1

Single grain OSL dating of the Middle

Palaeolithic site Lusakert in Armenia

V. Lukich

Submitted as an integral part of the Masters of Science Degree in Quaternary Science,

Royal Holloway, University of London. This report presents the results of original

research undertaken by the author and none of the results, illustrations or text are based

on the published or unpublished work of others, except where specified and

acknowledged. This text does not exceed the 10,000 word limit, being 9,691 words in

length (excluding bibliography, appendices and illustrations).

Date of Submission: 24.08.2012

......................................................

Vasilija Lukich

Paper ID 18017443

2

Acknowledgements

First and foremost I would like to express my deepest gratitude to Dr. Simon Armitage,

for providing unwavering guidance and support in the face of my ceaseless pestering;

you deserve a medal, seriously. Thanks also to Dr. Simon Blockley and Dr. Ian Candy

for always being willing to answer even the smallest questions, and to Iñaki Valcarcel

and Natalie Russell for their faultless direction in the lab.

This project would not have been possible without the cooperation and advice from Dr.

Dan Adler and Dr. Keith Wilkinson, many thanks for their informative visits and quick

email responses, and crucially, the Lusakert samples themselves.

I am indebted to Matt, Betty and Jonny for their meticulous editing, and to the 2012

MSc Quaternary Science gang for being the best classmates a lone Canadian could ask

for.

Finally, thank you to my parents, whose love and encouragement made this happen.

3

Abstract

Previous chronological studies indicate the possibility of Middle Palaeolithic industries

in the Southern Caucasus at a later date than elsewhere in Europe. Lusakert, a

rockshelter in the Armenian Caucasus, has an abundance of Late Middle Palaeolithic

tools in a stratified depositional environment. This arrangement provides the potential to

create a robust chronology for this time period in the southern Caucasus. The only

existing chronological control for the site is an Argon date of ~200 ka on the basalt flow

in which the rock shelter is formed; a more widespread application of modern

chronological techniques is required to make sense of this complicated story. In turn,

the archaeological record in Armenia could provide crucial clues for deciphering the

patterns of Neanderthal social interaction amongst themselves and possibly also with

modern humans.

Single grain Optically Stimulated Luminescence (OSL) dating was undertaken on three

archaeological units from the interior of the rockshelter. Initial analysis showed that the

samples have a low quartz content, low intrinsic brightness, and are dominated by a

relatively slowly decaying OSL component. To account for these characteristics,

samples were subject to various tests to determine the best possible methods for

obtaining accurate equivalent doses. Overdispersion was uniformly over 20%,

warranting the use of the Finite Mixture Model, from which three equivalent dose

populations emerged; the main group is centered at approximately 20ka, with the older

and younger at around 40ka and 8ka respectively. Possible reasons for the spread in

equivalent doses are explored, including both luminescence aspects (beta heterogeneity,

partial bleaching and geologic instability) and external environmental factors

(bioturbation, cryoturbation, and input of fluvial sediments). Geologic instability and

reworking are identified as the most likely factors.

It is concluded that the ages for the sediment units sampled are unreliable and further

work on the luminescence characteristics and depositional environment is required to

obtain a more reliable OSL chronology at Lusakert.

4

Table of Contents

1. Introduction 1

1.1 Neanderthals and Modern Humans: Setting the Scene 2

1.2 The Role of the Caucasus 3

1.3 Archaeology in the Southern Caucasus 4

1.4 Lusakert Rockshelter 7

1.5 OSL Dating of Archaeological Deposits 7

1.6 Aims and Objectives 10

2. Principles of OSL 11

2.1 Basic Principles 12

2.2 Single Grain OSL 13

3. Methodology 15

3.1 Sampling Strategy and Sample Preparation 16

3.2 Luminescence Equipment 17

3.3 Single-Aliquot Regenerative Dose Protocol 18

3.4 Dose Recovery Test 20

3.5 Rejection Criteria 23

3.6 Statistical Models for Estimating Burial Dose 23

3.7 Environmental Dose Rate Estimation 25

3.8 Synthetic Aliquots 26

4. Results 28

4.1 Sample Characteristics 29

4.2 Equivalent Dose Estimation 29

4.3 Dosimetry and Age Estimation 31

4.4 Synthetic Aliquots 32

5. Discussion 33

5.1 Synthetic Aliquots 34

5.2 Component Analysis 34

5.2.1 Sample Characteristics 34

5.2.2 Fast Ratio 34

5.2.3 Linearly-Modulated OSL 35

5.3 Final Age Determination Uncertainties 36

5.3.1 Luminescence Properties 37

5

5.3.2 External Factors 39

5.3.2.1 River and Floods 39

5.3.2.2 Bioturbation and Cryoturbation 40

6. Conclusion 43

Bibliography 46

Appendicies 52

Appendix 1. Summary of rejected grains 52

Appendix 2. Water content measurements 52

Appendix 3. Values for cosmic dose rate 53

Appendix 4. Synthetic aliquot data 53

Appendix 5. Fast Ratio calculations and results 54

6

Tables

1.1 Archaeological sites in the Caucasus 6

1.2 Summary of Lusakert Stratigraphy 9

4.1 Accepted Grains 29

4.2 Overdispersion Values 30

4.3 Age Summary – Measured Water Content 31

4.4 Age Summary – Estimated Water Content 31

4.5 Synthetic Aliquot Results 32

Figures

1.1 Map of Dispersal Routes 3

1.2 Map of the Caucasus and Important Archaeological Sites 5

1.3 Excavation Plan Map 8

2.1 Band Gap Diagram 13

3.1 Sample Locations 16

3.2 SAR Protocol 19

3.3 Dose Recovery Slow Curve 21

3.4 Dose Recovery Results 22

3.5 Growth Curve Examples 24

4.1 Radial Plots of FMM Des 30

5.1 LM-OSL Graph 36

5.2 Overdispersion from Partial Bleaching 39

5.3 Location of Lusakert in Relation to River 40

5.4 Microphotographs of Bioturbation and Cryoturbation 41

Equations

2.1 Age Equation for Luminescence 12

3.1 Dose Rate Equation 26

3.2 Equation for Wet Gamma 26

3.3 Equation for Wet Beta 26

7

1. INTRODUCTION

8

1.1 Neanderthals and Modern Humans: Setting the Scene

In the fields of palaeoanthropology and Palaeolithic archaeology, investigations into the

uniqueness of human beings are part of a much larger inquiry concerning the origins of

modern humans (Shea, 2011a). What characterizes humans, both behaviourally and

physically, is a topic that is heavily debated in the literature of both disciplines, and

discussion can only be advanced through continued analysis and discovery of sites

containing both hominin fossils and artefacts. As such, much of the research

surrounding the Middle and Upper Palaeolithic (MP and UP) in Europe revolves around

the role that Homo neanderthalensis (Neanderthals) played in the evolution of

anatomically modern humans (AMH) (Bar-Yosef and Bordes, 2010). Modern human

traits of adaptability and behavioural variability may or may not be shared by

Neanderthals, a view which is being continuously developed and reassessed as new

research and evidence comes to light (Jöris and Adler, 2007). In the past, lithic

industries assigned to the Middle Palaeolithic of Europe were attributed solely to

Neanderthals – now it is known that both hominin groups created MP tool assemblages

in the Near East, and only the lack of fossils prevents such claims in Europe (Jöris and

Adler, 2007). Currently, the critical issues in need of clarification revolve around the

degree of cultural exchange between hominin groups, how and when modern humans

entered Europe, the period of time and location where Neanderthals and AMH might

have met, what those interactions entailed, and when and how Neanderthals became

extinct (Adler et al., 2008a).

In order to accurately assess dispersal rates and interactions between various hominin

populations in the Middle Palaeolithic, we must rely on chronometric records from

individual, inconsistently excavated archaeological sites (Adler et al., 2008a). Previous

dating attempts for the Palaeolithic were subject to substantial errors, preventing the

accurate interpretation of the time interval in which Neanderthals and modern humans

may have interacted (Jöris and Adler, 2007). As the greatest proportion of

archaeological information derives from material culture and the transitions therein, the

precise identification of the rate of these changes is crucial for compiling evidence for

the mechanisms operating during this sensitive time period (Adler et al., 2006).

9

1.2 The Role of the Caucasus

The Southern Caucasus is an area of particular interest to palaeoanthropological

research due to its position between the Black and Caspian seas which creates a

geographic corridor facilitating the migration of hominins between Africa, the Near

East, Europe and Asia (Fig.1.1) (Pinhasi et al., 2008). The main Caucasus mountain

range presents a significant barrier for the spread of floral and faunal communities,

effectively controlling and filtering the types of foreign interactions experienced by

local communities (Adler and Tushabramishvili, 2004). Weather systems are also

influenced by the range as cold dry air from the north is prevented from penetrating

south, whereas warm humid conditions originating over the Black sea predominate

(Adler et al., 2006). These conditions create an array of ecological niches populated by

diverse flora and fauna which may have promoted the creation of a biological refugium

during glacial periods (Bar-Yosef et al., 2006). The lack of significant climatic

oscillation during cold stages (Adler et al., 2006) makes the southern Caucasus an ideal

locale to study the interactions between Neanderthals and AMH (Bar-Yosef et al., 2006;

Adler et al., 2006). This isolation may have hampered the introduction of new cultural,

technological or biological innovations, resulting in the prolonged existence of Middle

Palaeolithic industries. The aim of current excavations and new chronological

investigations is to further clarify and provide evidence for or against this hypothesis

(Adler and Tushabramishvili, 2004; Jöris and Adler, 2007).

Figure 1.1. Map of Europe, Africa and Asia displaying some of the proposed dispersal routes, including a possible route through the Southern Caucasus (outlined).

10

1.3 Archaeology in the Southern Caucasus

As crucial as the Palaeolithic records from Armenia and Georgia may be, they have not

been studied in any type of systematic manner which employs modern scientific

methods. This prevents the comparison of material between sites of the Southern and

Northern Caucasus and hinders the meaningful integration of this region with a wider

picture of Middle Palaeolithic hominin distributions (Adler and Tushabramishvili,

2004). Prior to 2003, the only recognized MP sequence in Armenia was from Yerevan

Cave and Lusakert (Pinhasi et al., 2008). Many of the other known sites were open air

and their only contribution to the archaeological record is a techno-typological

assessment of lithic industries which were not found in situ; chronological estimates for

these sites can only be made through lithic correlation with nearby sites (Liagre et al.,

2006). The cultural groups referred to within these lithic industries are deemed to

represent variations in Middle Palaeolithic peoples (Adler and Tushabramishvili, 2004).

