Detection of Late Cretaceous eustatic signatures ... - GeoScienceWorld

Detection of Late Cretaceous eustatic signatures using quantitative biostratigraphy James S. Crampton† GNS Science, P.O. Box 30-368, Lower Hutt, New Zealand

Poul Schiøler The Geological Survey of Denmark and Greenland, Ø. Voldgade 10, DK-1350, Copenhagen K., Denmark

Lucia Roncaglia Danish Oil and Natural Gas A/S, Agern Alle 24-26, DK-2970 Hørsholm, Denmark ABSTRACT This study tested the potential for highresolution quantitative biostratigraphic methods to distinguish tectonic from supposedly eustatic sequences. The study employed automated multidimensional graphic correlation using constrained optimization (program CONOP). Our analysis was based on 15 onshore sections in eastern New Zealand spanning the Coniacian to Maastrichtian stages (Upper Cretaceous), and 398 wellconstrained lowest- or highest-occurrence records derived from 245 dinoflagellate species. The age of the resulting composite section was calibrated using six dated bioevents; two of these events were tied to geochemical or paleomagnetic datums. Following calibration, the composite section had an average relative temporal resolution of less than 130 k.y. through the study interval, although the succession of events was not dated to this level of precision in an absolute sense. Although the CONOP composite will not resolve unconformities or condensed intervals that occur across all studied sections, such “global” unconformities can be identified using clusters of events that are placed at a single composite level. Fifteen major event clusters were identified, 10 of which coincided closely with sequence boundaries identified in the Northern Hemisphere; the probability of this coincidence arising by chance alone is ~8%. Although these results must be regarded as provisional, they suggest that high-resolution quantitative stratigraphy can provide a potent tool for the identification and correlation of stratigraphic sequences. Furthermore, our findings add significant †

E-mail: [email protected].

support for recent studies that have argued for the presence of Late Cretaceous eustasy. Keywords: biostratigraphy, correlation, eustasy, Late Cretaceous, New Zealand, quantitative analysis, sequence stratigraphy, unconformities. INTRODUCTION Distinguishing tectonic from eustatic signatures within stratigraphic successions remains problematic (e.g., Pedley and Frostick, 1999, and associated papers). This issue is of particular interest for the Upper Cretaceous system, for which the evidence of high-frequency, largemagnitude global sea-level changes, and the implied growth and decay of continental-scale ice sheets, remains equivocal (e.g., Abreu et al., 1998; Barrera and Savin, 1999; Miller et al., 1999, 2003, 2004, 2005a, 2005b; Price 1999; Stoll and Schrag, 2000; Huber et al., 2002). In part, the problem reduces to one of resolution in biostratigraphic and sequence stratigraphic correlation: arguments for eustasy require demonstration of global synchroneity of third- and higher-order sequences (for relevant discussions of this problem, see Miall, 1992; Miall and Miall, 2004). This can be extremely difficult using conventional correlation tools, especially in regions of stratigraphic or structural complexity. In this paper, we employ the newly developed quantitative stratigraphic approach of automated multidimensional graphic correlation using constrained optimization (CONOP; Kemple et al., 1995) to derive a very high-resolution biostratigraphic framework for lithologically monotonous, but structurally and stratigraphically complex, Coniacian to Maastrichtian successions in eastern New Zealand. Using this framework, we differentiate numerous local unconformities from those of regional extent and develop an age

model that allows correlation of our regional unconformities with sequence boundaries recognized in the Northern Hemisphere. Although the results presented here must be considered provisional, they seem to provide a global-scale test of hypothesized Late Cretaceous eustasy. During the Late Cretaceous, New Zealand was positioned at ~70°S (Sutherland et al., 2001). Coniacian to Maastrichtian strata of eastern New Zealand are inferred generally to have been deposited during thermal subsidence on the passive paleo-Pacific margin of New Zealand, following its separation from Gondwanaland (e.g., Carter, 1988; Ballance, 1993; King et al., 1999). The studied successions lie close to the base of the first-order transgressive megasequence that characterizes New Zealand Late Cretaceous and Paleogene stratigraphy. Cretaceous subduction in eastern New Zealand is likely to have ceased by about Cenomanian times, although this interpretation remains contentious (Field et al., 1997, p. 121, and references therein). Regardless of this, Coniacian to Maastrichtian formations are dominated by fine-grained siliciclastics or pelagic carbonates and show little conspicuous evidence for significant syndepositional tectonism. The present study was focused on strata immediately overlying a regional onlap surface that started forming at the same time as initiation of Tasman Sea spreading (MacPherson, 1948; King et al., 1999). In stratigraphic updip locations, this surface has been called the Waipounamu erosion surface, and it is strongly diachronous, recording perhaps 50 m.y. of fluvial erosion, marine transgression, and planation (LeMasurier and Landis, 1996). Here, we concentrate on fully marine strata deposited basinward; it is these that preserve the most complete sedimentary record of geological events during the Coniacian to Maastrichtian stages.

