【作者】 林恬；

【导师】 黄儒珠；

【作者基本信息】 福建师范大学 ， 生物化学与分子生物学， 2010， 硕士

【摘要】 测定福建万木林自然保护区12种优势植物叶片的热值、灰分含量和C、N浓度、化学组分,并比较分析热值、养分和化学组分在乔木层、灌木层、草本层的分配情况及其季节动态,以及相互间的关联,探讨万木林中亚热带常绿阔叶林生态系统能量及物质分配特征。结果表明：(1)12种优势植物叶去灰分热值(年均值21.04 kJ·g-1)显著高于世界陆生植物(年均值17.77 kJ·g-1),与中亚热带其他常绿阔叶林相比,介于纬度较高的浙江与纬度较低的广东之间,从大范围空间尺度看,遵循纬度升高热值递减的规律,表明经600多年封禁保护的万木林常绿阔叶林植物热值达到较高水平；叶C、N浓度年均值分别为47.79%(变幅44.30%～50.70%)和1.77%(变幅1.21%～2.82%)与全球陆生植物或其他地区相比,表现为C浓度高,N浓度低,即N素受限,高的C/N表明该地区植物养分利用效率高。(2)12种优势植物叶干重热值、灰分含量、去灰分热值季节变化均表现为：冬季>秋季>夏季>春季,而C、N浓度呈：夏季>春季>秋季>冬季,C/N呈：秋季>冬季>春季>夏季,且除N浓度和C/N外,其他4项指标季节间的差异达显著或极显著水平；不同植被层次植物叶干重热值、去灰分热值、C浓度均为：乔木层>灌木层>草本层,且层次间的差异达显著或极显著水平,而灰分、N素在乔木层、灌木层、草本层的分配呈多元格局。(3)12种优势植物叶干重热值、去灰分热值与C浓度极显著正相关,灰分含量与C浓度显著负相关；去灰分热值与N浓度显著正相关,干重热值、灰分含量与N浓度相关均不显著；干重热值、灰分含量和去灰分热值与C/N相关均不显著。(4)比较分析表明,富含芳香油类物质的樟科植物叶灰分含量和去灰分热值极显著高于壳斗科,干重热值也高于壳斗科,但差异不显著。(5)12种优势植物叶FTIR存在细微差异。由FTIR表征的(纤维素+半纤维素)/木质素(1154/1220)和(纤维素+半纤维素)/脂类(1154/1733)在不同植被层次均表现为：乔木层>灌木层>草本层,前者层间差异达显著水平,后者达极显著水平,结果提示,FTIR表征的上述2项指标具有区分层间植物的作用。更多还原

【Abstract】 Caloric value, ash content (AC), C and N concentration, chemical composition in leaves of 12 dominant species in Fujian Wanmulin Nature Reserve were investigated, and the allocation of which among tree layer, shrub layer, herbaceous layer and the seasonal dynamics were analyzed. Then discussed the relationships between them, in order to reveal the characteristics of the energy and matter distribution in mid-subtropical evergreen broad-leaved forest ecosystems.The results showed that:(1) The ash free caloric value (AFCV) in leaves of 12 dominant species (21.04 kJ·g-1 per year) were higher than the terrestrial plant of the whole world significantly (17.77 kJ-g-1 per year), compared with other evergreen broad-leaved forests in mid-subtropical areas of China, which was between Zhejiang province in high latitude and Guangdong province in low latitude. Considered from spatial distribution pattern, the AFCV had decreased with increasing latitude, proved that the caloric value of evergreen broad-leaved forest of Wanmulin under integrated protection system of land prohibition had got a higher level. C and N concentration in leaves of 12 dominant species were 47.79%(range from 44.30% to 50.70%) and 1.77%(range from 1.21% to 2.82%), respectively. Compared with the terrestrial plant of the whole world or other areas, C concentration was higher, N concentration was lower, appeared limited N. The ratio C to N was high revealed the nutrient use efficiency got a good level.(2) The gross caloric value(GCV), AC and AFCV of 12 dominant species had the same seasonal change patterns decreased in the following order:winter, autumn, summer and spring, then C and N concentration decreased from summer, spring, winter and autumn, and the ratio C to N was autumn> winter> spring> summer. Except N and the ratio C to N, others at least differed significantly. Under different layers in the forest, the GCV, AFCV and C content all showed tree layer> shrub layer> herbaceous layer at the significant level, and the distribution of AC and N content in different layers were more and more diversified.(3) Both GCV and AFCV in leaves of 12 dominant species were found to be significantly positive correlated with C concentration, and AC was significantly negative correlated with C concentration. The AFCV was significantly positive correlated with N content, the GCV and AC were not to be significantly with nitrogen. The GCV, AC and AFCV were not to be significantly with the ratio C to N.(4) Because of Lauraceae was rich in lipid and volatile aroma compounds, the results showed that the AC and AFCV of Lauraceae were higher than Fagaceae significantly, the GCV of Lauraceae was higher than Fagaceae but not siginificant,(5) The Fourier transform infrared Spectroscopy (FTIR) of 12 dominant species had some differences. The targets (1154/1220,1154/1733) by FTIR both showed that tree layer> shrub layer> herbaceous layer, the differences of the target (1154/1220) and (1154/1733) among layers had a significant and highly significant, respectively. Therefore, it was suggested that the two targets with FTIR, could distinguish plants from layers.更多还原