摘要:选取西南喀斯特地区次生林中主要优势植物刺楸（Kalopanax septemlobus（Thunb.）Koidz.）、香椿（Toona sinensis）和化香（Platycarya strobilacea Sieb.et Zucc.）为研究对象，通过对不同土壤深度的土壤水、泉水、雨水和植物采样，利用氢氧稳定同位素技术，借助IsoSource和MixSIAR两种模型分析植物水分来源，通过直接相关法判断植物主要吸水源来衡量两种模型的适用性。结果表明，降雨δ¹⁸O值在3月-6月偏正，在6月-8月数据偏负，存在明显的季节变化。在春季不同土壤层土壤水δ¹⁸O值土壤深度增加而降低，夏季呈现相反的规律。基于IsoSource和MixSIAR模型计算植物不同水分来源比例时存在一定差异。基于直接相关法定性分析植物水分来源表明MixSIAR模型计算结果可靠性高于IsoSource模型。基于均方根误差（Root Mean Square Error，RMSE）进行模型评价，结果显示出MixSIAR模型的RMSE结果小于IsoSource模型，表明利用MixSIAR模型计算植物对各水源的利用比例适用性高于IsoSource模型。本文结果有助于在解析植物水分来源时为模型的选择提供参考。



Abstract:Plant water source is a prerequisite for research and management of agriculture and ecology. Especially in Karst areas, due to the special geological conditions, plants are prone to generally suffer in severe water deficit. Understanding the plant water sources is therefore important for ecological restoration. In this study, the main dominant plants in the secondary forest of southwest karst regions, Kalopanax septemlobus (Thunb.) Koidz., Toona sinensis and Platycarya strobilacea Sieb.et Zucc. were selected. Isotopic samples of soil moisture at different soil depth, spring water, rain water and plants were collected. We analyzed the plants water sources by IsoSource and MixSIAR models, and the performance of the two models were compared. The results showed that the δ¹⁸O values of rainfall were positive during March to June, while these values were negative during June to September, 2017. Thus, the δ¹⁸O of rainfall exhibited the significantly temporal or seasonal variations. The δ¹⁸O values of soil moisture at different soil layers decreased with the increase of soil depth in spring, while this circumstance was contrary in summer. There were significant differences in calculating the proportion of plants water sources between IsoSource and MixSIAR models. The analysis of plant water sources based on the direct inference approach showed that the performance of MixSIAR model was better than that of IsoSource model. The performance of MixSIAR model (Root Mean Square Error (RMSE), 0.61 in spring and 0.59 in summer) outperformed the IsoSource model (RMSE, 0.84 in spring and 0.74 in summer) in estimating the plants water sources. The results of the study can provide a beneficial guide in model decision for the future researchers in plant water sources.





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