GSA Bulletin; July/August 2006; v. 118; no. 7/8; p. 975–990; doi: 10.1130/B25826.1; 9 figures; Data Repository item 2006121.

For permission to copy, contact [email protected] © 2006 Geological Society of America

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Crampton et al. Fifteen outcrop sections were studied in detail (Fig. 1). Three of these lie within the northern part of the Canterbury basin (Field et al., 1989); the rest are distributed throughout the onshore extent of the East Coast basin (Field et al., 1997). Sections in the East Coast basin were selected, in part, to provide a series of three transects perpendicular to the paleo–continental margin, although it is possible that the original relationships have been disrupted substantially by Neogene deformation (see following). Sections from the Canterbury basin were included in an effort to resolve possible basinwide tectonic events in the East Coast basin. Because calcareous macro- and microfaunas are typically depauperate, poorly preserved, and/or of low diversity in the studied formations (e.g., Crampton et al., 2000), the present biostratigraphic analysis is based instead on diverse, abundant and well-known dinoflagellate floras (Wilson, 1984; Schiøler and Wilson, 1998; Roncaglia et al., 1999; Schiøler et al., 2000, 2001, 2002). Throughout this paper, in order to facilitate comparisons with previous studies, we have calibrated our biostratigraphic events to the global geochronological scale of Gradstein et al. (1995). We note that this scale differs somewhat from the recently proposed time scale of Gradstein et al. (2004), although these differences are minor in the studied interval (6 and/or mean penalties >50 (Fig. DR3A). These events were given weights of 0 in the input file used to generate the final composite section. Zero-weighted events do not influence the coexistence constraint in CONOP 9, and they do not contribute to the penalty score. In other words, they were effectively eliminated from the analysis. These events are indicated in the composite section (Table DR2, see footnote 1), but are omitted from all other plots and outputs based on the composite. RESULTS The CONOP Composite Section The CONOP composite section is presented in Figures DR4–DR17 and Table DR2 (see footnote 1). Because the individual events in the composite are too numerous to label and for ease of comparison between logs, the vertical scale of the composite is expressed as percentage units above the base. This convention deliberately separates the task of integrating biostratigraphic and field data from the explicit inference of an age model for the composite section (undertaken later). In the composite, the 398 reliable or well-constrained events are distributed across 182 event levels. In Figures DR4–DR17 (see footnote 1), the composite is shown against each of the studied sections; one example section, Ben More, is shown in Figure 4. Note that the “event clusters” marked on these plots are explained below. Typically, 25%–50% of expected taxa are present at each sampled horizon in each section. In Figure 4 and the plots of Figures DR4–DR17, convergence of many composite event levels to a single horizon in a given section, and corresponding steps in the event-depth plot, can indicate either true relative condensation of the section at that point and/or apparent condensation due to wide sample spacing or structural disruption. Bundling of composite events due to wide sample spacing results because CONOP locates events only at actually sampled horizons (see Methods)—wide sample spacing in a particular section relative to the composite inevitably causes several composite events to be clustered at sample horizons on either side of a sample gap. With these caveats in mind, all significant composite event convergences and bundles in each section have been examined against all available evidence to determine whether they mark true intervals of sedimentary condensation or are artifacts of sampling, faulting, or the method. Disconformities, unconformities, and condensed intervals indicated in the central

columns of Figures 4 and DR4–DR17 are those inferred to be real. From these results, it can be seen that CONOP has correctly identified all unconformities or disconformities recorded in the field. In addition, it has detected a large number of other possible disconformities or highly condensed intervals, many of which are supported by field observations. Using the Ben More section as an example (Fig. 4), later in this paper we cite corroborating field and other evidence for the unconformities and condensed intervals that have been identified using the CONOP composite. Detailed interpretation of all sections and an explanation of inferred depositional patterns, however, will be undertaken elsewhere. Age Interpretation To a first approximation, the spacing of events in the CONOP composite section is likely to be proportional to their true spacing in time (Sadler and Cooper, 2004). In order to correlate precisely the composite with the chronometric time scale, it is necessary to calibrate the composite using events of known age. Sadly, there are few suitable events in the Coniacian to Maastrichtian interval in New Zealand, and calibration to the local and international time scales is rather problematic (Crampton et al., 2000; Cooper, 2004). Events used here to correlate the composite section to the international time scale of Gradstein et al. (1995) are listed next in ascending stratigraphic order. These correlations are based either on direct geochemical or paleomagnetic ties in New Zealand, or on other Southern Hemisphere mid- to high-latitude bioevents that have themselves been correlated using a range of paleontological and geochemical criteria (refer to the cited publications). Only taxa that are believed to be well known taxonomically are used; some events, such as the lowest occurrence of Isabelidinium cretaceum s.s., are excluded because of uncertainties regarding consistency of identification and taxonomic concept. 1. The lowest occurrence (LO) of the dinoflagellate Conosphaeridium striatoconum, which is inferred to lie close to the base of the Coniacian stage in Australia (Young and Laurie, 1996) and in the Northern Hemisphere (Williams et al., 2004). In New Zealand, this event apparently lies low in the local Teratan stage (G.J. Wilson, March 1995, personal commun.; Crampton et al., 2001) and just above the base of the Coniacian according to the correlation of Cooper (2004). This event has been identified in three of the studied sections. Herein, we adopt an age of 88.5 Ma for the LO of C. striatoconum.

