Wilkes Land, East Antarctica: Using Subglacial Geology As a Key Test for Ice Sheet Stability

Wilkes Land, East Antarctica: Using subglacial geology as a key test for ice sheet stability

By Lara Urosevic

Supervisors: Dr Alan Aitken and Prof Ryan Lowe

This thesis is submitted to fulfil the requirement for Master of Science (Geology) by way of Thesis and Coursework,

School of Earth Sciences The University of Western Australia (November 2017)

Contents Abstract ...... 4 1. Introduction ...... 5 1.1 Aims and objectives ...... 7 1.2 Wilkes Land- geologic setting...... 8 1.3 Wilkes Land- glacial systems ...... 14 1.3.1 Introduction to Antarctic ice sheet dynamics ...... 14 1.3.2 Ice-Rafted Detrital studies and provenance ...... 17 1.3.3 Totten Glacier ...... 20 2. Interpretation of Subglacial Geology ...... 23 2.1 Method ...... 23 2.2 Results ...... 24 2.2.1 Albany-Fraser Province region ...... 26 2.2.2 West Mawson region ...... 27 2.2.3 East Mawson region ...... 28 2.2.4 Knox Rift region ...... 29 2.2.5 Aurora region ...... 30 2.2.6 Other Components ...... 31 2.2.7 Composite Bedrock Geology Map...... 32 2.3 Conclusive Remarks ...... 35 3. Erosional Spatial Analysis ...... 41 3.1 Methods ...... 42 3.2 Results ...... 43 3.2.1 Ice Sheet State 0_0 ...... 43 3.2.2 Ice Sheet State 4_1 ...... 45 3.2.3 Ice Sheet State 8_2 ...... 47 3.2.4 Ice Sheet State 12_5 ...... 49 3.3 Final Comparison and Conclusive Remarks ...... 51 4. Discussion ...... 56 4.1 Link to IRD records: Model Uncertainties ...... 56 4.1.1 Geological Uncertainty ...... 56 4.1.2 Ice Sheet Model and ‘erosion potential’ uncertainties ...... 57 4.2 Link to IRD records: Detrital Transport Mechanisms ...... 57

5. Conclusion ...... 62 5.1 Further Work ...... 62 6. References ...... 64 7. Appendix ...... 72 Appendix A (Subglacial Geology) ...... 72 Appendix B (Erosional Spatial Analysis) ...... 77

Acknowledgements

I would like to thank both Dr Alan Aitken and Prof Ryan Lowe for giving me the opportunity to work on this project in my concluding year at the University of Western Australia. I have learnt so much and have enjoyed the multi-disciplinary approach required to gain knowledge on the Antarctic continent and its ice shelves. I would also like to thank Prof Myra Keep, Dr Sandra Occhipinti and Prof Marco Fiorentini for the immensely helpful feedback throughout the length of the project. And finally, I would like to thank my family and friends for constantly supporting me throughout this final stretch.

Abstract

Ice sheets have been of global interest because of their influence on sea level rise (SLR) in our currently warming world. Ice sheet stability is difficult to simulate and model, especially past events of ice sheet destabilisation and growth. Studying ice-rafted detritus allows for these ice sheets processes to be better understood, however these are often limited by provenance determination. The aim of this study was to simulate detrital signatures from a determined provenance in Wilkes Land. This was achieved by mapping and interpreting data from geophysical data and spatially analysing the erosive potential within these maps via ice sheet modelling. The ice sheets models used were “retreat models” that analysed the retreat mechanisms of an ice sheet under different air and ocean temperature forcings. Results showed that the approach was able to simulate unique detrital signatures for each modelled ice sheet state, with connection to a known provenance. The limitation is that the ice sheet models were not time- and hence climate-constrained and did not account for all the processes undergone by a retreating ice sheet. This includes cycles of advance and processes of detritus after erosion, such as entrainment, transport and deposition. These are all factors that control current IRD signature genesis in Antarctica. Despite the limitations, this study shows that a complex system can be better understood through a multidisciplinary approach.

1. Introduction The Antarctic ice sheet holds the largest amount of fresh water globally with approximately 58 metres of sea level equivalent ice (Fretwell et al., 2013). About 90% of this ice sheet is the East Antarctic Ice Sheet (EAIS) (Williams et al., 2010). The EAIS has not been as extensively studied in the past as the West Antarctic Ice Sheet (WAIS), which has been more in focus because of its high melting and iceberg calving events (Rignot et al., 2013; Mackintosh et al., 2014). Melting and calving are important to note since they are an output which contribute to a budget which factors into ice sheet stability (Rignot et al., 2013). Rapid melting and calving become a problem when they outweigh mass gained from upstream (Rignot et al. 2013). EAIS responses to climate forcings and their consequent influences on sea level rise (SLR) remain uncertain. This uncertainty along with reports of high basal melt and thinning rates has contributed to the growing interest in the EAIS. There has also been increasing evidence (see Williams et al. 2010; Cook et al., 2014; Aitken et al., 2016) that the EAIS underwent numerous retreat events in warmer periods in the past. Wilkes Land is one of the weakest parts of the EAIS and one system in particular, Totten Glacier, has had increased melt and thinning rates (Zwally et al., 2005; Flament and Remy, 2012; Rignot et al., 2013; Gwyther et al., 2014), and is therefore the main glacier system in focus for the project.

These events released icebergs that deposited detritus locally and thousands of kilometres away (Williams et al. 2010; Licht and Hemming, 2017). This detritus is known as ice-rafted detritus (IRD) and has been broadly used as a technique for understanding past and present ice sheet stability in both Antarctica and the Northern Hemisphere. This IRD provides insight into past ice sheet histories such as iceberg production rates, and the flux of outlet glaciers from the ice sheet (Cook et al., 2014). Provenance studies of IRD signatures have been quite difficult to conduct in Antarctica since about 0.18% of the total land mass is exposed (Burton-Johnson et al., 2016). Therefore, geophysical data is necessary for provenance determination. Additionally, these ice-free regions are mostly located away from the major ice streams, and so these outcrops may not be representative of the detritus generated by these ice-streams.

The issue with assessing ice sheet stability and retreat is that there is no direct link of the data between the geophysical, geochemical and modelling techniques. The epoch/climate which is thought to have triggered these destabilisation events is the Pliocene (Cook et al., 2014). The modern-day CO2 concentrations have reached mid-Pliocene warm levels of 400ppm (Pagani 5 et al., 2010; Betts et al., 2016); when average temperatures where on average ~2-3°C greater than today (Dowsett et al., 2009). In our current changing climate, atmospheric warming will become the dominant driver of ice loss and prolonged ocean warming will delay the recovery of ice for thousands of years (DeConto and Pollard, 2016). Therefore, it is becoming imperative to combine all the revenues of knowledge to improve modelling and understandings of ice sheet stability and associated SLR in Totten Glacier and the rest of East Antarctica.

1.1 Aims and objectives The study will focus on better understanding the subglacial geology of Wilkes Land, and how this could constrain the ice sheet response to past climates. This includes understanding the Wilkes Land detrital signatures which could come from linking subglacial geology to modelled sources of erosion.

The main objectives of this study are listed below:

1. To map the geology of Wilkes Land, East Antarctica, and define distinct tectonic units at "supersuite" level. 2. Use numerical ice sheet models to generate potential detrital ‘fingerprints’ for different ice sheet states 3. To investigate the paths and mechanisms of ice-rafted detritus (IRD) transported from the study area (deposition sites as determined from Cook et al. (2014) and others).

The mapping process of Wilkes Land (objective 1) will focus on interpreting geophysical data obtained from the International Collaborative Exploration of the Cryosphere through Airborne Profiling (ICECAP) project and was processed by Aitken et al. (2014).

Objective 2 looks at the interaction between the ice sheet and the subglacial geology. This will be done by using ice sheet models as a proxy for erosional potential and will spatially analyse the likely erosion patterns to allow for an erosion signature to be derived for each ice state in the study area.

The mapping and statistical analysis processes can then be discussed in order to understand the likely IRD provenance for Wilkes Land. The mechanisms of transportation from the source of erosion (provenance) to the ocean (IRD deposition site) also needs to be considered.

1.2 Wilkes Land- geologic setting Antarctica and Australia have been key components in many supercontinent cycles, namely Columbia/Nuna, Rodinia and Gondwana (Fitzsimons, 2003; Boger, 2011). Wilkes Land in East Antarctica has great affinity with crustal components from the southern margins of Western and Southern Australia (Boger, 2011; Aitken et al., 2014). Wilkes Land is almost completely covered by thick ice sheets aside from several outcropping areas, namely the Windmill Islands (WI) and Bunger Hills (BH) regions. Though these sites are important reference points for the correlation of Antarctica to Australia, they define small points of the thousands of kilometres of geology that make up Wilkes Land. Also, both regions do not have a direct connection with Totten Glacier, or the Totten Glacier catchment. This is because the BH region lies adjacent to the Scott/Denman ice stream (> 800 km S of Totten, Fig. 1, A) and the WI region is not situated close to any major ice streams, making these regions not as relevant in relation to understanding Totten Glacier stability.

The most recent mapping of the area was undertaken by Aitken et al. (2014) by using airborne geophysical data (Fig. 1). This link between Australia and Antarctica is important since it provides context to the geophysical data, allowing for the major domains to be determined and geology to be inferred (Aitken et al., 2014) (Table 1).

Fig. 1. A. The Antarctic landmass (Australian Antarctic Division, 2005) representing the area mapped by Aitken et al. (2014) and some important glaciers/areas within this mapped area. WI= Windmill Islands, BH= Bunger Hills. B. The Aitken et al. (2014) Wilkes Land geological map which shows the major tectonic domains and boundaries.

Table 1 Antarctic major tectonic domains and the correlative Australian domains

Antarctic Region Australian Correlative

1. Albany- Fraser Province Albany- Fraser Province

2. West Mawson Madura Province and Forrest Zone (Coompana Province)

3. East Mawson Gawler Craton

4. Aurora Subglacial Basin Unknown

5. Knox Rift/ Subglacial Basin Pinjarra Orogen

The WI and BH both lie in the ‘Albany-Fraser Province’ region of Wilkes Land (Region 1, Table 1). The name for this region comes from the fact that both the BH and WI have a confirmed affinity with the Albany-Fraser Province (AFP) in Western Australia (Morrissey et al., 2017; Aitken et al. 2016b; Zhang et al., 2012; Clark et al., 2000). Nd model ages reported by Moller et al. (2002) indicate that the WI region falls within the Albany-Fraser Province (AFP) range of Proterozoic-Archean Nd model ages.

The Albany-Fraser Orogen (AFO) of Australia also forms a belt that can be traced along strike into Wilkes Land (Sheraton et al., 1993; Black et al., 1992b) in which two stages of orogenesis are reported (Clark et al., 2000; Bodorkos and Clark, 2004a). The two stages of the Australian Albany-Fraser orogenesis occurred between 1340 Ma and 1260 Ma (Stage I), and 1214 Ma and 1140 Ma (Stage II) (Clark et al., 2000) (Fig. 2). The corresponding stages of overprinting in the WI occurred between 1340 Ma and 1310 Ma (Stage I), and 1210 Ma and 1180 Ma for (Stage II) (Black et al., 1992b; Sheraton et al., 1993). The WI region also contains metasedimentary rocks (metapelite and metapsammite) that can be linked to the Arid Basin in the AFO (Zhang et al., 2012; Morrissey et al., 2017) (Fig. 2).

