The CO2 liberated along subduction zones through
intrusive/extrusive magmatic activity and the resulting active and diffuse
outgassing influences global atmospheric CO2. However, when melts
derived from subduction zones intersect buried carbonate platforms,
decarbonation reactions may cause the contribution to atmospheric
CO2 to be far greater than segments of the active margin that lacks
buried carbon-rich rocks and carbonate platforms. This study investigates the
contribution of carbonate-intersecting subduction zones (CISZs) to
palaeo-atmospheric CO2 levels over the past 410 million years by
integrating a plate motion and plate boundary evolution model with carbonate
platform development through time. Our model of carbonate platform
development has the potential to capture a broader range of degassing
mechanisms than approaches that only account for continental arcs.
Continuous and cross-wavelet analyses as well as wavelet coherence are used
to evaluate trends between the evolving lengths of carbonate-intersecting
subduction zones, non-carbonate-intersecting subduction zones and global
subduction zones, and are examined for periodic, linked behaviour with the
proxy CO2 record between 410 Ma and the present. Wavelet analysis
reveals significant linked periodic behaviour between 60 and 40 Ma, when CISZ
lengths are relatively high and are correlated with peaks in
palaeo-atmospheric CO2, characterised by a 32–48 Myr periodicity and a
∼ 8–12 Myr lag of CO2 peaks following CISZ length peaks.
The linked behaviour suggests that the relative abundance of CISZs played a
role in affecting global climate during the Palaeogene. In the 200–100 Ma
period, peaks in CISZ lengths align with peaks in palaeo-atmospheric
CO2, but CISZ lengths alone cannot be determined as the cause of a
warmer Cretaceous–Jurassic climate. Nevertheless, across the majority of the
Phanerozoic, feedback mechanisms between the geosphere, atmosphere and
biosphere likely played dominant roles in modulating climate. Our modelled
subduction zone lengths and carbonate-intersecting subduction zone lengths
approximate magmatic activity through time, and can be used as input into
fully coupled models of CO2 flux between deep and shallow carbon
reservoirs.
Introduction
The current paradigm of the deep carbon cycle (i.e. the planetary cycling of
carbon over million-year timescales) attributes fluctuations in the
atmospheric carbon dioxide (CO2) to the realm of tectonic forces,
where subduction-related emissions (van der Meer et al., 2014; Kerrick, 2001)
and metamorphic decarbonation (Lee et al., 2013) are major CO2
sources, and the processes of silicate weathering (Sundquist, 1991; Kent and
Muttoni, 2008), seafloor weathering (Brady and Gíslason, 1997;
Krissansen-Totton and Catling, 2017) and marine organic carbon burial (Berner
and Caldeira, 1997; Ridgwell and Zeebe, 2005) are major sinks removing
CO2 from the atmosphere. Subduction plays a critical role in this
cycle. In a dynamic interplay, oceanic lithosphere is consumed at subduction
zones, removing carbon bound in pelagic carbonate seafloor sediments from the
exogenic carbon cycle. Simultaneously, CO2 is emitted through
diffuse outgassing and arc volcanism along subduction zones (Keleman and
Manning, 2015). Recent studies have found support for links between periods
of increased global arc activity and warmer global climates using detrital
zircon ages, modelling and experimental techniques, particularly as drivers
of greenhouse conditions in the Cambrian (McKenzie et al., 2016; Cao et al.,
2017), Jurassic–Cretaceous (McKenzie et al., 2016) and early Palaeogene (Lee
et al., 2013; Carter and Dasgupta, 2015; Cao et al., 2017). Moreover, it has
been postulated that the relationship between arc activity and climate is
periodic, relating to ∼ 50 Myr global flare-ups along extended
segments of arcs (Lee and Lackey, 2015) as well as continent assembly and
dispersal which cause transitions from intraoceanic-arc- to
continental-arc-dominated states (Lenardic et al., 2011; Lee et al., 2013).
However, it is difficult to test this hypothesis, especially due to poor
preservation of ancient intra-oceanic arc rocks (Berner, 2004).
Recently, carbon and helium isotope analysis from modern volcanic arc gas has
provided evidence that volcanic arcs that assimilate crustal carbonate in
their magmas through decarbonation reactions have a greater atmospheric
CO2 contribution than other types of arcs (Mason et al., 2017).
Modern crustal carbonate reservoirs are a result of global organic and
inorganic carbonate production throughout the Phanerozoic, which has
contributed to the build-up of expansive, shallow-water carbonate sequences
including ramps and rimmed shelves along continental margins, hereafter
referred to as “carbonate platforms” (Kiessling et al., 2003). At different
points in Earth's history, active (from extrusive volcanism) and passive
(from intrusive magmatism) emissions from arcs along carbonate-intersecting
subduction zones (CISZs) may have dominated global carbon flux from all
subduction zones, such as during the Cretaceous (144–65 Ma) when
continental arcs are hypothesised to have been longer than modern-day lengths
and when a greenhouse climate prevailed (Lee et al., 2013; van der Meer et
al., 2014; Cao et al., 2017). We investigate this hypothesis using wavelet
analysis, which attempts to detect correlations and periodicities in two time
series, namely climate proxy data and subduction zone lengths, at any scale
or duration (Grinsted et al., 2004).
Specifically, we apply cross-wavelet analysis and wavelet coherence to
investigate whether the CO2 flux from carbonate-intersecting subduction
zones has been significantly different than the flux from the remainder of
subduction zones that do not intersect with buried carbonate reservoirs
(non-CISZ) in influencing global palaeo-atmospheric CO2 concentrations
since the Devonian (410 Ma). We define CISZ CO2 flux as the sum of
active volcanism and passive outgassing along arcs that develop at
subduction zones which intersect buried carbonate platforms in the
overriding lithosphere. Non-CISZ CO2 flux includes all volcanic
CO2 emissions from all subduction zones that exist where subduction
zones are not intersecting carbonate platforms (Fig. 1a).
A study by Cao et al. (2017) also endeavoured to apply regional geology in
combination with palaeogeographic maps to explore the distribution of
continental arcs through space and time in a plate tectonic framework.
