Modeling light competition in the forests of western Oregon Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/0r967728m

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  • A plant's immediate neighborhood reflects its realized level of competitive stress, since competition and natural selection act at the individual level. In stands with continuous canopies competition for light is the dominant spatial interaction. Over 100 spatially explicit indices have been used to characterize the local competitive environment in models of individual tree growth. These indices can be divided into those that indirectly characterize the light environment and those that directly characterize the light environment. The three classes of indirect measures are: size-distance, competitive influence zones, growing space and the two classes of direct measures are open sky views and light-interception methods. Studies that have compared the ability of the indirect indices of the light environment have failed to identify a universally superior measure of competition. However, the two direct measures of the light environment have not been included in the comparisons. An examination of the comparative studies showed that most of them identify indices characterizing competition from larger neighbors as superior. This finding leads to the conclusion that competition for light is the dominant spatial interaction in the stands examined. Thus, spatial indices that directly quantify light should explain more variation than those that quantify both above and below ground competition. Light intensity is modeled with the radiation transport equations. SEALS is a program for calculating light intensity in forest stands. It uses the radiation transport equations to model seasonal quantum light flux (SAL). It uses simulated hemispherical photographs to model direct beam light intensity (PCSHS). SAL and PCSHS were compared to three indirect measures of light competition in a planted western hemlock understory and 11 managed Douglas-fir plots. It was found that SAL reduced the residual variation in height growth of understory western hemlock by 48% over a model including only a power of tree height and PCSHS reduced the residual variation by 40%. SAL also reduced residual variation by 48% for overstory Douglas-fir and 18% for understory Douglas-fir while PCSHS reduced the residual variation by 15% and 14% respectively. These reductions were significantly better than those from the indirect classes of spatially explicit index.
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