El Niño in the Eocene Greenhouse Recorded by Fossil Bivalves and Wood from
Antarctica
Linda C. Ivany, Thomas Brey, Matthew Huber, Devin P. Buick, Bernd Schöne
Auxiliary Material (AM)
Geologic and Paleoenvironmental Setting
Seymour Island is located roughly 100 km east of the Antarctic Peninsula near
its northern end (Fig. S1). Specimens used in this analysis were collected from the
Eocene La Meseta Formation, a shallow marine succession comprised of sandstones,
mudstones, and shell beds [MTM, Elliot and Trautman, 1982; S. A. Marenssi et al.,
1998; S.A. Marenssi et al., 2002; Porebski, 1995; 2000; Sadler, 1988] that
accumulated in a fault-bounded basin. The formation has been divided into seven
members termed TELMs [Tertiary Eocene La Meseta, Sadler, 1988], with Telm 1
being the oldest; samples used in this analysis come from Telm 5. Internal
architecture is complex, with stacked and interfingering sediment lenses and
occasional slumps of variable thickness. Different authors have variously stressed
estuarine, deltaic, and channel or valley fill interpretations for the depositional setting
of different parts of the La Meseta Formation [Elliot and Trautman, 1982; S. A.
Marenssi et al., 1998; S.A. Marenssi et al., 2002; Porebski, 1995; 2000; Sadler, 1988;
Stilwell and Zinsmeister, 1992; L S Wiedman and Feldmann, 1988], though stable
oxygen and strontium isotope analyses of included shell material suggest limited if
any freshwater influx [Dutton et al., 2002; Ivany et al., 2008] and the diverse
invertebrate fauna preserved within the unit [Baumiller and Gazdzicki, 1996; D B
Blake and Zinsmeister, 1988; D D Blake and Aronson, 1998; Filkorn, 1994;
McKinney et al., 1988; Stilwell and Zinsmeister, 1992; L A Wiedman et al., 1988]
suggests accumulation under relatively normal marine conditions.
Age control within the La Meseta Formation has been based primarily on
biostratigraphy and suggests that deposition spanned much of the Eocene [e.g., Wrenn
and Hart, 1988, many others]. Strontium isotope stratigraphy has recently offered
new constraints on the age of sediments within the unit, and suggests that Telm 5 is
early Eocene to earliest middle Eocene in age [Ivany et al., 2008]. As such, fossils
recovered from this interval come from organisms that experienced some of the
warmest conditions on the planet during the Cenozoic. Paleontological studies
suggest cool- to warm-temperate conditions at this time even in Antarctica [Askin,
1997; Askin and Fleming, 1982; Case, 1988; Doktor et al., 1996; Francis and Poole,
2002; Stilwell and Zinsmeister, 1992; L A Wiedman et al., 1988], a conclusion
supported by oxygen isotope paleothermometry [Ditchfield et al., 1994; Dutton et al.,
2002; Gazdzicki et al., 1992; Ivany et al., 2008; Pirrie et al., 1998]. Stable isotope
data from Telm 5 bivalves Cucullaea raea (Arcoida) and Eurhomalea antarctica
(Veneroida), the shells of some of which are used in this study, suggest temperatures
of around 15°C at the time of deposition [Dutton et al., 2002; Ivany et al., 2008].
Detailed Methodology.
Fossil bivalve shell preparation and growth increment reading
Shells of Cuculaea raea and of Eurhomalea antarctica from TELM 5 were
sectioned through the umbo along the maximum growth axis and polished to reveal
internal growth increments (Fig. 2). We measured the distances between consecutive
pairs of dark bands, moving around the outer margin of the shell from umbo to
commissure until bands were too compressed to be resolved. In the present analysis,
we include only data from shells that span a minimum of 55 consecutive years.