However, Cao et al. (2017) show conservative estimates of continental arc
lengths, and may underestimate the lengths and duration of some arcs. The
approach we propose measures subduction zone lengths as opposed to arc
lengths, and therefore may capture some carbonate-intersecting arcs that the
Cao et al. (2017) model may miss.
Furthermore, wavelet analysis is used to deconvolve two time series at a
time (e.g. our CISZ and non-CISZ lengths with the palaeo-atmospheric
CO2 record by Foster et al., 2017) to uncover any periodicities or
correlations. Compared to other techniques that find time-dependent
correlations between two signals such as the windowed Fourier transform, the
wavelet transform is preferable because it is localised (bounded) in both
time and frequency, whereas Fourier transforms are only localised in
frequency (Torrence and Compo, 1998). Hence, the wavelet transform can
better constrain correlations in time and is better suited than the Fourier
transform to approximating data with sharp discontinuities, such as those
addressed in this investigation.
This paper is accompanied by an open-source “subduction zone analysis
toolkit” (Doss et al., 2016), including a model of spatio-temporal carbonate
platform accumulation that extends from the Precambrian, to help enable the
use of digital plate motion models (e.g. Matthews et al., 2016) and other
tools to investigate aspects of the deep carbon cycle.
Modelling subduction zones evolution
We investigate the combined effect of evolving global subduction zone
lengths and the subsequent decarbonation of crustal carbonates by subduction
zone melts to create a first-order approximation of the contribution of
CO2 outgassed at CISZs to palaeo-CO2 levels over the past 410 Myr. An
“accumulation model” of carbonate platform evolution since the Precambrian
represents the long-term persistence and build-up of carbonate platforms in
upper continental crust. The plate reconstructions used in this study have
been developed through a synthesis of marine and continental geological and
geophysical data, including seafloor spreading histories for the post-Pangaea
time frame (Seton et al., 2012; Müller et al., 2016), and largely
palaeomagnetic and continental geological constraints for pre-Pangaea
time frame
(Domeier and Torsvik, 2014; Matthews et al., 2016). Subduction zones are
implemented where the geological record indicates arc volcanism or intrusive
magmatism, an active accretionary melange, active orogens associated with
subduction zones, formation of supra-subduction zone ophiolites, and other
indicators of an active margin. As our plate reconstructions are global,
plate boundary evolution requires continuously evolving topological polygons
to capture plate motions (Gurnis et al., 2012), meaning that subduction
zones are implemented along entire convergent margins, rather than only
where preserved arc volcanics are found. Our plate reconstructions that
include continental motions and plate boundary evolution are available as
open-access community resources (https://www.earthbyte.org/global-plate-models/, last access: 20 June 2018).
An “accumulation model” of carbonate platform development
Palaeogeographic maps of carbonate platforms spanning the Phanerozoic since
the Ordovician in Kiessling et al. (2003) have been used to model carbonate
platform accumulation through time. The 31 maps represent the spatial extent
of carbonate platforms at the maximum marine transgression within each epoch
for the Phanerozoic (Kiessling et al., 2003). Additionally, all instances of
carbonate lithologies of Precambrian (4600–541 Ma) and Cambrian age (541–485 Ma)
are extracted as point data from the Paleobiology Database (2017) (304 data
points; https://paleobiodb.org/, last access: 15 May 2018),
the PaleoReefs Database (19 data points; Kiessling and Flugel, 2002) and some well-studied carbonates in
northern China (Meng et al., 2011). Considering that the spatial extent of the
Precambrian carbonate platforms is poorly constrained, we applied a 200 km
buffer to the point data from the databases. All carbonate platform
geometries are georeferenced to WGS84 co-ordinates in ArcGIS (ESRI, 2011) to
be compatible with GPlates, the open-source plate reconstruction software
(Boyden et al., 2011). A GPlates file is created to depict carbonate platform
accumulation from 410 Ma to the present day using platforms which have existed since the
Precambrian, in order to better capture buried carbonate platforms at the
beginning of the model time frame. Creating this model involves stitching
together all carbonate platform shapefiles and allowing them to persist until
present day. Ages were ascribed based on the Golonka and Kiessling (2002)
Phanerozoic timescale. However, owing to new chronostratigraphic data, the
geological times ascribed to the existence of carbonate platforms in our
model for each epoch are converted to the corresponding times in the latest
chronostratigraphic scheme given in the 2016 version of the International
Stratigraphic Chart (Cohen et al., 2013). Subsequently, the static carbonate
platform shapefiles are reconstructed with the rotations and plate geometries
associated with an older plate motion model (Scotese, 2016), similar to the
model used by Kiessling et al. (2003). In GPlates, the carbonate platform
geometries are assigned plate IDs based upon their overlapping position
within the reconstructed continental geometry. Carbonate platforms are
rotated to their present-day positions, and plate IDs associated with the
Scotese (2016) model were translated into corresponding plate IDs from the
Matthews et al. (2016) plate motion model. By obtaining the present-day
geometry of the ancient carbonate platforms, attaching these geometries to
any other plate motion model becomes straightforward. The evolving carbonate
platform model is created by layering each carbonate platform geometry such
that it persists to present day. The accumulation model we implement in
this study embodies the idea that carbonate platforms accumulate in crustal
reservoirs through time.
(a) Schematic representation of the ∼ 450 km long
cross-profile “whiskers” that are constructed along subduction zones
(purple and black), spaced 10 km apart in the direction of subduction. The
carbonate polygons (light blue) of the carbonate platform mask have a value
of 1 (including those on the continental and oceanic crust), and
elsewhere the grid values are zero. All whiskers that intersect, at some
point along their length, with the carbonate platforms in the mask will
contribute 10 km to the total count of carbonate-intersecting subduction
zones. (b) Schematic representations of carbonate-intersecting
continental subduction zones. Carbonate platforms become buried over time,
forming reservoirs in the crust. Through assimilation and decarbonation
reactions, arc magmas interact with upper-crustal carbonates and liberate
significantly more CO2 emissions that at non-intersecting
continental arcs.
