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87Sr86Sr and REE variations along the Easter Microplate boundaries (south Pacific): Application of multivariate statistical analyses to ridge segmentation
ChemicalGeology, 89 ( 1991 ) 209-241
209
Elsevier Science Publishers B.V., Amsterdam
[21
875r/86Sr and REE variations along the Easter Microplate boundaries (south Pacific): Application of multivariate statistical analyses to ridge segmentation D. F o n t i g n i e a a n d J-G. Schilling b aUniversit~ de Gen~ve, D~partemen.t de Min&alogie, 13 rue des Maraichers, CH-1211 Gen~ve 4, Switzerland bGraduate School of Oceanography, University of Rhode Island, Kingston, RI 02881, U.S.A. (Received July 4, 1990; revised and accepted August 16, 1990 )
ABSTRACT Fontignie, D. and Schilling, J-G., 1991. 87Sr/S6Sr and REE variations along the Easter Microplate boundaries (south Pacific): Application of multivariate statistical analyses to ridge segmentation. Chem. Geol., 89:209-241. We report S7Sr/a6Sr, REE, Sc, V, Cr and Co analyses on 48 basaltic glasses dredged at 47 different localities along the spreading boundaries of the Easter Microplate (EMP). The latitudinal STSr/S6Sr variation along the East and West Rifts closely parallels that of the Pb isotope variation previously published and confirms the strong abnormality of the mantle underlying this part of the East Pacific Rise (EPR). The data also further support the binary mantle mixing model previously proposed. We evaluate the potential of multivariate statistical analyses in studying this and previously published geochemical data obtained on these very same 48 basaltic glasses. The data base includes major and trace elements ranging from compatible (e.g., Cr) to highly incompatible (e.g., La), and the Pb and Sr isotope ratios. Multivariate classification of these geochemical variables in Q-mode (sample space) allows to clearly distinguish major-element grouping from those of moderate to highly incompatible elements, and the isotope ratios reflecting mantle source heterogeneities present in the region. The power of this multivariate geochemical classification is best represented in two-dimensional space by combining principal components analysis (PCA) with cluster analysis (CA) illustrated in the form of a dendrogram. The method is further illustrated by classifying elements of the lanthanide series at different statistical level of affinities. Using the variance-covariance matrix and correlation matrix in R-mode, we further demonstrate a close relationship between segmentation revealed by the multiple variation of the four isotope ratios and the actual tectonic segmentation. Both discriminant analysis and PCA further indicate a close relationship between the geochemical anomaly located on the East Rift of the EMP and Sala y Gomez and Easter Island, to a lesser extent the Tuamotu Chain, whereas there is no close affinity between the EMP and the more distant Juan Fernandez, San Felix or Society Islands in the isotopic space considered. This provides further support that the geochemical anomaly located on the East Rift of the EMP may be related to the influence of a plume located either beneath the East Rift, or in the vicinity of Sala y Gomez, or Easter Island. In the last two models the plume would be laterally deflected at shallow depth towards the EPR-EMP spreading complex. An analysis of statistical generalized distances against geographical distances rules out that such influence is caused by radial dispersion of this plume in the upper mantle. The flow between the plume and the East Rift of the EMP must be more confined or channelled. The possibility that the plume would be located directly beneath the East Rift cannot be ruled out but appears less likely.
1. Introduction
The problem of the nature and scales of mantle heterogeneities to that of the tectonic and magmatic segmentation found along midocean ridges is long standing. Schilling ( 1975 ) 0009-2541/91/$03.50
first divided the mid-ocean ridge system into normal, plume-influenced and transitional ridge segments on the basis of long-wavelength rare-earth element (REE) and morphologic variation observed primarily in the North Atlantic. The enriched ridge centered plume-depleted asthenosphere binary mixing model was
© 1991 - - Elsevier Science Publishers B.V.
210 proposed to explain such segmentation. With increasing documentation of ridge segments influenced by progressively more distant hotspots, the model evolved to the migrating ridge - - hotspot source model (Morgan, 1978; Schilling, 1985) and the blob-cluster model (All~gre et al., 1984). The latter two models are not mutually exclusive and have much in common. Both include spreading rate as an influential factor but for different reasons. The former emphasizes the distance of the ridge to the hotspot (or time since it left the hotspot), whereas the latter considers spreading rate (or underlying mantle convection rate), as the dominant factor controlling the dispersion and dilution of plumes with the depleted asthenosphere. It has also been suggested that geochemical anomalies may coincide with fracture zones and the geochemical segmentation may be a reflection of the convective pattern in the underlying mantle (Langmuir and Bender, 1984 ). Others now contend that short-wavelength geochemical anomalies are a mere reflection of small-scale passive mantle heterogeneities ubiquitously present in the mantle (Sleep 1984; Zindler et al., 1984), and the morphotectonic ridge segmentation is primarily controlled by the wavelength of mantle or melt instabilities present directly beneath the ridge system (Schouten et al., 1985 ). Thus it has become increasingly more difficult to decide the cause (s) of the geochemical variability along ridges. A more powerful means for fingerprinting mantle source derivations has been to use several isotopes or trace-element ratios measured on the same samples. For example, 3He/4He variation with that of 87Sr/86Sr along the Mid-Atlantic Ridge (MAR) has helped distinguishing the influence of the Iceland plume from that of the Azores plume (Kurz et al., 1981; Poreda et al., 1986 ). Also, the influence of the South Atlantic-off-ridge plumes on the MAR has been pinpointed with the use of the covariation of the three Pb isotopes ratios in a single two-dimen-
D. FONTIGNIE AND J-G. SCHILLING
sional (2-D) Pb isotope space representation (Hanan et al., 1986 ). These approaches are all limited to 2 to 3 geochemical variables and 2-D representations. Despite its potential power, little use has been made so far of multivariate statistical analyses for fingerprinting the nature or cause of mantle heterogeneities simultaneously with a larger number of variables. Nor does its potential been exploited for classifying and delineating objectively possible ridge segmentation with petrological-geochemical data, with or without a priori evidence based on tectonic segmentation. Of course, the practical difficulty of gathering geochemical, petrological and isotopic data on the very same and fresh glass samples has been a limiting factor. In this paper we report 87Sr/86Sr, REE, Sc, V, Cr and Co data on the very same Easter Microplate (EMP) basaltic glasses we previously studied for major and Pb isotopes (Schilling et al., 1985; Hanan and Schilling, 1989 ). We then illustrate the potential of multivariate statistical analysis in handling and interpreting this entire data set in terms of mantle source heterogeneities and their relation to morphotectonic ridge segmentation in the region. For comparison we also include new data on a few basalts from Easter and Sala y Gomez Islands. Multivariate statistical methods provide a means to consider simultaneously a large number of variables from a given data set. They are essentially a generalization of uni- or bivariate statistical analyses. These methods provide also ways of reducing the number of variables by linearly combining them and optimising their 2-D presentations without significant loss of information. Depending on the way the data are investigated, relationships between the variables or between the samples can be drawn. The multivariate statistical techniques used in this study include principal components (PCA), discriminant (DA) and cluster (CA) analyses (Tatsuoka, 1971; Green, 1976; Le Maitre, 1982; Dagn61ie, 1986). A brief description of these methods is included as an
86Sr/a6Sr A N D R E E V A R I A T I O N S A L O N G T H E E A S T E R M I C R O P L A T E
common at a smaller scale along the EPR (Lonsdale, 1983; MacDonald et al., 1988), or is it the result of the influence of a plume in the region, or both? (3) If the plume model first revealed by the topographic character of the region (Anderson et al., 1974; Vogt, 1976) is considered, can the nature and location of the plume be further defined? For example, is the plume located beneath the East Rift as inferred first by Morgan ( 1971 ) and Handschumacher et al. ( 1981 ), or
Appendix. We will show that the EMP provides a good opportunity to reveal the potential power of multivariate statistical analyses in objectively tackling existing problems, such as: (1) Delineating underlying mantle heterogeneities present in relation to that of the morphotectonic tectonic segmentation of the East Pacific Rise (EPR) in the region. (2) Does the microplate represent only a mega-case of ridge overlap, a feature quite I
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211
BOUNDARIES
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Fig. 1. Plate boundary configuration of the Easter Microplate modified from Naar and Hey ( 1989, 1990) and Searle et al. (1989). Spreading directions and rates (double arrows) and absolute plate motion of the Nazca Plate near Easter Island (single arrow) are taken from Naar and Hey ( 1989 ). Also shown are the location and denomination of the dredge hauls and ridge segments used in this study. West Rift: capital letters; East Rift: small letters and numbers. See Table I for corresponding station numbers; Ridge segment numbers considered in the text are circled. Right insert: Location map of the Easter Microplate in the south Pacific.
212
off-ridge as suggested by Schilling et al. ( 1985 ) and Hanan and Schilling ( 1989 )? (4) If the EMP anomaly is influenced by an off-ridge hotspot, is it located west (e.g., Tuamotu or Society hotspot ) - - or east of the ridge (e.g., Easter, Sala y Gomez), or somewhere else?
2. Tectonic setting The existence of the EMP located between the Pacific and Nazca plates (Fig. 1 ) was first reported by Forsyth (1972) and Herron (1972). Its exact tectonic configuration and origin remains uncertain and keeps evolving as new data accumulates (Anderson et al., 1974; Hey and Vogt, 1977; Handschumacher et al., 1981; Engeln and Stein, 1984). A seabeam/ magnetic survey by Hey et al. (1985), combined with evidence from dredged rocks by Schilling et al. (1985), led to the conclusions that the eastern and western boundaries are actively spreading and propagating, northward along the Eastern Rift, and southeastward along the Western Rift. Both the northern and southern boundaries of the EMP are probably broad transform zones or pseudo-faults. Both remain to be better defined. The EMP boundary configuration shown in Fig. 1 takes into account the recent GLORIA and SeaMARC sonar survey (Searle et al., 1989 ) and the study of Naar and Hey ( 1989, 1990). Because of dual spreading and rift propagation the spreading rate vary widely in the region ( ~ 0 - 1 8 5 km M a - 1_ see Fig. 1 and Naar and Hey, 1989 ).
3. Sampling During the 1984 dredging cruise with R / V "Endeavor" (EN-113), 48 stations at ~ 25-km intervals were collected along what were thought at the time to be the spreading boundaries of the EMP and adjacent EPR, between 22 ° and 29°S (Fig. 1; Schilling et al., 1985). Two samples collected during the cruise Pascua 04 are also included (Craig et al., 1984;
D. FONTIGNIE AND J-G. SCHILLING
Macdougall and Tanzer, 1984). It is evident from Fig. 1 that not all the samples may be located exactly on the present ridge axis. This is particularly the case south of the EMP (27 °S ) where the sampling is ~ 20-35 km further east, and in the NW and NE corners of the EMP which is tectonically complex and the boundaries are still ill defined. Using current spreading rates and visual inspection, we estimate that none of the basalts from this collection are likely to be older than 0.2-0.3 Ma. The locality and sample descriptions of the Easter and Sala y Gomez Islands and dredged glasses from its flank are given in Hanan and Schilling ( 1989 ). For convenience, in our geochemical scrutiny the spreading boundaries are first subdivided into two branches, the East and the West, and subsequently into eight segments as shown in Fig. 1. The basalt glasses studied correspond to three petrological types (Schilling et al., 1985; Sigurdsson et al., 1985 ): ( 1 ) The most abundant are tholeiitic basalts ranging from quartz to olivine normative. (2) A few basalts are nepheline normative (stations L, I, m and 8). All of these are light REE (LREE) depleted, lower in SiO2, higher in A1203 and Na20 than the tholeiites, and have been the least affected by low-pressure fractional crystallization. (3) Among the nepheline-normative basalts, two are primitive picritic basalts which may have equilibrated at pressures of > 20 kbar (stations G and d; Sigurdsson et al., 1985 ). The major-element analyses and (La/Sm)n ratios have been reported by Schilling et al. (1985) and Pb isotope ratios by Hanan and Schilling ( 1989 ).
4. Analytical results Except for four samples, the REE, Sc, V, Cr, Co, major elements and the isotopic analyses were all performed on carefully selected glass chips from the same pillow or sheet flow. Fur-
S6Sr/S6SrAND REE VARIATIONSALONG THE EASTER MICROPLATE BOUNDARIES
213
TABLE I
875r/S6Sr ratios in basalt glasses from the Easter Microplate and basalts from Easter and Sala y Gomez Islands Sample *~
Segment
Code
Location lat.
long.
22.53 22.68 22.90 23.00 23.08 23.25 23.48 23.77 24.11 24.31 24.64 24.64 24.99 24.99 24.99 25.28 25.66 25.90 26.13 26.35 26.52 26.70 23.86 24.20 24.36 24.53 24.61 24.78 24.86 24.86 24.98 25.03 25.24 25.24 25.47 25.66 25.98 26.27 26.27 26.46 26.58 26.81 26.81 26.92 27.21 27.21 27.30 27.53 27.53
114.47 114.51 114.51 114.53 114.54 115.43 115.38 115.47 115.41 115.47 116.42 116.42 116.36 116.36 116.36 116.27 116.13 115.86 115.64 115.32 115.09 114.92 111.82 111.93 111.98 111.79 111.95 111.97 112.45 112.45 112.42 112.41 112.38 112.38 112.39 112.38 112.55 112.62 112.62 112.57 112.65 112.64 112.64 112.70 112.77 112.77 112.81 112.76 112.76
(os)
EN113 35D-1g ENI13 36D-1g ENI13 34D-Ig E N l l 3 37D-Ig E N l l 3 38D-llg ENI13 33D-1 E N l l 3 32D-lg ENI13 31D-1 EN 113 30D- lg EN113 29D-Ig EN113 28D-1Bg E N l 1 3 28D-lAg E N l l 3 27D-IAg E N l l 3 27D-1Bg E N l l 3 2719-1 ENII3 26D-lg EN 113 25D-1g EN 113 24D-lg EN 113 23D-1g ENI13 22D-1g ENII3 21D-lg ENII3 20D-lg EN113 17D-lg ENI13 16D-lg EN I I 3 39D-2g ENII3 15D-lg EN I13 40D-lg E N l l 3 14D-lg EN 113 13D-lg EN 113 13D-4 PAO4-12-A.4 ENII3 12D-1 ENII3 IlD-1A ENII3 llD-1B EN113 lOD-lg EN113 9D-lg EN113 8D-lg PA04-11-CA .4 PAO4-11-CB EN113 7D-lg EN113 41D-lg E N l l 3 6D-1Bg EN 113 6D-lAg EN l l 3 4 2D- Ig E N l l 3 5D-IAg E N l l 3 5D-ICg EN I 13 43D-2g ENI13 4D-lAg ENII3 4D-lg
1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 7 7
W X V Y Z N M L K J I I H H H G F E D C B A q p 1 o 2 n m m * 1 k k j i h s s g 3 f f 4 e e 5 d d
Depth (m)
878r/86Sr(*2 )
20* 3
2,912 2,975 2,975 3,032 3,125 2,815 3,270 2,660 2,800 2,692 2,740 2,740 2,060 2,060 2,060 2,052 2,240 2,212 2,608 2,788 2,705 2,918 3,905 2,950 2,898 2,975 2,825 2,630 2,948 2,948 3,264 3,255 3,158 3,158 2,970 2,865 2,668 2,425 2,425 2,272 2,282 2,362 2,362 2,590 2,632 2,632 2,438 2,520 2,520
0.702427 0.702470 0.702391 0.702397 0.702398 0.702573 0.702443 0.702409 0.702285 0.702425 0.702499 0.702516 0.702928 0.702866 0.702859 0.702289 0.702487 0.702595 0.702599 0.702598 0.702584 0.702723 0.702392 0.702513 0.702538 0.702619 0.702798 0.702656 0.702490 0.702709 0.702643 0.702612 0.702781 0.702780 0.702696 0.702710 0.702683 0.702859 0.702846 0.702854 0.702850 0.702989 0.702981 0.702807 0.702608 0.702585 0.702686 0.703218 0.703204
0.000022 0.000016 0.000020 0.000016 0.000016 0.000018 0.000020 0.000018 0.000016 0.000016 0.000020 0.O00018 0.000022 0.000018 0.000020 0.000018 0.000018 0.000020 0.000022 0.000014 0.000022 0.000020 0.000020 O.000018 0.000018 0.000020 0.000022 0.000016 0.000024 0.000018 0.000022 0.000018 0.000024 0.000014 0.000020 0.000020 0.000020 0.000012 0.000030 0.000018 0.000024 0.000020 0.000022 0.000018 0.000016 O.000018 0.000020 0.000024 0.000016
(ow)
214
D. FONTIGNIE AND J-G. SCHILLING
TABLE I (continued) Sample*'
Segment
Code
Location
Depth
S7Sr/S6Srt*2)
20 *3
0.702685 0.702775 0.702547 0.702632 0.702696 0.702663 0.702494 0.702450 0.702421
0.000016 0.000014 0.000018 0.000018 0.000018 0.000014 0.000016 0.000014 0.000026
0.702930 0.703015 0.702962
0.000018 0.000018 0.000018
0.703116 0.703195 0.703025
0.000018 0.000020 0.000020
(m)
EN 113 44D-5g ENI13 3D-lg ENl13 2D-2g EN 113 45D-lAg EN113 45D-1Bg ENl13 1D-Ig E N l l 3 46D-2 EN113 47D-2g EN 113 48D- lg Easter Island
7 7 8 8 8 8 8 8 8
6 c b 7 7 a 8 9 +
lat.
long.
(os)
(ow)
27.64 27.88 28.08 28.29 28.29 28.48 28.72 29.01 29.02
112.84 112.81 112.66 112.66 112.66 112.65 112.73 112.79 112.70
26.92
109.35
P3B P4 P7 Sala y Gomez
26.58
Y 73-4-30-4 Y 73-4-30-20 Y 73-4-30-5
2,522 2,300 2,784 2,758 2,758 2,950 2,750 2,488 2,448
105.38
*~The g in the sample identification stands for glass, otherwise pillow interiors were used. *2The 87Sr/86Sr ratios are normalized to Srsr/SaSr= 0.1194 and adjusted to Eimer & Amend* SrCO3 standard S7Sr/a6Srvalue of 0.70800. The Eimer & A m e n d * standard was 0.708039_+ 0.000008 ( 2 a from the mean, 31 replicates analyses) during the period of measurements of ~ 1 yr. *3Errors are the estimated in-run 2 standard deviations. *4These two samples have also been analyzed by Macdougall and Lugmair ( 1986 ). The results between the two laboratories are identical within the errors quoted.
thermore, the Pb and Sr isotopic data were obtained from the very same dissolution of such glass fragments, hand-picked under the binocular microscope after ultrasonic cleaning in distilled water. The 87Sr/86Sr data reported in this study are listed in Table I. The REE and Sc, V, Cr and Co data, obtained by instrumental neutron activation analysis (INAA), are listed in Table II and Table III, respectively. The Sr isotopic analyses were carded out on a VG Micromass ® 30B single-collector, double-focusing, thermal ionization mass spectrometer at University of Rhode Island (URI), Measured blanks for the procedure are negligible, giving uncertainties significantly lower than the in-run errors.
