Smithian and Spathian (Early Triassic) ammonoid assemblages from terranes: Paleoceanographic and paleogeographic implications

Smithian and Spathian (Early Triassic) ammonoid assemblages from terranes: Paleoceanographic and paleogeographic implications

Journal of Asian Earth Sciences 36 (2009) 420–433 Contents lists available at ScienceDirect Journal of Asian Earth Sciences journal homepage: www.el...

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Journal of Asian Earth Sciences 36 (2009) 420–433

Contents lists available at ScienceDirect

Journal of Asian Earth Sciences journal homepage: www.elsevier.com/locate/jseaes

Smithian and Spathian (Early Triassic) ammonoid assemblages from terranes: Paleoceanographic and paleogeographic implications Arnaud Brayard a,*, Gilles Escarguel b, Hugo Bucher c,d, Thomas Brühwiler c a

LMTG, UMR 5563 CNRS - Université Toulouse - IRD - Observatoire Midi-Pyrénées, 14 Avenue Edouard Belin, F-31400 Toulouse, France UMR 5125 PEPS CNRS, France; Université Lyon 1, Campus de la Doua, Bât. Géode, F-69622 Villeurbanne Cedex, France c Paläontologisches Institut und Museum, Universität Zürich, Karl-Schmid Strasse 4, CH-8006 Zürich, Switzerland d Department of Earth Sciences, ETH Zürich, Switzerland b

a r t i c l e

i n f o

Article history: Received 7 January 2008 Received in revised form 29 April 2008 Accepted 6 May 2008

Keywords: Early Triassic Ammonoids Biotic recovery Terranes Chulitna South Primorye South Kitakami Biogeography Paleoceanography

a b s t r a c t Early Triassic paleobiogeography is characterised by the stable supercontinental assembly of Pangea. However, at that time, several terranes such as the South Kitakami Massif (SK), South Primorye (SP) and Chulitna (respectively, and presently located in Japan, eastern Russia and Alaska) straddled the vast oceans surrounding Pangea. By means of quantitative biogeographical methods including Cluster Analysis, Non-metric Multidimensional Scaling and Bootstrapped Spanning Network applied to Smithian and Spathian (Early Triassic) ammonoid assemblages; we analyze similarity relationships between faunas and suggest paleopositions for the above-cited terranes. Taxonomic similarities between faunas indicate that primary drivers of the ammonoid distribution were Sea Surface Temperature and currents. Possible connections due to current-controlled faunal exchanges between both sides of the Panthalassa are shown and terranes such as SK, SP and Chulitna played an important role as stepping stones in the dispersal of ammonoids. SK and SP terranes show strong subequatorial affinities during the Smithian, thus suggesting a location close to South China. At the same time, the Chulitna terrane shows strong affinities with equatorial faunas of the eastern Panthalassa. This paleoceanographic pattern was markedly altered during the Spathian, possibly indicating significant modifications of oceanic circulation at that time, as illustrated by the development of a marked intertropical faunal belt across Tethys and Panthalassa. Ó 2008 Elsevier Ltd. All rights reserved.

1. Introduction Paleobiogeography plays a crucial role in the reconstruction of the paleopositions of continents and terranes. The latter are principally composed of ancient island arcs, oceanic plateaus or continental fragments, which travelled across oceans during part of their geological history before amalgamating with other blocks or continents (Schermer et al., 1984; Nokleberg et al., 2000). For instance, some paleontological data from American Cordilleran terranes indicate that they have been latitudinally offset by transform faults after docking with the Pacific margin (Coney et al., 1980). Latitudinal displacements are relatively easy to determine from paleomagnetic data or from the comparison of faunal compositions between terranes (Miller and Wright, 1987; Newton, 1987; Silberling et al., 1997; Orchard et al., 2001). For instance, the occurrence of low-latitude faunas in present-day high-latitude positions can provide key evidence for the movement of so-called suspect or displaced terranes (e.g. Kuenzi, 1965). In contrast, longitudinal displacements are more difficult to recognize. Nevertheless, some * Corresponding author. Tel.: +33 (0) 5 61 33 26 44. E-mail address: [email protected] (A. Brayard). 1367-9120/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.jseaes.2008.05.004

attempts of quantitative reconstruction based on corals have been rather successful (Belasky, 1996; Belasky and Runnegar, 1994; Belasky et al., 2002). The Early Triassic interval is globally represented by the simple and stable Pangea paleogeography (Fig. 1). However, several microcontinents and terranes crossed the Tethys (Ricou, 1994) and the Panthalassa at that time (Natal’in, 1993; Parfenov et al., 1993; Sokolov et al., 1997; Otoh et al., 1999). In this work, we focus on the paleobiogeographical relationships between worldwide Early Triassic ammonoid assemblages, with a special attention to faunas from the South Kitakami, South Primorye, and Chulitna terranes, which are presently located in Japan, eastern Russia, and south-central Alaska, respectively (Fig. 2). The main topic of the present study is to clarify the paleopositions and geodynamic of these three terranes based on their respective Early Triassic ammonoid faunas. For the Smithian and Spathian, numerical biogeography methods based on the computation and graphical display of taxonomic similarity structures allow us to quantitatively investigate the large-scale faunal affinities of these three terrane ammonoid assemblages with respect to 19 Tethyan and Panthalassic basins with known paleopositions (Brayard et al., 2006, 2007b). Hence, the present study differs from the methodology and first results

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90

Spitsbergen Ellesmere Axel Heiberg Islands

70

HALAS SA

50

10

British Columbia Greenland

? Chulitna

Idaho/Utah California Nevada

Balkans Albania

NT A P

latitude (˚)

30

-10

TETHYS

Caucasus South China Chios Iran Afghanistan Salt Range

Oman

PA

-30

Olenek-Lena Rivers

N

-50

Timor

?

South Primorye

South Kitakami

Spiti

GE A

Madagascar

-70 -90 -180

-120

-60

0 longitude (˚)

60

180

120

Fig. 1. Simplified Early Triassic paleogeographical map with the paleopositions of the studied basins and terranes (modified from Péron et al., 2005). Terranes with only estimated paleopositions are represented by black stars.

A

100 km

B

100 km

70˚

Russian South Primorye 45˚

60˚

Hokkaido

Vladivostok

40˚

Alaska

Chulitna

South Kitakami Tokyo

Anchorage 35˚

Honshu

-160˚

Yukon Kyushu 130˚

135˚

140˚

145˚

-140˚

Fig. 2. Present-day location of the South Primorye, South Kitakami and Chulitna terranes. Rectangle area overlapping the South Primorye indicates the studied terrane unit with Early Triassic outcrops.

published by Brayard et al. (2007b) in that it newly incorporates data from terranes into the paleobiogeographical analysis. Here, the compositions of terrane faunas are compared to those of paleogeographically well-known faunas (mostly plate-bound), which leads essentially to independent inferences about oceanic circulation and climate changes, and inferences about the dispersal mode of ammonoids, as well.