However, the lack of chronological control makes it impossible to determine if these

groups were contemporary and represented unique local traditions in lithic manufacture

or if they were mobile groups evolving their production strategies through time (Adler

et al., 2006). In addition to the issues surrounding sound chronologies previous

fieldwork has often lacked the precision and contextual control required to adequately

separate distinct archaeological horizons, and this confuses the true nature of lithic

assemblages, and creates false evidence of transitional industries (Adler et al., 2006).

Given the importance of its location a detailed understanding of the region’s MP

systems of subsistence and settlement is vital (Adler and Tushabramishvili, 2004), but it

cannot be achieved at present time using only the existing records.

To date, all hominin fossils recovered from the MP in Georgia have been attributed to

Neanderthals, with no fossils found in UP deposits or anywhere in Armenia. Although

there are no fossils associated with UP layers, the stark separation and contrast between

lithic assemblages from the MP to the UP points to AMH’s production of those

technologies (Adler et al., 2006). The lack of fossil evidence places the onus on the

modes of technology and faunal exploitation in the region to better pinpoint the manner

and rate of cultural change between hominin populations (Adler and Tushabramishvili,

2004).

11

Figure 1.2 Map of the Caucasus highlighting the most well-stratified and excavated sites to date. All but Mezmaiskaya are located in the Southern Caucasus (Map source: USGS).

Sites with comprehensive stratigraphies in the Caucasus are uncommon (Fig. 1.2), and

those that have been flagged as significant for this study are in Table 1. The best

represented Caucasus site is Orvale Klde, where the late MP ends and transitions

abruptly into the early UP, indicating a rapid population replacement. Although the

faunal assemblages between the MP and UP are largely the same there are striking

differences in the usage of specific raw materials for lithic production. For instance,

Neanderthals used very little exotic obsidian in their production of tools (only debitage

and very reduced lithics are present) and AMH assemblages were comprised of 5%

obsidian with full reduction sequences. This pattern may reflect an increase in mobility,

land use and social network size for AMH; these are factors which might have given

them an advantage over Neanderthals (Adler et al., 2006; Adler et al., 2008b; Adler and

Tushabramshvili, 2004). Striking similarities have been observed between the lithic

assemblages at Ortvale Klde and another well-stratified site, Mezmaiskaya, however

questionable chronological data prevent more in-depth comparisons between

archaeological strata at these sites (Golovanova et al., 1999; Pinhasi et al, 2011). Until

12

recently, all of the dates obtained were from unfiltered and often uncalibrated

radiocarbon dates, from units with questionable stratigraphic context. Lusakert presents

an important opportunity for the ongoing correlation of stratigraphic units between sites

across the southern Caucasus, based on both archaeological and chronological evidence.

Many of the existing interpretations are flawed because they seek to create a very neat

and narrow understanding of population movement, interaction, and replacement -

mechanisms which are surely more complex than originally hypothesized.

Table 1 Summaries of the archaeological data from the most stratigraphically reliable sites in

the Caucasus (Bar-Yosef et al., 2011; Golovanova and Dornichev, 2003; Pinhasi et al., 2008;

Adler et al., 2006).

Site Name Location Technology Additional Info Chronology

Orvale Klde Southern Caucasus (Georgia)

Three Upper Palaeolithic layers and six Middle Palaeolithic layers

A key site utilized primarily to facilitate the frequent probably seasonal hunting, processing and consumption of Capra caucasica

MP/UP transition – between 42.8 ka cal BPHulu and 41.6 ka cal BPHulu

Mezmaiskaya Northwestern Caucasus (Republic of Adygea, Russia)

Four Middle Palaeolithic and three Upper Palaeolithic layers

Partial Neanderthal skeletal remains in the lowermost and uppermost Middle Palaeolithic layers

Ultrafiltered collagen gives date of 42,960-44600 cal BP (68.2%) and 42,300-45,600 cal BP (95%) End MP ~37 ka cal BPHulu Start UP ~38–37 ka cal BPHulu

Dzudzuana Southern Caucasus (Georgia)

Two Early Upper Palaeolithic layers

UP begins at ~32 ka 14

C BP UP ends at ~20 ka 14

BP

Bronze Cave Southern Caucasus (Georgia)

Five Middle Palaeolithic layers

Most likely a campsite but occupations were intermittent and sometimes ephemeral

MP is broadly contemporaneous with MP at Ortvale Klde, based on lithic assemblages

Hovk 1 Southern Caucasus (Armenia)

Two phases of Early Middle Palaeolithic

Phases separated by period of abandonment. Overall site use is probably seasonal and short-lived during times of mild climate

MP- MIS5, dated to ~100 ka BP OSL, U-Th ~94 ka BP MP or UP - 39.12 +/- 1.32 ka cal yr BPHulu

13

1.4 Lusakert Rockshelter

Lusakert, a rockshelter site located in the Hrazdan Gorge in Armenia (Fig. 1.2), is the

only well-stratified, well-preserved MP site currently being excavated in Armenia. The

rockshelter is incised into a basalt flow which has been 40

Ar/39

Ar dated to 200 ka

(Wilkinson, 2011). After the volcanic events which deposited the basalts, the Hrazdan

river incised the gorge to its present level, creating the rockshelter. At some point in the

river’s history it abandoned the stretch of gorge in which Lusakert is located and moved

to its present course nearby. The first excavations of this site were undertaken by Soviet

archaeologists between 1971 and 1981, though the deposits were not systematically

studied or published. The Soviet trench was reopened in the early 1990s by an

Armenian-French team, however only the exterior of the rockshelter was excavated

(Chataigner et al., 2003). These deposits have been re-excavated by the current

excavation team and have been designated as alluvial floodplain deposits. The lithics

found within these units are oriented along the bedding plane of the sediments,

indicating probable reworking by continued fluvial activity. Upper layers that probably

post-date the presence of the river by Lusakert are deposited through colluvial processes

and pedogenesis. The interior and exterior of the cave are separated by a boulder layer

that has fallen from the lip of the mouth of the cave, and this disrupts the subsequent

stratigraphy between the two areas (Fig. 1.3). The sedimentological units have been

defined through sediment morphology since there is no distinct archaeological

difference between the units thus far; lithic analysis is ongoing. OSL samples were

acquired from Units 3, 4, and 5 in the interior, and Units D1B and D2 from the exterior.

A summary of the relevant units is described in Table 2. Some chronological

information has been previously obtained for the site, however it is deemed unreliable

for a variety of reasons: the 14

C dates were performed on samples that were not

ultrafiltered and close to the point where the calibration curve becomes unreliable, and

the OSL dating was conducted on the exterior units using single aliquots.

1.5 OSL Dating in Archaeological Deposits

Optically stimulated luminescence (OSL) has been used extensively in archaeological

contexts (Jacobs et al., 2006) to extend the chronological potential for a site past the

range of time that 14

C is reliable and is even being used to test the validity of 14

C dates

in questionable contexts (Morwood et al., 2004). The timescale accessed by OSL dating

14

Figure 1.3. Photo of the interior excavation units at Lusakert, looking northwest. 3b. Plan map of Lusakert, illustrating the back wall of the rockshelter (grey), the trench excavated in the 1970’s (blue), and the numbering system of the profiles (Wilkinson, 2011).

15

Table 1.2. Summary of the interior stratigraphic units at Lusakert based on site reports (Wilkinson, 2009; 2011) and micromorphology reports (Mallol 2009; 2011).

Sedimentology Formation Process Archaeology Previous Dating

Unit 2 Fine grained alluvium mixed with cave wall particles, some carbonaceous input and charcoal. Clay migration from present soil formation, also some burrows. Presence of iron nodules and sediment is broken into horizontal planes.

Iron nodules indicate a humid environment, while the bedding indicates ice formation in the winter.

Levallois (flake and blade) with facetted and plain platforms, few cores, denticulates, sidescrapers, burins, end scrapers; very low frequency of cortex. Obsidian preservation is excellent , edges sharp and undamaged: no post-depositional weathering.

OSL date from the top layers of the exterior of the site (Unit C) date to ~36,000, however AMS

14C

dating on an equid tooth gave an estimate of 31,540-31,040 cal yr BP. Assuming Unit C post-dates Units 2 and 3, they should date between ~31,000 and ~36,000 yr BP.

Unit 3 Fine grained alluvium mixed with cave wall particles, some carbonaceous input and charcoal. Clay migration from present soil formation. Presence of iron nodules and sediment is broken into horizontal planes.

Iron nodules indicate a humid environment, while the bedding indicates ice formation in the winter.

Levallois (flake and blade) with facetted and plain platforms, few cores, denticulates, sidescrapers, burins, end scrapers; very low frequency of cortex. Obsidian preservation is excellent , edges sharp and undamaged: no post-depositional weathering.

Unit 4 Fine grained alluvium mixed with cave wall particles, some carbonaceous input and charcoal. Presence of iron nodules and sediment is broken into horizontal planes.

Iron nodules indicate a humid environment, while the bedding indicates ice formation in the winter.

Levallois (flake and blade) with facetted and plain platforms, few cores, denticulates, sidescrapers, burins, end scrapers; very low frequency of cortex. Obsidian preservation is excellent - edges sharp and undamaged: no post-depositional weathering.

Charcoal dated to 36,260-33,530 cal yr BP

Unit 5 Fine grained alluvium mixed with cave wall particles, some carbonaceous input and charcoal (here distinct, fine horizontal layers). Some bioturbation from roots and burrows.

Levallois (flake and blade) with facetted and plain platforms, few cores, denticulates, sidescrapers, burins, end scrapers; very low frequency of cortex. Obsidian preservation is excellent, edges sharp and undamaged: no post-depositional weathering.

