Cumulative Environmental Impacts in the Gwich’in Cultural Landscape

: Environmental changes are impacting northern environments and human communities. Cumulative impact assessments are vital to understanding the combined e ﬀ ects of regional industrial developments and natural disturbances that a ﬀ ect humans and ecosystems. A gap in cumulative impacts literature includes methods to evaluate impacts in cultural landscapes. In this study, we utilized spatial overlay analysis to assess cumulative environmental impacts in the cultural landscape of northern Canada’s Gwich’in Settlement Region. In three analyses, we quantiﬁed and mapped: (1) Cultural feature density, (2) cumulative environmental disturbance, and (3) potential overlap between disturbances and cultural features. Our ﬁrst analysis depicts the extent and pattern of cultural relationships with regional landscapes and illustrates the Gwich’in cultural landscape, with widespread harvesting trails, named places, traditional use areas, and archaeological sites found in highest densities near important waterways. Our second analysis suggests that spatial overlay can track multiple disturbances, illustrating di ﬀ use, lower intensity cumulative environmental impacts. The ﬁnal analysis shows that overlaying disturbance and cultural feature data provides a novel way to investigate cumulative impacts in a cultural landscape, indicating relatively low levels of potential overlap between Gwich’in cultural features and disturbances. These methods provide one way to investigate cumulative impacts, relevant for well- documented cultural landscapes.


Introduction
The combined effects of intensified natural and anthropogenic disturbances are altering the structure and function of global ecosystems [1,2], with the potential to significantly impact the land-based livelihoods of many Indigenous groups [3,4]. In the Arctic, where the climate is warming more rapidly than anywhere else on Earth [5] and industrial development is expanding [6,7], changes to local livelihoods may be particularly severe [8,9]. Alongside the impacts of climate change to permafrost, vegetation, and hydrological conditions [10][11][12], northern regions are experiencing development projects like oil and gas exploration and extraction, mining, and road construction [13][14][15].
Incremental, compounding disturbances that can cause landscape and ecosystem change are often defined as cumulative impacts [16,17]. Over the past few decades, considerable effort has been devoted to assessing the cumulative impacts of natural and anthropogenic disturbances through studies examining existing or potential impacts of a specific development project [18,19], or the broader scale impacts of multiple stressors on regional ecosystems [1,20]. Accounting for cumulative environmental impacts is important because they can severely impair water quality, terrain stability, and animal habitat, and interact in unexpected ways [21][22][23][24].

Materials and Methods
This research explored the potential of regional scale spatial overlay analysis to assess the cumulative impacts of environmental disturbances in the Gwich'in Settlement Region. To accomplish this, we conducted three spatial overlay analyses using ArcGIS software (version 10.3.1). We quantified and mapped: a) The density of four categories of cultural features, b) the magnitude of cumulative impacts from seven types of environmental disturbances, and c) the potential overlap between cultural features and environmental disturbances. Cultural features and cumulative impacts were quantified by dividing the GSR into a grid of 3810 planning units (PUs) (Figure 2). The majority of PUs were 25km 2 in size, but a number of smaller PUs were located along the edges of the study area. We chose the PU size of 25km 2 to be consistent with past analyses [20], and to display our data at a scale conducive to visualization.
Community consultation was also key to this project. This consultation included collaboration with regional organizations, community meetings to share results, and interviews with four regional cultural heritage experts (a mix of Gwich'in and non-Gwich'in professionals) who provided key

Materials and Methods
This research explored the potential of regional scale spatial overlay analysis to assess the cumulative impacts of environmental disturbances in the Gwich'in Settlement Region. To accomplish this, we conducted three spatial overlay analyses using ArcGIS software (version 10.3.1). We quantified and mapped: (a) The density of four categories of cultural features, (b) the magnitude of cumulative impacts from seven types of environmental disturbances, and (c) the potential overlap between cultural features and environmental disturbances. Cultural features and cumulative impacts were quantified by dividing the GSR into a grid of 3810 planning units (PUs) (Figure 2). The majority of PUs were 25 km 2 in size, but a number of smaller PUs were located along the edges of the study area. We chose the PU size of 25 km 2 to be consistent with past analyses [20], and to display our data at a scale conducive to visualization.
Community consultation was also key to this project. This consultation included collaboration with regional organizations, community meetings to share results, and interviews with four regional cultural heritage experts (a mix of Gwich'in and non-Gwich'in professionals) who provided key guidance about this project, such as the appropriate representation of cultural features [42]. Interview participants provided their informed consent before each interview, and the research was conducted with ethical approval from the University of Victoria's Human Research Ethics Board (Protocol Number     Gwich'in Settlement Region used to assess documented cultural feature density, cumulative weighted environmental disturbance, and the potential overlap between environmental disturbances and cultural features.