2. Paleobiological and geological settings 2.1. The Early Triassic ammonoid recovery The End-Permian mass extinction (252 Ma) decimated more than 90% of the marine species (Raup, 1979; Erwin, 1993). Until recently, the rate of the recovery, which ended near the Early/Middle

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Triassic boundary, was usually supposed to be very slow when compared to that of other mass extinctions (Erwin, 1993, 2006). However, new Early and Middle Triassic radiometric ages from northwestern Guangxi allow significant improvements in the time calibration of the recovery (Fig. 3; Ovtcharova et al., 2006; Galfetti et al., 2007b). Rates of recovery are also highly disparate across the different Early Triassic clades. Ammonoids and conodonts (see Brayard et al., 2006 for ammonoids and Orchard, 2007 for conodonts) evidently possess the fastest recovery rates during the Early Triassic (compare with Crasquin-Soleau et al., 2006 for ostracods; Chen et al., 2005 for brachiopods; Komatsu et al., 2004 for bivalves; and Stanley, 2003 for corals). Ammonoids almost disappeared at the Permian–Triassic boundary. All Triassic ceratitids are usually considered to derive from the morphologically simple Ophiceras genus, an offshoot of the Late Permian Xenodiscidae (Tozer, 1981; but see Brayard et al., 2007a for an exception). The Early Triassic recovery of ammonoids followed a global increasing trend in diversity. However, this increase was neither a smooth, nor gradual process and their diversification was twice severely interrupted (Fig. 3; Brayard et al., 2004, 2006). Following a first phase of low diversity (Griesbachian and Dienerian), the first massive radiation of the Smithian was set back to initial, basal Early Triassic conditions at the end of this substage, with a concomitant shift from latitudinal to cosmopolitan distributions. Simultaneous changes in the Carbon cycle and in the Boreal palynofloras are compatible with a massive input of CO2, most likely of volcanic origin (Ovtcharova et al., 2006; Galfetti et al., 2007a,b,c; Fig. 3). This profound turnover was followed by a dramatic evolutionary radiation during the early Spathian, when ammonoid diversity first briefly reaches a plateau value, which was unsurpassed during later Middle Triassic times. This extreme diversification was accompanied by the emergence of a very pronounced latitudinal gradient of diversity (Dagys, 1988; Brayard et al., 2006, 2007b; Fig. 3). A second severe diversity drop occurred around the Early/Middle Triassic boundary. Substantial evidence indicating a sea-level change has been documented for this time interval (Embry, 1988, 1997). The latitudinal diversity gradient was not totally restored until mid-Anisian (Middle Triassic) times (see Bucher, 1993). Thus,

Diversity

Middle Triassic

2.2. Paleoposition of continental masses and terranes The Early Triassic distribution of continental masses is shown in Fig. 1. The distribution between land and seas was dominated by the wide Panthalassa Ocean in its major part (90%) and by the Tethys Ocean in a smaller part (10%). The latter was centered on the Equator. It was widely opened eastward and connected to the Panthalassa. At that time, several terranes (e.g. Cimmerian and Cathaysian microcontinents) drifted across the Tethys, docking with Laurasia during the Triassic (Ricou, 1994; Besse et al., 1998; Stampfli and Borel, 2002). At the same time, terranes travelled across Panthalassa and accreted to the western margin of Pangea (see Nichols and Silberling, 1979; Tozer, 1982; Hawley et al., 1987; Belasky, 1996; Belasky and Runnegar, 1994; Belasky et al., 2002; Yancey et al., 2005; Johnston and Borel, 2007 for Chulitna, eastern Klamath, Stikinia, Wrangellia, and Cache Creek terranes of North America) or to the eastern margin of Pangea (see Kojima, 1989; Burij, 1997; Taira, 2001; Ishiwatari and Tsujimori, 2003; Ehiro et al., 2005 for the South Kitakami and the South Primorye terranes). Shi (2006), to which the reader is referred to for further details provides a recent summary of the present-day Asian geological and tectonic framework. However, the Late Permian to Early Triassic position of some of these Panthalassic terranes, including Chulitna, South Kitakami and South Primorye terranes, are still poorly constrained. For instance, the paleoposition of the South Kitakami terrane is still intensively debated (Maruyama et al., 1997; Otoh et al., 1999; Ehiro, 2001; Hada et al., 2001; Tazawa, 2002; Ishiwatari and Tsujimori, 2003; Kobayashi, 2003). Their Early Triassic paleogeographical locations are usually estimated by means of qualitative taxonomic comparisons, generally based on the likeliness estimates of nearby localities (e.g. Nichols and Silberling, 1979 for Chulitna; Ehiro,

Latitudinal gradient of diversity

-

1

Early Anisian

available data strongly suggest that global constraints such as climatic and oceanographic changes played a major role in shaping the evolutionary radiation of Early Triassic ammonoids (Brayard et al., 2004, 2005, 2006; Galfetti et al., 2007a,b,c; Escarguel et al., 2008).

+

-30˚

2

Eq

30˚

60˚

δ13Ccarb (VPDB) [‰] Humidity - Boreal trend Climatic variations

Endemism 3

4

5

30

-2 0 2 4

20 10

-

0

X/H ratio 0.5 1

6

+

248.12 ± 0.28 40

Olenekian

Early Triassic

30 20

Spathian

10

10 0

250.55 ± 0.4

30 20

Smithian

10

251.22 ± 0.2

Induan

?

Dienerian

20 10 10

Griesbachian 252.6 ± 0.2

PERMIAN Fig. 3. Chronostratigraphic subdivisions of the Early Triassic (radiometric ages by Mundil et al., 2004; Ovtcharova et al., 2006 and Galfetti et al., 2007b). Simplified trends of the ammonoid recovery during this period are indicated within columns 1 to 3 (data from Brayard et al., 2006, 2007b). Geochemical (d13Ccarb) and palynological (xerophyte/ hygrophyte elements ratio: X/H) fluctuations are indicated in columns 4 and 5 (data from Galfetti et al., 2007a,b,c). Interpretation of Early Triassic climatic fluctuations is illustrated column 6.

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1997, 2005; Tazawa, 2002; Kobayashi, 2003; Kashiyama and Oji, 2004; Wang et al., 2006 for Japanese terranes; Shi et al., 2003; Kotlyar et al., 2006, 2007 for the South Primorye). Concerning Permian times, taxa considered in such biogeographical analyses (as well as for biostratigraphic correlations) are brachiopods, bivalves and foraminifers, sometimes completed with ammonoid data (e.g. Shen and Shi, 2000; Shi, 2006; Kutygin, 2006; Kotlyar et al., 2007). During the Early Triassic, brachiopods and bivalves are much less diverse than ammonoids, making their use in geographical neighbourhood comparisons difficult. As ammonoids (i) are often more diversified than other shelly invertebrates, (ii) have well constrained paleogeographical and temporal distributions, and (iii) show marked latitudinal diversity gradients during the Smithian and Spathian stages (Brayard et al., 2006, 2007b), they are of great significance for assessing paleolatitudes of these terranes during the Early Triassic. We used three complementary methods (Cluster Analysis, Non-metric Multidimensional Scaling and Bootstrapped Spanning Network; Brayard et al., 2007b) to quantify the biogeographical affinities of the ammonoid faunas of South Primorye (SP), South Kitakami (SK) massif, and Chulitna Panthalassic terranes (Fig. 2) during the Smithian and Spathian stages. Spathian ammonoid faunas are not known from the Chulitna terrane. Yet, a Smithian fauna is well represented and has already been studied by Nichols and Silberling (1979). Griesbachian and Dienerian ammonoid taxa are comparatively less documented and are therefore not included in this quantitative analysis. 2.3. Overview of the terrane geological settings SP is actually a complex collage of overlapping and suturing terranes with various ages and compositions. The Early Triassic ammonoid assemblages from SP are scattered around Vladivostok, in the southern part of the Khanka block (Fig. 2). The outcrop area mainly consists in Late Paleozoic and Early Mesozoic sedimentary rocks deposited in a back-arc basin setting (e.g. Markevich and Zakharov, 2004; Shi, 2006). In the Japanese islands, the SK terrane is characteristic as it is composed of a well-developed stratigraphic sequence ranging from the Silurian to the Lower Cretaceous (e.g. Yoshida and Machiyama, 2004). Sengör and Natal’in (1996) suggested that SK and SP constituted a single Paleozoic arc system. However, even if they were probably geographically close to each other, some inconsistencies in paleobiogeographical and stratigraphical data still persist, thus making this hypothesis ambiguous (e.g. Yoshida and Machiyama, 2004). The succession of Chulitna terrane is mainly represented by imbricated sedimentary and volcanic strata of Paleozoic and Mesozoic ages underlying an oceanic crust remnant (e.g. Schermer et al., 1984). This terrane is known to have moved ca. 30° northward in latitudes since the Triassic (Yancey et al., 2005).