Long bone dated to >45,810 cal yr BP

16

encompasses a crucial period in hominin evolution and dispersal (Armitage et al., 2011)

and provides a valuable chronological tool where 14

C is unusable. Many sites are rich in

archaeological deposits but lack an essential amount of dateable material, whereas OSL

makes use of sediments in which the archaeological remains are found. OSL in

rockshelters has primarily utilized single-grain methods which can increase the

reliability of OSL dates in these complicated depositional environments (Jacobs et al.,

2003; Goldberg and Sherwood, 2006). The existing chronology for Lusakert indicates

that the units in question were likely deposited between 30 and 50 ka; the lack of

datable faunal material suggests that OSL is the most appropriate method for attempting

to extract a more accurate chronostratigraphy for the Middle Palaeolithic at this site.

1.6 Aims and Objectives

Aims:

- To create a preliminary chronology for the Palaeolithic deposits at Lusakert

- To develop a methodology appropriate for the grain characteristics unique to

the sediments at Lusakert

Objectives:

- Assess the potential for single grain quartz OSL dating at Lusakert to

provide a stratigraphically sound chronology

- Identify potential sources of internal inconsistency such as dose rate

heterogeneity, incomplete bleaching and geological instability

- Explore the depositional environment for possible sources of post-

depositional disturbance of the units

- Test the reliability of the previous 14

C and OSL dates obtained from

Lusakert

17

2. PRINCIPLES OF OSL

18

2.1 Basic Principles

In the natural environment, sediments are exposed to alpha (α), beta (β) and gamma (γ)

radiation resulting from the decay of the radioisotopes of 235

U, 238

U, 232

Th and 40

K. In

addition, a small amount of radiation is also received from cosmic rays. This radiation

has sufficient energy to displace electrons from their parent atoms and trap them in an

excited state above the valence band (Duller, 2004). These areas are known as electron

traps; it is here that displaced electrons accumulate over time (Fig. 2.1). Crystalline

minerals such as quartz and feldspar are then able to be used as natural dosimeters as

they preserve the record of irradiation dose that has been accumulated over time.

Working under the assumption that the rate of irradiation is constant, the build-up of

charge can be equated to burial time (Aitken, 1998; Murray and Olley, 2002). Emptying

of electron traps (also known as bleaching) occurs when the minerals are exposed to

sufficient light or heat to provide enough energy to evict those electrons and move them

to recombination centres. It is during this process that a small amount of energy is

expelled as a photon of light.The amount of light emitted is therefore proportional to the

total radiation dose; it can be measured in a laboratory, so the radiation dose can be

estimated be estimated using the following equation:

Equation 2.1

where the age is the time elapsed since significant exposure to sunlight or heat (the

datum point used in this study will be 2012), equivalent dose (De) is the laboratory

estimation of the true quantity of radiation the sample was exposed to in the natural

environment (palaeodose), and the dose rate (Dr) is the rate at which the sample was

exposed to radiation (Murray and Roberts, 1997; Duller 2004).

The first instance of luminescence dating was applied to thermally reset minerals, a

process called thermoluminescence (TL) which is still commonly used to date materials

either deliberately fired (pottery) or inadvertently heated in hearths (lithics, stones)

(Roberts, 1997). Although TL is applicable in many studies it is limited for use on

sediments since it requires more heat than that given off by sunlight to fully bleach the

mineral. It is therefore preferable to use optically stimulated luminescence (OSL) for

19

dating sediments, where grains are bleached very rapidly when exposed to full sunlight

- a more likely experience than sufficient heat exposure (Jacobs and Roberts, 2007).

Figure 2.1 Band gap diagram illustrating the response of electrons to ionizing radiation (after

Aitken, 1989). 1) Radiation stimulates an electron to migrate from the valence band to the

conduction band, creating a positive charge (hole) which then moves to a recombination

centre. The electron becomes trapped in a crystal imperfection between the bands called an

electron trap. 2) Over time, more electrons become ionized and move to electron traps, as

more holes migrate to recombination centres. 3) The sample is exposed to either light or

heat, which stimulates the electrons to escape the electron trap by overcoming their

activation potential. The electrons move back through the conduction band and some may

become trapped in a recombination centre, producing luminescence.

Quartz OSL has been the most widely used and developed technique for Quaternary

contexts in recent years (Roberts, 1997; Jacobs and Roberts, 2007). Quartz has a

number of electron traps within the crystal with varying thermal stabilities; the 325°C

trap is very thermally stable with a lifetime of 108 years (Murray and Wintle, 1999) and

is the location from which most of the OSL signal originates (Wintle and Murray,

1997). For these reasons, quartz OSL has been selected as the mode with which to best

determine accurate and precise ages for the samples in question.

2.2 Single Grain OSL

Single grain luminescence dating was first used by Lamothe et al. (1994) and since then

has been refined and tested, becoming standard procedure for dating archaeological

20

deposits (Jacobs and Roberts, 2007). Single grain analysis was developed as a technique

to improve the accuracy of age determinations (McCoy et al, 2000) and was rendered

much more attainable with the development of a single grain OSL system that made

repeat measurements on large numbers of grains possible within a reasonable time

(Duller et al., 1999; Bøtter-Jensen et al., 2000). The primary benefit to measuring OSL

from individual grains is twofold: the identification of contaminant grains to a main

population, and the ability to exclude them before determining ages for the sample

(Thomsen et al., 2005; Jacobs and Roberts, 2007). This function allows for an

immediate assessment of the stratigraphic integrity of a site, something that is extremely

valuable regarding post-depositional disturbance, mixing, and roof-spall contamination

(Murray and Roberts, 1997; Roberts et al., 1998). Samples that have a very dim signal

or are poorly bleached also benefit from single-grain analysis as small aliquots are

likely to overestimate De (Jain et al., 2004). Single grain analysis is critical to this study

(see Methods) due to the poor yield of total grains from the sample processing; only a

small amount of sample is required compared to standard single-aliquot methods

(Murray and Roberts, 1997). The greatest fault with single-grain analysis is the

relatively large scatter of De values from a single sample. This is also known as

overdispersion, which is the relative standard deviation (RSD) of Des after all

systematic and statistical errors have been accounted for (Galbraith, 1999). The overall

characteristics of the sample and its overdispersion are taken into consideration when

choosing the appropriate statistical models to accurately simulate the most likely ages

corresponding to the scatter in Des. This aspect will be discussed in greater detail in the

following chapter.

21

3. METHODOLOGY

22

3.1 Sampling strategy and Sample Preparation

The samples from the interior of the rockshelter are thought to be significantly more

intact stratigraphically than the exterior (pers. com. Adler & Wilkinson), making their

analysis a priority. Samples from the levels that appear stratigraphically youngest (Units

3, 4 and 5) were chosen in an attempt to reveal the latest dates for the MP at the site

(Fig. 3.1). The four interior samples and one exterior sample were fully processed;

however time constraints and sample paucity prevented the analysis of two samples

from the exterior of the site.

Figure 3.1 Photo of profiles 2 and 4 from which the interior sample tubes were taken, facing southwest.

Originally one sample tube was collected for each of the samples, with subsequent

sampling of an additional proximal tube obtained for all of the samples except OSL 25.

The tubes were sealed and transported back to RHUL where they were analysed in low

light (red and orange) conditions throughout the sample preparation stage. The inner

third of the tube which may have had some exposure to light was weighed and dried for

field moisture content, while the middle third was taken for dating. Samples were wet-

sieved to obtain grain sizes between 150µm and 250µm in order to easily fit in the

single-grain discs and avoid subjection to any dose-dependent effects (Armitage and

23

Bailey, 2005). After sieving, carbonates were dissolved in 10% HCl, then quartz was

extracted through density separation by sodium polytungstate at a specific gravity of

2.62 (to remove potassium feldspar) and 2.75 (to remove heavy minerals). Samples

were then etched for 40 minutes in 48% HF to remove the outer rind of grains which

has been affected by alpha radiation, as well as to remove any remaining feldspar

(Aitken, 1985).

For the dose recovery test single aliquots were mounted on stainless steel discs. For the

single grain measurements grains were brushed onto SG-LL discs which hold 100

grains per disc, with all discs oriented the uniformly towards the beta source. Discs

were placed in odd-numbered positions in the carousel to avoid problems with cross-

irradiation and illumination (Bray et al., 2002). For dose rate calculation, two dried,

ground 1g subsamples of each sample were measured for 24 hours. In addition, two

standard samples with known beta dose rates of 0 Gy (Stainless steel disc) and 7.06

Gy/ka (NIM granite) were measured in each run. All laboratory procedures and analyses

were performed by the author at Royal Holloway, University of London, UK.

3.2 Luminescence Equipment

OSL measurements were conducted using a Risø TL/OSL-DA-15 automated dating

system fitted with a single-grain OSL attachment. Bleaching was performed using blue

(470nm) light emitting diode (LED) array with a power density of 33mW/cm2; single

grains were stimulated with a 10mW Nd: YVO4 solid-state diode-pumped laser

(532nm) focused to yield a nominal power density of 50 W/cm2. Infra-red (IR)

stimulation was carried out using an IR (870nm) laser diode array yielding a power

density of 132mW/cm2. OSL passed through 7.5mm of Hoya U-340 filter and was

detected using an Electron Tubes Ltd 9235QB15 photomultiplier tube. Irradiation was

carried out using a 40mCi 90

Sr/90

Y beta source giving ~7 Gy/min (0.1297 Gy/sec for

single aliquot stainless steel discs and 0.1180 Gy/sec for SG-LL discs) which was

calibrated relative to the National Physical Laboratory, Teddington 60

Co γ-source

(Hotspot 800). Dose rates were obtained through GM-beta counting performed using a

Risø GM-25-5 five sample low-level beta GM multicounter system. Curve fitting, De

determination, Monte Carlo simulation and synthetic aliquot calculation were

performed using version 3.24 of the Luminescence Analyst software (Duller, 2007).

