Search

Increasing flood losses in the Gulf of Mexico related to development patterns and climate hazards pose serious threats to resilience and insurability. The purpose of this study is to understand how scale, social vulnerability, risk, and urban form relate to National Flood Insurance Program (NFIP) policy coverage and flood exposure. Our multilevel models identify that flooding is significantly clustered by region and counties, especially shoreline counties. Our measures of risk suggest that the Federal Emergency Management Agency (FEMA) special flood hazard area (SFHA) underestimates risk and exposure when compared with the Flood Factor and that there is some compensation in terms of insurance coverage, suggesting a pattern of adverse selection. Older housing stock appears both less insured and less exposed, raising questions of whether current growth patterns are increasing risk independent of environmental change. Our models suggest that census tracts with higher percentages of black residents are less insured and more exposed, and a similar pattern exists for rural areas. Our results highlight the need to seek common solutions across the Gulf of Mexico, concentrating on the most flood-exposed counties, and that specific resilience strategies may be necessary to protect areas with socially vulnerable populations, especially in rural areas. Underlying challenges exist due to the spatial relationship between exposure and social vulnerability and the potential for adverse selection in insurance markets due to different measures of risk. [ABSTRACT FROM AUTHOR]

Community decision making based on the sustainability of ecosystem services is an integrated process that involves multiple complex decisions and is greatly aided by an understanding of how those decisions are interrelated. The interrelatedness of decisions can be understood and even measured based on connections between actions and services and influence of services on domains of human well-being. These connections can be formed into a network structure so that quantifiable properties of networks can be applied to understanding decision impacts. We developed an eco-decisional network based on weighted social-ecological networks as a tool for integrated decision making based on ecosystem services and human well-being. Nodes are actions, services, or domains of human well-being and they are linked by weighted influence derived from community stakeholder input. Examination of the eco-decisional network, as well as comparison to pattern in the random networks, suggest there are important patterns of influence among different influence pathways from actions to community well-being, which describe community priorities and define unique roles through which chosen sets of actions can influence human well-being. The eco-decisional network is generalized across communities but can also be made community specific, which provides a tool for comparison between communities in decisional priorities (network properties), as well as comparisons between proposed actions within a community (network paths). The well-studied properties of networks, well- established network theory, as well as established network metrics make this approach promising for application to integrated decision making and for communicating possible outcomes to stakeholders. The result is a guidance tool for connecting propose actions to ecosystem services and human well-being. [ABSTRACT FROM AUTHOR]