3. Data and methods 3.1. Nature of the data set Biogeographical patterns of ammonoids were analyzed from a data set made of 19 Tethyan and Panthalassic basins with known paleopositions (Brayard et al., 2006, 2007b), and the three studied terranes (Tables 1 and 2). Ammonoid data were taken from a taxonomically homogenized collection of published and unpublished systematic, biostratigraphical or paleobiogeographical lists (Table 3; Brayard et al., 2006). In most cases, fossil list for each basin represents a composite record made of all taxonomical occurrences recorded in several individual fossil localities from the same sedi-

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mentary basin. There is two, theoretical and practical advantages to work on such regional taxonomical assemblages. From a theoretical point of view, each basin covers a surface area ranging between 104 and 106 km2, which corresponds to a first order of approximation to regional metacommunities, i.e. sets of local communities related by migrations of interacting species (e.g. Leibold et al., 2004). From a practical point of view, the regional combination of local incidence data considerably reduces the incompleteness of single profiles affected by the variable distribution of selective preservation, as well by as the multiple potential sources of environmental, taphonomical and sampling biases related to the construction of fossil data sets. Indeed, for purely probabilistic reasons, a sampled regional taxonomical fossil assemblage, being the synthesis (and not the arithmetic sum) of the incidence data collected in several local assemblages, is expectedly less incomplete in expectancy than the individual local lists from which it is estimated. This is due to the fact that a given taxon will be falsely absent from a synthetic regional assemblage only if it is simultaneously falsely absent from all local assemblages where it should be recorded, which is statistically all the less likely as local lists are numerous. We processed all the available data at the generic level in order to minimize the taxonomic bias. Compared to the initial data set of Brayard et al. (2006), five genera strictly restricted to the studied terranes are added (Paleokazachstanites and Protophiceras for the Smithian; Eosturia, Ussuriphyllites, and Burijites for the Spathian; Tables 1 and 2), as well as one genus occurring both in Nevada and SP (Churkites). Generic determination is based on Tozer’s (1981, 1994) classification emended with some recently described and illustrated genera (e.g. Okuneva, 1990; Shevyrev, 1995; Brayard et al., 2007a; Jenks, 2007). 3.2. Inter-assemblage taxonomical similarities Taxonomically standardised incidence tables for the Smithian and Spathian stages were analyzed following the 3-fold methodology described and discussed in Brayard et al. (2007b). Unique taxa, i.e. found in only one locality, were not removed from the analysed data sets in order to take into account the level of faunal endemicity associated to each taxonomic assemblage when making the inter-locality comparisons. Based on the preliminary computation, for each incidence table, of its associated distance matrix using the square root of Watson et al.’s (1966) non-metric coefficient, two common multivariate techniques of hierarchical classification and ordination were first applied: (i) Cluster Analysis (CA), using computer softwares BIO-BOOT v. 1.0 (Escarguel, 2005) and PHYLIP v. 3.67 (Felsenstein, 2007); and (ii) Non-metric Multidimensional Scaling (NMDS), using computer software PAST v. 1.75 (Hammer et al., 2001). We preferred to use Watson et al.’s coefficient rather than other classical metrics such as Simpson’s and Jaccard’s coefficients, because of the double weight given to shared presences, and thus relative underweighting of absence and unique occurrence as an indication of faunal differences. As already emphasized by Legendre and Legendre (1998), such relative overweighting of double presences is an appealing property due to the always-ambiguous meaning of absence, which does not necessarily reflect real differences between the compared assemblages. The minimum spanning tree (MST; i.e. the chain of primary connections; Kruskal, 1956; Prim, 1957) associated to the ordination was superimposed onto each NMDS map in order to circumvent the problem of misrepresentation by projecting together objects which are distinct in higher dimensions (Legendre and Legendre, 1998). The stress value of each NMDS map is also given: the higher the threshold value, the more likely the ordination has not been successful (see Brayard et al., 2007b for details).

0

1

0

1

0

1

1

1

1

1

1

0

1

1

1

1

0

Oman

Timor

Afghanistan

South China

California

Nevada

Idaho

Caucasus

British Columbia

Spitsbergen

Ellesmere Isl.

Olenek-Lena Rivers 0

1

Salt Range

Japan

Primorye

Chulitna

0

0

0

0

1

1

1

1

1

1

1

0

0

0

0

0

0

Oman

Timor

Afghanistan

South China

California

Nevada

Idaho

Caucasus

British Columbia

Spitsbergen

Ellesmere Isl.

