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- Title
Estimating biomass of white spruce seedlings with vertical photo imagery.
- Authors
Michael T. Ter-Mikaelian; William C. Parker
- Abstract
Estimation of individual tree seedling biomass is required in a variety of forest management and research applications such as assessment of net primary productivity and carbon sequestration potential of forest stands, understory forest fuel inventories, and development of silvicultural guidelines to promote the growth of desired tree species. Photo imagery is a promising non-destructive method for estimating the aboveground biomass of tree seedlings. This method was tested using naturally regenerated white spruce (Picea glauca (Moench) Voss) seedlings growing in the understory of a mixed conifer shelterwood in central Ontario. In the fall of 1997, 45 seedlings were sampled from plots exposed to one of three mechanical release treatments (early spring release, mid summer release, and no release (control)) in 1994. Each seedling was photographed in the field to measure the vertical projected area (silhouette area) of the aboveground portion of the seedling. Seedlings were harvested, basal diameter and total height measured, and biomass (dry mass) of foliage, branches, main stem and total aboveground plant tissue determined. Regression analysis revealed a strong relationship between both silhouette area and basal diameter, and seedling biomass. Coefficients of determination for regression equations using silhouette area were equal to 0.892, 0.918, 0.926, and 0.937 for the main stem, branches, foliage, and total aboveground biomass, respectively. Respective coefficients of determination for regression equations using basal diameter were 0.960, 0.945, 0.953, and 0.977. Silhouette area-based equations for total aboveground and foliar biomass differed significantly (P < 0.005) among release treatments. No significant differences among treatments were observed between silhouette area-based equations for biomass of branches and main stem (P > 0.05), or between basal diameter-biomass (allometric) equations for all components (P > 0.1). The method was then tested by validating the biomass equations using an independent data set from 35 white spruce seedlings from the same site and cohort, but exposed to different treatments and microenvironmental conditions. For each seedling, biomass components were predicted using silhouette area-based and allometric equations, and a relative error of prediction calculated. The mean relative error for silhouette area-based predictions varied among biomass components from −20.25% to −3.21%, with standard deviation of the error ranging from 23.04% to 33.44%. The mean relative error for allometric equations ranged from −2.46% to −21.75%, with standard deviations of 23.34% to 32.61%. These results suggest that: (1) photo imagery can be used as an alternative to more traditional allometric methods of biomass estimation, and (2) general (developed for a broad range of growing conditions) equations derived by either method are preferable to those specifically calibrated for a given growing environment.
- Subjects
BIOMASS; WHITE spruce; TREE seedlings; FOREST management
- Publication
New Forests, 2000, Vol 20, Issue 2, p145
- ISSN
0169-4286
- Publication type
Article
- DOI
10.1023/A:1006716406751