2. The LO of the dinoflagellate Nelsoniella aceras, which is known to lie close to the C34/ C33 magnetochron boundary in New Zealand (Crampton et al., 2000). The age of this boundary is somewhat contentious (see Crampton et al., 2000, and references therein); here we assume that it is at the Santonian-Campanian boundary and adopt an age of 83.5 Ma, following Gradstein et al. (1995). The LO of Nelsoniella aceras was identified in nine of the studied sections. 3. The LO of the dinoflagellate Cerodinium diebelii, which has been inferred to lie at the base of the Upper Campanian in Antarctica and the Southern Ocean (Crame et al., 1991; Mohr and Mao, 1997; Pirrie et al., 1997) and, more recently, to lie within the middle Campanian in southern mid-latitudes (Williams et al., 2004). In Australia, there are conflicting reports of the age of this event (see references in Roncaglia et al., 1999; Young and Laurie, 1996). The LO of C. diebelii was identified in three of the studied sections. Herein, following Williams et al. (2004), we assume a mid-Campanian age of 78.5 Ma for this event. 4. The LO of the dinoflagellate Isabelidinium korojonense, which lies somewhere in the middle Campanian in Australia and Antarctica (Helby et al., 1987; Pirrie and Riding, 1988; Marshall, 1990b; Young and Laurie, 1996; Pirrie et al., 1997). This event was identified in nine of the studied sections. An age corresponding to the mid-point of the stage is adopted herein: 77.5 Ma. 5. The LO of the dinoflagellate Canninginopsis bretonica, which is inferred to lie at the base of the Upper Campanian in Antarctica, Australia, and southern mid-latitudes (Marshall, 1990a; Crame et al., 1991; Riding et al., 1992; Pirrie et al., 1997; Williams et al., 2004). This event was identified in 11 of the studied sections. An age of 76 Ma is adopted herein. 6. The highest occurrence (HO) of the dinoflagellate genus Odontochitina, which is inferred to lie at the base of the Upper Maastrichtian in Australia, Antarctica, and the Southern Ocean (Helby et al., 1987; Pirrie and Riding, 1988; Riding et al., 1992; Young and Laurie, 1996; Mohr and Mao, 1997). This event was identified in 14 of the studied sections. An age of 69.5 Ma is adopted herein. 7. The LO of the dinoflagellate Trithyrodinium evittii, which is known to lie close to the precisely located Cretaceous-Paleocene boundary in New Zealand (Wilson, 1987; Strong et al., 1995; Willumsen, 2000; Cooper, 2004). This event is known from just one of the studied sections. Its placement, however, is well constrained by numerous associated events that define a major event cluster at the CretaceousCenozoic boundary (see the following).

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Figure 4. Log of the Ben More section. The figure comprises four parts: On the left is the measured section based on field data. Lithostratigraphic and graphic symbols used on the log are explained in Figure DR4 (see text footnote 1). On the right of the figure is the relevant part of the composite section derived from constrained optimization program (CONOP); “global” event clusters identified later in this paper are indicated here by black triangles against the composite scale. The two central parts of the figure show events of the CONOP composite projected into the measured section—shown both as an eventdepth plot and, to the right of that, as bundled composite event levels. Not all sampled horizons have associated events. For clarity, events that cluster at the upper- and lowermost samples—i.e., events that most probably lie outside the range of the section—have been omitted. Unconformities or condensed intervals marked in the central column are inferred from all available evidence—from field data, from significant local convergence and bundling of biostratigraphic events relative to the CONOP composite, and from “global” event clusters. Not all local event convergences are interpreted as unconformities. Instead they may mark intervals of low sedimentation rate, faults, or result simply from wide sample spacing relative to the spacing of events in the composite. Mst—mudstone; Sst— sandstone; Cgl—conglomerate.