24

3.3 Single-Aliquot Regenerative Dose Protocol

To obtain reasonable information about the depositional age of the quartz grains it is

necessary to convert the natural OSL signal into a reliable estimate of the dose received

in Gy (Jacobs et al., 2008). Due to the analytical restrictions of measuring grains with

an additive dose on multiple aliquots (Murray and Roberts, 1998) a system called the

single-aliquot regenerative (SAR) dose protocol was developed. The SAR dose protocol

performs repeat measurements on the same sample to obtain the De by interpolation

rather than extrapolation (Murray and Roberts, 1997; Murray and Wintle, 2000). The

analytical procedures required to make all the measurements necessary for constructing

a growth curve for a single aliquot were first produced for feldspars (Duller, 1995), but

later were developed and revised in more detail for quartz (Murray and Wintle, 2003).

These procedures have subsequently been tested and proven to provide valid results in a

variety of settings (Murray and Olley, 2002, Jacobs and Roberts, 2007). The underlying

assumption of the SAR protocol is that it is possible to measure a signal after each dose

and stimulation cycle, which acts as a surrogate measurement of the sensitivity

applicable to the previous measurement cycle. This assumption allows for the

sensitivity changes inherent to the method to be corrected for in both natural and

regenerated signals (McCoy et al., 2000; Murray and Wintle, 2003). By making all of

the measurements on a single subsample the analytical precision of acquiring equivalent

doses is greatly increased. This process can be fully automated, making it simple to

generate multiple measurements of the De on the same sample and thus the uncertainties

associated with each De can be calculated more easily and precisely (Duller, 2004). The

application of SAR to individual grains allows a significant number of De values to be

generated for each sample, and by examining the pattern of the resulting distribution

potential complications such as partial bleaching and sediment mixing can be identified

(Jacobs et al., 2008b). Due to the spatial inhomogeneity of beta emitters across the

active face of our beta source it was necessary to calibrate the dose rate to each

individual grain position on a single-grain disc (Ballarini et al., 2006).

The SAR technique involves making a series of paired measurements of OSL intensity,

where the first measurement gives the natural, or regenerated OSL intensity (LN and LX,

respectively), and the second (TX) gives the luminescence intensity as a response to a

constant test dose (Murray and Wintle, 2003). TX is the measurement used to monitor

sensitivity change and since the stimulation is fixed, changes in response can be readily

25

identified and corrected for in the regenerated dose. This is done by dividing the natural

or regenerated luminescence intensity by the test dose intensity (LN/TN or LX/TX). The

precise protocol outlining the selected doses for this project is shown in (Fig. 3.2), with

measurement conditions kept constant for all samples.

Figure 3.2 Flow chart illustrating the sequence of procedures utilized in the SAR protocol for single grain dating, modified for the characteristics of this sample (after Murray and Wintle, 2000).

OSL is performed at 125°C in order to prevent the re-trapping of electrons in the

geologically unstable 110°C trap (Murray and Wintle, 2000), without affecting the

signal through thermal transfer (Ward et al., 2003). In addition, this temperature

prompts rapid signal evacuation to minimize the contribution from the PM tube

background. Due to the significant presence of a non-fast dominated signal, OSL was

conducted at 50% power for 4 seconds (s) in attempt to separate the various components

in greater detail and thereby better understand the internal characteristics of the sample.

Samples were heated at a rate of 5°C/s and held at 125°C for 10s to take into account

the time lag between the heating of the disc and sample. The test dose needs to be as

26

small as possible so as not to affect the sensitivity, but must be large enough to be

detected and be used to correct for the sensitivity changes; hence a 10 Gy dose was

used. A bleach at 280°C for 200s at 90% power was performed at the end of each run

to completely eliminate any signal carry-over from previous doses. Regenerative doses

were used for the construction of the sensitivity-corrected dose response curve upon

which the natural signal was plotted, providing the De. The growth curves were plotted

using a saturating-exponential-plus-linear function due to the good mathematical fit for

the behaviour of single grains.

Errors for individual Des were calculated using the Monte Carlo technique run with

1000 iterations to give the most accurate representation for the goodness of fit. The

performance of the SAR protocol sensitivity correction was assessed via the repeat

point test (recycling ratio), while IR depletion ratios were used to test for contamination

from feldspars (Duller, 2003). A recuperation test in the form of a 0 Gy regeneration

dose was used to determine if thermal transfer had any effect on the samples (caused by

preheats creating false doses) (Murray and Wintle, 2003).

At the single grain level, there is considerable variety in the number and type of OSL

components and their relationships to one another (Adamiec, 2000; Jacobs and Roberts,

2007; Buller et al., 2000), most often referred to as the fast, medium and slow

components. The initial signal is made up of the most readily bleachable components,

usually the fast and medium. To minimize the problems from a multi-component

growth curve analysis was restricted to only the initial signal (McCoy et al, 2000), in

this case the first 65 bins. The background signal was taken from the last 60 and

subsequently subtracted from the luminescence signal produced during the first 1-2

seconds for De calculation (Murray and Wintle, 2000).

3.4 Dose Recovery Test

A dose recovery test was performed as an empirical means of identifying the most

appropriate preheat and cutheat temperatures, bleach parameters, and artificial doses for

the samples in question, as well as to test the reproducibility of De determinations

(Murray and Wintle, 2003). Preheating is used to remove the thermally unstable signals

which would otherwise contribute to age underestimation (Rhodes, 1988; Murray and

Wintle, 2000). This test involves artificially bleaching electron traps then applying a

27

known dose that mimics the natural, if the measured De matches the known recovery

dose the test is passed and the sample is internally consistent and appropriate. The

experimental conditions which produced these results are utilized in the rest of the SAR

protocol. Experimental conditions were modelled after those in Jacobs et al. (2008), due

to contextual similarities. Dose recovery experiments were performed on one sample

from Lusakert, OSL 25, under the assumption that the quartz characteristics would be

consistent between samples. Twenty-four aliquots were mounted on stainless steel discs

using Silkospray silicone oil applied via a 2mm mask. Prior to the dose recovery test, a

few single aliquots of sample were run at average preheats to establish an approximate

natural dose, which in turn informed the selection of data points for the various doses in

the SAR protocol. Des of 77 and 143 Gys were obtained although the 77 Gy dose was

chosen to represent the natural sample in order to avoid issues with potential partial

bleaching (Galbraith et al., 1999). To bracket the natural dose, doses of 26, 52, 78 and

104 Gy were used. Interestingly, the decay curve did not decay quickly (Fig. 3.3),

indicating the possible presence of feldspars or a very strong slow signal.

Figure 3.3 An example of the slow signal decay curve from the dose recovery test on OSL 25.

As a result, various alterations were made to the usual dose recovery test protocol to

account for the slow decay. A range of eight commonly adopted preheating regimes

were employed: preheat 1(PH1) temperatures of 160-280°C at 20 degree intervals, held

for 10s, all with 160°C, 0s preheat 2 (PH2), and also a 260°C PH1 and 220°C PH2, both

held at temperature for 10s. Preheats above 300°C cannot be used due to the effects of

thermal erosion, causing the OSL signal to become unacceptably large (Murray and

Roberts, 1997). An initial bleach of 400s was used to reduce signal carry-over, while a

28

second bleach was set at 200s. After the first bleach the samples were left for 400s to

allow any residual dose from the 110°C trap to decay away; any dose that is left is

removed by the second bleach. To remove any contribution from feldspars all samples

were stimulated under IR light for 100s. Standard OSL was performed using the blue

diodes for 200s to measure the extent of the slow decay, with 5000 data points to keep

the same resolution. Two final bleaches were performed at 280°C for 100s to get rid of

any slow component remaining before every following run; this was done in two stages

to prevent the instruments from overheating. Recuperation and recycling ratios were run

as normal and the IR test was reversed, the last run performed without any IR to

compare to the initial dose of 200s. The results are displayed in Fig. 3.4 and clearly

demonstrate a range of doses returned for various preheats with the highest preheat

combination (260°C for PH1 and 220°C for PH2) returning the only consistent accurate

dose. No feldspars were detected indicating that there was, in fact, a significant non-fast

component dominating the sample.

Figure 3.4 Results from the dose recovery test with PH1 temperatures from 160°C to 280°C,

and PH2 constant at 160°C, barring the last set created to test high PH1 and PH2

temperatures, at 260°C and 220°C, respectively. Three aliquots were tested per preheat sets,

and the given dose was 600s. The majority of the resulting doses clearly deviate dramatically

away from the given dose; the only aliquots consistently providing the correct answer are

highlighted in red. These are the higher PH1 and 2 values, though they have been graphed at

262°C to distinguish them from the other preheat at 260°C.

29

3.5 Rejection Criteria

Many grains lack a measurable OSL signal, and others exhibit luminescence

characteristics that make them undesirable for final age determination; thus a set of

rejection criteria have been formulated modelled on those detailed in Jacobs et al.

(2008). Single grains were rejected when one or more of the following criteria were

met: the OSL signal was weak (TN signal is less than 3 times the instrumental

background), the recuperation was high (if LX/TX for the 0 Gy dose point is greater than

10% of LN/TN) (Murray and Wintle, 2000), the recycling ratio was poor (it is more than

two standard errors away from unity), the sensitivity corrected natural signal was

greater than any of the sensitivity-corrected LX/TX ratios (it does not intersect the dose

response curve), the exposure to infrared stimulation caused significant loss of OSL

signal (IR OSL depletion ratios are smaller than unity by more than two standard

errors), or when the dose response curve shape precluded the generation of a

meaningful equivalent dose. These criteria are all based on mathematical

determinations, except for the shape of the dose response curve and no-intercept criteria

which are dependent on user judgement (Fig. 3.5).

3.6 Statistical Models for Estimating Burial Dose

The equivalent doses obtained from the SAR protocol for single grains frequently

express a certain degree of overdispersion (OD), which is the distribution of data which

is more than can be expected from instrumental errors (Adamiec, 2000). There are a

variety of reasons for the diverse characteristics of grains- some internal (individual

properties of the grains) and some external (inhomogeneous irradiation in the field or

partial bleaching). Instrumental errors can be minimized by improving experiment

design, though thermal transfer can still be a significant source of OD (Jain et al., 2004).

At low signal levels, counting statistics are the dominant control of this uncertainty,

though brighter grains are subject to greater instrument uncertainty (Duller et al., 2000).

Various statistical models have been developed for dealing with OD (Galbraith et al,

1999) and calculating appropriate De used in age determination (Jacobs et al., 2006).