Assumptions and limitations of the accumulation model
The accumulation model is an end-member scenario of how carbonate platforms
evolve through time. Carbonate accumulation is assumed to accrete on
primarily continental lithosphere and persist as mid-crustal carbonate
reservoirs from the time of their formation to the present (Fig. 1). Ancient
carbonate platforms are known to persist to the present day in surface
reservoirs, and can be reconstructed from the geological record as they outcrop, are sampled by drilling or are interpreted from seismic
reflection studies (Kiessling et al., 2003). Some crustal carbonate is
inevitably eroded or subducted into the deep mantle, however it is improbable
that most reservoirs have been destroyed in this way as most carbonate
platforms accumulate on continental margins and are not likely to subduct
(Lee and Lackey, 2015). Given limited erosion on passive continental margins,
except in the cases of major uplift and deformation through
mountain-building, it is far more likely that carbonate platform accretion
has exceeded their depletion by erosion or consumption through time (Ridgwell
and Zeebe, 2005). Moreover, the existence of fossil reef data as far back as
the Precambrian (Grotzinger and James, 2000) favours the notion that
extensive portions of platforms have been well preserved in continents.
Nevertheless, our model assumes that carbonate platforms have not been
significantly depleted by sustained mantle-crust interaction through time.
We follow this assumption because there is no way to account for their rate
of depletion given the complexity of inter-dependent factors such as
platform thickness, heat, pressure, composition and the duration of
interaction (Johnston et al., 2011). Accounting for the thickness of
platforms and the depletion of reservoirs over time are areas of necessary
future developments in the model. We accept that our accumulation model is a
simplification of the carbonate reservoir system and may lead to an
overestimation of CISZ lengths. However, this may be a reasonable proxy for
the substantial amount of CO2 emitted via diffuse outgassing that is
largely unaccounted for in global estimates of carbon emitted at continental
arcs (fore-arc, arc and back-arc settings; Keleman and Manning, 2015).
Given little evidence of carbon storage in arc crust, these estimates
provide important information on, if not an upper-bound estimate of, degassing
from CISZs, which are hypothesised to be a significant source of atmospheric
CO2 (Keleman and Manning, 2015). While some Precambrian carbonate
platforms have been described (Grotzinger and James, 2000), no effort has
yet been made to map their occurrence globally. It is beyond the scope of
this work to map the global spatio-temporal patterns of Precambrian
carbonate platforms, and thus only those point data captured by the
PaleoReefs and Paleobiology databases were incorporated into our accumulation
model. While it is expected that accounting for the entire extent of
Precambrian platforms would not drastically change the analysis if
Precambrian platforms largely lay over the extent of platforms already
accounted for, the accumulation model nevertheless represents a degree of
underestimation of the Earth's crustal carbonate reservoir.
Measuring global subduction zone lengths with pyGPlates
We use the open access global plate motion model from Matthews et al. (2016)
to analyse the spatio-temporal distribution of subduction zone volcanic arcs
in a deep-time tectonic framework and test the hypothesis that subduction
zone arc lengths are correlated with atmospheric CO2 levels. The
model spans much of the Phanerozoic as it links the 410–250 Ma Domeier and
Torsvik (2014) and the 230–0 Ma Müller et al. (2016) plate motion
models. Using open-source and cross-platform plate reconstruction software
GPlates (http://gplates.org/download.html, last access: 20 June 2018) and a new pyGPlates Python application programming interface
(API; https://www.gplates.org/docs/pygplates/, last access: 20 June 2018), we measure the length of subduction zones at 1 Myr
intervals since 410 Ma and track the length of subduction zones that
interact with carbonate platforms (CISZ), the length of all subduction zones
that do not intersect carbonate platforms (non-CISZ), and total global
subduction zone lengths. Using the pyGPlates workflow (Doss et al., 2016),
global subduction zone boundaries were extracted from the Matthews et
al. (2016) plate motion model, and subduction zone geometries were adjusted
to remove any overlapping line segments that would overestimate subduction
zone lengths through time (Doss et al., 2016).
Computing the intersections of carbonate platforms and subduction
zones
We test whether subduction zones interacting with carbonate platforms are
different from non-intersecting portions of subduction zones in their
contribution to global atmospheric CO2 concentration, and hence we
track the lengths of subduction zones that both do and do not intersect with
carbonate platforms in the overriding lithosphere. Carbonate platform
geometries are converted to polygons using grdmask from the
development version of Generic Mapping Tools (GMT; v.5.2.1; Wessel et al.,
2015), which create a Boolean-style mask consisting of closed domains with a
value of 1 where carbonate platforms existed and 0 elsewhere. We identify
polygons proximal to subduction boundaries through time using the exported
subduction zone geometries from the pyGPlates workflow. We compute the
signed-distance function, positive toward the overriding plate, on the
surface of the sphere for all subduction zones and computed where the
carbonate platforms lie within +448 km of the trench. The
grdtrack tool in GMT is used to create large tracks of 448 km long
cross-profiles perpendicular to subduction boundaries at a uniform spacing of
10 km, with “whiskers” pointing in the direction of subduction (Fig. 1a).
The whiskers have five evenly spaced nodes to detect intersections with
carbonate platform polygons anywhere along the cross-profiles. The whiskers
function as a buffer, allowing us to identify the lengths of subduction zone
boundaries within ∼ 450 km perpendicular radius of a carbonate
platform polygon. Cross-profiles that overlap with carbonate platform
polygons demarcate areas where continental subduction zones interact with
crustal carbonates (Fig. 1b).
We statistically determine the 448 km long inclusion distance by calculating
average arc-trench distances using the present-day “Volcanoes of the World”
database maintained by the Smithsonian Institution's Global Volcanism Program
(2003). From a sample size of 1023 volcanoes, average
arc-trench distances are 287 km with a standard deviation of 161 km, such
that one standard deviation greater than the mean arc-trench distance gives
448 km. This captures 84 % of the location of all present volcanic arcs.
While flat slab subduction may cause arc-trench distances in excess of
500 km (Espurt et al., 2008), a 448 km long whisker length is likely to
capture the majority of carbonate intersections through time.
Linking arc volcanism to palaeoclimate change
Relationships between oscillations in two time series can be examined using a
wavelet analysis to elucidate the scales and time intervals where the proxy
record and modelled data display correlated, periodic signals. We performed
wavelet analysis as a means of identifying localised variations of power
between proxy records of CO2 and modelled CISZ lengths and in turn
investigate the temporal evolution of these aperiodic signals. We are able to
carry out this analysis as the geophysical data exhibit non-stationarity;
dominant periodic signals vary in their frequency and amplitude through time.
