Efficiency of sample-based indices for spatial pattern recognition of wild pistachio (Pistacia atlantica) trees in semi-arid woodlands

Abstract

The efficiency of sample-based indices proposed to quantify the spatial distribution of trees is influenced by the structure of tree stands, environmental heterogeneity and degree of aggregation. We evaluated 10 commonly used distance-based and 10 density-based indices using two structurally different stands of wild pistachio trees in the Zagros woodlands, Iran, to assess the reliability of each in revealing stand structure in woodlands. All trees were completely stem-mapped in a nearly pure (40 ha) and a mixed (45 ha) stand. First, the inhomogeneous pair correlation function [g(r)] and the Clark–Evans index (CEI) were used as references to reveal the true spatial arrangement of all trees in these stands. The sampled data were then evaluated using the 20 indices. Sampling was undertaken in a grid based on a square lattice using square plots (30 m × 30 m) and nearest neighbor distances at the sample points. The g(r) and CEI statistics showed that the wild pistachio trees were aggregated in both stands, although the degree of aggregation was markedly higher in the pure stand. Three distance- and six density-based indices statistically verified that the wild pistachio trees were aggregated in both stands. The distance-based Hines and Hines statistic (h _t) and the density-based standardised Morisita (I _p), patchiness (IP) and Cassie (C _A) indices revealed aggregation of the trees in the two structurally different stands in the Zagros woodlands and the higher clumping in the pure stand, whereas the other indices were not sensitive enough.

Keywords

Density-based indices / Distance-based indices / Pattern recognition / Wild pistachio / Woodland

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