These models identify mixing in the sediment and provide a reliable estimate of the

number of dose components making up the sample (Roberts, 2000). The choice of

model is dependent on the OD value, which is primarily determined using the Central

Age Model (CAM). For samples with OD under 20% the CAM model is deemed

30

Figure 3.5 A. Example of a rejected growth curve with no y-intercept from OSL24 27JUN12B1,

disc 15, grain 77. B. Example of a rejected, saturated growth curve OSL24 27JUN12B1, disc

17, grain 85. C. Example of an accepted growth curve from Curve OSL24 27JUN12B1, disc 23,

grain 3.

31

sufficient, however, if the OD exceeds 20% the samples are considered to be affected

by variations in beta dose rate to individual grains, or by post-depositional mixing of

grains with varying burial ages (Jacobs et al., 2008). In these situations the Finite

Mixture Model (FMM) is considered appropriate. Described by Roberts et al. (2000),

the FMM enables the estimation of the number of dose components within a dose

distribution, the corresponding Des for those components, and the relative proportion of

grains in each component (Rodnight et al., 2006; Jacobs et al., 2006). The model is run

using OD values between 10 and 20% and a set number of components between 2 and

6. The minimum number of components is statistically supported by means of

maximum log likelihood and the Bayesian Information Criterion (BIC) (Jacobs et al.,

2008a). The BIC takes into account the complexity of the model and the goodness of fit,

considering the minimum value to reflect best fit (Rodnight et al, 2008). Since single

grains from archaeological contexts and rockshelters often exhibit a much wider range

of De values than would be expected from instrumental errors alone, it was very likely

that the FMM would be necessary to obtain realistic component Des (Jacobs et al.,

2006; Jacobs and Roberts 2007).

These data are best displayed in a radial plot described by Galbraith (1990) which

allows for variation in precision of data points from single grain data. This graphical

medium was originally developed for fission track dating then later adopted for OSL by

Roberts et al., (1998) and Galbraith et al. (1990). The radial plot displays each De as a

single point with precision plotted on the x-axis and the De values plotted on the Y-axis

as the number of standard deviations away from the central value (Duller, 2004; Jacobs

and Roberts, 2007).

3.7 Environmental Dose Rate Estimation

For samples etched in HF environmental dose rates are comprised of external beta,

gamma and cosmic ray components, as well as an internal beta dose rate (Jacobs et al.,

2008a). The external beta and gamma dose rates are calculated from water content and

beta particle emissions of the sediments. Gamma is commonly measured in the field,

however this was impossible with the study in question, so the gamma contribution was

also counted in the lab. Cosmic dose rates were calculated using the site location (40°N,

44°E, 1.2 km elevation), burial depth, and sediment density (1.8g/cm3). Although it is

an assumption that ionizing radiation is homogenous through a sediment body there are

32

other factors which can alter the absorption coefficients of the sediments (Aitken,

1998). Dose rates were thus corrected for the effects of HF etching (Hong, 1988), grain

size (Mejdahl, 1979) and water content. Water absorbs radiation that would normally be

taken in by the grain, which equates to a ~1% reduction in dose rate for a 1% increase in

water (Duller, 1996; Jacobs et al., 2008). The present day water content is measured as

the mass of water divided by the mass of dry sediment and expressed as a percentage.

Between the original and the duplicate samples, water content was measured on the

subsample from the tube which contributed the most sediment to the final De estimation

process. Estimated water content was calculated on the basis of the measured water

content in order to account for the full range of conditions likely to be encountered

during burial; both the measured and the estimated water contents were used in age

calculation.

The dose rate calculations were performed using the following equations (Aitken,

1985):

Equation 3.1

Equation 2.2

Equation 3.3

The uncertainty attached to the dose rate upon the completion of all calculations

represents the quadratic sum of all known and estimated sources of random and

systematic error (Jacobs et al., 2008).

3.8 Synthetic Aliquots

Previous ages for the site were obtained by single aliquot OSL dating, however due to

the significant problems encountered in archaeological sites using single aliquots

(Jacobs and Roberts, 2007) single grains were chosen in this study. To reinforce this

33

decision, a demonstration of the significant difference in the results obtained by using

single grain and single aliquot methods was required. To complete this, synthetic

aliquots were created from the single grain measurements to determine if similar age

estimates could be obtained from single aliquots. By summing grains into 100 grain

aliquots and 50 grain aliquots a single De was obtained per aliquot after being run

through the same rejection criteria as the single grains. This method operates under the

assumption that all of the sediment was deposited in the same event, and if not, the

brightest grains in the sample dominate the resulting De (Jacobs et al., 2003).

34

4. RESULTS

35

4.1 Sample Characteristics

All seven samples were fully processed; however certain characteristics prevented some

samples from being used for equivalent dose estimation. OSL19 possessed a high

concentration of carbonate material and was therefore largely dissolved when put

through HCl, with no sample surviving after the HF etch. OSL22 and OSL20 both had

very poor sample yield after processing, and only OSL22 was used for equivalent dose

estimation due to its stratigraphic importance. Midway through sample processing

duplicate samples of all but OSL25 were taken in the field; duplicates of OSL22, 23, 24

and 21 were combined with the originals in order to increase the number of grains

available for analysis. OSL23b contained an unidentified powdery residue post-HF etch

but it was re-sieved at 60µm to remove any particles that may distorted the signal. Due

to time constraints only 3 discs of OSL21 were run and none from OSL20 since

obtaining dates for the interior of the cave was deemed a higher priority. Obsidian

flakes were discovered from tubes both inside and outside the rockshelter, however as

they were not fully formed lithics and most likely debitage they were of little

importance archaeologically; they do, however, highlight high artefact density found at

Lusakert.

4.2 De Estimation

A total of 4700 grains were measured, resulting in 258 accepted grains. Sample specific

results are displayed in Table 4.1, rejected grain statistics in Appendix 1.

Table 4.1 Summary of the proportions of grains accepted to total grains analysed.

OSL21 OSL22 OSL23 OSL24 OSL25

Grains Accepted 0 6 69 134 49 Total Grains Analysed 300 300 1800 1100 1200

Grains Accepted (%) 0% 2% 3.8% 12.2% 4.08%

Overdispersion values were obtained using the CAM model of position corrected Des

for each sample. Values were uniformly above 20% except for OSL22, which was

negative, probably due to the extreme paucity of the sample (Table 4.2). These

overdispersion values warranted the use of the FMM to obtain realistic Depopulations,

displayed in Fig. 4.1. Three populations of Des were observed for OSL23, OSL24 and

OSL25, clustering around ~40 ka, ~20 ka and ~8 ka, in all three samples, with the 20 ka

population being the largest. OSL22 consisted of only two main populations, but they

are also ~40 ka and ~20 ka, with the latter population dominating.

36

Figure 4.1 Radial plots displaying De population distributions obtained from the finite mixture model for OSL22, OSL23, OSL24 and OSL25. Scales plot the relative standard estimate estimation (%) of each De value and the standard error. Circles represent individual grain De estimations, and the central grey line indicates the De population with the highest proportion.

Table 4.2 Overdispersion values for the interior samples, determined by the Central Age

Model.

De (Gy) ± (Gy) Overdispersion ±

OSL22 80.68 13.93 -0.33 0.14 OSL23 58.47 4.25 0.53 0.06 OSL24 53.76 2.6 0.49 0.04 OSL25 63.63 5.92 0.53 0.07

37

4.3 Dosimetry and Age estimation

Water content and dose rate calculation results are displayed fully in Appendices 2 and

3 with the total Dr and age calculations based on the FMM De components displayed in

Tables 4.3 and 4.4. Highlighted age estimates indicate those that have been chosen for

final age determination, to be discussed below.

Table 4.3 Summary table of dosimetry and dating results based on measured water content.

Total uncertainties are associated with the propagation of individual errors from all

measured values.

Measured Water Content

Sample Popln Proportion Dose Error ± Total Dr Error ± Age Error ±

OSL22 1 0.58 61.39 5.84 2.68 0.12 22.94 2.50

OSL22 2 0.42 122.23 18.4 2.68 0.12 45.67 7.29

OSL23 1 0.3 29.36 2.35 2.50 0.18 11.73 1.31

OSL23 2 0.42 60.97 4.37 2.50 0.18 24.36 2.57

OSL23 3 0.29 112.57 6.73 2.50 0.18 44.97 4.40

OSL24 1 0.15 25.14 2.87 2.55 0.12 9.86 1.25

OSL24 2 0.64 50.81 2.91 2.55 0.12 19.94 1.58

OSL24 3 0.21 110.6 9.29 2.55 0.12 43.40 4.35

OSL25 1 0.1 19.26 2.88 2.91 0.14 6.63 1.06

OSL25 2 0.58 56.17 3.58 2.91 0.14 19.33 1.64

OSL25 3 0.32 116.13 9.67 2.91 0.14 39.97 4.02

Table 4.4 Summary table of dosimetry and dating results based on estimated water content. Total uncertainties are associated with the propagation of individual errors from all measured values.

Estimated Water Content

Sample Popln Proportion Dose Error Total Dr Error Age Error

OSL22 1 0.58 61.39 5.84 2.80 0.13 21.95 2.40

OSL22 2 0.42 122.23 18.4 2.80 0.13 43.71 6.99

OSL23 1 0.3 29.36 2.35 2.48 0.18 11.85 1.32

OSL23 2 0.42 60.97 4.37 2.48 0.18 24.60 2.59

OSL23 3 0.29 112.57 6.73 2.48 0.18 45.42 4.43

OSL24 1 0.15 25.14 2.87 2.69 0.13 9.36 1.19

OSL24 2 0.64 50.81 2.91 2.69 0.13 18.92 1.51

OSL24 3 0.21 110.6 9.29 2.69 0.13 41.18 4.15

OSL25 1 0.1 19.26 2.88 3.00 0.15 6.43 1.03

OSL25 2 0.58 56.17 3.58 3.00 0.15 18.75 1.60

OSL25 3 0.32 116.13 9.67 3.00 0.15 38.76 3.91

38

4.4 Synthetic Aliquots

Ages obtained from the accepted synthetic aliquots are displayed in Table 7, using both

the measured and estimated water contents. Time constraints precluded the

measurement of beta dosimetry for OSL21, however it should be noted that although no

single grains were accepted in the analysis, a single aliquot passed the rejection criteria.