Tree-disk preparation and growth increment reading
Sections of trees that entered the marine shelf environment as driftwood were
recovered from the same unit in which the bivalves were collected. Most were
colonized by boring bivalves (‘shipworms’) that left traces known as Teredolites in
the fossilized wood (Fig. S6A). Annual growth increments are evident in the wood,
and one section preserved a record long enough to be considered in this analysis. The
fossil log was cut across its diameter, polished to reveal growth bands, photographed,
and the digital images enhanced so as to make growth increments more apparent. No
single trajectory across all growth increments was preserved well enough to measure
inter-annual distances consecutively, so three overlapping trajectories were identified
and measured using ScionImage software. We adjusted increment widths of the inner
and outer series to the middle series by the average ratio of overlapping increments
thus obtaining a combined series of 157 annual growth increments (Fig. S6B).
Computation of standardized growth index time series
Bivalves: The five shells with the longest growth increment records were
selected for further analysis, i.e. four C. raea (58, 72, 79, and 82 yr) and one E.
antarctica (76 yr). We removed the ontogenetic trend of decreasing increment size
([see Buick and Ivany, 2004]) by means of standard individual-based detrending as
developed in dendrochronology ([e.g., Cook and Kairiukstis, 1990]) and used in a
number of mollusc studies ([e.g., Schöne et al., 2003]). For each individual, a cubic
spline was fitted to the series of measured growth increments Mi (i = 1, 2, … n;
software JMP 7 by SAS Institute
expected increments Ei,. Growth indices GIi were computed by
GIi = Mi / Ei
and standardized growth indices by
SGIi = (GIi - mean of all GIi) / S.D. of all GIi (see Fig. S2)
Tree cross section: The growth increment time series was detrended by cubic
spline interpolation (smoothing parameter λ = 10000) as described above.
Subsequently, significant autocorrelation was removed by means of a 1st order
AutoRegressive Integrated Moving Average (ARIMA) model (Fig. S7).
Spectral analysis of SGI time series
Bivalves: A variogram, i.e. a plot of the variance of the differences of SGI
values versus the time lag between these values, served as a first check for SGI
oscillation patterns (Fig. S3). We analysed each SGI time series by a two-step
procedure using the software package kSpectra by SpectraWorks Inc. In the first step
we applied Singular Spectrum Analysis [SSA; settings: window length 15, covariance
estimation by Vautard & Ghil [Vautard and Ghil, 1989] approach, Monte Carlo
significance test] to reduce the noise level in the time series [Vautard and Ghil, 1989].
Ranked by variance explained, the first eight SSA components (singular values)
captured more than 65% of total variance in each SGI time series. These eight
components were used to reconstruct a “filtered” SGI time series. In the second step,
the reconstructed SGI time series was subjected to the nonparametric Multi-Taper
method (MTM; settings: significance = “red noise”, 3 tapers, adaptive procedure,
robust background noise) of spectral analysis that is a common tool in geophysics,
oceanography, climatology, and geochemistry [e.g., Mann and Lees, 1996]. Within
the frequency range zero to 0.5, spectral density is computed for 512 equally spaced
frequencies. See Ghil et al. [2000] for more detailed information on SSA and MTM
(Fig S4). The resulting matrix of 512 frequencies x 5 individuals is subjected to
Principal Component Analysis (on the covariance matrix) and an average composite
frequency series is computed from the first three principal components. In order to
verify the MTM spectrum, we constructed a second composite spectrogram from the
simple Fourier Series of the five SGI time series (Fig. S5). This spectrogram should
resemble the most distinct peaks of the MTM spectrum in order to confirm the latter.
Tree cross section: The tree chronology was treated as the bivalve data, except
with slightly different SSA settings (window length 30) and the construction of the
“filtered” SGI time series from the first 20 SSA components (singular values) that
captured 78% of total variance (Fig. S7).
Correlation of environmental factors with fossil bivalve growth.
