Abstract
Functional characteristics reflect plant strategies and adaptability to the changing environment. Determining the dynamics of these characteristics after harvesting would improve the understanding of forest response strategies. Strip clearcutting (SC) of moso bamboo forests, which significantly reduces the cutting cost, has been proposed to replace manual selective harvesting. A comparison of restoration features shows that 8 m is the optimal cutting width. However, the precise response of functional features to the resulting harvest-created gap remains unclear. In this study, three SC plots were selected which was performed in February 2019, with three unharvested plots as a control (C). The study focused on 10 functional traits, including leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), leaf nitrogen content (LNC), leaf phosphorus content (LPC), nitrogen/phosphorus ratio (N:P), wood density (WD), fine root biomass (FRB), specific fine root length (SRL), and root length density (RLD). A one-way ANOVA was used to compare differences in functional traits and soil nutrients between treatments. Strip clearcutting significantly reduced the soil organic carbon (SOC) and total nitrogen (TN) contents (p < 0.05). In terms of functional characteristics, SC significantly decreased LA and increased LNC, LPC, and N:P (p < 0.05). However, SC had no significant effect on fine root traits (p > 0.05). This study highlighted that root trait, soil content of total phosphorus (TP) and total potassium (TK) returned to the level of uncut plots after a year’s recovery. The LPC, LNC, and N:P were negatively correlated with LA, and LDMC and WD were negatively correlated with SLA, while the effect of SC on fine root traits was limited (p > 0.05). Fine root traits (FRB, RLD, and SRL) were positively associated with SOC, TN, and TP, but negatively correlated with TK. The changes in soil nutrient content caused by the removal of biomass were normal. Increased light and the rapid growth of new trees will increase nutrient regressions; therefore, these results further confirm the feasibility of SC.
Highlights
China has an extensive range of bamboo species, which are widely distributed in the country
The principal component analysis (PCA) analysis showed that leaf phosphorus content (LPC), leaf nitrogen content (LNC), and N:P were negatively correlated with leaf area (LA)
The leaf dry matter content (LDMC) and wood density (WD) were negatively correlated with specific leaf area (SLA)
Summary
China has an extensive range of bamboo species, which are widely distributed in the country. The high cost of harvest, caused by a shortage of labor, has become a practical problem in its production. This expense has reduced the interest in artificial management, and many bamboo plantations are neglected. High densities of moso bamboo adversely affect understory vegetation and nutrient cycling [3]. These problems have reduced productivity and bamboo production, and have serious effects on the sustainable management of plantations. There is, increasing demand for cost reductions in the management of moso bamboo forest
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