Documented Cultural Feature Density
To quantify the density and distribution of cultural features in the GSR, we created an index of cultural feature intensity (CFI) (Figure 3). This index is based on the assumption that the density of tangible and intangible cultural features can be used as an indicator of the intensity of cultural use in a given landscape unit. Data on four categories of cultural features (historic harvesting trails, named places, traditional land use areas, and archaeological sites) were obtained from several sources (Table  1).   Gwich'in Settlement Region used to assess documented cultural feature density, cumulative weighted environmental disturbance, and the potential overlap between environmental disturbances and cultural features.

Documented Cultural Feature Density
To quantify the density and distribution of cultural features in the GSR, we created an index of cultural feature intensity (CFI) (Figure 3). This index is based on the assumption that the density of tangible and intangible cultural features can be used as an indicator of the intensity of cultural use in a given landscape unit. Data on four categories of cultural features (historic harvesting trails, named places, traditional land use areas, and archaeological sites) were obtained from several sources ( Table 1).   To ensure that point, polygon, and polyline data had a similar influence on the CFI, we used the procedures outlined below. Each cultural feature mapped as a point in a PU received a score of 1. The cultural feature intensity of polygon data was calculated by dividing the total area of polygon within each PU by the area of the PU that the polygon was located within. The cultural feature intensity for polyline data was determined by dividing the total length of polylines within each PU by the length of one side of a PU (5000 m). Despite a lack of recorded cultural features within some PUs, we assumed that all PUs had a baseline of cultural activity, evidenced by oral and written history that describes the importance of the entire landscape for Gwich'in cultural use [28,37,48]. To reflect this baseline of cultural activity, we set the minimum value of the CFI in each PU to 1 by adding 1 to the CFI in each PU. We then scaled the CFI values from 0-100, to have the same scale as the environmental disturbance scores. To determine the total CFI in each PU, the scores from each category of cultural feature were summed within each PU ( Figure 3).
To visualize the distribution and density of cultural features, we mapped the CFI in each PU of the GSR grid. We then grouped PUs into five classes (light, moderate, high, very high, and extreme) based on their CFI, using the ArcGIS geometric interval classification [49] (see Figure 4). We used the geometric interval classification because it is designed to represent continuous data [49]. We named the lowest CFI class of PUs "light" instead of "low" or "very low" because we feel that this terminology better represents the baseline of cultural activity in the GSR.

