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曾祥明,徐宪立,钟飞霞,易汝舟,徐超昊,张耀华.MixSIAR和IsoSource模型解析植物水分来源的比较研究.生态学报,2020,(16).http://dx.doi.org/10.5846/stxb201910302294  
MixSIAR和IsoSource模型解析植物水分来源的比较研究
Comparative study of MixSIAR and IsoSource models in the analysis of plant water sources
投稿时间:2019-10-30  修订日期:2020-04-23
DOI: " target="_blank" title="转向doi官网查询:http://dx.doi.org">10.5846/stxb201910302294
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基金项目国家自然科学(41571130073);中国科学院创新交叉团队
作者单位E-mail
  364052559@qq.com 
  xianlixu@isa.ac.cn 
   
   
   
   
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摘要:
本研究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值随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 δ 18O values of rainfall were positive during March to June, while these values were negative during June to September, 2017. Thus, the δ 18O of rainfall exhibited the significantly temporal or seasonal variations. The δ 18O 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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