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Luminescence dating of the Tsodilo Sand Ramp, Botswana

FHS in Geography 2015

2015

Candidate Number: 901056

Word Count: 11778

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Burrough, 2007

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Acknowledgements

Many thanks to all those who helped with my dissertation. Particularly

my supervisor whose guidance, support and patience were invaluable.

Thank you also to everyone in the luminescence and geography labs, in

the department, for all their help and support.

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Abstract Aeolian landforms, such as dunes and sand ramps, provide a wealth of palaeoenvironmental data of past and future climate and environmental change (Stocker et al., 2013). Whilst dunes are well studied landforms, sand ramps are little studied and are thus poorly understood, with their formation and structure still much debated (Bateman et al., 2012). The Tsodilo Hills UNESCO World Heritage Site in northern Botswana contains a number of paleolandforms, such as dunes and relict shorelines, which have been studied using thermoluminescence, optically stimulated luminescence (OSL) and radiocarbon dating (Thomas et al., 2003). These papers, along with other studies in the northern Kalahari, have offered a comparison for this Tsodilo sand ramp chronology.

Optically Stimulated Luminescence (OSL) dating has advanced considerably over the past decade and is a key technique in assessing aeolian sediment in drylands (Stone and Thomas, 2013). This study aims to add to the picture of environmental change, in the late Quaternary, in the northern Kalahari and Tsodilo region by employing OSL dating and sedimentological analysis to create a chronology for the Tsodilo sand ramp. It also addresses the lack of consensus on sand ramp formation as well as adding to the current debate on the rate of formation and structure of this landscape feature.

Compared with other sand ramp studies the Tsodilo sand ramp represents a more aeolian dominated landform as it lacks talus or paleosol layers in its strata (Telfer et al., 2012 and Turner and Makhlouf, 2002). In addition, this study indicates that sand ramps can form over a period of over 80ka. This is a much longer evolution period than has been recorded in other papers (e.g. Bateman et al., 2012 and Telfer et al., 2012). The Tsodilo sand ramp demonstrates that generalised definitions of sand ramps cannot necessarily be used as site specific factors play a dominant role in their evolution.

Within the sand ramp’s history there are two distinct periods of accumulation - the

first centred on 80ka and the second between 45-22ka. These accumulation periods

are interspersed with an episode of reduced activity, centred on 55ka. The 80ka

episode is a period of very rapid accumulation not recorded elsewhere in the Tsodilo

area nor in the northern Kalahari. In contrast, both the period of reduced activity and

second period of gradual accumulation correlate with other studies of Tsodilo and the

northern Kalahari. Overall there has clearly been climatic change in the Tsodilo area

throughout the late Quaternary. However, it is difficult to specify what the changes

were as accumulation of the sand ramp seems to coincide with both wet and dry

episodes already recorded in the region. Instead this study concludes that sediment

supply and windiness may be the more dominant factors in the sand ramp’s formation

rather than arid or wet conditions. Overall the results of this study adds to the

increasing number of palaeoenvironmental studies in southern Africa. It demonstrates

that sand ramps are a key palaeoenvironmental proxy which, when identified, can aid

our understanding of past environmental change.

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Contents Page

Acknowledgement………………………………………………………………………...………….3

Abstract…………………………………………………………………………………………………….4

1. Introduction…………………………………………………………………………….…..……………6

1.1 Context and location…………………………………………………………….…………….8

1.2 Aims and Research Questions…………………………………………………….………10

1.3 Contemporary Setting……………………………………………………………….……….11

1.4 Palaeoenvironmental Setting…………………………………………………….…..….13

1.5 Sand Ramp Geomorphology……………………………………………….……………..18

1.6 Theory of luminescence dating…………………………………………….………...…21

2. Methodology…………………………………………………………………………….………….….22

2.1 OSL Dating………………………………………………………………………………….……..23

2.2 Sedimentological Analysis……………………………………………………….…………33

3. Results and Analysis…………………………………………………………………………………35

3.1 OSL Dating………………………………………………………………………………………...35

3.2 Chronology of Tsodilo Sand Ramp……………………………………………………..42

3.3 Sedimentological Analysis………………………………………………………….………44

4. Discussion……………………………………………………………………………………….……….48

4.1 Sand Ramp Formation……………………………………………………………………….48

4.2 Forcing Factors…………………………………………………………..………………..……53

4.3 Palaeoenvironmental Context………………………….………..……….….…………53

5. Conclusion………………………………………………………………………………………….……58

6. Bibliography………………………………………………………………….……………….………..60

7. Appendices……………………………………………………………………………….….…………70

A. Radial Plots……………………………………………………………………………………….70

B. Cosmic Dose Rate Modelling…………………………………………………………….71

C. Radial Plots for all samples……………………………………………………………….72

D. Summary of Sedimentological Analysis…………………………………………….74

E. Grain size distributions for all samples…………………………….……………….75

F. Key for Geological map……………………………………………………………..……..77

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1 Introduction There have been a number of studies undertaken in the northern Kalahari Desert

looking at palaeoenvironmental change during the Quaternary period (Thomas and

Burrough, 2013). Sand dunes, lake shorelines and speleothems have been some of the

areas researched and assessed using a range of techniques such as radiocarbon,

thermoluminescence, and optically stimulated luminescence dating. These techniques

have created chronologies for past environmental change in the northern Kalahari. An

understanding of these chronologies gives an insight into past climatic changes which

aids in our interpretation of climate models for the future (Stocker et al., 2013). The

Kalahari seems to be characterised as having periods of dune activity and inactivity

throughout the past 100ka (Thomas and Burrough, 2013). Furthermore, evidence of

paleolake shorelines suggests that it also underwent wetter, lacustrine phases and

would have looked very different from its current arid state (Burrough et al., 2009).

Figure 1 captures the Okavango delta during its yearly flood. Currently arid areas of

the Kalahari may have looked similar to this at different periods during the

Quaternary.

Figure 1 –The Okavango Delta in northern Botswana during the wet season (BBC,

2014)

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To the west of the Okavango Delta lies the Tsodilo Hills World Heritage Site. This

heritage site contains the longest archaeological record in the Kalahari with evidence

of prehistoric man dating from 95ka (Nash et al., 2013). It has also been the site of

environmental studies looking at evidence of wet lacustrine and dune building periods

during the last 50ka, as evidenced by a paleo-shoreline and vegetated dune fields to

the south of the hills (Thomas et al., 2003). This dissertation will focus on this area of

the Kalahari in order to better understand the local and regional environmental

change experienced in the northern Kalahari. Unlike other studies in the Kalahari

Desert this research will focus on a sand ramp as a proxy for environmental change.

These formations are little studied features of the landscape (Bateman et al., 2012).

No sand ramps have been researched in the Kalahari with only around six sites studied

worldwide. This dearth of research means they are relatively poorly understood

geomorphological features. The rate of their formation and the processes involved are

still much debated. However, due to their stability in the landscape, they contain a

wealth of data relating to past climates and processes (Bateman et al. 2012).

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1.1 Context and Location

The Tsodilo Hills, are situated in Northern Botswana (close to the border with Namibia)

in the Ngamiland District (Wendorff, 2005) (figure 2). The area consists of the Nxum

Ngxo (Male), Nxum Di (Female) and Picannin (Child) Hills which form the Tsodilo Hills

World Heritage Site (Wendorff, 2005 and UNESCO, 2014). The Tsodilo sand ramp is

itself situated southeast of the male hill (figure 3).

Figure 2 - A map showing the location of the Tsodilo Hills (Thomas et al. 2003)

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Figure 3 - the Male Hill of the Tsodilo National Park and the location of the Hills in

Botswana (Robbins et al. 2000, p.1086)

These inselbergs are located 40km southwest of the Okavango River (Thomas et al.,

2003). The area covers around 10km2 and contains rich archaeological evidence of

past humans including over 4,000 rock paintings (figure 4) and 7, 500 artefacts found

in many of the caves and exposed cliffs which cover the Hills (Ivester et al., 2010 and

Robbins et al., 2000).

Figure 4 - Rock paintings found in the “White Painting Shelter” showing a rhino, snake

and zebra. It is attributed to ancient local farmers around 900 years ago. (Robbins et

al., 2000)

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The Tsodilo hills are of particular significance to understanding past environmental

change in the Kalahari as there is evidence of both wet (paleolakes) and dry

(paleodunes and sand ramps) conditions in the area during the Quaternary (Thomas et

al., 2003). This allows a direct comparison between these different climatic periods

(Thomas et al., 2003). Another advantage of the Tsodilo Hills in paleoenvironmental

assessments is the evidence of human archaeological remains which have offered a

further method for dating and understanding the past climates experienced by the site

(Brook et al., 2011).

1.2 Aims and Research Questions

The aim of this study is to better understand the formation of sand ramps through

chronological and sedimentological evidence (Bateman et al., 2012). This study also

aims to better understand the local and regional environmental change around the

Tsodilo Hills by using the sand ramp as a proxy for environmental change. To achieve

this, this dissertation will address the following aims and research questions.

Aims:

1. To investigate the formation of the Tsodilo sand ramp

2. To understand how the environment changed in the Tsodilo Hills and

surrounding area during the Quaternary

Research questions:

1. What is the age and rate of accumulation of the Tsodilo sand ramp?

2. What can the Tsodilo sand ramp tell us about the formation of sand ramps?

3. What can the Tsodilo sand ramp tell us about the changing environment in the

Tsodilo Hills area?

4. How does the palaeoenvironmental history of the sand ramp compare to local

and regional records of change?

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1.3 Contemporary Setting

1.3.1 Geology

The Tsodilo Sand Ramp sits in the centre of the Damara belt which crosses Botswana

from Namibia to the Congo (Wendorff, 2005). Orogenic movements in the Damara

belt occurred within the range of 534-516 Ma (Hanson, 2003 cited in Wendorff, 2005

p.17). The hills rise around 420m above the surrounding landscape and consist largely

of schist, quartzite and marble (Thomas et al., 2003) (figure 5). The hills also sit on the

edge of a relict shoreline and lake. Evidence of a shallow lake has been found to the

south of the Hills adjacent to a region of linear sand dunes (Grove, 1969).