The BH region shows similarly aged rocks as the Biranup Zone of southern WA (Boger, 2011), although it cannot be directly connected in Gondwana reconstructions (Aitken et al., 2014). Overall, the outcropping areas of WI, and to a lesser extent the BH, have a relatively robust link with the Albany-Fraser Province (Zhang et al., 2012; Aitken et al., 2014; Morrissey et al., 2017).

Fig. 2. A time-space plot showing the relative relationship of the AFO and the Madura Province (adapted from Spaggiari et al., 2015). The red lines show the timing of events and the blue boxes show the Australian zones that most correlate with Wilkes Land.

The second major domain that could be correlative with Australia is the West Mawson region of Wilkes Land (Fig. 1, B). A correlative point in Australia for this region is the Madura Province, and the Forrest Zone of the Coompana Province. The Rodona Shear Zone separated the Madura Province from the AFP (Australia) and extends into Wilkes Land. This is known as the Rodona-Totten Shear Zone (RT) in Gondwana reconstructions (Fig. 3). The Mundrabilla Shear Zone separates out the Madura Province from the Coompana Province (Smithies et al., 2015b). The Madura Province is characterised by a change in tectonic regime around 1410 Ma to an oceanic arc (Fig. 2) (Spaggiari et al., 2015). The Coompana and Madura regions together represent a huge tract of mainly juvenile material (Kirkland et al., 2017).

The final Australian domain that can be correlated to Wilkes Land is the Gawler Craton. This is related to the East Mawson region in Wilkes Land (Fig. 1, B). The Gawler Craton made part of the original nucleus of the Mawson continent (or “Mawson Block”) from which the rest of Antarctica formed (Boger, 2011; Halpin and Reid, 2016). The correlative points to this

early nucleus are inferred to underlie Wilkes Land and Adelie Land in East Antarctica (Fanning et al., 1995 (c.f. Boger, 2011)). Therefore, it is characterised by a late Archean to Mesoproterozoic crystalline terrane consisting of rocks that have undergone tectonothermal events between 2560 and 1450 Ma (Halpin and Reid, 2016; Kirkland et al., 2017).

A. B.

Fig. 3. A Leeuwin Gondwana reconstruction of Antarctica and Australia, from Aitken et al. (2016b). A. Total magnetic intensity anomalies B. Isostatic residual gravity anomalies.

Knowing what is being sampled is very important for IRD and provenance studies since there can be biases in signatures, depending if they come from basin or basement material. If the basement is being sampled, then the ages inferred from linking Australian correlatives to Antarctic correlatives can be used to determine provenance. If a basin is being sampled, the ages and geochemistry will reflect varied geological sources and ages, making provenance determination very difficult. The main subglacial basins (SBs) in the mapping area are the Aurora (including North Aurora), Sabrina, Vincennes, Knox and Frost Subglacial Basins (Aitken et al., 2014; Maritati et al., 2016). The Aurora SB shows a smooth magnetic character with low gravity, has depth-to-magnetic basement estimates, lies several km below the ice sheet bed, and is flanked by three faults (Siegert et al., 2005; Aitken et al., 2014). The Sabrina SB, East Antarctica, is tectonically comparable with the Bight (Mesozoic) and Eucla (Cenozoic) Basins of Australia (Direen et al., 2011; Aitken et al., 2014). A lot of information

12 has been acquired on the geology of the Australian domains. This will be imperative when correlating Antarctic regions and geology to Australia, since then there would likely be corresponding events (e.g. the two stages of metamorphism found in the WI (East Antarctica) and in the AFP (West Australia)).

1.3 Wilkes Land- glacial systems The main glacial systems in the mapping area include the Denman/Scott, Vanderford, Totten, Moscow University and Holmes Glaciers and which are all ice shelf systems connected to the East Antarctic Ice Sheet (EAIS). Totten Glacier has the greatest potential for instability and is a rapidly changing part of the EAIS; showing evidence of net-thinning from enhanced basal melting (Aitken et al., 2016; Pritchard et al., 2012; Rignot et al., 2013; Gwyther et al., 2014). It is also the biggest outlet glacier by mass flux (Rignot, 2002) and is the focus of the project.

The first Cenozoic ice sheets in Antarctica were thought to have initiated around 34 Ma at the Eocene–Oligocene boundary from rapid cooling, marking the transition from a greenhouse to an icehouse world on Earth (Zachos et al., 2001; Hay et al., 2005; van de Flierdt, 2011). Since the onset of glaciation, the ice sheets have undergone periods of cyclical expansion and retreat amounting up to 30 times in the subsequent 20 Ma (Zachos et al., 2001; Young et al., 2011).

Ice sheets and shelves are highly dynamic systems, they have discrete steady-states and can undergo hysteresis when external forcings or material parameters (e.g. basal slipperiness) are applied (Schoof, 2007). Understanding the effect of these parameters and forcings on the ice sheet can allow for a mass balance to be calculated, which can provide information on their sea level contribution (Mouginot et al., 2012; Pritchard et al., 2012; Gwyther et al. 2015).

1.3.1 Introduction to Antarctic ice sheet dynamics The most important concept to understand in ice sheet dynamics is the grounding line (Fig. 4). The grounding line is defined as the transition boundary where an ice sheet meets the ocean and the ice mass begins to float by buoyancy (Rignot et al., 2011a; Hanna et al., 2013). It is critical for creating ice sheet mass budget calculations and for modelling ice sheet dynamics, ice-ocean interactions and subglacial environments (Rignot et al., 2011a). This grounding line migrates back and forth with changes in oceanic tides within a “grounding zone” whose width is controlled by the glacier bed (and surface) slope and tides (Rignot et al., 2011a).

A. B.

Fig. 4. Ice sheet dynamics. A. Melting at the grounding line occurs from influx of warm/modified Circumpolar Deep Water (mCDW) leading to ice shelf thinning. B. Marine ice-sheet instability, the absence of buttressing has caused grounding line retreat in the direction of flow on the upward sloping bedrock (unstable) causing enhanced calving as the ice shelf thins. Adapted from Hanna et al. (2013). The calving front is represented by the blue dashed line.

In a schematic ice shelf system (Fig. 4), the ice shelf floats in water and is controlled by buoyancy yet is still connected to an ice sheet. This can form both a stable and unstable configuration, where stabilisation can be achieved/enhanced from buttressing effects. An iceberg is a free-floating ice mass which was once connected to an ice shelf (Hanna et al., 2013) but has been broken off, mainly due to hydrofracturing (Pollard et al., 2015). This break off process from ice shelves, glaciers, or crevasses is called iceberg calving (Greve and Blatter, 2009). Therefore, two processes are required; the initial fracturing combined with the transport of the detached iceberg from its source (the calving front, Fig. 4) (Bassis and Jacobs, 2013).

Ice shelf buttressing is the mechanical effect of an ice shelf on the state of stress at the grounding line, removal of the ice shelf would cause a new calving front and the grounding line would come into direct contact with the ocean (Gudmundsson, 2013). A buttressing effect can reduce the flow rate of ice shelves and can delay ice sheet retreat for several millennia (Gudmundsson, 2013). Ice rises may also cause buttressing effects which can stabilise the retreated ice sheet, relying on the bedrock shape and marine ice sheet conditions (Gudmundsson, 2013; Favier and Pattyn, 2015). Ice rises result from ice sheet deglaciation and grounding line retreat across a continental shelf (Favier and Pattyn, 2015) and represent small areas of grounded ice near a near an ice shelf.

Two major ways that ice is lost from Antarctic ice shelves is through calving and basal melting of the ice shelf (Dinniman et al., 2015). Ice shelf basal melting has three characterised modes as defined by Dinniman et al. (2015):

- Mode 1: high-salinity shelf water intrudes at the bottom of cavities below the ice shelves, causing melting underneath deep ice shelves, especially near the grounding line. - Mode 2: a relatively warm (> 0ºC) modified Circumpolar Deep Water (mCDW) (Fig. 4) intrudes onto continental shelves and underneath ice shelves, leading to rapid melting (Dinniman et al., 2015; Bassis et al., 2017). - Mode 3: warm surface waters enter the ice cavity near the surface and cause melting near the ice shelf front.

This oceanic melting at the base of ice shelves is more significant than iceberg calving in terms of mass loss in the Antarctic ice sheet (Dinniman et al., 2015). Basal melting is greatest at the grounding lines of major glaciers and along large ice shelves (Rignot et al., 2011a; Rignot et al., 2013). It is an important control on mass loss in ice shelves in Antarctica and subsequent sea level rise (Gwyther et al., 2015). Therefore, this access to warm, deeper water (Fig. 4) is a critical factor controlling grounding line retreat and ice sheet thinning. In situations where this access to warm water is denied by ocean access, such as topography or strong sea ice production, then the basal melt rate is low, and the ice shelf can stabilise (Dinniman et al., 2015).

Basal melting drives ice shelf instability when permitted. This means that major shifts in sea ice cover and ocean circulation could cause major changes in ice shelf and ice sheet mass balance and stability (Rignot et al., 2013). One such event was observed in Porpoise Bay, Wilkes Land, by Miles et al. (2017); large calving events occurred here and were driven by the break-up of sea ice which usually occupied the area. This shows that the floating ice shelves and glacier tongues that fringe Antarctica are important for stabilising the ice sheet through buttressing (Miles et al., 2017).

In terms of stability, ice sheets transition between periods of long-lived, quasi-stable configurations interspersed with shorter-lived, unstable configurations (Aitken et al., 2016). These unstable configurations ultimately seek stable configurations.

It is also vital to understand the subglacial geology and geomorphology when investigating ice sheet dynamics. Geological differences in the ice sheet bed are important focusing mechanisms for erosion (Aitken et al., 2014), and areas where a strong boundary layer exists will focus melting more than a deep grounding line (Gwyther et al., 2015). In Antarctica, the geophysical patterns of smooth lows (fjords) and rougher stippled highs are interpreted to result from the highlands being preferentially protected from glacial erosion (from cold-based ice), compared to valleys that form focusing points for both fluvial and glacial erosion (Jamieson et al., 2014; Young et al. 2011). From a topographical perspective, ice sheet modelling and airborne geophysics suggest that low-lying continental depressions, such as the ASB, caused the most pronounced ice sheet retreat in East Antarctica, especially during the Miocene/Pliocene (Young et al., 2011; Cook et al., 2014).

This means that ice sheets are highly dynamic, much like the factors that influence them. For this reason, Antarctic ice sheet dynamics are difficult to understand, especially through geological time where the climatic forcings and controls were different. One tool that is used to understand these ice dynamics through time is ice-rafted detritus (IRD).

1.3.2 Ice-Rafted Detrital studies and provenance Ice-rafted detritus or debris (IRD) is important for understanding changes in ice shelf instability as postulated from the amount of icebergs released, changes in transport conditions of glaciers, and changes in source regions of past iceberg production such as grounding line retreat/advance (Cook et al., 2014). Ice rafted debris comes from the erosion of the bedrock by the ice sheet.

The eroded detritus can become entrained in the ice sheet which can eventually destabilise and release debris-rich icebergs which melt and deposit the debris/detrital material. Knowledge of detrital signature provenance can determine areas where the ice sheet became unstable and how the icebergs calved from the icesheet could have drifted in the past (Williams et al., 2010).