Cumulative Weighted Environmental Disturbance
The cumulative impact of disturbances on the terrestrial environment in the GSR was estimated by compiling spatial data on seven types of environmental disturbance. Most of these disturbances are the direct result of anthropogenic activity, but one disturbance (retrogressive thaw slumps) is a form of permafrost degradation that is intensifying in response to climate change [50,51].
Environmental disturbance data were acquired from various sources ( Table 2). The spatial distribution of these disturbances is displayed in Figure S1. Drilling mud sumps (pits holding buried drilling fluids and waste from mining exploration) were represented as point data. The area of sumps in each PU was estimated by multiplying the number of sumps by the average area of sumps (2.2 ha) estimated using aerial imagery of the Inuvialuit Settlement Region [20,52]. Polyline data on seismic cut lines (right of ways cut to conduct seismic testing for oil and gas exploration) were buffered to create polygons extending 3.5 m on each side of the line, based on the average width of seismic lines in the Inuvialuit Settlement Region [20,52]. Polyline data for the Dempster Highway right of way were buffered 10m on each side to represent the average width of the highway. Community infrastructure in Aklavik, Fort McPherson, Inuvik, and Tsiigehtchic was represented by polygon data. Gravel quarries were represented as polygon data in the Northwest Territories, and point data in Yukon Territory. The spatial extent of Yukon quarries was estimated using the average size of quarries in the Northwest Territories (7.2 ha). Data on the right of way for the Mackenzie Valley Fibre Link (MVFL) (a fiber-optic cable running through the Mackenzie Valley) were buffered by 3 m per side to reflect the area of land cleared [53,54]. The area of retrogressive thaw slumps per PU was estimated using a map of slump density across northwestern Canada [50]. In this dataset, the density of slumps is represented categorically (low (1-5), medium (6)(7)(8)(9)(10)(11)(12)(13)(14), or high (≥15)) across a grid of 225 km 2 cells [55]. Following Tyson et al. (2016) [20], we assumed that low density cells contained 3 slumps, medium density contained 10, and high density contained 20. We estimated the average area of slumps within each 225 km 2 cell by multiplying the average number of slumps per cell by the average slump area (3.02 ha) reported by   [55]. We then intersected the 225 km 2 cells with our grid to calculate the average area of slump within each 25 km 2 PU.     [14,76] To quantify the impacts of these disturbances, we calculated a disturbance score for each PU that was based on disturbance weights that integrated estimates of disturbance severity, recovery, and area (Table 2). Although there is no unilateral approach to weighted analyses, they can be utilized in cumulative impacts research to account for differing effects and magnitudes of disturbance [20,77]. In our analysis, we used the weighting approach outlined by Tyson et al. (2016) [20], where disturbance weights were obtained by multiplying a severity score by a recovery score for each disturbance type. Severity scores characterize a disturbance's impact on vegetation structure, soils, and ground temperature, and range from 1 (minimal ecological alteration) to 10 (complete land transformation). Ecosystem recovery scores range from 0 to 1, and denote the length of time a disturbance is likely to persist on the land. Disturbances persisting for more than 50 years received a score of 1 (i.e., community infrastructure), whereas disturbances that were likely to experience significant recovery of vegetation structure and ecological processes within 50 years received a score ranging from 0.1 to 0.9 (i.e., seismic lines) [20]. Disturbance weights range from 1.2 (lower severity and faster recovery, i.e., seismic lines) to 10 (higher severity and limited recovery, i.e., community infrastructure). With the exception of the fiber-optic cable and gravel quarries, we used the weights created for the Inuvialuit Settlement Region by Tyson et al. (2016) [20].
Following Tyson et al. (2016) [20], we used the disturbance weights to calculate and map a disturbance score in each PU. This was achieved by summing the weighted areas of each disturbance (the percentage of PU affected by each disturbance, multiplied by the disturbance weight) using the following formula: Disturbance Area Planning Unit Area * 100 * Disturbance Weight The resultant disturbance scores were then scaled between 0 and 100, so they had the same scale as the cultural feature intensity. After these scaled disturbance scores were calculated in each PU, we used the ArcGIS geometric interval classification to group PUs into six ranges (none recorded, low, moderately low, moderate, high, and very high) based on their cumulative weighted disturbance density (see Figure 5). We labeled the PUs with lower disturbance densities as "low" and "moderately low" instead of "very low" and "low" to avoid mislabeling PUs which might contain disturbances not included in our analysis that are causing ecological impacts.

Potential Overlap between Cultural Features and Disturbances
To quantify and map areas of overlap and potential impact between environmental disturbances and cultural features, we multiplied the scaled cultural feature intensity by the scaled disturbance score in each PU. Throughout this paper, we refer to these values as overlap scores. Overlap scores are a relative measure of overlap between disturbances and culturally significant landscape features, and can be used to identify areas where disturbances may alter, damage, or destroy ecological and cultural features. Overlap scores were classified into six categories (baseline-none recorded, low, moderately low, moderate, high, and very high) using the ArcGIS geometric interval classification scheme (see Figure 6). We chose to label these categories the same as the disturbance density categories, both for consistency and to avoid mislabeling PUs that may contain cultural or ecological impacts not included in our analysis.  Following mapping, we assessed the relative influence of disturbance types and cultural feature categories on overlap scores. To do this, we grouped our data into the five overlap score ranges that depicted potential overlap between cultural features and disturbances, and calculated the total disturbance score and CFI from all of the PUs in each range. To understand the influence of each disturbance type or cultural feature category on the overlap score in each range, we calculated the percentage contribution of each disturbance type and cultural feature category to the total disturbance score or CFI in each overlap score range.