Olenek-Lena Rivers 0

0

Salt Range

Japan

Primorye

Chulitna

0

1

0

0

0

0

0

0

1

1

1

1

0

0

0

0

0

Madagascar

Spiti

1

1

0

0

0

0

0

0

1

1

1

1

0

0

0

0

0

0

0

1

0

0

0

0

0

1

0

1

1

0

0

0

0

0

0

0

suria

suria

ria

koceras

0

0

0

0

0

0

0

0

0

0

0

0

1

1

1

1

1

0

Metus- Parus-

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

celtites

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

suria

Oxyus-

0

1

0

0

0

0

0

1

0

0

1

1

0

0

0

0

0

0

anites

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

suria

Platus-

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

1

0

0

mirites

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

1

1

0

0

1

1

0

1

1

1

1

1

1

1

1

1

0

1

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

birites eyites

0

Xeno-

Prio-

0

0

0

0

0

0

0

1

0

0

0

1

1

1

0

0

0

0

nuites

0

1

1

0

1

1

1

0

1

1

1

1

1

1

0

1

1

0

0

0

0

0

0

1

0

1

0

1

1

1

1

1

1

0

1

1

0

1

0

1

1

1

1

0

1

1

1

1

1

1

0

1

1

0

chites

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

1

0

1

0

0

0

0

0

0

0

0

0

0

0

phanites atchites

0

1

0

0

1

1

1

0

0

0

0

0

0

0

0

0

0

0

prionites

Paraste- Anawas- Arcto-

0

1

0

0

0

0

0

0

0

0

0

1

1

0

1

0

0

0

Wasat-

0

0

0

0

1

0

1

0

1

0

0

0

0

0

0

0

0

0

ceras

1

1

1

0

1

0

1

1

1

1

1

1

1

1

0

1

0

0

lites

0

0

1

0

0

0

0

0

0

0

0

1

1

0

1

1

1

1

ceras

0

0

0

0

0

0

0

0

0

0

1

1

1

1

0

1

0

0

nites

0

1

0

0

0

0

0

1

1

1

1

1

1

1

1

0

0

0

ites

1

0

0

0

0

0

0

1

1

1

1

1

0

0

0

0

0

0

olites

Lance-

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

ratoides

0

0

0

0

0

0

0

0

1

1

0

0

0

0

0

0

0

0

ceras

Elko-

0

1

0

0

0

0

0

0

1

1

1

1

1

1

0

0

1

0

Owe-

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

nites

0

1

1

0

0

1

1

1

0

1

1

1

1

1

1

1

0

0

0

1

1

1

0

0

0

0

1

1

1

1

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1

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

oites

Metiny-

1

1

0

0

0

0

1

1

1

1

1

1

1

1

1

0

0

0

gites

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

1

0

0

tes

Clypi-

0

0

0

0

0

0

0

0

1

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

1

1

1

1

1

lobus

0

1

0

0

0

0

1

0

1

1

1

1

0

0

0

0

0

0

erites

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

rites

Pseudo-

0

1

1

0

0

0

1

0

1

1

1

1

1

1

1

1

1

1

gites

Flemin-

1

0

1

0

1

1

1

1

0

1

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0

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0

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0

0

0

0

0

naspis

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

1

1

1

0

0

0

0

0

1

1

1

1

1

1

1

1

1

0

nites

Subfle-

Arcto-

0

0

0

0

0

0

0

0

1

1

0

0

0

0

0

0

0

0

spenites

Hemia-

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

1

1

0

1

1

1

1

0

1

1

1

1

1

1

0

1

0

0

0

1

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

ites

Churk-

0

0

0

0

0

0

0

0

0

0

0

1

1

1

1

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

stanites

spenites zach-

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

ceras

Pseuda- Paleoka- Protophi-

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

flemingites mingites ceras

Anaxe- Pseudo-

Mesoheden- Aspe-

1

1

0

0

1

1

1

0

1

1

1

1

1

1

1

0

0

0

gites

Euflemin-

stroemia sageceras stroemia

Cordill- Telle- Heden-

1

1

1

0

1

0

1

1

1

1

1

1

1

1

1

1

0

0

nites

Meeko- Gyro- Priono-

mingites ceras

Lingyu- Wyomin- Anafle-

nannites nites

Para-

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

spidites spidites

Clypeo- Clypeoce- Pseuda- Para-

Stepha- Inyo-

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

kites

Therma- Proharpo- Lepis-

0

0

0

1

1

1

1

0

1

0

0

0

0

0

0

0

0

0

thiceras nites

Subvish- Melaga- Juve-

prionites nites

Hemi-

1

0

0

1

1

1

1

0

1

1

1

1

1

1

0

1

1

0

phiceras celtites

Anasi- Gurl-

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

elites

Pseudo- Preflori- Eukash- Hani- Glypto-

Submee- Ussu-

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

Spiti

0

0

ceras

mirites

aites

Keltero- Sakh-

Kash-

Madagascar

Smithian

Incidence matrix of the Smithian genera

Table 1

424 A. Brayard et al. / Journal of Asian Earth Sciences 36 (2009) 420–433

0

0

0

1

0

0

0

0

0

0

Iran

South China

Albania

California

Balkans

Nevada

Idaho

Chios

Caucasus

British

0

0

Ellesmere Isl.

Olenek-Lena

0

0

1

0

0

0

0

0

0

0

Iran

South China

Albania

California

Balkans

Nevada

Idaho

Chios

Caucasus

British

0

0

Ellesmere Isl.