The Sr was isolated using essentially the method of Hart and Brooks (1974), after dissolving ~ 0.2-0.4 g of carefully cleaned and hand-picked basaltic glass fragments. Approximately 50/lg Sr were loaded in phosphoric acid form on rhenium single filament using tantalum oxide as an activator. The normalization procedure used and associated statistics is given at the bottom of Table I. The REE pattern for the East Rift and EPR southern extension shows a much wider range of LREE enrichment and fractionation than the West Rift and EPR just north of the microplate (Fig. 2 ). The Sr isotopic ratios along the EMP bracket the entire EPR and range in values from 0.7023
86Sr/86SrAND REE VARIATIONSALONGTHE EASTERMICROPLATEBOUNDARIES
215
TABLEII
REE concentrations (ppm) and chondrite-normalized (La/Sm)n ratio in glassy basalts from the boundaries of the Easter Microplate and the East Pacific Rise ID *l
EN11335D-Ig EN113 35D-2g E N l l 3 36D-lg ENI1336D-2 ENI13 34D-lg EN113 34D-2 EN113 37D-lAg EN11327D-2 EN113 38D-I EN113 38D-llg E N l l 3 33D-1 EN113 33D-2 EN113 32D-lAg E N l l 3 32D-2 EN1331D-I ENl1331D-2g ENl1330D-1g ENl1330D-2g ENl1329D-1g E N l l 3 29D-2 E N l l 3 28D-lAg E N l l 3 28D-2 ENl1327D-1 ENI1327D-2 ENl1326D-1g EN113 26D-2 E N l l 3 25D-1g ENI13 25D-2g EN11324D-1g ENII3 24D-2 ENI13 23D-lg ENII3 23D-2 EN11322D-1 ENII3 22D-2 EN113 21D-1 ENI1321D-2 ENl13 20D-1 EN113 20D-2 ENl13 18D-1 ENl13 17D-1 ENl13 17D-2g E N l l 3 16D-lg E N l l 3 16D-2 E N l l 3 39D-1 E N l l 3 39D-2g E N l l 3 15D-I E N l l 3 15D-2 ENl13 40D-lg EN11340D-2 ENI13 14D-lg
La 2.39 2.33 2.85 2.83 1.56 1.32 3.67 3.30 1.52 1.54 2.35 2.65 4.10 2.99 2.49 2.64 1.16 2.31 4.03 5.08 1.52 1.47 4.29 4.98 0.99 1.14 4.54 3.96 5.13 4.88 4.64 5.95 5.17 6.04 4.06 4.61 4.51 5.25 4.79 3.26 2.97 5.02 5.03 4.17 3.56 4.99 5.12 1.52 2.62 2.83
Ce
Nd
Sm
Eu
Tb
8.41 7.91 10.38 9.37 6.73 6.33 14.32 11.95 6.80 6.68 6.74 9.98 12.26 9.51 8.22 8.20 4.99 9.12 13.01 15.28 5.72 6.77 11.63 14.99 3.74 4.00 13.17 11.48 14.82 13.89 13.40 16.55 14.01 17.00 11.17 13.46 12.68 14.96 15.86 11.22 10.67 13.13 13.69 14.44 13.37 17.46 18.12 5.97 9.11 9.87
8.98 8.54 9.64 6.97 6.33 13.68 10.92 6.78 7.52 5.98 9.49 11.68 7.90 7.39 9.27 11.16 6.49 7.35 8.04 9.88 4.19 3.89 10.86 11.73 10.36 10.96 12.50 10.57 13.50 10.97 8.76 11.64 13.80 10.40 8.78 10.62 9.69 13.91 12.59 15.59 15.58 7.27 7.17 -
3.27 3.34 3.47 3.63 2.49 2.13 5.04 4.61 3.11 3.05 2.67 3.45 4.17 3.00 2.67 3.10 2.33 3.30 3.99 4.86 2.64 2.82 2.72 2.97 1.63 1.65 3.82 3.59 3.73 3.83 3.68 4.20 3.81 4.79 3.29 3.99 2.90 4.06 5.60 3.68 3.77 3.43 3.52 5.00 4.64 5.50 5.77 2.41 3.27 3.34
1.17 1.21 1.37 1.23 0.96 0.98 1.83 1.49 1.07 1.17 0.97 1.34 1.44 1.08 1.01 1.08 0.90 1.26 1.43 1.63 1.08 1.04 0.97 1.35 0.79 0.74 1.39 1.14 1.41 1.34 1.32 1.47 1.28 1.59 1.11 1.30 1.12 1.37 1.76 1.34 1.30 1.24 1.26 1.58 1.66 1.79 1.99 0.94 1.26 1.20
0.86 0.90 0.91 0.89 0.70 0.66 1.41 1.11 0.84 0.91 0.65 0.86 1.07 0.80 0.73 0.90 0.68 0.99 1.01 1.18 0.66 0.75 0.59 0.79 0.50 0.48 0.94 0.83 0.94 0.94 0.91 1.00 0.93 1.15 0.84 0.98 0.68 0.98 1.37 0.93 0.88 0.77 0.79 1.27 1.20 1.60 1.41 0.66 0.86 0.84
Dy 5.16 5.52 6.41 6.14 5.02 4.76 7.16 5.38 5.78 4.73 6.66 5.36 4.70 5.57 4.17 6.65 7.45 4.21 3.90 4.65 2.93 6.39 5.80 5.90 5.32 6.25 6.08 6.59 5.16 6.38 4.15 6.54 8.81 5.77 6.02 4.47 5.25 8.55 8.36 8.76 5.13 5.53
Tm
Yb
Lu
( L a / S m ) n .2
0.65 0.72 0.74 0.70 0.57 0.46 1.02 0.83 0.64 0.66 0.50 0.77 0.52 0.66 0.51 0.66 0.68 0.75 0.44 0.41 0.41 0.68 0.53 0.63 0.68 0.79 0.61 0.68 0.46 0.68 0.61 0.59 0.53 0.55 0.82 0.86 0.93 -
3.77 3.90 3.78 3.69 2.98 2.85 5.40 4.74 3.55 3.77 2.57 3.83 4.23 3.05 3.19 3.69 2.77 3.90 3.68 4.46 2.56 2.65 2.17 2.71 2.29 2.25 3.46 3.10 3.35 3.59 3.50 3.71 3.67 4.36 3.57 3.79 2.53 3.79 5.66 3.53 3.55 2.89 2.98 4.71 4.40 5.37 5.85 2.76 3.39 3.26
0.52 0.55 0.54 0.52 0.40 0.41 0.74 0.64 0.53 0.52 0.41 0.57 0.56 0.41 0.44 0.52 0.37 0.54 0.51 0.61 0.36 0.37 0.30 0.40 0.33 0.34 0.48 0.45 0.46 0.47 0.48 0.56 0.50 0.62 0.48 0.57 0.35 0.52 0.79 0.49 0.51 0.38 0.41 0.65 0.60 0.77 0.87 0.36 0.49 0.45
0.51 0.49 0.57 0.55 0.44 0.43 0.51 0.50 0.34 0.35 0.62 0.54 0.69 0.70 0.65 0.60 0.35 0.49 0.71 0.73 0.40 0.36 1.10 1.17 0.43 0.48 0.83 0.77 0.96 0.89 0.88 0.99 0.95 0.88 0.86 0.81 1.09 0.91 0.60 0.62 0.55 1.02 1.00 0.58 0.54 0.64 0.62 0.44 0.56 0.59
216
D. FONTIGNIE AND J-G. SCHILLING
T A B L E II (continued) ID *~
La
Ce
Nd
Sm
Eu
Tb
E N l l 3 14D-2g ENl13 13D-lg ENl13 13D-2 EN113 13D-4 PAO4-12-A E N l l 3 12D-1 E N l l 3 12D-2 ENl13 llD-1 EN113 llD-2 ENI13 lOD-lg E N l l 3 lOD-2 ENII3 9 D - l A g E N l l 3 9D-2g EN113 8D-lg EN1138D-2 ENl138D-4g PAO4-11-A PAO4-11-B PA04-11-C E N l l 3 7D-lg E N l l 3 7D-2g ENl1341D-Ig ENl1341D-2 EN1136D-1Ag EN1136D-2 ENII3 42D-lg ENI1342D-2 EN1135D-1Ag ENI13 5D-2 ENI13 43D-1 ENI1343D-2g ENI134D-1 ENI13 4 D - l A g E N l l 3 4D-2 E N l l 3 44Dol EN11344D-5 ENI133D-Ig ENI13 3D-2 ENI13 2D-1 ENl132D-2 E N l l 3 45D-lAg ENI13 45D-2 EN113 1D-I ENI13 1D-2 EN11346D-I EN11346D-2 EN11347D-1A ENII3 47D-2 ENII3 48D-lg E N l l 3 48D-2
3.15 1.78 1.72 4.37 6.70 7.00 9.26 7.42 9.58 6.39 6.94 7.62 7.27 6.89 6.94 6.18 6.80 6.47 7.08 12.25 14.05 9.90 8.44 15.41 16.89 8.10 9.48 1.70 1.80 5.53 5.38 2.18 2.24 2.58 3.90 2.21 8.17 7.97 7.75 5.20 9.76 4.59 3.26 7.38 2.72 2.78 3.92 3.98 4.85 4.61 0.3
10.32 7.84 7.14 15.39 20.38 20.07 25.97 19.65 27.72 19.27 20.30 21.91 21.86 19.74 20.24 17.41 20.54 18.05 20.97 31.44 34.05 26.13 23.32 37.16 41.42 22.24 25.76 5.89 5.95 15.42 16.00 8.06 7.90 8.94 10.00 6.25 21.13 20.94 20.56 15.19 31.80 14.74 9.91 23.36 8.67 8.87 14.20 14.06 16.92 16.77 0.84
9.64 7.59 14.44 14.04 18.93 14.27 18.40 17.60 15.69 18.80 18.76 16.78 15.13 21.23 20.05 14.26 6.10 4.96 11.50 11.83 6.43 6.04 14.37 12.50 13.49 11.54 8.72 17.96 7.71 12.31 13.99 14.80 14.44 0.58
3.34 3.15 3.08 4.32 5.59 5.23 6.39 4.53 6.70 5.04 5.22 5.72 5.35 5.00 4.70 4.07 4.33 4.24 3.99 5.00 5.56 4.98 4.78 5.57 5.52 4.49 5.30 2.20 2.01 3.77 3.93 2.56 2.69 2.76 2.64 2.13 3.97 3.71 4.02 4.30 7.84 5.14 3.22 6.18 2.78 3.17 4.30 4.58 5.47 4.94 0.21
1.33 1.27 1.15 1.85 2.08 1.70 2.19 1.55 2.28 1.86 1.84 1.99 1.88 1.59 1.71 1.48 1.73 1.62 1.51 1.69 1.94 1.71 1.67 1.89 1.93 1.60 1.81 0.88 0.86 1.27 1.37 1.01 1.07 1.10 0.95 0.84 1.41 1.42 1.45 1.61 2.56 1.70 1.15 2.13 1.13 1.19 1.64 1.58 1.86 1.96 0.074
0.91 0.71 0.73 1.13 1.30 1.19 1.62 0.96 1.56 1.30 1.20 1.35 1.28 1.19 1.12 0.95 1.14 1.15 0.87 1.04 1.12 1.02 1.02 1.02 1.01 0.94 1.16 0.58 0.58 0.83 0.90 0.65 0.67 0.70 0.56 0.54 0.85 0.75 0.86 1.10 1.91 1.21 0.81 1.57 0.69 0.67 1.02 1.13 1.29 1.29 0.049
C h o n d r i t e s .2
Dy 6.16 4.76 4.51 8.20 7.21 9.41 5.76 9.88 7.57 7.45 7.46 7.99 6.88 7.04 6.79 5.67 5.89 5.38 7.11 4.16 3.62 5.26 5.15 4.50 4.55 3.74 3.69 4.76 5.18 6.70 11.53 6.79 4.86 10.10 4.10 4.50 6.69 6.99 8.06 0.31
Tm
Yb
Lu
( L a / S m ) n .2
0.49 0.48 0.74 0.83 0.79 0.98 0.97 0.85 0.89 0.76 0.77 0.84 0.72 0.57 0.57
3.50 2.72 2.60 4.59 5.24 4.54 5.61 3.46 5.53 4.55 4.60 4.73 4.43 4.13 4.19 3.25 3.63 3.51 2.86 3.08 3.63 3.29 3.19 3.10 2.97 3.23 3.68 2.41 2.35 2.86 2.96 2.50 2.72 2.88 2.09 2.23 2.57 2.51 2.94 4.27 7.39 4.81 3.19 6.06 2.46 2.63 4.23 4.32 4.98 4.80 0.18
0.49 0.38 0.37 0.66 0.68 0.67 0.74 0.49 0.82 0.61 0.63 0.64 0.58 0.60 0.59 0.44 0.51 0.47 0.39 0.41 0.50 0.48 0,41 0,41 0.40 0.47 0.52 0.34 0.32 0.39 0.41 0.35 0.39 0.40 0.27 0.32 0.32 0.32 0.42 0.60 1.06 0.68 0.47 0.83 0.33 0.37 0.62 0.64 0.74 0.68 0.025
0.66 0.40 0.39 0.71 0.84 0.94 1.01 1.15 1.00 0.89 0.93 0.93 0.95 0.96 1.03 1.06 1.10 1.07 1.24 1.72 1.77 1.39 1.24 1.94 2.14 1.26 1.25 0.54 0.63 1.03 0.96 0.60 0.58 0.65 1.03 1.73 1.44 1.50 1.35 0.85 0.87 0.63 0.71 0.84 0.68 0.61 0.64 0.62 0.62 0.65
0.46 0.42 0.45 0.55 0.44 0.75 1.21 0.79 0.56 1.01 0.43 0.47 0.82 0.93 0.77 0.0315
- - = n o t detected; I N A A analyst: B. McCully, U R I . *Jg s t a n d s for glass, otherwise pillow interior. *2Average o f 20 c h o n d r i t e s f r o m S c h m i t t et al. ( 1 9 6 4 ) except for Tin, Yb a n d Lu which were a d j u s t e d for systematic analytical biases between laboratories.
86Sr/86Sr AND REE VARIATIONSALONGTHE EASTERMICROPLATEBOUNDARIES
217
TABLE III
TABLE III (continued)
Trace-element concentration ( p p m ) by INAA in basalt glasses from the boundaries of the Easter Microplate and the East Pacific Rise
ID *l
Sc V
Cr
Co Mg( L a / S m ) . .3 number.2
ENII313D-lg ENII313D2 EN11313D-4 PAO4-12-A ENII312D-1 ENII312D-2 ENI1311D-1 ENl1311D-2 ENl1310D-lg ENl13 IOD-2 ENl139D-1Ag ENl139D-2g EN1138D-1g EN1138D-2 ENI138D-4g PAO4-11-A PAO4-11-B PA04-11-C ENl13 7D-lg EN1137D-2g EN11341D-lg
32 33 44 44 42 41 40 40 41 42 40 41 39 39 40 42 40 33 33 39 37 38 31 30 37 41 38 40 43 41 34 34 36 36 41 30 32 38 43 38 43 41 43 31 31 42 41 41 39
450 548 130 80 117 124 187 9 44 47 84 87 221 227 279 205 198 242 201 188 229 232 234 327 140 126 344 358 270 251 369 376 347 338 396 241 263 167 89 118 130 179 84 383 373 247 233 287 263
44 52 50 44 42 41 39 45 42 43 40 41 40 40 39 40 39 36 37 36 39 39 39 42 45 40 43 44 41 39 57 58 58 41 45 37 39 38 44 38 44 39 46 42 43 40 38 42 40
1D*l
Sc V
Cr
Co Mg( L a / S m ) . .3 number.2
EN11335D-lg ENII335D-2g ENl1336D-1g ENl1336D-2 EN11334D-Ig ENI1334D-2 ENl1337D-1Ag ENl1337D-2 ENlI338D-I ENII338D-11g ENI1333D-1 ENII333D-2 EN11332D-1Ag ENl13 32D-2 ENl13 31 D-1 EN113 31D-2g ENll3 30D-lg EN 113 30D-2g ENll3 29D-1g ENll3 29D-2 EN11328D-1Ag EN 113 28D-2 ENl13 27D-1 ENl l 3 27D-2 ENl13 26D-1g EN113 26D-2 EN113 25D-lg EN 113 25D-2g ENl13 24D-Ig EN 113 24D-2 EN113 23D-lg EN 113 23D-2 ENl13 22D-1 ENl13 22D-2 ENl l 3 21D-1 ENl l 3 21D-2 ENl l 3 20D-1 ENll3 20D-2 EN113 18D-I EN113 17D-I ENl l 3 17D-2g ENl l 3 16D-lg ENII3 16D-2 ENII3 39D-1 ENl13 39D-2g ENl13 15D-1 ENI13 15D-2 ENl13 40D- lg EN113 40D-2 ENII3 14D-lg ENl l 3 14D-2g
43 43 42 41 39 38 50 43 42 42 42 38 40 37 45 43 40 42 42 45 37 38 40 42 35 34 42 40 42 43 42 42 40 41 41 42 42 40 43 37 39 35 37 41 42 39 42 44 43 40 42
310 305 267 265 335 353 194 167 190 191 194 102 261 314 255 244 393 96 192 156 314 319 358 368 314 389 187 275 136 148 223 127 117 116 199 190 315 175 64 239 275 280 279 170 224 169 218 403 206 209 226
42 42 40 39 41 37 47 41 44 45 41 38 41 39 43 43 43 44 43 62 43 46 39 47 52 55 41 43 42 42 42 43 41 44 39 39 45 41 32 40 42 38 40 39 44 43 41 43 42 39 41
299 322 341 342 291 275 390 387 341 339 340 324 357 297 337 332 288 394 350 369 245 240 267 250 181 182 329 288 331 333 322 361 375 396 424 337 313 349 539 329 311 276 276 353 344 487 438 257 330 320 318
61.7 62.3 60.0 65.4 54.4 60.3 57.6 16.2 60.0 68.8 59.2 56.6 60.5 66.3 62.0 68.4 59.0 58.1 58.0 58.0 53.2 52.1 51.5 55.3 59.0 57.3 61.5 66.6 63.3 54.1 58.6 46.9 52.6 65.2 61.7 62.6 61.9
0.51 0.49 0.57 0.55 0.44 0.43 0.51 0.50 0.34 0.35 0.62 0.54 0.69 0.70 0.65 0.60 0.35 0.49 0.71 0.73 0.40 0.36 1.10 1.17 0.43 0.48 0.83 0.77 0.96 0.89 0.88 0.99 0.95 0.88 0.86 0.81 1.09 0.91 0.60 0.62 0.55 1.02 1.00 0.58 0.54 0.64 0.62 0.44 0.56 0.59 0.66
ENl1341D-2
EN1136D-1Ag EN1136D-2 EN11342D-lg ENl1342D-2 ENII35D-IAg EN1135D-2 EN11343D-1 ENl1343D-2g ENl134D-1 EN1134D-1Ag EN1134D-2 EN11344D-I EN11344D-5 EN1133D-Ig ENI133D-2 ENl132D-I ENI132D-2 EN11345D-1Ag EN11345D-2 EN1131D-1 EN113 1D-2 ENlI346D-1 EN11346D-2 EN11347D-1A ENI1347D-2 ENI1348D-Ig EN11348D-2
235 212 405 446 407 408 350 468 417 408 429 411 355 347 332 335 352 283 323 304 329 266 244 366 268 259 353 337 187 182 189 245 260 261 232 350 382 299 402 383 460 214 214 335 360 404 362
66.0 66.8 52.3 47.9 47.0 44.6 55.0 42.0 60.2 45.7 49.8 50.5 55.7 55.3 59.6 56.6 58.2 51.4 59.0 59.5 60.8 61.7 67.5 68.6 60.8 66.2 66.2 63.5 66.1 64.4 54.5 52.5 47.6 55.4 46.0 69.5 65.2 59.5 58.2 -
0.40 0.39 0.71 0.84 0.94 1.01 1.15 1.00 0.89 0.93 0.93 0.95 0.96 1.03 1.06 1.10 1.07 1.24 1.72 1.77 1.39 1.24 1.94 2.14 1.26 1.25 0.54 0.63 1.03 0.96 0.60 0.58 0.65 1.03 0.73 1.44 1.50 1.35 0.85 0.87 0.63 0.71 0.84 0.68 0.61 0.64 0.61 0.62 0.65
- - = not detected; INAA analyst: B. McCully, URI. , l g stands for glass, otherwise pillow interior. *2Mg-number=Mg2+/(Mg2+ + F e 2+ ) atomic ratio assuming an atomic ratio of Fe3+ / (Fe 2+ + F e 3+ ) =0.14. *3La/Sm ratio normalized relative to chondrites.
218
D. FONTIGNIE
10 z
AND J-G. SCHILLING
(La/Sm)n (a)
West Branch (a)
~ /i
fi i
,
1.o 101-
I 24
o.o La
102-
Ce
Nd
Sm
b
Eu
Dy
Tm
b
I 26
i 28
Lu
2°6pb / 2°4pb (b)
East Branch
,
(b)
,~
.r, i:
/'4
•,"
~,
[it
19.0
101 18.0
; 24
17.5 ,
i
La
Ce
,
,
i
~
Nd
Sm
Eu
~
i
,
Tb
Dy
i
i
i
Tm
/
Yb
I 28
I 28
A
Lu
87Sr / 86Sr
Fig. 2. REE patterns for the West Rift (a) and East Rift (b) of the EMP.
to 0.7032. Strangely enough, the lower and upper isotopic bounds are represented by the two picritic basalt glasses (G and d ). The 875r/86Sr latitudinal profiles along the East and West Rifts of the EMP mimic that of ( L a / S m ) , and Pb isotope ratios (Fig. 3 ). Consequently, there are rather good positive linear correlations between these variables (Table IV). The East Branch is more radiogenic than the West Branch and the data scatter about a general dome-like trend which culminates at around 26 ° S. Superimposed over this general trend are small 87Sr/a6Sr spike-like peaks which are poorly understood. The southern spike occurs at station d, though this basalt is a LREE-depleted picritic basalt glass. The real maximum is apparent at the station fwhich is much more conformable in terms of Sr and Pb isotopes,
(c) !
,
0.7030
/i
0.7025
Latltude°S
0.7022
214
I 26
I 28
Fig. 3. Latitudinal profiles between 22 ° and 30°S for: (a) (La/Sm).; (b) 2°6Pb/2°4Pb; and (c) 87Sr/86Sr.
(La/Sm) n and ridge elevation as well. Two samples were analyzed at station m (located in segment 5), just north of the proposed 25°S propagating rift tip. One sample is a young basaltic glass collected on the top of a recently active seamount. The other is an older
NazO TiOz (La/Sm), zo6pb/2O4pb 2OTpb/zO4pb 2OSpb/2O4pb STSr/a6Sr La Ce Nd Sm Eu Tb Dy Tm Yb Lu Sc V Cr Co Mg
MgO CaO
SiOz A1203 FeO*
CaO Na20 TiO2 (La/Sm), 2o~pb/ZO4pb 2O~pb/2O4pb 2Oapb/2O4pb 87Sr/n6Sr La Ce
MsO
SiO2 A1203 FeO*
Sm
0.3365 0.4949 -0.3221 -0.4925 0.3251 0.4853 -0.6380 -0.7063 -0.5463 -0.5795 0.4613 0.2512 0.7567 0.6783 0.7010 0.4224 0.5148 0.3534 0.4890 0.3511 0.5207 0.3340 0.3338 0.2071 0.8916 0.7383 0.9472 0.8447 1.0000 0.9387 1.0000
Nd 0.4227 -0.4235 0,4294 -0.6606 -0.5456 0.3129 0.6350 0.4060 0.3401 0.3257 0.3170 0.1936 0.7202 0.8338 0.9312 0.9804 1.0000
Eu
TiO2
0.5489 -0.5332 0.4854 -0.5859 --0.4814 -0.0019 0.4353 0.0562 -0.0067 0.0152 -0.0212 -0.0267 0.5522 0.6965 0.7145 0.9163 0.8950 0.9671 1.0000
Dy 0.4699 -0.5961 0.3605 -0.3236 0.1739 -0.3908 0.0286 -0.3585 -0.3836 -0.3947 -0.3881 -0.3192 -0.3183 -0.2493 -0.1875 0.0330 0.0255 0.2152 0.1969 0.4837 0.3643 0.3755 1.0000
Sc
-0.0928 -0.0209 0.0691 -0.1201 -0.3039 0.1488 0.3832 0.7444 0.9760 1.0000
0.5693 -0.6019 0.5666 -0.6226 -0.4523 0.0374 0.4562 -0.1055 -~1008 -0.0956 -0.1373 -0.1830 0.2596 0.4253 0.4661 0.8186 0.8017 0.9330 0.9650 0.9749 0.9910 1.0000
Lu
-0.1200 -0.0199 0.0872 -0.1371 -0.3298 0.1599 0.4130 0.7631 1.0000
0.6077 -0.8426 0.6755 -0.7430 -0.2703 -0.0784 0.6068 0.0201 -0.0453 -0.0726 -0.0707 -0.1647 0.1786 0.2523 0.4443 0.5287 0.4819 0.6277 0.5263 0.6404 0.6277 0.6303 0.5767 1.000
V
-0.1200 -0.0059 0.0717 -0.1272 -0.3207 0.1301 0.4022 0.7954 0.9943 0.9762 1.0000
Ce
-0.4679 0.6540 -0.6354 0.6741 0.4317 0.0452 -0.5475 -0.2781 -0.1479 -0.1452 -0.1431 -0.0275 -0.4496 -0.4986 -0.5083 -0.6356 -0.6082 -0.6587 -0.6683 -0.6578 -0.6050 -0.5967 -0.3106 -0.7157 1.0000
Cr
-0.6754 0.3834 -0.0946 0.5850 0,0573 -0.0957 -0.3895 -0.4396 -0.1557 -0.1871 --0.1656 0.0064 -0.4625 -0.4445 -0.4644 -0.3820 -0.3329 -0.2580 -0.2765 -0.3391 -0.1739 -0.1518 0.0463 -0.3230 0.3671 1.0000
Co
-0.4363 0.6999 -0.6867 0.7029 0.5163 -0.0437 -0.5969 -0.0774 0.0342 0.0275 0.0479 0.0479 -0.2497 -0.3228 -0.3401 -0.4964 -0.4852 -0.5536 -0.5368 -0.5943 -0.5686 -0.5827 -0.3437 -0.6364 0.5455 0.3105 1.000
Mg
-0.2192 0.2112 0.2839 0.0187 -0.1892 -0.2582 0.0977 0.2516 0.3086 -0.0079 -0.5088 -0.5692 -0.2921 -0.5432 -0.5782 -0.0057 0.2732 0.2830 0.2923 0.6368 0.6617 0.6749 0 . 8 8 9 1 0.8070 0.9125 0 . 6 8 6 1 0.6389 0.8955 0.6676 0.6238 0.9298 0.7055 0.6489 1.0000 0.5582 0.5065 1.0000 0.9801 1.0000
2°6pb/2°apb 2°7pb/2°4Pb z°aPb/Z°4pb aTSr/86Sr La
0.5806 -0.5934 0.5468 -0.6207 -0.4279 0.0293 0.4469 -0.0858 -0.1016 -0.0984 -0.1347 -0.1779 0.2815 0.4445 0.5116 0.8314 0.8163 0.9492 0.9703 0.9841 1.0000
Yb
0.0480 -0.0535 0.0799 -0.3281 -0.3539 0.2353 0.5015 1.0000
La/Sm
0.6949 -0.6841 0.5831 -0.7121 -0.5104 -0.0704 0.5874 0.2229 0.0295 0.0682 0.0231 -0.0006 0.7276 0.8282 0.8854 0.9422 0.9274 0.9692 0.9744 1.0000
Tm
-0.2063 0.3103 0.1624 -0.6715 -0.0489 0.7773 -0.1876 -0.8421 -0.2304 -0.7573 1.0000 0.2823 1.000
Na20
0.5300 -0.5671 0.5416 -0.6765 --0.5001 0.1322 0.5844 0.1562 0.1251 0.1187 0.0985 0.0210 0.5029 0.6479 0.7514 0.9375 0.9262 1.0000
Tb
CaO
-0.7080 0.3124 -0.6764 -0.0229 1.0000 -0.8369 0.8406 0.3807 1.0000 -0.7412 -0.7235 1.0000 0.5165 1.0000
MgO
1.000
FeO"
A1203
SiO2
Linear correlation coefficients between selected geochemical variables
TABLE IV
0
r~ t~
"0 t"
O
E
K
m
m m
re
X
>
z
m rll
Z
O~
-7.
