Graduate Thesis Or Dissertation
 

A biological classification and characterization of structure in managed, mixed-species, multi-aged stands

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/cf95jf32m

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  • Forest management requires classification of forest stands into groupings or types based on structural similarities, even when structure varies continuously along gradients. Managed, mixed-species, multi-aged forest stands often display complex structures containing extreme variation in trees size, density, and species composition, and as a result have diverse canopy structures. A classification of these stands is quite challenging and has usually been done rather subjectively. The first objective of this study was to identify and apply an effective methodology to classify stand structures in mixed-species, multi-aged stands. Cluster analysis provided an approach for objective classification of stands based on a set of structural variables available from typical inventory data. A commercial forest ownership in northern California comprised the target population. Stands investigated were primarily mixed-species, multi-cohort stands that had been managed predominantly using single tree selection methods, resulting in a diverse range of vegetation structures. Crown area profile (cross-sectional crown area per relative stand height) (Dubrasich et. al 1997) served as basis for the classification since it embodies the size, density, and crown structure attributes necessary to characterize complex stands. The stand types identified were then fully characterized and differentiated from each other with respect to various attributes allowing realization of the full benefit of the classification developed. The second objective was to fully characterize the stand types identified through cluster analysis. Three categories of attributes were regarded as most important for making silvicultural decisions in the target mixed conifer forests: 1) size distribution and density, 2) canopy structure, and 3) growth dynamics.
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