Abstract
Horizontal point sampling is only occasionally applied under natural tropical forest conditions. Reasons for this include those relating to the complex floristic composition and structure of these forests and to the presence of unacceptable non-sampling errors resulting from missing trees and incorrect borderline tree checking procedures. Concerning the latter, results from this study, based on probabilities and data derived from computer-simulated sampling on each of three 16 ha real tree stem maps (from Surinam, Kalimantan and Thailand), suggest that there is a statistically valid practical solution. Clusters of points using large basal area factors are used to concentrate work and to ensure that less effort is required in checking the ‘in/out’ status of a borderline tree. For a given basal area factor and bulk of sample, there is no significant difference between the various cluster point layouts used — this offering flexibility in execution.
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