Figure 5 - Geological Map of the Tsodilo Hills. Unit I – fine-grained ferruginous and micaceous

quartzites. Unit II – Schist with quartzite layers. Unit III – Sandstone and quartzite. Unit IV –

Polymictic conglomerate containing pebbles set into quartzite (Wendorff, 2005)

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1.3.2 Climate

The current climatic conditions experienced in the north-western Kalahari are shown

in figure 6. This climate graph represents 112 years of data from Shakawe, which is

around 65km to the North of the Tsodilo Hills (Wendorff, 2005). The climate is

characterised by very high average temperatures as well as a clearly defined wet

season between November and April. The climate of Northern Botswana is dictated by

seasonal changes in precipitation and temperature. During the winter high pressure

cells bring cold, dry weather (Burrough et al., 2007). In the summer heavy rain

showers and warm weather are caused by the movement of the ITCZ and Congo Air

Boundary (Thomas and Shaw, 1991). The region also experiences periodic, high

intensity thunderstorms which can cause flash flooding in the area.

Figure 6 - Temperature and prepcipitation graph for Shakawe, a town 50km to the north of the

study site (Botswana Met Office, 2014).

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1.4 Palaeoenvironmental Setting

1.4.1 Regional Palaeoenvironment

The climate of Southern Africa has changed dramatically over the Quaternary period.

It has experienced periods of drying and wetting as the climate has warmed and

cooled (Thomas and Burrough 2013). These environmental changes are recorded by a

number of different landscape features such as speleothems, sand dunes, relict

shorelines and sand ramps (Stone and Thomas 2008). Due to the low levels of organic

material in this arid environment the majority of recent studies in the area have

focused on luminescence dating as a proxy for past environmental change (Thomas,

2013). Overall 620 luminescence ages have been measured in southern Africa covering

a period of over 250ka (Thomas and Burrough, 2013). The majority of these

luminescence ages have been taken from over 550 sand dune studies with only around

74 dates taken from other landforms such as relict shorelines and sand ramps (Thomas

and Burrough, 2013). The geographical distribution of studies is also very uneven. The

majority have been taken in the western, southern and eastern Kalahari with only

three study sites recorded in the northern Kalahari where the Tsodilo Hills are situated

(Thomas and Burrough, 2013).

The first studies in the Kalahari (e.g. Stokes et al., 1997) interpreted luminescence ages

as specific periods of aridity and sediment accumulation (Thomas and Burrough,

2013). These periods during the late Quaternary were thought to have been between

95-115ka, 41-46ka, 20-26ka and 9-16ka (Stokes et al., 1997). Other studies more

focused on the northern Kalahari (e.g. Thomas et al., 2000) suggest a different

palaeoenvironmental history with significantly more activity recorded during the

Holocene as well as a period of accumulation between 33-26ka. Overall, as Thomas

and Shaw (2002) suggest, different environmental factors dominate in different parts

of this vast desert. However, as dating techniques have improved and the volume and

geographical extent of luminescence ages has increased, theories relating to the

environmental change in the Kalahari during the Quaternary have also advanced.

Figure 7 demonstrates that when multiple studies form the Kalahari are combined the

distinct periods of aridity seem to vanish and have instead been replaced by a more

continuous record of dune accumulation (Thomas and Burrough, 2013). The southern

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Kalahari record in figure 7 shows how difficult it is to ascertain any sort of pattern or

distinct periods of aridity from this large number of ages. In contrast the northern

region contains a less continuous record with more distinct clusters of luminescence

ages (Thomas and Burrough, 2013). This may be due to the increased sensitivity and

background noise of the southern Kalahari in comparison with the northern region

(Stone and Thomas, 2008). Overall this complexity demonstrates the need to place

studies in a local and regional context in order to understand what they might mean in

relation to changing environments during the Quaternary in the Kalahari (Thomas and

Burrough, 2013). The Tsodilo Hills Sand ramp will hopefully add to this growing

database of ages and allow for a comparison with other records in the region.

Figure 7 - A summary of dune field accumulation data from Thomas and Burrough (2013). Each

bar indicates a period of 1ka in which at least one luminescence date has been recorded.

Whilst the majority of studies in the Kalahari have focused on sand dunes, a number

have been undertaken of the paleolakes within the Kalahari region. These lakes are

mainly situated to the South East of the Okavango Delta and include paleolake

Thamalakane (Burrough and Thomas, 2009a) and other sub-basins such as paleo-Lake

Makgadikgadi (Podgorski et al., 2013), paleolake Nagami (Burrough et al., 2007) and

paleolake Mababe (Burrough and Thomas, 2008). Such studies demonstrate that the

relict lake shorelines, created by these now almost dry bodies of water, exhibit clear

wet periods during the Quaternary. These lakes grew and contracted throughout the

Quaternary with Lake Makgadikgadi thought to have extended over 90,000km2; the

largest freshwater body on earth (Podgorski et al., 2013). There are some

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inconsistencies between the studies undertaken on these different paleo-lakes.

However, the evidence suggests there were at least 7 mega-lake phases in the

Makgadikgadi, Ngami and Mababe area. These were centred on 8.5ka, 17.1ka, 26.8ka,

38.7ka, 64.2ka, 92.2ka and 104.6ka (Burrough et al., 2009a). The cause of these lake

high-stands is the result of both changing hydrological dynamics in the area as well as

changing climatic regimes (Burrough et al., 2009b). Furthermore the existence of

these large bodies of water would have themselves altered and affected both local

and regional climatic patterns (Burrough et al., 2009b).

1.4.2 Local Palaeoenvironment

Multiple lake high stand periods have also been recorded in the Tsodilo area through

analysis of relict shorelines to the south of the Tsodilo Hills (Thomas et al., 2003).

Whilst not as large as other paleolakes, such as Makgadikgadi and Ngami, these

shorelines can offer a more localised understanding of environmental change during

the Quaternary in the Tsodilo Hills. Robbins et al. (2000) suggest three lacustrine

phases in the Tsodilo area: 36-32ka, 26.5-22.5ka and 19-11ka. The largest of these was

thought to have been the 19-11ka lake (Brook et al. 1992). Further evidence has been

put forward for a number of other freshwater lakes to the southwest of the Tsodilo

Hills at around 37ka, 32-27ka and 28-26ka (Brook et al. 1992). A number of these

localised wet phases also seem to correlate with lake high phases elsewhere in the

Kalahari. For example paleo-Lake Ngami experienced a lake high stand between 18-

12ka around a similar time to paleo-Lake Tsodilo (Burrough et al., 2007).

A number of studies have also pointed towards periods of sediment accumulation in

the area. Most recently Thomas et al. (2003) undertook a study of the relict lake shore

line and the current dune field to the south of the Tsodilo hills using radiocarbon, OSL

and AMS dating (figure 8). Thomas et al. (2003) suggest that the Tsodilo area

experienced a period of dune accumulation between 36-28ka as well as wetter periods

between 40-32ka. These wetter and drier climatic periods are thought to have

influenced aeolian sediment sources as well as aeolian transportation processes in the

locality (Thomas et al., 2003).

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Figure 8 - a timeline showing the periods of wetting and drying around the Tsodilo Hills

Other studies of the region offer slightly different pictures of the environmental

change experienced by the area in the last 50ka. Thomas et al. (1997) suggest that

there were periods of dune construction between 27-23ka and 17-10ka. This phase of

aeolian activity partially agrees with Blumel et al. (1998) who suggests a similar period

of activity around 20-17ka. However, the dune building period between 17-10ka

seems to coincide with a lacustrine phase noted by Thomas et al. (2003), Robbins et

al. (2000) and also Brook et al. (1992), who suggest that a long permanent wet phase

occurred at around 20.6ka. Evidence of the alternating wet and dry periods can also

be found in the sedimentary records of numerous caves found in the Tsodilo Hills

(Robbins et al., 2000). Alternating layers of aeolian sediment and coarse gravel were

found and are thought to indicate dry climatic episode of sand accumulation followed

by episodes of stability with little aeolian accumulation. The periods of sand build-up

were rapid, occurring over a few thousand years (Robbins et al., 2000). These gravel

layers mirror those found in other studies of aeolian environments (e.g. Bateman et

al., 2012) and are thought to originate from weathered material from the cave walls

and roof (Robbins et al., 2000). Studies looking at the Tsodilo area prior 50ka are

scarce. However, Stokes et al. (1997) suggests that a number of dune building periods

may have occurred in the locality at around, 73ka, 101ka, 109ka and 102ka. Overall

there seems to be differing accounts of climate change in the area. This may be due to

localised variations in climate or changes and anomalies in dating techniques between

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studies. Some studies may even need to be reassessed due to out of date techniques

employed (Thomas and Burrough, 2013). However, alternating wet and dry periods do

seem to be dominant throughout the late Quaternary in the Tsodilo Area, with little

activity occurring in the mid to late Holocene (Thomas et al., 2003). A quantitative

analysis of the Tsodilo sand ramp may provide a clearer picture of the environmental

changes in this area and provides a possible insight into the effects of features such as

paleolakes on the morphology and sedimentology of local landforms (Thomas, 2013).

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1.5 Sand Ramp Geomorphology

Sand ramps have been used in a number of studies to better understand

environmental changes in particular regions of the world. The term “sand ramp” was

first coined in the late 1980s and discussed for the first time in Tchakerian’s 1991

paper. Since then around six major studies (figure 9) have been published relating to

sand ramps worldwide and their formation (Rendell and Sheffer 1996, Clemmensen et

al. 1997, Thomas et al. 1997 and Turner and Makhlouf 2002, Bateman et al. 2012,

Telfer et al. 2012).

Figure 9 - a location map of sand ramp studies

Whilst there are disagreements relating to the formation of these landscape features

figure 10 represents the possible structure of a typical sand ramp. However, not all the

features indicated in the diagram are essential for a landscape feature to be classified

as a sand ramp. Sand ramps are large scale sedimentary deposits of sand and sediment

against a topographical feature such as a cliff or mountain (Bateman et al., 2012). Such

accumulations against topographical features are common but poorly defined features

in the landscape (Telfer et al., 2012). This has resulted in a range of names for these

landforms, including sand shadows (Bagnold, 1941 cited in Bateman et al., 2012),

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anchored dunes (Livingstone and Warren, 1996) and climbing dunes (Besler, 1992

cited in Bateman et al., 2012). These accumulations of alternating layers of talus and

aeolian sediment result from aeolian and fluvial processes from one or multiple

sources (Lancaster and Tchakerian, 1996). The formation of sand ramps has been

suggested to be akin to the formation of a falling or climbing dune (Livingstone and

Warren, 1996). However, due to the input of both aeolian controlled sediment and

talus deposits from erosion, there is a greater complexity than is found within dune

systems (Bateman et al., 2012).

