This study quantitatively examines indicators frequently used to estimate community resilience and proposes a method for assessing the validity of indicators used in community resilience measurement. An array of 18 indicators and related measures were identified as being common to existing methodologies. A comprehensive and replicable method that can evaluate the reliability and validity of community resilience indicators was then employed to explore the appropriateness of indicator selection by comparing different sets of measures. Multiple internal consistency test methods, such as Cronbach’s alpha, correlation analysis, cluster analysis, and classification tree, were conducted to address varying aspects of community resilience and to estimate commonalities in indicator selections. Structural equation modeling (SEM) provided a system to investigate indicators’ validity and overall performance in a hypothetical construct of community resilience predicting a proxy of community resilience outcomes. In exploring internal consistency and external validation of indicators, the importance of conducting validation studies is highlighted. To ensure indicators are ready for use among practitioners and policymakers, the quality of indicators needs to be tested and clearly stated in the context of other indicators and empirical outcomes of community resilience.

This data article provides details of an analysis of an inventory of 56 community resilience frameworks. In this article, a description of how the inventory data was catalogued is presented. Section 3 outlines the categories used to analyze the frameworks as well as the categories used to bin the indicators and measures used in each. Section 3.1 describes the results of the categorization process for the 56 resilience frameworks. Section 3.2 outlines the results of the categorization of the 3,298 indicators used in each framework. Section 3.3 describes the 7,165 measures used in the 56 frameworks.

As natural disasters have increased in frequency and magnitude, there has been an increasing need to understand what underlying factors are likely to lead to faster recovery and more resilient communities. One way of addressing this need has been to develop sets of indicators or indicator indices that serve as proxy measurements for resilience, which is an emergent system property and cannot be directly measured. Once operationalized, resilience indicators can be used for planning, making funding decisions, and tracking program progress. Since all of these uses can have profound effects on community well-being, it is important that indicator selection involves stakeholders and is based on the best available science. For the latter criteria, this can be determined by assessing what evidence is used to justify indicator choices and validating candidate indicators on observed data. Previous reviews of resilience indicator frameworks have attempted to gauge the state of evidence used for indicator selection by looking for consensus of indicator choices across different frameworks. Similar to a multi-expert elicitation, it is inferred that agreement on an indicator among frameworks points to strong evidence that the indicator is a good measurement of resilience. Using a novel categorization methodology based in systems science, this study reviews a small set of resilience frameworks for indicator consensus. Compared to previous reviews, this methodology allows for clear distinction between consensus of concepts and consensus of indicators to measure concepts. Our results show two new insights. The first is that common usage of an indicator does not mean that agreement also exists on what the indicator is actually measuring. The second is that even if a common indicator has agreement on what concepts are measured, it is not guaranteed that this consensus is backed by high quality evidence. These results call into question the practice of reviewing many frameworks to identify common indicators during model development, and instead points to the need for more detailed assessment of background evidence and indicator validation.

Despite being among the most valuable ecosystems on Earth, coral reefs face ongoing threats that could negatively impact the human populations who depend on them. The National Coral Reef Monitoring Program (NCRMP) collects and monitors data on various aspects of U.S. coral reefs to provide a holistic understanding of the status of the reefs and adjacent human communities. This paper explores results from the NCRMP’s first socioeconomic monitoring cycle using an ecosystem services framework and examines how these results can be used to improve coral reef management in the following U.S. coral reef jurisdictions: American Samoa, the Commonwealth of the Northern Mariana Islands, Florida, Guam, Hawai’i, Puerto Rico, and the U.S. Virgin Islands. Results suggest that residents in the U.S. Pacific coral reef basin may hold stronger cultural and provisioning values, whereas residents in the U.S. Atlantic coral reef basin may hold stronger regulating values. These findings suggest that outreach efforts have been successful in communicating benefits provided by coral reef ecosystems to the public. They also provide insight into which ecosystem services are valued in each jurisdiction, allowing resource managers to make science-based decisions about how to communicate conservation and management initiatives.