Carmela B.M. Arevalo، نويسنده , , Timothy A. Volk، نويسنده , , Eddie Bevilacqua، نويسنده , , Lawrence Abrahamson، نويسنده ,
Commercial and research scale plantings of short-rotation woody crops require reliable and efficient estimations of biomass yield before time of harvest. Biomass equations currently exist but the accuracy and efficiency of estimation procedures at the level of specificity needs to be quantified for clones being used in North America. Diameter-based allometric equations for aboveground biomass for four clones of willow (Salix discolor, Salix alba, Salix dasyclados, and Salix sachalinensis), between two sites (Canastota and Tully, NY), and across four years (1998–2001), were developed using ordinary least-squares regression (OLSR) on log-transformed variables, weighted least squares regression (WLSR) on log-transformed variables, and nonlinear regression (NLR) methods and validated using independent data sets. Biomass estimations derived from clone, age, and site (Specific) using OLSR equations had highest R2 and lowest percent bias (<2.3%) allowing for accurate estimations of standing biomass. Values for specific equations using WLSR were similar, but bias was higher for NLR (0.7–12.5%). However, the amount of time and effort required to develop specific equations, is large and in many situations prohibitive. Biomass estimates derived from clone and age, regardless of site (Intermediate), resulted in small increases in prediction error and a small increase in percent bias using OLSR (<0.4%) and WLSR (<1.7%). The increase in percent bias was larger (1.1–5.7%) for NLR equations. Intermediate models correspond to the loss of only a small amount of accuracy while gaining more efficiency in estimating standing biomass. Estimates of biomass derived from clone alone (general) equations, considering neither age nor site, had the weakest prediction abilities that may lead to large errors for biomass estimations using OLSR (7.0–9.5%), WLSR (1.1–21.7%) or NLR (31.9–143.4%).
Lithuania , Bioenergy , Forest fuel , Forest management , Biofuel markets