The varied effects of recent extreme weather events around the world exemplify the uneven impacts of climate change on populations, even within relatively small geographic regions. Differential human vulnerability to environmental hazards results from a range of social, economic, historical, and political factors, all of which operate at multiple scales. While adaptation to climate change has been the dominant focus of policy and research agendas, it is essential to ask as well why some communities and peoples are disproportionately exposed to and affected by climate threats. The cases and synthesis presented here are organized around four key themes (resource access, governance, culture, and knowledge), which we approach from four social science fields (cultural anthropology, archaeology, human geography, and sociology). Social scientific approaches to human vulnerability draw vital attention to the root causes of climate change threats and the reasons that people are forced to adapt to them. Because vulnerability is a multidimensional process rather than an unchanging state, a dynamic social approach to vulnerability is most likely to improve mitigation and adaptation planning efforts. This article is categorized under: Vulnerability and Adaptation to Climate Change > Values‐Based Approach to Vulnerability and Adaptation

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Rising seas will impact millions of coastal residents in coming decades. The vulnerability of coastal populations exposed to inundation will be greater for some sub-populations due to differences in their socio-demographic characteristics. Many climate risk and vulnerability assessments, however, model current populations against future environments. We advance sealevel rise risk assessments by dynamically modeling environmental change and sociodemographic change. We project three scenarios of inundation exposure due to future sea-level rise in coastal Georgia from 2010 to 2050. We align the sea-level rise projections with five population projection scenarios of socially vulnerable sub-populations via the Hamilton-Perry method and the theory of demographic metabolism. Our combined fast sea-level rise and middle population scenarios project a near doubling of the population exposed, and a more than fivefold increase for those at risk (i.e., residing in a census tract with high social vulnerability) and most at risk (i.e., high social vulnerability and high exposure) compared to the same estimate based on 2010 population data. Of vulnerable sub-populations, women had the largest absolute increase in exposure for all scenario combinations. The Hispanic/Latinx population's exposure increased the largest proportionally under the fast and medium sea-level rise projections and elderly people's (65+) under the slow sea-level rise scenario. Our findings suggest that for coastal areas experiencing rapid growth (or declines) in more socially vulnerable subpopulations, estimates based on current population data are likely to underestimate (or overestimate) the proportion of such groups' risk to inundation from future sea-level rise.

The exposure of populations to sea-level rise (SLR) is a leading indicator assessing the impact of future climate change on coastal regions. SLR exposes coastal populations to a spectrum of impacts with broad spatial and temporal heterogeneity, but exposure assessments often narrowly define the spatial zone of flooding. Here we show how choice of zone results in differential exposure estimates across space and time. Further, we apply a spatio-temporal flood-modeling approach that integrates across these spatial zones to assess the annual probability of population exposure. We apply our model to the coastal United States to demonstrate a more robust assessment of population exposure to flooding from SLR in any given year. Our results suggest that more explicit decisions regarding spatial zone (and associated temporal implication) will improve adaptation planning and policies by indicating the relative chance and magnitude of coastal populations to be affected by future SLR.