The continuous wavelet transform (CWT) is particularly useful for this task
as it better characterises oscillatory behaviours of signals than discrete
wavelet transforms. The CWT was applied to decompose arc lengths and proxy
signals into time and frequency space simultaneously using functions
(wavelets) that vary in width to discern both the high- and low-frequency
features present (Lau and Weng, 1995; Supplement Sect. S3). To examine whether
trends in atmospheric CO2 and CISZ arcs are connected in some way,
the cross-wavelet transform (XWT) was carried out between the
proxy CO2 data (Fig. S1 in the Supplement) and each of the modelled
data on carbonate-intersecting arc lengths (Supplement Sect. S4). The XWT
reveals space-time regions where the two datasets coincidentally have high
common power as well as calculating the phase relationships between signals,
indicating where two series co-vary (Grinsted et al., 2004). Wavelet
transform coherence (WTC) is computed in tandem with the XWT and determines if the time
series are significantly interrelated in the frequency domain. All wavelet
analysis was carried out for each detrended and filtered time series based on
the statistical approach applied to geological and geophysical data by
Torrence and Compo (1998) and Grinsted et al. (2004).
Data filtering
The modelled results and proxy CO2 time series were pre-processed
for wavelet analysis by detrending and applying a low-pass filter. A moving
average filter was applied with a window size of 5 Myr to remove
high-frequency signals that may represent noise or other short-term
perturbations (Fig. S2). In the time-frequency domain, our focus is on the
power in the low-to-mid-frequency spectrum and so the moving average filter
was designed to remove periods less than 5 Myr. As a result, the analysis
does not capture any geologically rapid (few Myr) changes in CO2
that may be driven by changes in plate tectonics and carbonate platform-arc
interactions.
Rather than comparing estimates from the Accumulation Model with Phanerozoic
atmospheric CO2 models like COPSE (Bergman et al., 2004) or
GEOCARBSULF (Berner, 2006), results were compared to the proxy CO2
record compiled by Foster et al. (2017) because the unresolved uncertainties
in model calculations may have rendered comparisons less meaningful than when
comparing with proxy records. The multi-proxy CO2 dataset presented
by Foster et al. (2017) is the most up-to-date compilation of CO2
data at the highest temporal resolution available (0.5 Myr sampling
interval), representing their highest probability estimate of CO2
at each interval and is the proxy CO2 signal used in this study.
ResultsContinuous wavelet transform (CWT)
The wavelet power spectrum in the CWT shows the spatio-temporal distribution
of amplitudes of correlation between the time series and a Morlet wavelet of
a specific scale. Areas outside the cone of influence (COI) are not localised
in time and are thus unreliable for constraining the duration of periodicity.
For this reason, results within the 5 % significance level outside the COI
(in white translucent regions of the wavelet power spectra) are ignored.
There is significant wavelet power in the 24–48 Myr waveband (period
length) for CISZ lengths, which is intermittent in time yet dominates for
time intervals (365–295 Ma, 250–115 Ma, 90–35 Ma; Fig. 2a). Significant
wavelet power also exists in the 48–64 Myr waveband of 175–100 Ma and in
the 72–128 Myr waveband of 220–120 Ma. In contrast, periodic signals of
length ∼ 24–32 and 48–64 Myr have the highest wavelet power and are
significant in the non-CISZ time series from ∼ 360–150 Ma (Fig. 2b),
and are notably absent from the CISZ time series. Total global subduction
zone lengths have two clear and persistent signals through time, primarily in
the 24–32 and 48–64 Myr wavebands (Fig. 2c). Significant, high wavelet
power in the 16–32 Myr waveband exists in the proxy CO2 time
series of 280–150 Ma and of 125–50 Ma (Fig. 2d). The ∼ 96 Myr
waveband has the highest wavelet power at the 5 % significance level in the
proxy CO2 time series of 300–120 Ma (Fig. 2d). There is overlap
in periodic behaviour between the CISZ, non-CISZ, global subduction zone and
CO2 proxy data in the 16–32 Myr wavebands.
Continuous wavelet transforms (CWT) for four time series:
(a) carbonate-intersecting subduction zone (CISZ) lengths,
(b) non-CISZ lengths, (c) global subduction zone lengths
and (d) the proxy CO2 data from Foster et al. (2017).
Thick black contours designate the 5 % significance level against a red
noise background spectrum. The cone of influence (white translucent region)
is where edge effects distort the spectrum, meaning that results in this
region are not reliable. The colour bar indicates the range of wavelet power
in the wavelet power spectrum, with hotter colours corresponding to the
maximum peaks in wavelet power. Note the logarithmic scale of the period
(Myr) axis.
Cross-wavelet transform (XWT) and wavelet transform coherence (WTC)
The periodic components common in the subduction zone length time series and
the proxy CO2 record were investigated further using XWT and WTC
(Fig. 3). The XWT highlights areas of common high wavelet power between two
CWTs, whereas the WTC finds the correlation between two CWTs in time,
highlighting persistent and significant periodic signals even if cross-wavelet power is low (Grinsted et al., 2004). Phase-locked arrows within the
95 % confidence contours in the WTC (arrows that do not change direction
through time) are the strongest indicator of a persistent periodic signal.
Generally, the WTC analysis between subduction zone lengths and the
proxy CO2 record does not highlight significant and prolonged
coherence through time, but rather, highlights time intervals where periodic
behaviour was significant and stable.
While a prolonged interval of high joint power in the XWT spectra between
CISZ lengths and proxy CO2 exists in the 24–48 Myr waveband
(Fig. 3a), this is not found to be coherent through time in the WTC
(Fig. 4d). However, the ∼ 96 Myr waveband is coherent in 200–100 Ma and likewise, the 32–48 Myr waveband is coherent
in 60–40 Ma (Fig. 3d). Portions of these regions lie outside the COI and are
thus cannot be well localised in time. Other areas of high coherence are not
linked to significant cross-spectral power in the XWT.