This is achieved through three main mechanisms which include:

1. Basal Erosion/ abrasion (e.g. Herman et al. 2015), which is best represented by Totten. 2. Quarrying- material falling onto the ice surface (e.g. Iverson, 2012a). 3. “Plucking” of headwalls onto the ice surface (Fairbridge, 1968).

Sea surface temperatures and warming ocean temperatures are great factors of IRD signatures. This is because even small amounts of atmospheric warming cause ice sheets to become susceptible to destabilisation and catastrophic collapse events (causing an IRD signature) (Bassis et al., 2017; Cook et al., 2014). These catastrophic collapse or massive discharge events are known as Heinrich events in the North Atlantic (Heinrich, 1988). These events leave behind distinct IRD layers in ocean sediments (Heinrich, 1988; Hemming, 2004; Bassis et al., 2017). It is not certain if these events occur at Antarctica, but there is evidence that large-scale calving events have occurred in the past (William et al., 2010).

IRD provenance studies are conducted to investigate the response of ice sheets to climate in the past, where there were different global temperatures and conditions. This characterisation of the past can allow for modelling ice sheet stability and prediction of responses much like in Cook et al., (2014).

Investigations of marine sediment cores from the Prydz Bay area were conducted by Williams et al. (2010) and Cook et al. (2014) (Fig. 5). Both investigations recorded distinct IRD in the core sections from the Pliocene to Holocene. Thermochronological ages of the IRD were determined from hornblendes and micas and zircons. There were two main thermochronological age groups that separated out the population of hornblendes from Prydz Bay, these were the a. Prydz Bay Ar-Ar signatures at 455-575 Ma, and b. Wilkes Land Ar-Ar signatures from 1035-1315 Ma (Fig. 5). This was interpreted as the “Wilkes signature” since the age coincides with many geological processes that link Wilkes Land to Australia and the AFP (Fig. 2, 3) compared to the ages observed in Prydz Bay showing Paleozoic Pan-African Orogeny ages (Boger, 2011 (cf. Cook et al., 2014)).

Another key point of evidence for this signature being from Wilkes Land was determined by Williams et al. (2010) from offshore core-IRD and core-top data for Wilkes Land, and from using ages from outcrops of the Windmill Islands as a proxy. The age that was observed the most was the Ar-Ar age between 1100-1300 Ma and hence became the Wilkes Land signature, whereas the ~1700 Ma (Ar-Ar) defined the Adelie Land signature.

Fig. 5. (from Cook et al., 2014) Thermochronology data from Prydz Bay to Wilkes Land. The spotted polygon represents the interpreted provenance for the “Wilkes” detrital signature (blue box), whereas the “Prydz Bay” detrital signature is in the orange box. The arrows show approximate transport regions and iceberg pathways. Each pie chart represents a modern sedimentary core which was thermochronologically dated.

These distal Wilkes IRD signatures are important because they would require enormous amounts of large, detritus-carrying icebergs to be released from an ice shelf (Williams et al. 2010). The transportation paths and mechanisms of this detritus are not well understood, especially since the Wilkes Land icebergs would have to travel and survive melting (and deposition) for over 1500 km.

In Cook et al.’s (2014) study, there is an increased flux of Wilkes Land IRD to the Prydz Bay site between ~3.2 and 2.65 Ma making up 33% of total IRD deposited and 18% between ~5 and 3.27 Ma. The sample which reveals the greatest influx of Wilkes Land IRD signatures is one taken from the Pliocene epoch (5.33-2.58 Ma) at ~3.3 Ma (Cook et al. 2013). There are no ice cores for the Pliocene, therefore the major constraint on temperature and CO2 levels come from the ANDRILL sedimentary core (Harwood et al. 2006; Naish, 2009; Wilson et al. 2012).

One major control on IRD flux to the Southern Ocean during the Pliocene was orbital-scale fluctuations in ice volume. An increased IRD flux during a Pliocene interglacial (~2-5 Ma) would require five to ninefold increase in iceberg productivity from the Wilkes Land margin

19 to allow IRD to travel over 1500 km (Cook et al., 2014). A ninefold increase is comparable to Heinrich events in the North Atlantic (Cook et al., 2014). This idea is broadly summarised in equation 1. Here P_IRD is the production rate (of icebergs and IRD) at an individual glacier (n) and T_IRD is the proportion of these glaciers that survive. IRD refers to the observed IRD at a site.

IRD= (P_IRDn1*T_IRDn1) + (P_IRDn2*T_IRDn2)… … (1)

This 15% increase of IRD influx from Wilkes Land during ~3.2-2.65 Ma is attributed to the factors outlined in equation 1; IRD_P and IRD_T. The challenge of using the IRD method is that the influences of P_IRD and T_IRD are superimposed and need to be deconvolved and determined separately to be understood for the overall detrital record.

In conclusion, Wilkes Land is an important site for studying IRD patterns, since the area has a high potential for provenance determination (links to Australia), has observed IRD layers in the marine sedimentary record (e.g. Cook et al. (2014), Williams et al. (2010) and Pierce et al. (2014)) and is one of the least stable parts of the EAIS (Williams et al., 2010). This means that there have been destabilisation events in the past and there is a great potential for these to happen in the future, especially under warming oceans and changing climatic conditions. Therefore, IRD and provenance studies are necessary in order to understand what part of the ice sheet destabilised, when (time and climate) and why (tipping point).

1.3.3 Totten Glacier In the EAIS large areas are primarily grounded below sea level and are vulnerable to melting by ocean currents (Mackintosh et al. 2014), including Totten Glacier (Greenbaum et al., 2015), Fig. 1. The Totten Glacier is the largest EAIS outlet by mass flux in East Antarctica and is greatly influenced by subglacial flow from upstream (Wright et al., 2012). It is also the primary outlet of the Aurora Subglacial Basin (ASB) in Wilkes Land which drains into the Sabrina Coast area (Greenbaum et al., 2015). The glacier has an area of 6,032 km2, releases 71.0 ±3 GL/year and has a deep grounding line that is 2.2 km deep with larger than expected meltwater production (Rignot et al., 2013). It drains a sector which is 537,900 km2 in size (Young et al., 2011). Totten Glacier forms an iceshelf between Law Dome and Sabrina Coast (Khazendar et al., 2013) where the fastest flow is concentrated along the flanks of Law Dome (Rignot, 2002). The coastal ice is grounded below sea level creating a potential for local marine ice sheet instability (Fig. 4, B) upstream of the grounding line (Pollard et al., 2015; Greenbaum et al., 2015). The Totten ice shelf provides a buttressing effect to the section of

EAIS that it is connected to, collapse of this ice shelf would lead to rapid thinning of that grounded ice (Rignot et al., 2011; Liu et al., 2015; Sun et al., 2016).

This system currently has the greatest thinning rate in East Antarctica (Flament and Remy, 2012) and hence also the greatest mass loss (Li et al., 2015) and surface lowering (Khazendar et al., 2013). This observed thinning of Totten Glacier is due to enhanced basal melting (Liu et al., 2015) caused by a decrease in cold polynya water reaching the cavity of the glacier (Khazendar et al., 2013; Gwyther et al. 2014). Polynya are areas of open water within sea ice cover within which sea-ice production rates are high (Khazendar et al., 2013). Polynya can protect ice shelf cavities from warm water incursion due to the production of cold, saline Antarctic Bottom Water during sea ice production (Khazendar et al., 2013).

The rates of thinning at Totten were reported to increase from 0.5 m/yr in the 1990s to ~1.5 m/yr in 2003-2009 (Zwally et al., 2005; Flament and Remy 2012), with widespread retreat of the grounding line at Totten Glacier of up to 3km from 1996 to 2013 (Li et al., 2015).

The glacier has gone through many cycles of stability to instability in the past and is likely to do so in the future. This is seen in the topography of the ASB (and surrounding areas) which reveal a surface sculpted by successions of ice sheet configurations different from today (Young et al., 2011). Totten Glacier has two distinct quasi-stable configurations which correspond to a retreated ice sheet and a modern-scale ice sheet (Aitken et al., 2016). This modern-scale EAIS configuration has a marginal zone near the present ice-sheet margin and has been modelled to increase global sea levels (SL) by less than 90 cm, whereas the retreated configuration has a marginal zone located much further inland which increases global SL by 2m (Aitken et al., 2016). The reason why Totten is quasi-stable is because it is likely that after a destabilisation event, it will reach a new stable position which is re- established further into the continent (Aitken et al., 2016).

The region is vulnerable to change driven by the entrance of mCDW (Fig. 4) through a trough (Greenbaum et al., 2015) which provides a pathway, allowing the mCDW to enter and melt the ice shelf cavity (Aitken et al., 2016). This mCDW could hence lead to rapid thinning and subsequent collapse of the ice shelf. The average ice mass loss is 7 ± 2 Gt/yr for Totten which is dominated by ocean temperature (Li et al., 2016). The melt rates simulated for Totten showed a larger than expected amount, which were linked to warm water intrusions across the continental shelf break (Gwyther et al., 2014). This access to a mCDW current is a

21 critical factor controlling grounding line retreat and ice sheet thinning in Totten and is best described by mode 2 basal melting (Sub-section 1.3.1).

Even though current temperatures are not the same as Pliocene temperatures, the Earth is currently out of energy balance and will continue warming regardless if the current CO2 (and greenhouse gas) emissions are stabilised at the current level (Hansen et al., 2017). This means that atmospheric warming will become the dominant driver of ice loss, the recovery of which will be delayed by thousands of years from prolonged ocean warming (DeConto and Pollard, 2016), meaning that Totten Glacier could be approaching a tipping point.

Since the Pliocene can serve as a potential analogue for projected future climates (de Boer et al., 2015), especially the Mid-Piacenzian Age (~3), with similarities in continental positions and oceanic circulation patterns allowing for a comparison of environmental conditions (Dowsett et al., 2017). Since IRD shows potential EAIS destabilisation in this time-period (Williams et al., 2010; Cook et al. 2014) there is a need to fully understand the effect of the Pliocene-like environment on EAIS (and Totten Glacier) stability to assess the response of ice-sheets to modern climate forcing. The study will therefore focus on characterising the geology of Wilkes Land to understand IRD provenance and detrital signatures under different ice sheet states (and climatic forcings).

2. Interpretation of Subglacial Geology

Subglacial geology was mapped using geophysical datasets acquired as part of the ICECAP program. They include magnetic, gravity and subglacial topography data processed and interpreted by Aitken et al. (2014), and sedimentary thickness data modelled by Aitken et al. (2016a).

2.1 Method In order for the subglacial geology to be characterised, the following steps were completed:

1. Review locations of major crustal boundaries in Wilkes Land and tectonic correlations with Australia. 2. Map basement geology to a “supersuite” level from magnetic and gravity data. 3. Map bedrock geology, including sedimentary basins.

The major tectonic domains were compiled and updated from Aitken et al. (2014) and Maritati et al. (2016). The supersuites were characterised from the interpretation of Total Magnetic Intensity (TMI) magnetic data, First Vertical Derivative (1VD) magnetic data, and Isostatic Residual Anomaly (IRA) gravity data (Appendix A, Fig. A1). The magnetic data provided greater resolution than the gravity data and was used primarily for mapping and characterisation as it allowed for a better classification of geological units.

The mapping of these geological units along with the related tectonic boundaries will allow for a basement geology map to be constructed. The bedrock geology map will use subglacial topography and total sedimentary rock thickness models to define the extent of sedimentary basins within the area. The sedimentary thickness data was classified into three unique categories for both the 10k and 20k data grids. The categorisation and the processing applied to the geophysical data sets are detailed in Appendix A.