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The correlation between the position of these seven points in the composite section and their inferred ages is high (Pearson’s product-moment correlation coefficient, r = −0.967), but there is still significant scatter in the data (Fig. 5). In part, this scatter results from the arbitrary placement of biostratigraphic range ends at substage boundaries that, for most cited studies, represent the finest practical units of chronostratigraphic resolution. Also, of course, scatter may result from true diachroneities in the timing of particular events between regions. With these considerations in mind, we regard point number 5, the LO of Canninginopsis bretonica, to be an outlier and exclude it subsequently from the construction of the age model. Based on the remaining six points, r = −0.990. In Figure 5, a straight line is fitted to these six data points. Because the last event, the LO of T. evittii, is considered to be a precise marker of the Cretaceous-Paleocene boundary, the regression is constrained to pass through this point. The regression line defines our best estimate of an age model for the composite section. In using a straight line, the model assumes that the spacing of events in the composite is indeed proportional to their spacing in time. From the available data, there is no reason to suspect a nonlinear relationship for the data set as a whole (but see following). Based on this age model, the 182 composite event levels yield an average relative temporal resolution of ~128 k.y. If one considers just the latest Coniacian to earliest Maastrichtian interval, then the average relative temporal resolution is 102 k.y. These figures refer just to the relative resolving power of the composite section; as discussed already, precision in absolute dating is limited by comparatively large uncertainties in our age model. Using this age model, Figure 6 shows the composite against the global geochronological time scale of Gradstein et al. (1995). Also shown are the New Zealand dinoflagellate zones and subzones of Wilson (1987), Schiøler and Wilson (1998), Roncaglia et al. (1999), and Cooper (2004). The older zonal boundary index events occur in their expected order in the composite sequence, and the zones can be identified unambiguously. In contrast, some of the younger zones cannot be identified unambiguously because index events are apparently out of order in the composite. This problem may reflect any of the factors that contribute to the correlation problem, discussed already. In essence, during the conventional process of creating a zonation, complex biostratigraphic data are filtered in a subjective but intelligent way. The CONOP composite, on the other hand, is an objective ordering that follows simple mechanical rules. For a data set of this size, however, there is no

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Figure 5. Construction of the age model used to calibrate the composite section. Numbered points shown are the selected dinoflagellate event datums described in the text; all other event levels in the composite section are shown as vertical lines above the x axis. Error bars on inferred ages are conservative and based on possible age limits discussed in the text. Error bars on the height in the composite section, based on the best-fit intervals, are all negligible (i.e., 0 or smaller than the plotted symbols). Point 5, representing the lowest occurrence of Canninginopsis bretonica, is regarded as an outlier and is not used in the construction of the age model. The correlation coefficient, r, for the remaining six points is −0.990. The linear regression is constrained to go through the youngest point (point 7, LO of Trithyrodinium evittii). The ages of all other event levels are determined by interpolation through the regression line. The equation of this line is: y = −0.286x + 91.633.

single, unique best composite, but a range of equally best-fit solutions. There is, therefore, a stochastic element to the final CONOP composite sequence. For these reasons, it is unsurprising that there is some disagreement between event orders inferred during conventional zonation and those inferred using CONOP, as noted previously by Sadler and Cooper (2004). Because of this problem, in Figure 6 the bases of the Isabelidinium korojonense and I. pellucidum zones are placed at the lowest co-occurrences of three key or characteristic taxa identified in Roncaglia et al. (1999). Using the same convention, it is not possible to separate the overlying Alterbidinium acutulum and Manumiella druggii zones;

resolution of this problem is beyond the scope of the present paper. Identification of “Global” Event Clusters As noted previously, without independent age control, CONOP cannot resolve “global” changes in depositional rate that affect all sections in a sample. Thus, for example, unconformities that are present in all sections will not be resolved in the individual sections. We would expect, however, that given relatively uniform event-level spacing in time, “global” unconformities would be marked by event clusters in the composite section—the placement of


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Figure 6. Inferred ages of event levels in the composite section, as derived from Figure 5, and New Zealand dinoflagellate zonal boundaries. Zone boundaries shown with a dashed line are those located using the lowest occurrences of three key or characteristic taxa (see text for further explanation). On the right are summary plots of the sections studied here; boxes indicate time that is represented in the sections, vertical lines mark time that is missing at unconformities. Black fill indicates mudstone-dominated strata; stippled fill marks intervals containing significant sandstone. Wavy lines denote unconformities that were recorded in the field (see supplementary material [see text footnote 1] for detailed section logs). Horizontal gray lines represent the positions of significant event clusters in the composite section (see Figs. 7–8).

