Changes in vegetation–environment relationships over long-term natural restoration process in Middle Taihang Mountain of North China

Understanding relationships between vegetation and environmental variables is very important for ecosystem restoration and management efforts in middle Taihang Mountain of North China, However, information on how environment factors influence the long-term natural restoration process is lacking. The objective of this research is to identity controlling environmental variables over natural restoration process in middle Taihang Mountain of North China using multivariate techniques of detrended correspondence analysis (DCA) and redundancy analysis (RDA). Vegetation and soil surveys were performed in 144 permanent sampling plots in Niujiazhuang Catchment in 1986 and 2008. Vegetation variables include shrub height, shrub coverage, shrub biomass, herb height, herb coverage, herb biomass, species richness (S), Shannon–Wiener's (H), Simpson's predominance index (D), and evenness index (Jsw). Topographic variables include elevation, slope, slope position, and slope aspect. Soil variables include soil thickness, humus thickness, rock content, soil organic matter, and total N, P, and K. Results indicate that the most important factors that influence the composition of vegetation assemblages (diversity, distribution and above-ground biomass) were total K in 1986 and total P in 2008. Also, the results suggest significant correlations among vegetation variables, soil nutrient contents, and topographic variables. For example, total N, P, and K were positively correlated with soil organic matter significantly. Relationships between vegetation and environmental variables over long-term natural restoration provide some valuable implications for regional ecological restoration and land management. To restore the degraded ecosystems, maintain the diversity and structure of ecosystems in middle Taihang Mountain, we should consider the co-evolution of both vegetation and soil, and also natural succession sequence.