Destructive sampling of 20 trees of four tree species in a mixed New England conifer/hardwood stand shows that leaf area comprises 72, 77, and 78 percent of plant area as measured with digital hemispherical photography of the stand in (1) leaf-off, (2) leaf-out and pre-harvest, and (3) leaf-out and post-harvest conditions. Leaf area index values for the stand, estimated through destructive sampling, were 4.42, 5.98, and 5.08 respectively, documenting the progression of leaf growth through post-harvest. Terrestrial lidar scans (TLS) of the stand in (1) leaf-off and (2) leaf-out and pre-harvest conditions provided leaf area index values of 4.49 and 6.00 using the correction applied to observed plant area index, showing good agreement. The method relies on destructive sampling to relate the weight of foliage removed from sample trees to leaf area and fine twig area within the foliage as measured by a flatbed scanner. Two conifer species, eastern hemlock and white pine, and two deciduous species, red maple and red oak, in five diameter-size classes, were harvested from the 50 x 50-m stand in late summer. Leaf and twig areas of these trees provided species-specific allometric equations relating stem basal area to leaf and twig area, and a stand map provided species, counts and diameters of all trees in the plot. These data then allowed estimation of the leaf area of the stand as a whole for comparison with optical methods. The ratios of leaf to fine-branch area for each species vary, with values of 5.33, 25.38, 260.88 and 140.35 for eastern hemlock, white pine, red maple, and red oak respectively. This variance shows that woody-to-total area constants, which are used for calculating leaf area index from plant area index values determined by optical gap probability methods, will be quite dependent on stand composition and questions the common usage of literature constants for this purpose. This study shows how destructive sampling can lead to better estimation of forest leaf area index and wood area index from hemispherical photography and terrestrial lidar scanning, which has the potential to improve modeling of nutrient cycling and carbon balance in ecosystem models.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/37054 |
| Date | 05 July 2019 |
| Creators | Condon, Timothy |
| Contributors | Strahler, Alan H. |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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