Some issues with the sedimentary thickness data include the fact that it is best suited to one and two-dimensional data, but not more complex data (3D) (Aitken et al., 2016a). The greatest amount of uncertainty in the models occurs near rugged topography, for example the edge of Highland A, fjords and deep channels; these areas also most likely possess large errors in the subglacial topography data set. The reason for this is because ice sheet bed data was resolved at a much finer degree in comparison to the gravity data (only features > 6.75-8 km wide) (Aitken et al., 2016a). Areas such as the Sabrina Subglacial Basin had an

23 uncertainty of 600 m, but the sedimentary basin thickness could usually be defined within ±300m (Aitken et al., 2016a). Though there were large associated uncertainties; these had no influence on the overall pattern of basin thickness, only on the magnitude of this thickness (Aitken et al., 2016a).

This also required gravity data and gravity modelling which came with its own uncertainties. Some issues with the gravity method were that it only included relative gravity differences and the lines were not directly comparable (Aitken et al., 2016a). The various corrections that were applied to the geophysical datasets are shown in Table A1 (Appendix A).

2.2 Results The geological interpretation of the subglacial basement geology of Wilkes Land is shown in Fig. 6. The major domains were adapted from Aitken et al. (2014) and Maritati et al. (2016). The major domains were summarised in Table 1 along with their correlative region in Australia. Each major domain was split into several units which were fully characterised in Table A2 (Appendix A) and Table 3. The provinces of greatest interest for the project are the regions closest to Totten Glacier and its catchment. This means that Charcot Terrane and the Undifferentiated Indo-Antarctic supersuites were not focused on. The basement to the Aurora Basin region also had no known correlation with any province, regardless, it was included into the analysis since it forms part of the Totten Glacier catchment and will likely have a distinct detrital signature.

Intrusives

Aurora Subglacial Basin

Knox Rift

Indo- Antarctica

Albany-Fraser Province

West Mawson

East Mawson

Fig. 6. Interpretation of the basement geology of Wilkes Land, East Antarctica. The major tectonic regions and faults were adapted from Aitken et al. (2014) and Maritati et al. (2016). SZ= Shear Zone, IAAS= Indo-Australo Antarctic Suture. 25

2.2.1 Albany-Fraser Province region The Albany-Fraser Province (AFP) region of Wilkes Land contains outcrop that has a confirmed affinity with the AFP of Australia (Sheraton et al., 1992; Black et al., 1992). The extent of this region in Wilkes Land is shown in Fig. 7. This Wilkes AFP region was divided into four main units (Fig. 7, D) which were distinguished by their differences in magnetic character (Fig. 7, A-B); AFA, AFB, AFC and AFD. The unit AFA has the greatest positive magnetic character and AFD had the strongest negative magnetic character. They were also separated on accounts of texture; AFB had a very distinct mottled look to it, AFA seemed to form more coherent blebs and was associated with a gravity high, AFC had a very smooth character, and AFD formed coherent blebs. One structure identified in the area which was interpreted to be a fault (Fig. 7) and forms a guide for locating Vanderford Glacier. In relation to the other regions, the AFP region has the strongest positive magnetic (TMI, Fig. 7, A) and gravity anomalies and a very distinct stippled look in 1VD magnetic data (Fig. 7, B). The unit H (red unit, Fig. 7, D) also has a strong positive response but cross-cuts a major domain boundary and some AFP units as well and has hence been included as its own unit rather than an extension of AFA or a component of the West Mawson region.

Fig. 7. The Albany-Fraser region of Wilkes Land. A. Total Magnetic Intensity Map. B. First Vertical Derivative Magnetic Map. C. Isostatic Residual Anomaly Gravity Map. D. Geological Interpretation.

2.2.2 West Mawson region The West Mawson (WM) region takes up the largest amount of area in Wilkes Land, its extent shown in Fig. 8. There are three main geological units/supersuites which make up this region, these were all distinguished by their magnetic character. There is a vast difference in texture of magnetic anomalies in comparison to the AFP (2.2.1, Fig. 7), the textures here are smoother and less stippled. Though this can be said to contribute from lack of data density in the area and from ice sheet smoothing, there is still a genuine difference seen even with the sparse data. The extent of the WM region followed some interpretations made by Maritati et al. (2016), but altered the upper section near Knox to AFP material as the geophysical character did not match WM material (had the characteristic AFP stippled look). WMA generally has a patchy, strong positive magnetic character, WMB also shows a patchy character but formed a weaker magnetic response, and WMC is characterised by a magnetic low and generally looked smoother. A linear feature on the right side was interpreted as a fault (Fig. 8). The gravity low seen (Fig. 8, C) also marked the Moscow University ice shelf cavity. The accompanying magnetic low (Fig. 8, A-B), also supports the interpretation of a fault but could also be an intrusion.

Fig. 8. West Mawson region of Wilkes Land. A. Total Magnetic Intensity Map. B. First Vertical Derivative Magnetic Map. C. Isostatic Residual Anomaly Gravity Map. D. Geological Interpretation.

2.2.3 East Mawson region The East Mawson (EM) region had quite sparse data with large gaps in between lines (Fig. 9); this made it very difficult to interpret the supersuites and relative boundaries. On a whole, the EM region was defined by much less ‘cluttered’ high and low responses, with lower concentrations of magnetic and gravitational highs in comparison to AFP and WM. Structural boundaries were adapted from Aitken et al. (2014) and were used to understand the extent of the EM region (Fig. 9). There were four identified units in the area which all had distinct magnetic characteristics; their contacts between the gaps in data were extrapolated. EMA was defined by magnetic and gravity highs which were smooth and coherent, EMB showed moderate magnetic responses with a patchy character and a slight gravity low. EMC had a very smooth low magnetic response and EMD had a strong negative magnetic response with a character similar to the intrusive L unit.

Fig. 9. East Mawson region of Wilkes Land. A. Total Magnetic Intensity Map. B. First Vertical Derivative Magnetic Map. C. Isostatic Residual Anomaly Gravity Map. D. Geological Interpretation. 28

2.2.4 Knox Rift region Knox Rift region, as classified by Aitken et al. (2014) and Maritati et al. (2016) encompasses many different blocks but has been reclassified into a larger generalised area (Fig. 10) for simplicity. This will not impact further analyses as the Totten Glacier does not sample this area. The unit KA (Fig. 10) makes up the ‘Bunger Hills’ (BH) block (see Aitken et al., 2014) and most likely relates to the AFP. The units KB and KC make up the basement of the Knox Subglacial Basin (KSB) area (see Maritati et al. 2016). These units were separated on basis of magnetic intensity, especially since the gravity data was too patchy. The faults and extent of the tectonic domain were adapted from Maritati et al. (2016) for this area, especially around unit KA, mainly from the data sparsity (especially in gravity). KB and KC could be a part of the WM area as they look magnetically similar, but a large gravity low meant that there was something a little different occurring here. There is quite a stark contrast in geophysical character between the BH (unit KA) to KSB (units KB + KC) blocks. The KSB region looks much smoother whereas the BH area shows a similar stippled look to the units AFA and AFB in the Wilkes extension of the AFP (Fig. 7).

Fig. 10. Knox Rift region of Wilkes Land. A. Total Magnetic Intensity Map. B. First Vertical Derivative Magnetic Map. C. Isostatic Residual Anomaly Gravity Map. D. Geological Interpretation.

2.2.5 Aurora region The basement of the Aurora region, also known as the Aurora Subglacial Basin, is shown in Fig. 11. One striking feature that this area has is that there was a strong negative gravity signature that made up most of it (Fig. 11, C). Overall, it shows a lower average magnetic response in comparison to the other units and has a more smeared look in 1VD but this could be attributed to thicker ice in the area (average thickness 3500-3600 m; Wright et al., 2012). The low gravity response and smooth low elevation n topography data was the main reason why the area was primarily defined as a basin. The units separated out in the area have a much higher degree of uncertainty in comparison to the other regions from the lack of data density.

Fig. 11. The Aurora region of Wilkes Land. A. Total Magnetic Intensity Map. B. First Vertical Derivative Magnetic Map. C. Isostatic Residual Anomaly Gravity Map. D. Geological Interpretation.

2.2.6 Other Components The units H, M and L seemed to cross-cut major tectonic units and boundaries and were interpreted to be three different intrusive events (Fig. 12). H and L were quite easily discernible in TMI magnetic data as they were characterised by either strong negative or positive anomalies. The unit L in the AFP region had a strong negative magnetic anomaly; the gravity signature was moderately positive. Unit M has a weaker positive magnetic response in comparison to unit H and a slightly weaker gravitational response, its extent was difficult to interpret since the data was quite sparse and was extrapolated (Fig. 12). From the extrapolation of unit M, it seems to form relatively larger intrusions and is more associated with the Indo-Antarctic and Aurora regions and was therefore classed separate to H even though it contains a relatively strong positive magnetic response. In IRA gravity data, the units were much more difficult to differentiate from the rest of the area.

Fig. 12. The units ‘H’, ‘M’ and ‘L’ that cross-cut other units and tectonic boundaries. A. Unit M near the Aurora and Charcot regions. B. Corresponding TMI magnetic data. C. H and L units near the AFP and WM regions. D. Corresponding TMI magnetic data.

2.2.7 Composite Bedrock Geology Map The extent of the basin cover in the Wilkes Land area is shown along with the geophysical data used to interpret them in Fig. 13. The subglacial topography was not used as extensively as the sedimentary thickness data since there could still be cover in areas with topography. Therefore, by combining topography and sedimentary thickness data the interpretations were easier to make.

The sedimentary thickness data was classified into three unique categories for both the 10k and 20k data grids, these are shown below:

- No Basin; 0 m - Possible Basin: 0-1000m - Basin: 1000+ m

The composite surface geology map is shown in Fig. 14; here the basin cover was superimposed over interpreted basement material (Fig. 6). The basins that have been identified include the Knox, Sabrina, Aurora, Aurora-North, Vincennes, Frost and Law Dome basins.

The area near the Totten Fault shows ‘basin’ material, but represents the Totten ice shelf, other areas around the coast that also showed the same signature were also associated with ice shelves and were not included. The uncertainty was quite large for where the exact extent of the basin cover could reach since the sedimentary thickness data is very approximate and carries many uncertainties. The Vincennes Basin and the Aurora Basins were primarily interpreted from gravity data as there is a strong negative response near them (Fig. 9, C for VSB, Fig. 11, C for ASB). The ASB shows incisions within topographic highs (Fig. 13, B), these could represent smaller, overdeepened basins (Cook and Swift, 2012).

Law Dome

Aurora North Sabrina

Frost

Knox

Aurora

Vincennes

Fig. 13. Geophysical data used to create composite surface geology map. A. Interpreted subglacial basins overlayed onto sedimentary thickness. B. Labelled and interpreted subglacial basins with subglacial topography.

Basement units

Intrusives

Albany-Fraser Province

West Mawson

East Mawson

Aurora Subglacial Basin

Knox Rift

Indo- Antarctica

Fig. 14. Composite surface geology map of Wilkes Land, East Antarctica. The basins are shows as translucent white cover over the coloured basement units. 34

2.3 Conclusive Remarks

Magnetic TMI-RTP anomaly data of the correlative Australian regions and their interpreted supersuites (Fig 15, 16) have been broadly correlated to the interpreted Wilkes Land basement geology in Table 2. This includes related geo- and thermo-chronological data. Table 3 shows the legend of all the units of Wilkes Land, including both basement and basin components.

