Permafrost landsystems define regional variability in climate change effects on northern environments

Domain: biology
Published: 2026-04-03
Editorial outcome: major_revision

Abstract
Anticipating the environmental and societal consequences of climate-driven permafrost
thaw requires knowledge of terrain and subsurface conditions, which prove challenging to
obtain at spatial scales necessary for rigorous prediction and decision-making. Analysis of a
systematic inventory of permafrost landforms across northwestern Canada demonstrates
that landform assemblages co-develop with ecosystems, distinguishing fundamental
permafrost properties across a continental-scale ecoclimatic gradient (106 km2) and among
finer-scale ecological regions (103 to 104 km2). This approach quantifies variation in
geological and climatic legacies and delineates the diverse consequences of thaw. Here we
show that permafrost landsystems, defined by characteristic landform assemblages, express
spatial variation in soil, ground ice, geochemical, and carbon characteristics, enabling these
intrinsic conditions to be inferred at regional scales through integrated mapping and
analyses. Permafrost landsystems also provide a conceptual framework to inform
predictions of thaw-driven change, and to formulate, share, and apply permafrost knowledge
across scales, disciplines, and ways of knowing.

Introduction
Permafrost underlies approximately 12–17 million km² of the land surface in the Northern
Hemisphere1 and profoundly influences physical and biological processes in circumpolar
environments. Observed permafrost thaw2 is projected to increase in the coming century3.
The development of ground ice gives rise to periglacial landforms, whereas thaw-driven
processes that transform ice-rich landscapes produce a wide range of thermokarst
landforms, collectively expressing variation in terrain and permafrost conditions4,5
(Supplementary Fig. 1, Supplementary Table 1). The broad relevance of permafrost to
ecosystems, infrastructure, traditional land use, and the global climate6,7 underscores the
need for holistic approaches to characterize permafrost and integrate this knowledge
across scales and disciplines to better predict thaw and understand its consequences.

Modeling and remote sensing approaches generate timely, broad-scale spatial
information that shapes how the scientific community conceptualizes permafrost thaw8–11
and how policymakers and the public may perceive it. However, the heterogeneity in
permafrost characteristics and variation in thaw-driven consequences revealed by field
research, regional-scale analyses, and the diverse experiences of northerners diverge from
the results reported by many of these studies5,12,13. Increases in thaw-driven landslides14,15,
ice-wedge melt pond formation16, thaw lake expansion, rapid lake drainage17,18, and
peatland degradation19 are prominent processes that shape thawing terrain over the vast
permafrost regions (Supplementary Table 1). The persistent gap between broad-scale
predictions and empirical observation impedes the advancement and application of
permafrost knowledge across scales and disciplines. Improved conceptual and quantitative
understanding of thaw-driven change and ecosystem vulnerability requires knowledge of
the terrain and subsurface, particularly ground ice and soil conditions, which is difficult to
obtain at regional scales20,21, where it is necessary for analysis, prediction, and decision-
making. However, there is growing recognition that the distribution and dynamics of
landforms provide rich information on permafrost properties and on thaw-driven change
and ecosystem vulnerability4,5,22,23 (Figs. 1, 2).

Landsystem approaches have long provided a nested, spatial framework for
characterizing terrain patterns that reflect landform-subsurface relations, and, when
mapped, they support land-use planning24,25. They also provide insights into past geological
processes and climate, such as the nature of glaciation26. Within multi-level ecological land
classification systems, landsystems define recurring regional patterns of landforms, soils,
and vegetation comprised of landform assemblages or "land types"25 (Supplementary Table
2). Building on traditional landsystem concepts, we propose that geological inheritance and
paleoenvironmental history are most intimately linked in the evolution of permafrost
landscapes, producing distinct permafrost landform assemblages (Supplementary Table 1)
that co-develop with ecosystems to reflect fundamental permafrost properties9,27–29 (Figs.
1, 3). These landform assemblages, comprised of permafrost landforms —products of cold-
climate processes and ground-ice development, and thermokarst landforms resulting from
the thaw of ice-rich permafrost— develop in association with characteristic surficial
deposits to organize at regional scales (103 to 104 km2), forming permafrost landsystems
(Figs. 2, 3; Supplementary Table 1).

In this study, we utilize a robust, systematic inventory of permafrost-associated
landforms from northwestern Canada5 to explore variation in the patterns of landform
assemblages, and by extension, the range of terrain conditions and thaw sensitivities they
reflect (Figs. 1, 2; Supplementary Table 1; also see Methods). Specifically, we (1) explore
the broad-scale patterns of permafrost landform assemblages, and (2) evaluate the
influence of climate and terrain conditions on their distribution across a continental-scale
biophysical gradient (105 km2), (3) determine the influence of geologic, and
paleoenvironmental history on variation in landform assemblages and permafrost
conditions within and among smaller, landsystem-scale ecoregions (103 to 104 km2) (Figs.
2, 3), and (4) demonstrate that permafrost landsystems offer a conceptual framework for
understanding the spatial variation in permafrost properties and thaw trajectories from
quantitative analysis of permafrost landforms. An ecological classification for the
Northwest Territories (NWT), Canada, defines the spatial extent of our study and
structures the analyses30–34 (Fig. 2; Supplementary Table 2). The subsample of the NWT-
wide permafrost landform inventory used in this study captures a range of permafrost
landforms that reflect major ground ice types, as well as soil, ground temperature, and
ecological conditions encountered across northwestern Canada5,9 (Supplementary Fig. 1 &
Table 1). These data are from a 7.5 x 7.5 km grid-based inventory of the presence or
absence of 28 permafrost landform types (Supplementary Table 1) across 3292 grid cells.

The observed landforms within a grid cell combine to form assemblages and reflect
permafrost conditions (Supplementary Table 1). Feature identification is constrained by
the use of Sentinel-2 imagery with a 10 m pixel size, which was available for the entire
study region at the initiation of the NWT Thermokarst Collective mapping project5. The
sampled grid cells represent the total areas of 14 Level IV ecoregions nested within seven
ecozones5 (Level II ecoregions) (Fig. 2; Supplementary Table 2). Redundancy analysis
(RDA) was applied to a subsample of the grid-based inventory of permafrost landform
types (1,959) across the level IV ecoregions (Supplementary Table 2) to examine general
associations between landform assemblages and primary climate and terrain conditions
(Supplementary Table 3). To visualize broad-scale patterns in the RDA site scores, grid
cells (sites) are labeled by ecozone (105 km2) (Fig. 2, Supplementary Table 2). Fourteen
level IV ecoregions provide spatial boundaries for exploring finer-scale regional patterns of
variation in permafrost landform assemblages as they are conceptually similar to
landsystems, representing regions (103 to 104 km2) of recurring landform, soil and
vegetation conditions25,30–34(Fig. 2; Supplementary Table 1 & Appendix 1). For landsystem-
scale analyses, the RDA scores are stratified by level IV ecoregions. The richness of
permafrost landforms across ecoregions was compared by creating landform accumulation
curves from inventory data for 3292 grid cells within level IV ecoregions. We also
developed a clustered heatmap to explore the natural groupings of permafrost landform
assemblages and how these influence similarities and clustering of level IV ecoregions. The
data used in these analyses are in Weiss et al.35.

This study demonstrates that combinations of permafrost landforms are linked to
variation in permafrost conditions across a continental-scale ecoclimate gradient and
among landsystem-scale ecological regions (Figs. 2, 3; Supplementary Table 2). Here we
show that a permafrost landsystem approach enables spatial and stratigraphic variation in
soil, carbon, ground ice, and thermal conditions to be inferred at regional scales based on
the distribution of mapped permafrost landform assemblages (Figs. 1, 2) and provides a
conceptual framework for integrating knowledge of permafrost properties, ecosystems,
and trajectories of thaw across sites, spatial scales, disciplines, and ways of knowing (Fig.
3).

Results
Landform assemblages reflect variation in permafrost characteristics across
continental-scale gradients
Permafrost landforms across northwestern Canada exhibit patterns associated with
climate and terrain variables (Fig. 4). The RDA was statistically significant, explaining
23.3% of the variation in the composition of permafrost landforms within the inventoried
grid cells (F = 74.27, p = 0.001). All environmental variables were significant (p<0.01). The
analysis explained 16.6% of the variation across axis 1 (RDA1, F = 420.82, p = 0.001) and
3.2% across axis 2 (RDA2, F = 80.26, p = 0.001). Axis 1 separates data along a continental-
scale climate gradient, and axis 2 distinguishes site scores in relation to topographic relief.
Permafrost landform assemblages capture a continental-scale gradient in permafrost
conditions, and additionally, reflect the significant variation in substrate, ground ice, and
ground temperature conditions that characterize heterogeneity of this broad ecoclimate
transition indicated by the site scores along RDA axis 1 (Fig. 4a). Permafrost landform
assemblages in lowlands of the Taiga Plains low subarctic and Taiga Shield high boreal
(negative RDA1 scores) are associated with the highest mean annual air temperatures,
rainfall, and forest fire burn area (Fig. 4). These conditions are associated with permafrost
peatland-dominated landform assemblages dissected by dendritic and multi-basin
drainage patterns with permafrost-free string bogs, collapse scars, and thaw ponds, and
thaw-lake complexes (ramparted-lake lithalsas) which together reflect thin and patchy
permafrost (Fig. 2c, d). Sites that cluster across the origin of RDA1 reflect diverse lowland
landforms that characterize the range of ground temperatures and ground ice associated
with variation in permafrost conditions encountered across the high subarctic Taiga Plains,
of which the northern extent approaches the forest-shrub transition zone, and colder
ground temperatures. The Southern and Northern Arctic tundra plains plot positively on
RDA axis 1, with sites in the lower-right quadrant reflecting strong associations between
lowland landforms associated with wedge ice and related hydrological features (Fig. 2a, b).
These landform assemblages occur with low MAAT and rainfall, reflecting contemporary
permafrost conditions and the legacy of a cold Holocene climate (Fig. 4).

Positive RDA2 scores express the association between mass wasting features, greater
height above nearest drainage, and variation in terrain position classes (geomorphons)
(Fig. 4a), characteristic of foothills or plateaus in the transition between the Taiga Plains
and Cordillera, or localized areas of greater topographic relief in the Taiga or Arctic
ecozones. Topographically complex environments in discontinuous permafrost (upper left
quadrant of the RDA) are associated with shallow landslides and large slides that fail at the
base of thin permafrost36. Terrain with retrogressive thaw slumps plot in the upper right
quadrant of the RDA (Fig. 4b) and reflects geomorphically complex (RDA2) ice-rich terrain
in cold permafrost (RDA1) of the Northern Arctic ecozone. Across the climate gradient
expressed by RDA1, negative RDA2 scores are associated with low topographic variability
and reflect poorly drained, water-rich landscapes with string bogs and dendritically
drained permafrost peatlands in discontinuous permafrost of subarctic and boreal regions,
and lowland polygonal terrain in Arctic areas.

Over 75% of the variation in the composition of permafrost landforms across the
inventoried grid cells remains unexplained by the environmental variables used in the
RDA, indicating the limitations of the common practice of applying broad-scale spatial data
without field-informed evidence in modeling permafrost conditions9,37–39. Improved
predictor-variable datasets may reduce unexplained variation. However, additional
analysis, including derived and highly correlated variables such as surficial geology,
modeled ground-ice abundance, and permafrost probability (Supplementary Table 3), did
not improve the explanatory power of the RDA. The high percentage of unexplained
variation indicates that variation in geology, climate, and ecological conditions needs to be
better portrayed in spatial analyses, and that systematic landform mapping has significant
potential to advance quantitative knowledge of variability in permafrost terrain conditions,
intrinsic properties, and thaw-driven change trajectories5,22.

Landforms reveal variations in permafrost conditions between landsystems
The patterns of variation in permafrost landform assemblages distinguish landsystems and
provide insights into regional-scale differences in permafrost conditions and thaw
trajectories. Figure 5 shows RDA scores and landform richness grouped by level IV
ecoregions, and Figure 6 is a clustered heatmap that explores the natural groupings of
permafrost landforms into assemblages, and how these influence similarities and
clustering across the landsystem-scale level IV ecoregions. Coupled with these analyses, we
also apply permafrost landsystems as a conceptual framework to guide narratives that
explain how geological legacies, physiography, and climate have shaped spatial and
compositional variation in landform assemblages, intrinsic permafrost properties, and
thaw trajectories (Figs. 2, 5; Supplementary Appendix 1). From these quantitative analyses,
we draw five main insights:

(1) Geological boundaries demarcate significant differences in permafrost landform
assemblages. In the discontinuous permafrost zone, the narrowest RDA confidence
intervals and lowest landform richness and terrain coverage characterize ecoregions (i.e.,
Great Slave Lowland) within the bedrock-dominated Taiga Shield (Figs. 5a, b, 6). Ice-rich
permafrost is confined to pockets of fine-grained sediments, manifesting as ice-rich lithalsa,
thaw-lake assemblages, or discrete permafrost peatlands (Figs. 2c, d, 6), reflecting distinct
trajectories of thaw-driven change40 in an otherwise thaw-stable Taiga Shield landscape. In
contrast, the greater landform richness and RDA1 standard deviation (STDev) of the Keller
Plain are associated with extensive, thawing peatlands and shallow thermokarst lakes
(Figs. 5a, b, 6) reflecting warm and thin permafrost of the organic-rich, glacially-scoured
Low subarctic Taiga Plains (Fig. 6). The Mackenzie Foothills of the Taiga Cordillera (Fig. 2),
is characterized by a gradually increasing landform richness curve that indicates high
between-site diversity and relatively low overall richness: a product of geologic and
physiographic heterogeneity, and large areas of exposed bedrock or regolith. The variable
physiography and substrate yield a diversity of landslide types along incised valleys,
degrading permafrost peatlands on till plains, and thaw-lake complexes in glacial
meltwater channels, comprising distinct landform assemblages (Fig. 6). Within the Taiga
biome, the dendrogram clusters bedrock-dominated landsystems distal to the organic-rich
Keller Plain (Fig. 6).

(2) Within the same ecoclimate region (Low Arctic), glaciated and unglaciated terrain
hosts distinct landform assemblages. Widespread wedge ice comprises dominant lowland
landform assemblages reflecting cold, continuous permafrost across these tundra
landsystems28 (Figs. 1, 5a, c, and 6). However, the complexity of glacial deposits, variation
in post-glacial terrain evolution, and patchy preservation of relict massive ice41 yield
greater landform richness and between-site diversity in the glaciated Tuktoyaktuk Coastal
Plain than in the adjacent unglaciated Coastal Lowland, a sandy outwash plain with
shallow, oriented lakes distributed throughout42 (Fig. 5a, c). On the Tuktoyaktuk Coastal
Plain, ice wedges in uplands and lowland organic terrain, thaw slumps, pingos, and
involuted terrain comprise landform assemblages reflecting diversity in terrain and ground
ice conditions, and hence, thaw-trajectories17,28,29,41, contrasting ice-wedge pond expansion
and partial drainage of oriented lakes on the Coastal Lowland (Fig. 6).

