玄武岩类岩石大地构造环境的Th、Nb、Zr判别

本文通过研究Th、Nb、Zr的地球化学性质和判别机理，根据世界上典型大地构造环境区玄武岩类的Th、Nb、Zr数据，研究了Th、Nb、Zr判别玄武岩大地构造环境的地球化学机理，发现大同构造环境区玄武岩系的Th、Nb、Zr特征具有显著差异，其比值特征能将玄武岩形成的大地构造位置很好地划分出来，提出了判别玄武岩大地构造环境的Nb/Zr-Th/Zr双对数判别图，试图能较好地区分出大洋板块发散边缘，板块汇聚边缘，大洋板内，大陆板内及地幔热柱形成的玄武岩，得出了玄武岩大地构造环境判别的标志，指出了用Th、Nb、Zr判别玄武岩大地构造环境的方法。     

微量元素La,Nb,Zr在判别大地构造环境方面的应用

La，Nb，Zr是一组耐熔强亲岩浆元素。其相互之间的比值关系恢复深部作用的地球化学过程。玄武岩类特别是原始玄武岩浆形成的岩石的La／Zr及Nb／Zr比值，能较好地反映其源区的La，Nb。Zr之间的分异特征，在一般情况下这一特征与某种确定的大地构造环境有密切关系，可用来判别玄武岩类形成的大地构造环境及其源区分异特征。本文根据世界上典型大地构造环境区玄武岩类的La，Nb，Zr数据。划分玄武岩形成的大地构造位置，提出了La／Zr-Nb／Zr双对数图及判别方法。     

板块汇聚边缘玄武岩大地构造环境的Th、Nb、Zr判别

根据Th、Nb、Zr的地球化学性质和判别机理，利用世界上典型大地构造环境区玄武岩类的Th、Nb、Zr数据，研究了Th、Nb、Zr判别玄武岩大地构造环境的地球化学机理，发现不同构造环境区玄武岩系的Th、Nb、Zr特征具有显著差异，其比值特征能将玄武岩形成的大地构造位置很好地划分出来。提出了板块汇聚边缘玄武岩大地构造环境的Nb/Zr Th/Zr判别图，该图不但能较好地区分出板块汇聚边缘中的洋—洋俯冲带、洋—陆俯冲带及陆—陆碰撞带，同时还能反映出岛弧区大地构造环境演化的趋势。     

基于改进遗传算法一神经网络的玄武岩构造环境判别及对比实验

通过岩浆岩的地球化学特征判别岩浆形成的大地构造环境和岩浆源区的化学性质是地球化学全岩分析最重要的应用之一。该方法利用全岩地球化学数据,包括主量元素、微量元素和同位素组成数据,对给定岩浆岩(玄武岩、花岗岩等)的大地构造环境进行判别。作为人工智能技术在地球化学研究领域中的新尝试,机器学习判别方法逐渐成为经典判别图解法的补充研究手段。然而,高维数据特征筛选和繁多未知参数确定是影响算法分类准确性的两个主要因素。为此,提出一种遗传算法优化神经网络耦合判别方法(GA-NNDM)。该方法利用特征选择、参数确定和分类性能之间的反馈联系,将分类准确率、所选特征数量和特征代价作为适应度函数,通过迭代演化寻求最佳特征子集和未知参数,从而达到减少特征、优化参数和提高性能的目的。此外,根据公开玄武岩样品地球化学数据,通过K折交叉验证等方法设置纵向、横向比较实验来验证GA-NNDM在玄武岩构造环境判别方面的准确性、稳定性和外延性。仿真实验结果表明,GA-NNDM具有优良的判别效果和泛化能力,其总体分类准确率能达到90%。因此,GA-NNDM值得在地球化学领域做进一步推广应用。     