Olenek-Lena

0

0

Japan

Primorye

Rivers

0

Spitsbergen

Columbia

0

0

0

Oman

Afghanistan

0

Salt Range

Timor

0

Spiti

ites

0

0

0

0

0

0

1

1

0

0

1

0

0

0

0

0

0

0

0

0

0

rites

Beat-

0

Dina-

0

Madagascar

0

0

Primorye

0

0

0

0

1

1

1

1

1

1

1

1

1

0

0

0

0

0

0

0

ceras

Japan

Rivers

0

Spitsbergen

Columbia

0

0

Oman

0

0

Afghanistan

0

Salt Range

Timor

0

Spiti

scoides

0

0

0

0

0

0

1

1

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

1

1

0

1

1

1

1

1

1

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

1

1

1

1

1

0

0

0

0

0

1

0

0

0

0

1

1

1

1

1

1

1

1

1

1

1

1

1

0

0

eites

Dagno- Stach-

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

nites

1

0

0

0

0

0

1

1

1

1

1

1

1

1

1

1

1

1

1

1

0

lites

Balka- Tiro-

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

toides

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

coceras

Diaplo-

0

0

1

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

koceras

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

kranites

Dori-

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

koceras

1

1

0

0

0

0

0

1

1

1

0

1

0

1

1

1

1

1

1

0

0

bites

Colum-

0

0

0

1

0

1

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

koceras

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

lites

?Tiro-

0

0

1

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

diceras

0

1

1

1

0

1

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

ceras

1

0

0

0

0

0

1

0

1

0

0

0

0

0

0

0

0

0

0

0

0

bites

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

bites

colum-

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

matites

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

tites

1

0

0

0

0

0

1

1

0

0

0

0

1

1

0

0

0

0

0

0

0

enites

?Cera- Hell-

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

ceras

1

0

0

0

0

0

0

1

1

0

0

0

0

0

0

0

0

0

0

0

0

sites

Palla-

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

oites

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

ites

Chiot-

0

0

0

0

0

0

0

1

0

0

0

0

0

1

0

0

0

0

0

0

0

ceras

Chio-

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

pites

Protro-

0

0

0

1

1

1

1

1

0

0

0

0

0

0

0

0

0

0

0

0

0

ites

Zeno-

0

0

0

0

0

0

0

1

0

0

0

0

0

1

1

1

1

0

0

0

0

erites

0

0

0

1

1

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

vites

0

0

0

0

0

0

1

1

0

0

0

0

1

1

1

1

1

0

0

0

0

ites

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

ceras

harpo-

1

0

0

0

0

0

0

1

0

1

0

1

1

1

1

1

1

0

0

0

0

ceras

0

0

0

0

0

0

0

1

0

0

0

0

1

0

0

0

0

0

0

0

0

tites

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

1

0

0

oides

1

1

0

0

0

0

0

1

0

1

0

1

1

1

1

1

1

1

0

0

0

bites

1

1

0

0

0

0

0

1

0

1

0

1

1

1

1

1

0

0

0

0

0

anites

1

1

0

0

0

0

0

1

0

0

0

0

1

1

1

1

0

0

0

0

0

kites

1

0

0

0

0

0

0

1

0

0

0

0

1

1

0

0

0

0

0

0

0

1

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

anites ynites

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

sovites

Kipari-

0

1

0

0

0

1

1

1

1

1

0

1

1

1

1

1

1

0

0

0

0

noceras

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

stroemia

heden-

Metadag- Meta-

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

goceras canites

Vickohl- Popo- Alban- Byrran- Hyr-

Pseudo- Parago- Epicel- Epiceltit- Subcolum- Fengsh- Pren- Tungl- Khval-

1

0

0

0

0

1

1

1

1

1

0

1

1

1

1

1

0

0

0

0

0

oides

Nordophi- Boreo- Pseudoky- Subiny- Isculit-

Procolum- Pleuro-

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

svalbar- runia

Even- Konincki- Arctomee- Boreomee- Neomee- Pseudo- Baja-

ritoides chitoides ites

dinarites ceras

Pseudo-

1

0

0

0

0

0

0

1

0

1

1

1

0

0

0

0

0

0

0

0

0

canites

?Xenodi- Sulioti- Hemile- Parano- Propty-

Madagascar

Spathian

Incidence matrix of the Spathian genera

Table 2

1

0

1

1

1

1

1

1

1

1

0

1

0

1

1

1

1

1

1

1

1

ceras

sage-

1

0

0

0

0

1

1

1

1

1

0

1

1

1

0

0

0

0

0

0

0

rites

1

1

0

0

0

1

1

1

1

1

0

1

1

1

1

1

1

1

1

0

0

nites

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

ceras

Digito-

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

geceras

Neo-

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Metasa- Eosturia

0

1

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

bites

1

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

(continued on next page)

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

panoceras phyllites colum-

Procar- Doabo- Neopo-

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

ceras

Tozeri- Pseudo- Cordille-

A. Brayard et al. / Journal of Asian Earth Sciences 36 (2009) 420–433 425

0

1 1 1 0 0 0 Primorye

0

0

0

0

0

0

1

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

1

0

0

0

1 0

1

0 0

0 0 0 0 0

0

0

0 0

1

0

0 1 0 0 0

1

0 0

1 Rivers

Japan

Olenek-Lena

1

0

1

0

0

0

1

0

0

1

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

1 0 0 1 0 Ellesmere Isl.

0

0

0

0

1

1

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0 0

0

1 0 0 0 0 Spitsbergen

0

0

0

0

0

1

1

0

1

1

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

1

0

0

0

1

1

0

0 1

0

0

0

0 0

0 0

0 0

0

0

0 0

0 0 0

0 0

0 0

0

0

0 0

0 0 1

0 0

1 0

0 0

1 1

0 0

0 0

1 1

0 0

0

1 British Columbia 0

0 0 0 Caucasus

0

0

0

0

0

0

0

1

0

1

0

0

1 0 0 0 0 Chios

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

1

1

1

0

1

0

0

0

0

0

0

0 1

0

0

0

0 0

0 0

0 0

0 0 0

0

0

1

0

0 0

0 0

1

1

1

1

0

0

1

1 0

0 0

0 1

1 0

0 0

0 0

0 0

0 0 0

0 0 0 Idaho

0 0 Nevada

0

0

0

1

0

1

0

0

0

0

0

0

0 1 0 0 Balkans

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

1 0

0 1

0 0

0 1

0 0

0

0

1 0

0 0 0

0 0

0 1

0

1

0 0

0

0

0

1 0

0 0

0 1

0 0

0 0

0 0

0 0

0 0 0

0 0 0 California

0 0 Albania

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1 0

0

1 0

0

1 0

0

0 1

1

0 1

1

1 1

1

1 1

0

0

1

0

0

0

0 0

0

0

0 0

0

1 1

0

0 0

0

1 0 0 1

0 0

0

0 0

0 1

1

0 0

0

0 0

0

0 0

1

1 0

0

0 0

0

0 0

0

1 0

0

0 0

0

0 0

0 0 0 South China

0 0 Iran

0 0 Afghanistan

0

0

0

0

0

0

0

0

1 0 0 0 Timor

0

0

0

0

0

0

1

0

0

1

0

0 0 0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

0 0

0

0

0 0 0 Oman

0

0

0

1

0

0

0

0

0

0

0

0 0 0

0

0

0

0

0

0

0

1

0

0

0

1

0

0

0

0

0

0

0

0

1

0

1

0

0

0

0

0

0 0

0

0 0

0

0 1

0

1 0

0

0

0

0

0

0

0

0

0 0

0 0

0

0 0

0

0 0

0

0

0

0

0

0

0 0

0 1

0 1

0

0 0

0

0 0

0

0 1

0

0 0

0

0 0

0

0 1

0

0 0

0

0 0

0

0 0

0 0 0 Salt Range

0 0 Spiti

0 0 Madagascar

0

0

0

0

0

0

0

0

0

0

rites llites pella lakites

Eophy- Mangysh- Mero- Leiophy- Ussu- Ussuri-

phyllites llites nites scites cereas

chordi- nites diceras

ceras

Proacro- ?Acrochor- Eoacro- Eogym- Ziyu- Procladi Paleo-

anitoides chordibites

yatesi

rites garites

Dalma- ?Prohun- ?Hunga- Eodanu- Preflori-

shanites tites missites garites thites ceras lingtes diceras kites tanites pites rites rites gites

Procarni- Prosphin- Sibi- Parasibi- Tjurur- Kazakhs- Oleni- Svalbar- Keyser- Oleneko- Monacan- Prohun- ?Middle- Qilian-

Table 2 (continued)

toides

Buri-

A. Brayard et al. / Journal of Asian Earth Sciences 36 (2009) 420–433 phyllites jites

426

In addition, we also computed the Bootstrapped Spanning Networks (BSN) associated to each distance matrix. Brayard et al. (2007b) first introduced the BSN method as a new non-hierarchical clustering technique allowing the visualisation of a non-metric interassemblages similarity structure as a connected network. Briefly stated, the construction of the BSN associated to a given incidence table involves the following three-step procedure: - preliminary computation of the undirected Minimum Spanning Network (i.e. the shortest connected network sensu Prim, 1957) corresponding to the observed dissimilarity matrix; - estimation, for each edge of the observed MSN, of its associated bootstrap support value. This estimation is achieved by repeated computation of the dissimilarity matrix and corresponding MSN for pseudo-samples randomly generated by non-parametric bootstrap of the observed data table; - removing, starting from the weakest (lowest bootstrap support value) to the strongest observed edge, of the observed MSN edges in order to simultaneously: * minimise the number of edges of the MSN (PN – 1 where N is the number of compared assemblages), * maximise the overall product of the bootstrap support values associated to the remaining edges. The resulting set of inter-assemblages links, which can be viewed as the simplest connected network best supported by the available data, can be easily visualized and interpreted by superimposing the BSN on a (paleo)geographical map showing the position of the taxonomic assemblages. The density and orientation of the BSN edges on such a map give direct indications about the biogeographical clusters and/or gradients underlying the analysed data set. Based on the bootstrapped dissimilarity pseudo-matrices computed using BIO-BOOT v. 1.0 (Escarguel, 2005), BSN v. 1.0 (Brayard et al., 2007b) and PAJEK v. 1.07 software’s (Batagelj and Mrvar, 2005) were used for BSN computations and visualizations, respectively.