(3) Holocene climate drives differences in permafrost landform assemblages between
ecoregions with similar geological legacies. Permafrost-preserved ice-cored moraines share
common landforms, such as thaw slumps, but variations in past climate and physiography
yield differences (Figs. 5a, d, 6). The richness curve for East Banks Hills in the Northern
Arctic rises rapidly and then flattens, indicating a diversity of landforms throughout the
landsystem (Figs. 5d, 6). Preservation of relict glacier ice and extensive development of ice-
wedge networks, indicated by abundant RTS14,29 and polygonal pond expansion16, comprise
thaw-sensitive upland assemblages reflecting glacial legacy and a cold Holocene climate
(Figs. 2a, b, 6). The larger RDA STDev and a slightly gentler rising richness curve for the
Richardson Plateau of the Tundra Cordillera reflect its ecotonal nature and greater
topography. Peatlands with dendritic drainage patterns transition northwards to polygonal
terrain. RTS and shallow slides are common, along with a few megaslumps in the fluvially
incised plateau and gullied terrain, and deep-seated failures occur on steeper slopes
underlain by sedimentary bedrock43. Preservation of relict glacier ice produces similar
conditions across ice-cored moraine landsystems; however, the greater variation in past
and present climate and topography in the Richardson Plateau yields diverse landform
assemblages and thaw-driven changes (Fig. 5a, d). The dendrogram represents these two
regions of similar glacial legacy and contrasting climate at opposite branches of the
landsystems we sampled within the Tundra biome (Northern Arctic, Southern Arctic,
Tundra Cordillera) (Fig. 6). However, landform assemblages of the Richardson Plateau are
most similar to the nearby glaciated Tuktoyaktuk Coastal Plain of the Southern Arctic,
reflecting terrain of common glacial origins and post-glacial climate (Fig. 6).

(4) Landsystems within ecotones express the greatest diversity in landforms and
permafrost conditions. Within the northern part of the Taiga at the boundary with the
Tundra biome (Fig. 2), the Travaillant Upland and Anderson Plain have the highest RDA1
STDev and landform richnesses (Fig. 5a, e). High diversity within these landsystem-scale
Level IV ecoregions is reflected by continually rising richness curves (Fig. 5e). Thawing
peatlands, patterned fens, and thermokarst ponds comprise landform assemblages that
transition northwards to polygonal peatlands and ponds. Variations in geology and
preservation of ground ice yield thaw-sensitive slopes in areas with greater topographic
relief (Figs. 1, 6). A wide range of landform assemblages indicates diversity in permafrost
conditions and, hence, thaw trajectories within Level IV ecoregions situated within a major
ecotone, distinguishing these high subarctic Taiga landsystems from those within the low
subarctic to the south (Fig. 6).

(5) Landscapes in discontinuous permafrost or with few excess ground ice types have lower
landform richness. Three of the four ecoregions with the lowest landform diversity are
underlain by discontinuous permafrost, and with bedrock areas, and where segregated ice
is the only common excess ground ice (Fig. 5b). In continuous permafrost, landform
homogeneity and low landform richness of the unglaciated Tuktoyaktuk Peninsula Coastal
Lowland characterizes a sandy outwash plain that only includes appreciable ground ice in
the form of ice wedges relatively low in ground ice abundance42 (Fig. 5c). As reflected in the
results of the RDA, landform richness curves, and a clustered heatmap (Figs. 5, 6), these
regions contain thaw-sensitive permafrost terrain, but the nature of thaw-driven changes
and environmental consequences is less variable than in other permafrost environments,
where ground ice types and abundance are more diverse.

Methods
Study area and permafrost landform inventory
Permafrost landforms indicating thaw-sensitive terrain are being systematically
inventoried for the entire Northwest Territories, Canada5, covering an area of more than
1.3 million km2. In this study, we sampled a total of 14 Level IV ecoregions comprising a
114, 187 km2 area that span several ecozones from discontinuous permafrost in the Taiga
Plains to cold continuous permafrost in the Arctic, bounded by bedrock-dominated Taiga
Shield to the east and the Taiga and Tundra Cordilleran to the west58 (Fig. 2). Most of these
regions are composed of glaciated terrain underlain by permafrost with a wide range of
ground ice9 and ground thermal conditions2. Variations in geology and climate yield
biophysical diversity, which is broadly grouped into the Taiga Plains, Taiga Shield, Taiga
Cordillera, Tundra Cordillera, and the Northern and Southern Arctic ecozones30–34
(Supplementary Table 2). This multi-scale, nested framework delineates ecological regions
based on climate, physiography, and vegetation30, which we apply in this study to guide
sampling design and to explore the permafrost landform data. The inventory of 28
landform types characterizes thermokarst landforms that develop due to the thaw of ice-
rich permafrost, and permafrost landforms that reflect intrinsic terrain properties, which
together are the product of geological legacy, and the interaction of cold region geomorphic
processes and biophysical factors, conditioned by past and present climate conditions
(Figs. 1, 2, Supplementary Fig. 1, Supplementary Table 1). Systematic observations of these
landforms, evaluated within a 7.5 x 7.5 km grid cell framework, described in Kokelj et al.5
and references within, were made from 14 level IV ecoregions (103 to 104 km2) across the
six ecozones to capture the range of climate, ecosystem, and geological conditions across
the Northwest Territories (Fig. 2; Supplementary Appendix 1). Sentinel-2 imagery (2016–
2017; 10 m resolution), viewed at a scale of 1:20,000 was used for this inventory. Level IV
ecoregions, mapped at a scale of 1:500,000, are conceptually similar to landsystems
because they describe broad recurring vegetation and landform patterns30 (Supplementary
Table 2). The presence or absence of inventoried features comprises a subsample of 3292
mapped grid cells or "sites" describing permafrost landform distribution over a 114, 187
km² area, which is a subset of the 1.3 million km² domain of the NWT Thermokarst
Mapping Collective5. Grid cells with water body coverage greater than 60% were excluded
from the analysis.

Statistical approach
Redundancy Analysis (RDA) was employed to quantify how the presence or absence of
permafrost landforms is constrained by primary environmental variables and how they
assemble across a latitudinal gradient of ecozones. The multivariate ordination explores
the associations between a response matrix of variables, specifically the presence or
absence of permafrost landforms (Supplementary Table 1), and a matrix of independent
environmental variables on a 1959 grid cell subset of the total 3292 grid cells across the 14
level IV ecoregions (Supplementary Tables 2, 3). We used primary environmental variables
commonly associated with variation in permafrost and geomorphic conditions. The eight
variables retained (Supplementary Table 3) included thirty year means (1991-2020) for: 1)
annual air temperature (Air temperature), 2) total annual rainfall (Rainfall), and 3)
maximum snow water equivalent, as well as 4) geomorphons, 5) mean height above
nearest drainage, 6) flow accumulation, 7) percentage of water area (Percent water), and
8) percentage of burn area for 1991-2020 (Burn area). The final analysis did not use
derived and highly generalized (surficial geology) or modeled (ground ice and permafrost
probability) categorical variables9,59 (Supplementary Table 3). Testing revealed the high
collinearity between the primary and derived variables, and their addition improved the
total explained variation of the RDA by less than 2%.

Statistical analyses were performed in R version 4.5.160, using functions in the vegan
package61. The RDA was performed using the rda function, with scaling applied to the
environmental variables. We applied variance inflation factors to assess collinearity in the
RDA dataset using vif.cca and removed highly collinear environmental or climate variables
from the analysis. The combined contribution of each landform feature on RDA1 and RDA2
was calculated as:
c=√(a^2 + b^2)
where a is the landform score on RDA1 and b is the landform score on RDA2 to calculate
contribution c. To compare variation in RDA scores between Level IV ecoregons we plot
their RDA1 and RDA2 centroids and standard deviations.