Figure 10 - A schematic view of sand ramp geomorphology

Bateman et al. (2012) state that whilst sand ramps can hold palaeoenvironmental

data, their formation first needs to be better understood. Furthermore, a better

understanding of the forcing factors involved in their evolution can allow for a better

assessment of the environmental and climatic change during their formation (Bailey et

al. 2014 and Thomas, 2013). Overall few sand ramps have been identified worldwide.

This is thought to be due to the fact that they are easily mistaken for other

geomorphological features such as alluvial fans and dunes (Bateman et al., 2012). Sand

ramps are created through the interaction between three main agents; wind, water

and gravity (in the form of mass movement) (Telfer et al., 2012). Figure 11 represents

a qualitative representation of six different sand ramp studies in relation to their

positon on the sliding scale between these three processes. Some studies suggest that

sand ramps form during brief periods of activity, or “windows of opportunity”, over

around 5ka (Bateman et al., 2012 p.107). Other studies point toward a more gradual

accumulation, around 29ka (Telfer et al., 2012) with others still suggesting an ongoing

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alternation between accumulation and activity lasting throughout the Quaternary

(Busche, 1998 cited by Bertram, 2003). The rates of formation also vary between sand

ramp studies. Some suggest rates of around 2mka-1 whilst others indicate a more rapid

accumulation rate of 15mka-1 (Telfer et al., 2012, Thomas et al., 1997 and Rendell and

Sheffer, 1996). Another area of dispute is the nature of sand ramp formation. Whilst it

is agreed that they contain alternating layers of sediment, the origin and

transportation of this sediment is disputed. Some suggest sand ramps originate from a

single rock fall and then accumulate aeolian sediment (Turner and Makhlouf, 2002)

whilst others suggest they originate from an accumulation of sand against a cliff face

followed by alternating periods of activity and reduced activity which create the

alternating layers in their strata (Telfer et al., 2012). Another theory is that sand ramps

form against a cliff face and then, due to their morphology, cause changes in wind

regimes over their surface allowing for periods of activity and inactivity to occur on

different parts of the sand ramp at different times (Clemmensen et al., 2007). Overall

the complexity of sand ramp formation and structure mean that sand ramps can be

important stores of information regarding past climates, ecosystems and landform

processes (Bateman et al. 2012). Due to the frequently low levels of organic matter

within sand ramps, optically stimulated luminescence dating is the most appropriate

method for assessing their palaeoenvironmental history (Thomas, 2013).

Figure 11 - A qualitative assessment of the formative causes of sand ramps.

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1.6 Theory of Luminescence Dating

Optically stimulated luminescence dating is a relatively new dating technique which

has evolved and changed over the past few years. It was first developed in the 1960s

and has been used in order to assess the age of sediments such as quartz where other

dating methods, such as radiocarbon dating, were impossible to employ (Singhvi et al.,

2001). It allows for high-resolution dating of sediment exceeding 50ka (the limit for

radiocarbon dating). Luminescence is created as a result of naturally occurring

radioactive isotopes in the ground, such as thorium, uranium and potassium (Duller,

2008). The radiation energy produced by these elements over time is stored in

minerals, such as quartz and feldspars. When the radiation comes into contact with

the crystal lattice structure of the mineral, electrons in the valence band may be

excited and gain enough energy to become trapped in the conduction band (figure 12

part i and ii)(Aitken, 1998). When the mineral is heated or exposed to light the

electrons can escape their traps and in doing so they emit photons of light which can

be detected and measured (figure 12 part iii)(Duller, 2008). This exposure to light or

heat resets the luminescence signal inside the mineral (Aitken, 1998). The brightness

of this emission of light (luminescence signal) combined with an understanding of the

rate at which the mineral has experienced radiation from the surrounding sediment

can allow us to calculate the time since the mineral was last reset (i.e. exposed to

sunlight). This allows us to calculate how long a layer of sediment has been buried

(Aitken, 1998).

Figure 12 - An energy level diagram from Duller (2008) summarising the process of

luminescence.

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2 Methodology

A total of 9 samples were collected in 2007 by Dr Sallie Burrough and Professor Dave

Thomas, to a depth of 8m at the site shown in figure 13. They were collected using a

drill were place in a light-tight plastic tube once removed. In 2007 most of the samples

were prepared for dating by Dr Burrough. The rest were completed (samples KAL-07-

01-7 and KAL-07-01-10) in 2014 for the purposes of this dissertation. By sampling

every 1m to a depth of 8m has allowed for a high resolution record of the sand ramps

formation to be created (Stone and Thomas, 2008).

Figure 13 - The study site at S18° 46' 51.6" E 21° 46' 6.96", elevation 1055m (Google Earth,

2014)

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2.1 Optically Stimulated Luminescence Dating

OSL dating, using the single aliquot regeneration (SAR) protocol was carried out on the

samples in the Oxford Luminescence Laboratory. The light exposed ends of the sample

tubes were removed and used for grain analysis and environmental dose rate

calculation. They were not used in the OSL itself as they may have been light

contaminated on removal from the ground and transport. The remaining sediment

was prepared for luminescence measurement (figure 14).

Figure 14 - A flowchart showing the sample preparation procedure.

Sediment treated in concentrated hydrochloric acid to remove carbonates and then concentrated hydrogen peroxide to remove organic matter

Sediment rinsed and sieved to isolate 180-210µm fraction

Sodium polytungstate was used to density seperate the quartz from feldspar and other heavy minerals

Hydroflouric was used for 45 minutes to remove any remaining feldspars and etch the outer layer of the quartz to the alpha-irradiated surface

Samples were rinsed in hydrochloric acid ro remove any bi-products of the etch

A final sieve was undertaken before the sample grains were placed on aluminium disc using silicon spray and a 2mm diameter stensil

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2.1.1 Single Aliquot Regeneration Protocol (Murray and Wintle, 2000 and 2006)

Once the sediment was prepared, the SAR protocol of Murray and Wintle (2000 and

2006) was used for dating. This protocol is used in preference to others such as

multiple-aliquot additive-dose (MAAD) and single-aliquot additive-diose (SAAD)

techniques as SAR is quicker, more robust and more accurate when calculating ages

(Thomas and Burrough, 2013). In addition, the SAR protocol is used in the majority of

current luminescence studies and has demonstrated reliability in giving ages which

have been found to be consistent with other dating proxies (Murray and Olley, 2002).

The SAR protocol was initially devised by Murray and Wintle in 1997 (Wintle and

Murray, 2006). The basis of the SAR protocol is to give the aliquots regenerative doses

in order to understand the sensitivity of the sample to multiple doses of radiation

(Bateman et al., 2012). These multiple regenerative doses are carried out in a series of

runs as shown in figure 15 (Murray and Wintle, 2000 and 2003). In addition three

recycling and two recuperation runs were also used.

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STEP RUN 1 RUN 2 RUN 3

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vity

4 Test Dose (e.g. 5Gy) Test Dose (e.g. 5Gy) Test Dose (e.g. 5Gy)

5 Preheat 2 (220°C) Preheat 2 (220°C) Preheat 2 (220°C)

6 Measure OSL at

130°C for 40 sec - Tn

Measure OSL at

130°C for 40 sec - L1

Measure OSL at

130°C for 40 sec - L2

7 Bleach at 280°C for

40 sec

Bleach at 280°C for

40 sec

Bleach at 280°C for

40 sec

Cal

cula

te s

en

siti

vity

co

rrec

ted

OSL

Figure 15 – The SAR protocol and dose recovery test (Duller, 2008 and Wintle and Murray,

2006). Run 2 and 3 represent two possible regeneration runs to take into account changes in

sensitivity

26

2.1.2 Combined Preheat Plateau and Dose Recovery Test

Pre-heating the samples before measuring the luminescence signal is important as it

allows for light-sensitive shallow traps to be emptied (Murray and Wintle, 2006).

However, by heating the samples prior to measurement, changes in sensitivity can

occur. In order to minimise this sensitivity change a pre-heat plateau test is carried out

prior to any measurements being taken in order to assess the pre-heat temperature

with the smallest change in sensitivity. The sample was bleached and then given a

laboratory dose. It was then heated at different temperatures from 180°C to 300°C

and the sensitivity changes were measured (figure 16). The temperatures which

displayed the smallest change in sensitivity were 240ᵒC and 220ᵒ so these were chosen

as the preheat temperatures.

Figure 16 - Preheat plateau test for KAL/07/01/1 (A) and KAL/07/01/11 (B) at various

temperatures. A line of unity is shown for reference.

0.8

0.85

0.9

0.95

1

1.05

1.1

1.15

1.2

160 180 200 220 240 260 280 300 320

Ad

min

iste

red

Do

se/M

eas

rue

d

Do

se

Preheat Temperature (°C)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

160 180 200 220 240 260 280 300 320

Ad

min

site

red

Do

se /

Me

asu

red

D

ose

Preheat Temperature (°C)

A

B

27

A dose recovery test was also undertaken at the same time as the pre-heat plateau

test to ensure that the SAR protocol was working correctly (Murray and Wintle, 2003).

It is undertaken by fully bleaching the sample, thus removing all trapped electrons

(Duller, 2008) and then giving it a pre-determined laboratory dose of radiation using

an artificial light source (Wallinga et al., 2000). When the luminescence of the sample

is then measured it should match the laboratory dose it received. This process was

carried out on samples KAL-07-01-1 (6.92Gy laboratory dose) and KAL-07-01-11

(34.6Gy laboratory dose) (figure 17). If the dose recovery test is successful then the

ratio between the given and measured doses should fall between 0.9 and 1.1. If the

ratio falls outside these limits then the sample is seen to have failed the test and that

aliquot is rejected. Both samples demonstrate good dose recovery with no ratios

outside 0.9-1.1.