基于全球橄榄石数据的玄武岩构造环境智能判别方法及其验证

一直以来,探索玄武岩地球化学特征与大地构造环境之间的联系是地球化学领域的一个重要研究方向。橄榄石是岩浆最早期结晶的矿物之一,其在玄武质岩浆形成和演化过程中记录了诸多信息。鉴于此,学者们尝试利用橄榄石的元素组成判别大洋中脊玄武岩(MORB)、洋岛玄武岩(OIB)和岛弧玄武岩(IAB)三种构造环境。常用的玄武岩构造环境判别图解难以满足精度要求,于是引入机器学习算法作为判别手段来解决上述问题。机器学习判别方法的分类效果在很大程度上取决于参数选取的合理性。为此,本文提出一种耦合灰狼优化算法(GWO)和支持向量机(SVM)的智能判别方法。该方法利用GWO寻求SVM算法最优参数组合,以形成橄榄石组成元素和玄武岩构造环境之间的最佳映射关系,从而实现对MORB、OIB和IAB三种构造环境的准确判别。此外,根据公开发表的玄武岩样品的地球化学数据,结合混淆矩阵及其衍生评价指标,通过仿真实验、随机子抽样验证和k折交叉验证等方式评估了所提方法的判别性能。评估结果表明, GWO-SVM耦合判别方法在利用橄榄石成分判别玄武岩构造环境方面具有较好的分类效果,其判别准确率可达85%以上。由此可见,相较于传统判别图解方法,基于多算法融合的机器学习判别方法能够更加有效地提升构造环境判别效果。     

玄武岩类形成的大地构造环境的Th／Hf—Ta／Hf图解判别

Th,Ta,Hf是一组耐熔强亲岩浆元素，由于地球化学性质的相似性，其相互之间的比值关系能将深部作用的地球化学过程较好地恢复出来，玄武岩类，是原始玄武岩浆形成的岩石的Ta/Hf及Th/Hf比值，能较好地反映其源区的Th,Ta,Hf之间的分异特征，在一般情况下，这一特征与某种确定的大地构造环境有密切关系和确定的因果联系，可用来判别玄武岩类形成的大地构造环境及其源区Th,Ta,Hf分异特征，本文根据典型大地构造环境玄武岩类的Th,Ta,Hf数据，提出了玄武岩类形成的大地构造环境判别的Th/Hf-Ta/Hf双对数图及判别方法。     

如何正确使用玄武岩判别图

为了正确使用玄武岩判别图,在投图之前要对样品加以筛选并对数据作出估计。还要将样品适当分组,投图时应遵循一定的程序。文中讨论了可能出现的几种判别结果及可能的解释方案,指出了判别图的局限性,认为玄武岩判别图所标定的各种构造环境的分区,实际上代表的是各种不同的岩浆类型。作者认为,投在洋中脊玄武岩区域的玄武岩绝大多数并非来自大洋中脊环境。     

基于GEOROC数据库的全球辉长岩大数据的大地构造环境智能判别研究

辉长岩是化学成分与玄武岩类似的侵入岩,前人认为它的形成过程太复杂,对应的岩浆可能经过了分离结晶作用、混染作用等,不能用Pearce判别图来判断岩浆岩形成的构造环境。本文利用GEOROC数据库的资料对辉长岩进行大数据挖掘。首先根据前人成果,将GEOROC数据库的辉长岩形成的大地构造环境分为大陆玄武岩环境、汇聚边界环境、板内火山岩环境和大洋岛弧玄武岩环境等4类;然后在数据清洗基础上,利用Python语言,依托sklearn库,实现支持向量机、K近邻和随机森林等3种机器学习算法,获得3种对应的分类器结果输出。对辉长岩的构造环境进行智能判别结果显示,随机森林方法效果最好,判断准确率可达97%,利用辉长岩的地球化学大数据来判断岩浆岩的构造环境是完全可行的。     