Documented Cultural Feature Density
The intensity of cultural features displayed in Figure 4 shows that the Gwich'in Settlement Region is highly culturally salient. The vast majority of PUs (88%) contained cultural features (Table 3). Twenty-eight percent of all PUs contained one category of cultural feature, while the majority (60%) contained overlap between two to four cultural feature categories (Table 3).  (Table 4). These PUs were located along rivers like the Peel (Teetł'it Gwinjik) and Mackenzie (Nagwichoonjik), and throughout the Mackenzie River Delta (Ehdiitat) (Figure 4). Planning units with CFI values in the moderate and high categories made up 58% of all PUs, and had average CFIs of 1.48 and 4.21 per PU ( Table 4). Most of these PUs were located adjacent to water bodies and throughout the Great Bear Lake Plain and Fort McPherson Plain ecoregions ( Figure 4). Twenty-one percent of all PUs were grouped in the light CFI class and had an average CFI of 0.47 per PU ( Table 4). The highest concentrations of these PUs were located in the Mackenzie Mountain and southern Peel Plateau ecoregions, with smaller concentrations found throughout the Great Bear Lake Plain and Fort McPherson Plain ecoregions and around the edges of the GSR (Figure 4).

Cumulative Weighted Environmental Disturbance
Our analysis shows that relatively low levels of environmental disturbance are present across the GSR ( Figure 5). Approximately half (55%) of the PUs contained recorded disturbances, but the majority of these contained one disturbance type (76% of disturbed PUs) ( Table 5). A smaller number of PUs contained two or more disturbance types, and no PUs included all seven of the disturbance types that we examined (Table 5). PUs with no recorded disturbances were common in most ecoregions ( Figure 5), and the low and moderately low disturbance score ranges contained the majority of disturbed PUs (63%) ( Table 6). PUs with low or moderately low disturbance levels had average disturbance scores of 0.004 and 0.05 per PU (Table 6). These PUs tended to contain small areas of seismic lines and thaw slumps, and were found in all of the ecoregions in the study area ( Figure 5). Moderately disturbed PUs comprised 33% of disturbed PUs and had an average disturbance score of 0.21 per PU (Table 6). These PUs contained clusters of overlap between larger seismic lines and thaw slumps with other disturbance types, and were located primarily in the Richardson Mountains, Peel Plateau, and Eagle Plains ecoregions ( Figure 5). Seventy PUs had high disturbance scores and were clustered close to the Dempster Highway, where gravel quarries, thaw slumps, and seismic lines frequently overlapped ( Figure 5). These PUs had an average disturbance score of 2.35 (Table 6), and comprised 3% of disturbed PUs. Ten PUs with very high disturbance levels were located near Fort McPherson, Inuvik, and Tsiigehtchic, where community infrastructure frequently overlapped with the Dempster Highway ( Figure 5). These PUs had average disturbance scores of 32.78, and were present in 0.5% of PUs containing recorded disturbances (Table 6). For reference, a very high disturbance score is roughly equivalent to the impacts which would result from half of the PU being covered by a thaw slump. A moderate disturbance score is roughly equivalent to the impacts stemming from 1/70 of the PU being covered in seismic lines.

Potential Overlap Between Cultural Features and Disturbances
The map shown in Figure 6 indicates that there is a moderate amount of potential overlap between environmental disturbances and cultural features in the GSR. Overall, 54% of PUs contained both disturbances and cultural features (Table 7). Of these PUs, most had low to moderate overlap scores (98%), and only a few had high or very high scores (2%) ( Table 7). PUs with potential overlap between disturbances and cultural features were located throughout the GSR, with moderate to very high overlap score ranges primarily located near the Peel River (Teetł'it Gwinjik), Dempster Highway, Fort McPherson, Inuvik, and Tsiigehtchic ( Figure 6). Decomposing overlap scores shows that some disturbances and cultural features had a larger impact on overlap scores than others. Thaw slumps and seismic lines were responsible for over 80% of the impact in the low and moderately low overlap score ranges, the Dempster highway was responsible for 46% of the impact in the moderate range, and community infrastructure caused 49% and 91% of the impact in the high and very high overlap score ranges (Table 8). Historic harvesting trails accounted for over 60% of the cultural feature intensity in each overlap score range (Table 9). Table 8. Contribution of environmental disturbance types to the total disturbance score across the five overlap score ranges. Values represent the percentage of the total disturbance score in each overlap score range attributed to each disturbance type.  Table 9. Contribution of cultural feature categories to the total cultural feature intensity across the five overlap score ranges. Values represent the percentage of the total cultural feature intensity in each overlap score range attributed to each cultural feature category. Some of this percentage is attributed to the planning units that did not contain documented cultural features, but that were given a cultural feature intensity value of "1" due to the baseline of cultural activity ascribed to each planning unit.