Figure 17 - Dose recovery ratio of samples KAL-07-01-1 (A) and KAL-07-01-11 (B)

0

5

10

15

20

25

30

0.960.970.980.991.001.011.021.031.04

FREQ

UEN

CY

DOSE RECOVERY RATIO (MEASURED/GIVEN DOSE)

0

5

10

15

20

25

0.960.970.980.991.001.011.021.031.04

FREQ

UEN

CY

DOSE RECOVERY RATIO (MEASURED/GIVEN DOSE)

B A

28

2.1.3 Measuring the luminescence signal

Once the preheat plateau and dose recovery tests had been carried out the samples

were dated using a Risø DA-15 luminescence reader. An example of a run can be seen

in figure 15 The luminescence signal is measured by taking the first few channels

(seconds) of the decay curve (the fast component) and subtracting a number of later

channels of the decay curve (the background signal) (figure 18).

Figure 18 - A decay curve from aliquot 1 from sample KAL/07/01/1 showing the

background radiation (in green) and the signal due to the environmental dose rate (in

red).

The equivalent dose is then calculated by plotting the natural signal (the amount of

radiation received during the burial period) and signals measured from known

laboratory doses of radiation on a graph (figure 19). The y axis is sensitivity corrected

OSL and the x axis is dose rate.

Figure 19 - A SAR dose response curve from aliquot 1 sample KAL/07/01/1

Natural

50ß

Time (s)

4035302520151050

OS

L (

cts

per

0.1

0 s

)26,000

24,000

22,000

20,000

18,000

16,000

14,000

12,000

10,000

8,000

6,000

4,000

2,000

0

Dose (s)

400350300250200150100500

Lx/T

x

5.5

5

4.5

4

3.5

3

2.5

2

1.5

1

0.5

0

29

2.1.4 Rejection Criteria

An important part of assessing the signals once they have been analysed on the

luminescence reader is rejection criteria so that anomalous results can be removed

from the data set (Roberts, 2008). A standard suite of rejection criteria were used:

1. Recycling ratio ±10% (0.9 and 1.1) (Murray and Wintle, 2000)

2. Recuperation less than 5% (Murray and Olley, 2002)

3. IR depletion ratio ±10% (Duller 2003)

4. Fast ratio (Durcan and Duller, 2011)

5. Saturation (Wintle and Murray, 2006)

Recuperation

Within the SAR protocol the measurement cycle is repeated but the aliquots are given

a dose of 0 Gy (Murray and Wintle, 2000). This should mean that a zero dose is

measured. If it is not then this suggests that there has been an unwanted signal

created due to pre-heating of the sample. Murray and Wintle (2000) state that if this

value is under 5% of the natural signal then it is insignificant. However, if it is over this

then that aliquot should be rejected.

Recycling Ratio

The recycling ratio is carried out at the end of each run on all aliquots. The

measurement for one of the SAR cycles in the run is repeated (Duller, 2008). The

original luminescence signal and the repeated dose should be the same. The ratio

between these two signals is called the recycling ratio and if it is greater than ±10% of

unity then the aliquot is rejected (Murray and Wintle, 2000).

IR depletion ratio

This ratio is used to determine the presence of feldspar in samples (Duller, 2003). In

the preparation process feldspar should have been removed through density

separation. However, this is not always the case. An additional measurement is made

on each aliquot at the end of the run using infra-red stimulation. If feldspar is present

30

then an IRSL signal will be detected (ibid.). If this signal is greater than 10% of unity

then the aliquot is rejected.

Fast ratio

When the OSL signal is detected it consists of a number of discrete components; fast,

medium and slow (Durcan and Duller, 2011 and Jain et al., 2005). The fast component

of the OSL signal refers to the electron traps which are most rapidly emptied when the

quartz is exposed to light or heat (Bailey et al., 1997). For the purposes of this study

the fast component is the part of the signal used to calculate the ages of samples. The

reasons for this are that it is stable over long periods of time (its mean lifetime is 850

million years at 20 degrees); it has low recuperation compared with other

components, it is thermally stable and it can be easily bleached in nature which allows

for complete resetting of the OSL signal (Singarayer and Bailey, 2003, Wintle and

Murray, 2006 and Li and Li, 2006). Overall, signals which are dominated by the fast

component seem to give more accurate dates. However, it can be difficult to isolate

the fast component of the luminescence signal as the fast, medium and slow

component are not released consecutively and overlap. There are a number of

methods for disseminating the fast component in a signal such as curve deconvolution

(Choi et al., 2006). However, in this study the fast ratio has been used as it can be

easily applied, calculated and is a quantitative assessment of the fast component in a

signal (Durcan and Duller, 2011). The fast ratio is based on the photo-ionisation cross-

sections of the fast and medium components and the power of the measurement

equipment used to record the OSL signal. In this study the threshold value for the fast

ratio has been taken as 20 as advised by Durcan and Duller (2011).

Saturation

In some cases the electron traps in the grains measured are saturated (Duller, 2008).

This may have been due to the sediment only being partially bleached prior to burial.

The protocol suggested by Wintle and Murray (2006) of rejecting all aliquots whose

signal exceeds 2D0 has been used. D0 is the “dose level that is characteristic of the

dose-response curve” and is obtained from the exponential curve fitting equation for

each aliquot (Wintle and Murray, 2006 p.382).

31

2.1.5 Environmental Dose Rate

Measurement of the environmental dose rate is fundamental to the calculation of the

luminescence age. The environmental dose rate consists of a number of components

including, alpha, beta and gamma radiation from elements, such as uranium and

thorium, potassium and cosmic radiation, originating from space (Duller, 2008).

Cosmic radiation is dependent on the altitude and latitude of the sample as well as

how deep it is buried (Prescott and Hutton, 1994). The samples in this study were

analysed using ICP (Inductively Coupled Plasma) at SUERC. Oxford Luminescence

Laboratories do not have the facilities to measure the environmental dose rate. The

conversion factors of Guerin et al. (2011) were used to convert radionuclide

concentrations to dose rates. The beta dose rate was attenuated for grain size and

etching using the attenuation factors of Mejdahl (1979) and Bell (1979). The beta and

gamma dose rates were corrected for water content. The dose rates were all

calculated using DRAC (Dose rate and age calculator for trapped charge dating)

(Durcan et al. Submitted).

2.1.6 Water Content

An estimate of moisture content in each sample was made based on other studies in

northern Kalahari as the samples were collected using wet coring and so their water

content on collection could not be measured. Burrough et al. (2009) estimated water

content to be between 7-11% ± 2. Ringrose et al. (2008) used 10-12% ± 5-8 and

Burrough et al. (2007) use 3-8%. For the purposes of this study 10% ± 2 will be used.

The large uncertainty demonstrates how it is difficult to tell how the water content of

the sand ramp has changed throughout its history.

2.1.7 Data Presentation

In this study De distributions have been displayed primarily in the form of radial plots.

Whilst histograms have been used to display the results from the dose recovery test

they have not been used elsewhere as the high levels of overdispersion in the results

do not lend themselves to being displayed in a histogram (Galbraith and Roberts,

2012). Overall radial plots are easy to interpret and allow the display of different

32

standard errors in the data (Galbraith et al., 1999). Patterns in the De values and the

extent of overdispersion are much easier to observe as well (Roberts et al., 2000).

Further details regarding radial plots can be found in appendix A.

33

2.2 Sedimentological Analysis

The sedimentological analyses used included; loss on ignition, grain size and also grain

shape. All of these factors aid our understanding of the processes and climatic

condition which led to the formation of the sand ramp.

2.2.1 Loss on Ignition

Loss on ignition (LOI) was used to assess the amount of organic material in each layer

of the sand ramp as well as the amount of carbonates present (Bengtsson and Enell,

1986). Following the protocol of Heiri et al. (2001) the samples were initially heated in

the furnace to 110 degrees celsius for 24 hours in order to dry them completely. They

were then left in a desiccator until cool, then weighed. This process was then repeated

at 550 degrees celsius for four hours) and at 950 degrees celsius for 2 hours. At 550

degrees the organic matter in the sample is oxidised to form carbon dioxide and ash

(Heiri et al. 2001). At 950 degrees the carbonates in the sample are also removed.

Three repeats were taken for each sample and an average taken of these.

2.2.2 Grain shape

The size and fourier shape of quartz grains was used to assess the origin of the

sediment. Grains that are aeolian in origin are spherical and well-rounded and fluvial

grains are angular with a low sphericity (Bui et al. 1989). This was done by eye using a

microscope and the classification according to Pettijohn et al. (1987) (figure 20).

Figure 20 - A table showing estimates for roundness and sphericity of different grains. From

Pettijohn et al. (1987)

34

Translucent grains with a red hue were identified as quartz and were estimated as a

percentage per sample compared to other minerals and rock types. This was done to

help assess the possible origin of the sediment as well as accounting for some of the

characteristics on the dose distributions.

2.2.3 Grain size

Grain-size distributions help to assess the processes involved in the formation of the

Tsodilo sand ramp as well as helping to demonstrate the origins of sediment (Liu and

Coulthard 2014). Furthermore it was carried in order to assess if there were any

changes throughout the sand ramp. In this study grain size analysis was undertaken

using a Mastersizer. The sediment was separated into small sub-samples using a riffle

box before being run through the machine using distilled water. The machine was

flushed with distilled water 4 times before each sample was measured to make sure

no sediment was left from the previous sample inside the machine. Three repeats

were taken of each sample, at pump speed 4000, and an average was taken of the

grain size distribution. Grain size distributions were created using GradiStat (Blott,

2000).

2.2.4 Grain Colour

The colour of the sediment was also assessed using a Munsell Chart in order to assess

any changes in the sediment throughout the core. Pictures were also taken of the

samples under a microscope in order to better understand the reason for the colour of

the sediment.

35

3 Results and Analysis

3.1 OSL Dating

3.1.1 Calculation of OSL age

In order to calculate the OSL ages of the samples both the environmental dose rate

and the equivalent dose rates (De) need to be calculated. The following equation is

then used to calculate the age of the samples:

𝑎𝑔𝑒 (𝑦𝑒𝑎𝑟𝑠) = 𝑒𝑞𝑢𝑖𝑣𝑎𝑙𝑒𝑛𝑡 𝑑𝑜𝑠𝑒 (𝐺𝑦)

𝑒𝑛𝑣𝑖𝑟𝑜𝑛𝑚𝑒𝑛𝑡𝑎𝑙 𝑑𝑜𝑠𝑒 (𝐺𝑦)

3.1.2 Environmental dose rate

Figure 21 shows the contribution of beta, gamma and cosmic rays as a percentage of

the overall environmental dose rate as calculated using DRAC (Durcan, submitted). As

with other studies in the Kalahari (e.g. Stone and Thomas, 2008) the cosmic dose rate

makes a relatively large contribution to the overall environmental dose rate due to low

levels of thorium, potassium and uranium concentrations in the sediment. As a sample

becomes buried deeper into the sand ramp the amount of cosmic radiation it receives

should decrease over time (Munyikwa et al., 2005). This process is not normally

accounted for in OSL dating as the cosmic dose rate generally makes up such a small

percentage of the environmental dose rate that any underestimate of the cosmic

component is subsumed by other errors (Burrough et al., 2009). However, in the

Kalahari the overestimation of the cosmic component can become significant.

