Spatial Clusters and Variability Analysis of Tree Mortality

Abstract

Spatial patterns of tree mortality are important factors in analysis of forest health and sustainable forest management. We analyzed spatial cluster characteristics of forest tree mortality among hardwoods, softwoods, and all species groups between 1989 and 1997 in Georgia. We used for this purpose the 1989 and 1997 USDA Forest Service Forest Inventory and Analysis (FIA) permanent sample plot data, spatial scan statistic and semivariogram analysis methods, and geographic information system (GIS) techniques. In Georgia, forest tree mortality for softwoods and all species groups formed clusters in North Georgia in 1989. These clusters became more widespread, but the aggregation intensity of tree mortality was decreased compared with that of the 1989 clusters. Another finding is that the locations for mortality clusters of softwoods were almost the same as those of all species combined both in 1989 and in 1997. In 1989 the forest tree mortality of softwoods and all species groups agglomerated with small clusters forming in north Georgia. In 1997, these clusters became more widespread, but the magnitudes of tree mortality within them decreased compared with those of 1989 clusters. Semivariogram analysis suggests that hardwoods, softwoods, and all species combined followed a similar trend for spatial variation in that they fit a spherical model of tree mortality. However, the strengths of spatial dependence were significantly different among the hardwoods, softwoods, and all species in 1989 and 1997. The higher the agglomeration of tree mortality, the stronger the spatial dependence. Spatial analysis of tree damage indicates that agents of tree damage were also agglomerated in the state. Eight kinds of tree damage, possibly combined with other kinds of damage, directly determined the spatial patterns of forest tree mortality. Out of these eight, only vegetation competition, insects, and weather caused the formation of the north Georgia tree mortality clusters.