Table 4.5 Summary table for the dating results from synthetic aliquots, using both the measured and estimated water contents.

Measured Water Content Values Estimated Water Content Values

Sample Aliquot Size

De (Gy)

± Total Dr

Error ±

Age Error ±

Total Dr

Error ±

Age Error ±

OSL23 50 Grain 62.78 9.22 2.50 0.18 25.13 4.17 2.48 0.18 25.39 4.21

OSL23 100 Grain 67.99 9.78 2.50 0.18 27.49 4.49 2.48 0.18 27.22 4.44

OSL24 50 Grain 68.34 7.78 2.55 0.12 26.83 3.39 2.69 0.13 25.44 3.23

OSL24 100 Grain 1027 91.8 2.55 0.12 403.2 42.2 2.69 0.13 382.3 40.3

OSL25 50 Grain 79.96 18.37 2.91 0.14 27.42 6.49 3.00 0.15 26.69 6.32

39

5. DISCUSSION

40

5.1 Synthetic Aliquots

When the results of the synthetic aliquot analysis (Appendix 4) are compared to the

FMM ages it is clear that the individual grain populations highlighted through the single

grain analysis produce a combined De in the majority of single aliquots (result for

OSL24 100 grain aliquot is assumed to be an extreme outlier, and will not be considered

in further discussion). This result falsely promotes the idea of a single De for the units in

question, making it appear as though the sediments were deposited ~25 ka when in fact

it is clear that there are distinct populations within all of the units. This approach

unequivocally confirms the choice of single grain analysis in this study and casts doubts

on the OSL dates obtained through single aliquot analysis previously at Lusakert

(Wilkinson, 2009).

5.2 Component Analysis

5.2.1 Sample characteristics

Results of the dose recovery test revealed a significant non-fast component for OSL25,

a characteristic that continued to be observed in all of the samples. Although it is ideal

to have grains dominated by the fast component due to high light sensitivity (Choi et al.,

2006), it is not necessarily possible in these circumstances; the medium component may

be substituted as it is also seen to be geologically stable over the timescales of interest

(Singarayer and Bailey, 2003). The sensitivity of these OSL components is not

identical, and can lead to poor sensitivity corrections and inaccurate De estimations (Jain

et al., 2003); this makes untangling the relative contributions of these components

crucial in obtaining a confident estimate of De. The first step is to confirm the presence

of the fast component, or the lack thereof in this particular example.

5.2.2 Fast Ratio

The most efficient method for determining which grains are dominated by the fast

component is through the use of the fast ratio, a technique developed by Durcan and

Duller (2011) for single aliquot work and subsequently established for single grains by

Duller (2012). The fast ratio provides a means of quantitatively comparing the OSL

decay curve shapes and determining what proportion of grains are dominated by the fast

component. The ratio is calculated as the initial OSL signal minus a background,

divided by the medium component minus a background. The intervals used to represent

41

each of the components are defined by the proportion of fast and medium components

to the background signal. The interval for the fast is calculated as the point where the

fast component reached half of one percent of the initial signal and the medium interval

was calculated as half of one percent of the medium component. Higher values of the

ratio indicate a greater dependence on the fast component and Durcan and Duller (2011)

suggest using a value of 20 or higher to denote fast component dominance for full

confidence in De estimates. The intervals used in the study by Duller (2012) were

replicated for this research, with the intervals adjusted to be proportional for the amount

of time and power that the samples were subjected to. The interval used by Duller for

the fast component was only one channel; however, to provide the best chance for

obtaining a significant proportion of the fast component the fast ratio in this study was

calculated in two ways, with the fast component represented by both one component

and five. The fast ratio was calculated for every accepted grain (Appendix 5) and out of

258 grains only two passed the fast ratio using one channel for the fast component; three

passed by using five channels. These results clearly indicate that the fast component is

nearly non-existent in these samples and therefore the methodologies adapted for

obtaining accurate Des for this sample may need to be adjusted. The decay of OSL

signal is still concentrated at the start of stimulation, likely representing the medium

component. Although the medium component has also been shown to be geologically

stable, the various signals need to be detangled and tested to confirm the soundness of

using this signal for De determination.

5.2.3 Linearly-modulated OSL

A way of determining the relative contribution of medium component in the decay

curve and isolating it for use in the signal channel choice for the analysis of grains is the

linearly-modulated OSL method (LM-OSL). Proposed by Bulur in 1996, LM-OSL

operates by linearly ramping up the intensity of the stimulation source during the

measurement of the luminescence, as opposed to the standard method of using a

continuous intensity (continuous-wave OSL). This produces a peak shaped OSL instead

of a monotonically decaying curve (Fig 5.1) and allows the number of components and

their kinetic properties to be recorded in much greater clarity (Bulur et al., 2002;

Singarayer and Bailey, 2003). Using this technique, De values can be obtained

separately for the fast and medium components then compared for consistency to

determine if samples had been bleached long enough. In addition, it is possible to

42

isolate the location of the medium component for use in De determination, a technique

which could be utilized for improved age determination at Lusakert (Jacobs and

Roberts, 2007). This method has been tested on archaeological sediments of the Kenyan

Rift Valley, where the deposits are also lacking in a significant amount of fast

component (Choi et al., 2006). The experiments performed there revealed the thermal

stability of the various components through pulse-annealing experiments and produced

results that indicated that the medium component can easily be identified and separated

from the slow component by curve fitting - a crucial step since the slow component has

been shown to be geologically unstable. LM-OSL is a very time consuming technique,

thus time constraints prevented the undertaking of this procedure. LM-OSL is the

logical next step to confirm the location of the medium component in the Lusakert

samples, so if required they may be used appropriately for De determination.

Figure 5.1 Graph showing the individual OSL contributions from each of the quartz

components: fast, medium, and slow 1, 2 and 3 (Singarayer and Bailey, 2003).

5.3 Final Age Determination

The final ages for all samples were calculated using both the measured water content

(Appendix 2) in the sediment and an estimated water content of 15 ± 5%. This value is

assumed to be representative of the full range of water contents experienced throughout

the period of burial at Lusakert from nearly arid to virtually submerged by water

(Duller, 1996). Although the estimated water content is based on the values obtained

from measurements all of the measured contents are within error of 15%, a value which

43

takes into consideration the seasonal variation, precipitation events and possible

flooding during the period when the river still occupied this reach. It is for this reason

that the ages obtained through the use of the estimated water content have been chosen

as the final ages. It should be noted that all differences between the dates obtained from

the varying water contents are within errors of each other, making it almost arbitrary

which data are chosen.

Once run through the FMM, the ages display an interesting mix of populations.

Although there is a ~40 ka population present in all four of the interior samples, it is not

the dominant group in any of them. The dominant component is dated at ~20 ka, and

even then it does not represent an overwhelming proportion of the whole sample, only

40-60%. The smallest component at ~8 ka represents only 10-30% of each sample and

will be addressed below. Had this been a blind study with no archaeological or

sedimentological context, the ages bracketing 20 ka would likely be accepted as true.

However; 20 ka is far too recent for the lithic assemblages found in these irrevocably

middle Palaeolithic layers, making the ages around 40 ka a much more logical fit. This

poses a very serious problem for the interpretation of ages for this site; consequently,

the following discussion will examine all possible reasons for this behaviour of Des.

5.3.1 Luminescence Properties

The displayed De values may be explained by the inherent properties of either the grains

themselves or the doses they received. Assuming that the De values obtained are true,

the primary reason for this disparity of values is variability in the doses received by the

grains. Beta dose heterogeneity is a known issue affecting dose rate determination in

archaeological samples (Jacobs et al., 2008b), where the spatial variation in the

distribution of radioisotopes or the matrix density can result in variations of dose

magnitude and distribution (Nathan et al., 2003). These differences can arise from small

scale variation in water content, the proximity of minerals with a different radioactivity

compared to the rest of the sediment body, the blocking of radioactivity by objects large

enough to prevent dose from reaching certain grains, or by local porosity variations

(Galbraith et al., 1999; Murray and Roberts, 1997). However, clasts large and common

enough were not seen in the tubes of sediment received from the site or described in site

sediment logs, making it highly unlikely that this is the cause of any heterogeneity.

Percolation of various minerals such as clays and carbonates could have a significant

44

effect on the dose received by grains if coated, preventing all grains from receiving the

same dose (Jacobs et al., 2008a). This is also unlikely given the absence of such

features throughout the units in questions as evident in the micromorphology report,

which only features some iron staining of units. Finally, excess water can potentially

absorb and deposit excess uranium in sediments, affecting the amount of dose that

grains receive (Readhead, 1987; Olley et al., 1996). This scenario would require a 50%

increase in the uranium content in order to create the differences in dose seen between

the De populations of the sediments, an amount that would have had to be present for a

long enough period of time to significantly affect some grains and not others (Olley et

al., 1996). It would have to then be removed before measurements were made using the

beta counter, since the measured Drs were not abnormally high enough to record this.

When considered critically, the previously discussed reasons do not provide significant

evidence of their action on the sediments at Lusakert.

Under the assumption that the De values obtained from this study are false, partial

bleaching becomes a possible factor for the variation in dose. Deposits are sometimes

stained, preventing a full bleach, or not exposed to sufficient light for enough time to

fully remove the signal; this problem is sometimes seen in fluvial deposits, where the

water attenuates specific wavelengths of light which most easily bleach sediments

(Olley et al., 1999; Rodnight et al., 2006). Given that these sediments may have been

deposited during flood events from the river, it is possible that they were only partially

bleached upon deposition. Partial bleaching, however, is unlikely due to the

characteristic appearance of overdispersion in radial plots (Fig. 5.2), which displays a

very scattered range of values with no distinct populations. Furthermore, the oldest

dates obtained from the Des match the expected ages and are not older, whereas partially

bleached grains appear older due to the addition of previous doses to the dose acquired

during the most recent burial.