Consequently the cosmic dose rate has been modelled using methods suggested by

Munyikwa et al. (2000) to account for the overburden history of each sample

(Burrough et al., 2009). This method has been exhibited in Telfer and Thomas (2006),

Burrough et al. (2007), Burrough and Thomas (2008) and Burrough et al. (2009). A

detailed description of the modelling process can be found in appendix B. The mean

cosmic dose rates can be seen in table 1 along with total environmental dose rate

after modelling.

36

Figure 21 - The contribution by beta, gamma and cosmic rays as a percentage of the overall

environmental dose rate

Table 1 - Environmental dose rate summary

0%10%20%30%40%50%60%70%80%90%

100%

Beta (% of total Dose Rate) Gamma (% of total Dose Rate)

Cosmic (% of total dose rate)

Sample

Depth

(m) ± 0.1

K-40

(%) ± 0.01

Th-232

(ppm)

U-238

(ppm)

Water

content

(%)

Dose Rate (Gy/ka) Total Env.

Dose Rate

after

modelling

(Gy/ka)

Beta Gamma Mean

Modelled

Cosmic

KAL/07

/01/1

1.00 0.01 1.32 ± 0.26

0.31 ± 0.06

10 ± 2 0.06 ± 0.01

0.09 ± 0.01 0.20 0.35 ± 0.08

KAL/07

/01/2

1.50 0.01 1.52 ± 0.30

0.42 ± 0.08

10 ± 2 0.08 ± 0.01

0.11 ± 0.01 0.21 0.39 ± 0.08

KAL/07

/01/4

2.50 0.01 1.10 ± 0.22

0.35 ± 0.07

10 ± 2 0.06 ± 0.01

0.08 ± 0.02 0.19 0.34 ± 0.07

KAL/07

/01/6

3.50 0.01 1.71 ± 0.34

0.57 ± 0.11

10 ± 2 0.10 ± 0.02

0.13 ± 0.02 0.18 0.41 ± 0.08

KAL/07

/01/7

4.00 0.01 1.64 ± 0.33

0.48 ± 0.10

10 ± 2 0.09 ± 0.02

0.12 ± 0.02 0.30 0.51 ± 0.1

KAL/07

/01/8

5.00 0.01 1.48 ± 0.30

0.50 ± 0.10

10 ± 2 0.09 ± 0.02

0.11 ± 0.02 0.26 0.46 ± 0.1

KAL/07

/01/9

6.00 0.01 1.52 ± 0.30

0.40 ± 0.08

10 ± 2 0.08 ± 0.01

0.11 ± 0.02 0.18 0.36 ± 0.06

KAL/07

/01/10

7.00 0.01 1.51 ± 0.30

0.53 ± 0.11

10 ± 2 0.09 ± 0.02

0.12 ± 0.02 0.17 0.38 ± 0.06

KAL/07

/01/11

8.00 0.01 2.35 ± 0.47

0.50 ± 0.10

10 ± 2 0.10 ± 0.02

0.15 ± 0.03 0.17 0.43 ± 0.08

37

3.1.3 Equivalent dose distribution

De values were measured and then processed using the rejection criteria. Overall the

aliquots measured were very bright with the natural signal frequently being measured in the

thousands of counts per Gy per second. Only 3 aliquots were rejected due to the fast ratio

and 6 aliquots were rejected due to saturation. No samples were rejected due to IR-ratios,

recycling ratios. Overdispersion was also calculated and found to be very high throughout

the sand ramp. Table 2 shows a summary of rejected aliquots and overdispersion values.

Table 2 - Summary of rejected aliquots and overdispersion values

Sample Depth

(m) ± 0.1

Number of

aliquots

Number of Aliquots

rejected due to:

Overdispersion

(%)

Overdispersion

Error

measured

(accepted)

Fast

Ratio

Saturation

KAL/07/01/1 1 25 (25) 74.00 9.67

KAL/07/01/2 1.5 24 (21) 3 68.33 9.48

KAL/07/01/4 2.5 24 (22) 2 55.54 7.07

KAL/07/01/6 3.5 24 (22) 1 57.21 7.35

KAL/07/01/7 4 24 (23) 1 42.13 4.97

KAL/07/01/8 5 24 (24) 42.54 4.92

KAL/07/01/9 6 24 (23) 1 28.66 3.40

KAL/07/01/10 7 24 (24) 21.48 2.74

KAL/07/01/11 8 24 (23) 1 24.97 3.07

38

3.1.4 Age model selection

In order to calculate the equivalent dose an age model needs to be used in order to acquire

the most appropriate equivalent doses for the site and samples measured. The age model

used should be chosen as a result of context, stratigraphic consideration, the nature of

deposition and other observations of the De values (Galbraith et al., 2005). Dose rate

distributions can be affected by a number of different factors such as bioturbation, micro-

dosimetry and partial bleaching (Galbraith and Roberts, 2012). In this study there was a

difficulty in assessing which age model to use as the reason for the variation in De values is

difficult to pinpoint.

Partial Bleaching

Partial bleaching is caused when grains are not exposed to enough sunlight possibly caused

by rapid or night-time deposition. It can result in a residual signal in the grain which is

frequently characterised by large values for overdispersion. Furthermore Olley et al. (2004)

and Lian and Huntley (1999) suggest that aeolian transport will not always guarantee

complete bleaching of the samples. However, the majority of studies on sand dunes and

ramps imply that aeolian transported sediment is completely bleached prior to burial.

Partial bleaching is a factor mainly in fluvial sediments (Bailey and Arnold, 2006 and Lomax

et al., 2007). When partial bleaching is thought to be a factor the use of the minimum age

model (MAM) is thought to be most appropriate (Galbraith and Roberts, 2012). However, in

this study, due to the evidence from the sedimentological record of rounded and spherical

grains, suggesting that the sediment is aeolian transported, partial bleaching has been

discounted.

Bioturbation

Bioturbation is the process by which animals or plants move sediment between the strata of

a landform through processes such as burrowing (Balek, 2002). It has been found that

bioturbation can affect age distributions by bringing older sediment upward or burying

younger sediment deeper in the feature post deposition (Bateman et al., 2007). An example

of this can also be found in Kalahari where termites can move sediment up to 2.4 m from its

source strata (West 1970 cited Bateman et al., 2007). In the case of the Tsodilo sand ramp

there are no other dating methods (such as radiocarbon dating) with which to provide

39

independent age controls in this study. This makes it difficult to ascertain if bioturbation has

occurred and if the dates calculated are accurate. However, evidence suggests that

bioturbation might be an important factor. Firstly bioturbation seems to be a common

occurrence in the Kalahari Desert (e.g. Bateman et al., 2003). In addition luminescence

studies exhibit multi-peak De distributions with high overdispersion when bioturbation is a

factor (Bateman et al., 2003). This lack of a gaussian distribution in De values is also present

in the samples measured in this study (Forrest et al., 2003) (figure 21). Similar multi-peak De

distributions have also been measured at the Tsodilo Hills dune field suggesting that

bioturbation is a factor that might be found across this region (Thomas et al., 2003 and

Bateman et al., 2007). The addition of older and younger sand to a sample suggests that

models such as the finite mixture model are not appropriate in this study as the grains used

in each aliquot may be drawn from above or below the sample site (Galbraith et al., 2005).

Figure 21 - KAL-07-01-04 Weighted histogram showing multiple peaks

Beta Microdosimetry

The Kalahari is characterised by low levels of radioactive elements such as thorium,

potassium and uranium as well as a lack of very fine sediment. Both these characteristics are

demonstrated in this study. This can cause a process known as non-uniformity to occur

where hot-spots are created in the sediment concentrated around particles of radioactive

elements. These hot-spots can cause increased environmental dose rates to a limited

N = 22 Mean = 211.7± 143.10

Dose (s)

8007006005004003002001000

Pro

b. D

ensity

40

number of grains. This process could account for the large overdispersion experienced in the

samples in this study, particularly because of the low concentrations of radionuclides.

Age model selection

Olley et al. (2004) suggest that MAM, and not CAM, should be used when the

overdispersion seen in all samples is greater than 10%. However, the reason this decision

process has not been used is twofold. Firstly, Olley et al. use large overdispersion as an

indicator in fluvial sediments whereas the samples in this study are thought to be aeolian in

origin. Bailey and Arnold (2006) also put forward a decision process for age model selection.

However, this method was not used to assess which model was best in this study as it

included models (such as the lower 5% model) which were not applicable to these samples.

Overall the most appropriate model is the Central age model (CAM) (Galbarith et al., 1999).

This model was used because there may have been post-depositional mixing of sediment in

an unknown direction. In addition the large overdispersion may be the result of

microdosimetry. This model is also used in other northern Kalahari studies for the reasons

outlined above (e.g. Burrough et al., 2009). This model was used for all samples as there was

little variation in the sample overdispersion and radial plot structure throughout the sand

ramp core (figure 22).

41

Figure 22 - Radial plots from the top, middle and bottom of the sand ramp core. Other radial plots

are shown in appendix C An important point to note is the unusual structure of the radial plots. It

seems that as the De increases the precision of the value decreases. All values have been checked to

make sure they are not saturated and also that the most appropriate fits have been used for the

data. There is currently no explanation as to the reason for the structure observed.

42

3.2 Chronology of the Tsodilo Sand Ramp

Having used the central age model, the equivalent doses and the final OSL ages were

calculated. Table 3 summarises the OSL dating results. The sand ramp started to form over

82ka. In general the OSL ages measured are in chronostratigraphic order within errors

(figure 23). However, there is a minor age inversion between KAL-07-01-11 and KAL-07-01-

10 (A). This inversion coupled with the large errors and proximity of sample KAL-07-01-9

suggest the possibility of a period of rapid accumulation followed by a period of inactivity.