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Quantitative biostratigraphy and Cretaceous eustasy anomalously high numbers of apparently coeval events at a single composite event level. In addition, however, such clusters are also expected at intervals of anomalously high biotic turnover, either real or apparent (the latter resulting from monographic and/or taxonomic artifacts at key stratigraphic boundaries). Examination of Figure 7A reveals that there are, indeed, conspicuous event clusters in the composite. When interpreting this plot, however, it is necessary to account for event-level spacing in the composite—spacing that is determined by the spacing of sampled levels in the original sections (see Methods section). Clearly, if two event levels are widely spaced in the composite, one would expect that, on average, more events would be assigned to one or both of these levels than to closely spaced levels. Here, we have standardized for event-level spacing in two ways. First, we calculated the adjusted event clusters, E, as the number of events at a level divided by the average spacing between this level and those above and below (Fig. 7B):

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Where el is the number of events at event-level l, and hl + 1 and hl – 1 are the heights of the adjacent event levels above and below (in percentage composite units). Secondly, we fitted a smooth curve—a sixth-order polynomial—to the cumulative distribution of events against time (Fig. 7E); the local slope of this curve represents the expected average accumulation rate of events at that point in time. From this, we calculated differences between the expected number of events at each level in the composite and the observed number of events; these differences are plotted in Figure 7C. Examination of Figures 7A–7C reveals that all the major event clusters are identified in all three plots, although the relative magnitudes of peaks vary somewhat. This correspondence suggests that the event clusters are more than just artifacts of event-level spacing in the composite. On Figure 7D, adjusted event clusters (E) are plotted in rank order on semilog axes. (Henceforth, we ignore the events below the 10% level and above 90% in the composite that may be, in part at least, edge effects or artifacts—see discussion of unreliable or poorly constrained events, and discussion of the Cretaceous-Paleocene boundary, below.) Whereas much of the ranked event-cluster distribution is log-linear, the curve below rank ≈36 is very markedly non-log-linear. This suggests that adjusted event clusters larger than E ≈10 may be qualitatively and genetically different from those smaller than

10. Thus, for the purposes of this discussion, we have adopted a value of E = 10 as the threshold between “significant” event clusters and “background” event densities. This threshold is marked on Figure 7B as a dashed line, and event clusters that exceed this threshold are indicated with arrows. These event clusters are interpreted in the next section. The largest event cluster shown on Figure 7A, 24 events at 93% in the composite section, requires special mention. According to our age model, this cluster corresponds to the Cretaceous-Paleocene boundary. It is likely to reflect four underlying causes. First, the CretaceousPaleocene boundary could mark an interval of truly enhanced microfloral turnover, although globally there is no evidence for a major turnover of dinoflagellates at this boundary (Galeotti et al., 2004). Secondly, apparent turnover may be exaggerated by monographic effects inasmuch as many studies have tended to extend up to, but not across, the boundary (e.g., Roncaglia et al., 1999; but see Willumsen, 2000). Thirdly, the Cretaceous-Paleocene boundary is known to correspond to an unconformity in many or most New Zealand sections (Hollis, 2003). Finally, event levels in the composite are relatively widely spaced around the CretaceousPaleocene boundary, and, thus, for the reasons outlined above, the size of the cluster is likely to be exaggerated (compare Figs. 7A and 7B). INTERPRETATION AND DISCUSSION The 15 major adjusted event clusters shown on Figures 6 and 8, we believe, most likely represent regional unconformities or condensed horizons that are present in all 15 of the studied sections. If this is correct, then their presence will affect the age model used here. In essence, regional unconformities will introduce nonlinearities into the simple, linear age model of Figure 5. Using the simple age model, events between each of the unconformities will be widely separated compared to their true spacing in time (Fig. 9). Discrepancies between apparent and true ages will vary in magnitude depending on the position of the event relative to the unconformities, the duration of the unconformities, their frequency and spacing in time, and the distribution of dated events used to calibrate the model. In particular, errors in the age calibration of individual events will be greatest close to the regional unconformities and smallest midway between the unconformities. In the absence of many more numerous and precise age-control datums, we are unable to recalibrate our age model to account for the presence of regional unconformities. Our age model remains, however, the best “average” model available to us.