We created landform accumulation curves using landform inventory data from 3292
mapped grid cells to compare the richness of permafrost landforms among first-order
landsystems (level-IV ecoregions) using the accumcomp function from the BiodiversityR
package62, using method “exact”. Here, sampling effort refers to the number of grid cells
mapped in the ecoregion, and landform richness is the number of permafrost feature types
observed. The heatmap with dendrograms in Figure 6 was created using the pheatmap
package63. Data from 3292 grid cells were summarized as the proportion of gridcells with a
landform present within each level-IV ecoregion. The clustering method was complete-
linkage clustering using Euclidean distances and without scaling. The datasets used in
these statistical analyses are in Weiss et al.35. Final graphics in Figures 4-6 were optimized
using Adobe Illustrator64. Hand drawn schematics, mapping, and data graphic elements
integrated to create Figures 1-3 and Supplementary Figure 1 were also developed in Adobe
Illustrator64.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The authors introduce in their manuscript the concept of “permafrost landsystems” which are spatial assemblages of Quaternary landforms (glacial, non-glacial, glacio-lacustrine plains, wetlands,..etc.) bearing typical permafrost features (e.g. tundra polygons, thermokarst ponds, retrogressive thaw slumps.. etc. (a list of 28 of them in supplementary table 1, illustrated with nice photographs). Perfectly true in my opinion: landforms and the ecosystems they support provide an excellent mean to map permafrost properties (e.g. types and amounts of ground ice, sensitivities to thaw, susceptibilities for landslides and mass movements). Currently, almost all of the broadscale (e.g. circumpolar) efforts in mapping permafrost conditions using climate data, climate model outputs and remotely sensed surface parameters fail to produce outputs that can inform well on high resolution characterization of permafrost and thaw sensitivity. Those models do not either provide truly useful knowledge for decision and policy makers at the level of a country (like Canada) or a region, even a large one such as NWT. This manuscript therefore proposes an improvement in regional and national approaches of permafrost knowledge acquisition and sharing. Thanks to the work of some of the co-authors (O’Neill et al. 2019), Canada already has a predictive map of ground ice that is unique. It is currently being refined. This paper goes further in the same direction.\nI think the manuscript needs major revisions, particularly in tightening the reasoning and focusing the arguments for the use of integrated surveys (“multivariable” here is not the correct word) and ecological mapping. From the start, the reader needs to have a clearer view of how the existing land classification scheme in NWT is structured and what is its terminology. The reader has difficulty to find his way among the ecozones and the ecoregions of various levels of integration. What levels are defined by biomes and climate. What levels are defined on vast areas by physiography. How do they nest into each others. Integrated surveys and ecological land classification started in the 1950s by the CSIRO in Australia. They were adopted in Canada in the 1960s (see Lacate, 1969, pdf joined). The nested concepts of land region, land district, land system, and land types are straihgtforward and provide a basic framework. A comparable framework is absent from the manuscript and this creates confusion (see my comment at line 280 of the annotated pdf manuscript). Having done contract work in ecological mapping in the late 1970s, my experience tells me that the “permafrost land systems” are the same thing as conventional landsystems, but applied to permafrost landform assemblages.\nThe paper lacks a clear statement of what are its objectives. As far in the text as line 114, I could not find such a statement. The aims of the paper should appear clearly.\nAt line 120, the term landform type is introduced. I would say permafrost landform (there are 28 of them that reoccur in the landscape) and save the word “type” for “land type”, which refers to a high level of integration of soil, morphology, vegetation and wetness (but at a larger mapping scale) in land classification procedures. For instance, the nice block-diagrams of figures 1 and 2 which represent assemblages of landforms can be subdivided in land types that have almost uniform combinations of soil, morphology, slopes and vegetation cover. Similarly, block-diagram 3 on figure 3 could be subdivided into three permafrost land types (ridge with ice wedges, wetland with low center polygons, high center polygons). Both in theory and practically, this is the level at which permafrost conditions are nearly uniform. This is the level of integration that would be applicable for designing an infrastructure, for instance.\nSome questions that rose in my mind while reading are: are the permafrost land systems mapped over the study region? Is there a map or a data file of them? Or are the land systems a concept that the authors recommend using on an ad hoc basis for specific infrastructure, community or impact assessment projects in the region? Could a gridded climate model be overlayered and integrated with a map of permafrost land systems? These are matters at least for discussion.\nThe process, or method, applied to run the RDA analysis needs to be explained more simply. See my comments in bubbles and highlighted text on the pdf. I was a bit confused about what variables were used in the RDA. I understood these are only the climate variables and the morphons (i.e. relative elevation values). If so, it is not surprising in my mind that the total explanation of variance is only 23%. Of course, climate regulates the thermal regime and the rates of the processes acting in permafrost. But the surficial geological units (an identification value) that are the main controls on ground ice contents is not a numerical value usable in statistics.\nFrom lines 280 to 364, the five insights can be commented upon in much shorter text. Some basic ideas can be stated more simply. For example, there is less diversity in the discontinuous permafrost zone simply because only palsas and peat plateaus are left as permafrost in the landscape.\nSimilarly, the discussion is too long and should be more focused.\nThere is no concluding statement. There is so much value to be added in permafrost mapping in adopting geomorphology and Quaternary through the permafrost landsystem approach.\nIn general the text could be better integrated, concise, somewhat compacted and less “overtheoretical”.\nThe figures are excellent. I made many comments on the pdf.", "reviewer_2": "Review of \"Permafrost landsystems provide the key to understanding climate change effects on northern terrain and ecosystems\"\nby Steven V. Kokelj et al.\nThis study analyzes an extensive dataset on the occurrence of permafrost landforms gathered by the NWT Thermokarst Mapping Collective, in order to bring the wealth of information it contains to a wide audience. The authors' interesting analytical innovation is to apply statistical techniques developed in plant community ecology to a geomorphological dataset, by treating systematic 7.5 x 7.5 km remotely-sensed grid squares as the \"plots\" and the permafrost landforms in each plot like plant species in community ecology. These statistical techniques are then used to draw inferences about the significance and distribution of permafrost landforms in the study area.\nI believe the application of the community-ecology methods to this dataset is both innovative and promising. RDA analysis (the main statistical tool used here) is a powerful technique, and it yielded reasonable results, but nonetheless I have some thoughts about its application.\n1) My understanding is that RDA is appropriate for response variables with more-or-less normal distributions, while in your data set the response variable was binary presence-absence (as stated in the methods, p. 22 line 21, though the barplots in Fig. 3 imply a semiquantitative scale \"trace\", \">trace\").\n2) RDA is designed to ordinate the response variables (samples of permafrost landform assemblages) in a space created by the explanatory (environmental) variables. It did this successfully here in the sense that RDA discovered the familiar north-south climatic gradient in permafrost landforms and also a sloping vs. flat landform gradient. It is comforting (but not highly informative) to see these well-known trends confirmed using \"big data\", and also not surprising that most of the variation in landforms (77%) was actually not explained by available GIS variables. The authors undoubtedly suspected that this was going to be the case beforehand, from their very extensive experience with mapping permafrost landforms; that is probably why they invested so much effort in manual mapping! So my reaction to this would be to recognize RDA's limited usefulness in this context: the explanatory (GIS) variables are statistically significant but have weak explanatory power; RDA actually limits your understanding of permafrost landform assemblages to the 23% of the variation in permafrost landforms that is associated with the environmental (GIS) variables. Unfortunately, the nature of the remaining 77% of the variation unknowable by this method. My response then would be to spend less time on RDA and look at other community ecology methods that might teach us new things. The use of species accumulation curves by level IV ecoregions was a good first step.\nSpecifically, I was left wanting know see the \"Permafrost landform assemblages\" defined and described quantitatively. The illustrations in the paper only hint at which landforms occur together in assemblages. Multivariate plant community analysis techniques like cluster analysis, PERMANOVA, and NMDS are designed specifically to discern and describe communities/assemblages. The NWT Thermokarst Mapping Collective dataset is globally unique in it's suitability for such analysis. The 7.5 x 7.5 km grid cells are a huge unbiased sample of the permafrost landforms assemblages (and ecoregions are excellent strata to summarize them). I would like the authors to consider using other community ecology methods to shed some light on questions like: What are the natural groups of permafrost landforms? How distinct are the groups and how do they overlap? Are they distinct enough to be mappable? Which \"species\" (landforms) are \"generalists\" (occur everywhere and thus are not highly diagnostic of permafrost conditions), and which landforms are very specific and diagnostic of a unique assemblage or diagnostic of unique permafrost conditions? I understand that classification of permafrost landform assemblages, like any classification exercise, could be a time-consuming rabbit-hole to disappear down, but it might also be very fruitful. And you appeared to suggest doing it on p.18 line 16. If you were able to develop a classification of permafrost landform assemblages, such that the dominant assemblage in each grid cell could be classified, then you would instantly have a 7.5 km pixel resolution map of permafrost landform assemblages for your whole study area. It would undoubtedly be related closely to the ecoregions, but the finer patterns within and between ecoregions could be fascinating and useful. If the authors attempted this and decided it wasn't worth pursuing, please explain why.\nAn additional benefit to defining concrete landform assemblages would be to give the reader a better picture of what they are. Along similar lines, the \"permafrost landsystem\" concept can be difficult to grasp. Would a mapped area dominated by one or few permafrost landform assemblages qualify as a \"permafrost landsystem\"? If so then defining landform assemblages and mapping them by labeling the 7.5 km grid squares would be a great way to make permafrost landsystems more concrete and understandable.\nA few other miscellaneous comments:\nThis study relies heavily on the Level IV Ecoregions by the Ecosystem Classification Group (2008-2013). However, only the 2008 Taiga Shield ecoregion inventory is cited in this article, though ecoregions from several other reports were used.\nMost text on the graphics is 6 pt., with some as small as 4 pt. The resolution is good so I was able to read them, but only after enlarging the text on-screen to 200%.\nThe Methods section begins by saying that permafrost landforms were systematically inventoried for the entirety of the Northwest Territories. But the soon after on p. 22 line 16 it says that systematic observations of these landforms were made from 14 level-IV ecoregions. So it appears that this report is specifically about the subset of 14 ecoregions. Please clarify the connection of this study to the territory-wide inventory.\nIt would be helpful to provide some more information about the sampling methods, beyond the citation of Kokelj et al. (2023). I understand that you selected 2030 7.5 x 7.5 km squares, which cover 114187 km2, and presumably these were restricted to be within the 14 ecoregions. This is just under 10% of the full area of the NWT, and judging from the size the ecoregions on Fig. 2 it appears that the 7.5 x 7.5 km squares covered the entirety of the selected ecoregions. Do you have any more explanation for why you chose these 14 ecoregions? Also, citing Kokelj et al. (2023) and also the barplot in Fig. 3 might imply that you inventoried some landforms by cover classes, but p. 22 line 21 implies only presence/absence of landforms within each grid cell was recorded. I get why you would have done this (presence/absence is much faster), but please clarify. Also please note briefly what imagery was used in the inventory.\np.23 line 662. \"Topographic indices\" were computed for each 7.5 x 7.5 km grid cell. These appear to me to be indices that are typically computed for pixels (90 or 250 m), and it seems to me that they could vary widely across a 7.5 x 7.5 km grid cell. Please explain how they were generalized for 7.5 x 7.5 km grid cells.\np.23 line 672. \"Following standard procedures, we scaled environmental variables for the 7.5 x 7.5 km grid cell framework.\" It's not clear to me what the standard procedures might be. Z-score across the whole study area?\nSupplementary Table 1\nVery useful and well done. One comment:\nPatterned_Forest_Lowland - the caption seems to indicate that this class was used on both polygonal and string-flark patterns. I hope not, as they are usually distinguishable and, as the caption notes, have different permafrost interpretations. And then later you indicate that you have a separate string fen class.\nSupplementary Appendix 1\nWell constructed and very helpful. A few comments:\nAnderson Plain - \"Black arrows\" noted in the caption are not visible.\nEast Bank Hills, Richarson Plateau, Travaillant Upland - Retrogressive thaw slumps can difficult to find, especially for the inexperienced eye at the publication scale. Consider arrows to indicate, and possibly mention the resulting turbid lakes.", "reviewer_3": "This is a well-written paper with sound scientific information. I envision the methodologies established here as being useful in Arctic regions for work that will help educate decision-makers on potential climate-driven landscape changes. I can imagine future applications of this study helping to prioritize areas for future investigations by the Alaska Division of Geological and Geophysical Surveys.\nWhat are the noteworthy results?\n• This work provides a significant way to compare permafrost between diverse regions by looking at similarities in landform packages. I think it’s a significant broad-scale step in understanding landscape evolution and its relationship to climate change. As noted, it does have its challenges, and field data will improve the process.\nWill the work be of significance to the field and related fields? How does it compare to the established literature? If the work is not original, please provide relevant references.\n• Yes. It will help us better understand the evolution of permafrost over time on regional scales. As we make land management decisions, it’s essential to have a good understanding of potential landscape changes, which can inform land management decisions and planning for mitigating possible impacts.\nDoes the work support the conditions and claims, or is additional evidence needed?\n• As a first pass, yes. As the authors state, some conditions can’t be accounted for with this analysis, and so the methodology could undoubtedly be improved upon, especially with more landforms for the input.\nAre there any flaws in the data analysis, interpretation and conclusions? Do these prohibit publication or require revision?\n• It would be good to apply this methodology in other areas. The results are dependent on ecozone mapping. Consistency in scale and detail of that mapping when working between areas will impact results for comparison. This work is undoubtedly a significant first step, but how does this work account for those potential inconsistencies?\n• What was the reasoning for choosing the grid size? How do the results differ if you select a different grid size?\nIs the methodology sound? Does the work meet the expected standards in your field?\n• The scientific methodology is sound\nOther comments\n• Figure 4 is confusing. There is a line labelled “rainfall”, but it’s unclear what you are trying to convey with that line. The same is true for “percent water,” “air temperature,” and so on. These are explained in the text, but it’s not clear in Figure 4a.\n• Figure 4b, there are numerous labels “rock glacier,” “patterned fen,” etc. It would be helpful if there were lead lines. In its current state, these look like a bunch of words on an image, and it’s unclear what you are trying to convey."}, "author_response": "1\nReviewer Reply Summary\nWe have provided detailed replies to all reviewer comments, most of which have helped to clarify the\nManuscript, resulting in editorial modifications and the addition of one analytical figure, and one\nsupplementary Table. Our key objectives and findings, as well as primary analytical techniques and\ninterpretations, remain largely unchanged. We have indicated that three anonymous reviews have\nimproved the clarity and quality of the Manuscript.\nWe appreciate the detailed comments from the reviewers and their recognition of the value of the\nconceptual approach and the significant potential of integrated mapping and ecological analysis\ntechniques to advance understanding of variation in permafrost conditions. We address the main\ncomments regarding greater clarity on land classification frameworks and research objectives, and the\nimplementation of additional multivariate methods in the following ways:\n1. R1 Ecological land classification schema that we adopt to visualize our data and analyses is clarified. We\nprovide updated references to traditional landsystem approaches, and clearly explain how our study\nadvances these concepts by quantitatively exploring variation in permafrost landform characteristics and\ndeveloping a coupled conceptual framework to support inferences on intrinsic properties and thaw\ntrajectories. We improve clarity and consistency of language regarding land classifications, and that level\nIV ecoregions are \"a priori\" landsystems. We clarify that our landform inventory data is compiled at the\nscale of a landform assemblage and synthesized at the regional or landsystem scale. We have added a\nsupplementary table to help readers understand how the Northwest Territories (NWT) Land Classification\nsystem relates to National frameworks.