The AFP domain of Wilkes, which is bounded by the Aurora Fault and the Totten SZ, is thought to most relate to the Nornalup Zone most of the Australian AFP (Aitken et al., 2016b; Morrissey et al., 2017), whereas the area near the BH forms part of the Biranup Zone (Tucker et al., 2017) (Fig. 15). Granites classified by Brisbout (2014), from the Recherche SS and Esperance SS in the Nornalup Zone show that both the Esperance and Recherche SS (Fig. 15) have high specific gravity and high magnetic susceptibility, with some exceptions from the Esperance SS that show markedly stronger magnetic susceptibilities. This could help to separate out AFA and AFB (Table 3) signatures which were differentiated greatly from their difference in texture. As for unit L, Zhang et al. (2012) distinguished a late felsic dyke or intrusion at 1100-1110 Ma, as L seems to cross cut all the other units, even L, it could be this late felsic intrusion. It is difficult to say whether H and L actually cross cut each other since magnetic and gravity data can only show a 2D representation of a much more complex 3D system. Therefore, both features could be at completely different depths (Dentith and Mudge, 2014).

The Windmill Islands have high temperature charnockites (known as the Ardery Charnockite) which generates a dominant gravity high (Bailey et al., 2016). This unit was interpreted as a cluster of intrusion which occurred after the main phase of deformation from 1200-1160 Ma and most correspond to Esperance Supersuite magmatism in the (Australian) AFP (Zhang et al., 2012; Morrissey et al., 2017). The Moodini Supersuite, Madura Province (Fig. 16), also had magmatism which occurred around 1225-1160 Ma and has similar characteristics to the Esperance Supersuite (Zhang et al., 2012; Smithies et al., 2015b; Morrissey et al., 2017).

Therefore, the unit that would most correspond the Ardery Charnockite, and hence to Esperance Supersuite (SS) magmatism is either unit H or AFA. The reason why it could be unit H is because it is only seen in the AFP and WM areas, much like the Esperance and

Moodini Supersuites are only seen in their regions. Therefore, AFA could form part of the Recherche Supersuite, though this is difficult to conclude as AFB shows similar a similar gravity and magnetic high, though is differentiated on geophysical texture. The Ford Island Granite of the Windmill Islands creates a localised gravity low near the Ardery Charnockite (Bailey et al., 2016). A unit which mimics this behaviour is AFD which is closely associated with both units AFA and AFB.

From the WM region, the main supersuite that can be correlated in the area is the Moodini SS. The other interpretations of geology in the WM region come from a tentative correlation with core (GSWA publications), magnetic susceptibility and specific gravity (Brisbout, 2014).

The cores FOR 10/11/12 are all part of the Undawidgi SS, these range from 1488-1500 Ma, they can be broadly classed as metagranites (Spaggiari et al., 2015). Similar rocks in the Biranup zone (metamonzogranites/syenogranites, etc.) had a moderate specific gravity and a very low to mixed magnetic susceptibility (Brisbout, 2014). This would best describe unit WMB.

The magnetic low in the Forrest Zone (FOR004; Fig. 15) corresponds to the Toolgana SS which contains (leucogranite and granodiorite) gneisses ~1611-1613 Ma in age that exhibit metamorphism from 1179-1185 Ma, respectively (Spaggiari et al., 2015). In relation to the WM region, this strong magnetic low could relate to WMC. Even though the unit L exhibits a similar strong magnetic low, this unit has been interpreted to cross-cut many older structures and boundaries, meaning that is would be much younger than the average Toolgana SS age of 1600Ma.

RS ES

Fig. 15. Adapted from Spaggiari et al. (2015), interpretations from Spaggiari et al. (2012), reduced-to- pole (RTP) aeromagnetic image of East AFP and the Eucla Basin with major tectonic basement units and simplified structures. ES= Esperance Supersuite in white, RS= Recherche Supersuite in yellow, MS= Moodini Supersuite in pink.

The EM region is thought to correlate to the eastern extent of the Gawler Craton, one striking magnetic feature in this area is the Hiltaba SS (Fig. 16). This SS could relate to EMA. This largely remains speculation as the data loses quite a lot of density in this region. In Wilkes Land the overprinting H and L units does not extend into the East Mawson. This is similar to Australia, here the ~1100-1140 Ma (Esperance and Moodini SS) magmatic events overprint the AFP, Madura, Forrest and Coompana provinces but exclude the Gawler Craton (Spaggiari et al. 2015).

SP S

Coompana Province MC

H GV S Gawler Craton SP GV S

SP SF S C

Fig. 16. The Gawler Craton, data from SARIG (Geological Survey South Australia, 2017), interpretations from Dutch et al. (2015) with TMI- RTP Magnetic Data. HS= the Hiltaba Supersuite in white, GV= the Gawler Volcanics in yellow, SPS= the St Peter Supersuite in blue, the circled SPS area is Late Mesoproterozoic, MC= Mulgathing Complex in pink, SFC= Sleaford Complex in grey.

Table 2 Major Antarctic tectonic regions correlated to possible matching Australian supersuites (SS) with geochronological and thermochronological data. MA: Madura Province, CP: Coompana Province. Data was summarised from Cawood and Korsch (2008), Boger (2011), Dutch et al. (2015), Spaggiari et al. (2015), Smithies et al. (2015b), Wingate et al. (2015), Scibiorski et al. (2016), Kirkland et al. (2015), and Kirkland et al. (2017). Wilkes Land Region Australian Correlative Australian Correlative Supersuites (zircon U-Pb Data) (Hornblende Ar-Ar Data)

Albany- Fraser Broad overprints Province - Widespread 1200-1150 Ma Stage I: 1345-1260 Ma, Stage II: Ma.

- H unit/ L unit - Esperance SS: 1200-1140 Ma

- AFA - Recherche SS: 1330-1280 Ma

- AFBAFD - Nornalup Zone: 1800-1760 Ma - NZ: cooling from peak conditions at c. 1170 Ma - Biranup Zone: 1800-1650 Ma - BZ: cooling from peak conditions c. 1190 Ma

West Mawson - H unit - Moodini SS (MA): 1181-1125 Ma

- Moodini SS (CP): 1192-1140 Ma

- Haig Cave SS (MA): 1415-1389 - WMAWMC Ma (including the Loongana Arc (MA): 1410 Ma)

- Undawidgi SS (CP): 1490 Ma - USS: 1174 Ma

- Toolgana SS (CP): 1610 Ma - TSS: 1150-1179 Ma metamorphism

East Mawson

- EMAEMD - Multiple tectonothermal events - Widespread metamorphism between c. 2560 and 1450 Ma and deformation: 1630-1600 Ma

- Sleaford & Mulgathing complexes: 2560-2510 Ma

- Gawler Range Volcanics and Hiltaba SS: 1600-1575 Ma

- St Peter Suite: 1647-1604 Ma

Table 3 A legend and summary of the geological units (both basement and basin components) of Wilkes Land, East Antarctica, defined from the mapping process.

3. Erosional Spatial Analysis

This section focuses on the spatial erosion analyses of Wilkes Land. This was done using existing ice sheet models from Aitken et al. (2016) combined with the basement and bedrock geological maps from Section 2 (Figs 6, 14). The ice sheet models provide the numerical and physical maps of the ice sheet under different forcings, and the geological maps provide the spatial reference/zones. The ice sheet models were created by Aitken et al. (2016) from an open-source, 3D, thermodynamic coupled ice sheet/shelf model called the Parallel Ice Sheet Model (PISM). These models were simulated to run for 20, 000 years so that a steady-state system could be modelled, but ultimately are “retreat” models which simulate retreat through various air and temperature conditions.

The resolution of the ice sheet models was quite coarse at 20 km, but it allowed for continental-scale simulations of dynamic grounding line behaviour (retreat processes, for this model). Golledge et al., (2015) assessed the difference of running the model on a finer resolution of 10 km but found that both 10km and 20km resolutions reached identical final ice volumes. The 20 km resolution experiment simulated slightly greater ice loss, and therefore Golledge et al. (2015) concluded that fully dynamic simulations of the present-day ice sheet can use either resolution over multi-millennial timescales at a continental scale. Therefore, the subsequent modelling in Aitken et al., (2016) followed this principle.

Four different ice sheet states were modelled at this resolution: these were named State 0_0, State 4_1, State 8_2 and State 12_5. The first number in the name corresponds to increases in air temperature and the second number corresponds to increases in oceanic temperatures from present-day conditions. The present-day conditions formed the initial value for each ice sheet state which was run separately each with their own air and ocean temperature forcings.

To map the erosion associated with each ice sheet state, spatial analyses will be applied to the ice sheet models. In order to do this the erosion potential was defined at the base of the ice sheet. The ice sheet models were able to compute various proxies for erosion, but this would add a lot of complexity (Licht and Hemming, 2017). Therefore, to adhere to a simple model, the sliding (basal) velocity squared principle was used as a proxy for erosion potential (e.g. Herman et al., 2015). This only accounted for abrasion and quarrying processes and did not account for material that could be plucked or basally accreted (Herman et al., 2015).

3.1 Methods The results from Section 2 were "supersuite" level interpretations of Wilkes Land basement and bedrock geology. In order to gain a source spectrum for the Totten catchment the following steps were applied:

1. Mask and process ice sheet model results 2. Apply zonal statistics tool to the erosion potential map 3. Extract the total erosion potential of each geological unit 4. Graph and compare the results in order to gain a source spectrum for each ice sheet state.

The process of the zonal statistical calculation was conducted on ArcGIS. The first step was to create analysis mask from the basal velocity data. This analysis mask set the boundary for the spatial analyses and set up a mask for grounded ice. Then the ‘Con’ function was used to set the pixels for the mask. Following that the mathematical function ‘Power’ was used on the mask to get the basal velocity squared as a raster data set. The spatial erosional analysis used the zonal statistics function, this calculated the raster (basal velocity squared) of the ice sheet in zones (mapped units) defined by a vector file (geological map). This prodecued a table of different statistical information (e.g. the mean, sum, max, min, range, etc.).

The reason why the basal velocity was squared was because Herman et al. (2015) demonstrated that the glacial erosion rate was proportional to the ice-sliding (basal) velocity squared. Here the maximum erosion rates were concluded to occur around the steeper, faster parts of the glacier and low erosion rates corresponded to the glacier front, or to slowly moving accumulation areas (Herman et al., 2015). This was a rough proxy for erosion potential as there were many uncertainties associated with the generated erosion potential/amount.

There could be issues with detrital signature bias when determining provenance in areas with a lot of sedimentary rock cover. The “bedrock” model gave a more realistic idea of the Wilkes Land detrital signature, and the basement model filled in gaps of knowledge where there was no basin data.

3.2 Results 3.2.1 Ice Sheet State 0_0

This state simulated an ice sheet with conditions that were analogous to present-day conditions. The greatest basal velocities occurred at the coast near the Albany-Fraser Province (AFP), West Mawson (WM) and the East Mawson (EM) regions of Wilkes Land (Fig. 17, A, Table 3).

In the zonal analysis of the basement geology (Fig. B1, Appendix B) the zones were classed by basement units and the sum of basal velocity2 was used to provide the erosive signature for the ice sheet state. The WM region accounted for ~ 64% of the total sum of basal velocity2. The basement units that had the greatest cumulative erosion potential were WMA, AFB, EMD and the intrusive unit L (Table 3).