基于镁铁-超镁铁岩中单斜辉石主量元素含量的决策树集成算法对比

依靠岩浆构造环境的地球化学成分认识岩浆形成过程是岩石地球化学中的重要应用。当前利用岩石地球化学成分判别构造环境的工作还不够深入。用4种基于决策树的机器学习方法对来自全球新生代洋岛玄武岩(OIB)、岛弧玄武岩(IAB)及大洋中脊玄武岩(MORB)等镁铁-超镁铁岩中单斜辉石的13种主量元素构成数据集进行了岩浆构造环境判别和主要特征排序。通过对比4种基于决策树的机器学习方法,验证了树类算法对于地球化学成分识别问题的有效性,并总结出4种方法在处理岩浆构造环境判别问题时的优劣:决策树算法判别过程更易于理解,但是其准确率欠佳;boosting算法中的AdaBoost和GBDT对于岩浆构造环境的鉴别准确度较高,但构造过程复杂;bagging集成算法随机森林在权衡性能和模型可理解性时不失为一个良好的选择。此外,还通过4种算法的特征重要性排序得出Cr_2O_3,TFeO,TiO_2,FeO和Al_2O_3是进行岩浆构造环境判别的重要成分。     

阿克苏前寒武纪蓝片岩原岩产出的大地构造背景

阿克苏蓝片岩地体位于塔里木盆地西北缘。在其东南侧蓝片岩与上覆震旦纪地层不整合接触,因此被认为是目前世界上仅有的两个有确切证据的前寒武纪蓝片岩之一。过去人们对这个地区的工作主要围绕高压变质的同位素定年展开,若干个年龄数据均表明阿克苏蓝片岩的俯冲折返过程发生在新元古代。但是关于俯冲之前蓝片岩原岩产出的大地构造环境,目前还缺乏研究。本文通过对研究区内基性片岩的地球化学分析,得出蓝片岩原岩主要是洋壳玄武岩的结论。样品硅含量和一系列玄武岩不活动元素分类图解表明所有样品的原岩是拉斑玄武岩。由于明显的元素含量差异,样品被划分为A、B两组。稀土元素配分曲线、原始地幔标准化微量元素蛛网图以及常见的玄武岩大地构造判别图解都表明A组样品具有异常洋脊玄武岩的特征,而B组样品具有正常洋脊玄武岩的特征。阿克苏蓝片岩的原岩是新元古代邻近塔里木的某一洋壳的残片,它作为俯冲带增生楔的一部分经历深俯冲—折返过程,最终出露于地表。     

Basalt geochemistry as a diagnostic indicator of tectonic setting

Basalt geochemistry can be used as a diagnostic indicator for determining the tectonic setting of origin, because specific plate tectonic settings often impart distinctive geochemical characteristics. For example: (1) mid-ocean ridge basalts (MORB) and oceanic island basalts (OIB) have clearly distinguishable trace element and Sr-Nd isotope geochemical characteristics; (2) arc related basalts, including IOAB (intra-oceanic arc basalts), IAB (island arc basalts) and CAB (continental arc basalts), exhibit following distinguishing features: all are characterized by low Nb/La ratios (<0.85) and negative Nb, Ta and Ti anomalies; most exhibit low Nb concentrations (<8 ppm), high positive ɛ_Nd values and low enrichment of incompatible elements except the continental arc shoshonitic basalts that possess high concentrations of incompatible trace elements and lower to negative ɛ_Nd values; (3) although contamination by continental crust or lithosphere can impart subduction-like signature (e.g., low Nb, low Ta and low Ti) and lead to misidentification of contaminated continental intraplate basalts as arc related, there are still some essential differences between continental intraplate basalts and arc related ones; such as: uncontaminated continental intraplate basalts have high Nb concentrations, Nb/La > 1, “hump-shaped” OIB-like trace element patterns and moderate positive ɛ_Nd values that distinguish them from the arc related ones; whereas, the contaminated continental intraplate basalts are characterized by pronounced negative Nb, Ta and Ti anomalies, but their concentrations of incompatible trace elements are conspicuously higher than those of subduction-zone basalts that also distinguishes them from the arc related ones; (4) an important difference between back-arc basin basalts (BABB) and the MORB is that the former exhibit both MORB-like and arc-like geochemical characteristics; (5) most oceanic plateau basalts (OPB) show diagnostic geochemical characteristics of enriched MORB (E-MORB) to transitional MORB (T-MORB); only the Kerguelen Plateau is an exception; the early (pre 90 Ma) volcanism of the Kerguelen Plateau is associated with the Early Cretaceous break-up of Gondwana and displays features of continental flood basaltic volcanism; with time, the tectonic setting of the Kerguelen plume-derived volcanism changed from a rifted continental margin setting (133–118 Ma) through a young, widening ocean (118–40 Ma), finally to an oceanic intraplate setting (~40 Ma to the present).Tectonic discrimination diagrams should not be used in isolation, but can still be useful as part of holistic geochemical characterization. For example: (1) MORB and OIB are distinguishable from each other in the 3Tb-Th-2Ta diagram; (2) the arc related basalts, including IOAB, IAB and CAB, constantly plot in the arc-related basalts fields in the Th/Yb-Ta/Yb diagram; (3) the 3Tb-Th-2Ta diagram can be utilized to fully illustrate both MORB-like and arc-like characteristics of BABB; (4) some discriminant diagrams (such as Zr/Y-Zr, Th/Yb-Ta/Yb, 3Tb-Th-2Ta and Hf/3-Th-Nb/16 diagrams) can be used to distinguish continental intra plate basalts from arc related ones; (5) although there are not any discrimination diagrams published that delineate an OPB field, some trace element diagrams can still reveal diagnostic characteristics of the OPB.     