\n2. R1 We explicitly state the aim and objectives of the paper and have added a distinct conclusion section.\n3. R1&R2 We better describe our rationale for use of the RDA to explore the landform data and how\nenvironmental variables influence their distribution and organization. The technique is valuable in\ndemonstrating that broadscale trends are partially explained by predictor variables, thereby confirming\nexpectations. However, the low explained variation and the graphical patterns illustrate the high degree\nof diversity in permafrost characteristics across these \"known\" environmental gradients, which cannot be\ndiscovered through heuristic approaches that rely on common predictor variables. This provides a key\nargument for the value of this novel dataset. The RDA scores and landform richness plots enable\nquantitative comparison of conditions between level IV ecoregions (a priori landsystems), so both\nanalyses are retained.\nIn response to R2's comments proposing several analytical methods to further explore the data, we chose\nto develop a clustered heatmap. This heatmap provides a strong complement and addition to the RDA,\nexploring common landform assemblages through hierarchical clustering and their influence on\ndistinguishing similarities and differences among a priori landsystems. Other suggestions, including the\ndevelopment of landsystem maps, are beyond the scope of this paper, although we acknowledge that\nthey offer excellent opportunities for future research.\nNumerous additional comments are addressed through minor text modifications.\nReviewer #1 (Remarks to the Author):\nThe authors introduce in their Manuscript the concept of \"permafrost landsystems\" which are spatial\nassemblages of Quaternary landforms (glacial, non-glacial, glacio-lacustrine plains, wetlands,..etc.)\nbearing typical permafrost features (e.g. tundra polygons, thermokarst ponds, retrogressive thaw slumps..\netc. (a list of 28 of them in supplementary table 1, illustrated with nice photographs). Perfectly true in my\nopinion: landforms and the ecosystems they support provide an excellent mean to map permafrost\nproperties (e.g. types and amounts of ground ice, sensitivities to thaw, susceptibilities for landslides and\nmass movements). Currently, almost all of the broadscale (e.g. circumpolar) efforts in mapping\npermafrost conditions using climate data, climate model outputs and remotely sensed surface parameters\nfail to produce outputs that can inform well on high resolution characterization of permafrost and thaw\nsensitivity. Those models do not either provide truly useful knowledge for decision and policy makers at\nthe level of a country (like Canada) or a region, even a large one such as NWT. This Manuscript therefore\nproposes an improvement in regional and national approaches of permafrost knowledge acquisition and\nsharing. Thanks to the work of some of the co-authors (O'Neill et al. 2019), Canada already has a\npredictive map of ground ice that is unique. It is currently being refined. This paper goes further in the\nsame direction.\nI think the Manuscript needs major revisions, particularly in tightening the reasoning and focusing the\narguments for the use of integrated surveys (\"multivariable\" here is not the correct word) and ecological\nmapping. From the start, the reader needs to have a clearer view of how the existing land classification\nscheme in NWT is structured and what is its terminology.\nResponse: We appreciate the comment.\nLand classification schemes: We clarify the NWT land classification scheme and provide more consistent\nlanguage, along with a supplementary table that provides the necessary details. We clarify that the\npaper uses the scheme to stratify and visualize our integrated landform mapping, demonstrating that\nour permafrost landform inventory approach provides a quantitative basis for exploring regional-scale\nvariability in permafrost conditions. The supporting conceptual framework enables the growing research\ncommunity to interpret landform data and make inferences about subsurface conditions and the\ntrajectories of thaw-driven change. We have refined our terminology and provided additional\nbackground on the NWT land classification scheme and its linkage with national frameworks. This is\naccomplished through minor modifications in the Introduction, text, and minor labeling adjustments in\nthe figures, as well as some additional information in the methods, including a key supplementary table\n(2) and references to Lacate (1969).\nClarifying objectives: We have modified the text to clarify the utility and application of permafrost\nlandsystem and mapping approaches. We explicitly state four objectives and the methods applied to\nachieve them. We have adjusted the text to clarify how the existing land classification scheme in the\nNWT was utilized to support visualization of the multivariate landform mapping analyses. We\nemphasized that our goal is to demonstrate that integrated permafrost landform mapping and\nmultivariate analyses methods provide a key opportunity to quantify regional variability in permafrost\nlandscapes, and that permafrost landsystems provides both a mapping and conceptual framework for\ninterpreting results towards better understanding consequences of thaw, upscaling with appropriate\n3\ncontext, and communicating permafrost knowledge across disciplines, knowledge systems, and to the\npublic. We believe this contribution constitutes a substantial advance in quantifying regional variability\nin permafrost conditions and provides a framework enabling multidisciplinary permafrost science.\nThe reader has difficulty to find his way among the ecozones and the ecoregions of various levels of\nintegration. What levels are defined by biomes and climate. What levels are defined on vast areas by\nphysiography. How do they nest into each others. Integrated surveys and ecological land classification\nstarted in the 1950s by the CSIRO in Australia. They were adopted in Canada in the 1960s (see Lacate,\n1969, pdf joined). The nested concepts of land region, land district, land system, and land types are\nstraihgtforward and provide a basic framework. A comparable framework is absent from the Manuscript\nand this creates confusion (see my comment at line 280 of the annotated pdf manuscript). Having done\ncontract work in ecological mapping in the late 1970s, my experience tells me that the \"permafrost land\nsystems\" are the same thing as conventional landsystems, but applied to permafrost landform\nassemblages.\nResponse: We appreciate the comment. We clarify that our paper builds on traditional landsystem\nconcepts, and advances a quantitative, permafrost mapping approach to enrich the existing, qualitative\nland classification schemes adopted in the NWT. We now provide sufficient background on the nested\nNWT land classification scheme, along with tables and references, to clarify how we utilize it to organize\nour data and analysis. The analysis demonstrates that integrated mapping enriches our understanding of\nspatial variation in permafrost conditions within a priori ecological regions. We clarify that an NWT\n\"level IV ecoregion\" is conceptually the same as a \"landsystem\", and that our mapping of landform\nassemblages and analytical approach allows variation in permafrost conditions within and between\nthese a-priori landsystems to be quantitatively explored. Finally, we demonstrate that permafrost\nlandsystems also offer a conceptual framework to interpret results and communicate more effectively\nthe integrated nature of permafrost, ecosystems, and thaw-driven landscape responses.\nThe paper lacks a clear statement of what are its objectives. As far in the text as line 114, I could not find\nsuch a statement. The aims of the paper should appear clearly.\nResponse: We have added a clear statement of our goal and objectives.\nAt line 120, the term landform type is introduced. I would say permafrost landform (there are 28 of them\nthat reoccur in the landscape) and save the word \"type\" for \"land type\", which refers to a high level of\nintegration of soil, morphology, vegetation and wetness (but at a larger mapping scale) in land\nclassification procedures. For instance, the nice block-diagrams of figures 1 and 2 which represent\nassemblages of landforms can be subdivided in land types that have almost uniform combinations of soil,\nmorphology, slopes and vegetation cover. Similarly, block-diagram 3 on figure 3 could be subdivided into\nthree permafrost land types (ridge with ice wedges, wetland with low center polygons, high center\npolygons). Both in theory and practically, this is the level at which permafrost conditions are nearly\nuniform. This is the level of integration that would be applicable for designing an infrastructure, for\ninstance.\nResponse: We removed the word \"type\". We added an annotation to the Figure showing indicating the\nlandform assemblages.\nSome questions that rose in my mind while reading are: are the permafrost land systems mapped over the\nstudy region? Is there a map or a data file of them? Or are the land systems a concept that the authors\nrecommend using on an ad hoc basis for specific infrastructure, community or impact assessment projects\nin the region? Could a gridded climate model be overlayered and integrated with a map of permafrost\nland systems? These are matters at least for Discussion.\nResponse: We appreciate these thoughts and feel that the integrated landform mapping and analyses,\nconsidered within a Permafrost Landsystem framework, have exciting potential to build a more\nquantitative understanding of variability in permafrost conditions and thaw trajectories of northern\nlandscapes.\nThe raw data in our analyses will be provided with the Manuscript at publication. The gridded climate\ndata is integrated in our analyses as an explanatory variable in the RDA. Several of the points raised by\nthe reviewer are considered in the Discussion.\nThe process, or method, applied to run the RDA analysis needs to be explained more simply. See my\ncomments in bubbles and highlighted text on the pdf. I was a bit confused about what variables were used\nin the RDA. I understood these are only the climate variables and the morphons (i.e. relative elevation\nvalues). If so, it is not surprising in my mind that the total explanation of variance is only 23%. Of course,\nclimate regulates the thermal regime and the rates of the processes acting in permafrost. But the surficial\ngeological units (an identification value) that are the main controls on ground ice contents is not a\nnumerical value usable in statistics.\nResponse: We have revised the text and Supplementary table to indicate the explanatory variables used\nin the RDA clearly. We indicate that surficial geology and modeled ground ice, included as categorical\nvariables in testing, were collinear, derived variables, and did not improve the percentage of variability\nexplained by the model. This finding highlights the importance of the landform inventory in\nunderstanding regional-scale variability in permafrost conditions. Broadscale surficial maps or modeled\nground ice are not of sufficient resolution to improve knowledge of variation captured by mapping\nlandforms at the regional scale of inquiry.\nOne might argue that better or finer-scale surficial maps are a key to improved prediction of permafrost\nproperties (see O'Niell et al., 2024). However, to reiterate, fine-scale surficial products are only available\nsporadically across vast northern regions. Furthermore, when employed in a heuristic framework, they\ndo not really enable new knowledge to be generated.\nFrom lines 280 to 364, the five insights can be commented upon in much shorter text. Some basic ideas\ncan be stated more simply. For example, there is less diversity in the discontinuous permafrost zone\nsimply because only palsas and peat plateaus are left as permafrost in the landscape.\nResponse: We appreciate this comment, and numerous others provided as embedded reviewer notes\nfrom P12 and 14. However, the \"common knowledge\" of experts is neither explicit nor accessible in a\nquantitative manner. The analyses and results presented in this paper provide a basis to improve\nunderstanding and quantitatively compare variation in permafrost landscapes at the landsystem scale.\nThe multivariate analyses contain a large amount of information, which we feel is best expressed\nthrough explanation tied to place. In relation to R2 comments, we have also produced a clustered\nheatmap based on all of the mapped grid cells to more deeply support this text. The analysis illustrates\nnovel ways to quantitatively assess and visualize similarities and differences in permafrost conditions\n5\nbetween a-priori level 4 ecoregions (landsystems), and explore how permafrost landforms assemblages\ncombine to determine the differences amongst them.\nSimilarly, the Discussion is too long and should be more focused.\nResponse: We have condensed parts of the Discussion while elaborating on a few points and questions\nhighlighted by the reviewer in a previous comment.\nThere is no concluding statement. There is so much value to be added in permafrost mapping in adopting\ngeomorphology and Quaternary through the permafrost landsystem approach.\nResponse: Thank you, we have added a concluding paragraph.\nIn general the text could be better integrated, concise, somewhat compacted and less \"overtheoretical\".\nResponse: We have considered this comment in revising the Discussion.\nThe figures are excellent. I made many comments on the pdf.\nResponse: We are glad the reviewer appreciated the figures.\nSpecific comments in annotated PDF. Reviewer 1\nP2L36. not clear what is meant by \"multivariable\" landform inventory. In fact ecological land\nclassification consists in mapping units of territory at different scales of integration of landforms, soil,\nvégétation, climate etc. (ex. region, district, system, type, phase..). They are integrated surveys, an\napproach to ressources mapping developped sinve the 1950s. In Canada, see Lacate, 1969). As I read in\nthe paper, typical permafrost landforms (a list of 28 of them, as insupplementary file 1) were counted in a\nnumber of map pixels (not clear if it is in whole land systems) and the classification tested in a RDA with\na limited number of climate variables.\nReply: To clarify the reviewer's initial comment, we have removed the word “multivariable” and\nadjusted the text to \"Here, we analyze an inventory of permafrost landforms from across of\nnorthwestern Canada …\"\nWe have also now clarified that permafrost landforms were assessed in all grid cells (3,290) from the 14\nlevel 4 ecoregions, and a subset of these (2,030) was input into the RDA. Primary climate and\nterrain/environmental variables were used as explanatory variables in the final RDA.\nRatoinale and strengths of the approach are described in our general comments, above.\nP2L37. assemblages by definition are not homogenous, therefore the mapped permafrost properties will\nalso be spatial assemblages. Differences in \"superficial\" permafrost landforms and permafrost\nthemperature regime wil be noticeable at the scale of ecoregions because they have different climate\nconditions by definition.\nReply: We agree with the reviewer's comment and have expressed the integrated nature of permafrost\nenvironments in our text, which is the essence of permafrost landsystems as a conceptual framework.\nThe approach in the paper enables spatial landform assemblages to be evaluated quantitatively. We\n6\nexplore variation in the landform data stratified by level IV Ecoregions, conceptually similar to\nlandsystems as expressed in the Ecosystem Classification Group (2007). The hierarchy in the NWT\nClassification system and its relation to the national framework are referenced directly to a source figure\nin Ecosystem Classification Group (2007) and summarized in Supplementary Table 2.\nP2L39. Quaternary and Holocene history.\nReply: We keep our text more accessible to a broad community and have expressed these two ideas\nmore generally as \"geological and climate legacies.\"\nP2L41. maybe make a clearer distinction between variability within land systems (defined by internal\ngeomorphic composition) and variability between land systems of different ecoregions and ecozones\nwhich have different climate conditions along the gradient from Subarctic to Arctic). There are local\ntrajectories within systems dependant mostly on soils for impacts and climate-driven regional trajectories\nto be understood for broader adaptation.\nReply: We appreciate the comment and have made a minor adjustment on Figure 3 to clarify this point.\nP2L49. maybe be more specific in the paper. Engineering and infrastructure issues are often at the local\nscale. Land use planning and policy making are regional in scope. Ways of knowing refer to traditional\nkwoledge of the land by Northeners.\nReply: We appreciate the comment and consider this in our revisions throughout. A minor editorial\nmodification establishes the link between landsystem concepts and decision-making in the abstract;\nhowever, word limits constrain further elaboration.\nP3. Good general Introduction\nReply: We appreciate the reviewer's comment.\nP3L71. I think the O'Neill et al. 2019 model is different from the other ones. In comparison with them it is\nbased on surficial geology and Quaternary history. It better predicts ground ice conditions, hence\nthermokarst. Most other ones are based on data from climate model outputs and remotely sensed\nparameters. What you propose here, to me, is different from climate-model based systems and better\nsuited for support national, regional and local decision-making for adaptation.\nReply: We appreciate that the reviewer's comment on O'Neill et al 2019. All of the products referenced\nin the list are heuristic in nature. While the logic behind O'Neill et al. (2019) aligns well with landsystem\nconcepts, its manifestation summarizes existing knowledge in the rule-based geomatics framework. We\nconsolidate these references to highlight several broadscale, permafrost-related outputs that, despite\ntheir inherent limitations in generating new knowledge, collectively shape our understanding of the\npermafrost environment and the consequences of thaw. The statement sets the context for regional-\nscale permafrost mapping and the generation of new knowledge within a quantitative framework.\nRegarding the final part of the R1 comment, we adjusted the text to emphasize the utility of empirically-\ndriven permafrost landform mapping, analysis, and interpretation within a permafrost landsystems\nframework, aiming to advance understanding of variation in permafrost conditions necessary for\nnational, regional, and local decision-making.