Discussion
Cultural landscapes have been described as areas defined by intricate relationships between humans and the land, including longstanding land use and spiritual connections [78][79][80]. Our analysis shows that the Gwich'in Settlement Region represents a cultural landscape characterized by features linked to oral traditions and multigenerational land use [28]. In this region, relationships between people and place are essential aspects of Gwich'in well-being, livelihood, and identity that are embedded in the cultural features that define this landscape [38,81]. We found that we could discern broad-scale patterns that characterize cultural landscapes by overlaying cultural feature data. For example, Figure 4 shows that the most intensive cultural use in the GSR occurs near waterways like the Peel River (Teetł'it Gwinjik), Mackenzie River (Nagwichoonjik), the Mackenzie River Delta (Ehdiitat), and Travaillant Lake (Khaii Luk), showcasing the prominence of these features in Gwich'in livelihoods. This finding is consistent with the ethnographic literature, which highlights the importance of rivers for travel, harvesting, identity, and language in Gwich'in culture, and for Indigenous peoples around the world [25,82,83].
Our maps also show some areas of the GSR, including the Mackenzie Mountains and the headwaters of the Arctic Red River (Tsiigehnjik), with no cultural features recorded in the spatial data we utilized. This may be because difficult travel conditions in these areas limited their use [84]. However, it is also likely that these areas experienced more widespread use prior to European contact in the mid-1800s, which isn't captured by the spatial data we analyzed [28]. These areas also border the territory of Indigenous groups like the Sahtú Dene, who have highlighted place names, trails, and harvesting areas near the headwaters of the Arctic Red River (Tsiigehnjik) [85]. With further field studies and traditional knowledge research, additional cultural features could be identified in these areas.
The widespread density of cultural features in the Gwich'in Settlement Region, combined with the extent of disturbances across this area, highlights the need for methods to assess the cumulative impacts of disturbance on the cultural and ecological landscape. While social and cultural components are included in cumulative impact assessments in some regions, they are typically less prevalent than biological components in the available literature [32,34]. This is concerning because omitting some features underrepresents the extent of the cultural landscape, running the risk that decisions will be made with incomplete information that distorts the magnitude of impacts [27,86]. Because of this, additional tools are needed to include cultural features in cumulative impact assessments [32].
The methods for overlaying cultural features and disturbances outlined in this paper provide a unique and straightforward approach that can be used as a first step to a more comprehensive consideration of the cultural landscape in cumulative impact assessments. Overlay analysis has been used to assess the risks from specific environmental disturbances to socio-culturally important locations around the world [87][88][89]. Map overlays have also been described as a tool to examine cultural impacts in Environmental Impact Assessments, or to analyze cumulative environmental impacts [16,90]. Our approach builds on, yet is distinct from, these efforts because it is driven by both detailed ecological data and local knowledge of relationships between people, land, and water.
Our overlay analysis illustrates regional scale patterns of cumulative environmental impacts in the cultural landscape that would not be evident by focusing on a single disturbance type or cultural feature category [91,92]. The map displayed in Figure 6 shows that the highest amounts of potential overlap and impact between cultural features and disturbances occur along sections of the Dempster Highway that intersect with community infrastructure, areas of the Peel Plateau containing thaw slumps and seismic lines, and along the Peel River (Teetł'it Gwinjik), which contains dense concentrations of cultural features. It is particularly noteworthy that the majority of planning units in the Peel Plateau ecoregion contained both cultural features and disturbances such as thaw slumps. This highlights the fact that this region is experiencing particularly intensive, rapid geomorphological change in a culturally important area [23,51,93].
The overlay methods described here have the potential to inform cultural heritage and land use management, as well as regional environmental monitoring. For example, broad-scale overlay analysis can be used to determine where to conduct fieldwork for cultural heritage managers, who make decisions about vast cultural landscapes impacted by environmental disturbance [28]. Examining potential overlap between cultural features and disturbances could also be used to assess impacts to valued ecosystem components [16,94]. In northern regions, these methods could contribute to co-management decision making about a culturally important species like caribou, by combining information on caribou harvesting areas [95] and relevant disturbance data like roads [96]. In terms of environmental monitoring, significant efforts are being directed at land-based monitoring which utilizes traditional knowledge and/or scientific methods to document changes of interest to community members and researchers [97,98]. The methods described here could augment these initiatives by identifying areas where rapid environmental change may impact cultural features, which should be prioritized for monitoring [28,99].
