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There has been a growth in the number of composite indicator tools used to assess community risk, vulnerability, and resilience, to assist study and policy planning. However, existing research shows that these composite indicators vary extensively in method, selected variables, aggregation methods, and sample size. The result is a plethora of qualitative and quantitative composite indices to choose from. Despite each providing valuable location-based information about specific communities and their qualities, the results of studies, each using disparate methods, cannot easily be integrated for use in decision making, given the different index attributes and study locations. Like many regions in the world, the Arctic is experiencing increased variability in temperatures as a direct consequence of a changing planetary climate. Cascading effects of changes in permafrost are poorly characterized, thus limiting response at multiple scales. We offer that by considering the spatial interaction between the effects of permafrost, infrastructure, and diverse patterns of community characteristics, existing research using different composite indices and frameworks can be augmented. We used a system-science and place-based knowledge approach that accounts for sub-system and cascade impacts through a proximity model of spatial interaction. An estimated ‘permafrost vulnerability surface’ was calculated across Alaska using two existing indices: relevant infrastructure and permafrost extent. The value of this surface in 186 communities and 30 military facilities was extracted and ordered to match the numerical rankings of the Denali Commission in their assessment of permafrost threat, allowing accurate comparison between the permafrost threat ranks and the PVI rankings. The methods behind the PVI provide a tool that can incorporate multiple risk, resilience, and vulnerability indices to aid adaptation planning, especially where large-scale studies with good geographic sample distribution using the same criteria and methods do not exist. 

This paper presents the results of a community survey that was designed to better understand the effects of permafrost degradation and coastal erosion on civil infrastructure. Observations were collected from residents in four Arctic coastal communities: Point Lay, Wainwright, Utqiaġvik, and Kaktovik. All four communities are underlain by continuous ice-rich permafrost with varying degrees of degradation and coastal erosion. The types, locations, and periods of observed permafrost thaw and coastal erosion were elicited. Survey participants also reported the types of civil infrastructure being affected by permafrost degradation and coastal erosion and any damage to residential buildings. Most survey participants reported that coastal erosion has been occurring for a longer period than permafrost thaw. Surface water ponding, ground surface collapse, and differential ground settlement are the three types of changes in ground surface manifested by permafrost degradation that are most frequently reported by the participants, while houses are reported as the most affected type of infrastructure in the Arctic coastal communities. Wall cracking and house tilting are the most commonly reported types of residential building damage. The effects of permafrost degradation and coastal erosion on civil infrastructure vary between communities. Locations of observed permafrost degradation and coastal erosion collected from all survey participants in each community were stacked using heatmap data visualization. The heatmaps constructed using the community survey data are reasonably consistent with modeled data synthesized from the scientific literature. This study shows a useful approach to coproduce knowledge with Arctic residents to identify locations of permafrost thaw and coastal erosion at higher spatial resolution as well as the types of infrastructure damage of most concern to Arctic residents. 

The current Arctic security environment is poorly characterized. In the past few years, it has been termed “a return to great-power competition” and now is oscil- lating around discussions of hybrid threats or gray-zone warfare. Whatever the term, these are methods and means designed to avoid notice, obscure intent and origin, and exploit the seams in the targets’ awareness and response capabilities. In this article we use the term asymmetric competition (AC) to describe such ac- tivities, which exist as a continuum of conflict below open warfare, rather than fitting neatly into the binary notion of war and peace. While many national se- curity scholars and practitioners are aware of and concerned about the use of AC by the People’s Republic of China (PRC), the ability of the United States and its allies to detect and protect against such behavior is limited. At the same time, the PRC has demonstrated a growing interest in the Arctic due to the region’s geo- strategic importance and has taken an unusually aggressive posture toward as- serting and securing Beijing’s interests there. We conducted an initial assessment to detect the extent, types, and tempo of AC using the Strategic Intelligence Framework (SIF)—a systems science methodology—to identify PRC asymmet- ric competition activities in the North American Arctic. Our results suggest an ongoing and pervasive AC campaign. We offer that integrative frameworks like the SIF can assist the United States, its allies, and its partners in detecting and characterizing AC with the accuracy and precision required for the development of strategy, policies, and response.