Abstract
An individual tree-based forest succession model was modified to simulate a forest stand as a grid of contiguous 0.01-ha cells. We simulated a 9 ha stand for 750 years and sampled the stand at 50 yr intervals, outputting structural variables for each grid cell. Principal components analysis was used to depict temporal patterns in forest structure as observed in 0.01 ha samples (individual grid cells). We then resampled the grid using square aggregates of 4 to 100 grid cells as quadrats. Principal component scores recalculated for the aggregates, using the original (0.01 ha scale) scoring matrix, depict the effects of obervational scale on perceived patterns in forest structure. Larger quadrats reduce the apparent variation in forest structure and decrease the apparent rate of structural dynamics. Results support a scale-dependent conceptualization of forest systems by illustrating the qualitative difference in forest dynamics as viewed at the scale of individual gap elements as compared to the larger scale steady state mosaic. The aggregation exercise emphasizes the relationship between these two observational scales and serves as a general framework for understanding scaling relationships in ecological phenomena.
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