Expert consultation is an important aspect of cumulative impact assessment [16,100], and our experience indicates it is particularly important when examining cumulative impacts in cultural landscapes. In this project, local collaboration, expert consultation, and community visits provided vital direction. The Gwich'in have a long history of engaging in mapping projects [40,82,93], and their collaboration in this project ensured that Gwich'in knowledge and data were used appropriately and that mapping was undertaken respectfully. Interviewing and consulting community members, professionals invested in the region, and Gwich'in organizations also shaped the way that we conceptualized and represented cultural features [42]. For instance, our interviewees were clear that creating a rigorous weighting scheme for cultural features would be challenging and could not be completed by a small number of people. Community visits also ensured that we could update organizations and community members to gain feedback and share results.
Alongside potential applications of these methods, there are challenges associated with mapping cultural landscapes. For instance, demarcating cultural locations on a map may fail to fully represent the knowledge, relationships, and collective memories associated with tangible and intangible cultural features [101,102]. Maps are a powerful means to convey information [103], and to ensure that knowledge is not misrepresented or distorted in the mapping process, it is vital that cultural mapping projects that are warranted in an area are conducted in a culturally appropriate manner. For example, certain locations (i.e., sacred sites, harvesting locations) are confidential and cannot be presented in the public domain [104]. To protect culturally sensitive places and confidential information, our mapping analysis presents our results in aggregate form, ensuring that confidential cultural features are not identifiable. While maps from our analysis do not display discernible cultural feature locations, there may be concerns in other projects about releasing spatial data representing cultural features to individuals outside the community to analyze. In these cases, funding and training (if necessary) should be provided to the interested communities to conduct or be engaged in the analyses.
Additional challenges associated with the approach outlined here relate to data availability and type. Acquiring high quality, up to date data is a well-documented challenge [89,105]. Although there is a wealth of spatial data representing cultural features in the GSR, limited data may be a significant constraint in other regions. This obstacle is magnified by the pace of ecological change in some regions [106,107], which can quickly make spatial data outdated. Utilizing different types of data (i.e., point, line, polygon) can also pose a challenge to this kind of synthesis. In our analysis, while the methods used to calculate the cultural feature intensity index differed between data types and likely affected the absolute values of the index, we are confident that the overall pattern inherent in the data was not affected by our approach to mapping.
Another drawback of our overlay method is that it highlights potential, rather than known, impacts. As such, we recommend that overlay analysis is deployed as an initial step that is followed up with finer-scale spatial analysis and the inclusion of impacts that are not mapped. Finer scale analysis may be important for land managers and researchers who want to examine a particular area in maximum detail. For instance, the potential overlap between cultural features and disturbances in the Peel Plateau ecoregion illustrated by our analysis could lead cultural heritage managers to conduct a more intensive analysis of this specific area to better guide the assessment of impacts to cultural features or implementation of potential protective measures. Finer scale analyses could also more effectively include both positive and negative impacts of disturbances. In our regional-scale analysis, we made the simplifying assumption that disturbances causing ecological damage and overlapping with cultural features led to negative outcomes. However, many disturbances also include positive aspects. Community infrastructure has obvious positive attributes, and attendees at our community meetings discussed benefits like economic gain and travel corridors associated with seismic lines. Related to this, it is important to account for the cultural and environmental impacts of disturbances beyond overlap that are not mapped. As one example, future analyses should include social impacts of development that often accompany industrial camps and housing created for temporary workers [108,109]. Additionally, future analyses should include environmental changes such as community members' observations of increased air temperatures [110]. While increased air temperatures do not directly manifest on the land, they impact disturbances like thaw slumps [51] and cultural activities like drying fish [110].

Conclusions
This paper outlines a method of spatial overlay analysis designed to quantify and map cultural features, cumulative environmental disturbance, and the potential overlap between these landscape features. When combined, these methods provide a means to recognize regional scale patterns of cultural use and characterize cumulative environmental impacts in a cultural landscape. Our analysis illustrates the nature of the cultural landscape in the Gwich'in Settlement Region, which contains expansive cultural features and is impacted by widespread but relatively low-intensity disturbances. Overlaying cultural feature and disturbance data revealed low to moderate overlap between disturbances and cultural features. To understand the implications of ongoing environmental change, cultural features must be included in cumulative impact assessments. The methods described here provide a straightforward step to addressing the exclusion of the cultural landscape in most cumulative impact assessments. Our analysis focuses on the cultural landscape at the regional scale, but with appropriate data and local consultation, our methods could also be deployed across a range of scales relevant to land use and cultural heritage managers.