Figure 8 shows the durations of hiatuses identified on the New Jersey coastal plain by Miller et al. (2003, 2004) and Van Sickel et al. (2004) that are inferred to mark eustatic falls. Using the age model developed here, 10 out of the 15 major event clusters fall within the durations of the New Jersey hiatuses (Fig. 8). One can estimate the probability of this correspondence occurring by chance alone by using the standard binomial probability equation:

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where n is the number of trials, r is the number of successes, and p is the probability of a single success. The probability of a single success can be approximated by calculating the proportion of total age-calibrated composite event levels that lie within the age range of the hiatuses. In our case, n = 15, r = 10, p = 85⁄175 = 0.486, and P = 0.079, or ~8%. In other words, the probability that 10 of our 15 major clusters would lie within the time spans of the New Jersey hiatuses due to chance alone is ~8%. Also shown for reference on Figure 8 are the sequence boundaries identified by the Exxon Production Research team (EPR; Haq et al., 1987), as recalibrated to the time scale of Gradstein et al. (1995) by Miller et al. (2003). Miller et al. (2003) discussed correlations between their New Jersey hiatuses and the EPR sequence boundaries. In the present paper, we are concerned primarily with the relationships of our event clusters to the explicitly age-calibrated New Jersey hiatuses; the EPR sequence boundaries are not discussed here. Taken at face value, these results suggest that we can identify seven out of the eight Santonian to Maastrichtian hiatuses described by Miller et al. (2003, 2004) in the New Jersey coastal plain. We cannot exclude the possibility that this correspondence has arisen by chance alone, although the probability of this is small (~8%). The only New Jersey hiatus that is not observed in New Zealand defines the base of the Englishtown composite sequence (Fig. 8) and is in fact relatively poorly dated (K. Miller, December 2005, personal commun.). In addition, we can resolve other significant event clusters and inferred unconformities in the New Zealand sections that have not been observed in the New Jersey succession, at ca. 68.5 Ma, 72.1 Ma, 76.2 Ma, 78.2 Ma, and 78.8 Ma. Based on our preferred age model, therefore, we suggest that apparent unconformities resolved in New Zealand are approximately coeval with sequence boundaries identified in the Northern Hemisphere. This conclusion lends considerable weight to


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Quantitative biostratigraphy and Cretaceous eustasy the suggestion that these sequence boundaries reflect eustatic changes in sea level. Given the uncertainties in our age model, we do not consider this to be the last word on the subject. In particular, the correspondence between our event clusters and the New Jersey hiatuses is sensitive to the position of the line of correlation shown on Figure 5. To test the most conservative scenario, we used a Monte Carlo approach to determine the distribution of matches between our event clusters and the New Jersey hiatuses, based on the uncertainty limits for the age-calibration points shown on Figure 5 and assuming uniform probability distributions within these limits. From 1000 Monte Carlo trials, we found that the average number of matches—6.8—is statistically indistinguishable from the random expectation (based on the relative durations of hiatus to nonhiatus in the New Jersey succession). This test represents the worst-case scenario—the uncertainty limits in the age model are highly conservative, the assumption of uniform distributions is unrealistic for at least some of the calibration points, and the regression lines of the Monte Carlo trials were not constrained to pass through point 7 at the Cretaceous-Paleocene boundary. This test serves, however, to highlight the difficulties inherent in long-distance biocorrelation, difficulties that will only be overcome by the refinement of our age model and incorporation of additional, age-calibrated data points. From palynofacies analysis of four of the sections used herein, Schiøler et al. (2002) inferred that sea-level cycles in the East Coast basin showed a poor correlation with the EPR cycle chart. As noted already, in the present study, we focused on the well-constrained hiatus intervals identified from the New Jersey coastal plain; however, we agree with Schiøler et al. that Late Cretaceous unconformities in eastern New Zealand appear not to correlate closely with the EPR sequence boundaries. Correlations between the New Jersey hiatuses and the EPR sequences are discussed in Miller et al. (2003).

Despite the different approaches, there is substantial congruence between apparent sealevel signatures detected here using high-resolution quantitative biostratigraphy and those inferred using palynofacies analysis (Schiøler et al., 2002). Although detailed interpretation of all sections will be undertaken elsewhere, here we use the example of the Ben More section (Fig. 4) to compare results from the present study with evidence from field data and results from Schiøler et al. (2002). 1. A possible bundling of composite events at 30 m in the section does not correspond to any recognized lithological or palynofacies signature of condensation. This bundling, however, lies immediately below a 5 m interval of no exposure and a gap in sampling, and may be nothing more than an artifact of sample spacing. 2. Sequence boundary 1 of Schiøler et al. (2002), at 45 m, was not detected in the CONOP composite section and, again, corresponds to a gap in exposure. 3. A pronounced bundling of composite events occurs at 82 m. Within sample spacing uncertainty, this corresponds to both a conspicuous interval of red and greenish sandstone interbeds and sequence boundary 2 of Schiøler et al. (2002). 4. Maximum flooding surface 2 of Schiøler et al. (2002), at ~115 m, is not detected in the composite section, but is placed at a shell bed of disarticulated and fragmented bivalves. 5. An event cluster occurs at 135 m. This level was not distinguished by Schiøler et al. (2002), but corresponds to a conspicuous shell bed of disarticulated and fragmented bivalves and a gradational increase in mudstone content upsection. It is possible that this level represents the maximum flooding surface 2 of Schiøler et al. (2002). 6. Two event clusters are included within an event bundle at 150 m in the section. Although not distinguished by Schiøler et al. (2002), this level corresponds to an abrupt increase in sandstone proportion and loss of siltstone interbeds.

