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首页> 外文期刊>Journal of Geophysical Research. Biogeosciences >Stable Oxygen and Carbon Isotopic Composition of Rice (Oryza sativa L.) Grains as Recorder of Relative Humidity
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Stable Oxygen and Carbon Isotopic Composition of Rice (Oryza sativa L.) Grains as Recorder of Relative Humidity

机译：稳定的氧气和碳同位素组成的水稻（Oryza Sativa L.）谷物作为相对湿度的记录器

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摘要

Southwest monsoon season over India exhibits spatial variation in the relative humidity (RH) levels. We took advantage of rice (Oryza sativa L.), cultivated in varied RH condition during the southwest monsoon season, to study the relationship of oxygen and carbon isotopic composition in the bulk grain organic matter (δ~(18)OOM, δ~(13)COM) with the hydroclimatic parameter of RH. Seasonal harvests of the years 2010 through 2014, sampled from 23 sites located in different climatic zones over India, were used for this experiment. Several fields and different genotypes (n = 105) were sampled at each site to arrive at representative values of δ~(18)OOM and δ~(13)COM. Based on regression analyses, the δ~(18)OOM variation across sites showed significant dependence on the δ~(18)O of source water (δ~(18)OSW) used by the crops, with the humid region registering the strongest correlation (r~2 = 0.95, p < 0.0001). After normalizing δ~(18)OOM values with respect to δ~(18)OSW and expressing the deviation as Δ18OOM, we obtained a significant relationship between the growing-season average RH and Δ~(18)OOM (r~2 = 0.90, p < 0.0001). This is represented by a linear response function: Δ~(18)OOM = (-0.45 ± 0.03) × RH + (66.4 ± 2.7). The relationship established in this study enables the reconstruction of RH level from the isotopic measurement of rice grain OM in modern-day and palaeo samples. Further, the relationship of the carbon isotope discrimination in rice grain OM (Δ~(13)COM) with RH gradient demonstrates the role of the evaporative demand in governing the dual-isotope variability.
机译：印度西南季风季节在相对湿度（RH）水平上表现出空间变化。在西南季风季节，在各种Rh条件下培养了大米（Oryza Sativa L.），研究了氧气和碳同位素组合物在散装谷物有机物中的关系（δ〜（18）Oom，δ〜（ 13）COM）随着RH的水加工参数。 2010年至2014年的季节收获，从印度的不同气候区的23个站点取样，用于该实验。在每个部位采集几个字段和不同的基因型（n = 105），以获得δ〜（18）Oom和δ〜（13）Com的代表值。基于回归分析，δ〜（18）横跨部位的OOM变化显示了作物使用的源水（δ〜（18）OSW的δ〜（18）O的显着依赖性，所述潮湿区域注册最强的相关性（R〜2 = 0.95，P <0.0001）。在相对于Δ〜（18）OSW的Δ〜（18）Oom值归一化Δ〜（18）OOM值之后，并将偏差表示为Δ18孔，我们在生长季节平均RH和δ〜（18）OOM之间获得了显着的关系（R〜2 = 0.90 ，p <0.0001）。这由线性响应功能表示：Δ〜（18）OOM =（-0.45±0.03）×RH +（66.4±2.7）。本研究中建立的关系使得能够从现代和甘头群样品中的大米籽粒OM的同位素测量重建RH水平。此外，用Rh梯度的水稻谷物OM（δ〜（13）COM）的碳同位素辨别的关系表明了蒸发需求在控制双同位素变异性方面的作用。

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