High-resolution stable oxygen and carbon isotope data collected across 17
years of growth in the fossil bivalve Cucullaea provide insight into the environmental
variables that correlate with thicker or thinner growth bands. Measured increment
widths for the 17 years of isotope data [Buick and Ivany, 2004] were detrended, and
deviations each compared to the mean 18O and 13C values for the corresponding
year, as well as seasonal extremes for each year (Fig. S8). Thinner growth increments
exhibit a range of oxygen isotope values, but all thick increments correspond to lower
18O values and hence warmer temperatures. This suggests that, while poor annual
growth might be due to a variety of factors, robust growth only happens during
warmer years on average. Increment thickness shows a weak positive relationship
with carbon isotope values (p=.03), suggesting a connection with primary production
on the shelf. These relationships are complicated by the general pattern by which
Cucullaea grows, with more shell accretion in the cold months than in the warm
months. ‘Summertime’ isotope values represent a truncated or time-averaged meaure
of warm month means, and underestimate actual values. Most of the variation in
increment width is associated with accretion during the winter (see light growth bands
in Fig. 2), thus it appears that more metabolic energy can be devoted to precipitation
of shell material following warmer, more productive summers.
Coupled climate model.
The simulations analyzed for this study included long, fully coupled, Eocene
Community Climate System Model version 3 (CCSM3) runs which were carried out
with CO2 mixing ratios of 1120 and 2240 ppmv and they have been described in
Hollis et al. [2009] and Liu et al. [2009]. Both simulations produce similar
teleconnection patterns, and both are similar to the Eocene CSM version 1.4 results
presented in Huber and Caballero [2003]. We focus here on the results of the
simulation with 2240 ppmv CO2 because that simulation produces SSTs in the
Seymour Island region that match the Early Eocene SST proxy records of Ivany et al.
[2008]. We present a time series correlation analysis and spectral analysis of the last
360 years of a 3000 year long, coupled, equilibrated Eocene simulation at 2240 ppmv
CO2. Analysis of annual and monthly-mean timeseries reveals robust teleconnections,
which are maximized in July. In Figure 4 we show the global correlation between
SST variations in the Eocene Quasi-Nino Index region of Huber and Caballero
[2003], the mean SST from 5°N to 5°S and 190° to 240° Longitude. Seymour Island
SST variability in July has a correlation of 0.20 with EQNI variability. As revealed
by analyzing the spectral coherence of the two modeled timeseries, variability on time
scales of ~2, 4, and 6 years is coherent (0.2, 0.2, and 0.4, respectively).
Supplementary Figures.
Figure S1. Geologic map of TELMs 1 through 7 of the La Meseta Formation,
exposed on the NE half of Seymour Island (Isla Marambio), Antarctica [modified
from Ivany et al., 2008; based on Sadler, 1988]. Age of TELM 5 sediments from
which the samples come is about 50 MA [Ivany et al., 2008].
Figure S2. Standardized Growth Index (SGI) time series derived from the five shells.
Pink dots indicate increments unmeasurable owing to obscured growth bands.
Figure S3. Variograms of the Standardized Growth Index (SGI) time series of the
five shells in Fig. S2. The variogram measures the variance of the differences between
two points with time lag k years and compares it to that for points one year apart. It is
computed from the autocorrelation as Vk = 1 – rk+1 / 1- r1
Figure S4. Relative spectral density (adjusted to the range 0 - 1) of the five bivalve
SGI time series as computed by the Multi Taper Method [MTM, Ghil et al., 2000].
Red line indicates “red noise” 95% significance level.
Figure S5. Mean Variogram, Fourier series (composite of first three PCA
components of individual Fourier series) and spectral density plot (composite of first
three PCA components of MTM based frequencies) of the five bivalve SGI time
series. Error bars represent one standard error.
Figure S6. A) Section of tree recovered from TELM 5 of the La Meseta Formation.
Cement- and sediment-filled voids are borings (Teredolites) made by bivalves
(‘shipworms’) during the time the wood was floating in the sea as driftwood. Red
lines mark the positions of growth increments along trajectories 1, 2, and 3. B)
Corresponding composite time series.
Figure S7. Standardized Growth Index time series derived from tree cross section
measurements (upper plot) and corresponding time series analysis (lower plots). Red
line indicates “red noise” 95% significance level.
Figure S8. Relationship between detrended growth increment width of Cucullaea
and (A) annual average 18O and (B) summer average 13C. Shaded envelope in part
A illustrates the tendency for thick growth increments to only be produced during
warm (low 18O) years, while thinner increments can be characteristic of a range of
temperature conditions. Trendline and reported r2 and p-value in part B exclude a
single outlier (unfilled circle).
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