磷灰石Eu/Y-Ce:基于大数据的源区类型判别新图解SCIEI北大核心CSCD

磷灰石广泛分布于火成岩、沉积岩和变质岩中,是一种常见的、包含丰富微量元素的副矿物。磷灰石晶格可容纳丰富的微量元素,且因其形成的物理化学条件不同会表现出差异明显的微量元素特征。利用磷灰石微量元素特征可以追踪物质来源和演化。现在常用的方法是利用磷灰石的微量元素绘制二元判别图解,经典判别图解包括Sr-Y、Sr-Mn、Y-(Eu/Eu^(*))和(Ce/Yb)_(N)-REE图解。随着微区测试技术发展,磷灰石微量元素数据日渐丰富,同时由于磷灰石化学成分的复杂性,传统图解已逐渐无法有效利用这些数据所携带的信息,进而无法准确判别其生成环境。建立能准确判别磷灰石物源的新型判别图解故而迫切。近年来,磷灰石微量元素数据的大量积累,为运用以大数据为依托,准确判别磷灰石物源奠定了数据基础。本研究将大数据技术与地球化学数据相结合,共收集整理了1925个代表性磷灰石测试点的微量元素数据,对富碱性火成岩、超镁铁质岩石、镁铁质火成岩、长英质花岗岩、中-低级变质岩、高级变质岩六种类型中磷灰石微量元素数据进行穷举端元处理,共获得7140个磷灰石物源判别图解端元组合,在轮廓系数限定下,进一步有效筛选并提取出能判别磷灰石物源类型的最优图解端元。本文构建了Eu/Y-Ce磷灰石判别新图解,相较于之前的磷灰石判别图解,其涵盖了更全面的物源类型,可以更准确地判别源区类型。     

N-MORB和E-MORB数据挖掘——玄武岩判别图及洋中脊源区地幔性质的讨论

MORB分为N-MORB和E-MORB,二者的区分通常是以LREE亏损和富集为标志。玄武岩的基本理论主要是在MORB研究成果的基础上建立起来的。通常认为,N-MORB和OIB是两个独立的端元,E-MORB是N-MORB与OIB不同程度混合形成的。在20世纪70~80年代,玄武岩构造环境判别图的建立极大促进了玄武岩在地球动力学及大地构造背景研究的进展,其方法应用持续盛行了几十年。然而,国外学者现在已逐渐淡化玄武岩判别图解的应用,但在中国仍有方兴未艾之势。本文利用Pet DB数据库5万多个MORB数据的投图表明,全体样品投图的效果显然比抽样和典型样品得出的结果更扎实可靠,许多原先被广泛应用的主量、微量元素判别图无论从实践上还是理论上均存在一些问题。本文的研究结果进一步表明,MORB样品既有LREE亏损的,又有富集的,但亏损和富集程度与早先定义的差异较大,揭示了洋脊下地幔不均一性要比早先认识的更为复杂,成分范围变化更大,仅少数是强烈亏损的,部分可能是相当富集,甚至可以与OIB源区相类比;玄武岩构造环境判别图需要重新审视,基于岩浆成因机理的多维度、高置信度的判别体系有待于建立。     

