EFFECTS OF BASAL AREA OR DENSITY AS SAMPLING METRICS ON OAK WOODLAND CLUSTER ANALYSES

This study compared the effects of sampling metrics (basal area and de nsity of trees) on cluster analyses of oak woodland vegetation. Minimu m-variance clustering was used to define communities within oak woodla nds. Communities derived from basal area data were more distinct and m ore homogeneous than communities derived from density data. Consistent with previous research, minimum-variance clustering of basal area dat a produced groups of approximately equal size. In contrast, minimum-va riance clustering of density data did not result in similar-sized grou ps. Formation of similar-sized groups, which is generally reported to be an advantage of minimum-variance clustering, apparently is dependen t on the sampling metric employed.