220
D.
FONTIGNIE
AND
J-G.
SCHILLING
87Sr/SSSr (a) ~d • . . . . . . . . .
. .
..
•
°f
0 . 7 0 3 0 .H
• • • • -
=H • • , "2
o4
.k a
n
oC
i A • °h 5=6 °
7wl
e ° oo :e N
o.7o25
°p
m.~ .~ .,:~ .z •v .~ ;..• L •J K,
•F
"G
(La/Sm)n
01-5
0.7020 0.0
11o
115
87Sr/86Sr (b) . . .
.•
•
0 . 7 0 3 0
ft
.•.
,H .. ,2
•, • " • "
• X
0 . 7 0 2 5
,(3
."
• ."
,M
YOOV3
*L
.m
5 1 . '6 7 . "
o3og
-4 OC
, " . •
.ZA.
. ."
,..
12 B
b•
1 |*'P
.9 •Z
°s ,k
n
8 Fa e m
W~
•
. • "
. " ' " " ..
"
"÷"q..
oK
. . . . . • •
2O6pb/2O4pb I
0.7020 17.5
I
I
18.0
19.0
2O6pb/2O4pb . • • • ....
(c)
. . .
"
of
• •
o3 ,s °4 A ,
Ih
. c
°k
,.J .,, :so
19.0
oe jp -
,e
I11
,1
h
•n , o
B°,
.--
oF
~9 8
z . . m o2 W
:v
.H
aobe7
X
...~o..j
I K
, "
°c
,#E
. .
. ."
.
. .
18.0 •K
. • • •
(La/Sm) n 17.5 0.0
I
I
I
0.5
1.0
1.8
Fig. 4. Correlation diagrams for: (a) (La/Sm)n vs. S7Sr/S6Sr; (b) ( L a / S m ) , vs. 2°6pb/2°4pb; and (c) 2°6pb/2°4pb vs. 87Sr/S6Sr"
SrSr/a6SrANDREEVARIATIONSALONGTHE EASTERMICROPLATEBOUNDARIES
looking basalt which appears to belong to the northeastern segment 4 in term of bulk chemistry but not from Sr and Pb isotope composition. Along the West Rift, 875r/S6Sr increases progressively from north to south. The highest value is reached at the most southern station, which is also the closest from the East Rift. The regular and general trend is scattered by the sample H, the picritic basalt G and the samples N and K. Reasons for some of this scatter are discussed in Section 6. Finally, the 87Sr/ 86Sr profile along the West Rift does not confirm the possibility of a small spike-like radiogenic isotope anomaly around 25°S on the West Rift (samples H and I), as suggested by the Pb isotope variation and discussed by Hanan and Schilling ( 1989 ). Within the binary mantle plume-asthenosphere mantle source mixing model discussed by Hanan and Schilling (1989), the good linear correlations observed in Fig. 4 between the Pb isotope ratios and 878r/86Sr, rather than hyperbolic trends, indicate that the Pb/Sr concentration ratio in the two mixing end-members must be similar. Furthermore, the high degree oflinearity between 875r/86Sr and (La/ S m ) , (Fig. 4; Table IV) would also suggest similar Sr/Sm ratios in the two end-member sources. A noticeable amount of curvature has been previously noted between (La/Sm) n and Pb isotope ratios (Hanan and Schilling, 1989 ), suggesting higher P b / S m ratios in the enriched mantle source of this region. A plot of Pb isotope ratio with S m / L a shows an hyperbolic trend of opposite curvature, suggesting lower Pb/La ratios in the enriched source. In other words, the scale of relative enrichment, or degree of incompatibility, in the processes responsible for the fractionation between these two types of mantle sources in the region appears to have been La> P b > Sr> Sm. 5. Statistical methods
Our Easter Microplate data set is now composed of 48 basalt glasses from 47 different 1o-
221
calities. Each basalt glass is described by 27 geochemical variables, which are: 7 major elements: 10 REE: 4 transitional elements: 4 isotopic ratios: 2 derived variables:
SiO2, A1203, FeO *, MgO, CaO, Na20, TiO2 La, Ce, Nd, Sm, Eu, Tb, Dy, Tm, Yb, Lu Sc, V, Cr, Co 2°6pbF°4pb, 2°Tpb/2°4pb, 208pb/204pb' 875r/a6Sr (La/Sm)., Mg-number [Mg/(Mg+ Fe 2÷ ) ]
To maximize the number of samples used in the multivariate analysis, we did not use K20 and P205 because there were too many missing values (Schilling et al., 1985 ). Although there are statistical methods for handling missing values, we chose to avoid them because of the many assumptions involved and the biases these could introduce. In what follows, we will treat and interpret the above variables together and simultaneously, instead of successively and independently. The multivariate statistical methods used are primarily drawn from those described by Tatsuoka ( 1971 ), Green (1976), Le Maitre (1982) and Dagnrlie (1986). The computer programs were developed by the first author in GWBASlC for an Olivetti ® M24, and are IBM ® PC compatible with minor modifications. Listing of these programs are available upon request from the first author. The data set is composed ofp samples (48) each described by n variables (27). This set can be reported in a matrix A composed o f p rows and n columns, with pXn entries a(i,j), or of dimension p × n. As it is commonly the case, p < n. Each sample is now expressed in a multiple space by a n × 1 component vector. A "mean" in such a space is also represented by a vector of n elements. For a given data set, it is customary to compute for each variable (column) the deviation of every sample from its mean and report the results in a mean-corrected matrix A~ instead of ,4. The product ,4aW,4d is the sum-of-the,squares-and-crossproducts matrix (SSCP) which is the basic
222
D. FONTIGNIE AND J-G. SCHILLING
block of any multivariate statistical manipulation and analysis (e.g., Green 1976). The scalar variance is replaced in multivariate analysis by an n × n variance-covariance matrix D, whose principal diagonal d(i,i) are the variances and the other elements d(i,j), the covariances. It is defined by:
O = [ 1/ ( p - 1 ) ]A d "rAa
( 1)
Because of the uneven nature of the geochemical variables in terms of units, magnitudes, range of variability, analytical errors and geological sampling errors one must weight in some rational fashion the raw data and arrive for direct comparison to some dimensionless geochemical variables (Le Maitre, 1982; A1l~gre et al., 1986). The reader is referred to those authors for a more thorough discussion of these problems. Because of the homogeneous quality of the analytical data of the EMP we did not weight the data for "analytical" and "geological" errors as done by All~gre et al. ( 1986 ). Their isotopic data set were global in nature and their generalized reduction m e t h o d concerned with inhomogeneous analytical data quality, particularly for 2°7pb/2°6pb relative to other Pb, Sr and Nd isotope ratios and relative to its limited variation range in m o d e m oceanic basalts. Instead, we weighted the variance-covariance matrix D in such a way that the variance of all the variables are equal to unity. This is equivalent to using the correlation matrix R instead of D in the following way:
Adw=AdW
(2)
where Wstands for the weighting diagonal matrix whose elements, w(i,i), are the reciprocal of the square root of the diagonal elements of the matrix D [i.e. w(i,i) = 1 / ~ ]; and
R = [ 1 / ( p - 1 ) ],4aw "rAdw = [ 1 / ( p - - 1 ) ] (,4aW)T(,4aW)
= [l/(p-1)]WV(Ad'rAo)W = [l/(p-
1)] W T [ D / { 1 / ( p -
1}]W
=WDW
(3)
since for a diagonal matrix W T = W. Information can be drawn from the matrix R (or alternatively, another derived matrix where D is weighted differently) either about the samples or about the variables. Both are considered to be "objects". In the former case, the R-mode, the rows are taken into account in a derived matrix Adw'rAdw of n × n dimension whose rank is ~
86Sr/a6SrAND REE VARIATIONSALONGTHE EASTERMICROPLATEBOUNDARIES
CA reveals a hierarchy among the data by grouping together data progressively more distant from each other, statistically speaking, in multivariate space (Appendix, A-2 ). There are several ways to measure statistical distances between objects and to group them (Le Maitre, 1982). Usually, we have used the "single-linkage of the generalized distances D 2'' (Appendix, A-6 ). DA enhances and optimizes differences between groups a priori chosen (Appendix, A-3 ). Similarly to "univariate analysis", the statistical significance of differences between two multivariate means can also be tested using extended and well-defined statistics (Appendix, A-4). The univariate equivalent testing of multivariate variability becomes an "analysis of the covariance" (Appendix, A-5 ). 6. Outliers
Singular samples ("outliers") from this data base can be recognized from their statistical distance to some mean. We have applied this principle in three different ways: ( l ) Arbitrarily identify outliers which deviate by 3-standard deviations from the means. No real statistical level is attached to such value because the real nature of the distribution is unknown. These outliers are listed in Table V. (2) We consider samples lying outside of an ellipse of 95% confidence in the correlation diagrams 87Sr/g6Sr vs. 2°6pb/2°4pb (Fig. 4b) or vs. (La/Sm)n (Fig. 4a). For the same reaTABLE V "Outliers": samples having one or several variables outside the _+3 standard deviations range from the mean Sample
Number of variables
Variables
G m f d 7
2 1 2 4 7
SiO2, Co Na20 (La/Sm)n, La, Ce SiO2, MgO, 875r/86Sr, Co SiO2, all MREE and HREE
223
son, the level of confidence is again arbitrary. Because of the very high correlation between the different Pb isotope ratios, comparison of Sr isotopic ratios with 2°Tpb/2°4pb or 2°8pb/ 2°4pb would be redundant. ( 3 ) We consider collectively k selected geochemical variables and calculate the generalized distance of individual samples from the centroid in that k-dimensional space. Fig. 5 illustrates this result applied separately to the major elements (Fig. 5a), a selected group of REE (Fig. 5b), the four isotopes ratios (Fig. 5c), and finally the set of four transition metals (Fig. 5d). The results of these three different methods are essentially concordant in revealing the dominant outliers. These are: ( 1 ) The picritic basalts d and G. These samples were known to be anomalous in bulk chemistry and in their mineralogy (Sigurdsson et al., 1985). This is confirmed in Fig. 5a, as well as by the REE data set (Fig. 5b ). The same conclusion is reached using the set of the four isotope ratios (Fig. 5c) and the correlation diagrams (Fig. 4). The latter diagrams show that sample d is the most radiogenic in Pb and Sr, and sample G the least of the entire EMP data set; and for that matter of the entire EPR so far published (see comparison in Hanan and Schilling, 1989). (2) Samples 2 and H. These samples outlaw the correlation especially in the Sr vs. Pb isotope diagram (Fig. 4b). In the (La/Sm)n diagram (Fig. 4a), they are inside but near the edge of the ellipse of confidence. Their abnormal character is also well apparent in Fig. 4c. The altered character of the pillow basalt from station H was evident to the naked eye. The freshest fragments were picked. Two fractions were analyzed, one with an acid leach prior dissolution, the other without. The unleached sample gave a higher 875r/86Sr ratio of 0.702928, and the leached fraction a value of 0.702866; thus suggesting seawater alteration. As for sample 2, since the 875r/86Sr ratio is enhanced with respect to the Sr-Pb isotope cor-
224
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86Sr/a6Sr AND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES
relation, we presume that this sample suffered also some seawater alteration. (3) Sample 7 is unusually low in REE and SiO2 contents, probably because of its porphyritic nature. Its ( L a / S m ) , and Sr and Pb isotopic compositions show no unusual character. (4) Sample f lies outside the confidence ellipse in the Sr vs. (La/Sm)n diagram (Fig. 4a), but otherwise has no real unusual character. It is located on the East Rift (26.8°S) where the latitudinal profiles in La/Sm and Pb and Sr isotope ratios and ridge elevation reach a broad maximum (Fig. 3). 7. Geochemical classification based on multivariate analysis in Q-mode
Various geochemical parameters are conventionally used in petrogenesis for sorting out probable geological processes in operation, depending on their sensitivity to such effects. For example, it is readily accepted that Pb and Sr isotope ratios reflect mantle source heterogeneities if equilibrium partial melting prevailed. Major-element ratios such as FeO/ MgO, CaO/MgO, CaO/A1203, or NazO/CaO reveal the combined effect of varying extents of melting and fractional crystallization. Incompatible to lesser incompatible trace-element ratios such as La/Sm reflect partial fusion, if the operative degree of melting (F) is small (say < 10%). But it tends to reflect mantle source heterogeneities i f F > 10-15%, such as in the generation of tholeiitic volcanism. Such conventional wisdom is based on some 25 years of accumulated evidence in experimental petrology and geochemistry and forward modelling. It is possible to classify such geochemicalpetrological parameters according to their relative sensitivities to magma formation and evolution processes and mantle source heterogeneities, using multivariate analysis in Qmode. This approach was alluded to by All6gre et al. ( 1986 ) and is considered here to provide
225
objectively relative affinities between the geochemical variables. The method is considered here to illustrate its potential not only as a classification tool, but to some extent also in petrogenesis modelling because the closer these geochemical variables are to each other, the more geochemically alike they are, and the more likely their variation reflect a common cause or operative process. In view of the great number of geochemical variables and the difficulty of representing graphically on paper their affinities in such multi-dimensional sample space, we have made us in Q-mode of both PCA (Fig. 6a and b) and CA using Euclidean distances (Fig. 6c). PCA gives the relative position of the variables in some optimized projections. A part of the information is lost by reducing the multispace, here 22 dimensions, to a much smaller space, 3 in this case, by projecting onto principal axes 1,2 and 1,3. Only 72% of the total information can be represented in this 3-dimensional space. The three principal axes carry respectively 35.7%, 26.1% and 10.2% of the total variability. In contrast, a better estimation of the statistical distances between the variables is given by CA and the corresponding dendrogram. The latter illustrates the hierarchy of the distances between the 22 variables. However, the shortcoming of CA is that it does not provide any sense for the relative position of the variables. Thus, we emphasize that interpretation on the basis of these two types of analyses should be done simultaneously by considering together the overall information represented in Fig. 6a-c. Several major "geochemical" groupings are readily recognized in these two PCA projections: at one pole along principal axis 1, the major elements CaO, MgO, A1203, Mg-number, Co and Cr form a broad cluster. At the other end of axis I, two clusters are present, namely: incompatible trace elements and the three Pb and Sr isotope ratios. On the other hand, SiO2, NazO and Sc have intermediate and somewhat ill-defined positions or affini-
226
D. FONTIGNIE AND J-G. SCHILLING
(a)
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ties relative to these first-order groups. F e O * has an affinity for the moderately incompatible elements. Further sub-groups or even close
pairs, such as La-Ce or Eu-Sm,, can be defined. Not all these subgroups are necessarily retained in higher-order projections. For example, Fe and V are no longer close to each other in PCA projection 1,3 (Fig. 6b). Also, not that 2°7pb/2°apb is more removed from 2 ° 6 p b / 2 ° a p b than 2°8pb/2°4pb. This most likely reflects analytical uncertainties, since the analytical errors on 2°Tpb/2°4pb are significantly greater than for the other two isotopic ratios (Hanan and Schilling, 1989 ). The 2°7pb/ 2°4pb normalized variability is greater. As a result its correlation withw 2°6pb/a°4pb is decreased. Overall, however, the grouping observed make geochemical sense. As expected, the (La/ S m ) n plots close to that of the mantle source isotope indicators as well as to the most incompatible LREE, La and Ce (which are sensitive to mantle heterogeneities, partial melting, fractional crystallization and mixing as well). We interpret this to suggest that La/Sm variation in the region may also be influenced by varying degree of partial melting, as also evident from the fact that these basalts range widely from quartz to olivine and nephelinenormative compositions (Schilling et al., 1985). The middle REE (MREE) and heavy REE (HREE), F e O * and TiO2 have a close affinity• This is consistent with the observation that F e O * enrichment by extensive shallow-depth fractional crystallization among mid-ocean ridge basalt (MORB) tholeiites, as for example along the Gahipagos Spreading Center, east Pacific, is usually accompanied by an enrichment of the overall REE pattern and a resulting correlation between F e O * and Yb (Schilling et al., 1976). Note that in the dendrogram representation, the affinity of V and Yb, originally proposed by Bougault (1980), is for this region not better than for example Cr for Mg-number, statistically speaking. The usefulness of the combined multivariate classification procedure is further illustrated in the classification of individual ele-
S6Sr/86Sr A N D REE V A R I A T I O N S A L O N G T H E EASTER M I C R O P L A T E B O U N D A R I E S
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227
Eu) are at an intermediate position. The corresponding dendrogram shows at various hierarchic levels of affinity the progressive character of the REE series (Fig. 7c). At the lowest level, direct links are generally found between REE of adjacent atomic numbers (in the Masuda-Coryell REE diagram, atomic number correlates with the inverse of the ionic radius ). At the highest hierarchic level, only two major groups are recognized, the LREE (La, Ce, and presumably Pr) and the HREE (Sm to Lu ). At the next lower level of affinity one finds the three LREE, MREE and HREE groups noted earlier along principal axis I. Because of the close affinity of the four isotope ratios considered in Q-mode of analysis, one can conjecture that their variability have probably a common cause, which we interpret to be mantle heterogeneities. Therefore, the simultaneous use of these four variables together is an appropriate way to investigate mantle heterogeneity domains, their relation to ridge segmentation in the region, and their probable cause (s). We now turn to such an analysis using only these four variables. Because of their anomalous character, the two exotic picritic basalt glasses d and G will be excluded from the remaining multivariate statistical treatment.
8. Ridge segmentation 8.1. Principal components analysis (PCA)
Fig. 7. Q-mode analysis on matrix R for the REE: (a) PCA, projection onto axes 1 and 2; (b) PCA, projection onto axes 1 and 3; and (c) dendrogram for CA single-linkage, Euclidean distances.
ments within the REE group (Fig. 7). Three groups are apparent along principal axis 1, which contain 55.4% at the total variability (Fig. 7a). The LREE (La, Ce) form one pole, the HREE the other, and the MREE (Nd, Sin,
First, we briefly investigate the nature of the dispersion of the isotopic data, using the Rmode on the correlation matrix R (Appendix, A- 1 ). Fig. 8 shows the projection of the isotope data onto the principal axes 1,2 and 1,3. In a four-dimensional (4-D) space, the data scatter in the form of a very elongated and flat hyper-ellipsoid. Indeed, the first axis corresponds to 93.7% and the second to 5.2% of the total variability. The ellipsoid stretches from the less radiogenic samples (K type) to the more radiogenic ones (f type). The departure
228
D. F O N T I G N I E AND J-G. S C H I L L I N G
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from a more elongated ellipsoid comes partly from the weights of the altered basalts H and 2. Without them, the two principal axes would carry 96.3% and 3.0% of the total variability. Note that the second axis is not negligible. The scattering of the data is not simply along a straight hyperline, i.e. the limiting case of an
ellipsoid. Nor is its deviation from such a hyperline simply due to an increase scattering in the Sr ratios due to seawater alteration, because in the Pb isotope space only the second principal axis is also significant (1.3%). Thus the shape of the cloud is ribbon-like. The possibility that the EMP represents two
86Sr/S6Sr AND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES
giant overlapping ridge axes, perhaps characterized by distinct and isolated mantle source domains, was previously considered by Hanan and Schilling (1989), using only L a / S m a n d / or Pb isotopes. The test of binary mixing in three Pb isotope dimensions between the two rift populations can be conducted fairly well, since it should be two lines, or two fairly elongated ellipsoids if for analytical a n d / o r geological reasons a certain degree of heterogeneity in the Pb isotopic composition of the two endmembers is accepted. To do this, one needs first to investigate if the two ellipsoids are parallel or not. If they are, one has to determine then if the two main axes are distinct or not. The first step is to investigate if the two correlation matrices are statistically distinct, i.e. to determine if the orientation of the two ellipsoids are distinguishable or not. An analysis ofcovariance (Appendix, A-5 ) shows that they are not, ( • 2 o b s - 8 . 0 , theoretical Z 2 at 5% for 6 d.f. is 12.6). As they are not, a second step should decide if the correlation matrices, calculated separately for the two branches, are not significantly different from the matrix calculated for both branches together; that is to determine whether the two ellipsoids have indistinguishable elevations or not. In other words, we not test whether the two elongated ellipsoids are parallel, or colinear. In the latter possibility the two branches of the EMP would share he same end-members in such mixing model. The covariance analysis shows that the two trends are not distinguishable ()~2ob s = 10.9, theoretical Z 2 at 5% for 12 d.f. is 21.0). We conclude that the end-members in the binary mixing beneath the two rifts cannot be distinguished, at least by this statistical method. One could extent such test of mixing between the two rifts in 4-D isotopic space by adding the 87Sr/86Sr ratio, providing that Sr/ Pb concentration ratio in the two end-members are not too different. Otherwise, the mixing trends in such space would not be linear. We have seen in Table IV and Fig. 4 that 87Sr/ 865r is strongly linearly correlated with 2°6pb/
229
2°4pb or other Pb ratios. Thus such test is justified. Again tests I and 2 were found to be both acceptable (test 1: Z2obs = 15.7; Z2th. (10) = 18.3; test 2: Z2obs = 20.5, Z2th (20) = 31.4). We again conclude that the end-members in the suggested binary mixing taking place beneath the two overlapping rifts are indistinguishable, at least by this statistical method. However, CA and DA discussed below reveals some important differences between the two depleted type of EPR segments located just north and just south of the EMP (i.e. segments I and 8).
8.2. Cluster analysis (CA) A more objective and quantitative approach to geochemical ridge segmentation without a priori classification can be made using CA, the four isotopic ratios as variables, and generalized distances (Appendix, A-2 ). On this basis, Fig. 9a shows the connections between samples in the form of a dendrogram. A good separation of the overall data can be obtained with the first five groups. The stations H, 2 and K are too poorly connected to be attributed to any of these groups (for drafting convenience only, these three samples are labelled as group 6 in Fig. 9a). The 5-group definition is very significant (Rao's F = 19.3 with nl = 16 and n2= 126; theoretical F at 0.01% is 2.15 ). The geographical distribution along the EMP boundaries of these five statistically defined groups are shown in Fig. 9b. Geographically, not all five groups are randomly distributed. Groups 2-4 tend to form a coherent geographical structure, or isotopic segmentation, which broadly coincide with the morphotectonic segmentation shown in Fig. 1. Namely: Geographically, cluster 2 spans the northern segments I and 2. This reinforces our earlier belief that segment 2 is a mature ridge segment underlain by a "normally" depleted mantle and is merely an extension of the EPR (Hanan and
230
D. FONTIGNIE AND J-G. SCHILLING
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Schilling, 1989 ). However, segment 8 south of the EMP is represented by cluster 3 which is slightly more radiogenic and cannot be considered as normal. In contrast, cluster 5 is confined to the East Rift, where the geochemical anomaly is present and the ridge is also unusually elevated. Group 4 tends to flank group 5 along the East Branch but, interestingly, it also spread to the southeastern most tip of the West Rift, which
is also closer to the East Rift and the main geochemical anomaly. Finally, cluster I is broadly distributed along the EMP boundaries and seems to dominate segment 4. Group I is also intermediate in radiogenic Sr and Pb content (as evident in Figs. 3 and 4), and this may explain its more random geographical distribution. It is also instructive to illustrate directly the relative position of these samples and their
S6Sr/S6Sr AND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES 2
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explain the same amount of variability in DA, one has to use the projections in planes 1,2 and 1, 3 (Fig. 10b and c, respectively). The three axes carry respectively 50.0%, 27.3% and 21.3% of the total variability. PCA shows clearly the progressive radiogenic evolution of the samples from groups 2 and 3 towards the most radiogenic group 5, and the intermediate positions of groups I and 4. A similar evolution is also observed in DA for groups 2-5, but the order of the two intermediate groups 1 and 4 is reversed as a result of the distortion caused by the method, whose objective is to maximize differences among groups (see the Appendix, A-3 ). It also brings out more clearly the important difference existing between groups 2 and 3 on projection of axes 1,3 (Fig. 10c); that is, the EPR "normal ridge segments" 1 and 2 in the north and NW corner of the EMP, from that of the EPR segment 8 present south of the EMP. The difference between groups I and 3 is also optimized in DA compared to PCA (Fig. 10a-c). The two groups are both mildly radiogenic (Fig. 3 ), and hardly distinguishable in conventional 2-D isotope diagrams (e.g., Fig. 4b), but perhaps for slightly higher 87Sr/86Sr a t a given 2°TPb/ 2°6pb in group 3 relative to 1. However, the difference of multiple means between these two groups are statistically significant [F(16,4) =6.3, at 95% the F-limit is 3].