4. Results 4.1. Smithian (Fig. 4) The bootstrapped CA (Fig. 4A) identifies five clusters showing support values >50%. Three of them were previously found in Brayard et al. (2007b): Sm1, corresponding to northeastern Panthalassic localities (Olenek, Spitsbergen, Ellesmere, British Columbia); Sm2, including three, geographically close equatorial localities from eastern Panthalassa (California, Nevada, Idaho); and Sm3 that groups two well diversified South Tethyan localities (Salt Range and Spiti). Departing from Brayard et al.’s (2007b) results, two new clusters appear as: Sm4, grouping two sub-equatorial Tethyan localities (Afghanistan and Timor); and Sm5 that surprisingly corresponds to two geographically distant localities (Caucasus and Chulitna). Note that in Brayard et al. (2007b) Caucasus was also linked to geographically distant localities within the Sm2 cluster. SK and SP display unresolved relationships with all other localities. The NMDS analysis (Fig. 4B) shows a similar biogeographical structuring but allows a more precise biogeographical location of SP, intercalated between Sm2 and South China, and defining with Sm4 a sub-equatorial group not identified by CA. This group was previously evidenced in Brayard et al. (2007b) and highlights the intense faunal exchanges between both sides of the Panthalassa. The BSN (Fig. 4C) returns an essentially similar pattern and yields several complementary insights. Principal clusters are recovered (Sm1, Sm3 and the sub-equatorial group made of Sm2, Sm4 and South China). The sub-equatorial position of SP interca-

A. Brayard et al. / Journal of Asian Earth Sciences 36 (2009) 420–433 Table 3 References for the studied terranes Terranes

References

South Kitakami – Japan

Kummel and Sakagami (1960) Bando (1964) Bando and Shimoyama (1974) Bando and Ehiro (1982) Hase et al. (1983) Ehiro (1993) Diener (1895) Burij and Zharnikova (1981) Zharnikova (1985) Okuneva (1990) Zakharov (1968, 1997, 2002) Markevich and Zakharov (2004) Nichols and Silberling (1979)

South Primorye – Russia

Chulitna – Alaska

lated between South China and Sm2 is clearly identified by the BSN. SP shows strong affinities with each group, highlighting the strong faunal exchange between both sides of the Panthalassa. In contrast with the CA and NMDS analyses, the BSN analysis clearly highlights the low-latitudinal position of Chulitna in the eastern Panthalassa, as previously suspected by Nichols and Silberling (1979) based on a qualitative analysis of ammonoid faunas. As it could be expected from its paleogeographical position, Madagascar is linked to Sm3. Oman appears preferentially connected to the subequatorial group rather than to Sm3. Caucasus displays a relatively weak and rather enigmatic biogeographical link with the distant and low-latitude Chulitna terrane, the latter being linked to the equatorial Sm2. We cannot exclude that this link might be explain by a poorly resolved data set. SK appears preferentially connected with Sm3 whereas this terrane is usually placed near South or North China. However, this pattern could actually reflect the incomplete knowledge of ammonoid from the SK massif: more data from the Smithian sections are needed here to complete the incidence table. Discrepancies between biogeographical analysis and paleobiogeographical distribution of localities (i.e. basins) may reflect either a primary signal such as thresholded distributions or modification of the biogeographical pattern due to subsequent geodynamic displacement. 4.2. Spathian (Fig. 5) The bootstrapped CA yields a hierarchy characterized by four well supported clusters (Fig. 5A): Sp1, corresponding to northeastern Panthalassic localities (British Columbia, Ellesmere/Axel Heidberg Islands, Spitsbergen and Olenek); Sp2, grouping three equatorial Panthalassic localities (California, Nevada, Idaho); Sp3, corresponding to equatorial Tethyan localities (Albania, Chios, Iran, Afghanistan, Timor, South China); and Sp4 represented by southern Tethyan localities (Salt Range and Oman) but excluding Himalaya and Madagascar. Other localities and especially the SP and SK terranes display unresolved relationships with these four main clusters. Within the Sp3 group, Albania and Chios show strong relationships due to several shared endemic taxa (e.g. Chiotites, Beatites). This hierarchy is similar to the previous analysis of Brayard et al. (2007b). The NMDS (Fig. 5B) displays a V-shaped gradational structure and recovers the four main clusters of the CA. This general configuration reflects a marked latitudinal biogeographical differentiation. Interestingly, Sp2 and Sp3 appear very close, suggesting strong faunal similarities between both sides of the Panthalassa. Contrary to the Smithian, SP and SK are close to this equatorial set but do not indicate the same affinities. Interestingly, the position on the NMDS map of SK suggests a close relationship with Sp2, a group of localities located on the other side of the Pantha-

427

lassa. The position of SP is also illustrated by an unexpected relationship with Chios, a locality far from its closest geographical neighbors. The BSN (Fig. 5C) allows the recovery of the main structures evidenced by CA and NMDS (Sp1, Sp2, Sp3, and Sp4) and returns the same information on the position of SP and SK. Madagascar is preferentially linked to Sp4 via Himalaya, as it could be expected on geographical evidences and as suspected on the NMDS map. The relationships of Balkans were unresolved by the CA and NMDS analyses. The BSN indicates that Balkans can be related to Sp2, a set of localities located on the other side of Tethys and Panthalassa, but within the same, equatorial latitudinal band. This preferential link, coupled with the inferred relationships of SK and SP, is tentatively interpreted as being influenced by the action of the surface oceanic circulation on the dispersal of ammonoids. Parallel to the observed biogeographical latitudinal structuring of faunas (Brayard et al., 2006, 2007b), the three approaches considered together thus evidence marked trans-oceanic equatorial connections (Sp2 with Balkans and SK) and specific current dispersal within the Tethys (SP with Chios). 5. Discussion 5.1. Chulitna As previously suggested by Nichols and Silberling (1979) by means of qualitative comparisons, and as highlighted here by our quantitative analyses, Chulitna displays marked sub-equatorial affinities during the Smithian. The Smithian ammonoid fauna of this terrane is closely linked to those from California, Nevada and Idaho (Sm2). However, Chulitna is also connected to Caucasus. This unexpected link might be explained by a poorly resolved data set or by some rare arrivals of populations from the eastern equatorial Panthalassa using Chulitna as a stepping-stone (Fig. 6). This faunal exchange was possibly allowed by a Smithian equivalent of the present-day North Equatorial Current (NEC) of the Pacific (Pickard and Emery, 1990; Stewart, 2005). Another possible eastward dispersion within the Panthalassa as suggested by the Pantropic hypothesis of Newton (1988) cannot also be excluded. This global scheme is complicated at the interface between the Tethys and the Panthalassa. Actually, it is hardly conceivable that the Early Triassic NEC freely passed through microcontinents and terranes of the eastern Tethys and kept its overall intensity and direction. A potential relaying Tethyan NEC or a multidirectional slow dispersion through the Tethys might have acted as relay. However, during Smithian times, the existence of a gyre within the northern Tethys appears improbable as none equatorial Tethyan fauna indicates specific affinities with Caucasus. A slow diffusive dispersion through the Tethys is also difficult to consider as none Tethyan fauna shows affinities with Caucasus. As previously highlighted in the methodological section, it seems quite unlikely that the inferred, statistically supported biogeographical link between synthetic assemblages from Chulitna and Caucasus, exclusive to any other Tethyan basins, is the spurious byproduct of sampling biases. Thus, based on the available evidences, we believe that another possibility must also be considered: (i) the Smithian Panthalassic NEC could have been deviated northward and prolonged in the northwestern Panthalassa, from the equator and along the northern coast of North China and Tarim; (ii) then this current could have turned left southward through a tight oceanic corridor between Pangea and Tarim/North China, and thus reaching Caucasus. At that time, this working hypothesis remains difficult to test due to the lack of published ammonoid faunas from this potential seaway. As Caucasus ammonoid diversity, recognized until then, is low and constituted by relatively intertropical cosmopolitan taxa (e.g. Owenites, Inyoites,

