| 摘要 |
[Objectives] This study was conducted to provide good basic research data for Cunninghamia lanceolata plantations in southern Anhui, so as to improve local ecological, economic and social benefits. [Methods] A 22-year-old near-mature C. lanceolata plantation in Lingnan Forest Farm, Xiuning County, Huangshan City, Anhui Province was investigated and analyzed by sample plot survey. [Results] The average DBH value of the C. lanceolata plantation at the lower slope was the largest, 24.7% and 19.2% higher than those at the upper and middle slopes, respectively. The average single plant wood volume at the lower slope was 47.6% and 49.1% higher than those in the upper and middle slopes, respectively. However, the average tree heights at various slope positions showed little difference. Meanwhile, all the indexes showed the phenomenon of semi-shady slope>sunny slope>shady slope under different slope directions. Among them, the effect of slope position on DBH was extremely significant, but the effect of slope direction on DBH was not significant, and slope position, slope direction and the interaction of slope direction and slope position had no significant effects on the tree height of the C. lanceolata plantation. In addition, slope direction and slope position had extremely significant effects on single plant wood volume. From the overall growth situation of the C. lanceolata plantation in Lingnan Forest Farm, the slope position factor had greater effects on various indexes of forest growth than the slope direction factor, mainly manifested in that the lower slope was better than the middle slope, and the middle slope position was better than the upper slope, while although slope direction had some effect on the growth of the C. lanceolata plantation, the influence degree was not as significant as that of slope position. [Conclusions] This study provides some reference for the adjustment and optimization, development and renewal of C. lanceolata plantation structure in the later period in this area, as well as some data support for other theoretical research on economic forests. |