The most likely reason for this distribution of Des based on luminescence properties of

the sediment is the possibility that the primary components which the signal is

originating from are geologically unstable, and the signal has decayed over the burial

period; this results in ages significantly younger than expected for the MP. To test this,

samples can be artificially dosed and left for a period of time at a slightly elevated

temperatures to simulate the passage of time, then measured to see if the known dose

was retained. If the equivalent dose is significantly lower than originally stimulated, the

45

geologic stability of the sample would be called into question; the decision on whether

the sample was suitable for OSL dating in the first place could be made. Time

constraints prevented this technique from being undertaken prior to the completion of

this project; however it is of the highest priority to complete this test as it is one of the

more viable options for the disparity in dose populations.

Figure 5.2 Example of the distribution of grains found in partially bleached samples, in this

instance from fluvial deposits (Rodnight et al., 2006).

5.3.2 External Causes

External reasons for the difference in De values are characterized by mixing agents such

as animals, plants, ice formation, and flood plain activities. The presence of the two

dominant populations must first be addressed.

5.3.2.1 River and Floods

Due to the proximity of the rockshelter to the present day river (Fig. 5.3) it has been

determined that sediment was deposited through the settling of sediments from periodic

flooding (Wilkinson, 2009). This could have occurred when the river still inhabited this

meander or during a very large flood event that caused the overspill from the river to re-

occupy this meander (Collinson, 1996). The presence of at least two distinct populations

of grains without an intermediate population might suggest a hiatus in between

depositional events, creating the unique appearance of two De populations. The river

could have deposited sediment and then either relocated to a different portion of the

46

valley when it flooded, or there could have been a climatic reason for the cessation of

flooding altogether. This depositional pattern would have created a period of little to no

sedimentation at Lusakert, followed by deposition at a much later date, either through

the return of climatic conditions necessary for flooding or by the river floodplain being

large enough to spill into the cut-off meander (Collinson, 1996). Either option presents a

very likely method of sedimentation whereby there is a hiatus allowing two distinct age

populations of grains to be deposited without an intermediate sedimentary unit. After

deposition erosion from subsequent flooding events could have led to the reworking of

these earlier floodplain deposits, creating the mixture seen currently and also possibly

contributing the third and youngest De population at around 8 ka (Collinson, 1996).

Figure 5.3 Image illustrating the proximity of the Lusakert rockshelter to the present day river (Google Earth, 2012).

5.3.2.2 Turbation

Micromorphological reports (Mallol, 2009) from the site indicate the presence of

rhizomes throughout the sediment body for all analysed units, suggesting significant

root activity (Fig. 5.4A). This would cause a substantial amount of reworking, a process

by which two De populations could become interspersed with one another. The iron

staining found throughout the profile habitually follows root tracks and pores left by ice,

further supporting the evidence of turbation by these processes. Laminar cryoturbation

structures were also identified (Fig. 5.4B), indicating the presence of ice lenses formed

47

in the winter or in cold stages (Van Vliet-Lanoë, 1998). Frost can influence soil

deformation through differential frost heave, in which horizons of differing water

retention or frost susceptibility develop. This is a very likely process, as the sediments

most susceptible to these processes are fine-grained with water content close to field

capacity, much like those at Lusakert. Frost can also create particle translocation where

fine particles can be moved vertically through the profile, resulting in an accumulation

of clay and silt sized particles close to the surface (Van Vliet-Lanoë, 1998). This

would, incidentally, account for the lack of sand-sized particles from OSL22, which is

found in Unit 3, roughly 35cm below the surface. If a soil is susceptible to freezing it is

often saturated by spring melt, creating desiccation fissures to allow for increased

drainage. These fissures are often filled with windblown or in-washed particles, which

may account for the presence of the ~8 ka grain population. The repeated saturation and

drainage of these sediments provides additional support for the decision to utilize the

estimated water contents to take account of these seasonal and climatic changes. All of

these actions can be repeated annually, creating an immense amount of cryoturbation in

these units.

Figure 5.4 Images from the micromorphology report (Mallol, 2011), indicating bioturbation (A) and cryoturbation (B) of sediments. These features indicate sources of known sediment mixing throughout units 3-5.

Finally, the activities of burrowing animals such as some insects and rodents can

introduce significant amounts of sediment mixing and turnover, as well as destroy

existing sedimentary units and create false ones (Bateman et al., 2003). Any or all of

these turbation factors may have acted on this sediment body from the period of burial

through to the present day on a variety of scales. This is a very likely cause of the

specific distribution of Des seen for each of the units, and in combination with the

48

proposed depositional mechanism of interrupted floodplain action, provides a very

convincing picture for uniqueness of the sediment age distributions at Lusakert.

49

6. CONCLUSIONS

50

Although there was a population of Des that matched the expected dates for the Middle

Palaeolithic of this region (Pinhasi et al., 2011), it is clear that the overall results are not

reliable enough to create a secure chronology for Lusakert. Three populations of

equivalent doses were determined using the Finite Mixture Model, coming out at ~40

ka, ~20 ka and ~6 ka, in all four of the units. OSL22 from Unit 3 only yielded 6 grains;

nevertheless, once run through the FMM it too provided the two dominant populations

at 20 and 40 ka. The predominance of the ~20 ka population in all of the units could

have been caused by a number of factors both from luminescence causes and exterior

influences. The hypothesis that geological instability affects the traps containing most

of the luminescence signal can be easily tested. If proven true, it would indicate the

unsuitability of these samples for accurate OSL dating. External forces suggest an

alternative explanation, by which separate depositional events at the rockshelter are

mixed together, through some mode of turbation or a combination of many over time.

Although single grain analysis was proven to be far more accurate over single aliquot

methods for this site, the current methodology is unable to provide statistically

significant dates with which to securely identify the end of the MP at Lusakert.

LM-OSL and decay characteristics are the next logical steps for determining any

luminescence reasons for these dose distributions, while further investigation into the

sedimentary processes acting at this site would provide some insight into the degree

type of mixing experienced by these upper units. Further sampling throughout the

profile may also help identify the dominant populations below the units analysed in this

study for the identification of the latest possible middle Palaeolithic unit. If there

continues to be two distinct populations, one at 20 ka and one at 40 ka, an extended

chronostratigraphy to track the changes in population proportions may be able to

support a decision to select the 40 ka population as the true age of the lithics found

within it. In addition, the analysis of alternative grain sizes may increase the sample

yield if, in fact, there has been significant movement of various grain sizes throughout

the profile.

Archaeologically, Lusakert remains a critical site for the establishment of

chronologically reliable tool assemblages and the research conducted in this study is a

step in the right direction toward untangling the complicated and, as of yet, incomplete

record presented by the Southern Caucasus. Although on their own these dates cannot

provide an ironclad argument for any of the archaeological issues mentioned in the

51

introduction, these data can at the very least inform the continued research of these

deposits, as well as provide a methodological guideline for the obstacles likely to be

encountered in other, similar archaeological sites. By instigating some of the

experimental protocols utilized throughout the analysis of these samples, OSL analysis

can quickly overcome some of the problems discussed above and even determine the

suitability of certain deposits for OSL dating at the start of testing. Issues such as

geological instability can be identified immediately, and by isolating the contribution

from the various OSL components more accurate results may be possible in the future.

52

Bibliography

Adamiec G. 2000. Variations in luminescence properties of single quartz grains and

their consequences for equivalent dose estimation. Radiation Measurements 32:

427–432.

Adler DS, Bar-Oz G. 2009. Seasonal Patterns of Prey Acquisition and Inter-group

Competition During the Middle and Upper Palaeolithic of the Southern Caucasus.

In, The Evolution of Hominin Diets, Hublin JJ and Richards MP (eds.). Springer

Press, Netherlands: 127–140.

Adler DS, Bar-Yosef O, Belfer-Cohen A, Tushabramishvili N, Boaretto E, Mercier N,

Valladas H, Rink WJ. 2008a. Dating the demise: Neandertal extinction and the

establishment of modern humans in the southern Caucasus. Journal of Human

Evolution 55: 817–833.

Adler DS, Belfer-Cohen A, Bar-Yosef O. 2006. Between a Rock and a Hard Place:

Neanderthal-Modern Human Interactions in the Southern Caucasus. In

Neanderthals and Modern Humans Meet, Conard, NJ (Ed.). Publications in

Prehistory, Kerns: Tübingen; 165–187.

Adler DS, Jöris O. 2008b. Dating the Middle to Upper Palaeolithic Boundary Across

Eurasia. Eurasian Prehistory 5(2): 5–18.

Adler DS, Tushabramishvili N. 2004. Middle Palaeolithic Patterns of Settlement and

Subsistence in the Southern Caucasus. In Middle Palaeolithic Settlement

Dynamics, Conard, NJ (Ed.) Publications in Prehistory, Kerns: Tübingen; 91–132.

Aitken, MJ. 1998. An Introduction to Optical Dating: The Dating of Quaternary

Sediments by the Use of Photo-Stimulated Luminescence. Oxford University

Press: Oxford. 267pp.

Armitage SJ, Bailey RM. 2005. The measured dependence of laboratory beta dose rates

on sample grain size. Radiation Measurements 39:123–127.

Armitage SJ, Jasim SA, Marks AE, Parker AG, Usik VI, Uerpmann H-P. 2011. The

Southern Route “Out of Africa”: Evidence for an Early Expansion of Modern

Humans into Arabia. Science 331: 453–456.

Bailey RM, Arnold LJ. 2006. Statistical modelling of single grain quartz De

distributions and an assessment of procedures for estimating burial dose.

Quaternary Science Reviews 25: 2475–2502.

Ballarini M, Wintle AG, Wallinga J. 2006. Spatial variation of dose rate from beta

sources as measured using single grains. Ancient TL 24: 1-8.

Bar-Yosef O, Bordes J-G. 2010. Who were the makers of the Châtelperronian culture?

Journal of Human Evolution 59: 586–593.

53

Bar-Yosef O, Belfer-Cohen A, Adler DS. 2006. The Implications of the Middle-Upper

Paleolothic chronological Boundary in the Caucasus to Eurasian Prehistory.

Anthropologie 54(1): 49–60.

Bar-Yosef O, Belfer-Cohen A, Mesheviliani T, Jakeli N, Bar-Oz G, Boaretto E,

Goldberg P, Kvavadze E, Matskevich Z. 2011. Dzudzuana: an Upper Palaeolithic

cave site in the Caucasus foothills (Georgia). Antiquity 85: 331–349.