When the same analysis was run on the composite bedrock geology map, basin material made up about 30% of the total signature (Fig. 17, B). The units that lost signal due to cover included AFA and L, both in the AFP area. Most of their signature was taken up by the Law Dome (Fig. 13) basin which made up ~55% of total basin material. The units that were not covered by basins include WMA, WMC and EMD. These still showed the same peaks as they did in the basement analysis (Fig. B1, Appendix B). The basins that contributed the greatest amount to the overall basal velocity (erosive signature) were the Law Dome Basin and the North Aurora Basin. Therefore, the overall erosional signature expected for this ice sheet state was mainly comprised of WMA, Law Dome basin and EMD, with minor components of AFP units and the North Aurora basin (Table 3).

Law Dome

Sabrina Frost Aurora North

Knox

Aurora

Vincennes

B. Ice Sheet State 0_0- Bedrock 6% 16% 9% 14000000 5%

12% LD 12000000 1% AN 24% 10000000 1% 16%

(Sum) 6% 2 8000000 LD 2% 6000000 AN

4000000 Basal Basal Velocity

2000000

KA KB

AFA AFB

AFC AFD

ABA

ABC

EMA EMB

EMC EMD

Frost

Knox

WMA WMB

WMC

Aurora

Sabrina

Undif IA Undif

Aurora_N…

Charcot L Charcot

Charcot H Charcot

Vincennes Law Dome Law Fig. 17. Ice sheet state 0_0 bedrock statistical results. A. Bedrock geology map with basal velocity contours, the edge of the contours shows the margin of the ice sheet, where the greatest velocity is in black. B. Resulting histogram showing the sum of basal velocity2 as defined by the bedrock geology units and a corresponding pie chart showing the contribution of each unit to the total. The white colour represents basin material; the others correlate to basement geology.

3.2.2 Ice Sheet State 4_1 Ice sheet state 4_1 had forcing applied from initial conditions with an increase of 4°C for air temperature and 1°C for ocean temperature. The differences of note between state 0_0 and state 4_1 included the position of the ice sheet margin, and the areas of greatest cumulative erosional potential (Fig. 18). The retreat of the ice sheet was not uniform, there was substantial retreat along Totten and Moscow University, with a residual cap that persisted on Law Dome (Fig. 18, A).

The zones that had the greatest basal velocity at this current ice sheet state moved from further inland, making the signature mainly comprised of WM and smaller sections of the EM and AFP components (Fig. 18, A). The results from the basement analysis are shown in Fig. B2 (Appendix B). The intrusive unit H showed the greatest cumulative erosion potential, followed by L, WMA and WMB (reference- Table 3). The reason for this high H peak can be seen in the velocity contours which were greatest near the unit (Fig. 18, A). The ‘intrusive’ supersuites made up 42% of the total possible signature for the basement analysis of this ice sheet state.

The subsequent bedrock analysis showed that basins made up 27% of total signature (Fig. 18, B). The three different basins that made up this 27% included the Sabrina, North Aurora and Frost Basins. This was different to state 0_0 which mostly sampled the Law Dome basin. Both states still had a North Aurora signature but state 4_1 showed a lower potential for it. Sabrina basin had the largest cumulative erosion potential out of the other basins. Between bedrock and basement analyses units H, WMA and AFB yielded the same values (since they had no basin cover), whereas WMB and KC were covered by the Sabrina and Knox basins, respectively, and yielded different values.

The bedrock units that had the greatest potential to erode in state 4_1 were H, the Sabrina SB and WMA. Here the intrusive units made up 35% of the signature. This strong intrusive signature was good since it may provide an important marker for provenance. This was because, in Section 2, this unit was correlated to an Australian supersuite, allowing for an age and possibly a composition to be defined.

TG Law Dome MU

Sabrina Frost Aurora North

Knox

Aurora

Vincennes

B. Ice Sheet State 4_1- Bedrock 20000000 20% 18000000 26% 2% K S 16000000 5% AN

14000000 7% 9% S (Sum)

2 12000000 1% 3% 17% 1% 10000000 6% 1% 8000000 6000000

Basal Basal Velocity 4000000 2000000 AN

0 K

KA KB

AFA AFB

AFC AFD

ABA

ABC

EMA EMB

EMC EMD

Frost

Knox

WMA WMB

WMC

Aurora

Sabrina

Undif IA Undif

Charcot L Charcot

Charcot H Charcot

Vincennes

Law Dome Law Aurora_North Fig. 18. Ice sheet state 4_1 bedrock statistical results. A. Bedrock geology map with basal velocity contours. The black, dashed line shows the approximate position of the ice sheet margin. B. Resulting histogram showing the sum of basal velocity2 as defined by the bedrock geology units, the corresponding pie chart showing the contribution of each unit. The white colour represents basin material; the other colours correspond to basement geology units. MU= Moscow University Ice Sheet, TG= Totten Glacier.

3.2.3 Ice Sheet State 8_2 This ice sheet state simulated basal velocity2 with an 8°C increase in air temperature and a 2°C increase in ocean temperature. In relation to both state 0_0 and state 4_1 the ice sheet margin moved further back into the landmass (Fig. 19). The largest amount of retreat occurred near the EM region and the area near AFP. The main regions that were being sampled in this state included the WM, Knox Rift, and part of the EM area (Table 3, Fig. 19).

The results from the basement analysis are shown in Fig. B3 (Appendix B). In the analysis KC and L had the greatest cumulative erosion potential, followed by WMB and WMA. There was no AFP signature in this state, in comparison to the previous two states. There also was a much smaller range of signatures; most of the signatures came from the WM (including intrusive unit L) region and Knox region.

In the bedrock analysis (Fig. 19), basins made up 75% of the total signature. The contribution of the basins to the total signature was more than double of the previous two states. The WM region made up the remaining 24% (L unit included). The Basin that had the greatest cumulative erosive potential was Knox, followed by North Aurora and Sabrina Subglacial Basins (Fig. 19). The overall signature for this state was mainly WM and basin material.

Law Dome

Aurora North Sabrina Frost

Knox

Aurora

Vincennes

5% B. 7% 14% Ice Sheet State 8_2- Bedrock S 16000000 10% 14000000 K 2% K 2% 12000000 35% AN (Sum) 17% 2 10000000 F 7% 8000000 AN 6000000 S

4000000 Basal Basal Velocity 2000000 F

KA KB

AFA AFB

AFC AFD ABA

ABC

EMA EMB

EMC EMD

Frost Knox

WMA WMB

WMC

Aurora

Sabrina

Undif IA Undif

Charcot L Charcot

Charcot H Charcot

Vincennes Law Dome Law

Aurora_North Fig. 19. Ice sheet state 8_2 bedrock statistical results. A. Bedrock geology map with basal velocity (log) contours. The black, dashed line shows the approximate position of the ice sheet margin. B. Resulting histogram showing the sum of basal velocity2 as defined by the bedrock geology units and the corresponding pie chart showing the contribution of each unit. The units follow the colour scheme of the basement map.

3.2.4 Ice Sheet State 12_5 The final ice sheet simulated a 12°C increase in air temperature and a 5°C increase in ocean temperature. In this state the ice sheet margin showed the greatest amount of retreat (Fig. 20, A) and had migrated back approximately 400-500 km from the initial state (Fig. 17, A). In the basement geology analysis (Fig. B4, Appendix B) the WM area made up 79% of the total signature with minor components from Aurora basement and the Indo-Antarctic terrane. Since the ice sheet retreated so far back, this was the first time that the Aurora basement made up part of the signature. The unit with the largest response was WMB, followed by WMA and WMC.

The zonal statistics of the bedrock geology showed that basins made up 85% of the signature, which left the final 15% as exclusively WM material (Fig. 20, B). In relation to the basement analysis, almost all the previous signatures were lost or reduced by the basin cover. The units most affected by the basin cover were from the WM region, these were reduced to ~15% from 79%,

The basin that has the greatest erosive potential was Aurora, followed by North Aurora. The Aurora SB made up almost 50% of the total signature and was a significant component for the ice sheet state. Overall, the range of basement material being sampled was very small and there were at least 5 different basins which added to the signature for this ice sheet state, the most dominant signature coming from Aurora SB (including North Aurora).

Law Dome

Aurora North Sabrina Frost

Knox

Aurora

Vincennes

2% 1% Ice Sheet State 12_5- Bedrock 1% S 16000000 9% 7% K 7% 14000000 A 12000000

25% (Sum) 2 10000000 AN A 8000000 47% AN 6000000

4000000 Basal Basal Velocity 2000000 K S

KA KB

AFA AFB

AFC AFD ABA

ABC

EMA EMB

EMC EMD

Frost

Knox

WMA WMB

WMC

Aurora

Sabrina

Undif IA Undif

Charcot L Charcot

Charcot H Charcot

Vincennes

Law Dome Law Aurora_North Fig. 20. Ice sheet state 8_2 bedrock results. A. Bedrock geology map with basal velocity (log) contours. The black, dashed line shows the approximate position of the ice sheet margin. B. Resulting histogram showing the sum of basal velocity2 as defined by the bedrock geology units and the corresponding pie chart showing the contribution of each unit. The units follow the colour scheme of the basement map.

3.3 Final Comparison and Conclusive Remarks

The major trends that were observable from states 0_0 to 12_5 was the retreat in the ice sheet margin associated with increases in air and ocean temperature forcing (Fig. 21). This forcing caused the ice sheet to destabilise and find a new steady state position much further back than the initial state (most similar to state 0_0). The ice sheet also did not uniformly retreat with increased climatic forcing (from state 0_0 to 12_5, Fig. 21). Each point of the grounded ice sheet had its own boundary conditions which had to be overcome before retreat could occur. The retreat caused by state 8_2 and could be attributed to the removal of ice shelves after the additional increase in ocean temperatures. This could be from the ice shelves no longer being sustainable after oceanic temperatures increased by 2°C.

Fig. 21. A summary of state 0_0 to 12_5. The extent of the ice sheet ice margin is shown in black, the (log of the) basal velocity contours are coloured blue in blue. Each ice sheet state retreats from an initial model (closely mimics state 0_0) to reach a new steady state position.

From both the bedrock and the basement erosional analysis, the major trends showed that the WM region covered the largest part of the study area and was a key component of many signatures (Table 4). The bedrock map had the most realistic signature when spatially analysed. The reason for this was that there is sediment cover in the area; the area was largely sculpted by a succession of ice sheet configurations different to the present-day one (Young et al., 2011). Therefore, by understanding where the basins are, what they are (or could be) constituted of, and how much of their potential to be an erosional signature in different ice sheet states, the IRD, and the stability of the system producing it, can be better understood.

Where there is no data on basin material or constituents, basement trends can be used to predict what the basins could constitute of when there is limited/no data on the basin or area.

The comparison between the two analyses also showed that many areas of basement preferentially got left out of the final erosive signature (the bedrock signature) as they were covered by a basin (Table 4). This overlap between the basin and the basement material could provide an understanding of potential sources that generate the basin fill. This also relies on understanding where other sediments could be coming from (not just locally derived sediments), and how they are influenced by topography. Sediments are most likely to come from the interior from proximal highlands.