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A

B

Madagascar Salt Range

Sm3

Spiti

51.2

0.5

South Kitakami 0.4 Olenek

Sm1

0.3

56.5

British Columbia

0.2

60.3

Ellesmere

Chulitna

Sm5

66.3

Caucasus

South Primorye

Coordinate 2

Spitsbergen

75.4

Madagascar Spiti

Sm1

0.1 Olenek 0

SR Spitsbergen BC Ellesmere

Sm2

South Primorye

-0.2 Nevada

80.6

Chulitna Sm5

Oman -0.3

-0.2

Caucasus

-0.1 0 Coordinate 1

South China

54.3

Oman

-0.3

Idaho

0.1

South Kitakami

Sm4

AT South China

Sm2

-0.1

California 72.6

I NC

Sm3

0.1

0.2

0.3

Afghanistan

Sm4

Timor

Olenek

C

60˚N 94.9

Ellesmere British Columbia 78.2

Spitsbergen

30˚N

Chulitna

Caucasus Afghanistan

95.1

South Primorye South China

California

Idaho Nevada

Eq.

Timor Oman 30˚S

Salt Range 2

95.

Spiti

80.3

South Kitakami

Madagascar 50˚

100˚

150˚

200˚

250˚

300˚

350˚

Fig. 4. Biogeographical structuring of the Smithian dataset. (A) Fitch and Margoliash’s Least-square majority-rule consensus tree (bootstrap supports estimated with 10,000 iterations; <50% when not indicated; APSD = 6.7% [see Felsenstein, 2007 for definition]; the bar scale indicates the length of 0.1 Watson et al.’s distance-unit on the tree [vertical branches are null-distance lines displayed for graphical convenience]); (B) Non-metric Multidimensional Scaling map and superimposed Minimum Spanning Tree (stress = 0.13 [see text for details]). BC, British Columbia; SR, Salt Range; I, Idaho; N, Nevada; C, California; T, Timor; A, Afghanistan. (C) Bootstrapped Spanning Network: numbers indicate the bootstrap support values for each edge (100% when not reported; see Brayard et al., 2007b for details).

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A

B

Olenek

80

British Columbia

Sp1

Ellesmere

62.7

Spitsbergen

0.5

Himalaya 0.4

Madagascar Balkans

Madagascar

0.3

Sp1

Oman

Sp4 Salt Range Caucasus

South Kitakami South Primorye

0.2

Coordinate 2

85.5

Spitsbergen

Ellesmere 0.1 SR

55.1

0

T A Iran

-0.1 California

95.9

-0.2

Nevada

Oman

Sp4

Idaho

Sp2

Olenek

Himalaya

Balkans

BC

South Kitakami C

N I Sp2 South China Chios South

Sp3 Albania

Caucasus

-0.1

0

Primorye

South China -0.2

Timor

0.2

0.3

0.4

Iran

69.8 68.3

62.1

0.1 Coordinate 1

Afghanistan

Sp3 Chios

0.1 81.2

Albania

Olenek 98

.7

C

60˚N

Ellesmere Spitsbergen British Columbia Caucasus

98.7

99.1

South China Afghanistan

98.2

Eq.

South Kitakami

.2

96

Oman

Idaho Nevada California

70.3

Iran 99.5

Albania

30˚N

South Primorye

Chios Balkans

5

99.

86

Salt Range

Timor 30˚S

Himalaya

Madagascar 50˚

100˚

150˚

200˚

250˚

300˚

350˚

Fig. 5. Biogeographical structuring of the Spathian dataset (tree’s APSD = 5.4%; NMDS’ stress = 0.15). See Fig. 4 for details.

Preflorianites, Lanceolites; Table 1) this excludes endemism and suggests a poor sampled area. New sampling from this basin as

well as North China and Tarim blocks might question the first or second scenario.

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A. Brayard et al. / Journal of Asian Earth Sciences 36 (2009) 420–433

Spathian

1

PANTHALASSA

60

3

40

2

4

20

18

19

TETHYS

17 0 16

15

-20 -40

13

11

14

B 8 A

?

9

C

?

76

5

10

12

50

100

150

200

250

300

350

PANGEA

PANGEA

Smithian

1

PANTHALASSA

60

?

40

3

2

4

20

19

C

TETHYS

0

14

-20 -40

8

13

76

B A

5

9 11

10

12

50 PANGEA

100

150

200

250

pantropic dispersion

300

350 PANGEA

weak dispersion intense dispersion Fig. 6. Paleoceanographic and paleogeographic scenario for Smithian and Spathian (latitudes and longitudes expressed in degrees). See text for details. Fossil assemblages: (A) South Kitakami; (B) South Primorye; (C) Chulitna; (1) Olenek-Lena rivers; (2) Spitsbergen; (3) Ellesmere-Axel Heidberg islands; (4) British Columbia; (5) Idaho; (6) Nevada; (7) California; (8) South China; (9) Timor; (10) Spiti; (11) Salt Range; (12) Madagascar; (13) Oman; (14) Afghanistan; (15) Iran; (16) Albania; (17) Balkans; (18) Chios; (19) Caucasus.

5.2. South Primorye The three quantitative methods used in this study show that the SP terrane was very likely located near the Equator, at the interface between the Panthalassa and the Tethys. Here too, strong faunal similarities with Sm2 highlight the intense faunal exchanges between both sides of the Panthalassa, and suggest that a Panthalassic NEC or an eastward Pantropic dispersion, both using intervening terranes, existed during the Smithian and the Spathian (Fig. 6). All analyses show that SP and Chulitna were not strongly connected, which very likely indicates that these two terranes were located at different latitudes. SP may have occupied a lower latitudinal position than Chulitna. Indeed, in a reverse case, SP should have shown high similarity values with Chulitna, the Panthalassic NEC current bringing common taxa to both places. Contrary to the Smithian, the Spathian taxonomic affinities of SP do not indicate any connection with the eastern Panthalassa and the equatorial Tethys affinities, but now show strong relationships with northern Tethyan faunas. This might indicate a profound modification of marine faunal exchanges between the Smithian and the Spathian, and thus, of currents. Sub-equatorial faunal exchanges between each side of the Panthalassa intensified during the Spathian (Fig. 5C). Yet, SK and SP terranes are less implied as stepping stones at that time. Thus, Pan-

thalassic currents probably intensified during the Spathian, as illustrated by the erection of numerous sub-equatorial links across Tethys and Panthalassa. The same hypothesis can be applied to the Tethys and explain the new affinities of SP. By the Spathian, a true and intensive North-Tethyan gyre could have been active, transporting taxa to the western Equatorial Tethys and bringing them back along the Cathaysian terranes. In this hypothesis, SP was probably on the way of this return current. Interestingly, preliminary paleomagnetic data from Sokarev et al. (2004) suggest a northern equatorial position (ca. 10°N) for SP during the Smithian and Spathian. These quantitative analyses also strongly highlight the importance of SP for biostratigraphical correlations between both sides of the Panthalassa. Indeed, as SP shows marked taxonomical affinities with each Panthalassic sides during the Smithian and Spathian, it is very likely that SP will eventually serve as a major reference for equatorial correlations. 5.3. South Kitakami A controversy exists concerning the paleolatitude of the SK during the Permian and around the Permian–Triassic boundary. On the one hand, based on coral, bivalves, foraminifer or ammonoid faunas, SK is often considered to have been located at a southern