7. A relatively minor, but almost certainly significant, bundling of composite events occurs at the Paton-Herring Formation contact, at 168.5 m. Schiøler et al. (2002) placed their sequence boundary 3 at this level, and noted that this represents a relatively short hiatus in deposition. 8. A minor bundling of composite events, which includes one event cluster, occurs at 179 m. This level was not distinguished by Schiøler et al. (2002) and is marked by only a small lithological change, namely the loss of minor, centimeter-bedded, glauconic, fine sandstone. 9. Maximum flooding surface 3 of Schiøler et al. (2002) was placed tentatively at 208 m. This level probably corresponds to an event cluster identified herein. 10. Sequence boundary 4 of Schiøler et al. (2002), at 229 m, corresponds to a major bundling of composite events, including two event clusters. From these results it is clear that three of the four sequence boundaries recognized in the Ben More section by Schiøler et al. (2002), using palynofacies analysis, were detected here using quantitative biostratigraphic analysis. Sequence boundary 1 of Schiøler et al. is not identified using the CONOP composite section, possibly a consequence of relatively poor resolution and wide spacing of events in the lower part of the composite. Finally, it is interesting to note just how little time is actually represented by rock in the sections examined here (Fig. 6). At the scale of the study, on average just 24% of time is recorded across all the sections (maximum 47%, minimum 14%). These values will be overestimates for two reasons. First, because there is a positive relationship between the total range of any section and its apparent stratigraphic completeness, the measured levels of completeness would decrease at finer scales of resolution (e.g., Sadler, 1981). Secondly, our estimates of completeness do not take into account the regional

Figure 7. Clustering of events in the composite section. (A) Plot of number of events clustered at discrete levels in the composite section against inferred age and position in the composite. (B) Adjusted event clusters, E: event clusters from A are scaled by the average spacing between the event level in question and levels immediately above and below (see Equation 1). Arrows to the right of the plot indicate values of E that exceed the threshold of 10 (see explanation in D). In some cases, pairs of closely spaced maxima in E are regarded as a single significant peak (indicated by brackets next to the arrows). (C) Differences between the expected numbers of events at each level, based on a sixth-order polynomial fit to the cumulative distribution of events against time (shown in E), and the observed numbers of events. (D) Rankorder distribution of adjusted event clusters, E (shown in B, arranged from largest to smallest) plotted on semilog axes (event levels below 10% and above 90% in the composite section are ignored). Much of this distribution is log-linear, as indicated by the thick gray line. The extremes of the distribution deviate from log-linearity—there are more large event clusters than predicted by the log-linear relationship, whereas the tail of small clusters is truncated. We interpret clusters larger than E ≈10 (rank 36) as “significant” (see text). This threshold is indicated on B with a dashed line. (E) Cumulative distribution of events against time and sixth-order polynomial curved fitted to these data. Differences between the expected number of events at each level, based on this curve, and the observed number are shown in C.


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unconformities identified by the event clusters. Our results are comparable with other studies that have determined levels of completeness in continental-margin marine strata ranging from ~20% to 50% at similar scales of study (e.g., Barrell, 1917; Kamp and Turner, 1990; Callomon, 1995). CONCLUSIONS Distinguishing tectonic from supposedly eustatic Upper Cretaceous stratigraphic sequences is problematic and contentious. A key

988

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70

Figure 8. Adjusted event clusters from Figure 7B and sequence stratigraphic interpretations from Miller et al. (2003, 2004). The thick horizontal gray bars correspond to the ages of hiatuses in the New Jersey coastal plain succession that were identified by Miller et al. (2003, 2004). “EPR sequences” are the Exxon Production Research sequence boundaries from Haq et al. (1987) as recalibrated to the Gradstein et al. (1995) time scale by Miller et al. (2003, 2004). The EPR sequence boundaries are placed at the inflexion points of the EPR sea-level curve as presented in Figure 1 of Miller et al. (2003). The major event clusters identified herein are explained in Figure 7.

question remains unresolved: were there highfrequency, eustatic fluctuations during the Late Cretaceous, and, if so, what was their cause? In order to answer these questions, it is necessary first to demonstrate that Upper Cretaceous sequence boundaries are synchronous across the globe. Given that the frequency of inferred sequences is at or below the finest resolution of most standard biostratigraphic subdivisions, demonstration of synchroneity is extremely difficult. This problem is exacerbated when considering stratigraphic successions in New Zealand, which are structurally and/or stratigraphically

