植物中硅矿化作用的硅同位素示踪研究

项目首次对田地生长的水稻与竹子和室内栽培水稻中氧化硅的含量、形态、分布及硅同位素组成进行了系统研究。研究发现水稻中的氧化硅含量有由根到茎、叶、稻壳逐渐增高的趋势, 但在米粒中含量急剧降低。竹子中的氧化硅含量也显由杆到枝、叶逐渐增高的趋势。在竹子和水稻的根部, 氧化硅都集中在内皮层;而在其地上部分(竿、枝、叶、壳), 氧化硅主要出现于外皮层。在单株水稻和竹子中都发现不同器官间存在显著的、系统的硅同位素分馏。水稻的? 30Si显示有由根到茎降低, 而后向叶、壳和米逐渐增高的趋势。竹子的? 30Si也显由根到竿降低, 而后向枝、叶增高的趋势。这种硅同位素变化可能是由植株内体液中的溶解硅在竿、枝、叶、壳相继沉淀出氧化硅时, 产生瑞利过程的硅同位素分馏的结果。研究得出竹子和水稻中溶解硅与沉淀硅间的硅同位素分馏系数分别为0.9981和0.9996。研究发现水稻根和竹根从土壤溶液中吸取硅时, 也存在硅同位素动力分馏。竹子与水稻吸收硅与土壤可溶硅之间的硅同位素分馏系数分别为0.9988和0.9989。研究得出：1)水稻与竹子由外界吸收的含硅化合物主要为正硅酸;2)被动吸收是其吸收硅的重要形式;3)蒸发作用是硅在这些植物中迁移和沉淀的主要机制。研究结果为理解植物中硅吸收、搬运和沉淀硅的方式与机制和探讨植物在硅、碳生物地球化学循环方面的作用提供了可靠的证据     

辽河三角洲滨海湿地有机碳的时空演变、环境功能及其埋藏机制

滨海湿地有机碳的时空分布规律, 是研究影响滨海湿地固碳能力及其对当今环境演化与全球气候变化的响应及反馈作用的关键。尽管土壤中总碳含量是评价固碳能力的重要指标, 但其中球囊霉素相关蛋白质(glomalin-related soil protein, GRSP)作为有机碳的一种重要组在部分, 可代表和行使有机碳在滨海湿地固碳能力中的相关作用。     

封闭酸溶-硅钼蓝比色分光光度法测定地质样品中的硅

由于聚合态的硅酸无法与钼酸根定量络合,采用硅钼蓝比色分光光度法测定地质样品中的硅,其关键在于如何将固体试样消解制备成溶液且保证硅酸全部以单分子状态存在。本文以氢氟酸-硝酸封闭酸溶消解地质样品,使样品中的硅完全转化为氟硅酸稳定存在于溶液中;再加入硼酸和钼酸铵,使过量的氢氟酸与硼酸生成稳定的BF~-_4配离子,此步骤代替了蒸干赶除氢氟酸,从而避免了赶酸过程中硅与氟离子转化为气态SiF_4而挥发损失,在钼酸铵作用下,硅则充分转变为硅钼杂多酸。在显色过程中通过加入丙酮显著提高了硅钼黄的稳定性,且在一定程度上增加了吸光度,从而改善了硅钼蓝分光光度法测定硅的显色效果。该方法避免了常规碱熔消解样品后在酸化过程中硅酸易聚合、引入大量熔剂造成空白偏高等问题,经岩石、土壤、沉积物和石英岩国家标准物质分析验证,SiO_2测试结果准确且重现性好(RSD1%,n=10),适用于一般地质样品中硅的快速、准确分析。     

植硅体在河流硅输送中的作用

高等植物产生的植硅体是古气候和古环境研究的重要手段,也是陆地硅循环中重要的硅的储库;植硅体通过河流的跨区域输送在全球硅的生物地球化学循环中起着重要作用,是区域硅循环研究的重要载体,然而这方面的关注却很少。河流输送的生物硅大致分为自源和异源两种类别。"自源"生物硅主要包括河流水体本身自生浮游植物(主要是淡水硅藻)产生的硅质颗粒;"异源"生物硅主要由流域土壤的侵蚀输出到河流的植硅体所构成。流域地表过程是使得部分土壤中的植硅体进入河流的主要途径,并成为河流生物硅输送中重要的形式,这对河流-河口水循环体系的硅生物地球化学循环过程产生了重要的影响,但人们对河流输送的植硅体在硅循环中的作用的研究还不够。文章着眼于陆海相互作用研究,以河流中水体携带的植硅体为中心,总结了河流植硅体输送在地表水体硅循环系统中贡献的研究进展,分析了长江与黄河植硅体入海通量与河口行为及对近海海洋环境的影响。最后,对未来河流输送的植硅体参与硅循环研究可能需要加强的科学问题提出了建议。     

Laser Ablation In Situ Silicon Stable Isotope Analysis of Phytoliths

Silicon is a beneficial element for many plants and is deposited in plant tissue as amorphous bio‐opal called phytoliths. The biochemical processes of silicon uptake and precipitation induce isotope fractionation: the mass‐dependent shift in the relative abundances of the stable isotopes of silicon. At the bulk scale, δ³⁰Si ratios span from ?2 to +6‰. To further constrain these variations in situ, at the scale of individual phytolith fragments, we used femtosecond laser ablation multi‐collector inductively coupled plasma‐mass spectrometry (fsLA‐MC‐ICP‐MS). A variety of phytoliths from grasses, trees and ferns were prepared from plant tissue or extracted from soil. Good agreement between phytolith δ³⁰Si ratios obtained by bulk solution MC‐ICP‐MS analysis and in situ isotope ratios from fsLA‐MC‐ICP‐MS validates the method. Bulk solution analyses result in at least twofold better precision for δ³⁰Si (2s on reference materials ≤ 0.11‰) over that found for the means of in situ analyses (2s typically ≤ 0.24‰). We find that bushgrass, common reed and horsetail show large internal variations up to 2‰ in δ³⁰Si, reflecting the various pathways of silicon from soil to deposition. Femtosecond laser ablation provides a means to identify the underlying processes involved in the formation of phytoliths using silicon isotope ratios.     