East-pointing arrows that are phase-locked in the WTC in the ∼ 96 Myr
waveband indicate in-phase peaks, such that local maxima in CISZ lengths and
palaeo-atmospheric CO2 are aligned over the 200–100 Ma time
interval (Fig. 3d). Between 60 and 40 Ma, coherent behaviour between CISZ
lengths and the proxy CO2 record is characterised by a 32–48 Myr
periodicity and CISZ lengths lead CO2 peaks by ∼ 90∘
(∼ 8–12 Myr; Fig. 3d). Over a similar time interval, coherent
behaviour is found between the proxy CO2 record and global
subduction zones. Between ∼ 60 and 20 Ma in the 16–24 Myr waveband,
CO2 peaks lag by 5–8 Myr behind peaks in global subduction zone
lengths (Fig. 3f). However, cross-wavelet power is stronger between the
CO2 record and CISZ lengths compared to global subduction zone
lengths over the 60–20 Ma interval (Fig. 3a, c).
Non-CISZ lengths and proxy CO2 record share broad areas of high
common power (Fig. 3b), yet the most significant region in the WTC is the
12–16 Myr waveband of 275–225 Ma (Fig. 3e), corresponding to a
significant area of the XWT. In this region, north-pointing phase arrows
indicate a 90∘ (∼ 3–4 Myr) lag of peaks in the
proxy CO2 record compared to peaks in non-CISZ lengths. Similarly,
peaks in the proxy CO2 record lag global subduction zone lengths by
3–4 Myr in a cyclic period of 12–16 Myr (Fig. 3e). South-pointing
phase-locked arrows indicate that CO2 peaks are leading peaks in
non-CISZ lengths (48–64 Myr waveband, 315–185 Ma) and west-pointing
arrows indicate anti-phase behaviour (where peaks in one time series coincide
with troughs of another time series; 16–32 Myr, 210–150 Ma), both of
which do not support causal relationships.
The cross-wavelet transforms (XWT; top) and wavelet transform coherence (WTC; bottom) for (a, d) CISZ, (b, e) non-CISZ and (c, f) global subduction zone lengths respectively and the proxy CO2
record (Foster et al., 2017). Thick black contours designate the 5 %
significance level against a red noise spectrum. The white translucent region
designates the cone of influence (COI). The colour bar indicates the
magnitude of cross-spectral power for the XWT, and for the WTC it represents
the significance level of the Monte Carlo test. The arrows indicate the phase
relationship of the two time series in time-frequency space, where
east-pointing arrows indicate in-phase behaviour, west-pointing arrows
indicate anti-phase behaviour, north-pointing arrows indicate that the peaks
in subduction zone lengths leads the CO2 peaks and south-pointing
arrows indicating that CO2 peaks lead peaks in subduction zone
lengths.
The XWT shows that global subduction
zone lengths and the proxy CO2 record share regions of high joint
wavelet power (Fig. 3c). Nevertheless, extended horizontal regions in the WTC
with south-pointing arrows indicate that CO2 peaks lead subduction
zone lengths (48–64 Myr waveband, 315–185 Ma) and areas of coherence
coincide with areas of low cross-spectral power (wavebands < 16 and
16–24 Myr, 380–340 Ma), undermining the potential of causal
relationships (Fig. 3f).
Graph of total global lengths of subduction zones (black) compared
with lengths of all subduction zones that intersect with buried crustal
carbonate platforms (magenta, thick) and those subduction zone lengths that
do not intersect crustal carbonate platforms (dark magenta, thin). The
proxy CO2 record (blue) from Foster et al. (2017) with upper and
lower bounds (blue envelope) is displayed for comparison.
Comparing carbonate-intersecting arc length and
palaeo-CO2 trends
At present day, our estimates of CISZ and global subduction zone lengths
reach approximately 35 300 and 62 000 km respectively. CISZ lengths show
an increasing trend over time, especially from 220 Ma to present when
lengths reliable reach above 10 000 km globally. From 250 Ma, accumulated
carbonate platforms consistently intersect ∼ 70 % of total global
subduction zone lengths (Fig. 4). Coherence analysis suggests that CISZ
lengths and palaeo-atmospheric CO2 peaks may not be well correlated
prior to 200 Ma. Indeed, CISZ lengths make up a small proportion of global
subduction zones prior to 200 Ma, beginning at 8600 km at 410 Ma and
increasing to over 14 000 km only after 200 Ma (Fig. 4). During some time
windows, periodic behaviour may be correlated. These two areas of
significance highlighted by the XWT and WTC analysis are between
200 and 100 Ma, and between 60 and 40 Ma (Fig. 3a, d). Between 200 and 100 Ma, WTC
highlights linked periodic behaviour between CISZ lengths and the
proxy CO2 record for a period length of ∼ 96 Myr (Fig. 3d).
CISZ lengths increase non-uniformly over this period from ∼ 14 300
to ∼ 23 800 km, whereas palaeo-atmospheric CO2 levels drop
from ∼ 1700 parts per million (ppm) to ∼ 860 ppm. Over the
60–40 Ma period, where WTC analysis found that CISZ lengths lead
CO2 peaks by ∼ 8–12 Myr (Fig. 3d), CISZ lengths show
small-scale oscillations between 28 400 and 33 700 km compared with
broader, defined peaks in atmospheric CO2 (Fig. 4). Note that WTC
analysis also found coherence with the proxy CO2 and global
subduction zone lengths over a similar period (∼ 60–20 Ma), where
peaks in global subduction zone lengths lead peaks in CO2 by
∼ 5–8 Myr in a 16–24 Myr cycle (Fig. 3f).
At 258 Ma, non-CISZ lengths reach a peak of 86 424 km as global subduction
zone lengths reach 95 500 km, followed by palaeo-atmospheric CO2
reaching a peak of 880 ppm at 252 Ma. This result coheres with cyclic
behaviour found in the WTC, where peaks in non-CISZ and global subduction
zone lengths precede local CO2 maxima by 3–4 Myr in the
275–225 Ma time frame (Fig. 3e). In the same interval, a peak at 230 Ma in
total subduction zone lengths and non-CISZ lengths (73 700 and 63 600 km
respectively) precede a peak at 226 Ma in the proxy CO2 record
(∼ 2100 ppm).
