Data from: Spatial patterns and interspecific associations among trees at different stand development stages in the natural secondary forests on the Loess Plateau, China
Gu, Li; O’Hara, Kevin; Li, Weizhong; Gong, Zhiwen (2020), Data from: Spatial patterns and interspecific associations among trees at different stand development stages in the natural secondary forests on the Loess Plateau, China, Dryad, Dataset, https://doi.org/10.5061/dryad.hk31vm7
Quercus wutaishansea populations on the Loess Plateau are currently becoming more dominant in natural secondary forests, whereas Pinus tabulaeformis is declining. In the present paper, the diameter class (instead of age) was used to classify the different growth stages as juvenile, subadult, or adult, and the univariate function g(r) was used to analyze the dynamic changes in spatial patterns and interspecific associations in three 1‐ha tree permanent plots on the Loess Plateau, NW China. Our results suggested that the niche breadth changed with the development stage. The diameter distribution curve was consistent with the inverted “J” type, indicating that natural regeneration was common in all three plots. There was a close relationship between the spatial pattern and scale, which showed significant aggregation at small distances, and became more random as distance increased, but in the Pinus + Quercus mixed forests, the whole species were aggregated at distances up to 50 m. The degree of spatial clumping decreased from juvenile to subadult and from subadult to adult. The spatial pattern also differed at different growth stages, likely due to strong intraspecific competition. Associations among different growth stages were positively correlated at small scales. Our study is important to the understanding of the development of the Q. wutaishansea forests; thus, the spatial dynamic change features should be received greater attention when planning forest management and developing restoration strategies on the Loess Plateau.
southeastern Loess Plateau in northern Shaanxi Province