Corrections for cluster-plot slop.

Cluster-plot designs, including the design used by the Forest Inventoryand Analysis program of the USDA Forest Service (FIA), are attended by a complicated boundary slopover problem. Slopover occurs where inclusion zones of objects of interest cross the boundary of the area of interest. The dispersed nature of inclusion zones that arise from the use of cluster plots precludes the use of most of the slopover-correction methods that apply to solitary plots. One exception is the walkthrough method, which corrects for slopover bias in radially symmetric cluster-plot designs. In this article, we provide a modification of the walkthrough method, the "walkabout method," which is applicable to some asymmetric cluster-plot designs, such as the one used by FIA. We also present two general correction methods, the "vectorwalk method" and the "reflection method," both of which are applicable to cluster-plot designs with satellite subplotsarranged in a regular or irregular pattern. The reflection method has two sets of protocols, one that applies to radially symmetric designs and to asymmetric designs with random orientation; the other set applies to asymmetric designs with fixed orientation. Both the vectorwalk and reflection methods incorporate the walkthrough method on a subplot-by- subplotbasis. All four methods correct for slopover bias for straight or curved boundaries, and where work outside the tract is impossible. FOR .S CI. 52(1):55-66. LUSTER-PLOT DESIGNS, which are widely used to estimate forest inventories, tend to complicate the problem known variously as slopover, boundary overlap, or edge effect. Slopover occurs where inclusion zones of objects of interest cross the boundary of the area of interest. Slopover can lead to bias in estimates unless cor- rective measures are taken. In this article we describe four methods that solve the slopover problem for cluster plots. The walkthrough method (Ducey et al. 2004) solves the problem for radially symmetric cluster-plot designs, and a new variant of the walkthrough method—the walkabout method—solves the problem for some asymmetric cluster- plot designs, including the design used by the USDA Forest Service in its nationwide Forest Inventoryand Analysis (FIA) program. We also present two general methods, the vectorwalk and reflection methods, that solve the slopover problem for both symmetric and asymmetric cluster-plot designs, including the FIA design. Finally, we discuss and compare the practical implications of the four correction methods, and we discuss the choice of symmetric versus asymmetric designs. Sampling sans Slopover