Integrative Biology Journals

JOURNAL OF FORESTRY RESEARCH ›› 2023, Vol. 34 ›› Issue (4): 949-962.DOI: 10.1007/s11676-022-01538-6

• Original Paper •     Next Articles

Spatial patterns of Picea crassifolia driven by environmental heterogeneity and intraspecific interactions

Changxing Zhao1, Weijun Zhao2, Ming Jin2, Jiqiang Zhou3, Feng Ta2, Lei Wang1, Wenbo Mou4, Longju Lei1, Jinrong Liu1,j, Junlin Du5, Xinglin Zhang6   

  1. 1 State Key Laboratory of Grassland Agro-Ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, 730000, Lanzhou, People’s Republic of China
    2 Academy of Water Resources Conservation Forests in Qilian Mountains of Gansu Province, 734000, Zhangye, People’s Republic of China
    3 Gansu Nonferrous Engineering Survey, Design and Research Institute, 730000, Lanzhou, People’s Republic of China
    4 State Key Laboratory of Grassland Agro-Ecosystems, School of Life Science, Lanzhou University, 730000, Lanzhou, People’s Republic of China
    5 Hexi University, 734000, Zhangye, People’s Republic of China
    6 Gansu Academy of Eco-Environmental Sciences, 730030, Lanzhou, People’s Republic of China
  • Received:2022-02-16 Accepted:2022-06-17 Online:2024-10-16
  • Contact: Jinrong Liu

Abstract:

Research on the spatial patterns of tree populations is critical for understanding the structure and dynamic processes of forests. However, little is known about how the underlying drivers shape these patterns and species interactions in forest systems. In this study, spatial point pattern analysis investigated the combined effects of intraspecific interactions and environmental heterogeneity on the spatial structure and internal maintenance mechanisms of Picea crassifolia in the Qilian Mountain National Nature Reserve, China. Data were obtained from a 10.2-ha dynamic monitoring plot (DMP) and sixteen 0.04-ha elevation gradient plots (EGPs). Under complete spatial randomness, both mature trees and saplings in the DMP demonstrated large-scale aggregation with negative correlations. In EGPs, saplings were clustered in small mesoscales, mature trees were randomly distributed, and the interactions of saplings-trees at all elevations were not correlated. By eliminating the interference of environmental heterogeneity through the inhomogeneous Poisson process, saplings in the DMP and EGPs were clustered in small scales and trees randomly distributed. Intraspecific associations were negatively correlated, in the DMP and at low elevations, and no correlations in high elevations of EGPs. In the vertical scale, saplings showed a small-scale aggregation pattern with increase in elevation, and the aggregation degree first decreased and then increased. The interactions of saplings-trees and saplings–saplings showed inhibitions at small scales, with the degree of inhibition gradually decreasing. Spatial patterns and associations of adults–adults did not change significantly. The results revealed that intraspecific interactions and environmental heterogeneity regulated the spatial patterns of P. crassifolia at small and large scales, respectively. Environmental heterogeneity might be the most decisive factor affecting the spatial patterns of saplings, while trees were more affected by intraspecific interactions. Moreover, competition between trees in this area could be more common than facilitation for the growth and development of individuals.

Key words: Picea crassifolia, Spatial point pattern analysis, Intraspecific interactions, Environmental heterogeneity