\nfrom model-based circumpolar maps of permafrost conditions\nReply: We appreciate the reviewer's view on this contextual statement, which helps make a case for\npermafrost landsystems as an important analytical and conceptual framework.\nP3L84. I agree. Wide scale predictive models ar of little practical use because they are not based on\nadequate knowledge of the terrain and subsurface conditions that can be captured only at the scale of\nlandforms and mappable surficial geological units.\nReply: We appreciate the reviewer's comment.\nP3L84 Why renewed?\nReply: We have changed this to \"growing\" rather than \"renewed\". The citations here provide examples\nof mapped variation in permafrost landforms over large areas. In two cases, the papers demonstrate\nincongruence between modeled outputs and systematically collected permafrost landform data.\nP4L93. I suggest here that you revisit the concepts of ecological mapping and land classification that were\nwidely applied in Canada in the 1970s and 1980s. see Lacate, 1969. Although they were not used in\npermafrost regions, they still hold very well. (Region, district, systems, types, phase)\nReply: We thank the reviewer and have added reference to Lacate 1969. As indicated above, we now\nprovide additional context on traditional land classification systems by adding a concise narrative, a new\nsupplementary table 2, and references, clarifying how the NWT land classification framework relates to\nthe legacy of past approaches (e.g., Lacate, 1969), and fits within the national/continental framework\n(Table 1 in Ecosystem Classification Group, 2007).\nWe also add text in the Methods to clarify the NWT land classification system and its linkages to ideas\npresented by Lacate and others. We also clarify that the approach in this paper \"extends Landsystem\nthinking through an explicitly permafrost lens, applying a conceptual tool to support mapping and\nadvance discourse on critical permafrost issues.\"\nP4L111.integrated mapping = beter understanding of the functionning of ecosystems. Can lead to better\napparisal of environmental and social consequences of climate warming and thawing permafrost.\nReply: We agree, and this point is expressed in the Introduction and now explicitly in the Fig 3 caption.\nP4L111. At this point, it is unclear what the objectives of the paper are. In the following paragraphs, you\nexplain the concept of permafrost land systems and you attempt to demonstrate its \"applicability\"\nrather\nthan a real or potential application. The concept of land system in ecological land classification is 60-70\nyears old. You are ably extending it to permafrost regions.\nReply: We have adjusted text to indicate the overarching aim, specific study objectives, and explicit\nlinkages to analytical methods. We clarify that this paper aims to extend traditional landsystem concepts\nto permafrost regions, and develop coupled mapping and analyses to characterize and contrast\npermafrost landscapes quantitatively within a landsystem framework.\nTo our knowledge, this is the first time that systematic permafrost landform inventories have been\nanalyzed quantitatively to evaluate the composition and variability of the permafrost landscape at\nregional scales. Furthermore, we highlight the permafrost land system framework as a conceptual tool\n8\nfor interpreting spatial landform patterns and inferring ground-ice, soil, and temperature conditions,\nas\nwell as potential trajectories of thaw-driven change. While this may be known to the expert reviewer,\nwe feel it is important to express this in quantitative terms to the growing diversity of scientists,\nplanners, and policymakers interested in understanding variation in permafrost environments.\nP5L120. so a 7.5 X 7.5 km grid was laid over the study region and you counted the permafrost landforms\nin 2030 cells. Were the cells selected at random or by some stratified sampling among ecoregions?\n2030\nrepresent what % of the total number grid cells over the study region? how can you affirm that the sample\nis representative of the whole set?\nReply: We have adjusted the text to clarify that our RDA analyses (mapped cells and derived\nenvironmental/predictor variables) comprises a subsample of 7.5x7.5 grid cells (1959) from 14 level 4\necoregions, which are conceptually similar to \"landsystems\". Descriptive summaries, landform richness\ncurves, and a new clustered heatmap depicting landform and landsystem associations comprise all grid\ncells (3,402) within the 14 level 4 ecoregions.\nWe clarify that our selected ecoregions aim to evaluate conditions encountered across the NWT. We did\nNOT randomly sample the entire 1.3 million km2 area of the NWT. In the Introduction and methods, we\nclarify that the ecoregions selected represent a sample of climate and geological endmembers found\nacross the continental-scale ecoclimate gradient in the NWT, allowing us to demonstrate the application\nand utility of our quantitative approach. The NWT Ecoregion hierarchy used to stratify our data is now\nalso shown in Supplementary Table 2.\nP5L123. I see in text and supplementary table 2 that only the climate variables and the morphons were\nused in the RDA (am I correct?). These are numerical variables (ex. temperature values, elevation\ndifferences). Therefore the geological variables (ex. sediment type (not numerical) and classes of ground\nice contents (not truly numerical like volumetric ice contents) were not applied in the RDA). Am I\ncorrect? this is not crystal clear in the text, one has to search for these precisions in the text and tabl\nReply: We indicate that only primary numerical variables or those derived directly from quantitative\ndatasets are used as predictor variables. Following careful consideration among the diverse Authorship\nteam, we chose not to include hueristically-derived broadscale modeling products as predictor variables\nbecause they typically reflect an integration of other broadscale datasets, which are often highly\ncorrelated. Regardless, we tested categorical data from several derived or generalized datasets as\npredictor variables in the RDA, including surficial geology and predicted ground-ice and permafrost\nprobability. We found that their inclusion had little to no impact on the % of variability explained in the\nobservational data. We indicate this highlights the importance/utility of systematic landform mapping\nfor understanding variability in permafrost conditions.\nP5L124. Ecozone\nReply: Our stratification for broadscale analysis is at the level 2 ecoregion, or ecozone. We adjust the\ntext and figures accordingly. We reference to the NWT classification system, as well as mapping scales\nand terminological equivalents in Supplementary Table 2.\nthis is a very complex land classification system. The international reader will have much difficulty to\nunderstand it. Where do excatly permafost land systems fit in that scheme. Have you mapped the land\n9\nsystems at a scale corresponding to diagrams of figure 1 and 2? or are they concepts to be used at variable\nscales? is the concept primarily intended for extracting local permafrost information from maps of\necoregions?\nReply: We have provided Supplementary Table 2 that summarizes the NWT classification scheme and\nhow the levels fit within national frameworks. We clarify that level 4 ecoregions are conceptually similar\nto landsystems, explain this in the methods, and provide a reference and table to clarify this. We clarify\nthat our data is generated at the grid cell scale, and is analyzed and summarized at the landsystem scale\nfor regions ranging from 10^3 to 10^4 km2. We also demonstrate that analyzing systematic landform\ninventory data alone has potential to derive permafrost landsystems. Our analysis highlights the\npotential of systematically collected permafrost landform data and analyses to enrich or even\nrestructure existing schemes on a quantitative basis, thereby enabling the generation of new knowledge\nabout permafrost terrain conditions. We also indicate that the approach can upscale local results to\nbroader regions with quantitative context.\nP5L131. mabe be more specific here: by permafrost conditions one means ground ice types and contents,\nrange of temperature profiles, carbon (organic matter) contents ??\nReply: We clarify this through a minor modification of the text.\nP5L134. \"integrated\"\nReply: The suggested editorial modification has been implemented.\nP5L136. If I understand well, the aims of this paper is to explain the approach and to propose to use the\nland system concept for those objectives. But are the mapping units (permafrost land systems) available\non maps/file?\nReply: We have adjusted the text to clarify that we advance a permafrost landform inventory/mapping\napproach to quantify variability in permafrost landscapes at the \"landsystem scale\", and a conceptual\nframework (permafrost landsystems) within which to interpret the data. We emphasize that combining\na quantitative approach with a conceptual framework can support a more robust appraisal of the\nenvironmental and societal consequences of climate change and thawing permafrost at regional scales.\nThe inventory results of mapped grid cells for the ecoregions will be provided upon publication.\nP7L166. I think the ground ice in the glaciolacustrine sediments must be segregated.\nReply: Yes, we agree and have modified the text accordingly.\nP8 L 177. as in previous land classification schemes, permafrost land systems are themselves assemblages\nof higher scale assemblages of \"permafrost land types\". In fact the true integration, i.e. one soil type - a\ndominant pattern of permafrost landforms (metre to decameter scale), one class of ground ice content, one\nclass of organic layers thickness - is at the land type level.\nReply: We appreciate the reviewer's views.\nMinor modifications to the captions/descriptions of Figures 1-3 clarify that assemblages and land types\nare synonymous. The reviewer's point is expressed through the graphic.\nplain is a vast ecotone (i.e. transitional), then it poorly represents regional climate. It is rather\nphysiographic.\nReply: The high subarctic Taiga plains are a level 3 ecoregion, comparable to an Ecoprovince (as defined\nby the Canada Committee on Ecological Land Classification) or an ecoclimate region (Ecoregions\nWorking Group, 1989). Level 3 ecoregions are defined by regional climate differences within Level 2\necoregions (Ecozones). Terminology has been clarified in the text and linked to Supplementary Table 2\nand a referenced summary table in Ecoregions Classification Group, (2007).\nOur data and analysis show that hard lines on geology, ecoregion, and land cover maps are often fuzzy\nboundaries. The data and analyses provided here offer a transparent, accessible, and quantitative\napproach to explore a priori land classification schemes, the outputs of heuristic mapping products, and\nexciting opportunities to learn new things about variation in permafrost landscapes and existing\nclassifications that are products of mapping overlays integrated in a GIS framework.\nP10L248. i.e. applying only broadscale spatialized climate and modelled data without incorporating\nknowledge of surficial geology and climate history\nReply: We agree and have tweaked the sentence slightly to be more explicit. However, the salient point\nhere is the importance of advancing empirical approaches to generate new knowledge of variation in\npermafrost conditions.\nP10L251. this rather indicates that geology and ecological conditions need to be included in spatial\nanalyses and mapping through systematic landform inventories ...\nReply: We thank the reviewer for this comment and have made the necessary adjustments.\nP12L280. The paper needs more clarity. The recommended land units for understanding permafrost in the\npaper are land systems. In fact, the true integration of ecological components is a the land type level. And\nthe paper comments the results of the applied methodology at the ecoregion level. That creates confusion\nReply: We thank the reviewer for their perspective. We indicate that the mapping inventory of\nlandforms identifies assemblages and demonstrates that their organization at the landsystem scale can\nbe quantitatively assessed to better understand regional-scale variability. In the abstract, manuscript\ntext, and figures, we argue that the true integration of soil, ground ice, and ecological components is\nfound in landform assemblages or \"land types,\" and quantitatively assessing their patterns, here at the\n7.5x7.5 km grid cell provides data for quantitative analysis and regional-scale understanding of\npermafrost conditions.\nThe emphasis is that systematic and integrated permafrost landform mapping provides a critical vehicle\nfor generating a new understanding of regional variability in permafrost characteristics. This approach\nmoves beyond heuristic/expert knowledge-based classification frameworks or geomatics overlay\nactivities to portray landscape regions. Our mapping approach provides a first attempt to generate\nsystematic, quantitative regional-scale permafrost knowledge. A linked, geologically based conceptual\nframework (permafrost landsystems) enables information to be transferred across scales and\ncommunicates the impacts of thaw-driven change to broad audiences.\nto recall.\nReply: We appreciate the reviewer's comment and agree.\nP13L322. to be expected. Permafrost is a geological and a climatic phenomenon. The two are inseparable\nin permafrost science.\nReply: We appreciate the reviewer's comment and agree.\nP14L341. normal because ecotones are by definition transition zones where systems change and merge\nfrom one to another, thus creating diversity.\nReply: We appreciate the reviewer's comment and agree.\nP14L351 this is self evident! the only landforms left in the landscape are decaying palsas and peat\nplateaus. Often the discontinuous permafrost zone has more non-permafrost that permafrost terrain (as\nlow as 1-5% area)\nReply: We appreciate the reviewer's comment. However, although this may be self-evident to a\ndisciplinary specialist, we feel that the point is important for the broad audience that requires\nknowledge of permafrost and permafrost change.\nP14 L360. I suggest that those five paragraphs of insights be reduced in length and be explained in\nsimple sentences (maybe in a less theoretical style?)\nReply: We chose to keep this section to its original length and have added an additional figure (Figure 6,\nclustered heatmap) to quantitatively visualize \"self-evident\" knowledge. We agree that an expert may\nexpect the broadscale trends expressed in our analysis. However, these comments prompt recognition\nthat expert knowledge reflects a highly variable, non-explicit, and often proprietary understanding of\nthe permafrost landscape held by a small group within a rapidly growing community of multidisciplinary\nresearchers, planners, and policymakers interested in permafrost and ecosystem change. This expert\nknowledge is typically summarized through general statements and rules of thumb, supported by\nschematic representations of the environment. Expert knowledge, summarized through heuristics\napplied within a geomatics framework, manifests as rigid boundaries on maps, and the quality and\nresolution of derived data products constrain outputs. Rule-based models reflect decisions based on an\nexpert knowledge base, providing an economical way to portray what we think we already know. The\nsources of error and uncertainty are typically not explicit, and variability cannot be accurately assessed.\nP15L366. Figure 5. Maybe explain on the graph scale label or in the caption what is \"Richness\". Number\nof observed (recurring) landforms (from the list of 28 inventoried) counted in the grid cells\nReply: Minor editorial modification is applied.\nP16. The Discussion is too long and takes the reader in many different directions. Couls be shorten in half\nand adress only the central topic.\nReply: We appreciate the reviewer's perspective. Although we have removed a paragraph discussing\nlandform and ecosystem evolution, based on the reviewer's previous comments, we feel that the\nthe constraints of existing qualitative and heuristic products that portray regional-scale permafrost\nconditions, and emphasize the exciting potential of integrated permafrost landform mapping and\nquantitative analyses to gain new insights into regional-scale variation in permafrost conditions. We\nhighlight permafrost landsystems as a mapping and analytical approach to generate and visualize new\nknowledge about regional variability in permafrost conditions. We finally describe how the approach\nserves as a conceptual framework for interpreting data, making inferences, and communicating\npermafrost knowledge across disciplines, to decision-makers, and across knowledge systems. As\ndescribed above, our text is targeted toward a broad, non-specialized audience with a vested interest in\nthe permafrost sciences, as appropriate for the audience of Nature Communications.\nP16L393. Permafrost landforms and thermokarst landforms manifesting the consequence of thaw are\nregrouped in land patterns or spatial assemblages that we called permafrost land systems, which are\nindicative of the fundamental permafrost porperties in a region.\nReply: We implemented a minor editorial modification to the first sentence of the Discussion to address\nthis comment.\nP16L401. a question for Discussion: would simply use surficial geology map at a proper scale as base\nlayer and superimpose permafrost and thermokarst landforms make a product of equal or better value?\nReply: This integrated approach is certainly worthy of further exploration; however, it falls beyond the\nscope of this paper. A major challenge is to obtain surface geology maps at appropriate and consistent\nscales to address questions of variability in permafrost conditions across a territorial scale (10^6 km^2)\nand to ensure consistent comparison of ecoregions (landsystems), gradients, and patterns across\nregional scales. The RDA shows that if the best surficial map across all landsystems of interest is used, it\nis at an insufficient scale to explain much of the variability in the mapping data. So for characterizing\nregions within a comparable, quantitative framework, the mapping data reveals much new information.\nP16L414. is RDA the proper predicitive method? not sure because surficial geology units are not\nquantitative variables?\nReply: The RDA is a flexible tool for examining which environmental gradients explain the variability in\nhow permafrost features organize and where they occur. Adding surficial geology as a categorical\nvariable had little impact on the explanatory power of the RDA.\nP16L418. could the problem of heterogeneity be solved by integrated mapping at a larger scale (scale of\npermafrost land types). I understand however that NWT is vast. But that level of integration could be\nused for specific studies (communities, infrastructure projects, environmental assessments..)\nReply: We agree that heterogeneity at the regional (landsystem scale) can be described quantitatively\nthrough systematic/integrated mapping. We make a minor modification to emphasize this gap in the\nDiscussion, its application for comparing conditions between regions, and its use in community and\ninfrastructure planning projects for scoping Environmental Assessments.