A. Brayard et al. / Journal of Asian Earth Sciences 36 (2009) 420–433

equatorial position, close to South China during the Late Permian (Ehiro, 1997, 2005; Ehiro and Kanisawa, 1999; Hasegawa et al., 2003; Kashiyama and Oji, 2004; Wang et al., 2006). On the other hand, some authors place the SK massif close to North China, essentially justifying their opinions on brachiopod assemblages (Shi et al., 1995; Tazawa, 2002; Shi, 2006). Supporters of the latter hypothesis suggested that ammonoid assemblage analyses suffer from a potential post-mortem drifting of shells from other neighbouring biogeographical provinces (Tazawa in Yoshida and Machiyama, 2004). However, as far as we know and even if we cannot totally rule out this possibility, there is no major evidence (including fragmentation, breakage, current orientation, etc.) of any postmortem transport of Early Triassic ammonoid shells. Smithian results highlight high similarity values between SK and southern Tethyan faunas, thus providing more evidence for a southern equatorial position of the SK as already suggested by Ehiro (1997) based on a Permian ammonoid study. The similarities between these Tethyan sites could have been generated by a weak South-Equatorial current dispersal (Fig. 6A). At that time, an intense gyral current within the southern Tethys probably did not exist: in the opposite case, the SK terrane should show high faunal similarities with faunas from the western Tethys. This type of dispersal might be compared with a weak and slow diffusion process through Tethyan terranes. A true seaway, or at least a West-East directional current, along the northern margin of Gondwana as observed during the Middle Permian (Blendinger et al., 1992; Sone et al., 2001) is probably to be ruled out or is poorly efficient during the Smithian. As for SP, SK affinities change between the Smithian and the Spathian. The SK terrane shows several links with equatorial eastern Panthalassic faunas during the Spathian. Same explanations as for the SP can be suggested. The preferential link of the SK terrane with the eastern Panthalassic basins (cluster Sp2) may rather indicate a change of the oceanic circulation (Fig. 6B). In this way, SK was certainly close to SP but relatively isolated (possibly by South China) from a potential current from the western Tethys. The present study also indicates that, contrary to the Permian configuration where SP and SK shared closely related faunas (Shi, 2006); biogeographical similarities between SP and SK were weak during the Smithian and Spathian, while they were closely geographically located. This observation formally does not refute Sengör and Natal’in’s (1996) hypothesis of a single magmatic arc, but suggests that the two terranes were probably located on opposite sides of the arc, and thus related to rather independent water masses by threshold in SST and/or bathed by different currents. 5.4. The Smithian/Spathian boundary Our results clearly emphasize that, in addition to SST, which is the primary driver of large-scale latitudinal diversity gradients (Brayard et al., 2004, 2006, 2007b; Escarguel et al., 2008), Sea Surface Currents were an important parameter controlling large-scale taxonomical similarity patterns and dispersal of ammonoids. Indeed, our results indicate marked exchanges between both sides of the Panthalassa with a preponderant role for terranes as stepping-stones during the Early Triassic. During this interval, long-distance dispersal of ammonoids following the continental margins is to proscribe because taxa would have to cross unsuitable SST belts. Thus, changes of faunal affinities also emphasize modifications of the paleoceanographic configuration. In this way, the Smithian shows intense gyres within the Panthalassa but probably not within the Tethys, leading to rather high level of species endemicity (Brühwiler et al., 2007, in progress). Changes of ammonoid diversity and distributions observed between the Smithian and Spathian might correspond to a reorganization of the oceanic circulation (Fig. 6). The Spathian context

431

indicates a more complex system of intense gyres, especially highlighted by marked sub-equatorial faunal exchanges between both sides of the Panthalassa. This strongly suggests an intensified oceanic circulation at that time (Fig. 6B). To summarize, the Smithian/Spathian boundary (SSB) corresponds to a marked change of the oceanic circulation. As emphasized by previous works, the SSB is also concomitant with marked changes in overall taxonomic richness, gradients of diversity, and geographic rarity of ammonoid genera (Brayard et al., 2004, 2006, 2007b). The SSB also coincides with short, but drastic events identified in the palynological, global oceanic geochemical and sedimentary records (Galfetti et al., 2007a,b,c). These sudden SSB modifications reflect an important and global climate change as well as a possible shift in the oceanic circulation. It probably also reflects a return to normal marine geochemical conditions corresponding to the end of the carbon cycle perturbations associated to the Permian/Triassic boundary (Payne et al., 2004; Galfetti et al., 2007a,b). Anoxia, hypercapnia and CaCO3 undersaturation state are often suggested as a cause for the persistence of harsh environmental conditions during the Early Triassic, thus delaying the recovery (Fraiser and Bottjer, 2007; Payne and Kump, 2007). These possible environmental perturbations seem to have ended around the Smithian/Spathian boundary. 6. Conclusions Usually, studies on taxonomical similarities are done in a qualitative way, based on the closest neighbour(s) of the study area (e.g. Tazawa, 2002). However, our work clearly illustrates that a global scale quantitative analysis prevents biases linked to the author subjectivity such as an arbitrary association of taxa to a province. Quantitative analysis also provides an improved assessment of biogeographical structuring, e.g. through non-parametric bootstrap and Monte-Carlo methods for estimating statistical supports or generating null models of spatial organization. In this way, global scale analysis using methods such as BSN appears as a robust and powerful approach for resolving biogeographical relationships. As suggested by previous works (Brayard et al., 2006, 2007b), the spatial similarities between faunal assemblages indicate that main parameters controlling the ammonoid distribution were SST and currents. Trans-oceanic connections by oceanic currents between distant faunal assemblages are clearly suggested, and terranes such as the South Kitakami, the South Primorye and the Chulitna are likely to have played an important role as stepping stones in the ammonoid dispersal. During the Smithian, the South Kitakami and the South Primorye terranes show strong sub-equatorial relationships suggesting a location close to South China. At the same time, the Chulitna terrane shows strong affinities with equatorial faunas of the eastern Panthalassa. This paleoceanographic context drastically changes during the Spathian, as illustrated by the development of a marked intertropical faunal belt across Tethys and Panthalassa, and possibly indicates profound modifications of the oceanic circulation. This fact is corroborated by a marked shift in climate and depositional environments at the Smithian/Spathian boundary (Galfetti et al., 2007a,b,c), as well as in ammonoid and conodonts diversity and distribution (Brayard et al., 2006, 2007b; Orchard, 2007). Acknowledgements This work was supported by the Swiss NSF project 200020113554 (H.B.) and benefited from long-term exchanges about Early Triassic paleoenvironments and Smithian ammonoids with Thomas Galfetti and Nicolas Goudemand. Programs are available on

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