An Intelligent Method for Geochemical Discrimination of Tectonic Settings of Basalt Based on Olivine Composition: GWO-SVM Method and its VerificationEI北大核心CSCD

Geochemical discrimination of tectonic settings of basalts has been an important research direction of geochemistry for decades. Olivine is one of the earliest crystallized minerals of basaltic magma, which records a lot of hidden information of the formation and evolution of the magma. Therefore, basic elements in olivine are used to discriminate three tectonic settings, including the mid-ocean ridge basalt (MORB), ocean island basalt (OIB) and island arc basalt (IAB). However, it is still difficult to accurately discriminate the tectonic settings by using these diagrams. The machine learning algorithm is introduced to solve the aforementioned problem. The classification performance of the machine learning discrimination method largely depends on the rationality of parameter determination. To this end, the paper proposes a coupling intelligent method for geochemical discrimination of tectonic settings using olivine composition of the basalts based on the grey wolf optimizer (GWO)-optimized support vector machine (SVM), or GWO-SVM for short. GWO is used to seek the optimal parameter combination of SVM to form the optimal mapping relationship between basic elements in olivine and basalt tectonic settings, so as to realize the accurate discrimination of MORB, OIB and IAB. In addition, according to the published geochemical data of basalt samples, the discrimination performance of GWO-SVM is evaluated by means of the simulation experiment, hold-out validation and k-fold cross-validation. The evaluation results are represented by the confusion matrix and its derived evaluation indicators. The results show that GWO-SVM can discriminate the tectonic settings of the basalts based on olivine compositions with overall classification accuracy of up to 85%. Thus, in comparison with the traditional discrimination diagram method, the machine learning discrimination method based on multi-algorithm fusion can significantly improve the discrimination accuracy of basalt tectonic settings. © 2020, Science Press. All right reserved.     

云南大关新地2井奥陶—志留纪之交钾质斑脱岩岩石地球化学特征分析

扬子地台内晚奥陶世末—早志留世初五峰—龙马溪组内沉积了多层钾质斑脱岩,但对于该时期扬子地台西缘钾质斑脱岩的研究报道相对较少。本文旨在通过对云南大关地区新地2井五峰—龙马溪组内沉积的钾质斑脱岩进行矿物学及地球化学分析,进一步确定扬子西缘该时期钾质斑脱岩原始岩浆类型及其所产生的构造环境。矿物学特征表明,钾质斑脱岩主要由黏土矿物和非黏土矿物组成,其中黏土矿物由伊利石和伊蒙混层组成,非黏土矿物以石英、长石、方解石、白云石和黄铁矿等为主。钾质斑脱岩主量元素以高K_2O,低TiO_2为特征,微量元素特征表现为富集Rb、Ba、Th、U等元素,Ti、P元素相对亏损,Ti/Th值指示了酸性火山灰的性质;ΣREE在(49.86～209.43)×10~(-6);与球粒陨石相比,轻稀土轻微富集、具Eu负异常,无Ce异常;在Nb/Y-Zr/TiO_2图解中,数据点主要落在安山岩和粗面英安岩之间,表明钾质斑脱岩源岩浆性质为中酸性岩浆;依据微量元素特征和构造环境判别结果,初步认为原始岩浆可能形成于岛弧环境,其火山灰来源可能与扬子北缘早古生代秦岭洋闭合过程中的板块碰撞有关。     

Petrology,geochemistry, and geological significance of the Nadong ocean island,Banggongco–Nujiang suture,Tibetan plateau

