Balance between facilitation and competition determines spatial patterns in a plant population

A considerable challenge in plant ecology is to understand how interactions, such as competition or facilitation, shape the spatial distribution of plants. The “stress gradient hypothesis” predicts that facilitation and competition will vary inversely across gradients of abiotic stress or consumer pressure. Surprisingly, few previous studies have explored how the balance between facilitation and competition affects spatial patterns along gradients of stress in a plant population based on field experiments. In order to investigate the effects of consumer pressure, facilitation, and competition on the spatial pattern of plant populations, we conducted a restoration succession series field experiment in the Inner Mongolian steppe in which sample sites of graded consumer pressure, specifically grazing stress, were established. We chose to examine the spatial patterns of Leymus chinensis, a dominant species in our experimental site. In order to test the “stress gradient hypothesis,” we applied the univariate O-ring statistic to analyze local neighborhood density at different spatial scales. We used the pair-correlation function to detect the characteristics of point patterns using complete spatial randomness, the Poisson cluster process, and the nested double-cluster process. We found that the local densities of L. chinensis were higher under high stress than lower stress environments. This demonstrated the “stress gradient hypothesis” in that facilitation and competition varied inversely across gradients of consumer pressure. However, we found no differences in the spatial patterns of L. chinensis based on complete spatial randomness when interactions shifted from facilitation to competition along gradients of consumer pressure. Furthermore, we detected the characteristics of point patterns using the Poisson cluster and nested double-cluster processes. The results showed the spatial patterns of L. chinensis to fit well with the nested double-cluster model under highly stressful conditions, while in lower stress environments they were best approximated by the Thomas process. Our results illustrate that a shift in interactions from facilitation to competition along gradients of consumer pressure can shape spatial patterns and that a combination of the Poisson cluster process and nested double-cluster process can detect spatial pattern characteristics which cannot be detected by complete spatial randomness.