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Seeking spatiotemporal patterns about how citizens interact with the urban space is critical for understanding how cities function. Such interactions were studied in various forms focusing on patterns of people’s presence, action, and transition in the urban environment, which are defined as human-urban interactions in this paper. Using human activity datasets that utilize mobile positioning technology for tracking the locations and movements of individuals, researchers developed stochastic models to uncover preferential return behaviors and recurrent transitional activity structures in human-urban interactions. Ad-hoc heuristics and spatial clustering methods were applied to derive meaningful activity places in those studies. However, the lack of semantic meaning in the recorded locations makes it difficult to examine the details about how people interact with different activity places. In this study, we utilized geographic context-aware Twitter data to investigate the spatiotemporal patterns of people’s interactions with their activity places in different urban settings. To test consistency of our findings, we used geo-located tweets to derive the activity places in Twitter users’ location histories over three major U.S. metropolitan areas: Greater Boston Area, Chicago, and San Diego, where the geographic context of each location was inferred from its closest land use parcel. The results showed striking spatial and temporal similarities in Twitter users’ interactions with their activity places among the three cities. By using entropy-based predictability measures, this study not only confirmed the preferential return behaviors as people tend to revisit a few highly frequented places but also revealed detailed characteristics of those activity places.

 

Declining wild food use has been reported around the world for decades, with important implications for nutrition and well-being. Commonly listed threats include land-use change and overharvesting. Climate change acts to compound these. Herein, we examine the importance of wild foods around the world and the impact of climate change on wild food species. We highlight large variations between regions, both in terms of climate impacts on wild foods and their importance. The emerging evidence suggests that, in addition to the Arctic, arid regions (such as the Sahel region of West Africa) and mountain regions (such as the Himalayas) may be particularly vulnerable to the impact of climate change on wild foods. We conclude with a reflection on the role of wild foods in climate change adaptation strategies and the ways that climate change adaptation strategies could threaten or enhance availability and accessibility to wild foods. 

Around 13,000 people from outside Alaska arrive each summer in the Bristol Bay region of Western Alaska to participate in the world’s most valuable wild salmon fishery. The small regional hub community of Dillingham is the home port of the Nushagak River salmon fishery. The National Science Foundation funded a RAPID project to assess planning needs for the fishery, community, and region. Our project developed pandemic preparedness scenarios for local residents and decision-makers through online surveys to better understand the costs and benefits of varied mitigation policies; and risk preferences from fishers, processors, local residents, and local decision-makers to better understand cooperation and decisions under risk and uncertainty.