For example, Law Dome depletes part of the AFB and all the L signature, and could be enriched in those units, in state 0_0. Otherwise the materials that could be derived in this basin could broadly constitute of AFP and WM regional material. Sabrina could constitute of broadly EM and AFP region material, Knox SB could broadly constitute of AFP and Indo- Antarctica, Aurora would have a mixture of regions but mainly AFP and Indo-Antarctica in the study area, Aurora North could have mainly WM, possibly Aurora basement and minor AFP material, and Vincennes will largely constitute of EM material (from the study area).

The trends associated with the basement analyses showed that from state 0_0 to state 12_5 the WM region covered the largest part of the study area and was a key component of many ice sheet states. The intrusive units were the next biggest contributors to erosional potential, they were apparent in every ice sheet state apart from 12_5. For the AFP province, the unit that was most sampled was AFB and L mainly in states 0_0 and 4_1, after state 4_1 the AFP signature was lost. The EM region had a relatively low signature for each state, apart from 0_0, and was represented mainly by the unit EMD. The Knox, Indo-Antarctic and Aurora

52 basement regions made up the smallest portions of total signature, apart from KC which was the largest component of 8_2.

The bedrock trends for each ice state are shown in Table 4. Much like the basement analysis these sample greater areas in state 0_0 and show could show up to 3 definable basement region signatures of the WM, AFP and EM with the two basin signatures Law Dome and Aurora North. State 4_1 erosion potential was defined by a large component of intrusive material, as well as WM and Sabrina Basin material. The intrusive material can provide a definitive age, allowing for a better link to the IRD record. State 8_2 was largely defined by basin material including Knox, Aurora North, Sabrina and Frost Subglacial Basins, with minor intrusive material (L) and WM material. State 12_5 was > 80% basin and largely made of Aurora Basin material, with minor WM basement material.

Summarised IRD data from Williams et al. (2010), Cook et al. (2014) and Pierce et al. (2014) (Table 5) could form the basis of linking modelled erosional potential to the dated IRD record in order to better understand how this material was eroded, from where it was eroded, and how it was entrained, and how it was subsequently transported and deposited.

Table 4 Basement and bedrock potential erosional signatures for each ice sheet state. Any region that added up to <10% was excluded for the final signature. AN=Aurora North, LD= Law Dome, S=Sabrina, K= Knox, A=Aurora, F= Frost.

Ice sheet state Basement Erosional Signature Bedrock Erosional Signature

0_0

AFP (33%) > WM (31%) > WM (30%) > Basins (29%) > AFP EM (18%) > Intrusives (15%) (20%) > EM (18%)

S K AN

4_1

Intrusives (42%) > WM (35%) Intrusives (35%) > Basins (27%) > > AFP (10%) WM (19%)

K AN 8_2 F

WM (36%) > Knox (35%) > Basins (75%) > WM (17%) Intrusives (23%) > EM (15%)

S K

AN A 12_5

WM (79%) > Aurora Basins (84%) > WM (15%) Basement (10%)

Table 5 A summary of Wilkes (and Adelie) thermochronological ages (hornblende Ar-Ar dating) of IRD from ODP Site 1165. Wilkes: 1100-1300 Ma, Adelie: 1450-1750 Ma (Williams et al., 2010). Wilkes= 1035-1315 Ma, 60% with 1151 Ma mean age (Cook et al., 2014). Wilkes= 1100-1200 Ma (peak ~1150 Ma) and 1440-1500 Ma (peak ~1494 Ma), Adelie= 480-520 Ma with small populations of 1608 and 1715 Ma (Pierce et al., 2014).

Age of IRD from Williams et IRD from Cook et al. IRD from Pierce et al. sedimentary al. (2010) (2014) (2014) core Late Pliocene 2.6 Ma N/A Wilkes= 33% Wilkes= 30% 3.1 Ma N/A Wilkes= 50% N/A 3.2 Ma N/A Wilkes= 30% N/A Late-Miocene to Mid-Pliocene 3.5 Ma Wilkes= 30-35% Wilkes: 35% 4.6 Ma N/A Wilkes= 40% Wilkes= 35-45% 4.8 Ma Adelie= ~40% Wilkes= 0% 7 Ma Wilkes= ~40% N/A Wilkes= 55%

4. Discussion

4.1 Link to IRD records: Model Uncertainties

4.1.1 Geological Uncertainty The geophysical data is limited in the area; there is only magnetic susceptibility and density which has large gaps in-between flight lines, and therefore the i. This is especially true when it comes to correlating different geological provinces. The Antarctic regions that are easiest to correlate to Australia (and other continents) are best defined at the coast. The boundaries and extent of the domains become harder to classify the further you get into the Antarctic land mass. Therefore, areas further from the coast of Wilkes Land were increasingly difficult to interpret and correlate to Australia because of geophysical data sparsity. The other issue associated with mapping the area was that the ice sheets created smearing within the geophysical data; this can make it easy to over-interpret structures and units.

This smearing effect is caused by the satellite which is used to collect data for many of the Antarctic datasets; i.e. the Gravity Recovery and Climate Experiment (GRACE), which has an effective bandwidth that can be reached before, regardless of processing, every single signal is smeared out (Velocogna and Wahr, 2013).

There is a stark difference in geophysical characteristics (intensity and texture) for the regions and many of the units within the regions. Correlating these units with provinces in Australia has proven quite difficult, the most that can be achieved is a ‘best guess’. A lot of the Australian provinces that were used for correlation to Wilkes Land have very little outcrop and correlating them by geophysics is the first step towards better characterisation. This is still a ‘best guess’ since areas in Wilkes that have a similar magnetic and gravitational character to Australian supersuites may not be geologically the same. This shows the need for detrital studies, not only to show the response of the ice sheet, but to also gain a proxy of what material could actually be coming out of the area. Therefore, the next section focuses on assessing what material is being eroded from the Totten Glacier area to understand what could potentially form the Wilkes Land IRD ‘signature’.

The uncertainty within the characterisation process of Wilkes Land geology is amplified from the fact that many of the Australian correlative provinces are buried deep under cover. Therefore, there is limited information that can be derived from these areas; mainly limited to

56 geophysics and analysis of core samples. How these correlative provinces might extend into Wilkes Land and their exact points of contact is also tentative, for example the Mundrabilla SZ is an area of uncertainty as it could easily cut off the Forrest Zone or other areas in the southern part of Australia.

4.1.2 Ice Sheet Model and ‘erosion potential’ uncertainties The ice sheet models that have been used for this study are location-driven and are not time (and hence climate) constrained. This means that a time-constrained climatic tracer is needed to provide this link; e.g. IRD signatures. This can be difficult to apply as the ocean and air temperature forcings are difficult to interpret a climate for. There are also difficulties associated with the assessment of paleoclimates where there can be localised differences, therefore it is difficult to know truly what a system experienced.

As for the ice sheet models used in the study, climates have been speculated and extrapolated from records of global climate and sea level data (Aitken et al., 2016). Ice sheet state 0_0 best represents the present-day ice sheet (and the predominant setting of the ice sheet since the mid-Miocene (Aitken et al., 2016)). The forcing experienced by state 4_1 could possibly be best represent the climate of the early-Pliocene before the onset of the Pliocene Climatic Optimum (PCO) (~4.5-4.0 Ma) (Fedorov et al., 2013).

Erosion rates are generally a function of the amount of water at the bed, which causes higher basal velocities from enhanced sliding, therefore meaning that where there is an absence of water, erosion rate is zero (Licht and Hemming, 2017). This was the principle behind using the basal velocity squared in this study (see Herman et al., 2015) which formed the basis for the spatial erosional analysis. Though this method was a very rough approach to quantifying erosional potential, it provided a first approximation.

4.2 Link to IRD records: Detrital Transport Mechanisms This study has demonstrated what the possible signature of erosion might be at each ice sheet state but in order to fully relate it to the IRD record the ability for this material to be entrained in the ice sheet, transported and subsequently deposited on the ocean floor needs to be further explored. Since ice sheets are steady-state systems (Schoof, 2007) they will experience periods of melting and re-freezing which are ideal for sediment erosion and entrainment (Licht and Hemming, 2017).

Generally, glacial ice actively entrains sediments primarily as basal debris (Anderson et al., 1980). This is where basal water, which is required for erosion, freezes on the base of the ice sheet, and trapping sediment (Hooke et al, 2013). Entrainment is greatest where basal water and ice velocity are highest, and transport is likely to be greatest where basal conditions change from a hard bed to a deformable, soft bed (Licht and Hemming, 2017). This could include the continental shelf of Antarctica’s perimeter or subglacial sedimentary basins; these often host granular material/ till, which actively deforms and is saturated with meltwater, and can become the main driver of glacier flow with effective stress (Cuffey and Paterson, 2010; Damsgaard et al., 2016).

This debris is subsequently transported around the ocean by icebergs (Gilbert, 1990) which come from calving events. Before the material is able to reach the ice shelf and hence become calved, it must first be subglacially transported from its source of erosion. The main way this occurs is through subglacial water systems (meltwater at the base of the ice sheet, subglacial lakes, ice streams) but can also be elevated upwards as a ‘plume’ of debris through the ice sheet itself (Hooke et al., 2013) and will eventually transport itself downstream, and can result in relatively long transport distances of that material (Licht and Hemming, 2017). The main ways in which ice-rafted debris is transported and subsequently deposited is shown in Fig. 22, with the focus being on glacial sources where iceberg rafting in the main mode/process of transport.

The erosional potentials of the modelled ice sheet states will most likely be different to their possible IRD signature. The reason for this is because sediments can become selectively eroded, entrained, transported and deposited. Therefore, it is necessary to understand the influence of the ice sheet, topography, geology, hydrology and climate on the ice system as a whole.

Fig. 22. A conceptual model of sources, processes and forms of rafted material in the glacimarine environment. The main source and process of the study area is highlighted in red. Adapted from Gilbert (1990).

The transport of debris in ice sheet state 0_0 is related to present-day modes of erosion, entrainment and transport. The dominant way that material is deposited from the ice mass to the ocean is by calving, which accounts for up to 50% of total mass loss to the ocean in Antarctica (Rignot et al., 2013). Miles et al. (2017) recently demonstrated that there was a large, near-simultaneous calving event across six glacial outlets of Porpoise Bay (550 km E of Totten Glacier, Fig. 23). The amount of passive ice in Totten is relatively small at ~4.2% (Fürst et al., 2016) (Fig. 23). Since there are far more calving events that occur near the Vanderford, Moscow University and Porpoise Bay outlet glacier, there can be a greater signature expected from them. In this first state the bedrock analyses showed that the most sampled areas were the coastal points of AFP (including Law Dome basin), WM and EM regions (Fig. 18, Section 3). Of that material, the most that could be expected to be calved under current conditions is the area closest to Porpoise Bay which is the EM region, and Vanderford area which is mainly Law Dome material with minor AFP basement. The WM unit WMA experiences the greatest sum of basal velocity2 and is located right near Moscow University.

500 km

Fig. 23. The maximum buttressing of ice shelves in Antarctica. The black box shows the study area and representative ice shelves which could be outlets of erosive material, the red contour shows where the passive ice shelf is. Adapted from Fürst et al. (2016).

When the system experienced state 4_1 climate forcing, the ice sheet margins retreated to the position seen in Fig. 20 (Section 3). In this state, Moscow University and Vanderford glaciers retreated and no longer have ice shelves, whereas Porpoise Bay and Totten Glacier both could have ice shelves and therefore potentially have calving events (Fig. 19, Section 3).