There is also a significant age inversion between two pairs of samples, KAL-07-01-8, KAL-07-

01-7 and KAL-07-01-6, KAL-07-01-4 (figure 23). However, the reason for this age inversion is

unknown. There may be methodological errors in the measurement or collection of the

samples, or they may represent post-depositional mixing due to bioturbation within the

sand ramp. This age inversion causes problems for assessing rates of accumulation further

up the sand ramp. This is because it is unclear whether older sediment has been moved

downwards or younger sediment upwards in the sand ramp. Therefore two different rates

of accumulation, using lines of best fit, have been calculated (figure 23 B and C). Between

samples KAL-07-01-6 and KAL-07-01-1 there seems to have been a possible period of

gradual accumulation at rate 0.12mka-1. In contrast a much faster rate of accumulation is

evident when KAL-07-01-6 and KAL-07-01-4 are excluded from the calculation and KAL-07-

01-8 and KAL-07-01-7 are included (0.31mka-1).

Sample

Depth (m) ±

0.1

Total Environmental

Dose Rate (Gy/ka)

CAM De (Gy) CAM De error

(Gy) Age (ka)

KAL/07/01/1 1.00 0.35 ± 0.03 8.08 1.24 22.81 ± 4.11

KAL/07/01/2 1.50 0.38 ± 0.03 8.87 1.38 22.52 ± 5.95

KAL/07/01/4 2.50 0.31 ± 0.03 12.00 1.51 35.57 ± 8.78

KAL/07/01/6 3.50 0.38 ± 0.04 17.75 2.30 42.87 ± 10.21

KAL/07/01/7 4.00 0.35 ± 0.03 13.36 1.30 26.46 ± 5.62

KAL/07/01/8 5.00 0.32 ± 0.03 15.88 1.53 34.71 ± 8.40

KAL/07/01/9 6.00 0.29 ± 0.03 25.34 1.86 69.61 ± 12.61

KAL/07/01/10 7.00 0.31 ± 0.03 31.18 1.89 82.42 ± 14.02

KAL/07/01/11 8.00 0.34 ± 0.04 34.85 2.34 82.07 ± 15.55

Table 3 - A table showing a summary of environmental dose rates and sample ages

43

Figure 23 - Sample OSL ages from the Tsodilo Sand Ramp. A – Possible period of instantaneous

deposition and then reduced activity B Line of best fit (y = 0.12x - 1.22, R2 = 0.95) for samples KAL-

07-01-6, KAL-07-01-4, KAL-07-01-2 and KAL-07-01-1 C – Line of best fit (y = 0.31x - 5.32, R2 = 0.82) for

samples KAL-07-01-8, KAL-07-01-7, KAL-07-01-2 and KAL-07-01-1

A

B

C

44

3.3 Sedimentology

Overall there seems to be a large degree of homogeneity throughout the sand ramp. In

addition no talus or fluvial deposits are recorded when the core was collected. A summary

of sedimentological data can be found in appendix D.

3.3.1 Percentage of Organic Matter and Carbonates

Both organic and carbonate content were under detectable limits for all samples

demonstrating the complete lack of any evidence of vegetation within the sand ramp’s

history. This is unusual as it was expected there would be some evidence of paleosols within

the sand ramp which may have represented periods of reduced activity. This lack of organic

content is uniform throughout the sand ramp possibly demonstrating that within the

lifetime of the ramp there have been no periods where inactivity has been sufficient to

allow vegetation to grow. This is in contrast to the current condition on the surface of the

sand ramp (figure 24) where bushes and small trees now dominate the landform.

Figure 24 - A photograph of the sample site showing large amounts of vegetation covering the sand

ramp’s surface

45

3.3.2 Grain Shape

Table 4 shows how the grains throughout the sand ramp have high levels of sphericity and

roundness. This suggests that aeolian processes were dominant on these grains prior to

burial. In addition there seem to be high quantities of quartz in comparison to other

minerals such as feldspar. This is a common occurrence in the Kalahari (Burrough and

Thomas, 2013).

Table 4 – Grain sphericity, roundness and % quartz in each sample.

Sample: Sphericity - assessed by eye (Pettijohn et al., 1987)

Roundness - assessed by eye (Pettijohn et al., 1987)

% Quartz assessed by eye

KAL/07/01/1 High

Rounded/ Subround 95

KAL/07/01/2 High Rounded/ Subround 98

KAL/07/01/4 High Subround 98

KAL/07/01/6 High Rounded/ Subround 98

KAL/07/01/7 Low Subround 98

KAL/07/01/8 Medium Subround 98

KAL/07/01/9 High Subround 98

KAL/07/01/10 High Subround 98

KAL/07/01/11 Low Subround 98

46

3.3.4 Grain size and colour

The average grain size for the sand ramp is 257 µm with the mean grain size remaining

relatively constant throughout the core (between 242 µm – 278 µm) (figure 25). The degree

of sorting (1.67-1.79) and distribution of grain sizes is also relatively consistent throughout

the sand ramp. All of the samples primarily consist of sand (over 90%) with a small amount

silt (between 1.9-3.9%). This suggests a strong influence from aeolian processes as opposed

to fluvial or mass movement. Figure 26 shows three grain size distribution graphs for

samples KAL-07-01-1, KAL-07-01-6 and KAL-07-01-11, i.e. the top, middle and bottom of the

sand ramp. Three images were also taken using a microscope camera at magnification x40

also help to demonstrate the similarity in the sedimentology between samples. Finally the

colour of the sediment analysed seems relatively consistent throughout the core (5 YR 5/6

Yellowish Red and 5 YR 5/8 Yellowish Red). The diagram of the sample points is also

coloured with the appropriate colour as measured on the Munsell Colour Chart. The red

iron oxide coating on the grains has been found in the elsewhere in the Kalahari and is

thought to be a pre-depositional feature (Stone and Thomas, 2008).

Figure 25 - the mean grain size for each sample and the percentage of different sediment types for

each sample

47

Figure 26. – Change in colour through the sand ramp (A), grain size distributions (B) and images of

grains at magnification x40 for samples KAL-07-01-1, KAL-07-01-6 and KAL-07-01-11 (C)

A B C

KAL-07-01-1

KAL-07-01-6

KAL-07-01-11

48

4 Discussion

4.1 Sand Ramp Formation

4.1.1 Age

From the dates that have been calculated the sand ramp is at least 82.42 ka ± 14.02ka.

However, due to equipment limitations no samples could be taken deeper than 8m which

suggests that the sand ramp may be older than 82ka. The age of the sand ramp demonstrates

the utility of such features in helping us to understand palaeoenvironmental change as they

clearly stretch further back than other more ephemeral landscape features such as dunes

which frequently do not often hold records for more than 80ka (Burrough and Thomas 2013).

The Tsodilo sand ramp is one of the oldest to be studied in the world; in the Mojave Desert the

Solider Mountain sand ramp is only 15ka (Bateman et al., 2012) and in South Africa the sand

ramp is 45ka (Telfer et al., 2012).

4.1.2 Accumulation Rates

An assessment of the sand ramp’s OSL ages can provide an indication as to the rate of

accumulation and periods of increased activity. Figure 23 shows there are three major

periods in the sand ramps chronology. The first is the period centred on 80ka when

around 2m of sediment were deposited. This is then followed by a period of decreased

activity centred on around 55ka followed by another period of more gradual

accumulation between 45ka to 22ka. However, it is difficult to assess the rate of

accumulation in this later episode due to the age inversion seen within the sand ramp

(figure 23). Two different rates have been calculated of 0.11mka-1 and 0.31mka-1. It is

impossible to tell which of these rates is the most appropriate for the sand ramp as it

is unknown the nature of post-depositional sediment mixing. However, it is clear that

the rates of accumulation recorded in this later episode are much lower than in other

sand ramp studies. The Ardakan sand ramp (Thomas et al., 1997) experienced periods

of accumulation of 15mka-1 and the South African sand ramp (Telfer et al., 2012)

experienced rates of up to 2mka-1. This difference in accumulation rates may be the

result of localised climate factors, such as windiness and sediment supply, at these

different sand ramp sites (Telfer et al., 2012). Another possible explanation is the

49

preservation of sediment within the sand ramp. This is a particular problem in the

northern Kalahari compared with the southern, as its drier climate can make it difficult

for the onset of dune accumulation to be easily recorded (Nanson et al., 1992 cited in

Thomas and Burrough, 2013). Bailey and Thomas (2014) suggest that periods of

accumulation directly followed by wetter periods of preservation will also be

preferentially recorded in the sediment record. This evidence suggests that the

accumulation of sediment centred on 80ka may have been preferentially preserved

during a period of stability compared with later episodes of accumulation which may

not have been as well preserved and so now exhibit much slower accumulation rates

(Bailey and Thomas, 2014).

The multiple episodes of accumulation seen in the Tsodilo sand ramp supports

theories provided by Telfer et al. (2012), Thomas et al., 2007, Tchakerian and

Lancaster (2002) and Thomas et al. (1997) concerning the multi-episodic nature of

sand ramp formation. Bateman et al.’s (2012) theory that sand ramps form in a single

“window of opportunity” is not evident in this study. However, Bateman et al. (2012)

does suggest that accumulation can occur over very short timescales (around 5ka)

which mirrors the period of very rapid accumulation centred on 80ka in the Tsodilo

sand ramp. However, the second, much longer, period of accumulation (between 45-

22ka) seems more representative of Telfer et al.’s (2012) study of the south African

sand ramp which accumulated over a period of 29ka. Overall these differing

accumulation rates seem to reflect the individuality of sand ramp formation as a result

of different localised factors influencing their formation. There seems to be no set

timeline or chronology for their rate of formation.

4.1.3 Sedimentary Record

The sedimentary record of the Tsodilo sand ramp also aids our understanding of its

formation. Overall the sediment characteristics are similar to those found in the sand

dunes in the Tsodilo area with high levels of sand content and a small amount of silt

(Thomas et al., 2003). These sediment characteristics are also found elsewhere in the

Kalahari where variations in colour and size of grains remain consistent throughout the

strata of sand dunes (Stone and Thomas, 2008). Another sedimentary feature found in

50

the Tsodilo Area is alternating layers of sand and rock debris found in the caves in the

Tsodilo Hills (Robbins et al., 2000). This layering is also found in other sand ramp

studies, where stone horizons, paleosol deposits or talus are interspersed with aeolian

sediment (Telfer et al. 2012, Bateman et al., 2012, Turner and Makhlouf, 2002 and

Thomas et al., 1997). However, this banding does not seem to be present in the

Tsodilo ramp’s formation. One possible reason for this discrepancy between the caves

and the sand ramp is due to the protected nature of the caves where layers of debris

can be conserved. The sand ramp is exposed to fluvial and aeolian erosion events.