Discussion
With growing global reservoirs of carbonate platforms since 250 Ma, we
expect to see linked, periodic behaviour in the most recent past compared to
410–250 Ma if the length of CISZs have had a dominant climate-forcing
effect. Indeed, our wavelet analysis highlights that CISZ lengths and the
proxy CO2 record have aligned local maxima in 200–100 Ma, and
found that ∼ 96 Myr cyclical behaviour between the two time series is
linked in that time interval. Furthermore, if results found outside the COI
could be localised better in time, it is possible that the cycle would extend
further toward the present day. Our result that increased CISZ lengths
200–100 Ma drove the Jurassic–Cretaceous peak in atmospheric CO2
is consistent with the latest COPSE model results where a peak and decline of
atmospheric CO2 and global temperature in the 200–0 Ma interval
was driven by a peak and decline in volcanic degassing (Lenton et al., 2018).
At this time, the breakup of Pangaea drove increased subduction zone lengths
with continental dispersal, and thus increased CISZ lengths, especially at
the northern edge of the Mongol–Okhotsk plate and in the Tethyan tectonic
domain (Fig. 5c). However, Brune et al. (2017) found that continental rifting
has the potential to drive massive CO2 emissions, especially from
the 160–100 Ma time interval. Furthermore, degassing of basalt flows from
the central Atlantic magmatic province (CAMP) ∼ 200 Ma has also been
postulated to have driven climate change as well as the end-Triassic
extinction (Davies et al., 2017).
As multiple feedback mechanisms between the geosphere, biosphere and
atmosphere are at play in the 200–100 Ma time frame, it is unclear whether
subduction zone lengths had a dominant or auxiliary effect in controlling
increased atmospheric CO2. Moreover, in 60–40 Ma, a 32–48 Myr
cyclicity prevailed, characterised by local maxima in CISZ lengths lead peaks
in CO2 by ∼ 8–12 Myr (Fig. 3a, d). The implications of this
result are discussed in Sect. 5.2.
From the WTC (Fig. 3e, f), we observe that local maxima in non-CISZ lengths
and global subduction zone lengths are found to lead local maxima in
palaeo-atmospheric CO2 by 3–4 Myr in a 12–16 Myr cycle, in the
Permian–Triassic interval (275–225 Ma). While this indicates that a trend
in global subduction zone and non-CISZ lengths may have had a climate-forcing
effect in the 275–225 Ma time frame, multiple tectonic and non-tectonic
events may have also influenced greenhouse conditions. It is during this time
that massive volcanism from the Siberian traps and Emeishan large igneous province (LIP) were
particularly important in the sudden increase in atmospheric CO2
(Renne et al., 1995; Johansson et al., 2018). Contemporaneously, it has also
been suggested that an asteroid impact (Kaiho et al., 2001), oceanic anoxia
(Wignall and Hallam, 1992) and a release of oceanic methane hydrates (Kump et
al., 2005) all contributed to elevated atmospheric CO2 and the
warmer climate at the Permian–Triassic boundary.
Overall, we find that multiple tectonic and non-tectonic forcings are at play
during the 275–225 and 200–100 Ma time intervals where CISZ lengths
appeared to have a dominant effect on atmospheric CO2.
Moreover, CISZ lengths and the proxy CO2 record are largely found
to be independent with no strong leading relationship in the signal phase
offset that is consistent through time. While there are several regions in
all XWTs of significant common power between the proxy CO2 record
and our subduction zone time series, the regions were not coherent in the WTC
and could not be distinguished from random coincidence. For example, the
prolonged ∼ 32 Myr cyclic trend in CISZ lengths appearing in the XWT
(Fig. 3a) was not found to be consistent in time in the WTC (Fig. 3d).
Additionally, in some time intervals, phase arrows in the WTC did not support
the climate-forcing effect of subduction zone lengths. Ultimately, our study
does not support the hypothesis that carbonate-intersecting arcs have had a
sustained and dominant influence on atmospheric CO2 levels over the
past 410 Myr. Instead, carbonate-intersecting subduction-derived magmatism
is likely to have episodic control on atmospheric CO2, perhaps
related to the inception or abandonment of major regional continental
subduction zones. However, potential issues with the large uncertainties in
the proxy record, complexities in reconstructing pre-Pangaea subduction zones
and carbonate platforms, as well as the requirement to filter the time
series, may influence this result.
Present-day subduction zone estimates
At present day, our estimates of CISZ lengths are approximately 2.4 times
greater than the recent calculations of present-day global continental arc
lengths by Cao et al. (2017; 62 000 and 15 000 km respectively). Cao et
al. (2017) focussed on measuring the extent of continental volcanic arcs,
whereas our investigation encompasses the total segment lengths of all
subduction zones, including those that intersect carbonate platforms.
Therefore, our analysis tends to capture a broader range of CO2
degassing mechanisms along subduction zones, including diffuse outgassing
from fore-arcs, back-arcs and volcanic arcs along faults, fractures and
fissures, in addition to arc volcanoes. This is because melt is ubiquitous
along subduction zones, and there is very little carbon storage along arcs
(Keleman and Manning, 2015). For this reason, our approach differs from that
of Cao et al. (2017), as we are attempting to capture additional mechanisms
of CO2 escape along continental subduction zones, as opposed to
only those directly associated with volcanic arcs, and our estimates may be
regarded as an upper bound on total CO2 emissions at subduction
zones.
Implications for Palaeogene climate
Wavelet analysis also reveals coherent behaviour in the 60–40 Ma interval
where local maxima in CISZ lengths consistently precede local maxima in
palaeo-atmospheric CO2 by ∼ 8–12 Myr in a 32–48 Myr
cycle. Between 60 and 40 Ma, subduction zone lengths also were found to have
local maxima preceding local maxima in palaeo-atmospheric CO2 by
∼ 5–8 Myr in a 16–24 Myr cycle. However, cross-wavelet power is
stronger between CISZ lengths and the CO2 record, suggesting that
CISZ volcanism on a global scale had marginally more effect on climate
60–40 Ma than global subduction zone volcanism. The results may indicate
that increases in global subduction zone lengths and CISZ lengths may have
contributed to the Early Eocene climatic optimum (EECO) in 53–51 Ma, where
temperatures were 14 ± 3 ∘C warmer than the pre-industrial
period (Caballero and Huber, 2013). While climate interactions and feedbacks
leading to the greenhouse state remain uncertain, climate sensitivity to
CO2 forcing is likely (Anagnostou et al., 2016).
