C) 1988-2017 |
MAPf2 | mean annual autumn (September, October, November) precipitation (mm) 1988-2017 |
MASf2 | mean annual autumn (September, October, November) snowfall (mm water equivalent) 1988-2017 |
MATwdiff | change in mean annual winter (December, January, February) temperature (deg C) T2 (1988-2017) - T1 (1978-2007) |
MAPwdiff | change in mean annual winter (December, January, February) precipitation (mm) T2 (1988-2017) - T1 (1978-2007) |
MASwdiff | change in mean annual winter (December, January, February) snowfall (mm water equivalent) T2 (1988-2017) - T1 (1978-2007) |
MATspdiff | change in mean annual spring (March, April, May) temperature (deg C) T2 (1988-2017) - T1 (1978-2007) |
MAPspdiff | change in mean annual spring (March, April, May) precipitation (mm) T2 (1988-2017) - T1 (1978-2007) |
MASspdiff | change in mean annual spring (March, April, May) snowfall (mm water equivalent) T2 (1988-2017) - T1 (1978-2007) |
MATsumdiff | change in mean annual summer (June, July, August) temperature (deg C) T2 (1988-2017) - T1 (1978-2007) |
MAPsumdiff | change in mean annual summer (June, July, August) precipitation (mm) T2 (1988-2017) - T1 (1978-2007) |
MASsumdiff | change in mean annual summer (June, July, August) snowfall (mm water equivalent) T2 (1988-2017) - T1 (1978-2007) |
MATfdiff | change in mean annual autumn (September, October, November) temperature (deg C) T2 (1988-2017) - T1 (1978-2007) |
MAPfdiff | change in mean annual autumn (September, October, November) precipitation (mm) T2 (1988-2017) - T1 (1978-2007) |
MASfdiff | change in mean annual autumn (September, October, November) snowfall (mm water equivalent) T2 (1988-2017) - T1 (1978-2007) |
Table 2: Explanation and description of fields included in “env_quadrat.csv”
Field | Description |
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quadratID | unique quadrat identifier in the form "time period code.site code.quadrat code.transect number within a site" |
site | site name, consistent with the naming scheme of the Mackenzie Valley Permanent Monitoring Plot Network (Errington et al. 2018, 2020) |
transect | within site transect identifier |
utransect | unique transect identifier in the form "site code.transect code" |
yr | measurement year |
tp | time period of measurement [T1: 2007-8; T2: 2017-18] |
quad | within site quadrat identifier |
type | quadrat classification based on permafrost presence / absence [CS: collapse scar - permafrost absent; PP: peat plateau - permafrost present; Trans: transitional - permafrost both present and absent in portions of the quadrat] |
Ecoclim | Ecoclimatic Region (Ecosystem Classification Group 2007, 2010) [MB: Mid-boreal; HB: High Boreal; LS: Low Subarctic] |
Pfzone | Permafrost Zone (Heginbottom et al. 1995) [C: Continuous; ED: Extensive Discontinuous; SD: Sporadic Discontinuous] |
dfc | distance from 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 were positive and distances farther into the peat plateau were negative |
tdr | volumetric soil moisture (%) |
cc | canopy cover (%) |
probe | material underlying deepest probe penetration (ice or mineral) |
maxpd | move to table 1 |
peatd | peat depth (cm) |
adjfd | adjusted frost depth (cm) |
frostd | frost depth (cm) |
probed | probe depth (cm); probe depth to frost or mineral soil |
adjwtd | adjusted water table depth (cm) |
wtd | water table depth (cm) |
shan | Shannon Diversity Index (H') |
simp | Simpson Diversity (1-D) |
rich | species richness (number of species) |
even | Pielou's Evenness (J) |
v.rich | vascular species richness (number of vascular species) |
b.rich | bryophyte species richness (number of bryophyte species) |
l.rich | lichen species richness (number of lichen species) |
m.rich | moss species richness (number of moss species) |
Lcover | lichen species richness (number of lichen species) |
Vcover | vascular species cover (%) |
Carex | Carex species cover (%) |
Cladina | Cladina species cover (%) |
Eriophorum | Eriophorum species cover (%) |
Sphagnum | Sphagnum species cover (%) |
Fcover | cover of forb species (%) |
Gcover | cover of graminoid species (%) |
Livcover | cover of liverwort species (%) |
Mcover | cover of moss species (%) |
Scover | cover of shrub species (%) |
Tcover | cover of tree species (%) |
Table 3: Explanation and description of fields included in “community.csv”
Field | Description |
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QuadratID | unique quadrat identifier in the form "time period code.site code.quadrat code.transect number within a site" |
other fields | percent cover by species where field headings contain species codes, as explained in Table 4 |
Table 4: Explanation and description of fields included in “species.csv”
Field | Description |
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species code | specie code as used in table 3; typically, the first four letters of the genus followed by the first three letters of the specific epithet |
scientific name | full scientific name associated with each species code |
genus | genus |
specific epithet | specific epithet |
authority | authority associated with species name |
subspecies | subspecies |
subsp authority | authority associated with the subspecies |
type | vegetation type [tree, shrub, forb, graminoid, moss, liverwort, or lichen] |
Literature Cited
- Ecosystem Classification Group. 2007. Ecological regions of the Northwest Territories – Taiga Plains. Dep. Environ. Nat. Resour., Gov. Northwest Territ., Yellowknife, NT. 173 p. plus map.
- Ecosystem Classification Group. 2010. Ecological regions of the Northwest Territories – Cordillera. Dep. Environ. Nat. Resour., Gov. Northwest Territ., Yellowknife, NT. 245 p. plus map.
