Six years of monitoring for ozone injury by the Pacific Northwest Research Station Forest Inventory and Analysis Program are reported. The methods used to evaluate injury, compute an injury index, and estimate risk are described. Extensive injury was detected on ozone biomonitoring sites for all years in California, with ponderosa and Jeffrey pines, mugwort, skunkbush, and blue elderberry showing injury. Little or no injury was detected in Oregon and Washington. The relation of observed injury to ambient ozone levels is discussed. The areas with the highest modeled risk of ozone injury are the areas east of Los Angeles, the southern Sierra Nevada, and portions of the central coast.

"The Forest Health Monitoring (FHM) Program's annual national report uses FHM data, as well as data from a variety of other programs, to provide an overview of forest health based on the criteria and indicators of sustainable forestry framework of the Santiago Declaration. It presents information about the status of and trends in various forest health indicators nationwide and uses statistically valid analysis methods applicable to large-scale ecological assessments. Five main sections correspond to the Santiago criteria: Biological Diversity, Productive Capacity, Health and Vitality, Conservation of Soil, and Carbon Cycling. A variety of indicators contribute information about the status of each forest ecosystem considered. Many indicators use data collected from ground plots. Such indicators include species diversity (tree and lichens), bioindicator species (lichens and vascular plants sensitive to ozone), changes in trees (crown condition, damage, and mortality), physical and chemical soil characteristics, and aboveground and belowground carbon pools. Additional information about forest health status and change is derived from data that are used to measure forest extent; data about insects and pathogens; and remotely sensed and/or ground-based data about forest fragmentation, fire, and air pollution. A sixth section presents and discusses a multivariate analysis of the indicators. The technique provides a composite picture of forest health, based on statistically significant principal components."--P. ii.