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cluster in this 4-D isotope space: (1) this is done with PCA more than 98% of the total variability is accounted for in projections onto axes 1 and 2 (Fig. 10a); and (2) in order to
An independent check of the segmentation revealed by factor analysis can be made in a somewhat less objective way, using the same isotopic data in the same space, but with an independent a priori choice of sample grouping. We now a priori divide our basalt sample population into eight groups according to their position with respect to the tectonic ridge segmentation shown in Fig. 1. The PCA representation of these eight groups are shown in Fig. 11 a, whereas the optimized
232
D. F O N T I G N I E A N D J-G. S C H I L L I N G
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isotopic differences between these eight groups a priori chosen, using DA, is shown in Fig. 1 lb. Despite the two independent approaches (i.e. with and without a priori classification ) a very similar picture is obtained because of the similarity between the isotopic structure and
the morphotectonic segmentation. The centroid of the EPR normal ridge segment I plots at one extreme of the principal axis 1. The centroid of segment 6 on the East Rift, which contains the geochemical anomaly, plots at the other extreme. Centroids from the other seg-
S6Sr/86Sr AND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES
ments plots primarily along the principal axis at intermediate distances between these two extreme poles. There is also a remarkable symmetry about segment 6, both with respect to statistical and geographical distances. Segments 5 and 7 immediately flanking segment 6 are very similar and plot in the isotopic space relatively close to segment 6. The two pairs are followed both in isotopic and geographical space by the pair of segments 4 and 8, which also located at about equal distance further out about segment 6 on the East Rift. PCA axis 1 can clearly be interpreted as a mixing line between the depleted asthenosphere type source and a plume-related type source. Note again that segment 2 is both geographically and statistically close to segment 1. The difference which statistically pulls apart segment 8 and 4 in DA is exaggerated, though significant (Fig. 11 b). We recall that the basalts from segment 8 are all clearly located off-ridge axis whereas this is not the case along segment 4 (Fig. 1 ). The distinction may suggest an aging effect for centroid 8. Although the segmentation suggested on the basis of such multivariate statistical analyses cold, to some extent, have been suggested on the basis single isotope profiles shown in Fig. 3, the power of the approach becomes more evident when more subtle differences such as between segments 4 and 8 need to be revealed and evaluated. DA has the potential to be a powerful tool for distinguishing "normal" ridge segments underlain by an asthenosphere with subtle isotopic and mean model-age differences. 10. Location of the influential plume The exact location of the so-called Easter hotspot remains uncertain. On the basis of plate reconstructions the hotspot has been located either ( 1 ) close or just west of Easter Island (Morgan, 1971; Minster et al., 1974; Hey et al., 1977; Chase, 1978); (2) in the vicinity of Sala y Gomez (Duncan and Hargraves,
233
1984; Okal and Cazenave, 1985), or (3) beneath the East Rift of the microplate (Handschumacher et al., 1981; Pilger and Handschumacher, 1981 ). The latter possibility has received support from basalts with high 3He/4He at two localities on the East Rift (Craig et al., 1984 and H. Craig, pers. commun., 1989), as well as from the good correlation of deviations in 875r/86Sr and 2°6pb/2°4pb with radial distances with respect to station f o n the East Rift (i.e. the geochemical anomaly maximum) (Fig. 12 ). For example for A2°6pb/2°apb, the correlation coefficient (r) is 0.860 and for the square of the same deviation it is even better ( r = 0.889 ). But no significant difference in the correlation could be found between the East and West Rifts. This suggest that segment 6 may indeed be a focal point of importance of controlling radially the mixing conditions and dispersion of heterogeneities along the boundaries of the EMP. This could indeed be interpreted as to suggest that the plume is centered beneath segment 6. On the other hand, we have previously suggested that the migrating ridge-hotspot source model adequately explains the geochemical anomaly observed on the East Rift and that the influential off-ridge hotspot may be located in the vicinity of Sala y Gomez (Schilling et al., 1985; Hanan and Schilling, 1989 ). We reached this conclusion on the basis of: ( 1 ) the width of the geochemical anomaly and empirical relationships previously established in this model context (Schilling, 1985 ); (2) Pb isotope compatibility of the EMP and off-ridge island volcanism in the region; and (3) the observation of a progressive decrease in radiogenic Pb from Sala y Gomez, Easter Island, and East and West Rifts of the EMP. We turn to these questions again using multivariate analysis in two ways: ( 1 ) with PCA to identify possible end-member mantle sources compatible with the binary mixing trend for the EMP, using Pb and Sr iso-
234
D. FONT1GNIE AND J-G. SCHILLING
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tope data from islands in the general vicinity; and (2) by comparing and modelling statistical distances between ridge segmentation and island groups revealed by DA and geographical distances between these segments or regions.
Fig. 13 compares the Pb-Sr isotope data from the EMP with those from ocean islands located east or west of the EMP, using PCA. It is clear that only Easter Island and Sala y Gomez Island are compatible with the EMP binary mixing tend present along PCA axis 1.
235
S6Sr/S6SrAND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES
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Neither the Polynesian Islands on the west, nor the distant Juan Fernandez-San Felix Islands on the east of the EMP are compatible with such a mixing trend. Note also that Sala y Gomez could possibly be the radiogenic-rich end-member of the EMP mixing line, whereas Easter Island already represents a mix since it overlaps with the EMP trend. This provides further and independent evidence that the offridge influential hotspot could indeed be in the vicinity of Sala y Gomez. It is interesting to note that the three older basalts from the Tuamotu Chain of atolls, west Pacific, analyzed in our laboratory (Grail et al., 1986), and one sample from Nuku Iva Island in the Marquesas, south Pacific (Vidal et al., 1984), plot very close to the Easter-Sala y Gomez end-member. This is not unexpected, since Pilger and Handschumacher ( 1981 ) have shown that the Tuamotu Chain on the Pacific Plate, and the conjugate aseismic Nazca Ridge on the Nazca Plate, east Pacific, may reflect the trace of Easter plume activity in the past, when the plume was ridge-centered. On the other
hand, this may be pure coincidence for Nuku Iva Island, as most other islands from the Marquesas are isotopically quite distinct and plate reconstructions does not suggest any connection. The second approach consists of plotting geographical distances against statistical generalized distances in Pb or Sr space, first between Sala y Gomez and the eight EMP ridge segment group centroids, assuming a priori the morphotectonic segmentation shown in Fig. 1 (Fig. 14). There is no particular trend. Thus, it is unlikely that the EMP geochemical anomaly was caused by radial dispersion into the asthenosphere of a plume located beneath Sala y Gomez. On the other hand, if the generalized statistical distances and the radial distances are measured relative to segment 6, two trends emerge with a discontinuity between the East and West Rifts (Fig. 15 ). The symmetry about segment 6 along the East Rift is particularly noticeable. We also recall that in the 4-D isotopic space representation, segment 6 plots
236
D. FONTIGNIEANDJ-G. SCHILLING D2
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Fig. 15. Radial distances vs. generalized distance for tectonic segments 1 - 8 relative to segment 6 or the EMP basalts: (a) generalized distances using the Pb isotope ratios; and (b) generalized distances using the Pb and Sr isotope ratios. Note possible discontinuity between the East and West Rifts.
closest to that of Sala y Gomez and Easter Island group than any of the other segments of the EMP (Fig. 13 ), thus suggesting a more direct geochemical link between these two groups. These relationships are also expected in the migrating ridge-plume source model discussed previously by Schilling et al. ( 1985 ) and Hanan and Schilling ( 1989 ). We also note that most recent and independent plate reconstructions carried out by Duncan and Hargraves ( 1984 ) and Okal and Cazenave ( 1985 ) place the influential hotspot also in the vicinity of Sala y Gomez. In view of these conflicting evidences, one needs to decide by some other independent means where the influential plume may be located and which of the two dynamical models may prevail. Currently we favor a plume rising in the vicinity of Sala y Gomez but tilted at shallow depth towards Easter Island and the EMP. This model does not necessarily rule out the possibility of a redistribution of excess plume-derived material from the point of discharge of the lateral plume flow channel on the East Rift (station f). It must be remembered that in order to create a geochemical gradient and excess elevation along the ridge axis, the plume flux, in this model, must exceed the flux required by passive spreading [see Schilling's (1985) model description]. The redistribution pattern would be radial if the trend revealed in Fig. 14 prevails, or somewhat more complicated if the discontinuity between the East and West Rifts revealed in Fig. 15 from the statistical multivariate analysis is emphasized. In the latter case, one can infer that the discontinuity reveals the sink effect of the active East Rift zone on the West Rift. Excess plume material reaching the East Rift would not only flow north and south along the East Rift from the point of injection (station f ), but also to a lesser extent, the plume-related tracer manages to reach the southeast most part of the West Rift where spreading is minimal, perhaps by some channeling below the 27°S pseudofault zone. From this point, the plume-related,
S6Sr/a6Sr AND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES
radiogenic-labeled, material would flow northwestward along the West Rift, be diluted and finally exhausted as a result of increasing spreading rate in this direction (Fig. 1 ). 11. Conclusions
Our conclusions will focus on two aspects: (1) multivariate statistics; and (2) interpretation of either the raw or the multivariate-manipulated geochemical data from the EMP. Three types of multivariate techniques have been used. ( 1 ) Principal components analysis (PCA), which does not distort the relative position of the data point in multispace, was found particularly useful for: (a) the Q-mode geochemical classification; and (b) in revealing probable end-members in the multicomponent mixing problem of the EMP. Its shortcoming is that it does not provide a direct numerical measure of closeness of the objects in a statistical sense. (i.e. statistical distances). (2) Cluster analysis (CA) and the dendrogram representation alleviated partly this problem, but the relative position of the objects in multispace is in turn lost. We emphasize the need of using and considering simultaneously the graphical representations provided by PCA and CA, as done in this paper for: (a) the Q-mode geochemical classification of the REE and (b) the R-mode classification of the samples in Pb-Sr isotopic space and resulting inferences obtained on ridge segmentation. (3) Discriminant analysis (DA), with its power of optimizing mutispace geochemical differences between groups a priori chosen by independent criteria (e.g., tectonic segmentation), was found useful in pinpointing more subtle isotopic differences between normal ridge segments 1 and 2, 4 and 8, or 1-2 from 4-8. As for the interpretation of the new EMP data reported, we emphasize the following: ( 1 ) The EMP basalt glasses show a particu-
237
larly large range of Pb and Sr isotopic ratios occurring over a short wavelength ( ~ 400 km), which is exceeding that of the entire EPR from 35°S to 45°N (i.e. ~ 10,000-km wavelength). This is also the case in the ondulation of the topography (Naar and Hey, 1990). It appears that the EMP isotopic anomaly is confined to the north by the 23 °S transform boundary, but appears to spill south of 27°S transverse boundary. (2) With the exception of a few outliers, the Pb and Sr isotope and La/Sm ratios are closely related, both geographically along the boundaries of the EMP as well as in sample space. As a result, the variation can readily be interpreted in terms of mixing of heterogeneous mantle domains. The possible effect of varying degrees of mantle fusion does not appear to have skewed significantly the distribution of the La/Sm ratio. (3) Whether the data were considered in 3Pb or 4-Pb-Sr isotope space, PCA, CA and DA all revealed at least three end-members: ( 1 ) a radiogenic Pb-Sr-rich component reflecting the plume influence on the EMP; (2) a radiogenic-poor end-member underlying the EPR just north of the EMP, which we associate with the depleted asthenosphere; and (3) a mildly radiogenic component, particularly in Sr, found along the EPR south of the EMP (segment 8). It is uncertain whether the later endmember is inherent of the underlying mantle source (and its past mixing and evolutionary history ), or is caused by some aging effects on these basalts which are located 20-30 km off the ridge axis (e.g., the 878r86Sr enhancement may reflect secondary high-T, or low-T, seawater alte;ation). (4) A comparison in 4-Pb-Sr isotopic space with PCA, of basalts from the EMP and hotspots on the Pacific and Nazca Plates indicates that Sala y Gomez has the greatest affinity to radiogenic-rich end-member plume component expected in the mixing model considered, followed by Easter Island, and the Tuamotu Chain. All these localities are lined up along the
238 so-called Easter hotline at ~ 26°S (Bonatti et al., 1977). The geographically more distant San Felix, Juan Fernandez, Society and Marquesas hotspots show no direct compatibility with the EMP geochemical anomaly. Easter Island represents a mixture diluted by the depleted asthenosphere. ( 5 ) Attempts to locate the influential plume, using various correlations between "statistical" and "geographical" distances, were inconclusive; but for the fact that station f o n the East Rift appears to be a focal point in controlling the radial dispersion o f plume-related material along the spreading boundaries o f the EMP. This exercise indicates that the plume may be located either beneath the East Rift a r o u n d 26°S, or due east. Instead o f modelling the Easter hotline as an elongated convective roll (Bonatti et al., 1977 ), we favor within the context of the hotspot source-migrating ridge model (Schilling, 1985 ), a plume rising in the vicinity o f Sala y G o m e z but tilted at shallow depth towards Easter Island and emerging on the East Rift of the EMP. (6) Finally, we note that the complementary and more general blob-cluster model of All6gre et al. (1984), remains a viable model for the region, since spreading rates on the EPR are anomalously low a r o u n d 26°S as result o f rift propagation and dual spreading over the EMP. The model predicts an inverse correlation between spreading rates and the wavelength and amplitude o f geochemical anomalies and associated ridge elevation. In this case, spreading rate is taken as a measure o f mantle convection rate. W h e t h e r in these two complem e n t a r y models, the most likely measure o f dispersion and dilution o f mantle plumes (blobs) is spreading rate (All6gre et al., 1984), or distance o f the migrating ridge to the hotspot (Schilling, 1985 ), remains an open question which will require more detailed considerations and tests. We emphasize that the two models are c o m p l e m e n t a r y and not mutually exclusive.
D. FONTIGNIE AND J-G. SCHILLING
Acknowledgements We t h a n k B. McCully for carrying out the REE analyses, and B.B. H a n a n and R. Kingsley for assistance in the laboratory and fruitful discussion. We thank D.F. Naar and two anonymous reviewers for useful comments. We are grateful to F. DiMeglio and his staff for neutron irradiations and facilities at RINSC. This work was partly supported by NSF (Grants OCE 8500683 and OCE 8710465) and the Swiss National F o u n d a t i o n for a Visiting Scientist grant ( 82,186.0.84 ).
Appendix A-1. Principal components analysis (PCA)
The most usual configuration of a cloud of points is a hyper-ellipsoid, a volume described by n axes in an n-dimensional geochemicalspace. PCA givesthe n perpendicular axes of the hyper-ellipsoid.The new coordinates are linear combinations of the original variables and are calculated from the eigenvaluesand eigenvectors associated either with the variance-covariance matrix D, or with the correlation matrix R. In the R-mode, the variance-covariance matrix D (or correlation matrix R) is n×n and there are a maximum of n eigenvaluesand eigenvectors.In the Q-mode,the matrix D (or R) is p × p but there are a maximum of n eigenvalues or eigenvectors. The first axis is the axis which contains the maximum variability of matrix D (or matrix R). The followingaxes are those, perpendicular to the previous ones, which explain the maximum of the remaining variability. If the ellipsoid is not a sphere, the meaning of one or more axes decrease and so, usually,a few axes onto which the objects are projected describe the cloud of points without too much loss of information. Attention has to be paid to avoid losingtoo much information in reducingthe number of dimensions. Nevertheless, for the kind of geochemical problems in hand, to be graphically useful, the considered space must be at least of two or three dimensions. This remark is also valid for DA. A limiting practical problem comes from the calculation of the eigenvalues and associated eigenvectors. The eigenvalues were calculated using Hotelling's iterating procedure (Tatsuoka, 1971 ). When the dimensionsof the matrices are large, the calculation time become prohibi-
239
S6Sr/S6Sr AND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES
tive, and sometime there is no convergence toward a solution because of numerical limitations resulting from precision.
A- 2. Cluster analysis (CA) In this analysis, the distances (generalized or Euclidean or some other measure of similarity or dissimilarity between the variables) are estimated between the various samples. The two nearest samples are then linked and grouped together. This procedure is repeated until all the samples and groups are linked. The result of this work is summarized into a hierarchic type of diagram, th "dendrogram", where samples and groups are linked two by two. The higher the connection between two groups, the greater is the difference between them. We follow the method described in Le Maitre ( 1982, p. 168 ).
A-3. Discriminant analysis (DA) In this method one calculates new variables, linear combinations of the old ones, to enhance the differences between groups a priori defined by other independent means. A maximum of n axes is so obtained. Contrary to PCA, the axes in DA are not necessarily perpendicular. However, for convenience they are usually drawn perpendicular. Since the axes are not orthogonal, DA projections, in contrast to PCA projections, induce some distortion.
A-4. Comparison o f multiple means Hoteling's T 2 is the generalization of the Student's t statistics in a multiple space to compare the multivariate means of two groups of data. In a multiple space the means are vectors. It is obtained from a ratio of variances calculated for the two groups (F-test). The greater the ratio, the more different are the multivariate means. The equivalent of univariate "analysis of the variance" are Rao's R statistics for comparing several means (Tatsuoka, 19 71 ). The statistics tests the significance of a particular organization of a set into some groups. It works from a ratio of the variance between groups to the overall variance. The greater the ratio, the greater are the differences between the groups, the higher is the significance of the organization.
A-5. Comparison o f two or several matrices D The multiple-space equivalent of the univariant F-test of twc variances, and of Bartlett's test for several variances (Le Maitre, 1982 ) is the "covariance test". It is carried out by using the generalized (multivariate) variances (the determinants of matrices D) and the test is achieved with a Z2 (Dagn61ie, 1986 ).
A-6. The generalized distance or Mahalonobis" D e
When the variables are correlated, it is better to use the "generalized distance" instead of the Euclidean distance. A generalized distance corresponds to the ratio of the square of an Euclidean distance measured on uncorrelated transformed variables to their variances. Thus, these distances are dimensionless, weighted and corrected for the non-independence of the variables. In matrix algebra, the generalized distance between the objects i a n d j is given by: D2= [ 1/ ( p - 1 )] (xi--xj)TD
--I(xi--Xj)
(A-1)
where xi and xj are the vectors of p dimensions corresponding to objects i and j. Depending on the case, the nature of these objects are the samples, the means or the centroids (Dagn61ie, 1986). The homogeneity inside a group is estimated from the generalized distances of the samples to the centroid of its group. The greater the distances, the higher is the heterogeneity inside the group. A search and elimination of outliers should be made prior calculating the generalized distances D 2, since in principle they are objective measures between objects belonging to the same population, i.e. which verify the same dispersion matrix. Otherwise it could lead to an erroneous estimation of the dispersion matrix D and, correspondingly, of the calculated generalized distances as well.
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D. FONTIGNIE AND J-G. SCHILLING
Pacific near Easter Island. Nature (London), Phys. Sci., 240: 35-37. Hey, R.N. and Vogt, P.R., 1977. Spreading center jumps and sub-axial asthenosphere flow near the Galapagos hotspot. Tectonophysics, 37:41-52. Hey, R.N., Johnson, G.L. and Lowrie, A., 1977. Recent plate motions in the Galapagos area. Geol. Soc. Am. Bull., 88: 1385-1403. Hey, R.N., Naar, D.F., Kleinrock, M.C., Phipps Morgan, W.J., Morales, E. and Schilling, J.-G., 1985. Microplate tectonics along a superfast seafloor spreading system near Easter Island. Nature (London), 317: 320325. Kurz, M.D., Jenkins, W.J., Schilling, J-G. and Hart, S.R., 1981. Helium isotopic variations in the mantle beneath the North Atlantic Ocean. Earth Planet. Sci. Lett., 58: 1-14. Langmuir, C.H. and Bender, J.F., 1984. The geochemistry of oceanic basalts in the vicinity of transform faults: Observations and implications. Earth Planet. Sci. Lett., 69: 107-127. Le Maitre, R.W., 1982. Numerical Petrology: Statistical Interpretation of Geochemical Data. Elsevier, Amsterdam, 28 l pp. Lonsdale, P., 1983. Overlapping rift zones at the 5.5°S offset of the East Pacific Rise. J. Geophys. Res., 88: 9393-9406. Macdonald, K.C., Haymon, R.M., Miller, S.P., Sempere, J-C. and Fox, P.J., 1988. Deep-tow and Sea Beam studies of dueling propagating ridges on the East Pacific Rise near 20°40'S. J. Geophys. Res., 93: 28752898. Macdougall, J.D. and Lugmair, G.W., 1985. Extreme isotopic homogeneity among basalts from the southern East Pacific Rise: Mantle or mixing effect? Nature (London), 313:209-211. Macdougall, J.D. and Lugmair, G.W., 1986. Sr and Nd isotopes in basalts from the East Pacific Rise: Significance for mantle heterogeneity. Earth Planet. Sci. Lett., 77: 273-284. Macdougall, J.D. and Tanzer, M.O., 1984. Easter Island hotspot, II. Isotopic and chemical evidence of its influence on EPR basalts. Eos (Trans. Am. Geophys. Union), 65:1140 (abstract). Minster, J.G., Jordan, T.H., Molnar, P. and Haines, E., 1974. Numerical modeling of instantaneous plate tectonics: Geophys. J.R. Astron. Soc., 36: 541-576. Morgan, W.J., 1971. Convection plumes in the lower mantle. Nature (London), 230: 42-43. Morgan, W.J., 1978. Rodriguez, Darwin, Amsterdam ..... a second type of hotspot island. J. Geophys. Res., 83: 5355-5360. Naar, D.F. and Hey, R.N., 1986. Fast rift propagation along the East Pacific Rise near Easter Island. J. Geophys. Res., 91: 3325-3438.
