Optimization of application parameters of soil seed bank in vegetation recovery via response surface methodology

• We optimized three parameters using response surface methodology methods.
• We found two different models according to different response values.
• Two optimal schemes of soil seed banks were found after optimization.
• Thickness of surface soil was the most important factor for soil seed banks.

Studies using the Box–Behnken central composite design (BBC) combined with response surface methodology (RSM) were conducted for the purpose of maximizing community indexes of soil seed banks (SSBs). 33 factorial designs were based on three independent variables: thickness of surface soil, covering thickness and the number of added tree seeds. Two comprehensive indexes with the name Component 1 and Component 2 (C1 and C2) abstracted by principal component analysis (PCA) from seven community indexes were used as two response values. The quadratic model was selected when the response value was C1, while the 2F1 model was more suitable when the response value was C2. ANOVA results showed that both models were significant, expressing ideal relationships between all independent and dependent variables. The optimum conditions of C1 and C2 were determined with the thickness of the surface soil of 4.17 cm and 4.75 cm respectively with a covering thickness of 2.37 cm and 1 cm, and the number of added tree seeds of 275 seeds/m2 and 151 seeds/m2 respectively. For the quadratic model, there were interactive effects between A and B and A and C. Of the three dependent variables, thickness of surface soil was the most important, having the most important influence on SSBs. The effect of the number of added tree seeds was more significant for C1 compared to C2, while the effects of the covering thickness on both C1 and C2 were less marked. The optimal schemes of SSBs can provide guidance for vegetation recovery when using a SSB, but a more practical experiment should be carried out for more exact results.