Summary
Agroforestry, the intentional integration of agriculture and forestry, is now one of several carbon (C) sequestering options being promoted for use in agricultural lands in the U.S. Quantifying this C contribution requires biomass equations that capture the growth differences (e.g., tree specific gravity, stem taper and branchiness) in these more open-canopy grown trees. Inclusion of agroforestry in agricultural C assessment tools at the farm, ranch and woodlot level requires measurements and estimation approaches that are both useful (science based and accurate) and usable (end users will be willing and able to gather the data required for input). Because agroforestry lacks the data foundation that forestry and agronomy can pull from for these activities, another requirement was finding a cost-efficient and timely means of providing the basis for C estimation in agroforestry's woody components. Utilizing one of the few datasets generated from destructive sampling of trees in agroforestry plantings, biomass equations were generated for three key windbreak species in the Northern Great Plains, each representing a different major morphological tree type used within agroforestry plantings: green ash, eastern red cedar, and Austrian pine. These windbreak-derived equations were then compared to three forest-derived equations: regional, nonregional and self-fitted. Forest-derived equations were found to significantly underestimate whole tree biomass. The National Agroforestry Center developed a constant adjustment factor that provides a cost-efficient approach to using forest derived equations for open-gown trees in agricultural lands. Information generated from this research provides the basis for determining how agroforestry's working tree C stocks are best included within entity and national-scale C tools.