S6Sr/S6Sr AND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES
Naar, D.F. and Hey, R.N., 1989. Recent Pacific-EasterNazca plate motions. In: Evolution of Mid-Oceanic Ridges, Symp. Vol., Am. Geophys. Union, Geophys. Monogr., 57: 9-30. Naar, D.F. and Hey, R.N., 1990. Tectonic Evolution of the Easter Microplate. J. Geophys. Res. (in press). Okal, E.A. and Cazenave, A., 1985. A model for the plate tectonic evolution of the east-central Pacific based on SEASAT investigations. Earth Planet. Sci. Lett., 72: 99116. Pilger, Jr., R.H. and Handschumacher, D.W., 1981. The fixed hotspot hypothesis and origin of the Easter-Sala y Gomez-Nazca trace. Geol. Soc. Am. Bull., 92: 437446. Poreda, R., Schilling, J-G. and Craig, H., 1986. Helium and hydrogen isotopes in ocean ridge basalts north and south of Iceland. Earth Planet. Sci. Lett., 78: 1-17. Rusby, R.H., 1988. Searle, R.C., Engeln, J., Hey, R.N., Naar, D.F. and Zukin, J., 1988. GLORIA and other surveys of the Easter and Juan Fernandez microplates. Eos (Trans. Am. Geophys. Union), 69: 1429 (abstract). Schilling, J.-G., 1975. Rare-earth variations across "normal segments" of the Reykjanes Ridge, 60-53°N, MAR, 29°S, and EPR, 2-19°S, and evidence on the composition of the underlying low velocity layer. J. Geophys. Res., 80 ( 11 ) 1459-1473. Schilling, J.-G., 1985. Upper mantle heterogeneities and dynamics. Nature (London), 314: 62-67. Schilling, J.-G., Anderson, R.N. and Vogt, P., 1976. Rare earth, Fe and Ti variations along the Galapagos Spreading Center and their relationship to the Galapagos mantle plume. Nature (London), 261:108-113. Schilling, J.-G., Sigurdsson, H., Davis, A.N. and Hey, R.N., 1985. Easter Microplate evolution. Nature (London), 317: 325-331. Schmitt, R.A., Smith, R.H. and Olehy, D.A., 1964. Rare-
241
earth, yttrium and scandium abundances in meteoritic and terrestrial matter, II. Geochim. Cosmochim. Acta, 28: 67-86. Schouten,, H., Klitgord, K.D. and Whitehead, J.A., 1985. Segmentation of mid-ocean ridges. Nature (London), 317: 225-229. Searle, R.C., Rusby, R.I., Engeln, J., Hey, R.N., Zukin, J., Hunter, P.M., LeBas, T.P., Hoffman, H.-J. and Livermore, R., 1989. Comprehensive sonar imaging of the Easter microplate. Nature (London), 341: 701-705. Sigurdsson, H., Schilling, J.-G. and Davis, A.N., 1985. Petrology of Easter Microplate basalts. Eos (Trans. Am. Geophys. Union), 66:405 (abstract). Sleep, N.H., 1984. Tapping of magmas from ubiquitous mantle heterogeneities, an alternative to mantle plumes. J. Geophys. Res., 89: 10,029-10,041. Tatsuoka, M.M., 1971. Multivariate analysis: techniques for educational and psychological research. Wiley, New York, N.Y., 310 pp. Vidal, P., Chauvel, C. and Brousse, R., 1984. Large mantle heterogeneity beneath French Polynesia. Nature (London), 307: 536-538. Vogt, P.R., 1976. Plumes, subaxial pipe flow and topography along the mid-oceanic ridge. Earth Planet. Sci. Lett., 29: 309-325. White, W.M., Hofmann, A.W. and Puchelt, H., 1987. Isotope geochemistry of Pacific mid-ocean ridge basalts. J. Geophys. Res., 92: 4881-4893. Zindler, A., Staudigel, H. and Batiza, R., 1984. Isotope and trace element geochemistry of young Pacific seamounts: implications for the scale of upper mantle heterogeneity. Earth Planet. Sci. Lett., 70:175-195. Zukin, J., Francheteau, J. and Armijo, R., 1988. Detailed studies of the Northern and Southern Rapanui (Easter) microplate boundaries. Eos (Trans. Am. Geophys. Union), 69:1423 (abstract).
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Elsevier Science Publishers B.V., Amsterdam
[21
875r/86Sr and REE variations along the Easter Microplate boundaries (south Pacific): Application of multivariate statistical analyses to ridge segmentation D. F o n t i g n i e a a n d J-G. Schilling b aUniversit~ de Gen~ve, D~partemen.t de Min&alogie, 13 rue des Maraichers, CH-1211 Gen~ve 4, Switzerland bGraduate School of Oceanography, University of Rhode Island, Kingston, RI 02881, U.S.A. (Received July 4, 1990; revised and accepted August 16, 1990 )
ABSTRACT Fontignie, D. and Schilling, J-G., 1991. 87Sr/S6Sr and REE variations along the Easter Microplate boundaries (south Pacific): Application of multivariate statistical analyses to ridge segmentation. Chem. Geol., 89:209-241. We report S7Sr/a6Sr, REE, Sc, V, Cr and Co analyses on 48 basaltic glasses dredged at 47 different localities along the spreading boundaries of the Easter Microplate (EMP). The latitudinal STSr/S6Sr variation along the East and West Rifts closely parallels that of the Pb isotope variation previously published and confirms the strong abnormality of the mantle underlying this part of the East Pacific Rise (EPR). The data also further support the binary mantle mixing model previously proposed. We evaluate the potential of multivariate statistical analyses in studying this and previously published geochemical data obtained on these very same 48 basaltic glasses. The data base includes major and trace elements ranging from compatible (e.g., Cr) to highly incompatible (e.g., La), and the Pb and Sr isotope ratios. Multivariate classification of these geochemical variables in Q-mode (sample space) allows to clearly distinguish major-element grouping from those of moderate to highly incompatible elements, and the isotope ratios reflecting mantle source heterogeneities present in the region. The power of this multivariate geochemical classification is best represented in two-dimensional space by combining principal components analysis (PCA) with cluster analysis (CA) illustrated in the form of a dendrogram. The method is further illustrated by classifying elements of the lanthanide series at different statistical level of affinities. Using the variance-covariance matrix and correlation matrix in R-mode, we further demonstrate a close relationship between segmentation revealed by the multiple variation of the four isotope ratios and the actual tectonic segmentation. Both discriminant analysis and PCA further indicate a close relationship between the geochemical anomaly located on the East Rift of the EMP and Sala y Gomez and Easter Island, to a lesser extent the Tuamotu Chain, whereas there is no close affinity between the EMP and the more distant Juan Fernandez, San Felix or Society Islands in the isotopic space considered. This provides further support that the geochemical anomaly located on the East Rift of the EMP may be related to the influence of a plume located either beneath the East Rift, or in the vicinity of Sala y Gomez, or Easter Island. In the last two models the plume would be laterally deflected at shallow depth towards the EPR-EMP spreading complex. An analysis of statistical generalized distances against geographical distances rules out that such influence is caused by radial dispersion of this plume in the upper mantle. The flow between the plume and the East Rift of the EMP must be more confined or channelled. The possibility that the plume would be located directly beneath the East Rift cannot be ruled out but appears less likely.
1. Introduction
The problem of the nature and scales of mantle heterogeneities to that of the tectonic and magmatic segmentation found along midocean ridges is long standing. Schilling ( 1975 ) 0009-2541/91/$03.50
first divided the mid-ocean ridge system into normal, plume-influenced and transitional ridge segments on the basis of long-wavelength rare-earth element (REE) and morphologic variation observed primarily in the North Atlantic. The enriched ridge centered plume-depleted asthenosphere binary mixing model was
© 1991 - - Elsevier Science Publishers B.V.
210 proposed to explain such segmentation. With increasing documentation of ridge segments influenced by progressively more distant hotspots, the model evolved to the migrating ridge - - hotspot source model (Morgan, 1978; Schilling, 1985) and the blob-cluster model (All~gre et al., 1984). The latter two models are not mutually exclusive and have much in common. Both include spreading rate as an influential factor but for different reasons. The former emphasizes the distance of the ridge to the hotspot (or time since it left the hotspot), whereas the latter considers spreading rate (or underlying mantle convection rate), as the dominant factor controlling the dispersion and dilution of plumes with the depleted asthenosphere. It has also been suggested that geochemical anomalies may coincide with fracture zones and the geochemical segmentation may be a reflection of the convective pattern in the underlying mantle (Langmuir and Bender, 1984 ). Others now contend that short-wavelength geochemical anomalies are a mere reflection of small-scale passive mantle heterogeneities ubiquitously present in the mantle (Sleep 1984; Zindler et al., 1984), and the morphotectonic ridge segmentation is primarily controlled by the wavelength of mantle or melt instabilities present directly beneath the ridge system (Schouten et al., 1985 ). Thus it has become increasingly more difficult to decide the cause (s) of the geochemical variability along ridges. A more powerful means for fingerprinting mantle source derivations has been to use several isotopes or trace-element ratios measured on the same samples. For example, 3He/4He variation with that of 87Sr/86Sr along the Mid-Atlantic Ridge (MAR) has helped distinguishing the influence of the Iceland plume from that of the Azores plume (Kurz et al., 1981; Poreda et al., 1986 ). Also, the influence of the South Atlantic-off-ridge plumes on the MAR has been pinpointed with the use of the covariation of the three Pb isotopes ratios in a single two-dimen-
D. FONTIGNIE AND J-G. SCHILLING
sional (2-D) Pb isotope space representation (Hanan et al., 1986 ). These approaches are all limited to 2 to 3 geochemical variables and 2-D representations. Despite its potential power, little use has been made so far of multivariate statistical analyses for fingerprinting the nature or cause of mantle heterogeneities simultaneously with a larger number of variables. Nor does its potential been exploited for classifying and delineating objectively possible ridge segmentation with petrological-geochemical data, with or without a priori evidence based on tectonic segmentation. Of course, the practical difficulty of gathering geochemical, petrological and isotopic data on the very same and fresh glass samples has been a limiting factor. In this paper we report 87Sr/86Sr, REE, Sc, V, Cr and Co data on the very same Easter Microplate (EMP) basaltic glasses we previously studied for major and Pb isotopes (Schilling et al., 1985; Hanan and Schilling, 1989 ). We then illustrate the potential of multivariate statistical analysis in handling and interpreting this entire data set in terms of mantle source heterogeneities and their relation to morphotectonic ridge segmentation in the region. For comparison we also include new data on a few basalts from Easter and Sala y Gomez Islands. Multivariate statistical methods provide a means to consider simultaneously a large number of variables from a given data set. They are essentially a generalization of uni- or bivariate statistical analyses. These methods provide also ways of reducing the number of variables by linearly combining them and optimising their 2-D presentations without significant loss of information. Depending on the way the data are investigated, relationships between the variables or between the samples can be drawn. The multivariate statistical techniques used in this study include principal components (PCA), discriminant (DA) and cluster (CA) analyses (Tatsuoka, 1971; Green, 1976; Le Maitre, 1982; Dagn61ie, 1986). A brief description of these methods is included as an
86Sr/a6Sr A N D R E E V A R I A T I O N S A L O N G T H E E A S T E R M I C R O P L A T E
common at a smaller scale along the EPR (Lonsdale, 1983; MacDonald et al., 1988), or is it the result of the influence of a plume in the region, or both? (3) If the plume model first revealed by the topographic character of the region (Anderson et al., 1974; Vogt, 1976) is considered, can the nature and location of the plume be further defined? For example, is the plume located beneath the East Rift as inferred first by Morgan ( 1971 ) and Handschumacher et al. ( 1981 ), or
Appendix. We will show that the EMP provides a good opportunity to reveal the potential power of multivariate statistical analyses in objectively tackling existing problems, such as: (1) Delineating underlying mantle heterogeneities present in relation to that of the morphotectonic tectonic segmentation of the East Pacific Rise (EPR) in the region. (2) Does the microplate represent only a mega-case of ridge overlap, a feature quite I
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211
BOUNDARIES
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Fig. 1. Plate boundary configuration of the Easter Microplate modified from Naar and Hey ( 1989, 1990) and Searle et al. (1989). Spreading directions and rates (double arrows) and absolute plate motion of the Nazca Plate near Easter Island (single arrow) are taken from Naar and Hey ( 1989 ). Also shown are the location and denomination of the dredge hauls and ridge segments used in this study. West Rift: capital letters; East Rift: small letters and numbers. See Table I for corresponding station numbers; Ridge segment numbers considered in the text are circled. Right insert: Location map of the Easter Microplate in the south Pacific.
212
off-ridge as suggested by Schilling et al. ( 1985 ) and Hanan and Schilling ( 1989 )? (4) If the EMP anomaly is influenced by an off-ridge hotspot, is it located west (e.g., Tuamotu or Society hotspot ) - - or east of the ridge (e.g., Easter, Sala y Gomez), or somewhere else?
2. Tectonic setting The existence of the EMP located between the Pacific and Nazca plates (Fig. 1 ) was first reported by Forsyth (1972) and Herron (1972). Its exact tectonic configuration and origin remains uncertain and keeps evolving as new data accumulates (Anderson et al., 1974; Hey and Vogt, 1977; Handschumacher et al., 1981; Engeln and Stein, 1984). A seabeam/ magnetic survey by Hey et al. (1985), combined with evidence from dredged rocks by Schilling et al. (1985), led to the conclusions that the eastern and western boundaries are actively spreading and propagating, northward along the Eastern Rift, and southeastward along the Western Rift. Both the northern and southern boundaries of the EMP are probably broad transform zones or pseudo-faults. Both remain to be better defined. The EMP boundary configuration shown in Fig. 1 takes into account the recent GLORIA and SeaMARC sonar survey (Searle et al., 1989 ) and the study of Naar and Hey ( 1989, 1990). Because of dual spreading and rift propagation the spreading rate vary widely in the region ( ~ 0 - 1 8 5 km M a - 1_ see Fig. 1 and Naar and Hey, 1989 ).
3. Sampling During the 1984 dredging cruise with R / V "Endeavor" (EN-113), 48 stations at ~ 25-km intervals were collected along what were thought at the time to be the spreading boundaries of the EMP and adjacent EPR, between 22 ° and 29°S (Fig. 1; Schilling et al., 1985). Two samples collected during the cruise Pascua 04 are also included (Craig et al., 1984;
D. FONTIGNIE AND J-G. SCHILLING
Macdougall and Tanzer, 1984). It is evident from Fig. 1 that not all the samples may be located exactly on the present ridge axis. This is particularly the case south of the EMP (27 °S ) where the sampling is ~ 20-35 km further east, and in the NW and NE corners of the EMP which is tectonically complex and the boundaries are still ill defined. Using current spreading rates and visual inspection, we estimate that none of the basalts from this collection are likely to be older than 0.2-0.3 Ma. The locality and sample descriptions of the Easter and Sala y Gomez Islands and dredged glasses from its flank are given in Hanan and Schilling ( 1989 ). For convenience, in our geochemical scrutiny the spreading boundaries are first subdivided into two branches, the East and the West, and subsequently into eight segments as shown in Fig. 1. The basalt glasses studied correspond to three petrological types (Schilling et al., 1985; Sigurdsson et al., 1985 ): ( 1 ) The most abundant are tholeiitic basalts ranging from quartz to olivine normative. (2) A few basalts are nepheline normative (stations L, I, m and 8). All of these are light REE (LREE) depleted, lower in SiO2, higher in A1203 and Na20 than the tholeiites, and have been the least affected by low-pressure fractional crystallization. (3) Among the nepheline-normative basalts, two are primitive picritic basalts which may have equilibrated at pressures of > 20 kbar (stations G and d; Sigurdsson et al., 1985 ). The major-element analyses and (La/Sm)n ratios have been reported by Schilling et al. (1985) and Pb isotope ratios by Hanan and Schilling ( 1989 ).
4. Analytical results Except for four samples, the REE, Sc, V, Cr, Co, major elements and the isotopic analyses were all performed on carefully selected glass chips from the same pillow or sheet flow. Fur-
S6Sr/S6SrAND REE VARIATIONSALONG THE EASTER MICROPLATE BOUNDARIES
213
TABLE I
875r/S6Sr ratios in basalt glasses from the Easter Microplate and basalts from Easter and Sala y Gomez Islands Sample *~
Segment
Code
Location lat.
long.
22.53 22.68 22.90 23.00 23.08 23.25 23.48 23.77 24.11 24.31 24.64 24.64 24.99 24.99 24.99 25.28 25.66 25.90 26.13 26.35 26.52 26.70 23.86 24.20 24.36 24.53 24.61 24.78 24.86 24.86 24.98 25.03 25.24 25.24 25.47 25.66 25.98 26.27 26.27 26.46 26.58 26.81 26.81 26.92 27.21 27.21 27.30 27.53 27.53
114.47 114.51 114.51 114.53 114.54 115.43 115.38 115.47 115.41 115.47 116.42 116.42 116.36 116.36 116.36 116.27 116.13 115.86 115.64 115.32 115.09 114.92 111.82 111.93 111.98 111.79 111.95 111.97 112.45 112.45 112.42 112.41 112.38 112.38 112.39 112.38 112.55 112.62 112.62 112.57 112.65 112.64 112.64 112.70 112.77 112.77 112.81 112.76 112.76
(os)
EN113 35D-1g ENI13 36D-1g ENI13 34D-Ig E N l l 3 37D-Ig E N l l 3 38D-llg ENI13 33D-1 E N l l 3 32D-lg ENI13 31D-1 EN 113 30D- lg EN113 29D-Ig EN113 28D-1Bg E N l 1 3 28D-lAg E N l l 3 27D-IAg E N l l 3 27D-1Bg E N l l 3 2719-1 ENII3 26D-lg EN 113 25D-1g EN 113 24D-lg EN 113 23D-1g ENI13 22D-1g ENII3 21D-lg ENII3 20D-lg EN113 17D-lg ENI13 16D-lg EN I I 3 39D-2g ENII3 15D-lg EN I13 40D-lg E N l l 3 14D-lg EN 113 13D-lg EN 113 13D-4 PAO4-12-A.4 ENII3 12D-1 ENII3 IlD-1A ENII3 llD-1B EN113 lOD-lg EN113 9D-lg EN113 8D-lg PA04-11-CA .4 PAO4-11-CB EN113 7D-lg EN113 41D-lg E N l l 3 6D-1Bg EN 113 6D-lAg EN l l 3 4 2D- Ig E N l l 3 5D-IAg E N l l 3 5D-ICg EN I 13 43D-2g ENI13 4D-lAg ENII3 4D-lg
1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 7 7
W X V Y Z N M L K J I I H H H G F E D C B A q p 1 o 2 n m m * 1 k k j i h s s g 3 f f 4 e e 5 d d
Depth (m)
878r/86Sr(*2 )
20* 3
2,912 2,975 2,975 3,032 3,125 2,815 3,270 2,660 2,800 2,692 2,740 2,740 2,060 2,060 2,060 2,052 2,240 2,212 2,608 2,788 2,705 2,918 3,905 2,950 2,898 2,975 2,825 2,630 2,948 2,948 3,264 3,255 3,158 3,158 2,970 2,865 2,668 2,425 2,425 2,272 2,282 2,362 2,362 2,590 2,632 2,632 2,438 2,520 2,520
0.702427 0.702470 0.702391 0.702397 0.702398 0.702573 0.702443 0.702409 0.702285 0.702425 0.702499 0.702516 0.702928 0.702866 0.702859 0.702289 0.702487 0.702595 0.702599 0.702598 0.702584 0.702723 0.702392 0.702513 0.702538 0.702619 0.702798 0.702656 0.702490 0.702709 0.702643 0.702612 0.702781 0.702780 0.702696 0.702710 0.702683 0.702859 0.702846 0.702854 0.702850 0.702989 0.702981 0.702807 0.702608 0.702585 0.702686 0.703218 0.703204
0.000022 0.000016 0.000020 0.000016 0.000016 0.000018 0.000020 0.000018 0.000016 0.000016 0.000020 0.O00018 0.000022 0.000018 0.000020 0.000018 0.000018 0.000020 0.000022 0.000014 0.000022 0.000020 0.000020 O.000018 0.000018 0.000020 0.000022 0.000016 0.000024 0.000018 0.000022 0.000018 0.000024 0.000014 0.000020 0.000020 0.000020 0.000012 0.000030 0.000018 0.000024 0.000020 0.000022 0.000018 0.000016 O.000018 0.000020 0.000024 0.000016
(ow)
214
D. FONTIGNIE AND J-G. SCHILLING
TABLE I (continued) Sample*'
Segment
Code
Location
Depth
S7Sr/S6Srt*2)
20 *3
0.702685 0.702775 0.702547 0.702632 0.702696 0.702663 0.702494 0.702450 0.702421
0.000016 0.000014 0.000018 0.000018 0.000018 0.000014 0.000016 0.000014 0.000026
0.702930 0.703015 0.702962
0.000018 0.000018 0.000018
0.703116 0.703195 0.703025
0.000018 0.000020 0.000020
(m)
EN 113 44D-5g ENI13 3D-lg ENl13 2D-2g EN 113 45D-lAg EN113 45D-1Bg ENl13 1D-Ig E N l l 3 46D-2 EN113 47D-2g EN 113 48D- lg Easter Island
7 7 8 8 8 8 8 8 8
6 c b 7 7 a 8 9 +
lat.
long.
(os)
(ow)
27.64 27.88 28.08 28.29 28.29 28.48 28.72 29.01 29.02
112.84 112.81 112.66 112.66 112.66 112.65 112.73 112.79 112.70
26.92
109.35
P3B P4 P7 Sala y Gomez
26.58
Y 73-4-30-4 Y 73-4-30-20 Y 73-4-30-5
2,522 2,300 2,784 2,758 2,758 2,950 2,750 2,488 2,448
105.38
*~The g in the sample identification stands for glass, otherwise pillow interiors were used. *2The 87Sr/86Sr ratios are normalized to Srsr/SaSr= 0.1194 and adjusted to Eimer & Amend* SrCO3 standard S7Sr/a6Srvalue of 0.70800. The Eimer & A m e n d * standard was 0.708039_+ 0.000008 ( 2 a from the mean, 31 replicates analyses) during the period of measurements of ~ 1 yr. *3Errors are the estimated in-run 2 standard deviations. *4These two samples have also been analyzed by Macdougall and Lugmair ( 1986 ). The results between the two laboratories are identical within the errors quoted.
thermore, the Pb and Sr isotopic data were obtained from the very same dissolution of such glass fragments, hand-picked under the binocular microscope after ultrasonic cleaning in distilled water. The 87Sr/86Sr data reported in this study are listed in Table I. The REE and Sc, V, Cr and Co data, obtained by instrumental neutron activation analysis (INAA), are listed in Table II and Table III, respectively. The Sr isotopic analyses were carded out on a VG Micromass ® 30B single-collector, double-focusing, thermal ionization mass spectrometer at University of Rhode Island (URI), Measured blanks for the procedure are negligible, giving uncertainties significantly lower than the in-run errors.