0

complex and remote from well-studied Northern Hemisphere localities. In order to address this problem, we used a new quantitative biostratigraphic method to derive a comparatively very high-resolution correlation for 15 onshore sections, spanning the Coniacian to Maastrichtian stages in eastern New Zealand. The method, constrained optimization (program CONOP), can be thought of as automated multidimensional graphic correlation. Our analysis was based on 398 wellconstrained lowest- and highest-occurrence bioevent datums derived from 245 dinoflagellate


Section missing at unconformities

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species. These data yielded a composite section with 182 discrete event levels that can be correlated between sections. The age of the composite was calibrated using an age model based on six dated bioevents, two of which were tied to geochemical or paleomagnetic datums. Following age calibration, the 182 composite event levels yielded an average relative temporal resolution of 128 k.y. through the entire Coniacian to Maastrichtian and just over 100 k.y. through the latest Coniacian to earliest Maastrichtian; these figures do not reflect precision in absolute dating, which is comparatively poor due to uncertainties in our age model. CONOP cannot resolve unconformities or condensed intervals that occur across all studied sections. Here we argue, however, that such “global” features can be recognized by the placement of multiple events at a single composite level. Before assigning significance to such event clusters, it is first necessary to account for spurious effects related to variable spacing of event levels in the composite. This was done here in two ways: by dividing the number of events by the average distance between adjacent levels, and by calculating the difference between the observed and expected number of events at any level, the expected number being estimated using a polynomial fit. Following adjustment for event-level spacing, we identified 15 major event clusters in Coniacian to Maastrichtian strata of eastern New Zealand. Of these, 10 coincide closely with well-dated hiatuses recorded in Upper Cretaceous sequences of the New Jersey coastal plain by Miller et al. (2003, 2004). The probability of this coincidence arising by chance alone is ~8%. We conclude that, at a resolution of less than ~±130 k.y., 10 New Zealand Coniacian to Maastrichtian unconformities or condensed intervals are likely to be coeval with hiatuses identified from the New Jersey coastal plain. Although these results must be regarded as provisional, they suggest that high-resolution quantitative stratigraphy can provide a potent tool for the identification and correlation of stratigraphic sequences. Furthermore, our findings add significant support for recent studies that have argued for the presence of Late Cretaceous eustatic changes. Finally, our results support other high-resolution studies that have demonstrated that the stratigraphic record of continental-margin marine strata is substantially incomplete, with typically ~20% to 50% of time represented by rock when observed at the scale of ~1 to ~25 m.y. Given the scale-dependence of completeness estimates, it is clear that far more time is missing in most continental-margin geological records than is present.

t

Quantitative biostratigraphy and Cretaceous eustasy

Composite section Figure 9. Age calibration of a hypothetical composite section using a simple linear age model (thick gray line, model 1) and a “true” age model that takes account of global unconformities (thin black line, model 2) (compare with Fig. 5). Dotted arrows illustrate the way in which events in the composite are age calibrated by projecting through the age model line onto the y axis.

ACKNOWLEDGMENTS

Crampton acknowledges funding from the Foundation for Research, Science and Technology program entitled “Towards self sufficiency: the geological basis for increasing New Zealand’s petroleum reserves” (contract C05X0302). Schiøler acknowledges a research grant from the Carlsberg Foundation, Denmark. Roncaglia acknowledges funding from the Ministry of University, Scientific Research and Technology, Italy. For assistance in the field and discussion, we would like to thank Peter King. We are grateful to landowners for access to the measured section localities. Craig Jones helped with data preparation; palynological samples were processed by Roger Tremain. For extensive and helpful discussions, and for reviewing earlier drafts of this paper, we gratefully acknowledge Ken Miller, Peter Sadler, and Roger Cooper. For useful discussions, we also acknowledge Charles Mitchell and Raphael Benites. We thank Peter Sadler for his ongoing development of CONOP and his generosity in making this program freely available. This is Institute of Geological & Nuclear Sciences contribution no. 3287. REFERENCES CITED Abreu, V.S., Hardenbol, J., Haddad, G.A., Baum, G.R., Droxler, A.W., and Vail, P.R., 1998, Oxygen isotope synthesis: A Cretaceous ice-house?, in Graciansky, P.-C.d., Hardenbol, J., Jacquin, T., and Vail, P.R., eds., Mesozoic and Cenozoic sequence stratigraphy of European basins: SEPM (Society for Sedimentary Geology) Special Publication 60, p. 75–80. Agterberg, F.P., 1990, Automated stratigraphic correlation: Amsterdam, Elsevier, Developments in Palaeontology and Stratigraphy, v. 13, 424 p. Ballance, P.F., 1993, The paleo-Pacific, post-subduction, passive margin thermal relaxation sequence (Late Creta-

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