Oxygen isotope analysis of diatom silica and authigenic calcite from Lake Pinarbasi, Turkey

There is increasing interest in the ¹⁸O/¹⁶O ratio of diatom silica, particularly for lakes where carbonates are absent. Here we compare the ¹⁸O/¹⁶O ratios preserved in diatom silica and authigenic calcite from an open, spring-fed, freshwater lake core from Turkey which spans marine oxygen isotope stage 3. The two sets of isotope data show contrasting trends in spite of their mutual dependence on the water ¹⁸O/¹⁶O ratio and lake-water temperature. The most likely explanation for this divergence is difference in seasonality of biological productivity mediated by the strongly continental climate of the Anatolian plateau. Diatom silica and authigenic calcite are precipitated from solutes in the lake-water at different times of the year. Diatom productivity follows a well-defined seasonal cycle, peaking first and most importantly in the spring and then in the autumn. The precipitation of calcite follows productivity by all forms of photosynthetic organisms that deplete CO₂ but in most lakes this occurs during the summer months. The ¹⁸O_calcite curve shows mean summer temperature maxima at ca. 30–35 and ca. 58 ka BP while the intervening data represent a period of relatively cool summers. The ¹⁸O_diatom curve shows bipolar results (15–20 and 29–33), which suggests that at least two discrete sources or processes contributed to the oxygen composition of the diatoms but probably involved a dilution mechanism to shift the isotopic values. The most likely source of depleted water is from snow entering the lake during the spring thaw. We infer that many authigenic calcite curves from regions with markedly seasonal climates may be temporally limited to a few summer months and that diatom silica provides complementary data on seasonally-specific water isotopic composition rather than a substitute for analyses based on carbonate.     

窗口环境中运行的质量管理系统

概述了题示系统的设计原理、软件功能和运行环境。系统是ＸＲＦＩＡＳＸ荧光集成分析系统的子系统，由数理统计和１：２０万化探样品质量管理模块组成，无需人工录入，即可使用Ｘ荧光分析结果，对化探样品进行日常监控、质量评估、绘制监控图、打印分析结果。设计了用户友好的汉化窗口界面，还能将分析结果数据转换成ＤＢＦ文件，供Ｄｂａｓｅ访问，由用户程序进一步处理数据。     

Identifying disaster related social media for rapid response: a visual-textual fused CNN architecture

ABSTRACT

In recent years, social media platforms have played a critical role in mitigation for a wide range of disasters. The highly up-to-date social responses and vast spatial coverage from millions of citizen sensors enable a timely and comprehensive disaster investigation. However, automatic retrieval of on-topic social media posts, especially considering both of their visual and textual information, remains a challenge. This paper presents an automatic approach to labeling on-topic social media posts using visual-textual fused features. Two convolutional neural networks (CNNs), Inception-V3 CNN and word embedded CNN, are applied to extract visual and textual features respectively from social media posts. Well-trained on our training sets, the extracted visual and textual features are further concatenated to form a fused feature to feed the final classification process. The results suggest that both CNNs perform remarkably well in learning visual and textual features. The fused feature proves that additional visual feature leads to more robustness compared with the situation where only textual feature is used. The on-topic posts, classified by their texts and pictures automatically, represent timely disaster documentation during an event. Coupling with rich spatial contexts when geotagged, social media could greatly aid in a variety of disaster mitigation approaches.     

Optimal season for discriminating C3 and C4 grass functional types using multi-date Sentinel 2 data

ABSTRACT

The ability of remote sensing systems to optimally discriminate and map C3 and C4 grass species varies over time, due to environmental changes, which influence their phenological, physiological and morphological characteristics. In this regard, the discrimination of C3 and C4 grasses is insufficient when using a single image acquired at a specific period. In this study, multi-date Sentinel 2A MultiSpectral Instrument (MSI) data were explored to determine the optimal period for classifying and mapping Festuca costata, C3 and Themeda Triandra, C4 grasses in the montane grasslands of South Africa. The study further assessed how seasonal variations in species classification can be explained by climatic variability (rainfall and temperature). Results showed that image acquisition dates influence the discrimination accuracy, spatial representation of the two grass species, as well as the performance of spectral bands. The winter period also presents a better temporal window for discriminating C3 and C4 target grass species, with higher overall classification accuracies (between 91.8% and 95.3%), than summer (between 81.4% and 90.3%). Lower omission (between 2.8% and 11.6%) and commission (between 2.5% and 14.2%) errors were also observed when discriminating using winter images, as compared to those acquired in summer. Summer images showed large grass species areal coverage (e.g. in November and March, C3 and C4 covered ±25%), whereas in winter (mainly August), a notable decrease was observed. Overall, findings of the study have demonstrated the relevance of multi-date Sentinel data in discriminating C3 and C4 grass species. There is, however, a need to explore the classification ability of Sentinel 2 derivatives, especially during early summer and winter fall.