Background/Question/Methods California has received vegetation mapping attention since the early 20^th century.  Several major efforts have managed to map much of the state at various resolutions using schemes that were either habitat -driven or quasi-floristic, based on major cover of dominant overstory plant species.  Some of these efforts were supported by extensive field data collection and some were more interpretive, relying primarily upon modeling of remotely sensed data to guide the development of the map units.  None of these earlier methods were driven by quantitative analysis of vegetation field plots.  As the state’s population grew in the mid and late 20^th century and more stress and emphasis was places upon its natural resources, the needs for defensible definition and assessment of vegetation increased.  Ad hoc mapping classifications with equivocal definitions along with spatially inaccurate and coarse delineation of natural patterns were not sufficient to interpret and assess the diverse array of vegetation and the biological wealth it contains. In the 1990’s floristic classification of California’s vegetation gained momentum. Vegetation mapping projects began, which relied upon analysis of field plot data to develop the classification. The mapping units were derived directly from the quantitative classification.

Results/Conclusions Currently the state’s resources agencies support an integrated process of representative sampling, analysis, and development of standardized National Vegetation Classification system definitions, which is followed by mapping of fine spatial scale down to stands of 0.5 ha or smaller.  Areas are prioritized for integrated classification and mapping based primarily on conservation needs.  Several of these projects have been completed and can serve as demonstrations of their value for scientifically grounded decisions on such basic concepts as reserve selection, specific impact assessments, and wildlife corridor establishment. These projects are also powerful tools for long-range adaptive management.  They may guide restoration efforts, monitor natural change, and enable broad scale measurement of the effects of multiple impacts in a large landscape.  Examples of these uses are discussed and suggestions for further implementation and improvements are given.