The Sr was isolated using essentially the method of Hart and Brooks (1974), after dissolving ~ 0.2-0.4 g of carefully cleaned and hand-picked basaltic glass fragments. Approximately 50/lg Sr were loaded in phosphoric acid form on rhenium single filament using tantalum oxide as an activator. The normalization procedure used and associated statistics is given at the bottom of Table I. The REE pattern for the East Rift and EPR southern extension shows a much wider range of LREE enrichment and fractionation than the West Rift and EPR just north of the microplate (Fig. 2 ). The Sr isotopic ratios along the EMP bracket the entire EPR and range in values from 0.7023
86Sr/86SrAND REE VARIATIONSALONGTHE EASTERMICROPLATEBOUNDARIES
215
TABLEII
REE concentrations (ppm) and chondrite-normalized (La/Sm)n ratio in glassy basalts from the boundaries of the Easter Microplate and the East Pacific Rise ID *l
EN11335D-Ig EN113 35D-2g E N l l 3 36D-lg ENI1336D-2 ENI13 34D-lg EN113 34D-2 EN113 37D-lAg EN11327D-2 EN113 38D-I EN113 38D-llg E N l l 3 33D-1 EN113 33D-2 EN113 32D-lAg E N l l 3 32D-2 EN1331D-I ENl1331D-2g ENl1330D-1g ENl1330D-2g ENl1329D-1g E N l l 3 29D-2 E N l l 3 28D-lAg E N l l 3 28D-2 ENl1327D-1 ENI1327D-2 ENl1326D-1g EN113 26D-2 E N l l 3 25D-1g ENI13 25D-2g EN11324D-1g ENII3 24D-2 ENI13 23D-lg ENII3 23D-2 EN11322D-1 ENII3 22D-2 EN113 21D-1 ENI1321D-2 ENl13 20D-1 EN113 20D-2 ENl13 18D-1 ENl13 17D-1 ENl13 17D-2g E N l l 3 16D-lg E N l l 3 16D-2 E N l l 3 39D-1 E N l l 3 39D-2g E N l l 3 15D-I E N l l 3 15D-2 ENl13 40D-lg EN11340D-2 ENI13 14D-lg
La 2.39 2.33 2.85 2.83 1.56 1.32 3.67 3.30 1.52 1.54 2.35 2.65 4.10 2.99 2.49 2.64 1.16 2.31 4.03 5.08 1.52 1.47 4.29 4.98 0.99 1.14 4.54 3.96 5.13 4.88 4.64 5.95 5.17 6.04 4.06 4.61 4.51 5.25 4.79 3.26 2.97 5.02 5.03 4.17 3.56 4.99 5.12 1.52 2.62 2.83
Ce
Nd
Sm
Eu
Tb
8.41 7.91 10.38 9.37 6.73 6.33 14.32 11.95 6.80 6.68 6.74 9.98 12.26 9.51 8.22 8.20 4.99 9.12 13.01 15.28 5.72 6.77 11.63 14.99 3.74 4.00 13.17 11.48 14.82 13.89 13.40 16.55 14.01 17.00 11.17 13.46 12.68 14.96 15.86 11.22 10.67 13.13 13.69 14.44 13.37 17.46 18.12 5.97 9.11 9.87
8.98 8.54 9.64 6.97 6.33 13.68 10.92 6.78 7.52 5.98 9.49 11.68 7.90 7.39 9.27 11.16 6.49 7.35 8.04 9.88 4.19 3.89 10.86 11.73 10.36 10.96 12.50 10.57 13.50 10.97 8.76 11.64 13.80 10.40 8.78 10.62 9.69 13.91 12.59 15.59 15.58 7.27 7.17 -
3.27 3.34 3.47 3.63 2.49 2.13 5.04 4.61 3.11 3.05 2.67 3.45 4.17 3.00 2.67 3.10 2.33 3.30 3.99 4.86 2.64 2.82 2.72 2.97 1.63 1.65 3.82 3.59 3.73 3.83 3.68 4.20 3.81 4.79 3.29 3.99 2.90 4.06 5.60 3.68 3.77 3.43 3.52 5.00 4.64 5.50 5.77 2.41 3.27 3.34
1.17 1.21 1.37 1.23 0.96 0.98 1.83 1.49 1.07 1.17 0.97 1.34 1.44 1.08 1.01 1.08 0.90 1.26 1.43 1.63 1.08 1.04 0.97 1.35 0.79 0.74 1.39 1.14 1.41 1.34 1.32 1.47 1.28 1.59 1.11 1.30 1.12 1.37 1.76 1.34 1.30 1.24 1.26 1.58 1.66 1.79 1.99 0.94 1.26 1.20
0.86 0.90 0.91 0.89 0.70 0.66 1.41 1.11 0.84 0.91 0.65 0.86 1.07 0.80 0.73 0.90 0.68 0.99 1.01 1.18 0.66 0.75 0.59 0.79 0.50 0.48 0.94 0.83 0.94 0.94 0.91 1.00 0.93 1.15 0.84 0.98 0.68 0.98 1.37 0.93 0.88 0.77 0.79 1.27 1.20 1.60 1.41 0.66 0.86 0.84
Dy 5.16 5.52 6.41 6.14 5.02 4.76 7.16 5.38 5.78 4.73 6.66 5.36 4.70 5.57 4.17 6.65 7.45 4.21 3.90 4.65 2.93 6.39 5.80 5.90 5.32 6.25 6.08 6.59 5.16 6.38 4.15 6.54 8.81 5.77 6.02 4.47 5.25 8.55 8.36 8.76 5.13 5.53
Tm
Yb
Lu
( L a / S m ) n .2
0.65 0.72 0.74 0.70 0.57 0.46 1.02 0.83 0.64 0.66 0.50 0.77 0.52 0.66 0.51 0.66 0.68 0.75 0.44 0.41 0.41 0.68 0.53 0.63 0.68 0.79 0.61 0.68 0.46 0.68 0.61 0.59 0.53 0.55 0.82 0.86 0.93 -
3.77 3.90 3.78 3.69 2.98 2.85 5.40 4.74 3.55 3.77 2.57 3.83 4.23 3.05 3.19 3.69 2.77 3.90 3.68 4.46 2.56 2.65 2.17 2.71 2.29 2.25 3.46 3.10 3.35 3.59 3.50 3.71 3.67 4.36 3.57 3.79 2.53 3.79 5.66 3.53 3.55 2.89 2.98 4.71 4.40 5.37 5.85 2.76 3.39 3.26
0.52 0.55 0.54 0.52 0.40 0.41 0.74 0.64 0.53 0.52 0.41 0.57 0.56 0.41 0.44 0.52 0.37 0.54 0.51 0.61 0.36 0.37 0.30 0.40 0.33 0.34 0.48 0.45 0.46 0.47 0.48 0.56 0.50 0.62 0.48 0.57 0.35 0.52 0.79 0.49 0.51 0.38 0.41 0.65 0.60 0.77 0.87 0.36 0.49 0.45
0.51 0.49 0.57 0.55 0.44 0.43 0.51 0.50 0.34 0.35 0.62 0.54 0.69 0.70 0.65 0.60 0.35 0.49 0.71 0.73 0.40 0.36 1.10 1.17 0.43 0.48 0.83 0.77 0.96 0.89 0.88 0.99 0.95 0.88 0.86 0.81 1.09 0.91 0.60 0.62 0.55 1.02 1.00 0.58 0.54 0.64 0.62 0.44 0.56 0.59
216
D. FONTIGNIE AND J-G. SCHILLING
T A B L E II (continued) ID *~
La
Ce
Nd
Sm
Eu
Tb
E N l l 3 14D-2g ENl13 13D-lg ENl13 13D-2 EN113 13D-4 PAO4-12-A E N l l 3 12D-1 E N l l 3 12D-2 ENl13 llD-1 EN113 llD-2 ENI13 lOD-lg E N l l 3 lOD-2 ENII3 9 D - l A g E N l l 3 9D-2g EN113 8D-lg EN1138D-2 ENl138D-4g PAO4-11-A PAO4-11-B PA04-11-C E N l l 3 7D-lg E N l l 3 7D-2g ENl1341D-Ig ENl1341D-2 EN1136D-1Ag EN1136D-2 ENII3 42D-lg ENI1342D-2 EN1135D-1Ag ENI13 5D-2 ENI13 43D-1 ENI1343D-2g ENI134D-1 ENI13 4 D - l A g E N l l 3 4D-2 E N l l 3 44Dol EN11344D-5 ENI133D-Ig ENI13 3D-2 ENI13 2D-1 ENl132D-2 E N l l 3 45D-lAg ENI13 45D-2 EN113 1D-I ENI13 1D-2 EN11346D-I EN11346D-2 EN11347D-1A ENII3 47D-2 ENII3 48D-lg E N l l 3 48D-2
3.15 1.78 1.72 4.37 6.70 7.00 9.26 7.42 9.58 6.39 6.94 7.62 7.27 6.89 6.94 6.18 6.80 6.47 7.08 12.25 14.05 9.90 8.44 15.41 16.89 8.10 9.48 1.70 1.80 5.53 5.38 2.18 2.24 2.58 3.90 2.21 8.17 7.97 7.75 5.20 9.76 4.59 3.26 7.38 2.72 2.78 3.92 3.98 4.85 4.61 0.3
10.32 7.84 7.14 15.39 20.38 20.07 25.97 19.65 27.72 19.27 20.30 21.91 21.86 19.74 20.24 17.41 20.54 18.05 20.97 31.44 34.05 26.13 23.32 37.16 41.42 22.24 25.76 5.89 5.95 15.42 16.00 8.06 7.90 8.94 10.00 6.25 21.13 20.94 20.56 15.19 31.80 14.74 9.91 23.36 8.67 8.87 14.20 14.06 16.92 16.77 0.84
9.64 7.59 14.44 14.04 18.93 14.27 18.40 17.60 15.69 18.80 18.76 16.78 15.13 21.23 20.05 14.26 6.10 4.96 11.50 11.83 6.43 6.04 14.37 12.50 13.49 11.54 8.72 17.96 7.71 12.31 13.99 14.80 14.44 0.58
3.34 3.15 3.08 4.32 5.59 5.23 6.39 4.53 6.70 5.04 5.22 5.72 5.35 5.00 4.70 4.07 4.33 4.24 3.99 5.00 5.56 4.98 4.78 5.57 5.52 4.49 5.30 2.20 2.01 3.77 3.93 2.56 2.69 2.76 2.64 2.13 3.97 3.71 4.02 4.30 7.84 5.14 3.22 6.18 2.78 3.17 4.30 4.58 5.47 4.94 0.21
1.33 1.27 1.15 1.85 2.08 1.70 2.19 1.55 2.28 1.86 1.84 1.99 1.88 1.59 1.71 1.48 1.73 1.62 1.51 1.69 1.94 1.71 1.67 1.89 1.93 1.60 1.81 0.88 0.86 1.27 1.37 1.01 1.07 1.10 0.95 0.84 1.41 1.42 1.45 1.61 2.56 1.70 1.15 2.13 1.13 1.19 1.64 1.58 1.86 1.96 0.074
0.91 0.71 0.73 1.13 1.30 1.19 1.62 0.96 1.56 1.30 1.20 1.35 1.28 1.19 1.12 0.95 1.14 1.15 0.87 1.04 1.12 1.02 1.02 1.02 1.01 0.94 1.16 0.58 0.58 0.83 0.90 0.65 0.67 0.70 0.56 0.54 0.85 0.75 0.86 1.10 1.91 1.21 0.81 1.57 0.69 0.67 1.02 1.13 1.29 1.29 0.049
C h o n d r i t e s .2
Dy 6.16 4.76 4.51 8.20 7.21 9.41 5.76 9.88 7.57 7.45 7.46 7.99 6.88 7.04 6.79 5.67 5.89 5.38 7.11 4.16 3.62 5.26 5.15 4.50 4.55 3.74 3.69 4.76 5.18 6.70 11.53 6.79 4.86 10.10 4.10 4.50 6.69 6.99 8.06 0.31
Tm
Yb
Lu
( L a / S m ) n .2
0.49 0.48 0.74 0.83 0.79 0.98 0.97 0.85 0.89 0.76 0.77 0.84 0.72 0.57 0.57
3.50 2.72 2.60 4.59 5.24 4.54 5.61 3.46 5.53 4.55 4.60 4.73 4.43 4.13 4.19 3.25 3.63 3.51 2.86 3.08 3.63 3.29 3.19 3.10 2.97 3.23 3.68 2.41 2.35 2.86 2.96 2.50 2.72 2.88 2.09 2.23 2.57 2.51 2.94 4.27 7.39 4.81 3.19 6.06 2.46 2.63 4.23 4.32 4.98 4.80 0.18
0.49 0.38 0.37 0.66 0.68 0.67 0.74 0.49 0.82 0.61 0.63 0.64 0.58 0.60 0.59 0.44 0.51 0.47 0.39 0.41 0.50 0.48 0,41 0,41 0.40 0.47 0.52 0.34 0.32 0.39 0.41 0.35 0.39 0.40 0.27 0.32 0.32 0.32 0.42 0.60 1.06 0.68 0.47 0.83 0.33 0.37 0.62 0.64 0.74 0.68 0.025
0.66 0.40 0.39 0.71 0.84 0.94 1.01 1.15 1.00 0.89 0.93 0.93 0.95 0.96 1.03 1.06 1.10 1.07 1.24 1.72 1.77 1.39 1.24 1.94 2.14 1.26 1.25 0.54 0.63 1.03 0.96 0.60 0.58 0.65 1.03 1.73 1.44 1.50 1.35 0.85 0.87 0.63 0.71 0.84 0.68 0.61 0.64 0.62 0.62 0.65
0.46 0.42 0.45 0.55 0.44 0.75 1.21 0.79 0.56 1.01 0.43 0.47 0.82 0.93 0.77 0.0315
- - = n o t detected; I N A A analyst: B. McCully, U R I . *Jg s t a n d s for glass, otherwise pillow interior. *2Average o f 20 c h o n d r i t e s f r o m S c h m i t t et al. ( 1 9 6 4 ) except for Tin, Yb a n d Lu which were a d j u s t e d for systematic analytical biases between laboratories.
86Sr/86Sr AND REE VARIATIONSALONGTHE EASTERMICROPLATEBOUNDARIES
217
TABLE III
TABLE III (continued)
Trace-element concentration ( p p m ) by INAA in basalt glasses from the boundaries of the Easter Microplate and the East Pacific Rise
ID *l
Sc V
Cr
Co Mg( L a / S m ) . .3 number.2
ENII313D-lg ENII313D2 EN11313D-4 PAO4-12-A ENII312D-1 ENII312D-2 ENI1311D-1 ENl1311D-2 ENl1310D-lg ENl13 IOD-2 ENl139D-1Ag ENl139D-2g EN1138D-1g EN1138D-2 ENI138D-4g PAO4-11-A PAO4-11-B PA04-11-C ENl13 7D-lg EN1137D-2g EN11341D-lg
32 33 44 44 42 41 40 40 41 42 40 41 39 39 40 42 40 33 33 39 37 38 31 30 37 41 38 40 43 41 34 34 36 36 41 30 32 38 43 38 43 41 43 31 31 42 41 41 39
450 548 130 80 117 124 187 9 44 47 84 87 221 227 279 205 198 242 201 188 229 232 234 327 140 126 344 358 270 251 369 376 347 338 396 241 263 167 89 118 130 179 84 383 373 247 233 287 263
44 52 50 44 42 41 39 45 42 43 40 41 40 40 39 40 39 36 37 36 39 39 39 42 45 40 43 44 41 39 57 58 58 41 45 37 39 38 44 38 44 39 46 42 43 40 38 42 40
1D*l
Sc V
Cr
Co Mg( L a / S m ) . .3 number.2
EN11335D-lg ENII335D-2g ENl1336D-1g ENl1336D-2 EN11334D-Ig ENI1334D-2 ENl1337D-1Ag ENl1337D-2 ENlI338D-I ENII338D-11g ENI1333D-1 ENII333D-2 EN11332D-1Ag ENl13 32D-2 ENl13 31 D-1 EN113 31D-2g ENll3 30D-lg EN 113 30D-2g ENll3 29D-1g ENll3 29D-2 EN11328D-1Ag EN 113 28D-2 ENl13 27D-1 ENl l 3 27D-2 ENl13 26D-1g EN113 26D-2 EN113 25D-lg EN 113 25D-2g ENl13 24D-Ig EN 113 24D-2 EN113 23D-lg EN 113 23D-2 ENl13 22D-1 ENl13 22D-2 ENl l 3 21D-1 ENl l 3 21D-2 ENl l 3 20D-1 ENll3 20D-2 EN113 18D-I EN113 17D-I ENl l 3 17D-2g ENl l 3 16D-lg ENII3 16D-2 ENII3 39D-1 ENl13 39D-2g ENl13 15D-1 ENI13 15D-2 ENl13 40D- lg EN113 40D-2 ENII3 14D-lg ENl l 3 14D-2g
43 43 42 41 39 38 50 43 42 42 42 38 40 37 45 43 40 42 42 45 37 38 40 42 35 34 42 40 42 43 42 42 40 41 41 42 42 40 43 37 39 35 37 41 42 39 42 44 43 40 42
310 305 267 265 335 353 194 167 190 191 194 102 261 314 255 244 393 96 192 156 314 319 358 368 314 389 187 275 136 148 223 127 117 116 199 190 315 175 64 239 275 280 279 170 224 169 218 403 206 209 226
42 42 40 39 41 37 47 41 44 45 41 38 41 39 43 43 43 44 43 62 43 46 39 47 52 55 41 43 42 42 42 43 41 44 39 39 45 41 32 40 42 38 40 39 44 43 41 43 42 39 41
299 322 341 342 291 275 390 387 341 339 340 324 357 297 337 332 288 394 350 369 245 240 267 250 181 182 329 288 331 333 322 361 375 396 424 337 313 349 539 329 311 276 276 353 344 487 438 257 330 320 318
61.7 62.3 60.0 65.4 54.4 60.3 57.6 16.2 60.0 68.8 59.2 56.6 60.5 66.3 62.0 68.4 59.0 58.1 58.0 58.0 53.2 52.1 51.5 55.3 59.0 57.3 61.5 66.6 63.3 54.1 58.6 46.9 52.6 65.2 61.7 62.6 61.9
0.51 0.49 0.57 0.55 0.44 0.43 0.51 0.50 0.34 0.35 0.62 0.54 0.69 0.70 0.65 0.60 0.35 0.49 0.71 0.73 0.40 0.36 1.10 1.17 0.43 0.48 0.83 0.77 0.96 0.89 0.88 0.99 0.95 0.88 0.86 0.81 1.09 0.91 0.60 0.62 0.55 1.02 1.00 0.58 0.54 0.64 0.62 0.44 0.56 0.59 0.66
ENl1341D-2
EN1136D-1Ag EN1136D-2 EN11342D-lg ENl1342D-2 ENII35D-IAg EN1135D-2 EN11343D-1 ENl1343D-2g ENl134D-1 EN1134D-1Ag EN1134D-2 EN11344D-I EN11344D-5 EN1133D-Ig ENI133D-2 ENl132D-I ENI132D-2 EN11345D-1Ag EN11345D-2 EN1131D-1 EN113 1D-2 ENlI346D-1 EN11346D-2 EN11347D-1A ENI1347D-2 ENI1348D-Ig EN11348D-2
235 212 405 446 407 408 350 468 417 408 429 411 355 347 332 335 352 283 323 304 329 266 244 366 268 259 353 337 187 182 189 245 260 261 232 350 382 299 402 383 460 214 214 335 360 404 362
66.0 66.8 52.3 47.9 47.0 44.6 55.0 42.0 60.2 45.7 49.8 50.5 55.7 55.3 59.6 56.6 58.2 51.4 59.0 59.5 60.8 61.7 67.5 68.6 60.8 66.2 66.2 63.5 66.1 64.4 54.5 52.5 47.6 55.4 46.0 69.5 65.2 59.5 58.2 -
0.40 0.39 0.71 0.84 0.94 1.01 1.15 1.00 0.89 0.93 0.93 0.95 0.96 1.03 1.06 1.10 1.07 1.24 1.72 1.77 1.39 1.24 1.94 2.14 1.26 1.25 0.54 0.63 1.03 0.96 0.60 0.58 0.65 1.03 0.73 1.44 1.50 1.35 0.85 0.87 0.63 0.71 0.84 0.68 0.61 0.64 0.61 0.62 0.65
- - = not detected; INAA analyst: B. McCully, URI. , l g stands for glass, otherwise pillow interior. *2Mg-number=Mg2+/(Mg2+ + F e 2+ ) atomic ratio assuming an atomic ratio of Fe3+ / (Fe 2+ + F e 3+ ) =0.14. *3La/Sm ratio normalized relative to chondrites.
218
D. FONTIGNIE
10 z
AND J-G. SCHILLING
(La/Sm)n (a)
West Branch (a)
~ /i
fi i
,
1.o 101-
I 24
o.o La
102-
Ce
Nd
Sm
b
Eu
Dy
Tm
b
I 26
i 28
Lu
2°6pb / 2°4pb (b)
East Branch
,
(b)
,~
.r, i:
/'4
•,"
~,
[it
19.0
101 18.0
; 24
17.5 ,
i
La
Ce
,
,
i
~
Nd
Sm
Eu
~
i
,
Tb
Dy
i
i
i
Tm
/
Yb
I 28
I 28
A
Lu
87Sr / 86Sr
Fig. 2. REE patterns for the West Rift (a) and East Rift (b) of the EMP.
to 0.7032. Strangely enough, the lower and upper isotopic bounds are represented by the two picritic basalt glasses (G and d ). The 875r/86Sr latitudinal profiles along the East and West Rifts of the EMP mimic that of ( L a / S m ) , and Pb isotope ratios (Fig. 3 ). Consequently, there are rather good positive linear correlations between these variables (Table IV). The East Branch is more radiogenic than the West Branch and the data scatter about a general dome-like trend which culminates at around 26 ° S. Superimposed over this general trend are small 87Sr/a6Sr spike-like peaks which are poorly understood. The southern spike occurs at station d, though this basalt is a LREE-depleted picritic basalt glass. The real maximum is apparent at the station fwhich is much more conformable in terms of Sr and Pb isotopes,
(c) !
,
0.7030
/i
0.7025
Latltude°S
0.7022
214
I 26
I 28
Fig. 3. Latitudinal profiles between 22 ° and 30°S for: (a) (La/Sm).; (b) 2°6Pb/2°4Pb; and (c) 87Sr/86Sr.
