Understory diversity prediction of urban forest based on the redundancy analysis (RDA)
基于冗余分析的城市森林林下层植物多样性预测

In this paper, four diversity indexes were considered as quantitative indicators of understory for urban forest, while the features of environment variables were recorded at the corresponding quadrat scale. By applying the redundancy analysis (RDA) the control factors that affect understory diversity in urban forest were extracted and the contributions to understory diversity were further disclosed. RDA results showed that litter cover, distance to the forest edge, road area and garbage four\|variables were the minimum variables combination which can significantly explain the understory plant diversity, with 61% information explaination. The 10 variables could explain 72.1% of all information. Based on the RDA, 10 environmental variables and understory features were performed duplicato bolting stepwise regression. The result showed that herb density and altitude, slope, distance to forest edge, litter cover were significantly related; Pielou evenness of herb significantly related with the altitude, slope, canopy cover, litter cover and rock cover; Simpson diversity of herb significantly related with slope, litter cover, distance to forest edge, rock cover and stake; Pielou evenness of shrub significantly related with altitude, canopy cover, road area and rock cover.