中文摘要：

[目的]植物残体是沼泽湿地古生态学研究的重要生物指标,现代植被与环境因子的转换函数为准确定量重建古环境和古气候提供了有效途径。[方法]本文利用R软件＂rioja＂软件包中的加权平均（Weighted Averaging,WA）和加权平均偏最小二乘法（Weighted Averaging Partial Least Squares,WAPLS）模型,以三江平原不同类型植物群落数据与相应的水位数据为样本,建立现代植被-水位转换函数。[结果]WAPLS模型的预测性能比WA模型好,WAPLS模型第3组分的预测性能最好,有最低的RMSEP值（3.69m）和最高的R2值（0.52）。经数据过滤后,两个模型的预测性能有所提高,其中WAPLS模型第4组分的预测性能最好,RMSEP为2.83,降低了23.3%,其精度达到了±2.83cm,结果较理想。[结论]研究结果可为三江平原古水位定量重建提供方法支撑,提高其准确性。

英文摘要：

[Objective]Plant macrofossil is an important biological proxy for palaeoecology study.The transfer function of vegetation-water level can provide an effective way to reconstruct accurate quantitative palaeoenvironment and palaeoclimate.[Methods]In this paper,the WA（Weighted Averaging）and WAPLS（Weighted Averaging Partial Least Squares）models of riojapackage in R were used to establish the vegetation-water level transfer function of Sanjiang Plain.[Results]The results showed that the prediction performance of the WAPLS model was better than that of the WA model.The third component of the WAPLS model had the best prediction performance,with the lowest RMSEP value（3.69m）and the highest R2 value（0.52）.After data filtering,the prediction performance of the two models were improved,the prediction performance of the fourth component of the WAPLS model was the best,with the lowest RMSEP 2.83,which reduced by 23.3% compared to the previous value.The accuracy reached to±2.83 cm,this result was relatively ideal.[Conclusion]This study provided a method and guarantee for the accurate quantitative reconstruction of the water level in Sanjiang Plain.