William S. Keeton, University of Vermont, Rubenstein School of Environment and Natural Resources, University of Vermont, 343 Aiken Center, Burlington, VT 05401, william.keeton@uvm.edu
Disturbance- and structure-based forestry are often proposed for the maintenance of biological diversity and ecosystem functioning across the “matrix” landscape, such as forestlands providing connectivity between protected areas. In the northern hardwood region of the United States and Canada this includes managing for late-successional structure, which is vastly under-represented relative to pre-settlement conditions. One possibility is to modify uneven-aged silvicultural practices to more closely approximate fine-scale natural disturbance effects. The as yet untested hypothesis is that these approaches would result in accelerated rates of late-successional structural development and related ecological functions. I am testing this hypothesis using a variant of uneven-aged forestry, termed “Structural Complexity Enhancement (SCE),” that promotes old-growth structural characteristics. This approach is compared against two conventional uneven-aged systems (single-tree selection and group-selection) modified to enhance post-harvest structural retention. The study is replicated at two mature, northern hardwood forests in Vermont. Manipulations and controls were applied to 2 ha units. The uneven-aged treatments were replicated twice; the SCE treatment and controls were each replicated four times.
Structural objectives in SCE include multi-layered canopies, elevated large snag and downed log densities, variable horizontal density, and re-allocation of basal area to larger diameter classes. The latter objective is achieved using an unconventional marking guide based on a rotated sigmoid target diameter distribution, applied as a non-constant q-factor. The marking guide is also derived from a target basal area (34 m2/ha.) and maximum diameter at breast height (90 cm) indicative of old-growth structure. Crown release was also used to promote growth in larger trees. Prescriptions for enhancing snag and downed woody debris density are based on stand potential. Forest structure data, including Leaf Area Index (LAI), detailed measurements of individual trees, and coarse woody debris (snags and downed logs) densities and volumes, have been collected over two years pretreatment and two years post-treatment. A before/after/control/impact approach was used to analyze these data. Fifty year simulations of stand development were run in NE-TWIGS, comparing alternate treatments and no treatment scenarios. Basal area retention, relative density, canopy closure, LAI retention, and coarse woody debris volumes and densities were significantly higher under the old-growth silvicultural system. Residual diameter distributions achieved the target rotated sigmoid form. There will be significant differences in stand development based on the simulation modeling. Late-successional structural and compositional characteristics will develop to a greater degree under SCE. Large tree (>50 cm dbh) recruitment will be impaired under the conventional treatments, whereas rates of large tree development will be significantly accelerated under SCE. Siviculturalists have the flexibility to manage for wide range of structural characteristics and associated ecosystem functions. Residual basal area, maximum diameter, and q factor can be modified singly or collectively, resulting in greater structural retention. Unconventional prescriptive diameter distributions, such as the rotated sigmoid, combined with higher levels of residual basal area, very large (or no) maximum diameters, and crown release are another alternative for retaining high levels of post-harvest structure and for promoting accelerated stand development. Applications range from old-growth and riparian forest restoration to low intensity, sustainable timber management.
Keywords : silviculture, northern hardwoods, structural complexity enhancement, old-growth, natural disturbance-based management, stand structure and development