We studied oceanic mafic igneous rocks of the Mesozoic Banggongco–Nujang suture zone in western Tibet to constrain the tectonic evolution of these rocks and the region as a whole. Two transects were accomplished. Seven basalt samples from the base of the Nadongshan transect (N1 basalts) have flat chondrite-normalized rare earth element (REE) and primitive-mantle-normalized trace element variation diagrams that are similar to MORB. Two basalt samples from the base of the Nadongshan transect (N1 basalts), ten gabbro samples from the middle of Nadongshan transect (N2 gabbros), four basalt samples from the bottom of Tanjiuxiama transect (T1 basalts), and four basalt samples from the top of the Tanjiuxiama transect (T2 basalts) are alkali basalts and have light rare earth element (LREE)-enriched chondrite-normalized REE patterns, and have primitive-mantle-normalized trace element variation diagrams that are enriched in highly incompatible elements, similar to OIB. LREE concentrations increase from N1 basalts to the T1 and T2 basalts, which have (La/Yb)_N up to 16 and have even higher (Ce/Sm)_N. These data indicate that the Nadong ocean island is an Azores-type ocean island that formed during the mature stage of development of the Banggongco–Nujiang Ocean. The conformable nature of the Nadong ocean island with the Mugagangri Group flysch indicates that the Banggongco–Nujiang Ocean was never a large ocean.     

哀牢山构造岩浆带晚二叠世-早三叠世火山岩特征及其构造环境

本文对中国云南哀牢山构造岩浆带内的雅轩桥、帽盒山、绿春火山岩等开展了相关研究.雅轩桥附近的火山岩为晚二叠世,岩性主要为橄榄粗安岩-玄武岩(少量安山岩),在TAS图上既有碱性又有亚碱性.钾含量较低(＜1.19％),为低钾钙碱-中钾钙碱性,Peacock碱钙指数以钙碱性为主.与MORB相比,其痕量元素蛛网图亏损Nb、Ta,而富集Pb,从Zr-V曲线呈平坦型,并且整体比MORB亏损.稀土元素配分模式与MORB相近,但略显轻稀土元素富集和重稀土元素亏损.在构造环境判别图上均位于火山弧环境.他郎河边(雅轩桥地区)火山岩为英安岩,属亚碱性,中钾钙碱性,Peacock指数为钙性.痕量元素蛛网图、REE模式图以及大地构造环境判别图,均表明其属于弧的构造环境.由上推测雅轩桥火山岩在晚二叠世属于弧火山岩.帽盒山玄武岩的锆石SHRIMP U-Pb测年结果为249±1.6Ma,为早三叠世.岩性为亚碱性钠长玄武岩,低钾钙碱性系列,Peacock碱钙指数以钙性为主.痕量元素蛛网图和REE配分模式图与MORB相比,LREE略微富集.在构造环境判别图中位于从E-MORB向岛弧过渡的构造环境.绿春地区流纹岩的锆石SHRIMP U-Pb年龄为247.3±1.8Ma,为早三叠世,属亚碱性,钾玄岩系列,Peacock碱钙指数为碱钙性.痕量元素蛛网图、REE配分模式图及大地构造环境判别图显示其为成熟岛弧向陆陆碰撞的过渡环境.结合前人研究,推测哀牢山洋在晚泥盆世形成,可能在石炭世-早二叠世(?)处于洋的扩张期.晚二叠世时,在哀牢山洋的西侧出现了雅轩桥的初始孤火山岩,预示着至少在这一时期,哀牢山洋已经开始俯冲.到三叠世早期(249±1.6Ma),在哀牢山洋的东侧出现了具有弧和MORB的双重特性的帽盒山玄武岩,可能指示此时哀牢山洋盆已经变小,或已转化为孤间或弧后盆地,洋的演化进入了晚期阶段,并且在局部地段,如绿春地区,此时(247.3±1.8Ma)已经进入到成熟岛弧向陆陆碰撞的过渡阶段.因此支持哀牢山洋在晚三叠世闭合的结论,亦符合上三叠统一碗水组不整合在哀牢山蛇绿混杂岩之上的事实.     