\nP17L432. you need to say how the distribution of carbon and its contents are related to the permafrost\nland systems by association with specific landforms and trough ecological history.\ndelete.\nP17L443. Thie whole paragraph is not necessary in the paper\nReply: The linkages made in this paragraph are implicit to the expert reviewer but they are not\ncompletely understood by many scientists studying permafrost systems. We have deleted most of the\nparagraph but retained the key point that field-based investigations and monitoring of landform\nassemblages are critical for guiding inferences from the spatial patterns determined by systematic\nlandform mapping.\nP18L474. Models based on climate projections, depicting permafrost distribution and predicting\nupcomimg degradation would benefit to be applied onto permafrost land system maps to truly represent\npermafrost conditions and be of practical use.\nReply: We thank the reviewer and adjust the text slightly to make this point.\nP19L482. this refers to people living in the North and to practitioners (e.g. engineers, land use planners).\nBut the paper does not allude to the variable perceptions and experiences of people across the vast region\nof study.\nReply: Variable perceptions of people's understanding of permafrost is not a focus of this paper. Our\npoint here is simply that there are variable perceptions and experiences regarding people's relationship\nwith and knowledge of permafrost. The conceptual framework offered by permafrost landsystems has\nsignificant potential to help foster communication of knowledge across different groups towards a\ncommon or better understanding of conditions, trajectories of change, and consequences.\nP18L488. Indigenous?\nReply: Yes and we have added an appropriate reference.\nReviewer #2 (Remarks to the Author):\nReview of \"Permafrost landsystems provide the key to understanding climate change effects on northern\nterrain and ecosystems\"\nby Steven V. Kokelj et al.\nThis study analyzes an extensive dataset on the occurrence of permafrost landforms gathered by the NWT\nThermokarst Mapping Collective, in order to bring the wealth of information it contains to a wide\naudience. The authors' interesting analytical innovation is to apply statistical techniques developed in\nplant community ecology to a geomorphological dataset, by treating systematic 7.5 x 7.5 km remotely-\nsensed grid squares as the \"plots\" and the permafrost landforms in each plot like plant species in\ncommunity ecology. These statistical techniques are then used to draw inferences about the significance\nand distribution of permafrost landforms in the study area.\nI believe the application of the community-ecology methods to this dataset is both innovative and\npromising. RDA analysis (the main statistical tool used here) is a powerful technique, and it yielded\nreasonable results, but nonetheless I have some thoughts about its application.\n1) My understanding is that RDA is appropriate for response variables with more-or-less normal\n14\ndistributions, while in your data set the response variable was binary presence-absence (as stated in the\nmethods, p. 22 line 21, though the barplots in Fig. 3 imply a semiquantitative scale \"trace\", \">trace\").\nReply: We appreciate the reviewer’s comment. We agree that the RDA approach is helpful and – as\ndescribed in our responses above – yielded illuminating results. In response to this comment and the\nfollowing comments, we have bolstered our statistical approach by adding analyses, as described below.\nThese additional analyses reinforce and add to the RDA outputs. We have additionally adjusted Fig. 3\nand plotted only presence/absence on the bar plot to avoid confusion.\n2) RDA is designed to ordinate the response variables (samples of permafrost landform assemblages) in a\nspace created by the explanatory (environmental) variables. It did this successfully here in the sense that\nRDA discovered the familiar north-south climatic gradient in permafrost landforms and also a sloping vs.\nflat landform gradient. It is comforting (but not highly informative) to see these well-known trends\nconfirmed using \"big data\", and also not surprising that most of the variation in landforms (77%) was\nactually not explained by available GIS variables.\nReply: We appreciate the reviewer's assessment and agree that this analysis supports general, known\ntrends. The data visualization shows substantial variation in permafrost site scores, with a significant\nportion unexplained by the primary environmental variables. In addition to quantifying the influence of\nenvironmental variables on landform patterns and combinations, the RDA illustrates significant\nvariability across the landscape that heuristic approaches and spatial modeling cannot capture. In\nessence, the fact that the RDA uncovered that the climate variables commonly used to predict\npermafrost distribution and thaw trajectories explain only part of the variation is a benefit of the\nanalysis. We describe this in our responses above, and also now add some text to the end of the second\nparagraph of the Discussion to better explain the importance of this finding.\nThe authors undoubtedly suspected that this was going to be the case beforehand, from their very\nextensive experience with mapping permafrost landforms; that is probably why they invested so much\neffort in manual mapping! So my reaction to this would be to recognize RDA's limited usefulness in this\ncontext: the explanatory (GIS) variables are statistically significant but have weak explanatory power;\nRDA actually limits your understanding of permafrost landform assemblages to the 23% of the variation\nin permafrost landforms that is associated with the environmental (GIS) variables. Unfortunately, the\nnature of the remaining 77% of the variation unknowable by this method. My response then would be to\nspend less time on RDA and look at other community ecology methods that might teach us new things.\nThe use of species accumulation curves by level IV ecoregions was a good first step.\nReply: Thanks for this comment. Please see our response above, describing how the “limitation” of the\nRDA is also illuminating, and our description below of additional analyses. We agree that the RDA\nconfirms general broadscale trends that are known, but are not quantified over regional scales. In this\nregard, the RDA demonstrates the power of the mapping dataset and highlights challenges with\nconventional approaches to classification and map drawing. Broadscale spatial modeling products shape\nour understanding of permafrost conditions and persist as the best input datasets for various broadscale\napplications. Stratifying RDA scores by level IV ecoregions (Fig. 5) was an obvious continuation of the\nRDA, to demonstrate a quantitative method for visualizing differences amongst regional-scale\necoregions (a priori landsystems). We appreciate the reviewer's comment on species (landform)\naccumulation curves as an additional step in understanding and quantifying regional variability.\nquantitatively. The illustrations in the paper only hint at which landforms occur together in assemblages.\nMultivariate plant community analysis techniques like cluster analysis, PERMANOVA, and NMDS are\ndesigned specifically to discern and describe communities/assemblages. The NWT Thermokarst Mapping\nCollective dataset is globally unique in it's suitability for such analysis. The 7.5 x 7.5 km grid cells are a\nhuge unbiased sample of the permafrost landforms assemblages (and ecoregions are excellent strata to\nsummarize them). I would like the authors to consider using other community ecology methods to shed\nsome light on questions like: What are the natural groups of permafrost landforms? How distinct are the\ngroups and how do they overlap? Are they distinct enough to be mappable? Which \"species\" (landforms)\nare \"generalists\" (occur everywhere and thus are not highly diagnostic of permafrost conditions), and\nwhich landforms are very specific and diagnostic of a unique assemblage or diagnostic of unique\npermafrost conditions? I understand that classification of permafrost landform assemblages, like any\nclassification exercise, could be a time-consuming rabbit-hole to disappear down, but it might also be\nvery fruitful. And you appeared to suggest doing it on p.18 line 16. If you were able to develop a\nclassification of permafrost landform assemblages, such that the dominant assemblage in each grid cell\ncould be classified, then you would instantly have a 7.5 km pixel resolution map of permafrost landform\nassemblages for your whole study area. It would undoubtedly be related closely to the ecoregions, but the\nfiner patterns within and between ecoregions could be fascinating and useful. If the authors attempted this\nand decided it wasn't worth pursuing, please explain why.\nAn additional benefit to defining concrete landform assemblages would be to give the reader a better\npicture of what they are. Along similar lines, the \"permafrost landsystem\" concept can be difficult to\ngrasp. Would a mapped area dominated by one or few permafrost landform assemblages qualify as a\n\"permafrost landsystem\"? If so then defining landform assemblages and mapping them by labeling the 7.5\nkm grid squares would be a great way to make permafrost landsystems more concrete and understandable.\nReply: We agree that there is much opportunity to further explore the novel dataset using the cross-\ndisciplinary approaches that we have employed. We addressed the reviewer's useful input by\ndeveloping a clustered heatmap (Fig. 6) to explore common assemblages through hierarchical clustering\nand to visualize their influence on distinguishing similarities and differences among level IV ecoregions\n(landsystems). Each row in the clustered heatmap essentially reflects a landform fingerprint distinct to\neach a-priori ecoregion. While we only explored a couple of methods from community ecology analysis,\nthey have demonstrated the utility and opportunities for adopting them in future research.\nThe potential for further exploration of this dataset, or of the entire NWT once complete, is\ntremendous. It offers significant opportunities to learn about common assemblages, their patterns of\nvariation across landscapes, and provides an exciting and relevant research avenue for researchers to\nexplore. We agree that mapping the assemblages is a good idea and will be a focus of future research.\nA few other miscellaneous comments:\nThis study relies heavily on the Level IV Ecoregions by the Ecosystem Classification Group (2008-2013).\nHowever, only the 2008 Taiga Shield ecoregion inventory is cited in this article, though ecoregions from\nseveral other reports were used.\nReply: We have added citations to the remaining Ecoregion reports.\nthem, but only after enlarging the text on-screen to 200%.\nReply: The figures conformed to Nature guidelines. We have increased font size where possible.\nThe Methods section begins by saying that permafrost landforms were systematically inventoried for the\nentirety of the Northwest Territories. But the soon after on p. 22 line 16 it says that systematic\nobservations of these landforms were made from 14 level-IV ecoregions. So it appears that this report is\nspecifically about the subset of 14 ecoregions. Please clarify the connection of this study to the territory-\nwide inventory.\nReply: We have clarified what ecoregions were sampled and the rationale at several places within the\nManuscript and in the methods.\nIt would be helpful to provide some more information about the sampling methods, beyond the citation of\nKokelj et al. (2023). I understand that you selected 2030 7.5 x 7.5 km squares, which cover 114187 km2,\nand presumably these were restricted to be within the 14 ecoregions. This is just under 10% of the full\narea of the NWT, and judging from the size the ecoregions on Fig. 2 it appears that the 7.5 x 7.5 km\nsquares covered the entirety of the selected ecoregions. Do you have any more explanation for why you\nchose these 14 ecoregions? Also, citing Kokelj et al. (2023) and also the barplot in Fig. 3 might imply that\nyou inventoried some landforms by cover classes, but p. 22 line 21 implies only presence/absence of\nlandforms within each grid cell was recorded. I get why you would have done this (presence/absence is\nmuch faster), but please clarify. Also please note briefly what imagery was used in the inventory.\nReply: We clarify the sampling design and the rationale for choosing the 14 level IV ecoregions to\nsample. We clarify that we use presence absence data in this paper. Presence/absence is available for all\nlandforms, and it enables patterns of variation to be explored in a manner that meets the paper\nobjectives. We have modified the plate on figure 3 to include only presence absence data to avoid\nconfusion. We have elaborated the methods provided in this manuscript and also point authors to\nKokelj et al 2023 and references within, including Open reports that summarize in detail the inventory\nmethods. Furthermnore we clarify that Sentinel-2 imagery (2016–2017; 10 m resolution) was used for\nthis inventory and now clearly indicated in the methods.\np.23 line 662. \"Topographic indices\" were computed for each 7.5 x 7.5 km grid cell. These appear to me\nto be indices that are typically computed for pixels (90 or 250 m), and it seems to me that they could vary\nwidely across a 7.5 x 7.5 km grid cell. Please explain how they were generalized for 7.5 x 7.5 km grid\ncells.\nReply: We clarify that we used the variation of \"geomorphons\" within a gridcell rather than the 'mean'.\nThe intention was to have a metric that separates grid cells with a larger number of different\ntopography types from more homogeneous ones, providing an intuitive index for topographic\ncomplexity. Details are in Supplementary Table 3.\np.23 line 672. \"Following standard procedures, we scaled environmental variables for the 7.5 x 7.5 km\ngrid cell framework.\" It's not clear to me what the standard procedures might be. Z-score across the whole\n17\nstudy area?\nReply: Scaling was applied in the RDA function for environmental variables. The sentence was adjusted\nto improve clarity.\nSupplementary Table 1\nVery useful and well done. One comment:\nPatterned_Forest_Lowland - the caption seems to indicate that this class was used on both polygonal and\nstring-flark patterns. I hope not, as they are usually distinguishable and, as the caption notes, have\ndifferent permafrost interpretations. And then later you indicate that you have a separate string fen class.\nReply: We removed the confusing extra narrative for Pattern_Forest_Lowland, which aims to capture\nforest patterns and their relation to polygonal terrain, sometimes visible in low subarctic alluvial\ndeposits.\nSupplementary Appendix 1\nWell constructed and very helpful. A few comments:\nAnderson Plain - \"Black arrows\" noted in the caption are not visible.\nEast Bank Hills, Richarson Plateau, Travaillant Upland - Retrogressive thaw slumps can difficult to find,\nespecially for the inexperienced eye at the publication scale. Consider arrows to indicate, and possibly\nmention the resulting turbid lakes.\nReply: We have added arrows to support readers understanding of imagery patterns.\nReviewer #3 (Remarks to the Author):\nThis is a well-written paper with sound scientific information. I envision the methodologies established\nhere as being useful in Arctic regions for work that will help educate decision-makers on potential\nclimate-driven landscape changes. I can imagine future applications of this study helping to prioritize\nareas for future investigations by the Alaska Division of Geological and Geophysical Surveys.\nReply: Thank you. We appreciate the reviewer's comment.\nWhat are the noteworthy results?\n• This work provides a significant way to compare permafrost between diverse regions by looking at\nsimilarities in landform packages. I think it's a significant broadscale step in understanding landscape\nevolution and its relationship to climate change. As noted, it does have its challenges, and field data will\nimprove the process.\nReply: We appreciate the reviewer's comment.\nWill the work be of significance to the field and related fields? How does it compare to the established\nliterature? If the work is not original, please provide relevant references.\n• Yes. It will help us better understand the evolution of permafrost over time on regional scales. As we\nmake land management decisions, it's essential to have a good understanding of potential landscape\n18\nchanges, which can inform land management decisions and planning for mitigating possible impacts.\nReply: We appreciate the reviewer's comment.\nDoes the work support the conditions and claims, or is additional evidence needed?\n• As a first pass, yes. As the authors state, some conditions can't be accounted for with this analysis, and\nso the methodology could undoubtedly be improved upon, especially with more landforms for the input.\nReply: We appreciate the reviewer's comment.\nAre there any flaws in the data analysis, interpretation and conclusions? Do these prohibit publication or\nrequire revision?\n• It would be good to apply this methodology in other areas. The results are dependent on ecozone\nmapping. Consistency in scale and detail of that mapping when working between areas will impact results\nfor comparison. This work is undoubtedly a significant first step, but how does this work account for\nthose potential inconsistencies?\nReply: We appreciate the reviewer's comment. Base imagery and scale will affect the comparability of\nthe data with studies from other regions. However, we are unaware of regional-scale datasets that are\ncomparable because studies typically assess one or two feature types. We are hopeful that this work will\nspur others to map permafrost features more broadly, which would enable the expansion of the\napproach. There is the possibility to extend the mapping across Canada, or at least to areas of concern.\n• What was the reasoning for choosing the grid size? How do the results differ if you select a different\ngrid size?\nReply: The grid size was chosen because they represent quartiles of a previous effort to map mass\nwasting using 15x15 km grid cells across northwestern Canada (Kokelj et al 2017), and they were\ndeemed granular enough to provide fine-scale patterns, within a mapping framework that could be\ncompleted by trained mappers over a reasonable timeframe\n(Kokelj, S. V., Lantz, T. C., Tunnicliffe, J., Segal, R. & Lacelle, D. Climate-driven thaw of permafrost\npreserved glacial landscapes, northwestern Canada. Geology 45, 371–374 (2017).\nIs the methodology sound? Does the work meet the expected standards in your field?\n• The scientific methodology is sound\nReply: We appreciate the reviewer's comment.\nOther comments\n• Figure 4 is confusing. There is a line labelled \"rainfall\", but it's unclear what you are trying to convey\nwith that line. The same is true for \"percent water,\" \"air temperature,\" and so on. These are explained in\nthe text, but it's not clear in Figure 4a.