Spatial pattern dynamics among co-dominant populations in early secondary forests in Southwest China

Abstract

The canopy of subtropical natural forests usually consists of several co-dominant populations (CDPs), which play a crucial role in forest structure, formation of the forest environment, and ecological function. However, little attention has been given to changes in spatial patterns in CDPs during natural succession. Cyclobalanopsis glauca (Thunb.) Oerst., Quercus variabilis Blume, and Pinus yunnanensis var. tenuifolia W.C. Cheng & Y.W. Law are canopy species that form CDPs in zonal forests along the Nanpan River in southwest China. We used the g(r) function and its bivariate distribution model, g12(r), which is based on distances between pairs of points, to explore the dynamics of the three CDP species with respect to distribution patterns and spatial correlations in two secondary forests (one 30-year-old forest [30-YF] and one 57-year-old forest [57-YF]). The following key results were obtained: (1) there was a clumped pattern in the 30-YF, but the intensity of aggregation varied among populations and life stages. The distribution pattern gradually shifted to become random with longer succession time (i.e., 30-YF vs. 57-YF), expansion of the observation scale (r = 0–20 m), and at later life stages. (2) Aside from the mid-sized C. glauca trees and large P. yunnanensis trees, the trees repulsed each other at certain scales (r = 0–2, 5–6, 11–12, 14–16 m) in the 30-YF. Almost all of the life stages in the CDPs were independently correlated. This independent correlation was exacerbated by a longer succession time. (3) An increase in life stages and longer succession also promoted independent changes in intraspecific correlations. (4) Intraspecific correlations were stronger than interspecific correlations. Our results showed that reducing exclusive competition is essential to coexistence in CDPs. Inter- and intra-specific repulsion may occur at the same time, but intraspecific repulsion was the main driving force behind the random distributions and independent correlations.