The termination of arc volcanism particularly along the Sundaland margin,
where a large area of carbonate platforms are buried, contributed
∼ 3000 km to the global reduction in CISZ lengths by ∼ 7000 km
between 75 and 65 Ma (Fig. 5e, f). The resumption of subduction along the
Sunda–Java trench at 65 Ma described by Zahirovic et al. (2016) and
the emplacement of a set of carbonate platforms in the lower latitudes at
63 Ma explain the modelled results of an increase in CISZ lengths at 63 Ma
which persist until present day (Fig. 5f). The EECO occurred approximately
10 Myr later, supporting the 8–12 Myr lag in peaks of a
∼ 32–48 Myr periodicity found by the CISZ-CO2 XWT and WTC
(Fig. 3a).
Our analysis shows a concomitant increase in global subduction zone lengths
(Fig. 4), which cannot be ruled out as an explanatory source of climate
forcing. However, modern volcanic CO2 output from arcs in
Indonesia, Papua New Guinea, parts of the Andes and Italian magmatic province
are strongly influenced by carbonate assimilation (Mason et al., 2017) and
volcanoes in those regions currently contribute significantly to global
atmospheric CO2 flux (Carter and Dasgupta, 2015). Assuming a
similar subduction style, this result gives plausibility to the idea that
volcanic activity along the Sunda–Java trench during the Palaeogene also
significantly contributed to global CO2 output.
Previous studies have suggested that global arc CO2 contributed to
the baseline warm climate of the Late Cretaceous and late Palaeogene, due to
the greater size of carbonate reservoirs in continents and the increased
continental arc lengths (Lee et al., 2013; Carter and Dasgupta, 2015;
McKenzie et al., 2016; Cao et al., 2017). Our results agree well with the
hypothesis, as a relative increase in carbonate-intersecting subduction zone
lengths has been linked to a peak in atmospheric CO2 in
60–40 Ma, contributing to enhanced CO2 degassing. However, it
cannot be determined from this study whether the increase in global
subduction zone lengths is more important than the relative increase in the
lengths that intersect carbonate platforms.
Plate reconstructions with plate boundaries (black), subduction
zones (purple) and distributions of carbonate platforms. Carbonate platforms
are distributed according to the accumulation model at key intervals from
400 Ma to present day. Colour bar corresponds to the time during
which the carbonate platforms were actively developing in the crust. In
addition, we set Precambrian and early Phanerozoic carbonate occurrences to
appear at the beginning of the model time frame, as the reconstructions do not
yet extend beyond Devonian times.
Limitations of wavelet analysis
Wavelet analysis is inherently sensitive to the shape of signals, and as
such, adjustment of filtering and processing techniques introduces variations
in the results. A 5 Myr moving average window filter was chosen to remove
high-frequency noise, yet it may have moved trends forward in
time, which
ultimately changes whether peaks overlap or not and adds uncertainty to
results. Peaks in the XWT were robust in that they were found to appear in
XWT plots regardless of the intensity of smoothing, yet the significance
contours differed strongly due to smoothing. For instance, with a longer
low-bandpass filter, small-scale oscillations < 5 Myr were removed,
reducing areas of significant power in the shorter wavebands. Similarly, when
experimenting with a high-bandpass filter, significant regions were directed
away from the longer periodicities of > 64 Myr to shorter periodicities.
The low-bandpass filter was chosen to remove the noise for smaller
periodicities where fluctuations were less likely to represent trends instead
possibly represent artefacts of interpolation, and as a result, this study
cannot evaluate short-term relationships between climate and subduction zone
volcanism.
Our analysis technique cannot quantify the error that propagates from
uncertainty in the proxy CO2 record and subduction zone length
signal through to the correlation uncertainty. Firstly, the Foster et
al. (2017) proxy CO2 record is a maximum probability estimate of
atmospheric palaeo-CO2 from a wider 95 % confidence envelope.
While the uncertainties appear to be time-localised, the uncertainty in
CO2 concentrations in the proxy record could not be captured by our
method of extracting only one time series for analysis. Similarly, the
Matthews et al. (2016) tectonic plate model represents one interpretation of
geological data which becomes sparse for deeper geological time, especially
for pre-Pangaea times (before ∼ 250–200 Ma). As there are no
comparable models, we cannot quantify uncertainty in our subduction length
signals. Therefore, we acknowledge that our comparison of two time series
with large uncertainties are insufficient in constraining periodic behaviour
and future research should involve comparing our estimates with other models
and data.
XWT analysis describes areas with high power which can be misleading when the
XWT spectrum is not normalised. For instance, areas of high joint power were
found where relatively flat peaks in the CISZ length data occurred simply
because of the large amplitude of peaks in the proxy CO2 data. The
vast differences in magnitude do not necessarily constitute a causative
relationship. WTC analysis does not present this problem because the spectrum
is normalised, and hence periodicities with strong power were not necessarily
found to be coherent (Maraun and Kurths, 2004). The combination of both
measures somewhat circumvents the problem of misleading peaks in the XWT, but
not entirely. Given that wavelet analysis is very sensitive to magnitude and
timing of peaks, the fact that the uncertainty in our modelled estimates of
subduction zone lengths are not well constrained introduces variability in
correlative relationships. Wavelet analysis, like other signal processing
techniques, is limited by the length of the time series data investigated.
Periods of greater than half the time series length cannot be examined using
this method (Winder, 2002). Therefore, very long oscillations on the scale of
250 Myr or more could not be derived from our data. One reason for examining
patterns on 250 Ma periods is due to the very long-term nature of
supercontinent cycles. The accretion of supercontinents such as Pangaea and
Rodinia is associated with shortened continental subduction zone lengths,
whilst continental break-up and dispersal initiates subduction on the edges
of continents, and thus increases continental subduction zone lengths
(Lenardic et al., 2011; Lee et al., 2016). These changing modes of
supercontinent break-up or accretion have the potential to influence climate.
