Circular distributions of fallen logs as an indicator of forest disturbance regimes

We present a retrospective method for studying forest disturbance regimes, and especially the role of windthrows, based on circular statistical models of directions of fallen logs. This approach was applied to fallen log data from three areas of pristine Picea abies-dominated boreal forests in northern Europe. The data consisted of 5 plots from each of the three areas, totaling 15 plots and covering an area of 24 ha. The disturbance history of the plots, which varied from area to area, was known from previous detailed studies. We selected and fitted the most suitable circular model for each plot, based on goodness-of-fit and the Akaike information criterion. For uneven-aged forests, the symmetric von Mises distribution, was best fitted, while for the even-aged forest the sine-skewed wrapped Cauchy distribution was selected. The degree of concentration around the mean direction of fallen trees was strongest for the late-successional even-aged forest most exposed to windthrow, while an uneven-aged forest with drought-driven mortality had the lowest concentration and the greatest variance over the mean directions. For the third area, characterized by an uneven age structure and tree mortality driven by heart-rot fungi in old trees in interaction with wind, an intermediate between these two were derived. Our results suggested the utility of circular distributions of fallen logs and their statistical models for retrospective assessments of forest disturbance regimes.