Modern silviculture is shifting from even-aged management toward sustainable management of the diversity of forest communities. Traditional growth-and-yield models are too simple for this new approach, but mechanistic models that can incorporate the complexity are too general. This shift in emphasis presents important scientific challenges and creates a critical need to update our modeling approaches. One response has been to manage forests by mimicking natural disturbance. Windstorm is the dominant natural disturbance in forests of northeastern North America. In Chapter 1, I use a mechanistic model (SORTIE) to explore the sensitivity of forest composition and structure to the resistance of individual trees to wind disturbance and the roles of local dispersal and seedling establishment. The results show that species-specific resistance to wind: drives the community response to disturbance; interacts with local dispersal patterns to influence succession; and interacts with seedbed substrate dynamics to influence canopy population dynamics. Biotic disturbances are also an important natural disturbance in these forests. In Chapter 2, I quantify how the presence of beech bark disease (BBD) alters the resistance of beech to uprooting and stem break, and explore the sensitivity of forests to subsequent increases in coarse woody debris (CWD). Results show that small seeded species increased in basal area primarily due to the increase in CWD caused by BBD. The results highlight the important indirect effects that pathogens can have on forest community dynamics. Managing complexity also requires improving our understanding of competition among trees and species responses along environmental gradients. In Chapter 3, I use USFS FIA data to analyze the effects of competition on tree growth along gradients for eight tree species in New England. I use information theory to determine the relative weight of evidence for each model. No species showed strong evidence in support of one model over others, implying that the robustness of predictions based on the selected best model is questionable. The complexity of competitive interactions and growth along gradients and the importance of including secondary effects via model averaging highlight key challenges for the management of mixed-species, uneven-aged stands.
| Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:dissertations-4080 |
| Date | 01 January 2005 |
| Creators | Papaik, Michael J |
| Publisher | ScholarWorks@UMass Amherst |
| Source Sets | University of Massachusetts, Amherst |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | Doctoral Dissertations Available from Proquest |
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