The current thinning at Totten has maintained a steady speed but is flowing above equilibrium conditions and has been losing mass (~6.8 Gt/yr) (Li et al., 2016). Most of the ice shelf is also grounded very close the hydrostatic equilibrium which means that change in ice thickness could have a large impact on the glacier flow (Li et al., 2016). This is since Totten is largely grounded (>95%, Fürst et al., 2016), and a small loss in ice from the calving front could cause flux changes across the grounding line (Sun et al., 2016).

Li et al. (2016) also stated that the ice velocity of Totten seemed to increase when the ocean temperature was warmer, accompanied by greater thinning rates changes (increases) in areas of fast flow (Appendix B, Fig. B6). Therefore, with the increased climate forcing experienced in state 4_1, there could be more potential for the detrital signatures near Totten, and also Porpoise Bay, to be transported and deposited, in comparison to the more retreated areas of the ice sheet. This is probable given that increased temperatures can cause greater thinning (Li et al. 2016) and more frequent calving events to occur, especially if the increase in ocean

60 temperature causes a decrease in buttressing affects and increase in ocean access (Li et al., 2015, 2016).

Even though the icebergs could undergo more calving off from the ice shelf, the distance of transport of these icebergs could be reduced as the increased ocean temperature may cause faster iceberg melting, a reduced capacity for offshore transport and hence more rapid deposition.

The issue with this state is that there will be two forces that are supplying detritus into the ocean, one will be from ice-rafting of the areas that still have active ice shelves, and the other from glacifluvial processes of the further retreated areas. Transport by meltwater, wind or ocean currents show substantial sorting and rounding of detritus in comparison to transport via subglacial and englacial pathways (Licht and Hemming, 2017).

As for ice sheet states 8_2 and 12_5, both experienced increased ocean temperatures to where ice shelves were no longer sustainable, and the ice sheet margin showed retreated back past the coast of the Antarctic landmass (Fig. 19, 20 Section 3). This lack of ice shelves means that there cannot be any calving events as all of the ice sheet will be grounded. The transport processes that would dominate in these states would be glacifluvial, therefore in these states there will be no ‘IRD’ signatures. The effect of this reduced ice sheet on isostasy, erosion and transport is unknown.

Dynamic topography plays a large factor in the ice sheet models as it forms a major boundary condition, as well as in the evolution of the EAIS in the Aurora subglacial basin (ASB) region which is drained by Totten Glacier (Young et al. 2011; Greenbaum et al., 2015; Sun et al. 2016). It also influences erosion, transport and ice sheet stability (when there is grounding line retreat) (Jamieson et al. 2014). Since the ice sheet models are not time-constrained and all rely on modern-day topography, these processes could be very different for states that show air and ocean temperature forcings and retreat (States 4_1, 8_2 and 12_5).

5. Conclusion The study used a combination of geophysics with ice sheet modelling to test whether a distinctive IRD “signature” could be determined for initial and future (modelled) ice sheet states in Wilkes Land, East Antarctica. This allowed for a tentative link between data sets that were important on their own (IRD for ice sheet dynamics, magnetics for geological characterisation, etc.), but had the ability to provide much more information on a complex system when combined.

The approach showed that as the ice sheet reached a steady state after a period of forcing (air and ocean temperature increases) the area of selective erosion, the position of the ice margin and the erosive signature would all likewise change. Therefore, the modelled erosional potentials were successful in simulating differences in erosion through a dynamic retreating ice sheet.

Though there were a lot of uncertainties associated with each approach, the results showed that the “Wilkes Land” signature was best defined by states 0_0, and in future state 4_1. These two states seemed the most realistic and had the greatest potential for correlating modelled signatures with real IRD data (from Williams et al. (2010) and Cook et al. (2014)). The reason being that these states had ice shelves, hence a potential for IRD (from calving events) generation, and had less input from subglacial basins in the overall erosive signature which could allow for better provenance determination.

The results also showed that if the Totten area reached forcings of greater than 8°C air temperature and 2°C ocean temperature the transport processes of detritus would change. After this increase in temperature the ice shelves would no longer be able to sustain themselves, affecting the processes which allow for IRD signatures to occur.

Both state 0_0 and 4_1 have ice shelves and experience calving events and since the model only shows retreat, there is no way of knowing how much of material that the erosional potential simulated can become entrained, and subsequently calved and deposited into the ocean. Therefore, this highlights the need to further integrate a multidisciplinary approach when analysing ice sheet stability through an integration of a variety of data.

5.1 Further Work

Using this process could be highly effective given the data. The IRD record is potentially able to be linked to the modelled erosive potential but this will require more data for empirical evidence; e.g. core-top geochemical and geochronological analyses of near-shore sediments and ice-rafted sediments, in which zircons, depending on the analytical technique used, are able to provide far more information than hornblende and biotite detrital grains.

The ice sheet simulations can also be further refined to include not only retreat, but advance cycles as well. This can allow for a better understanding of how the simulated detritus could become entrained in the ice sheet, and therefore subsequently transported and deposited.

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7. Appendix

Appendix A (Subglacial Geology)

Table A1 A broad summary of the ICECAP data previously collected and processed from Aitken et al.’s study (2014), A Basler DC-3T aircraft was fitted with all the instruments mentioned above.

Data Type Instrument Used Data Processing Magnetic Tail-boom-mounted Line data were levelled to minimise line- Geometrics G-823 A correlated noise. Then was interpolated cesium vapour (minimum curvature method) with a cell size of 2 magnetometer. km, finally then were merged into a single composite grid.

Gravity Bell Aerospace BGM-3 Corrections to latitude, instrument drift, Eotvos two-axis stabilised effect and observation elevation were applied to scalar gravimeter. the raw data. An isostatic residual model was used for interpretation with additional adjustments for glacial and subglacial topography. An isostatic correction was computed using the local Airy isostatic Moho depth (varies from 45-14 km depth, density contrast of 500 kg m -3). Grid was interpolated using minimum curvature method at 2 km cell size.

Subglacial A 60MHz High Derived from airborne radar sounding and is Topography Capability Radar described in Young et al. (2011). Bed topography Sounder-1 (HiCARS-1) was interpolated by kriging at a resolution of 2 ice-penetrating radar. km.

Fig. A.1 Study area geophysical data. A. Total magnetic intensity (TMI) magnetic data. B. Isostatic residual anomaly (IRA) gravity data.

Table A.2- Characterisation and description of units and supersuites of Wilkes Land, East Antarctica.

Knox Rift Unit name & Geophysical Description Other Comments colour KA A strong positive magnetic response with Is a part of the ‘Bunger Hills’ a stippled look to it. region defined by Aitken et al. Knox Rift Seems to correlate to a gravity high (data (2014) Unit A is slightly patchy). It is kept as a section of the Knox Rift area, but could have affinity with the AFP. KB Moderate magnetic response, looks much This is one of the units of smoother than KA. Patchy gravity data, basement that underlies the Knox Knox Rift could reflect the slight high in between the Subglacial Basin. Unit B lows. KC Low magnetic response with stripes of This forms another part of the slightly greater magnetic response. Has an basement which underlies the Knox Rift even smoother texture than KB. Gravity Knox Subglacial Basin Unit C low possibly Albany-Fraser Province AFA Strong magnetic high. Forms coherent blebs. Albany-Fraser Gravity seems to range from very high to Province high. Unit A AFB Stippled texture. Magnetic High response, Albany-Fraser with a high gravity response. Province Unit B AFC AFC has a very smooth texture

Albany-Fraser Province Unit C AFD Forms coherent and linear looking blebs in TMI mag. Albany-Fraser Province Unit D West Mawson Craton WMA Patchy, strong positive magnetic character

West Mawson Craton Unit A WMB Also patchy character, but generally weaker magnetic response than WMA West Mawson Craton Unit B

WMC Characterised by a magnetic low

West Mawson Craton Unit C

East Mawson Craton EMA High magnetic and gravity response

East Mawson Craton Unit A

EMB moderate magnetic responses with a patchy character and a slight gravity low. East Mawson Craton Unit B

EMC a very smooth low magnetic response East Mawson Craton Unit C

EMD Strong negative magnetic response with a character similar to the intrusive L unit. East Mawson Craton Unit D

Aurora Subglacial Basin ABA Smooth texture with a slight magnetic high, and a gravity low. Aurora Subglacial Basin Unit A ABB Moderate to high response Aurora Subglacial Basin Unit B

ABC Low to moderate magnetic response.

Aurora Subglacial Basin Unit C

ABD Smooth texture, characterised by magnetic low Aurora Subglacial Basin Unit D

Appendix B (Erosional Spatial Analysis)

B. 1% Ice Sheet State 0_0- Basement 15% 14000000 16% 2% 6% 12000000 6%

(Sum) 10000000

2 22% 25% 8000000 5%

6000000

Basal Basal Velocity 4000000

2000000

Fig. B1. Ice sheet state 0_0 basement statistical results. A. Basement geology map with basal velocity (log) contours. B. Resulting histogram showing the sum of basal velocity as defined by basement geology units and the corresponding pie chart showing the contribution of each unit to the total. Each unit follows the colour code of the basement map. LD= Law Dome, TG= Totten Glacier, PB= Porpoise Bay. 77

B. Ice Sheet State 4_1-Basement 1% 1% 20000000 1% 3% 7% 3% 28% 15000000 14%

10000000 14% 18% 7% 2% 5000000 1%

Fig. B2. Ice sheet state 4_1 basement statistical results. A. Basement geology map with basal velocity (log) contours. The black, dashed line shows the approximate position of the ice sheet margin. Totten Glacier outlet is circled in white. B. Resulting histogram showing the sum of basal velocity as defined by the bedrock geology units and the corresponding pie chart showing the contribution of each unit. The units follow the colour scheme of the basement map.

B. Ice Sheet State 8_2- Basement 27% 23% 12000000

12% 10000000 8% 7% 14% 8000000 8%

6000000

4000000

2000000

Fig. B3. Ice sheet state 8_2 basement statistical results. A. Basement geology map with basal velocity (log) contours. The black, dashed line shows the approximate position of the ice sheet margin. B. Resulting histogram showing the sum of basal velocity as defined by the bedrock geology units and the corresponding pie chart showing the contribution of each unit. The units follow the colour scheme of the basement map.

B. Ice Sheet State 12_5- Basement 6% 1% 14000000 6% 4% 12000000 2% 22% 2% 10000000

(Sum) 19% 2 8000000 38% 6000000

4000000 Basal Basal Velocty 2000000

Fig. B4. Ice sheet state 12_5 basement statistical results. A. Basement geology map with basal velocity (log) contours. The black, dashed line shows the approximate position of the ice sheet margin. B. Resulting histogram showing the sum of basal velocity as defined by the bedrock geology units and the corresponding pie chart showing the contribution of each unit. The units follow the colour scheme of the basement map.

Total basal velocity of basement regions 35000000

Intrusives AFP 2 WM EM 30000000 Knox Aurora Indo-Ant 25000000

20000000

15000000 TotalSum of Basal Velocity 10000000

5000000

0 0_0 4_1 8_2 12_5 Ice sheet state Fig. B5. A simplified histogram summarising the total basal velocity by region for each ice sheet state.

100.00% Basement V Basins- Total Basal Velocity

90.00%

80.00%

70.00%

60.00% Total Basement 50.00% Total Basins

40.00%

30.00%

% of Total Erosional of % Total Erosional Potential 20.00%

10.00%

0.00% 0_0 4_1 8_2 12_5 Ice Sheet State Fig. B6. The relative amount of total erosional potential that summed basin and basement units constitute in each ice sheet state.