Fire scars have been used extensively to understand the historical role of fire in ponderosa pine (Pinus ponderosa) ecosystems. However, the sampling methods and interpretation of fire scar data have been criticized as statistically invalid, biased, and leading to exaggerated fire frequency estimates (e.g., Johnson and Gutsell [1994], Baker and Ehle [2001]). We tested alternative sampling schemes by comparing “targeted” sampling, random sampling, and grid-based sampling to a comprehensive measurement and mapping of all fire-scarred trees in a 1-km² Arizona forest. We collected fire-scarred partial cross-sections from nearly 1,500 trees in 2002. Using sample sets stochastically generated from the comprehensive data, we are contrasting the effects of different sampling methods. Preliminary results suggest that “targeted” sampling did not result in the collection of the finest individual tree samples in the study area, but the composite fire history (fire frequency, variability, seasonality, and spatial extent) varies very little between sampling schemes. Quantification of the differences in sampling approaches will not resolve all the limitations of fire-scar methods, since scarred trees are inherently point-sources of data. But measurement of sampling uncertainty will reduce the scope of “uncertainty” in interpretation of fire regime statistics.