(La/Sm) n and ridge elevation as well. Two samples were analyzed at station m (located in segment 5), just north of the proposed 25°S propagating rift tip. One sample is a young basaltic glass collected on the top of a recently active seamount. The other is an older
NazO TiOz (La/Sm), zo6pb/2O4pb 2OTpb/zO4pb 2OSpb/2O4pb STSr/a6Sr La Ce Nd Sm Eu Tb Dy Tm Yb Lu Sc V Cr Co Mg
MgO CaO
SiOz A1203 FeO*
CaO Na20 TiO2 (La/Sm), 2o~pb/ZO4pb 2O~pb/2O4pb 2Oapb/2O4pb 87Sr/n6Sr La Ce
MsO
SiO2 A1203 FeO*
Sm
0.3365 0.4949 -0.3221 -0.4925 0.3251 0.4853 -0.6380 -0.7063 -0.5463 -0.5795 0.4613 0.2512 0.7567 0.6783 0.7010 0.4224 0.5148 0.3534 0.4890 0.3511 0.5207 0.3340 0.3338 0.2071 0.8916 0.7383 0.9472 0.8447 1.0000 0.9387 1.0000
Nd 0.4227 -0.4235 0,4294 -0.6606 -0.5456 0.3129 0.6350 0.4060 0.3401 0.3257 0.3170 0.1936 0.7202 0.8338 0.9312 0.9804 1.0000
Eu
TiO2
0.5489 -0.5332 0.4854 -0.5859 --0.4814 -0.0019 0.4353 0.0562 -0.0067 0.0152 -0.0212 -0.0267 0.5522 0.6965 0.7145 0.9163 0.8950 0.9671 1.0000
Dy 0.4699 -0.5961 0.3605 -0.3236 0.1739 -0.3908 0.0286 -0.3585 -0.3836 -0.3947 -0.3881 -0.3192 -0.3183 -0.2493 -0.1875 0.0330 0.0255 0.2152 0.1969 0.4837 0.3643 0.3755 1.0000
Sc
-0.0928 -0.0209 0.0691 -0.1201 -0.3039 0.1488 0.3832 0.7444 0.9760 1.0000
0.5693 -0.6019 0.5666 -0.6226 -0.4523 0.0374 0.4562 -0.1055 -~1008 -0.0956 -0.1373 -0.1830 0.2596 0.4253 0.4661 0.8186 0.8017 0.9330 0.9650 0.9749 0.9910 1.0000
Lu
-0.1200 -0.0199 0.0872 -0.1371 -0.3298 0.1599 0.4130 0.7631 1.0000
0.6077 -0.8426 0.6755 -0.7430 -0.2703 -0.0784 0.6068 0.0201 -0.0453 -0.0726 -0.0707 -0.1647 0.1786 0.2523 0.4443 0.5287 0.4819 0.6277 0.5263 0.6404 0.6277 0.6303 0.5767 1.000
V
-0.1200 -0.0059 0.0717 -0.1272 -0.3207 0.1301 0.4022 0.7954 0.9943 0.9762 1.0000
Ce
-0.4679 0.6540 -0.6354 0.6741 0.4317 0.0452 -0.5475 -0.2781 -0.1479 -0.1452 -0.1431 -0.0275 -0.4496 -0.4986 -0.5083 -0.6356 -0.6082 -0.6587 -0.6683 -0.6578 -0.6050 -0.5967 -0.3106 -0.7157 1.0000
Cr
-0.6754 0.3834 -0.0946 0.5850 0,0573 -0.0957 -0.3895 -0.4396 -0.1557 -0.1871 --0.1656 0.0064 -0.4625 -0.4445 -0.4644 -0.3820 -0.3329 -0.2580 -0.2765 -0.3391 -0.1739 -0.1518 0.0463 -0.3230 0.3671 1.0000
Co
-0.4363 0.6999 -0.6867 0.7029 0.5163 -0.0437 -0.5969 -0.0774 0.0342 0.0275 0.0479 0.0479 -0.2497 -0.3228 -0.3401 -0.4964 -0.4852 -0.5536 -0.5368 -0.5943 -0.5686 -0.5827 -0.3437 -0.6364 0.5455 0.3105 1.000
Mg
-0.2192 0.2112 0.2839 0.0187 -0.1892 -0.2582 0.0977 0.2516 0.3086 -0.0079 -0.5088 -0.5692 -0.2921 -0.5432 -0.5782 -0.0057 0.2732 0.2830 0.2923 0.6368 0.6617 0.6749 0 . 8 8 9 1 0.8070 0.9125 0 . 6 8 6 1 0.6389 0.8955 0.6676 0.6238 0.9298 0.7055 0.6489 1.0000 0.5582 0.5065 1.0000 0.9801 1.0000
2°6pb/2°apb 2°7pb/2°4Pb z°aPb/Z°4pb aTSr/86Sr La
0.5806 -0.5934 0.5468 -0.6207 -0.4279 0.0293 0.4469 -0.0858 -0.1016 -0.0984 -0.1347 -0.1779 0.2815 0.4445 0.5116 0.8314 0.8163 0.9492 0.9703 0.9841 1.0000
Yb
0.0480 -0.0535 0.0799 -0.3281 -0.3539 0.2353 0.5015 1.0000
La/Sm
0.6949 -0.6841 0.5831 -0.7121 -0.5104 -0.0704 0.5874 0.2229 0.0295 0.0682 0.0231 -0.0006 0.7276 0.8282 0.8854 0.9422 0.9274 0.9692 0.9744 1.0000
Tm
-0.2063 0.3103 0.1624 -0.6715 -0.0489 0.7773 -0.1876 -0.8421 -0.2304 -0.7573 1.0000 0.2823 1.000
Na20
0.5300 -0.5671 0.5416 -0.6765 --0.5001 0.1322 0.5844 0.1562 0.1251 0.1187 0.0985 0.0210 0.5029 0.6479 0.7514 0.9375 0.9262 1.0000
Tb
CaO
-0.7080 0.3124 -0.6764 -0.0229 1.0000 -0.8369 0.8406 0.3807 1.0000 -0.7412 -0.7235 1.0000 0.5165 1.0000
MgO
1.000
FeO"
A1203
SiO2
Linear correlation coefficients between selected geochemical variables
TABLE IV
0
r~ t~
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O
E
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m
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re
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z
m rll
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-7.
220
D.
FONTIGNIE
AND
J-G.
SCHILLING
87Sr/SSSr (a) ~d • . . . . . . . . .
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• • • • -
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Fig. 4. Correlation diagrams for: (a) (La/Sm)n vs. S7Sr/S6Sr; (b) ( L a / S m ) , vs. 2°6pb/2°4pb; and (c) 2°6pb/2°4pb vs. 87Sr/S6Sr"
SrSr/a6SrANDREEVARIATIONSALONGTHE EASTERMICROPLATEBOUNDARIES
looking basalt which appears to belong to the northeastern segment 4 in term of bulk chemistry but not from Sr and Pb isotope composition. Along the West Rift, 875r/S6Sr increases progressively from north to south. The highest value is reached at the most southern station, which is also the closest from the East Rift. The regular and general trend is scattered by the sample H, the picritic basalt G and the samples N and K. Reasons for some of this scatter are discussed in Section 6. Finally, the 87Sr/ 86Sr profile along the West Rift does not confirm the possibility of a small spike-like radiogenic isotope anomaly around 25°S on the West Rift (samples H and I), as suggested by the Pb isotope variation and discussed by Hanan and Schilling ( 1989 ). Within the binary mantle plume-asthenosphere mantle source mixing model discussed by Hanan and Schilling (1989), the good linear correlations observed in Fig. 4 between the Pb isotope ratios and 878r/86Sr, rather than hyperbolic trends, indicate that the Pb/Sr concentration ratio in the two mixing end-members must be similar. Furthermore, the high degree oflinearity between 875r/86Sr and (La/ S m ) , (Fig. 4; Table IV) would also suggest similar Sr/Sm ratios in the two end-member sources. A noticeable amount of curvature has been previously noted between (La/Sm) n and Pb isotope ratios (Hanan and Schilling, 1989 ), suggesting higher P b / S m ratios in the enriched mantle source of this region. A plot of Pb isotope ratio with S m / L a shows an hyperbolic trend of opposite curvature, suggesting lower Pb/La ratios in the enriched source. In other words, the scale of relative enrichment, or degree of incompatibility, in the processes responsible for the fractionation between these two types of mantle sources in the region appears to have been La> P b > Sr> Sm. 5. Statistical methods
Our Easter Microplate data set is now composed of 48 basalt glasses from 47 different 1o-
221
calities. Each basalt glass is described by 27 geochemical variables, which are: 7 major elements: 10 REE: 4 transitional elements: 4 isotopic ratios: 2 derived variables:
SiO2, A1203, FeO *, MgO, CaO, Na20, TiO2 La, Ce, Nd, Sm, Eu, Tb, Dy, Tm, Yb, Lu Sc, V, Cr, Co 2°6pbF°4pb, 2°Tpb/2°4pb, 208pb/204pb' 875r/a6Sr (La/Sm)., Mg-number [Mg/(Mg+ Fe 2÷ ) ]
To maximize the number of samples used in the multivariate analysis, we did not use K20 and P205 because there were too many missing values (Schilling et al., 1985 ). Although there are statistical methods for handling missing values, we chose to avoid them because of the many assumptions involved and the biases these could introduce. In what follows, we will treat and interpret the above variables together and simultaneously, instead of successively and independently. The multivariate statistical methods used are primarily drawn from those described by Tatsuoka ( 1971 ), Green (1976), Le Maitre (1982) and Dagnrlie (1986). The computer programs were developed by the first author in GWBASlC for an Olivetti ® M24, and are IBM ® PC compatible with minor modifications. Listing of these programs are available upon request from the first author. The data set is composed ofp samples (48) each described by n variables (27). This set can be reported in a matrix A composed o f p rows and n columns, with pXn entries a(i,j), or of dimension p × n. As it is commonly the case, p < n. Each sample is now expressed in a multiple space by a n × 1 component vector. A "mean" in such a space is also represented by a vector of n elements. For a given data set, it is customary to compute for each variable (column) the deviation of every sample from its mean and report the results in a mean-corrected matrix A~ instead of ,4. The product ,4aW,4d is the sum-of-the,squares-and-crossproducts matrix (SSCP) which is the basic
222
D. FONTIGNIE AND J-G. SCHILLING
block of any multivariate statistical manipulation and analysis (e.g., Green 1976). The scalar variance is replaced in multivariate analysis by an n × n variance-covariance matrix D, whose principal diagonal d(i,i) are the variances and the other elements d(i,j), the covariances. It is defined by:
O = [ 1/ ( p - 1 ) ]A d "rAa
( 1)
Because of the uneven nature of the geochemical variables in terms of units, magnitudes, range of variability, analytical errors and geological sampling errors one must weight in some rational fashion the raw data and arrive for direct comparison to some dimensionless geochemical variables (Le Maitre, 1982; A1l~gre et al., 1986). The reader is referred to those authors for a more thorough discussion of these problems. Because of the homogeneous quality of the analytical data of the EMP we did not weight the data for "analytical" and "geological" errors as done by All~gre et al. ( 1986 ). Their isotopic data set were global in nature and their generalized reduction m e t h o d concerned with inhomogeneous analytical data quality, particularly for 2°7pb/2°6pb relative to other Pb, Sr and Nd isotope ratios and relative to its limited variation range in m o d e m oceanic basalts. Instead, we weighted the variance-covariance matrix D in such a way that the variance of all the variables are equal to unity. This is equivalent to using the correlation matrix R instead of D in the following way:
Adw=AdW
(2)
where Wstands for the weighting diagonal matrix whose elements, w(i,i), are the reciprocal of the square root of the diagonal elements of the matrix D [i.e. w(i,i) = 1 / ~ ]; and
R = [ 1 / ( p - 1 ) ],4aw "rAdw = [ 1 / ( p - - 1 ) ] (,4aW)T(,4aW)
= [l/(p-1)]WV(Ad'rAo)W = [l/(p-
1)] W T [ D / { 1 / ( p -
1}]W
=WDW
(3)
since for a diagonal matrix W T = W. Information can be drawn from the matrix R (or alternatively, another derived matrix where D is weighted differently) either about the samples or about the variables. Both are considered to be "objects". In the former case, the R-mode, the rows are taken into account in a derived matrix Adw'rAdw of n × n dimension whose rank is ~
86Sr/a6SrAND REE VARIATIONSALONGTHE EASTERMICROPLATEBOUNDARIES
CA reveals a hierarchy among the data by grouping together data progressively more distant from each other, statistically speaking, in multivariate space (Appendix, A-2 ). There are several ways to measure statistical distances between objects and to group them (Le Maitre, 1982). Usually, we have used the "single-linkage of the generalized distances D 2'' (Appendix, A-6 ). DA enhances and optimizes differences between groups a priori chosen (Appendix, A-3 ). Similarly to "univariate analysis", the statistical significance of differences between two multivariate means can also be tested using extended and well-defined statistics (Appendix, A-4). The univariate equivalent testing of multivariate variability becomes an "analysis of the covariance" (Appendix, A-5 ). 6. Outliers
Singular samples ("outliers") from this data base can be recognized from their statistical distance to some mean. We have applied this principle in three different ways: ( l ) Arbitrarily identify outliers which deviate by 3-standard deviations from the means. No real statistical level is attached to such value because the real nature of the distribution is unknown. These outliers are listed in Table V. (2) We consider samples lying outside of an ellipse of 95% confidence in the correlation diagrams 87Sr/g6Sr vs. 2°6pb/2°4pb (Fig. 4b) or vs. (La/Sm)n (Fig. 4a). For the same reaTABLE V "Outliers": samples having one or several variables outside the _+3 standard deviations range from the mean Sample
Number of variables
Variables
G m f d 7
2 1 2 4 7
SiO2, Co Na20 (La/Sm)n, La, Ce SiO2, MgO, 875r/86Sr, Co SiO2, all MREE and HREE
223
son, the level of confidence is again arbitrary. Because of the very high correlation between the different Pb isotope ratios, comparison of Sr isotopic ratios with 2°Tpb/2°4pb or 2°8pb/ 2°4pb would be redundant. ( 3 ) We consider collectively k selected geochemical variables and calculate the generalized distance of individual samples from the centroid in that k-dimensional space. Fig. 5 illustrates this result applied separately to the major elements (Fig. 5a), a selected group of REE (Fig. 5b), the four isotopes ratios (Fig. 5c), and finally the set of four transition metals (Fig. 5d). The results of these three different methods are essentially concordant in revealing the dominant outliers. These are: ( 1 ) The picritic basalts d and G. These samples were known to be anomalous in bulk chemistry and in their mineralogy (Sigurdsson et al., 1985). This is confirmed in Fig. 5a, as well as by the REE data set (Fig. 5b ). The same conclusion is reached using the set of the four isotope ratios (Fig. 5c) and the correlation diagrams (Fig. 4). The latter diagrams show that sample d is the most radiogenic in Pb and Sr, and sample G the least of the entire EMP data set; and for that matter of the entire EPR so far published (see comparison in Hanan and Schilling, 1989). (2) Samples 2 and H. These samples outlaw the correlation especially in the Sr vs. Pb isotope diagram (Fig. 4b). In the (La/Sm)n diagram (Fig. 4a), they are inside but near the edge of the ellipse of confidence. Their abnormal character is also well apparent in Fig. 4c. The altered character of the pillow basalt from station H was evident to the naked eye. The freshest fragments were picked. Two fractions were analyzed, one with an acid leach prior dissolution, the other without. The unleached sample gave a higher 875r/86Sr ratio of 0.702928, and the leached fraction a value of 0.702866; thus suggesting seawater alteration. As for sample 2, since the 875r/86Sr ratio is enhanced with respect to the Sr-Pb isotope cor-
224
D. FONTIGNIE
D 2
AND J-G. SCHILLING
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Fig. 5. Generalized distances D 2 of individual samples to the centroid in the following selected multispaces for: (a) SiO2, A1203, FeO*, MgO, CaO, Na20 and TiO2; (b) La, Ce, Sm, Eu, Yb and Lu; (c) Pb and Sr isotope ratios; and (d) Sc, V, Cr and Co.
86Sr/a6Sr AND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES
relation, we presume that this sample suffered also some seawater alteration. (3) Sample 7 is unusually low in REE and SiO2 contents, probably because of its porphyritic nature. Its ( L a / S m ) , and Sr and Pb isotopic compositions show no unusual character. (4) Sample f lies outside the confidence ellipse in the Sr vs. (La/Sm)n diagram (Fig. 4a), but otherwise has no real unusual character. It is located on the East Rift (26.8°S) where the latitudinal profiles in La/Sm and Pb and Sr isotope ratios and ridge elevation reach a broad maximum (Fig. 3). 7. Geochemical classification based on multivariate analysis in Q-mode
Various geochemical parameters are conventionally used in petrogenesis for sorting out probable geological processes in operation, depending on their sensitivity to such effects. For example, it is readily accepted that Pb and Sr isotope ratios reflect mantle source heterogeneities if equilibrium partial melting prevailed. Major-element ratios such as FeO/ MgO, CaO/MgO, CaO/A1203, or NazO/CaO reveal the combined effect of varying extents of melting and fractional crystallization. Incompatible to lesser incompatible trace-element ratios such as La/Sm reflect partial fusion, if the operative degree of melting (F) is small (say < 10%). But it tends to reflect mantle source heterogeneities i f F > 10-15%, such as in the generation of tholeiitic volcanism. Such conventional wisdom is based on some 25 years of accumulated evidence in experimental petrology and geochemistry and forward modelling. It is possible to classify such geochemicalpetrological parameters according to their relative sensitivities to magma formation and evolution processes and mantle source heterogeneities, using multivariate analysis in Qmode. This approach was alluded to by All6gre et al. ( 1986 ) and is considered here to provide
225
objectively relative affinities between the geochemical variables. The method is considered here to illustrate its potential not only as a classification tool, but to some extent also in petrogenesis modelling because the closer these geochemical variables are to each other, the more geochemically alike they are, and the more likely their variation reflect a common cause or operative process. In view of the great number of geochemical variables and the difficulty of representing graphically on paper their affinities in such multi-dimensional sample space, we have made us in Q-mode of both PCA (Fig. 6a and b) and CA using Euclidean distances (Fig. 6c). PCA gives the relative position of the variables in some optimized projections. A part of the information is lost by reducing the multispace, here 22 dimensions, to a much smaller space, 3 in this case, by projecting onto principal axes 1,2 and 1,3. Only 72% of the total information can be represented in this 3-dimensional space. The three principal axes carry respectively 35.7%, 26.1% and 10.2% of the total variability. In contrast, a better estimation of the statistical distances between the variables is given by CA and the corresponding dendrogram. The latter illustrates the hierarchy of the distances between the 22 variables. However, the shortcoming of CA is that it does not provide any sense for the relative position of the variables. Thus, we emphasize that interpretation on the basis of these two types of analyses should be done simultaneously by considering together the overall information represented in Fig. 6a-c. Several major "geochemical" groupings are readily recognized in these two PCA projections: at one pole along principal axis 1, the major elements CaO, MgO, A1203, Mg-number, Co and Cr form a broad cluster. At the other end of axis I, two clusters are present, namely: incompatible trace elements and the three Pb and Sr isotope ratios. On the other hand, SiO2, NazO and Sc have intermediate and somewhat ill-defined positions or affini-
226
D. FONTIGNIE AND J-G. SCHILLING
(a)
8/4 7/6 • :6/4 7/4 .La/Sm .AI20a
.c,
.La .Ce
.Mg,h "MgO Na=O
.CaO
yio~
Co
EU.•sm ~102
.FeO~ Y b•
.v
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(b)
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7/6 La/Srn 8/4. .V 7 / 4 " "6/4
I
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I
I
I
I
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Yb.
Sm
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FeO~ ~ 1 .Ce
Ti02
.Eu
.Na20
(c)
[
Fig. 6. Q-mode analysis on matrix R for 22 selected geochemical variables: (a) PCA, projection onto axes 1 and 2; (b) PCA, projection onto axes 1 and 3; and (c) dendrogram for CA single-linkage, Euclidean distances. 7/ 6 = 87Sr/86Sr; 6/4 = 2°6pb/2°4pb; 7/4 = 2°TPbF°4Pb; 8/4 = 2°8pb / 2°4pb.
ties relative to these first-order groups. F e O * has an affinity for the moderately incompatible elements. Further sub-groups or even close
pairs, such as La-Ce or Eu-Sm,, can be defined. Not all these subgroups are necessarily retained in higher-order projections. For example, Fe and V are no longer close to each other in PCA projection 1,3 (Fig. 6b). Also, not that 2°7pb/2°apb is more removed from 2 ° 6 p b / 2 ° a p b than 2°8pb/2°4pb. This most likely reflects analytical uncertainties, since the analytical errors on 2°Tpb/2°4pb are significantly greater than for the other two isotopic ratios (Hanan and Schilling, 1989 ). The 2°7pb/ 2°4pb normalized variability is greater. As a result its correlation withw 2°6pb/a°4pb is decreased. Overall, however, the grouping observed make geochemical sense. As expected, the (La/ S m ) n plots close to that of the mantle source isotope indicators as well as to the most incompatible LREE, La and Ce (which are sensitive to mantle heterogeneities, partial melting, fractional crystallization and mixing as well). We interpret this to suggest that La/Sm variation in the region may also be influenced by varying degree of partial melting, as also evident from the fact that these basalts range widely from quartz to olivine and nephelinenormative compositions (Schilling et al., 1985). The middle REE (MREE) and heavy REE (HREE), F e O * and TiO2 have a close affinity• This is consistent with the observation that F e O * enrichment by extensive shallow-depth fractional crystallization among mid-ocean ridge basalt (MORB) tholeiites, as for example along the Gahipagos Spreading Center, east Pacific, is usually accompanied by an enrichment of the overall REE pattern and a resulting correlation between F e O * and Yb (Schilling et al., 1976). Note that in the dendrogram representation, the affinity of V and Yb, originally proposed by Bougault (1980), is for this region not better than for example Cr for Mg-number, statistically speaking. The usefulness of the combined multivariate classification procedure is further illustrated in the classification of individual ele-
S6Sr/86Sr A N D REE V A R I A T I O N S A L O N G T H E EASTER M I C R O P L A T E B O U N D A R I E S
(a)
2
.L=
.vm .Lu
.Dy
.Ce I
• I ¥b
i
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Sm"
1
Nd
.Eu
(b)
3
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Nd
.By
.Eu I
I
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F',
I Tb
i
1
• La ,Sm
.Lu
(c)
227
Eu) are at an intermediate position. The corresponding dendrogram shows at various hierarchic levels of affinity the progressive character of the REE series (Fig. 7c). At the lowest level, direct links are generally found between REE of adjacent atomic numbers (in the Masuda-Coryell REE diagram, atomic number correlates with the inverse of the ionic radius ). At the highest hierarchic level, only two major groups are recognized, the LREE (La, Ce, and presumably Pr) and the HREE (Sm to Lu ). At the next lower level of affinity one finds the three LREE, MREE and HREE groups noted earlier along principal axis I. Because of the close affinity of the four isotope ratios considered in Q-mode of analysis, one can conjecture that their variability have probably a common cause, which we interpret to be mantle heterogeneities. Therefore, the simultaneous use of these four variables together is an appropriate way to investigate mantle heterogeneity domains, their relation to ridge segmentation in the region, and their probable cause (s). We now turn to such an analysis using only these four variables. Because of their anomalous character, the two exotic picritic basalt glasses d and G will be excluded from the remaining multivariate statistical treatment.
8. Ridge segmentation 8.1. Principal components analysis (PCA)
Fig. 7. Q-mode analysis on matrix R for the REE: (a) PCA, projection onto axes 1 and 2; (b) PCA, projection onto axes 1 and 3; and (c) dendrogram for CA single-linkage, Euclidean distances.
ments within the REE group (Fig. 7). Three groups are apparent along principal axis 1, which contain 55.4% at the total variability (Fig. 7a). The LREE (La, Ce) form one pole, the HREE the other, and the MREE (Nd, Sin,
First, we briefly investigate the nature of the dispersion of the isotopic data, using the Rmode on the correlation matrix R (Appendix, A- 1 ). Fig. 8 shows the projection of the isotope data onto the principal axes 1,2 and 1,3. In a four-dimensional (4-D) space, the data scatter in the form of a very elongated and flat hyper-ellipsoid. Indeed, the first axis corresponds to 93.7% and the second to 5.2% of the total variability. The ellipsoid stretches from the less radiogenic samples (K type) to the more radiogenic ones (f type). The departure
228
D. F O N T I G N I E AND J-G. S C H I L L I N G
(a)
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Fig. 8. R-mode P C A on matrix R using Pb and Sr isotope ratios o f the EMP basalts: ( a ) projection onto axes 1 and 2; and ( b ) projection onto axes 1 and 3. 7/6 = 87Sr/86Sr; 6/4 = 2°6pbF°4pb / 7/4 = 2 ° 7 p b / 2 ° 4 p b / 8 / 4 = 2°8pb/2°4pb.
from a more elongated ellipsoid comes partly from the weights of the altered basalts H and 2. Without them, the two principal axes would carry 96.3% and 3.0% of the total variability. Note that the second axis is not negligible. The scattering of the data is not simply along a straight hyperline, i.e. the limiting case of an
ellipsoid. Nor is its deviation from such a hyperline simply due to an increase scattering in the Sr ratios due to seawater alteration, because in the Pb isotope space only the second principal axis is also significant (1.3%). Thus the shape of the cloud is ribbon-like. The possibility that the EMP represents two
86Sr/S6Sr AND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES
giant overlapping ridge axes, perhaps characterized by distinct and isolated mantle source domains, was previously considered by Hanan and Schilling (1989), using only L a / S m a n d / or Pb isotopes. The test of binary mixing in three Pb isotope dimensions between the two rift populations can be conducted fairly well, since it should be two lines, or two fairly elongated ellipsoids if for analytical a n d / o r geological reasons a certain degree of heterogeneity in the Pb isotopic composition of the two endmembers is accepted. To do this, one needs first to investigate if the two ellipsoids are parallel or not. If they are, one has to determine then if the two main axes are distinct or not. The first step is to investigate if the two correlation matrices are statistically distinct, i.e. to determine if the orientation of the two ellipsoids are distinguishable or not. An analysis ofcovariance (Appendix, A-5 ) shows that they are not, ( • 2 o b s - 8 . 0 , theoretical Z 2 at 5% for 6 d.f. is 12.6). As they are not, a second step should decide if the correlation matrices, calculated separately for the two branches, are not significantly different from the matrix calculated for both branches together; that is to determine whether the two ellipsoids have indistinguishable elevations or not. In other words, we not test whether the two elongated ellipsoids are parallel, or colinear. In the latter possibility the two branches of the EMP would share he same end-members in such mixing model. The covariance analysis shows that the two trends are not distinguishable ()~2ob s = 10.9, theoretical Z 2 at 5% for 12 d.f. is 21.0). We conclude that the end-members in the binary mixing beneath the two rifts cannot be distinguished, at least by this statistical method. One could extent such test of mixing between the two rifts in 4-D isotopic space by adding the 87Sr/86Sr ratio, providing that Sr/ Pb concentration ratio in the two end-members are not too different. Otherwise, the mixing trends in such space would not be linear. We have seen in Table IV and Fig. 4 that 87Sr/ 865r is strongly linearly correlated with 2°6pb/
229
2°4pb or other Pb ratios. Thus such test is justified. Again tests I and 2 were found to be both acceptable (test 1: Z2obs = 15.7; Z2th. (10) = 18.3; test 2: Z2obs = 20.5, Z2th (20) = 31.4). We again conclude that the end-members in the suggested binary mixing taking place beneath the two overlapping rifts are indistinguishable, at least by this statistical method. However, CA and DA discussed below reveals some important differences between the two depleted type of EPR segments located just north and just south of the EMP (i.e. segments I and 8).