松辽盆地三台地区营城组珍珠岩地球化学特征及地质意义

松辽盆地东南缘的三台地区营城组火山岩分布广泛,其中一部分为珍珠岩。通过岩石薄片鉴定,挑选了三台地区北山上的6块珍珠岩样品,进行了主量元素、微量及稀土元素分析测试。珍珠岩的主量元素组成表明,它们与流纹岩成分相当,具有高SiO_2、较高(NaO_2+K_2O)、低TiO_2和低CaO含量,属于铝饱和-弱过饱和的钙碱性系列。稀土元素配分模式以轻稀土富集、Eu负异常强烈为特征。在不相容元素蛛网图上,珍珠岩相对于洋脊花岗岩总体上富集大离子亲石元素和轻稀土元素,而明显亏损高场强元素Sr、Nb、Y。在Nb-Y和Rb-(Y+Nb)判别图上,它们分别落入板内和火山弧区。这些结果显示,所研究的珍珠岩应为类似弧后盆地的引张环境。     

The petrogenesis of modern and ophiolitic lavas reconsidered: Ti-V and Nb-Th

Tectonic discrimination diagrams are a key tool for understanding ancient volcanic rock origins. In this contribution we compile over 15,000 whole rock compositions to re-evaluate the Ti-V discrimination diagram and compare it to another commonly used tool, the Nb/Yb-Th/Yb diagram. We have reformulated the Ti-V diagram into a log–log plot to distinguish samples more clearly at lower concentrations. The compilation shows that MORB are dominated by Ti/V = 20–43, whereas juvenile arc tholeiites and boninites are characterized by Ti/V < 20 generally, although there is minor overlap at the boundary (Ti/V = 20–22). Plume-related volcanic rocks (ocean island basalts, oceanic plateaux, and continental flood basalts) generally have Ti/V > 43, although there may be significant overlap with MORB-like ratios for ridge-centered OIB and for some oceanic plateaux. About 56% of alkaline OIB have Ti/V > 70. Back-arc basins are dominantly MORB-like. Melt models show that MORB and juvenile arc volcanics most likely formed under different ?O₂ conditions, but are permissive of similar ?O₂ if the arc rocks form by much higher melt fractions. The Nb/Yb vs. Th/Yb plot clearly distinguishes most oceanic basalts (MORB, plateaux, OIB) from subduction-related volcanic rocks (boninite, juvenile arc tholeiite, calc-alkaline) and from flood basalts. We propose here a new two-proxy diagram of Ti/V vs. Th/Nb, which incorporates the advantages of both.     

Application of a new computer program for tectonic discrimination of Cambrian to Holocene clastic sediments

TecSand is a new Java software that is used for deciphering the tectonic setting of clastic sediments and sedimentary rocks through two new multidimensional discrimination diagrams. For each sample, TecSand calculates four complex discriminant functions: DF1_m1 and DF2_m1 for the high-silica diagram and DF1_m2 and DF2_m2 for the low-silica diagram, each representing linear combinations of log-ratios of all major elements. These functions determine the position of each sample within island or continental arc, continental rift, and collision/convergent settings. The program also calculates the probability values for the three tectonic fields. TecSand provides a “ready for publication” report for each locality, including the adjusted major elements, log-transformed variables, DF1 and DF2 results, and probability values for individual samples. Validations from samples of known tectonic settings, evaluation of chemical changes, and applications to Precambrian clastic sediments have previously been demonstrated in the literature. Therefore, we illustrate the use of TecSand in 10 case studies covering ages from the Early Cambrian to the Holocene. The results obtained from these two diagrams were not only mutually consistent but also with other geological constraints. As an innovation, TecSand provides an overall synthesis of the two diagrams as total percent probability values. Comparison of the results of this study with the previously published tectonic discrimination diagrams reveals that two recent multidimensional discrimination diagrams are more efficient in discriminating tectonic settings. Although TecSand does provide graphics, which can be imported and modified in commercial software, plotting of the sample diagram is no longer required.