Study of Quantitative Relationships Between Vegetation and Pollen in Surface Samples in the Eastern Forest Area of Northeast China Transect
Study of Quantitative Relationships Between Vegetation and Pollen in Surface Samples in the Eastern Forest Area of Northeast China Transect
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发表时间：
2000-01
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通讯作者：
Liu Yi-yin;Zhang Xin-shi;Zhou Guang-sheng
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作者：
Liu Yi-yin;Zhang Xin-shi;Zhou Guang-sheng
以东北中国样带东部林分为研究对象，研究了地表样品中植被与花粉的数量关系。计算了各花粉类型的A(联结指数)、O(超代表性指数)、U(欠代表性指数)、C(相关系数)和R(代表性系数)。结果表明，地表样品中植被与花粉类型的相关性显著，70%的花粉类型相关系数在0.5以上(α=0.0 5)，花粉组合与植物群落相似性较好，相似性系数在5 0%以上。通过TWINSPAN分类和主成分分析，将69种花粉类型按A、O、U、C划分为4个类群，反映了植物的授粉特性和花粉在土壤中的保存状态。第一类是能准确反映当地植被的联合类群；第二类是超代表性类群，其花粉比例与植被比例不成比例；第三类群是次代表性类群，其花粉很难从土壤中获得；第四类群也是次代表性类群，在植物直接生长的土壤中很容易获得花粉。研究还表明，A是一个校正花粉数据的参数，比参数R更容易获得。参数A与R关系密切，其回归方程为：A=-0.042 1R2+0.242 5R+0.392 6(R2=0.602 1)。这些类群和指数为利用花粉数据准确恢复植被提供了坚实的基础。
The eastern forest stands of Northeast China Transect (NECT) were chosen to study the quantitative relationships between vegetation and pollen in surface samples. The indices of A (association index), O (over_representation index), U (under_representation index), C (correlation coefficient) and R (representation coefficient) for each pollen type were calculated. The results indicated that the relationships between vegetation and pollen type in surface samples were significant and the correlation coefficients of 70% pollen types were more than 0.5 (α=0.05); the similarity between pollen assemblage and plant community was good and coefficient of similarity was more than 50%. 69 pollen types found in the surface samples could be divided into four groups with TWINSPAN classification and PCA ordination according to A,O,U and C. The four groups reflected the pollination characteristic of plants and the state of pollen conserved in soil. Group 1 was the associative group which could accurately reflect the local vegetation; Group 2 was over_representative group which had high pollen percentage outproportional to vegetation; Group 3 was the under_representative group in which the pollen were hardly obtainable from the soil, and Group 4 was also an under_representative group, in which pollen were easily obtainable in soil where plants directly grow from. The study also showed that A was a parameter to rectify pollen data and it was easier to obtain than parameter R . The parameters A and R have close relation and their regression equation was: A=-0.042?1R 2+0.242?5R+0.392?6(r 2=0.602?1). These groups and indices provide a solid foundation for using pollen data in accurately reinstating vegetation.