Branch aggregation and crown allometry condition the precision of randomized branch sampling estimators of conifer crown mass

Characterizations of conifer crown biomass are important for assessing forest fuel loadings, bioenergy supplies, carbon stocks, and growth and yield. There is considerable variation in conifer crown mass, but to guide sampling programs, there is little quantitative information available concerning its structure or extent. This research examines several randomized branch sampling (RBS) strategies adapted for excurrent crown forms, as well as the impact of allometric relationships on their precision. The RBS strategies differ in terms of how primary branches (those attached directly to the bole) are aggregated into selection nodes and are evaluated using destructively sampled Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) and western larch (Larix occidentalis Nutt.) trees. Strong linear relationships between branch mass and basal area improve the precision of RBS relative to simple random sampling. Yet because the sample trees exhibited area-increasing branching patterns, the RBS strategies could not achieve the same precision as two-pass probability proportional-to-size methods. For the same reason, aggregation of branches improved the precision of RBS. For practical reasons, we recommend aggregating branches by 1 m intervals along the stem. This strategy brought the relative standard errors for crown mass below 20% with sample sizes of four to eight branches, with smaller sample sizes yielding this result for more slender trees. We also report results on the variability of branch area and mass, as well as results that recommend against the practice of allocating equal numbers of sample branches to crown strata of equal length.