8.2. Cluster analysis (CA) A more objective and quantitative approach to geochemical ridge segmentation without a priori classification can be made using CA, the four isotopic ratios as variables, and generalized distances (Appendix, A-2 ). On this basis, Fig. 9a shows the connections between samples in the form of a dendrogram. A good separation of the overall data can be obtained with the first five groups. The stations H, 2 and K are too poorly connected to be attributed to any of these groups (for drafting convenience only, these three samples are labelled as group 6 in Fig. 9a). The 5-group definition is very significant (Rao's F = 19.3 with nl = 16 and n2= 126; theoretical F at 0.01% is 2.15 ). The geographical distribution along the EMP boundaries of these five statistically defined groups are shown in Fig. 9b. Geographically, not all five groups are randomly distributed. Groups 2-4 tend to form a coherent geographical structure, or isotopic segmentation, which broadly coincide with the morphotectonic segmentation shown in Fig. 1. Namely: Geographically, cluster 2 spans the northern segments I and 2. This reinforces our earlier belief that segment 2 is a mature ridge segment underlain by a "normally" depleted mantle and is merely an extension of the EPR (Hanan and
230
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Schilling, 1989 ). However, segment 8 south of the EMP is represented by cluster 3 which is slightly more radiogenic and cannot be considered as normal. In contrast, cluster 5 is confined to the East Rift, where the geochemical anomaly is present and the ridge is also unusually elevated. Group 4 tends to flank group 5 along the East Branch but, interestingly, it also spread to the southeastern most tip of the West Rift, which
is also closer to the East Rift and the main geochemical anomaly. Finally, cluster I is broadly distributed along the EMP boundaries and seems to dominate segment 4. Group I is also intermediate in radiogenic Sr and Pb content (as evident in Figs. 3 and 4), and this may explain its more random geographical distribution. It is also instructive to illustrate directly the relative position of these samples and their
S6Sr/S6Sr AND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES 2
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explain the same amount of variability in DA, one has to use the projections in planes 1,2 and 1, 3 (Fig. 10b and c, respectively). The three axes carry respectively 50.0%, 27.3% and 21.3% of the total variability. PCA shows clearly the progressive radiogenic evolution of the samples from groups 2 and 3 towards the most radiogenic group 5, and the intermediate positions of groups I and 4. A similar evolution is also observed in DA for groups 2-5, but the order of the two intermediate groups 1 and 4 is reversed as a result of the distortion caused by the method, whose objective is to maximize differences among groups (see the Appendix, A-3 ). It also brings out more clearly the important difference existing between groups 2 and 3 on projection of axes 1,3 (Fig. 10c); that is, the EPR "normal ridge segments" 1 and 2 in the north and NW corner of the EMP, from that of the EPR segment 8 present south of the EMP. The difference between groups I and 3 is also optimized in DA compared to PCA (Fig. 10a-c). The two groups are both mildly radiogenic (Fig. 3 ), and hardly distinguishable in conventional 2-D isotope diagrams (e.g., Fig. 4b), but perhaps for slightly higher 87Sr/86Sr a t a given 2°TPb/ 2°6pb in group 3 relative to 1. However, the difference of multiple means between these two groups are statistically significant [F(16,4) =6.3, at 95% the F-limit is 3].
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cluster in this 4-D isotope space: (1) this is done with PCA more than 98% of the total variability is accounted for in projections onto axes 1 and 2 (Fig. 10a); and (2) in order to
An independent check of the segmentation revealed by factor analysis can be made in a somewhat less objective way, using the same isotopic data in the same space, but with an independent a priori choice of sample grouping. We now a priori divide our basalt sample population into eight groups according to their position with respect to the tectonic ridge segmentation shown in Fig. 1. The PCA representation of these eight groups are shown in Fig. 11 a, whereas the optimized
232
D. F O N T I G N I E A N D J-G. S C H I L L I N G
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isotopic differences between these eight groups a priori chosen, using DA, is shown in Fig. 1 lb. Despite the two independent approaches (i.e. with and without a priori classification ) a very similar picture is obtained because of the similarity between the isotopic structure and
the morphotectonic segmentation. The centroid of the EPR normal ridge segment I plots at one extreme of the principal axis 1. The centroid of segment 6 on the East Rift, which contains the geochemical anomaly, plots at the other extreme. Centroids from the other seg-
S6Sr/86Sr AND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES
ments plots primarily along the principal axis at intermediate distances between these two extreme poles. There is also a remarkable symmetry about segment 6, both with respect to statistical and geographical distances. Segments 5 and 7 immediately flanking segment 6 are very similar and plot in the isotopic space relatively close to segment 6. The two pairs are followed both in isotopic and geographical space by the pair of segments 4 and 8, which also located at about equal distance further out about segment 6 on the East Rift. PCA axis 1 can clearly be interpreted as a mixing line between the depleted asthenosphere type source and a plume-related type source. Note again that segment 2 is both geographically and statistically close to segment 1. The difference which statistically pulls apart segment 8 and 4 in DA is exaggerated, though significant (Fig. 11 b). We recall that the basalts from segment 8 are all clearly located off-ridge axis whereas this is not the case along segment 4 (Fig. 1 ). The distinction may suggest an aging effect for centroid 8. Although the segmentation suggested on the basis of such multivariate statistical analyses cold, to some extent, have been suggested on the basis single isotope profiles shown in Fig. 3, the power of the approach becomes more evident when more subtle differences such as between segments 4 and 8 need to be revealed and evaluated. DA has the potential to be a powerful tool for distinguishing "normal" ridge segments underlain by an asthenosphere with subtle isotopic and mean model-age differences. 10. Location of the influential plume The exact location of the so-called Easter hotspot remains uncertain. On the basis of plate reconstructions the hotspot has been located either ( 1 ) close or just west of Easter Island (Morgan, 1971; Minster et al., 1974; Hey et al., 1977; Chase, 1978); (2) in the vicinity of Sala y Gomez (Duncan and Hargraves,
233
1984; Okal and Cazenave, 1985), or (3) beneath the East Rift of the microplate (Handschumacher et al., 1981; Pilger and Handschumacher, 1981 ). The latter possibility has received support from basalts with high 3He/4He at two localities on the East Rift (Craig et al., 1984 and H. Craig, pers. commun., 1989), as well as from the good correlation of deviations in 875r/86Sr and 2°6pb/2°4pb with radial distances with respect to station f o n the East Rift (i.e. the geochemical anomaly maximum) (Fig. 12 ). For example for A2°6pb/2°apb, the correlation coefficient (r) is 0.860 and for the square of the same deviation it is even better ( r = 0.889 ). But no significant difference in the correlation could be found between the East and West Rifts. This suggest that segment 6 may indeed be a focal point of importance of controlling radially the mixing conditions and dispersion of heterogeneities along the boundaries of the EMP. This could indeed be interpreted as to suggest that the plume is centered beneath segment 6. On the other hand, we have previously suggested that the migrating ridge-hotspot source model adequately explains the geochemical anomaly observed on the East Rift and that the influential off-ridge hotspot may be located in the vicinity of Sala y Gomez (Schilling et al., 1985; Hanan and Schilling, 1989 ). We reached this conclusion on the basis of: ( 1 ) the width of the geochemical anomaly and empirical relationships previously established in this model context (Schilling, 1985 ); (2) Pb isotope compatibility of the EMP and off-ridge island volcanism in the region; and (3) the observation of a progressive decrease in radiogenic Pb from Sala y Gomez, Easter Island, and East and West Rifts of the EMP. We turn to these questions again using multivariate analysis in two ways: ( 1 ) with PCA to identify possible end-member mantle sources compatible with the binary mixing trend for the EMP, using Pb and Sr iso-
234
D. FONT1GNIE AND J-G. SCHILLING
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tope data from islands in the general vicinity; and (2) by comparing and modelling statistical distances between ridge segmentation and island groups revealed by DA and geographical distances between these segments or regions.
Fig. 13 compares the Pb-Sr isotope data from the EMP with those from ocean islands located east or west of the EMP, using PCA. It is clear that only Easter Island and Sala y Gomez Island are compatible with the EMP binary mixing tend present along PCA axis 1.
235
S6Sr/S6SrAND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES
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Neither the Polynesian Islands on the west, nor the distant Juan Fernandez-San Felix Islands on the east of the EMP are compatible with such a mixing trend. Note also that Sala y Gomez could possibly be the radiogenic-rich end-member of the EMP mixing line, whereas Easter Island already represents a mix since it overlaps with the EMP trend. This provides further and independent evidence that the offridge influential hotspot could indeed be in the vicinity of Sala y Gomez. It is interesting to note that the three older basalts from the Tuamotu Chain of atolls, west Pacific, analyzed in our laboratory (Grail et al., 1986), and one sample from Nuku Iva Island in the Marquesas, south Pacific (Vidal et al., 1984), plot very close to the Easter-Sala y Gomez end-member. This is not unexpected, since Pilger and Handschumacher ( 1981 ) have shown that the Tuamotu Chain on the Pacific Plate, and the conjugate aseismic Nazca Ridge on the Nazca Plate, east Pacific, may reflect the trace of Easter plume activity in the past, when the plume was ridge-centered. On the other
hand, this may be pure coincidence for Nuku Iva Island, as most other islands from the Marquesas are isotopically quite distinct and plate reconstructions does not suggest any connection. The second approach consists of plotting geographical distances against statistical generalized distances in Pb or Sr space, first between Sala y Gomez and the eight EMP ridge segment group centroids, assuming a priori the morphotectonic segmentation shown in Fig. 1 (Fig. 14). There is no particular trend. Thus, it is unlikely that the EMP geochemical anomaly was caused by radial dispersion into the asthenosphere of a plume located beneath Sala y Gomez. On the other hand, if the generalized statistical distances and the radial distances are measured relative to segment 6, two trends emerge with a discontinuity between the East and West Rifts (Fig. 15 ). The symmetry about segment 6 along the East Rift is particularly noticeable. We also recall that in the 4-D isotopic space representation, segment 6 plots
236
D. FONTIGNIEANDJ-G. SCHILLING D2
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closest to that of Sala y Gomez and Easter Island group than any of the other segments of the EMP (Fig. 13 ), thus suggesting a more direct geochemical link between these two groups. These relationships are also expected in the migrating ridge-plume source model discussed previously by Schilling et al. ( 1985 ) and Hanan and Schilling ( 1989 ). We also note that most recent and independent plate reconstructions carried out by Duncan and Hargraves ( 1984 ) and Okal and Cazenave ( 1985 ) place the influential hotspot also in the vicinity of Sala y Gomez. In view of these conflicting evidences, one needs to decide by some other independent means where the influential plume may be located and which of the two dynamical models may prevail. Currently we favor a plume rising in the vicinity of Sala y Gomez but tilted at shallow depth towards Easter Island and the EMP. This model does not necessarily rule out the possibility of a redistribution of excess plume-derived material from the point of discharge of the lateral plume flow channel on the East Rift (station f). It must be remembered that in order to create a geochemical gradient and excess elevation along the ridge axis, the plume flux, in this model, must exceed the flux required by passive spreading [see Schilling's (1985) model description]. The redistribution pattern would be radial if the trend revealed in Fig. 14 prevails, or somewhat more complicated if the discontinuity between the East and West Rifts revealed in Fig. 15 from the statistical multivariate analysis is emphasized. In the latter case, one can infer that the discontinuity reveals the sink effect of the active East Rift zone on the West Rift. Excess plume material reaching the East Rift would not only flow north and south along the East Rift from the point of injection (station f ), but also to a lesser extent, the plume-related tracer manages to reach the southeast most part of the West Rift where spreading is minimal, perhaps by some channeling below the 27°S pseudofault zone. From this point, the plume-related,
S6Sr/a6Sr AND REE VARIATIONS ALONG THE EASTER MICROPLATE BOUNDARIES
radiogenic-labeled, material would flow northwestward along the West Rift, be diluted and finally exhausted as a result of increasing spreading rate in this direction (Fig. 1 ). 11. Conclusions
Our conclusions will focus on two aspects: (1) multivariate statistics; and (2) interpretation of either the raw or the multivariate-manipulated geochemical data from the EMP. Three types of multivariate techniques have been used. ( 1 ) Principal components analysis (PCA), which does not distort the relative position of the data point in multispace, was found particularly useful for: (a) the Q-mode geochemical classification; and (b) in revealing probable end-members in the multicomponent mixing problem of the EMP. Its shortcoming is that it does not provide a direct numerical measure of closeness of the objects in a statistical sense. (i.e. statistical distances). (2) Cluster analysis (CA) and the dendrogram representation alleviated partly this problem, but the relative position of the objects in multispace is in turn lost. We emphasize the need of using and considering simultaneously the graphical representations provided by PCA and CA, as done in this paper for: (a) the Q-mode geochemical classification of the REE and (b) the R-mode classification of the samples in Pb-Sr isotopic space and resulting inferences obtained on ridge segmentation. (3) Discriminant analysis (DA), with its power of optimizing mutispace geochemical differences between groups a priori chosen by independent criteria (e.g., tectonic segmentation), was found useful in pinpointing more subtle isotopic differences between normal ridge segments 1 and 2, 4 and 8, or 1-2 from 4-8. As for the interpretation of the new EMP data reported, we emphasize the following: ( 1 ) The EMP basalt glasses show a particu-
237
larly large range of Pb and Sr isotopic ratios occurring over a short wavelength ( ~ 400 km), which is exceeding that of the entire EPR from 35°S to 45°N (i.e. ~ 10,000-km wavelength). This is also the case in the ondulation of the topography (Naar and Hey, 1990). It appears that the EMP isotopic anomaly is confined to the north by the 23 °S transform boundary, but appears to spill south of 27°S transverse boundary. (2) With the exception of a few outliers, the Pb and Sr isotope and La/Sm ratios are closely related, both geographically along the boundaries of the EMP as well as in sample space. As a result, the variation can readily be interpreted in terms of mixing of heterogeneous mantle domains. The possible effect of varying degrees of mantle fusion does not appear to have skewed significantly the distribution of the La/Sm ratio. (3) Whether the data were considered in 3Pb or 4-Pb-Sr isotope space, PCA, CA and DA all revealed at least three end-members: ( 1 ) a radiogenic Pb-Sr-rich component reflecting the plume influence on the EMP; (2) a radiogenic-poor end-member underlying the EPR just north of the EMP, which we associate with the depleted asthenosphere; and (3) a mildly radiogenic component, particularly in Sr, found along the EPR south of the EMP (segment 8). It is uncertain whether the later endmember is inherent of the underlying mantle source (and its past mixing and evolutionary history ), or is caused by some aging effects on these basalts which are located 20-30 km off the ridge axis (e.g., the 878r86Sr enhancement may reflect secondary high-T, or low-T, seawater alte;ation). (4) A comparison in 4-Pb-Sr isotopic space with PCA, of basalts from the EMP and hotspots on the Pacific and Nazca Plates indicates that Sala y Gomez has the greatest affinity to radiogenic-rich end-member plume component expected in the mixing model considered, followed by Easter Island, and the Tuamotu Chain. All these localities are lined up along the
238 so-called Easter hotline at ~ 26°S (Bonatti et al., 1977). The geographically more distant San Felix, Juan Fernandez, Society and Marquesas hotspots show no direct compatibility with the EMP geochemical anomaly. Easter Island represents a mixture diluted by the depleted asthenosphere. ( 5 ) Attempts to locate the influential plume, using various correlations between "statistical" and "geographical" distances, were inconclusive; but for the fact that station f o n the East Rift appears to be a focal point in controlling the radial dispersion o f plume-related material along the spreading boundaries o f the EMP. This exercise indicates that the plume may be located either beneath the East Rift a r o u n d 26°S, or due east. Instead o f modelling the Easter hotline as an elongated convective roll (Bonatti et al., 1977 ), we favor within the context of the hotspot source-migrating ridge model (Schilling, 1985 ), a plume rising in the vicinity o f Sala y G o m e z but tilted at shallow depth towards Easter Island and emerging on the East Rift of the EMP. (6) Finally, we note that the complementary and more general blob-cluster model of All6gre et al. (1984), remains a viable model for the region, since spreading rates on the EPR are anomalously low a r o u n d 26°S as result o f rift propagation and dual spreading over the EMP. The model predicts an inverse correlation between spreading rates and the wavelength and amplitude o f geochemical anomalies and associated ridge elevation. In this case, spreading rate is taken as a measure o f mantle convection rate. W h e t h e r in these two complem e n t a r y models, the most likely measure o f dispersion and dilution o f mantle plumes (blobs) is spreading rate (All6gre et al., 1984), or distance o f the migrating ridge to the hotspot (Schilling, 1985 ), remains an open question which will require more detailed considerations and tests. We emphasize that the two models are c o m p l e m e n t a r y and not mutually exclusive.
D. FONTIGNIE AND J-G. SCHILLING
Acknowledgements We t h a n k B. McCully for carrying out the REE analyses, and B.B. H a n a n and R. Kingsley for assistance in the laboratory and fruitful discussion. We thank D.F. Naar and two anonymous reviewers for useful comments. We are grateful to F. DiMeglio and his staff for neutron irradiations and facilities at RINSC. This work was partly supported by NSF (Grants OCE 8500683 and OCE 8710465) and the Swiss National F o u n d a t i o n for a Visiting Scientist grant ( 82,186.0.84 ).
Appendix A-1. Principal components analysis (PCA)
The most usual configuration of a cloud of points is a hyper-ellipsoid, a volume described by n axes in an n-dimensional geochemicalspace. PCA givesthe n perpendicular axes of the hyper-ellipsoid.The new coordinates are linear combinations of the original variables and are calculated from the eigenvaluesand eigenvectors associated either with the variance-covariance matrix D, or with the correlation matrix R. In the R-mode, the variance-covariance matrix D (or correlation matrix R) is n×n and there are a maximum of n eigenvaluesand eigenvectors.In the Q-mode,the matrix D (or R) is p × p but there are a maximum of n eigenvalues or eigenvectors. The first axis is the axis which contains the maximum variability of matrix D (or matrix R). The followingaxes are those, perpendicular to the previous ones, which explain the maximum of the remaining variability. If the ellipsoid is not a sphere, the meaning of one or more axes decrease and so, usually,a few axes onto which the objects are projected describe the cloud of points without too much loss of information. Attention has to be paid to avoid losingtoo much information in reducingthe number of dimensions. Nevertheless, for the kind of geochemical problems in hand, to be graphically useful, the considered space must be at least of two or three dimensions. This remark is also valid for DA. A limiting practical problem comes from the calculation of the eigenvalues and associated eigenvectors. The eigenvalues were calculated using Hotelling's iterating procedure (Tatsuoka, 1971 ). When the dimensionsof the matrices are large, the calculation time become prohibi-
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tive, and sometime there is no convergence toward a solution because of numerical limitations resulting from precision.
A- 2. Cluster analysis (CA) In this analysis, the distances (generalized or Euclidean or some other measure of similarity or dissimilarity between the variables) are estimated between the various samples. The two nearest samples are then linked and grouped together. This procedure is repeated until all the samples and groups are linked. The result of this work is summarized into a hierarchic type of diagram, th "dendrogram", where samples and groups are linked two by two. The higher the connection between two groups, the greater is the difference between them. We follow the method described in Le Maitre ( 1982, p. 168 ).
A-3. Discriminant analysis (DA) In this method one calculates new variables, linear combinations of the old ones, to enhance the differences between groups a priori defined by other independent means. A maximum of n axes is so obtained. Contrary to PCA, the axes in DA are not necessarily perpendicular. However, for convenience they are usually drawn perpendicular. Since the axes are not orthogonal, DA projections, in contrast to PCA projections, induce some distortion.
A-4. Comparison o f multiple means Hoteling's T 2 is the generalization of the Student's t statistics in a multiple space to compare the multivariate means of two groups of data. In a multiple space the means are vectors. It is obtained from a ratio of variances calculated for the two groups (F-test). The greater the ratio, the more different are the multivariate means. The equivalent of univariate "analysis of the variance" are Rao's R statistics for comparing several means (Tatsuoka, 19 71 ). The statistics tests the significance of a particular organization of a set into some groups. It works from a ratio of the variance between groups to the overall variance. The greater the ratio, the greater are the differences between the groups, the higher is the significance of the organization.
A-5. Comparison o f two or several matrices D The multiple-space equivalent of the univariant F-test of twc variances, and of Bartlett's test for several variances (Le Maitre, 1982 ) is the "covariance test". It is carried out by using the generalized (multivariate) variances (the determinants of matrices D) and the test is achieved with a Z2 (Dagn61ie, 1986 ).
A-6. The generalized distance or Mahalonobis" D e
When the variables are correlated, it is better to use the "generalized distance" instead of the Euclidean distance. A generalized distance corresponds to the ratio of the square of an Euclidean distance measured on uncorrelated transformed variables to their variances. Thus, these distances are dimensionless, weighted and corrected for the non-independence of the variables. In matrix algebra, the generalized distance between the objects i a n d j is given by: D2= [ 1/ ( p - 1 )] (xi--xj)TD
--I(xi--Xj)
(A-1)
where xi and xj are the vectors of p dimensions corresponding to objects i and j. Depending on the case, the nature of these objects are the samples, the means or the centroids (Dagn61ie, 1986). The homogeneity inside a group is estimated from the generalized distances of the samples to the centroid of its group. The greater the distances, the higher is the heterogeneity inside the group. A search and elimination of outliers should be made prior calculating the generalized distances D 2, since in principle they are objective measures between objects belonging to the same population, i.e. which verify the same dispersion matrix. Otherwise it could lead to an erroneous estimation of the dispersion matrix D and, correspondingly, of the calculated generalized distances as well.
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