\n• Figure 4b, there are numerous labels \"rock glacier,\" \"patterned fen,\" etc. It would be helpful if there\nwere lead lines. In its current state, these look like a bunch of words on an image, and it's unclear what\nyou are trying to convey.\nReply:\nFigure 4b. We have adjusted the caption to more clearly explain that the position of the words indicate\nlandform loading scores for the RDA.\nReviewer Reply Summary\nWe have provided detailed replies to all reviewer comments, most of which have helped to clarify\nthe Manuscript, resulting in minor revisions to the text. We have acknowledged the contributions\nof the reviews by Dr. Allard and Dr. D. K. Swanson, and of one anonymous Reviewer, that have\nimproved the Manuscript.\nThe title has been shortened to 15 words as per Dr. Alves request.\n\" Permafrost landsystems define regional variability in climate change effects on northern\nenvironments\"\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nComments on the revised manuscript \" Permafrost landsystems define regional variability in\nclimate change effects on northern environments\"\nFirst, I notice that the title was changed. The original title was \"Permafrost landsystems provide\nthe key to understanding climate change effects on terrain and ecosystems\". The paper has now a\nheavier focus on regional variability of both the permafrost landform patterns and, as a\nconsequence, of the climate change impacts on permafrost thawing. As mentioned in the text\n\"the emphasis is that systematic and integrated permafrost mapping provides a critical vehicle for\ngenerating new understanding of regional variability of permafrost characteristics\". I interpret\nthat such understanding of regional variability is currently inadequately represented by general\nmodels (mostly circumpolar in scale) based on spatial climate models and other datasets of\nterrain variables. I concur with the authors that permafrost landforms being good indicators of\npermafrost properties, and also the heritage of past climate and ecological changes, they must\nnecessarily be a strong component of the capability for predicting permafrost conditions across\nlandscapes and for predicting the reaction of permafrost to climate change. This is what make\nthis paper important for the research community and the public.\nThe authors now state clear objectives at the beginning of the paper. They have added a table\n(No 2) in the supplementary information showing the existing land classification framework of\nthe NWT, which helps very much to understand the context of application of their proposed\nlandsystem approach. I understand that they consider the level IV ecoregions of this framework\nas corresponding to the permafrost land systems (this is also stated in their rebuttal letter),\nalthough I sense that the text does not seem to be so unequivocal on the matter at some places.\nThe statistical analysis (RDA) is well explained and the addition of figure 6 showing the\nloadings of the landforms and of their assemblages across the level IV ecoregions improves very\nmuch the communication of the key messages of the paper.\nMy second reading of the Manuscript raised a question in my mind: I think the authors must\nexplain by what scientific process they identified the 28 landform types that are the basic mosaic\npieces of landform assemblages that reoccur in the permafrost landscape. They have acquired a\nunique knowledge of the variety of permafrost landforms in NWT and were finally able to\nclassify them into this set of 28. One or two sentences reporting on their experience would be\nappreciated. This is important because the variability of occurrence of permafrost landforms in\nthe region reflects the variety of permafrost conditions. These key landforms are also the basic\nelements of their RDA analysis.\nI am adding an annotated manuscript with a few commentaries (mostly suggestions for small\nchanges) for the authors to consider.\nMichel Allard\nResponse\nWe appreciate Dr. Allard's insightful comments on our paper and his positive assessment of the revised\nManuscript, in particular, his observation that permafrost landforms reflect permafrost properties and the\nheritage of past climate and ecological changes. As such, integrated landform mapping must be a\nfundamental component of predicting regional variation in permafrost conditions and climate change\nimpacts on landscapes, making the analyses and concepts important to the research community and the\npublic.\nWe appreciate that the Reviewer finds the objectives clear and that Figure 6 contributes positively to the\npaper's overall message.\nIn response to Dr. Allard'c comment, we state early in the paper that level IV ecoregions are conceptually\nsimilar to \"Landsystems\". Furthermore, we provide 2 additional sentences explaining how the 28\npermafrost landform types comprising the data analyzed in this paper were determined. We also point to\na published research paper on the development of this unique dataset, to Figures 1 & 2, and to\nSupplementary Table 1. These additions make clear that the 28 landforms in the inventory reflect the\ndiversity of permafrost conditions across the NWT (and most permafrost regions), as emphasized through\nedits to the last two paragraphs of the Introduction. We also appreciate Dr. Allard's minor comments in\nthe annotated Manuscript and have made the majority of the suggested small changes, as described\nbelow.\nReviewer Replies\nP3. L87-89. but it is obtainable with more field surveys and characterization of representative\nsites. This is necessary in particular for construction, infrastructure and land management.\nMaybe say \"difficult to predict at regional scales...\"\nResponse: Minor editorial suggestion was implemented.\nP4. L98. \"regional\" is confusing here because some levels of ecoregions are defined by climate\nexpressed by vegetation. Maybe say \"spatial\"\nResponse: Minor editorial suggestion was implemented.\nP4. L105-109. note here that many of the permafrost landforms have developped or are\nimprinted over various Quaternary landforms and surficial deposits. This is important because\npermafrost ground ice content is often associated with sediment composition and fabric.\nResponse: We appreciate the comment and implemented the editorial modification to\nemphasize the Reviewer's point.\nP4. L110-11. I suggest: are linked to the different permafrost characteristics across...\nResponse: We have addressed the comment through a minor editorial revision.\nP4. L112. here make ref. to supp. table 2 (level IV ecoregions)\nResponse: Reference to Supplementary Table 2 has been added.\nP4. L115. on continental scale, the gradient is mostly climatic\nResponse: We appreciate the comment and indicate we sample across a \"continental-scale\necoclimate gradient\"\nP5. 124. you should change paragraph here, you are now taking the reader to the RDA.\nResponse: We did not break the paragraph here as it doesn't seem appropriate.\nP5. L126. see comment above. But you must explain how, by what method, you came to the\nrecognition that these 28 permafrost landform types are in fact all of the basic combinations of\nsurficial deposits, ground ice contents, permafrost local landforms, organic cover and contents\nand vegetation that compose the various permafrost landscapes of NWT (your study area).\nResponse: We appreciate the comment. We have adjusted the text to mention the dataset\nused, reference a paper that describes the mapping methods in detail, and include reference\nSupplementary Table 1 (which lists all landforms and the permafrost conditions they indicate).\nWe also point to Figures 1 & 2, which are schematics and an associated narrative of how\nlandforms evolve and reflect surficial deposits, ground ice, soils, and vegetation combinations.\nWe also mention here the benefits and constraints of the method, which utilized Sentinel 2\nimagery with a 10m pixel resolution.\nP5. L135. you already mentionned in 14 level IV ecoregions above\nResponse: We appreciate the comment.\nP5. L140-145. True. Also an original vision using the landforms as key indicators of permafrost\nconditions. I concur 100%. However the best integrated level of permafrost conditions would be\nat the \"permafrost land type\" level, i.e. at a larger mapping scale. In fact, rather than mapping the\nland types, you have identified the 28 key landforms that are recurrent across the landscape.\nYour statistical analysis bears on the spatial occurrences of these key landforms in the sampling\ngrid allows a regional appraisal of the variability of permafrost conditions. This is OK. However\nmy feeling is that the reader has too much effort to do to understand this simple approach\nbecause of complex text and some \"overtheorizing\". Your choice of communication approach.\nResponse: We appreciate the comment and are comfortable with our communication\napproach. We don't feel it is over-theoretical.\nP6. L153-165. nice figure and excellent explanations in the caption.\nResponse: Thank you.\nP8. L194-213great concept. Some confusion remains. No 3 shows the organization of a partial\n(block diagram) permafrost land system (assemblage defines the concept of landsystem). Now,\ndoes No 4 show a mosaic of permafrost land forms or a mosaic of permafrost land systems\n(shades of blue-grey blocks) that compose an ecoregion level IV (here Tuktoyaktuk coastal\nplain) or are the grey-blue blocks landform types forming an assemblage within the Tuktoyaktuk\ncoasta plain which is the Land system). Sorry, I feel being not bright.\nResponse: We appreciate the need for clarity. The patterns in #4 show distinct landform\nassemblages and their spatial distribution across the level IV ecoregion (landsystem). We clarify\nthis through a minor modification to the figure and caption text.\nText on Figure 3.\n\"#4. Permafrost landsystems\nComplex mapping unit composed of permafrost landform assemblages describing patterns and\nvariation within the landsystem.\"\nP9. L236-238. here I think you shoud say what axes 1 and 2 correspond to (1-climate gradient\nexpressed by some variables, 2- topographic relief expressed mostly by mass wasting\nlandforms). This would help the reader get into the following text.\nResponse: We provide a sentence to briefly summarize what the site scores along the 2 axes\nreflect to help a reader follow the RDA results.\nP9L239. what is the scientific hypothesis that underlies this anticipation?\nP9L239. correspond to ?\nP9.L239-241. confusing here. are land systems of regional-local mapping scale or continental?\nor\ndo you mean that they are recurrent across the landscape at continental scale?\nP9.2239-241. land systems ?\nResponse: The Reviewer raises several minor queries regarding this topic sentence. We\nappreciate Dr. Allard's comments and have restructured the sentence with a minor revision to\naddress these points, focusing mainly on clarifying that the RDA plot, stratified by\necozone/ecoclimate zone, captures broadscale variation rather than \"landsystem\" scale\nvariation. We don't adjust language here to mention \"landsystems\". We do not state a\nhypothesis here; rather, we summarize the results.\n\" Permafrost landform assemblages capture a continental-scale gradient in permafrost conditions, and\nadditionally, reflect the significant variation in substrate, ground ice, and ground temperature conditions\nthat characterize heterogeneity of this broad ecoclimate transition indicated by the site scores along\nRDA axis 1 (Fig. 4a). \"\nP10.L280-282. ? how do you quantify suficial geology and make it a variable in RDA? there is\nno value for surficial geology in Supplementary Table 3. Is permafrost probability also a\nquantitative value like temperature and precipitation ?? does that probability derives from a\nmodel or field checks?\nResponse: In testing, surficial geology was included as a categorical variable (presence/absence\nof the dominant class and the total number of different units). Modeled permafrost probability\nwas extracted from Obu et al. (2019) and used as a continuous variable in testing.\nP10. L281. why not observed (sample sites) ground ice abundance? as drilled in figure 3.\nResponse: The explanatory variables in the RDA are restricted to broad-scale published\nproducts for which data can be extracted for the inventoried grid cells.\nP10. L282In Obu et al. permafrost probability in % is based on modelled surface temperatures.\nOne can doubt this variable adds more explabatory power to the RDA which already includes all\nkey climate parameters.\nResponse: We appreciate the comment, and we agree, which is why we did not include it in the\nfinal model.\nP10. L282-288. agree. the map of landsystems would provide a great sampling base for\nvalidating permafrost properties across the region through characterization of representative\nsites. The predictive value would be high with a minimum (optimal?) number of sampled field\nsites.\nResponse: We appreciate the comment, and the point is elaborated on in the discussion.\nP13. L363. Here, do you mean Holocene climate history and (or) recent climate evolution? the\nfollowing lines suggest it is mostly past climate changes.\nResponse: Minor editorial adjustment clarifies that we mean Holocene climate history.\nP14. L391-393. what level of ecological region region? do you mean High landform diversity\nwithin some ecotonal level-IV ecoregions?\nResponse: We appreciate the comment, and a minor editorial modification was implemented.\nP14. L396-398. This repeats what you said a few lines above\nResponse: We appreciate the comment – the minor editorial modification above distinguishes\nthe first sentence from the last in this paragraph.\nP15. finally landsystems and level IV ecoregions are the same? (you say it also in your rebuttal\nletter): same definition, same mapping scale? I feel that either you state clearly that the already\nmapped land regions level IV are the assemblages of landforms or you propose to change their\ndesignation for \"permafrost land systems.\"\nResponse: We appreciate the comment. We indicate early in the paper that Level IV ecoregions\nare conceptually similar to landsystems. We are utilizing this existing land classification\nframework to demonstrate the applicability of permafrost landsystem concepts, and also a\nscalable mapping approach for deriving permafrost landsystems in a data-driven empirical\nframework. We have expressed this earlier in the Manuscript – in the Introduction, and again in\nthe results.\nIt is beyond the scope of this paper to suggest that a particular jurisdiction adjust terminology.\nPg 16 F6 maybe this graph would be more intuitive to read if the low % values had a light tone\n(colour) and the high % values a darker tone (color)\nResponse: We used the viridis color scale, which was developed for data visualization and\nperforms well in monochrome and across various types of colorblindness. The light/yellow end\nof the spectrum is commonly used to represent higher values.\nFigure 6 caption ?? why is this here?\nResponse: We make a minor editorial adjustment to clarify that: \"The Ecoregion labels indicate\nLevel IV ecoregions Level II & IIIand the Level II & III ecoregions they nest within are in italics.\"\nP17. 468. not an easy sentence to read..\nmaybe say something like \"Permafrost landsystems provide a conceptual framework for\nintegrating known site level permafrost conditions into landform assemblages and mapping them\nat the regional scale\"\nResponse: The sentence was modified to improve clarity.\nP17 474-477\nlandsytems making the patterned organization within ecoregions (???)\nResponse: We have made a minor adjustment to improve clarity.\nP17 483-486. is this necessary for the purpose of the paper? I think no.\nResponse: We agree.\nP18 L500. geology and soil mapping\nResponse: Minor editorial modification was implemented.\nReviewer #2 (Remarks to the Author):\nComments on \"Permafrost landsystem approaches provide the key to understanding regional\nvariability in climate change effects on northern environments\", Steven V. Kokelj et al. Nov.\n2025 revision.\nby Dr. David K. Swanson (recently retired from U.S. National Park Service, Fairbanks, Alaska)\nI thank the authors for their conscientious responses to my and the other reviewer's comments.\nMy few comments on this revised draft of this paper relate mostly to the newly added cluster\nanalysis. I found this analysis to be very interesting and believe it adds a lot to the paper. This\nanalysis provides a statistically-based picture of the composition of the Landform Assemblages.\nBelow are a few specific comments.\nResponse: We appreciate the positive feedback from Dr. Swanson on our revised version of our\nManuscript. We provided responses to specific comments below.\nPage 5. The introductory section provides a brief overview of the methods that mentions only the\nRedundancy Analysis. I recognize that the methods overview here must be very short, but given\nthe success of the cluster-heatmap analysis, I think it deserves mention too.\nResponse: We have added a sentence in the short methods section at the end of the\nIntroduction referencing the clustered heatmap.\nAlso on p. 5, this would be a good place to note that the presence/absence data for the 28\nlandforms by grid cell is your sample of the Permafrost Landform Assemblages. In other words,\nyour list of the landforms present in a cell is the Permafrost Landform Assemblage for that\nlocation (given the limitations that the sampling method has, as all of them do). This would help\nthe reader understand how the RDA sheds light on the properties of the Assemblages, because\nthe input data to the RDA is a direct sample of the Assemblages.\nResponse: We have added a few words to help clarify this point.\nPage 12, lines 4-5. The sentence here should read \"Figure 6 is a clustered heatmap that explores\nthe natural groupings of permafrost landforms INTO assemblages...\" Figure 6 is the place where\nwe get to see which landforms actually group together into assemblages. This info is also\navailable in part from Figure 4, but here the reader must infer the assemblages based on\nproximity between labels on the diagram, and also their distribution is based only on how they\nrelate to environmental variables (...with only 16.6% + 3.1% = 19.7% of the variability\nportrayed).\nResponse: Thank you for the comment. We have adjusted the caption text accordingly.\nPage 13, 3rd line from the bottom \"more gently rising richness curve for the Richardson\nPlateau\". At the scale of Figure 5 at least, the curves for RP and EBH seem to nearly overlap.\nResponse: We appreciate the comment and emphasize it to be a \"slightly\" gentler rise. We feel\nits worth pointing out.\nFigure 6 is great. I would experiment with the color scheme to show better contrast for the\nlandforms that occur at low frequency.\nResponse: We appreciate the comment. We have kept the color scheme for reasons addressed\nin a comment by Dr. Allard, and also because the resolving variation of landforms at high\nfrequency is more important for understanding overall sensitivity of the landsystem. However,\nwe may choose to explore different ways of representing landforms that are \"environmentally\nimportant\" but spatially infrequent in future publications.