Information Processing by Tree Fellers: Signal Detection Analysis

Eighteen experienced tree fellers and eighteen forestry students watched video recordings of mature eucalypts being felled by a man using a chain saw, and then rated whether each tree had fallen normally or abnormally. Signal-detection analysis showed that the tree fellers were more accurate than the forestry students in predicting eventual outcome. Further, the tree fellers achieved peak accuracy in discrimination by the time the logger had completed cutting the scarf (typically several minutes before the tree hit the ground), whereas the forestry students predicted outcome most accurately only when a tree was falling (and about 1 s from hitting the ground). Study of the bases for information processing and decision making by tree fellers has implications for personnel selection and training, as well as for formulation of effective work practices.