- Errington, R.C., S.E. Macdonald, and J.S. Bhatti. in press. Rate of permafrost thaw and associated plant community dynamics in peatlands of northwestern Canada. Journal of Ecology
- Errington, R.C., J.S. Bhatti, and E.H.Y. Li. 2018. Mackenzie Valley Permanent Monitoring Plot Network: site locations and descriptions. Nat. Resour. Can., Can. For. Serv., North. For. Cent., Edmonton, AB. Inf. Rep. NOR-X-426.
- Errington, R.C., J.S. Bhatti, and E.H.Y. Li. 2020. Mackenzie Valley Permanent Monitoring Plot Network: a database of stand characteristics. Nat. Resour. Can., Can. For. Serv., North. For. Cent., Edmonton, AB. Inf. Rep. NOR-X-428.
- Heginbottom, J.A., M.-A. Dubreuil, and P.A. Parker. 1995. Canada – Permafrost. Plate 2.1 in National Atlas of Canada, 5th Ed. Natural Resources Canada, Ottawa, ON. (MCR 4177; scale1: 7 500 000).
- Régnière, J., R. Saint-Amant, and A. Béchard. 2014. BioSIM 10 – User’s manual. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Québec (Quebec). Information Report LAU-X-137E
Sharing/Access information
Further information and data relating to the full Mackenzie Valley Permanent Monitoring Plot Network can be found at the supplemental links in the Related Works section.
Code/Software
No code or scripts are included in this submission.
Methods
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 (WTDadj) 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 WTDadj 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 (FDadj) 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, FDadj 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 (PDmax) 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 (Tmin) < 0) in the spring and the first 3 consecutive days with frost (Tmin < 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).
Literature Cited
- Ahti, T. 1984. The status of Cladina as a genus segregated from Cladonia. Nova Hedwigia 79: 25-61.
- Ahti, T. and P.T. DePriest. 2001. New combinations of Cladina epithets in Cladonia (Ascomycotina: Cladoniaceae). Mycotaxon 78: 499-502.
- Brodo, I.M., S.D. Sharnoff, and S. Sharnoff. 2001. Lichens of North America. Yale University Press, New Haven and London. 795 pp.
- Brouillet, L., F. Coursol, S.J. Meades, M. Favreau, M. Anions, P. Bélisle & P. Desmet. 2010+. VASCAN, the Database of Vascular Plants of Canada. http://data.canadensys.net/vascan/ (consulted on 2021-06-24)
- Cody, W.J. 2000. Flora of the Yukon Territory. 2nd Edition. NRC Research Press, Ottawa. 669 pp.
- Esslinger, T.L. 2021. A cumulative checklist for the lichen-forming, lichenicolous and allied fungi of the Continental United States and Canada, version 24. Opuscula Philolichenum 20: 100-394.
- Flora of North America Editorial Committee, eds. 1993+. Flora of North America North of Mexico. 22+ vols. Oxford University Press. New York and Oxford.
- Flora of North America Editorial Committee, eds. 2007. Flora of North America North of Mexico: Bryophytes: Mosses, part 1. Volume 27. Oxford University Press. New York and Oxford. 734 pp.
- Flora of North America Editorial Committee, eds. 2014. Flora of North America North of Mexico: Bryophytes: Mosses, part 2. Volume 28. Oxford University Press. New York and Oxford. 736 pp.
- Goward, T. 1999. The lichens of British Columbia Illustrated Keys Part 2 – Fruticose Species. Special Report Series 9, Ministry of Forests Research Program. Crown Publications, Victoria. 327 pp.
- Goward, T, B. McCune, and D.V. Meidinger. 1994. The lichens of British Columbia Illustrated Keys Part 1 – Foliose and Squamulose Species. Special Report Series 8, Ministry of Forests Research Program. Crown Publications, Victoria. 181 pp.
- Oksanen, J., G.L. Simpson, F.G. Blanchet, R. Kindt, P. Legendre, P.R. Minchin, R.B. O'Hara, P. Solymos, M.H.H. Stevens, E. Szoecs, H. Wagner, M. Barbour, M. Bedward, B. Bolker, D. Borcard, G. Carvalho, M. Chirico, M. De Caceres, S. Durand, H.B.A. Evangelista, R. FitzJohn, M. Friendly, B. Furneaux, G. Hannigan, M.O. Hill, L. Lahti, D. McGlinn, M.-H. Ouellette, E.R. Cunha, T. Smith, A. Stier, C.J.F. Ter Braak and J. Weedon. 2022. vegan: Community Ecology Package. R package version 2.6-4. https://CRAN.R-project.org/package=vegan
- Paton, J.A. 1999. The liverwort flora of the British Isles. Harley Books, Colchester, UK. 626 pp.
- Porsild, A.E. and Cody, W.J. 1980. Vascular Plants of Continental Northwest Territories, Canada. National Museum of National Sciences, Ottawa. 667 pp.
- R Core Team. 2022. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
- Régnière, J., R. Saint-Amant, and A. Béchard. 2014. BioSIM 10 – User’s manual. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Québec (Quebec). Information Report LAU-X-137E
- Schuster, R. M. 1966-1992. The Hepaticae and Anthocerotae of North America East of the Hundredth Meridian. 6 vols. New York, London and Chicago.
- Stotler, R. E. and B. Crandall-Stotler. 2017. A synopsis of the liverwort flora of North America north of Mexico. Annals of the Missouri Botanical Garden 102:574-709.
- World Meteorological Organization [WMO]. 2023. State of the Global Climate 2022. WMO-No. 1316. WMO, Geneva, Switzerland. 49 pp.