Climate change is impacting fisheries through ecological shifts altering the geographical distribution and quantity of fish species. About 60% of United States fish caught by volume is caught in the Alaska region, with Alaska's economy dependent on fisheries. Additionally, fisheries are an important source of employment for many Alaskan communities. Therefore, it is important to have policies and strategies in place to prepare for ongoing climate impacts. One step to support better tailoring policy to support those most likely to be negatively impacted is to identify the fishing communities most vulnerable to climate change. This study uses data on vulnerable fish species and fishery catch by species and community to identify what communities are most vulnerable to changing climate conditions. I identify 26 communities that are fishing climate vulnerable species. I then use vulnerable fish species revenue data to identify communities most at risk either because they generate a substantial amount of revenue from these species or a substantial proportion of their total revenue is derived from these species. Using species-specific revenue, I show that Sablefish contribute the most to this vulnerability.

This research explores the use of transformative urban scenarios and timelines as a planning tool for addressing future sustainability challenges in urban environments. The analysis comes from a set of scenarios that were explored through workshops conducted in 2019 in which Phoenix stakeholders developed timelines toward their visions of Phoenix 60 years into the future. To evaluate the pathways created in these timelines, we employed process tracing methodology to understand which causal mechanisms lead to certain phenomena. Or in other words, it helps us understand how changes happen. We converted the timelines into process tracing diagrams that categorized the relationship between actions, actors, and observable manifestations (OM’s) of change over time. To understand the relationship between these components, we then used a combination of inductive and deductive coding to categorize types of activities, actors, OM’s and sustainability topics and organized them into themes. This helped us to understand how city decision-makers and community leaders think sustainability and resilience transformation can and should occur. This thesis takes a closer look at one particular scenario, Some Like it Hot, which explores resilience to extreme heat. Through coding and analysis, we found trends, correlations, and missing pieces in the participants’ timeline. There are numerous overarching causal mechanisms throughout the scenario timeline. These trends offer insight into which activities and stakeholders are seen as significant drivers of sustainable transformation according to the workshop participants. The file attached is a pdf version of an ArcGIS Story Map completed for this honors thesis. To view the full, interactive thesis deliverable, visit https://storymaps.arcgis.com/stories/14d1e52a9448498e87f20e7566651a13