Given that supercontinent cycles exceed 200 Myr in length and exert a large
effect on the length of continental arcs (Lee et al., 2013), applying this
analysis to plate reconstructions that capture multiple supercontinent cycles
(e.g. Merdith et al., 2017) to investigate whether such long-term linkages
exist between atmospheric CO2 and global subduction zone emissions.
Limitations of model assumptions
The extent to which our models are representative of subduction zone
CO2 emissions is limited by some issues with the subduction zone
quantification approach. The subduction zone modelling attempted to
approximate atmospheric CO2 flux at subduction zones without directly
measuring it by assuming a constant CO2 flux and a unit correspondence
of subduction zone lengths to volcanoes, vents or fissures. Both assumptions
are problematic. There are several dynamic factors that govern
subduction zone CO2 flux such as convergence rates (van der Meer et
al., 2014), the composition and volume of subducted sediments (Rea and Ruff,
1996), convergence obliquity (Kerrick and Connolly, 2001), slab volume flux
(Fischer, 2008), the relative contribution of metamorphic decarbonation in
the crust and in the mantle wedge (Keleman and Manning, 2015) and the
efficiency of decarbonation (Johnston et al., 2011). The model does not
account for these factors and assumes that the parameters of CO2 flux
have remained constant in time. In addition, the number of volcanoes or
vents per unit length of subduction zones is neither constant through time
nor correlated, at least for the circum-Pacific arc and Central American arc
(Kerrick, 2001). Furthermore, the accumulation model has no way to account
for carbonate platform thicknesses, and thus cannot account for the
realistic depletion of crustal carbonate reservoirs through time. The
inability of the model to incorporate the complexity of depleting carbonate
platforms may lead to sampling bias during continental collisions. This
highlights an area of future improvement, including the utilisation of
subduction zone geodynamic–geochemical modelling (e.g. Gonzales et al.,
2016) by tracking different CO2 reservoirs in a geodynamic context.
Furthermore, uncertainty cannot currently be measured using our GPlates
modelling approach. Uncertainty propagates through the plate motion model
over deeper reaches of geological time, such that it is currently impossible
to quantify uncertainty of all possible configurations of subduction zones,
especially in the pre-Pangaea time frame. Moreover, there is much greater
uncertainty in the dynamic mechanisms of carbon cycling along subduction
zones, and quantification of all geochemical decarbonation reactions is
still in infancy (Gonzales et al., 2016). For these reasons, formal
uncertainties cannot yet be quantified for models of subduction zone carbon
cycling. Taking all limitations into consideration, the accumulation model
still provides a first-order approximation of changing subduction zone
lengths through time and the interaction with (buried) carbonate platforms
as an indicator of CO2 degassing, especially during the Palaeogene.
Conclusions
Wavelet analysis is a useful tool in elucidating coherent, phase-related
periodicities between the CO2 record and various climate-forcing
factors. Furthermore, our accumulation model has the potential to capture a
broader range of degassing mechanisms, and thus provide an upper bound of
total CO2 emissions at subduction zones.
Our analysis has revealed that carbonate-intersecting subduction zone
volcanism is likely to have contributed to the greenhouse excursion of the
Early Eocene climatic optimum, with the CISZs along the Sunda–Java trench
representing the largest contribution to atmospheric CO2. At other
times, our analysis reveals potentially causal relationships among CISZ,
non-CISZ and global subduction zone lengths and atmospheric CO2
trends, but the effect of subduction zones could not be disambiguated from
other tectonic and non-tectonic climate forcings.
This
analysis lends partial support to the idea that, at certain times,
carbonate-intersecting subduction zone volcanism is more important than
non-carbonate-intersecting activity in driving atmospheric CO2, yet
the climate system is vastly complex and the result could mean that other
processes have dominated climate feedback mechanisms through time, such as
the proliferation of terrestrial plant life (Algeo and Scheckler, 1995),
silicate weathering (Kent and Muttoni, 2008) and the emplacement of LIPs
(Belcher and Mander, 2012).
Generally, an absence of constraints on carbon–climate interactions in
deep time makes it difficult to test hypotheses about greenhouse and icehouse
climate states. Clearly, more robust reconstructions of climate-forcing
processes are needed to improve our understanding of the deep carbon system.
It is suggested that further investigations be carried out 410–350 Ma and
50–0 Ma to eliminate the uncertainty around the time periods at the end of the data series that lie within the COI. With
adjustments to the parameters and assumptions governing the carbonate
platform evolution models, the data can be used as input into fully coupled
planetary-scale climate and carbon cycle box models. This would provide the
most comprehensive and self-consistent approach to understand the
contribution of emissions at subduction zones to the deep carbon cycle.
Code and data availability
The subduction zone toolkit by Doss et al. (2016; 10.5281/zenodo.154001) was
developed as a product of this research and has been made publicly available
for use with open-source plate reconstruction software, GPlates. The toolkit
includes all proxy CO2 data, pyGPlates and bash scripts as well as
the Matthews et al. (2016) plate model.
Both the Signal Processing Toolbox™ and
Wavelet Coherence Toolbox™ for
MATLAB®
were used in analysis and the production of figures.
The Wavelet Coherence Toolbox™ can be found at
http://noc.ac.uk/marine-data-products/cross-wavelet-wavelet-coherence-toolbox-matlab (last access: 10 June 2018),
while the Signal Processing Toolbox™ can be
found at http://au.mathworks.com/help/signal/index.html (last access: 10 June 2018).
The supplement related to this article is available online at: https://doi.org/10.5194/cp-14-857-2018-supplement.
Author contributions
SD and JP developed the Subduction Zone toolkit
together and carried out modelling experiments under the supervision of DM
and SZ. Figures were prepared by JP and SD, and the toolkit repository was
prepared by SD. JP conducted wavelet analysis with assistance from RH. JP
also prepared the manuscript with contributions from all co-authors.
Competing interests
The authors declare that they have no conflict of
interest.
Acknowledgements
The authors acknowledge and thank the Alfred P. Sloan Foundation and the Deep
Carbon Observatory (DCO) for funding this research. We would also like to
thank members of the EarthByte Group for all their assistance, as well as the
University of Sydney for supporting open source and open access
research.Edited by: Laurie Menviel
Reviewed by: three anonymous referees
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