Double sampling may improve the efficiency of litterfall estimates

The effort required for an extensive litterfall measurement campaign can be prohibitive. We propose a double sampling approach, in which a large set of traps is used in each stand to estimate total litterfall, and only a subset of these traps is sorted to the relevant components. We examine its feasibility using data from a regional litterfall study of eastern white pine (Pinus strobus L.), in which the variables of interest were biomass of foliar litterfall from pine and nitrogen content of foliar litterfall from all vegetation. Double sampling was more efficient than simple random sampling but only if every trap received a rapid presorting to remove twigs and cones. The optimal strategy when pine foliar litterfall biomass was the target variable was to conduct full sorting on 33% of the traps. When foliar litterfall N was the target, sorting only 20% of the traps was optimal. Holding time costs constant, the variance of estimated pine foliar litterfall biomass could be reduced by 18%, whereas that for foliar litterfall N could be reduced by 49%. Alternately, when variance was held constant, the time cost could be reduced by 17% for pine foliar litterfall biomass or 44% for foliar litterfall N.