DOUBLE SAMPLING INCREASES THE EFFICIENCY OF FOREST FLOOR INVENTORIES FOR ARIZONA PONDEROSA PINE FORESTS

Stand and natural fuel conditions were sampled in ponderosa pine fores ts in northern and central Arizona to develop predictive fuel depth an d loading equations. Litter and duff depths can be estimated from meas urements of stand density (basal area, stand density index). Although woody fuel loading did not correlate well with stand variables, correl ations were found among loadings of different woody fuel size classes, so that results from a planar intersect tally of certain single woody fuel size classes may be used to predict the loadings in certain othe r size classes. The relatively low precision of estimates from these p redictive equations can be substantially increased by applying them in a double sampling scheme. Making use of these predictive relationship s, managers can devise simple, rapid, arid cost-effective fuel invento ries that focus on the fuel category of interest. Fuel loads can be es timated at a desired precision with reduced investment of time and fun ds compared to a more comprehensive direct fuel inventory.