Spatial distribution pattern and intraspecific association of dominant species Quercus aliena var. acu-tiserrata in Qinling Mountains, China

Abstract

To explore the spatial distribution and intraspecific correlation of Quercus aliena var. acutiserrata, a domi-nant tree species in a 25 hm2 plot of warm temperate deciduous broadleaved forest in Qinling Mountains, the pair-correlation function g(r) was used to study the spatial pattern and intraspecific association. The results showed that the diameter class structure of Q. aliena var. acutiserrata was bimodal, with a large proportion of young trees (1 cm≤DBH＜5 cm), indicating an increase population structure with good capability of regeneration. The abundance of middle trees (15 cm≤DBH＜25 cm) was slightly more than that of big trees (25 cm≤DBH＜35 cm) and old trees (DBH≥35 cm), but far less than that of young trees and small trees. The spatial distribution of Q. aliena var. acuteserrata was obviously altitude dependent, which mainly distributed in the middle and high altitude areas. Results of complete spatial randomness (CSR) model analysis showed that young trees, small trees, adult trees, big trees, and old trees were aggregated in the large scale (＜60 m). Heterogeneous Poisson (HP) model was used to eliminate habitat heterogeneity. The results of HP model showed that the individual aggregation degree of each diameter class decreased, indicating that the distribution was affected by habitat heterogeneity. At the small scale (＜40 m), spatial correlation was positively correlated between individuals with small diameter gap, whereas the spatial correlation was negative correlation and no correlation between individuals with large diameter gap. At large scale (>40 m), the spatial correlation was positively correlated between large-diameter individuals, but negatively correlated and unrelated between saplings and other diameter individuals. Our results indicated that biological cha-racteristics of Q. aliena var. acutiserrata and habitat heterogeneity were important drivers for the formation of population spatial pattern.