\nPage 26, Methods - Statistical approach. The RDA methods are described in great detail, but\ndocumentation for the cluster analysis is very brief. The R package \"pheatmap\" is cited as the\nmethod used for the cluster analysis, but this package can be used to plot heat maps made by a\nvariety of clustering methods. Based on the results (Figure 6) it appears that you collapsed the\ndata into a matrix of Level IV Ecoregions (rows) and landforms (columns), with matrix values\nbeing percents of the sample cells for each Ecoregion that contained that landform. I could be\nwrong about this, so please describe the initial matrix that was subjected to clustering, how the\ndistances were calculated, and what cluster method was used. The defaults in pheatmap are\nEuclidean distance and complete linkage clustering, which is a reasonable choice but not\nnecessarily optimal. You have 3 major clusters, and one of the clusters is quite large with\nchaining issues. I'd give Ward's method a try and see if it gives better results, if not here then in a\nfuture paper. Also, a more fundamental distance measure for the landform clustering might be\nsimply based on the count of 7.5x7.5 km grids where each pair of landforms was both observed.\nI look forward to reading about this in future publications!\nResponse: We greatly appreciate the comment. We have provided additional information on\nthe structure of the input matrix in the Methods section. Also we clarify that in \"pheatmap\" we\nuse Euclidean distance and complete linkage clustering. We experimented with other methods,\nincluding Ward's, which provided largely similar results with some minor differences. We were\nunable to find indications that either method was more appropriate for the current data and\nwe opted for the complete linkage method. We will consider this in more detail exploring\npermafrost landsystem clustering in the future.\nAlso in the Methods, you should probably also say which method you used with r function\n\"specaccum\". Presumably it was the default (\"exact\"), but it's best to specify this.\nResponse: We appreciate the comment and have updated the methods to clarify.\nReviewer #3 (Remarks to the Author):\nI believe the authors did a good job of addressing reviewer comments. The clarifications made\ngreatly improve the Manuscript and I believe this provides valuable information to assist users at\nbetter understanding permafrost conditions at a regional scale. I have not additional comments\nprior to publication.\nResponse: We appreciate the comment"}, {"round": 2, "reviewer_comments": {"reviewer_1": "I feel a bit sorry for having suggested so many changes to the authors and maybe for \"over debating\" in this review.The authors have generously accepted to consider the suggested improvements. The paper is an important contribution to permafrost and environmental science. Particularly, in the current research context on permafrost science, impacts of climate change and useful assessments, this paper demonstrates the fundamental importance of landforms (geomorphology) as key indicators of permafrost properties and dynamic evolution. Similarly inspired work should be expanded across the Subarctic and Arctic regions.\nCongratulations!\nMichel Allard", "reviewer_2": "Comments on \" Permafrost landsystems define regional variability in climate change effects on northern environments\",\nSteven V. Kokelj et al. 2nd revision (Jan 2026).\nI thank the authors for their conscientious responses to my and the other reviewer's comments. The second revision properly addresses the comments that I made on the first revision, and I have no further comments. This paper is an important contribution permafrost science and geomorphology.\nDavid Swanson"}, "author_response": "Reviewer Reply Summary\nWe have provided detailed replies to all reviewer comments, most of which have helped to clarify\nthe Manuscript, resulting in minor revisions to the text. We have acknowledged the contributions\nof the reviews by Dr. Allard and Dr. D. K. Swanson, and of one anonymous Reviewer, that have\nimproved the Manuscript.\nThe title has been shortened to 15 words as per Dr. Alves request.\n\" Permafrost landsystems define regional variability in climate change effects on northern\nenvironments\"\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nComments on the revised manuscript \" Permafrost landsystems define regional variability in\nclimate change effects on northern environments\"\nFirst, I notice that the title was changed. The original title was \"Permafrost landsystems provide\nthe key to understanding climate change effects on terrain and ecosystems\". The paper has now a\nheavier focus on regional variability of both the permafrost landform patterns and, as a\nconsequence, of the climate change impacts on permafrost thawing. As mentioned in the text\n\"the emphasis is that systematic and integrated permafrost mapping provides a critical vehicle for\ngenerating new understanding of regional variability of permafrost characteristics\". I interpret\nthat such understanding of regional variability is currently inadequately represented by general\nmodels (mostly circumpolar in scale) based on spatial climate models and other datasets of\nterrain variables. I concur with the authors that permafrost landforms being good indicators of\npermafrost properties, and also the heritage of past climate and ecological changes, they must\nnecessarily be a strong component of the capability for predicting permafrost conditions across\nlandscapes and for predicting the reaction of permafrost to climate change. This is what make\nthis paper important for the research community and the public.\nThe authors now state clear objectives at the beginning of the paper. They have added a table\n(No 2) in the supplementary information showing the existing land classification framework of\nthe NWT, which helps very much to understand the context of application of their proposed\nlandsystem approach. I understand that they consider the level IV ecoregions of this framework\nas corresponding to the permafrost land systems (this is also stated in their rebuttal letter),\nalthough I sense that the text does not seem to be so unequivocal on the matter at some places.\nThe statistical analysis (RDA) is well explained and the addition of figure 6 showing the\nloadings of the landforms and of their assemblages across the level IV ecoregions improves very\nmuch the communication of the key messages of the paper.\nMy second reading of the Manuscript raised a question in my mind: I think the authors must\nexplain by what scientific process they identified the 28 landform types that are the basic mosaic\npieces of landform assemblages that reoccur in the permafrost landscape. They have acquired a\nunique knowledge of the variety of permafrost landforms in NWT and were finally able to\nclassify them into this set of 28. One or two sentences reporting on their experience would be\nappreciated. This is important because the variability of occurrence of permafrost landforms in\nthe region reflects the variety of permafrost conditions. These key landforms are also the basic\nelements of their RDA analysis.\nI am adding an annotated manuscript with a few commentaries (mostly suggestions for small\nchanges) for the authors to consider.\nMichel Allard\nResponse\nWe appreciate Dr. Allard's insightful comments on our paper and his positive assessment of the revised\nManuscript, in particular, his observation that permafrost landforms reflect permafrost properties and the\nheritage of past climate and ecological changes. As such, integrated landform mapping must be a\nfundamental component of predicting regional variation in permafrost conditions and climate change\nimpacts on landscapes, making the analyses and concepts important to the research community and the\npublic.\nWe appreciate that the Reviewer finds the objectives clear and that Figure 6 contributes positively to the\npaper's overall message.\nIn response to Dr. Allard'c comment, we state early in the paper that level IV ecoregions are conceptually\nsimilar to \"Landsystems\". Furthermore, we provide 2 additional sentences explaining how the 28\npermafrost landform types comprising the data analyzed in this paper were determined. We also point to\na published research paper on the development of this unique dataset, to Figures 1 & 2, and to\nSupplementary Table 1. These additions make clear that the 28 landforms in the inventory reflect the\ndiversity of permafrost conditions across the NWT (and most permafrost regions), as emphasized through\nedits to the last two paragraphs of the Introduction. We also appreciate Dr. Allard's minor comments in\nthe annotated Manuscript and have made the majority of the suggested small changes, as described\nbelow.\nReviewer Replies\nP3. L87-89. but it is obtainable with more field surveys and characterization of representative\nsites. This is necessary in particular for construction, infrastructure and land management.\nMaybe say \"difficult to predict at regional scales...\"\nResponse: Minor editorial suggestion was implemented.\nP4. L98. \"regional\" is confusing here because some levels of ecoregions are defined by climate\nexpressed by vegetation. Maybe say \"spatial\"\nResponse: Minor editorial suggestion was implemented.\nP4. L105-109. note here that many of the permafrost landforms have developped or are\nimprinted over various Quaternary landforms and surficial deposits. This is important because\npermafrost ground ice content is often associated with sediment composition and fabric.\nResponse: We appreciate the comment and implemented the editorial modification to\nemphasize the Reviewer's point.\nP4. L110-11. I suggest: are linked to the different permafrost characteristics across...\nResponse: We have addressed the comment through a minor editorial revision.\nP4. L112. here make ref. to supp. table 2 (level IV ecoregions)\nResponse: Reference to Supplementary Table 2 has been added.\nP4. L115. on continental scale, the gradient is mostly climatic\nResponse: We appreciate the comment and indicate we sample across a \"continental-scale\necoclimate gradient\"\nP5. 124. you should change paragraph here, you are now taking the reader to the RDA.\nResponse: We did not break the paragraph here as it doesn't seem appropriate.\nP5. L126. see comment above. But you must explain how, by what method, you came to the\nrecognition that these 28 permafrost landform types are in fact all of the basic combinations of\nsurficial deposits, ground ice contents, permafrost local landforms, organic cover and contents\nand vegetation that compose the various permafrost landscapes of NWT (your study area).\nResponse: We appreciate the comment. We have adjusted the text to mention the dataset\nused, reference a paper that describes the mapping methods in detail, and include reference\nSupplementary Table 1 (which lists all landforms and the permafrost conditions they indicate).\nWe also point to Figures 1 & 2, which are schematics and an associated narrative of how\nlandforms evolve and reflect surficial deposits, ground ice, soils, and vegetation combinations.\nWe also mention here the benefits and constraints of the method, which utilized Sentinel 2\nimagery with a 10m pixel resolution.\nP5. L135. you already mentionned in 14 level IV ecoregions above\nResponse: We appreciate the comment.\nP5. L140-145. True. Also an original vision using the landforms as key indicators of permafrost\nconditions. I concur 100%. However the best integrated level of permafrost conditions would be\nat the \"permafrost land type\" level, i.e. at a larger mapping scale. In fact, rather than mapping the\nland types, you have identified the 28 key landforms that are recurrent across the landscape.\nYour statistical analysis bears on the spatial occurrences of these key landforms in the sampling\ngrid allows a regional appraisal of the variability of permafrost conditions. This is OK. However\nmy feeling is that the reader has too much effort to do to understand this simple approach\nbecause of complex text and some \"overtheorizing\". Your choice of communication approach.\nResponse: We appreciate the comment and are comfortable with our communication\napproach. We don't feel it is over-theoretical.\nP6. L153-165. nice figure and excellent explanations in the caption.\nResponse: Thank you.\nP8. L194-213great concept. Some confusion remains. No 3 shows the organization of a partial\n(block diagram) permafrost land system (assemblage defines the concept of landsystem). Now,\ndoes No 4 show a mosaic of permafrost land forms or a mosaic of permafrost land systems\n(shades of blue-grey blocks) that compose an ecoregion level IV (here Tuktoyaktuk coastal\nplain) or are the grey-blue blocks landform types forming an assemblage within the Tuktoyaktuk\ncoasta plain which is the Land system). Sorry, I feel being not bright.\nResponse: We appreciate the need for clarity. The patterns in #4 show distinct landform\nassemblages and their spatial distribution across the level IV ecoregion (landsystem). We clarify\nthis through a minor modification to the figure and caption text.\nText on Figure 3.\n\"#4. Permafrost landsystems\nComplex mapping unit composed of permafrost landform assemblages describing patterns and\nvariation within the landsystem.\"\nP9. L236-238. here I think you shoud say what axes 1 and 2 correspond to (1-climate gradient\nexpressed by some variables, 2- topographic relief expressed mostly by mass wasting\nlandforms). This would help the reader get into the following text.\nResponse: We provide a sentence to briefly summarize what the site scores along the 2 axes\nreflect to help a reader follow the RDA results.\nP9L239. what is the scientific hypothesis that underlies this anticipation?\nP9L239. correspond to ?\nP9.L239-241. confusing here. are land systems of regional-local mapping scale or continental?\nor\ndo you mean that they are recurrent across the landscape at continental scale?\nP9.2239-241. land systems ?\nResponse: The Reviewer raises several minor queries regarding this topic sentence. We\nappreciate Dr. Allard's comments and have restructured the sentence with a minor revision to\naddress these points, focusing mainly on clarifying that the RDA plot, stratified by\necozone/ecoclimate zone, captures broadscale variation rather than \"landsystem\" scale\nvariation. We don't adjust language here to mention \"landsystems\". We do not state a\nhypothesis here; rather, we summarize the results.\n\" Permafrost landform assemblages capture a continental-scale gradient in permafrost conditions, and\nadditionally, reflect the significant variation in substrate, ground ice, and ground temperature conditions\nthat characterize heterogeneity of this broad ecoclimate transition indicated by the site scores along\nRDA axis 1 (Fig. 4a). \"\nP10.L280-282. ? how do you quantify suficial geology and make it a variable in RDA? there is\nno value for surficial geology in Supplementary Table 3. Is permafrost probability also a\nquantitative value like temperature and precipitation ?? does that probability derives from a\nmodel or field checks?\nResponse: In testing, surficial geology was included as a categorical variable (presence/absence\nof the dominant class and the total number of different units). Modeled permafrost probability\nwas extracted from Obu et al. (2019) and used as a continuous variable in testing.\nP10. L281. why not observed (sample sites) ground ice abundance? as drilled in figure 3.\nResponse: The explanatory variables in the RDA are restricted to broad-scale published\nproducts for which data can be extracted for the inventoried grid cells.\nP10. L282In Obu et al. permafrost probability in % is based on modelled surface temperatures.\nOne can doubt this variable adds more explabatory power to the RDA which already includes all\nkey climate parameters.\nResponse: We appreciate the comment, and we agree, which is why we did not include it in the\nfinal model.\nP10. L282-288. agree. the map of landsystems would provide a great sampling base for\nvalidating permafrost properties across the region through characterization of representative\nsites. The predictive value would be high with a minimum (optimal?) number of sampled field\nsites.\nResponse: We appreciate the comment, and the point is elaborated on in the discussion.\nP13. L363. Here, do you mean Holocene climate history and (or) recent climate evolution? the\nfollowing lines suggest it is mostly past climate changes.\nResponse: Minor editorial adjustment clarifies that we mean Holocene climate history.\nP14. L391-393. what level of ecological region region? do you mean High landform diversity\nwithin some ecotonal level-IV ecoregions?\nResponse: We appreciate the comment, and a minor editorial modification was implemented.\nP14. L396-398. This repeats what you said a few lines above\nResponse: We appreciate the comment – the minor editorial modification above distinguishes\nthe first sentence from the last in this paragraph.\nP15. finally land level IV ecoregions are the same? (you say it also in your rebuttal\nletter): same definition, same mapping scale? I feel that either you state clearly that the already\nmapped land regions level IV are the assemblages of landforms or you propose to change their\ndesignation for \"permafrost land systems.\"\nResponse: We appreciate the comment. We indicate early in the paper that Level IV ecoregions\nare conceptually similar to landsystems. We are utilizing this existing land classification\nframework to demonstrate the applicability of permafrost landsystem concepts, and also a\nscalable mapping approach for deriving permafrost landsystems in a data-driven empirical\nframework. We have expressed this earlier in the Manuscript – in the Introduction, and again in\nthe results.\nIt is beyond the scope of this paper to suggest that a particular jurisdiction adjust terminology.\nPg 16 F6 maybe this graph would be more intuitive to read if the low % values had a light tone\n(colour) and the high % values a darker tone (color)\nResponse: We used the viridis color scale, which was developed for data visualization and\nperforms well in monochrome and across various types of colorblindness. The light/yellow end\nof the spectrum is commonly used to represent higher values.\nFigure 6 caption ?? why is this here?\nResponse: We make a minor editorial adjustment to clarify that: \"The Ecoregion labels indicate\nLevel IV ecoregions Level II & IIIand the Level II & III ecoregions they nest within are in italics.\"\nP17. 468. not an easy sentence to read..\nmaybe say something like \"Permafrost landsystems provide a conceptual framework for\nintegrating known site level permafrost conditions into landform assemblages and mapping them\nat the regional scale\"\nResponse: The sentence was modified to improve clarity.\nP17 474-477\nlandsytems making the patterned organization within ecoregions (???)\nResponse: We have made a minor adjustment to improve clarity.\nP17 483-486. is this necessary for the purpose of the paper? I think no.\nResponse: We agree.\nP18 L500. geology and soil mapping\nResponse: Minor editorial modification was implemented."}]

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