Coral reefs are threatened worldwide. To facilitate reef management and restoration decisions, resource managers require indicators of the biological condition of reef environments that can relate data acquired through remote-sensing, water quality and benthic-community monitoring to stress responses in reef organisms. A single-metric bioindicator has been developed that is based upon foraminiferal assemblages. The "FORAM" (Foraminifera in Reef Assessment and Monitoring) Index is based upon more than 30 years of research on reef sediments and reef-dwelling larger foraminifers. Several factors make these shelled protists ideal indicators for reef environments. While reef-building, zooxanthellate corals and foraminifers with algal symbionts have similar water-quality requirements, the relatively short life spans of foraminifers as compared with long-lived colonial corals facilitates differentiation between long-term water-quality decline and episodic stress events. Furthermore, foraminifers are relatively small and abundant, permitting statistically significant sample sizes to be collected quickly and relatively inexpensively, ideally as a component of comprehensive monitoring programs. Equally important for assessment and monitoring in protected areas, the collection of foraminifers has minimal impact on reef resources. The FORAM Index has been evaluated using USEPA guidelines for ecological indicators. Data required are relative abundances of foraminiferal genera in surface sediments of reef-associated environments. The FORAM Index provides resource managers with a simple procedure for determining the suitability of benthic environments to support communities dominated by algal symbiotic organisms. The FORAM Index can be applied independently or incorporated into monitoring progrmas. The simple calculations require limited computer capabilities and therefore can be applied readily in reef-associated environments worldwide. In addition, the foraminiferal shells collected can be subjected to morphometric and geochemical analyses in areas of suspected heavy-metal pollution, and data sets for the index can be used with other monitoring data in detailed multidimensional assessments.