These erosive periods may have removed all evidence of paleosols or debris. Another

reason for the lack of stratigraphy in the Tsodilo sand ramp can be found in other

studies of the Kalahari. These paleosol and debris layers have not been observed

elsewhere in the Kalahari, even during periods of inactivity. Tsoar et al. (2005) and

Munyikwa (2005) suggest that bidirectional wind regimes may account for the lack of

stratigraphy and structure to sand dunes as the change in wind direction can cause the

mixing of sediment which removes the layers of paleosols (Stone and Thomas, 2008).

This theory is supported by Clemmensen et al. (1997) who suggest that the

morphology of a sand ramp can causes alterations in the wind direction and regime

around it. This means that the lack of stratigraphy is as a result of the structure and

formation of the sand ramp rather than an indication of changes in the

palaeoenvironment.

Another possible reason for the lack of stone horizons or talus deposits in the sand

ramp is the distance of the sample site from the Male Hill. Unlike the Jordanian sand

ramp study, which forms as a result of a rock fall close to the topographical feature

against which the sand ramp forms, the lack of proximity to the Tsodilo hills, coupled

with the low erodibility of the Tsodilo quartzite inselbergs, may account for this

absence (Turner and Makhlouf, 2002). Further sampling closer to the Male Hill may

reveal this more distinct layering as it would be better protected from changing wind

directions and be more likely to be covered in rock falls or fluvial deposits from the hill.

Another difference between the Tsodilo sand ramp and other ramp studies is the lack

of river or stream channels on the surface of the ramp (e.g. Turner and Makhlouf,

2002). From observations during the collection of the sand ramp core there did not

51

seem to be any channels on the surface of the ramp. Further investigation on google

maps did not offer any indication of channels either. However, this may have been due

to the high levels of vegetation now present on the sand ramp’s surface (figure 24).

4.1.4 Sediment Source

Bateman et al. (2012) suggests that the source of sediment for the sand ramp may be

a controlling factor in its formation. However, the sediment source for the Tsodilo

sand ramp is unclear. The homogeneity in grain size, sorting, colour and shape

throughout the core suggests that the sediment originated from a single source.

Furthermore, the dominance of quartz coated in iron oxide and the orientation of the

sand ramp on south-east of the Tsodilo Hills, suggests the sediment source of the sand

ramp is to the South and might be from the sand dunes found there or the nearby

relict lake shoreline which contain sediment of a similar colour (Figure 27) (Thomas et

al., 2003). Other sources of sediment, such as the Okavango Delta and Makgadikgadi

Depression, are unlikely to be the origin of the Tsodilo sand ramp due to the different

coloured sediment found at these sites (white or pale brown) (e.g. Burrough et al.,

2009). However, the iron oxide coating may have arisen during transportation of the

sediment which does not completely exclude these two major sources of aeolian sand.

Further analysis of the sediment collected for the Tsodilo sand ramp, using techniques

such rare earth element content may offer a better understanding of its origin.

Sedimentological analysis also suggests that aeolian processes were dominant in the

accumulation of the sand ramp. The high percentage of fine sand, the small amount of

fine dust and the round and spherical nature of the grains found in the samples

demonstrates the sediment’s aeolian origin (Sun et al., 2002). If the Tsodilo Sand Ramp

were to be placed in the qualitative assessment of sand ramp processes in figure 11 it

would sit very close to the aeolian corner with features closely resembling a climbing

dune.

52

Figure 27 – A geological map of the Northern Kalahari (Mallick et al., 1979) the key can be found in appendix F

N

Okavango Delta

Delta

Tsodilo Hills

Makgadikgadi

Depression

Linear Sand Dunes

53

4.2 Forcing Factors

As well as providing a possible explanation of sand ramp formation, the rates of

accumulation and sediment properties of the Tsodilo sand ramp also provide an

insight into the possible driving factors for climatic change in the Tsodilo Hills area

over the past 80ka (Thomas et al., 2005). Sediment accumulation phases have often

been associated with dry climate periods (e.g. Munyikwa, 2005 and Stokes et al.,

1997). This would suggest that the sand ramp’s rapid formation at 80ka and the

gradual accumulation between 45-22ka are periods of aridity and the episode of

reduced activity at 55ka is a period of wetter conditions. However, a number of other

studies point towards other driving factors for sediment accumulation. Chase (2005)

and Chase & Thomas (2007) suggest that increased windiness coupled with a good

sediment source can cause accumulation even during wet periods. In contrast,

McFarlane et al. (2005) suggest that precipitation can cause the transfer of sand from

one part of a landform to another. Other studies suggest that the amount of

vegetation cover (Hesse and Simpson, 2006) and seasonal changes in climate (Wang et

al., 2005 cited in Telfer and Thomas, 2007) can also influence accumulation. Overall,

the complex interaction of these factors, coupled with climatic feedback mechanisms,

suggests a much more complicated picture of palaeoenvironmental change in the

Tsodilo region. It also demonstrates that it is only possible to distinguish the possible

driving factors in sand ramp formation by comparing the rates of accumulation and

OSL ages of the Tsodilo sand ramp with other studies in the Tsodilo area and Kalahari.

4.3 Palaeoenvironmental Context

4.3.1 Dune and paleolake chronologies

The large number of dune chronologies in the wider Kalahari region and Tsodilo area

allow for a direct comparison with the Tsodilo sand ramp to help identify the forcing

mechanisms which are dominant in its formation. The period of accumulation

recorded in the Tsodilo sand ramp between 45-22ka, coincides with other OSL ages

and perceived sediment accumulation periods in other parts of the Kalahari (figure 7)

(Thomas and Burrough, 2013). For example, in the northern Kalahari, Thomas et al.

(2000) suggests a period of aridity and dune building between 46-21ka and 32-20ka

54

and in the southern Kalahari Telfer and Thomas (2007) indicate a period of dune

building between 27-25ka. Thomas et al. (2003) and Blumel et al. (1998) also indicate

that in the local Tsodilo area dune building and increased windiness occurred between

37-28ka. These studies all demonstrate that this period of sediment accumulation in

the Tsodilo sand ramp was most likely during a dry phase in the climate record both

locally and regionally. The period of reduced activity recorded in the Tsodilo sand

ramp, centred on 55ka, can also be seen to correlate with the review of studies

undertaken by Thomas and Burrough (2013). Between 50-78ka there is a period where

no OSL ages have been recorded in the northern Kalahari which coincides with the

brief period of reduced activity in this study (figure 7). Furthermore, there is no record

of accumulation in the Tsodilo area during this time (Thomas et al., 2003). The period

of rapid accumulation centred on 80ka also coincides with a perceived dry period in

the northern Kalahari. Two mega lake phases between 64.2ka and 92.2ka are recorded

by Burrough et al., (2009a). This period of rapid accumulation in the Tsodilo ramp may

represent a period of aridity in the northern Kalahari following one of these mega lake

phases.

However, whilst there is agreement between some of the OSL dates from the Tsodilo

sand ramp and other luminescence studies in the Kalahari there are also discrepancies.

The period of accumulation at 80ka, whilst it falls between two meg-lake phases, does

not correlate with other periods of accumulation that have been recorded in the

northern Kalahari around 80ka (Thomas and Burrough, 2013). Dune building is

observed before and after 80ka, but not during this period. Thomas and Shaw (2002)

record a period of accumulation around 100ka and Telfer and Thomas (2007) record

two periods at 76-77 and 95-105ka. Stokes et al. (1998) also indicate periods of aridity

in the Tsodilo area centred on 73ka and 101ka. All these studies indicate dune building

either side of the accumulation period in the Tsodilo sand ramp. These studies imply

that this major accumulation phase in the Tsodilo sand ramp may have coincided with

a period of reduced accumulation elsewhere in the Kalahari and wetter conditions in

the Tsodilo region. There is also evidence for wetter conditions during the 45-22ka

period of accumulation in the Tsodilo sand ramp. Thomas et al. (2003) indicate wetter

conditions centred on 23ka. They also suggest that during this period of accumulation

55

there was overlap with two lacustrine phases in the Tsodilo Hills between 40-33ka and

28-23ka (Thomas et al., 2003). Robbins et al. (2000) also indicate lacustrine phases

around this period. Elsewhere in the Kalahari a number of mega-lake phases are also

recorded, centred on 26.8 and 38.7ka, which indicate the dominance of wetter

regional conditions around this period (Burrough et al., 2009a). Burrough et al (2007)

suggest that the occurrence of mega-lake phases during sediment accumulation could

be explained by the northward shift of the ITCZ as a result of changes in precessional

insolation (Shi et al., 2000) which causes wetter environments north of the Kalahari

whilst dry conditions prevailed in northern Botswana. The precipitation deposited

away from the Kalahari would then be transported via the Okavango River southwards

(Burrough et al., 2007). This would have accounted for the high lake stand phases

recorded in paleolake relict shorelines (Burrough et al., 2007). However, Thomas et al.

(2003) state that there are no river channels leading into the Tsodilo paleolake

indicating that precipitation must have occurred in the Tsodilo area for a lake high

stand to occur.

Overall the accumulation in the Tsodilo sand ramp supports the idea that periods of

accumulation can coincide with both phases of aridity and wetter conditions. During

the wetter conditions other factors may be dominant, such as increased windiness and

sediment supply (Chase, 2005). Thomas et al. (2000) demonstrate how climatic

conditions over the Indian Ocean increases wind speeds in continental Africa during

wet periods further pointing to a change in forcing factors not dependent on arid or

wet phases. The correlation between periods of accumulation and wet conditions,

coupled with the sedimentological evidence for a single sediment source, suggests

that the limiting factor in accumulation for the Tsodilo sand ramp is likely to be

dictated by sediment supply and windiness rather than phases of aridity. This theory is

supported by evidence from the Soldier Mountain sand ramp where sediment supply

was seen to play a significant role in sand ramp formation (Bateman et al. 2012). In

addition, this also suggests that the period of reduced activity centred on 55ka may

have been a period of reduced windiness and sediment supply rather than solely the

result of wetter conditions in the area (Bailey and Thomas, 2014).

