Efficient and cost-effective monitoring methods are critical for land management.  We examined the effect of sampling intensity on species composition, vegetation community delineation, and species richness on 17 montane meadows in the Sierra Nevada, California.  Randomly placed permanent line-point transects were sampled from 10 meadows in the Sierra National Forest and 7 meadows in the Stanislaus National Forest in 2006.  Species hits were recorded in a spatially explicit manner at 10cm intervals, along transects of all different lengths placed perpendicular to the water flow or topographic gradient across the entire meadow.  All point data were used to classify meadow types using PC-ORD cluster analysis and verified with TWINSPAN.  Species richness and native species richness were calculated.  Ten-cm data analysis results were used as the baseline from which comparisons of other point interval data (20cm, 50cm, 1m, 2m, 3m, 4m, and 5m) could be assessed.  The question was: what is the lowest sampling intensity required to identify species and community diversity?  We found community type delineation remained relatively stable until the 4m data.  At that sampling intensity, community types collapsed.  Species richness declined in absolute number with each reduction in sampling intensity.  However, the reduction in species richness leveled off at 2m, although there is a steep reduction in the number of species detected between 10cm and 1m sampling intervals.  Results suggest that the optimal sampling intensity will depend on management objectives.