SPATIAL AUTOCORRELATION IN GROWTH OF UNDISTURBED NATURAL PINE STANDS ACROSS GEORGIA

Moran's I statistic measures the spatial autocorrelation in a random variable measured at discrete locations in space. Permutation procedures test the null hypothesis that the observed Moran's I value is no greater than that expected by chance. The spatial autocorrelation of gross basal area increment is analyzed for undisturbed, naturally regenerated stands in three Georgia forest types: loblolly, shortleaf, and slash pine. The analysis uses 0.4-ha permanent sample plots from a forest inventory that included two remeasurement intervals (1961-1972 arid 1972-1982). We present a new statistic for exploratory spatial analyses, and this statistic revealed an anomalous duster of unusually slow-growing shortleaf pine plots occurred in the mountains 100 km north of Atlanta. A regression model was used to predict gross basal area increment as a function of variables that describe local stand conditions, and no significant spatial autocorrelations existed in the regression residuals. This result suggests that the anomalous cluster of slow-growing plots can be explained by the spatial distribution of local stand conditions rather than spatial patterns of other possible causes such as air pollution, although alternative interpretations are possible.