56

The dominance of forcing factors, other than wet and dry phases, for sediment

accumulation also causes problems in suggesting possible climatic changes in the

Tsodilo area. Overall, there are a number of possible millennial-scale climatic forcing

factors suggested as the reasons for environmental change in the Kalahari and Tsodilo

Area. These include movements of the ITCZ (Braconnot et al., 2000), changes in sea-

surface temperatures in the Atlantic (Little et al., 1997), changes in the inter-tropical

boundary, insolation variations, and “non-linear millennial-scale ice rafting events”

(Burrough et al., 2009, p.1409). However, because accumulation periods in the sand

ramp’s chronology cannot be solely attributed to wet and dry phases it is difficult to

assess which climatic changes occurred in the Tsodilo area. In addition the localised

nature of this study and the complex interactions of these climate regimes also make it

difficult to assess the relevance of different climatic changes as there are complex

feedbacks involved, particularly at a local scale (Burrough et al., 2009).

4.3.2 Holocene and LGM

Whilst no samples were taken from the top portion of the sand ramp, 1m of sand did

accumulate during the last 20ka. It is unclear at what point this occurred; whether it

was a continuation of the accumulation period recorded between 45-22ka or the

result of a short period of rapid accumulation. Thomas et al. (2003) suggest that a wet

period occurred between 27-12ka followed by a drier episode between 22-19ka. This

time period seems to overlap with a number of periods of dune building in the Tsodilo

area as mentioned by Thomas et al. (1997) and Blumel et al. (2000). Thomas et al.

(2003) also indicate that there has not been any dune building since the Last Glacial

Maximum which contrasts with the 1m of sediment measured on the sand ramp.

However, other studies in the Kalahari suggest there have been dry conditions and

dune accumulation since the Last Glacial Maximum (e.g. Telfer and Thomas, 2007 and

Burrough and Thomas 2013). Pollen data from the Atlantic also supports the

suggestion that dry climatic condition dominated from 14ka (Shi et al., 2000). In

contrast some studies show that between the LGM and the start of the Holocene

there was a period of wetter climatic conditions interspersed with intensely arid

periods (Brook et al., 1992). This supports the hypothesis that this layer of sediment

57

accumulated in short bursts. Further sampling closer to the surface of the sand ramp

could be undertaken in order to assess environmental change during the Holocene.

However, this comes with the increased risk of post-depositional mixing and other

difficulties associated with the environmental record.

58

5 Conclusion

The Tsodilo sand ramp is an important landform in the northeastern Kalahari Desert

and its chronology raises a number of questions as well as offering some answers to

the formation of sand ramps and palaeoenvironmental conditions in the Tsodilo area

as well as the Kalahari Desert itself.

The formation of the Tsodilo sand ramp occurred over a period of around 80ka. The

age of the sand ramp suggests that future use of these features could be useful for

further palaeoenvironmental analysis as they seem to be relatively stable over a very

long period of time. The Tsodilo sand ramp is predominantly aeolian in origin although

it may have experienced fluvial and mass movement influences which were eroded

before they could be conserved in the palaeoenvironmental record. This is in

opposition to other sand ramp studies where layers of talus, stone and paleosols are

dominant features of sand ramp stratigraphy. The sand ramp also contains no fluvial

channels on its surface further differentiating it from other studies. All of these factors

demonstrate the difficulty in creating general statements about the structure of sand

ramps. They are rare landforms whose evolution is heavily dependent on localised

factors.

The Tsodilo sand ramp accumulated in two distinct episodes (and also one of reduced

activity). This multi-episodic formation supports studies by Telfer et al. (2012), Thomas

et al., 2007, Tchakerian and Lancaster (2002) and Thomas et al. (1997) but challenges

the theory by Bateman et al. (2012) of a single episode or “window of opportunity”. In

addition the rates of accumulation of the Tsodilo ramp seem to differ from other

studies with an earlier period of very rapid accumulation and a much later period of

slow accumulation. This further supports the idea that site specific factors play a

dominant role in sand ramp formation.

The two accumulation episodes and the one of reduced activity were compared with

other palaeoenvironmental studies in order to discern the forcing mechanisms

involved in the accumulation of sediment in the sand ramp. There was some

correlation with other studies. However, it was found that the period of accumulation

59

in the Tsodilo ramp seemed to occur during localised and regional wet and dry phases

(e.g. Thomas et al., 2003 and Robbins et al., 2000). This suggests that forcing factors

other than aridity were dominant in the ramp’s formation. The single sediment source

and accumulation during wet conditions points to windiness and sediment availability

as the two primary factors in the sand ramp’s formation. Accumulation during both

wet and dry conditions coupled with the localised nature of this study also makes it

difficult to specify the controlling climatic factors during the ramp’s history. Further

analysis over a wider part of the Tsodilo area may allow for more specific conclusions

to be made in relation to the prevailing climatic condition during the last 80ka.

Overall, this study adds to the increasing number of palaeoenvironmental studies in

southern Africa. It demonstrates that sand ramps are a key palaeoenvironmental

proxy which, when identified, can aid our understanding of past environmental

change.

60

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7 Appendices

Appendix A - Radial Plots

Below is an example of a radial plot from this study (Figure 28). The y axis on the left-hand

side shows the standardised estimate. This shows how the De values measured vary from a

chosen De value (in this case the De value as calculated from the central age model) (Duller,

2008). In order to read De values off the plot a straight line must be drawn from the origin

to the curved y axis on the right where the equivalent dose can be read off (ibid.).The

position of the points on the graph also demonstrates the relative error and can be read off

from the x axis at the bottom of the plot (Galbraith et al., 2005).

Figure 28 - De values for sample KAL/07/01/1. The precision is plotted on the x axis. The De

value is given by the slope of the line from the origin. The most precise estimates fall to the

right and the least precise to the left.

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Appendix B – Cosmic Dose Rate Modelling

The equivalent dose (De) has been measured in the lab. De should equal the total radiogenic

dose (calculated from potassium, uranium and thorium levels) plus the cosmic dose

(modelled using DRAC (Durcan, submitted)). The sample ages were calculated using the “as

found” cosmic dose in order to achieve an estimate of how long each sample was buried for.

The calculation 𝐷𝑒 − (𝑐𝑜𝑠𝑚𝑖𝑐 + 𝑟𝑎𝑑𝑖𝑜𝑔𝑒𝑛𝑖𝑐) = 0 was entered into excel. Solver was then

used to minimize the difference between the total dose (cosmic + radiogenic) and De within

the boundaries that we provided (i.e. the time spent buried at a certain depth) (Burrough,

pers comms). Due to uncertainties associated with our De Monte Carlo method was used to

generate multiple solutions (100 iterations) in order to give an uncertainty for the final, total

environmental dose rate.

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Appendix C – Radial Plots of all samples

KAL-07-01-1 overdispersion = 74% central De = 8.08 ± 1.24 n = 25

KAL-07-01-6 overdispersion = 57% central De = 17.75 ± 2.3 n = 22

KAL-07-01-4 overdispersion = 56% central De = 12 ± 1.51 n = 22

KAL-07-01-2 overdispersion = 68% central De = 8.87 ± 1.38 n = 21

73

KAL-07-01-8 overdispersion = 43% central De = 15.88 ± 1.53 n = 24

KAL-07-01-7 overdispersion = 42% central De = 13.36 ± 1.3 n = 22

KAL-07-01-10 overdispersion = 21% central De = 31.18 ± 1.89 n = 24

KAL-07-01-9 overdispersion = 29% central De = 25.34 ± 1.86 n = 23

KAL-07-01-11 overdispersion = 25% central De = 34.85 ± 2.34 n = 23

74

Appendix D – Summary of sedimentological data

*All zero values as both organic and carbonate content was under detectable limits

Sample: Depth

(m) ±

0.1

Munsell Colour Mean Particle Size (µm)

Sorting (s.d.)

Coarse sand %

Medium sand (%)

Fine Sand (%)

Silt (%)

Clay (%)

Mud (%)

Organic Content* (%)

Carbonate Content* (%)

Sphericity - assessed by eye (Pettijohn et al., 1987)

Roundness - assessed by eye (Pettijohn et al., 1987)

% Quartz assessed by eye

KAL/07/01/1

1.00 5 YR 5/6 Yellowish Red

260.7 1.79 11.7 42.8 34.5 3.9 0 3.9 0 0 High Rounded/ Subround

95

KAL/07/01/2

1.50 5 YR 5/6 Yellowish Red

273.1 1.68 11.8 45.7 35.2 2.3 0 2.2 0 0 High Rounded/ Subround

98

KAL/07/01/4

2.50 5 YR 5/8 Yellowish Red

261.5 1.73 11 43.4 35.7 2.6 0 2.6 0 0 High Subround 98

KAL/07/01/6

3.50 5 YR 5/8 Yellowish Red

278.5 1.67 12.4 46.5 34.6 1.9 0 1.9 0 0 High Rounded/ Subround

98

KAL/07/01/7

4.00 5 YR 5/8 Yellowish Red

242.0 1.68 7.2 41.2 40.9 2.1 0 2.1 0 0 Low Subround 98

KAL/07/01/8

5.00 5 YR 5/8 Yellowish Red

247.3 1.69 8.6 42 39.6 1.9 0 1.8 0 0 Medium Subround 98

KAL/07/01/9

6.00 5 YR 5/8 Yellowish Red

260.1 1.67 9.7 43.9 37.8 1.8 0 1.8 0 0 High Subround 98

KAL/07/01/10

7.00 5 YR 5/8 Yellowish Red

242.8 1.71 8 40.7 39.9 2.2 0 2.2 0 0 High Subround 98

KAL/07/01/11

8.00 5 YR 5/8 Yellowish Red

242.1 1.74 8.2 40.7 38.8 3.2 0 3.1 0 0 Low Subround 98

75

Appendix E – Grain distribution graphs for all samples

KAL-07-01-1

KAL-07-01-8 KAL-07-01-7

KAL-07-01-6 KAL-07-01-4

KAL-07-01-2

76

KAL-07-01-10 KAL-07-01-9

KAL-07-01-11

77

Appendix F – Key to geological map (Mallick et al., 1979)