Bateman MD, Frederick CD, Jaiswal MK, Singhvi AK. 2003. Investigations into the

potential effects of pedoturbation on luminescence dating. Quaternary Science

Reviews 22: 1169–1176.

Bøtter-Jensen L, Bulur E, Duller GAT, Murray AS. 2000. Advances in luminescence

instrument systems. Radiation Measurements 32: 523–528.

Bray HE, Bailey RM, Stokes S. 2002. Quantification of cross-irradiation and cross-

illumination using a Risø TL/OSL DA-15 reader. Radiation Measurements 35:

275-280

Bulur E. 1996. An Alternative Technique for Optically Stimulated Luminescence (OSL)

Experiment. Radiation Measurements 26(5): 701-709.

Bulur E, Duller GAT, Solongo S, Bøtter-Jensen L, Murray AS. 2002. LM-OSL from

single grains of quartz: a preliminary study. Radiation Measurements 35: 79-85.

Bulur E, Bøtter-Jensen L, Murray AS. 2000. Optically stimulated luminescence from

quartz measured using the linear modulation technique. Radiation Measurements

32: 407–411.

Chataigner C, Ollivier V, Liagre J, Colonge D, Beauval C, Fourloubey C. 2003. Le

Paléolithique en Arménie : état des connaissances acquises et donneés récentes.

Paléorient 29(1) : 5-18.

Choi JH, Duller GAT, Wintle AG, Cheong C-S. 2006. Luminescence characteristics of

quartz from the Southern Kenyan Rift Valley: Dose estimation using LM-OSL

SAR. Radiation Measurements 41: 847–854.

Collinson JD. 1996. Alluvial Sediments. In Sedimentary Environments: Processes,

Facies and Stratigraphy (third ed.), Reading HG (ed.). Blackwell Science Ltd,

Oxford.

Duller GAT. 1995. Luminescence Dating Using Single Aliquots: Methods and

Applications. Radiation Measurements 24(3): 217-226.

Duller GAT. 1996. The age of the Koputaroa dunes, southwest North Island, New

Zealand. Palaeogeography, Palaeoclimatology, Palaeoecology 121: 105-114.

Duller GAT. 2003. Distinguishing quartz and feldspar in single grain luminescence

measurements. Radiation Measurements 37: 161–165.

54

Duller GAT. 2004. Luminescence dating of quaternary sediments: recent advances.

Journal of Quaternary Science 19: 183–192.

Duller GAT. 2007. Assessing the error on equivalent dose estimates derived from single

aliquot regenerative dose measurements. Ancient TL 25: 15-24.

Duller GAT. 2012. Improving the accuracy and precision of equivalent doses

determined using the optically stimulated luminescence signal from single grains

of quartz. Radiation Measurements 30: 1-8

Duller GAT, Bøtter-Jensen L, Murray AS. 2000. Optical dating of single sand-sized

grains of quartz: sources of variability. Radiation Measurements 32: 453–457.

Duller GAT, Bøtter-Jensen L, Murray A., Truscott A. 1999. Single grain laser

luminescence (SGLL) measurements using a novel automated reader. Nuclear

Instruments and Methods in Physics Research Section B: Beam Interactions with

Materials and Atoms 155: 506–514.

Durcan JA, Duller GAT. 2011. The fast ratio: A rapid measure for testing the

dominance of the fast component in the initial OSL signal from quartz. Radiation

Measurements 46: 1065–1072.

Galbraith RF. 1990. The radial plot: graphical assessment of spread in ages. Nuclear

Tracks and Radiation Measurements.17: 207–214

Galbraith RF, Roberts RG, Laslett GM, Yoshida H, Olley JM. 1999. Optical Dating of

Single and Multiple Grains of Quartz from Jinmium Rock Shelter, Northern

Australia: Part I, Experimental Design and Statistical Models. Archeometry 2:

339–364.

Goldberg P, Sherwood SC. 2006. Deciphering Human Prehistory Through the

Geoarchaeological Study of Cave Sediments. Evolutionary Anthropology 15: 20-

36.

Golovanova LV, Doronichev VB. 2003. The Middle Paleolithic of the Caucasus.

Journal of World Prehistory 17(1): 71-140.

Golovanova LV, Hoffecker, JF, Kharitonov, VM, Romanova GP. 1999. Mezmaiskaya

Cave: A Neanderthal Occupation in the Northern Caucasus. Current

Anthropology 40(1): 77-86.

Hong DG. 1988. Unpublished thesis. University of Edinburgh, United Kingdom.

Jacobs Z, Roberts RG. 2007. Advances in optically stimulated luminescence dating of

individual grains of quartz from archeological deposits. Evolutionary

Anthropology: Issues, News, and Reviews 16: 210–223.

Jacobs Z, Duller GAT, Wintle AG. 2006. Interpretation of single grain distributions and

calculation of. Radiation Measurements 41: 264–277.

55

Jacobs Z, Duller GAT, Wintle AG, Henshilwood CS. 2006. Extending the chronology

of deposits at Blombos Cave, South Africa, back to 140 ka using optical dating of

single and multiple grains of quartz. Journal of human evolution 51: 255–73.

Jacobs Z, Roberts RG, Galbraith RF, Deacon HJ, Grün R, Mackay A, Mitchell P,

Wadley L. 2008a. Ages for the Middle Stone Age of Southern Africa:

Implications for Human Behavior and Dispersal. Science. 322: 733–5.

Jacobs Z, Wintle AG, Roberts RG, Duller GAT. 2008b. Equivalent dose distributions

from single grains of quartz at Sibudu, South Africa: context, causes and

consequences for optical dating of archaeological deposits. Journal of

Archaeological Science 35: 1808–1820.

Jacobs Z, Duller GAT, Wintle A. 2003. Optical dating of dune sand from Blombos

Cave, South Africa: II—single grain data. Journal of Human Evolution 44: 613–

625.

Jain M, Murray AS, Bøtter-Jensen L. 2003. Characterisation of blue-light stimulated

luminescence components in different quartz samples: implications for dose

measurement. Radiation Measurements 37: 441–449.

Jain M, Thomsen KJ, Bøtter-Jensen L, Murray AS. 2004. Thermal transfer and

apparent-dose distributions in poorly bleached mortar samples: results from single

grains and small aliquots of quartz. Radiation Measurements 38: 101–109.

Jöris O, Adler DS. 2007. Setting the record straight: toward a systematic chronological

understanding of the Middle to Upper Paleolithic boundary in Eurasia. Preface.

Journal of Human Evolution 55: 761–3.

Lamothe M, Balescu S, Auclair M. 1994. Natural IRSL Intensities and Apparent

Luminescence Ages of Single Feldspar Grains Extracted From Partially Bleached

Sediments. Radiation Measurements 23(2/3): 555-561.

Liagre J, Gasparyan B, Olllivier O, Nahapetyan S. 2006. Angeghakot 1 (Armenia) and

the Identification of the Mousterian Cultural Facies of “Yerevan Points” Type in

the Sourthern Caucasus. Paléorient 32(1): 5–18.

Mallol C. 2010. Preliminary Observations: Micromorphology of Lusakert Cave, 2009

Samples. Unpublished report.

McCoy D, Prescott J, Nation R. 2000. Some aspects of single-grain luminescence

dating. Radiation Measurements 32: 859–864.

Mejdahl V. 1979. Thermoluminescence dating: Beta-dose attenuation in quartz grains.

Archaeometry 21: 61-72.

Morwood MJ, Soejono RP, Roberts RG, Sutikna T, Turney CSM, Westaway KE, Rink

WJ, Zhao J-X, van den Bergh GD, Awe Due R, Hobbs DR, Moore MW, Bird

MI, Fifield LK. 2004. Archaeology and age of a new hominin from Flores in

eastern Indonesia. Nature 431: 1087-1091.

56

Murray AS, Olley JM. 2002. Precision and Accuracy in the Optically Stimulated

Luminescence Dating of Sedimentary Quartz: A Status Review. Geochronometria

21: 1–16.

Murray AS, Roberts RG. 1997. Determining the burial time of single grains of quartz

using optically stimulated luminescence. Earth and Planetary Science Letters

152: 163–180.

Murray AS, Roberts RG. 1998. Measurement of the equivalent dose in quartz using a

regenerative-dose single-aliquot protocol. Radiation Measurements 29: 503–515.

Murray AS, Wintle AG. 1999. Isothermal decay of optically stimulated luminescence in

quartz. Radiation Measurements 30: 119–125.

Murray AS, Wintle AG. 2000. Luminescence dating of quartz using an improved

single-aliquot regenerative-dose protocol. Radiation Measurements 32: 57–73.

Murray AS, Wintle AG. 2003. The single aliquot regenerative dose protocol: potential

for improvements in reliability. Radiation Measurements 37: 377–381.

Nathan RP, Thomas PJ, Jain M, Murray AS, Rhodes EJ. 2003. Environmental dose rate

heterogeneity of beta radiation and its implications for luminescence dating:

Monte Carlo modelling and experimental validation. Radiation Measurements 37:

305–313.

Olley JM, Murray A, Roberts RG. 1996. The Effects of Disequilibria in the uranium

and Thorium Decay Chains on Burial Dose Rates in Fluvial Sediments.

Quaternary Science Reviews (Quaternary Geochronology) 15: 751–760.

Olley JM, Caitcheon GG, Roberts RG. 1999. The origin of dose distributions in fluvial

sediments, and the prospect of dating single grains from fluvial deposits using

optically stimulated luminescence. Radiation Measurements 30: 207–217.

Pinhasi, R, Higham TFG, Golovanova LV, Doronichev VB. 2011. Revised age of late

Neanderthal occupation and the end of the Middle Paleolithic in the northern

Caucasus. PNAS 108(21): 8611-8616.

Pinhasi R, Gasparian B, Wilkinson K, Bailey R, Bar-Oz G, Bruch A, Chataigner C,

Hoffmann D, Hovsepyan R, Nahapetyan S, Pike AW, Schreve D, Stephens M..

2008. Hovk 1 and the Middle and Upper Paleolithic of Armenia: a preliminary

framework. Journal of Human Evolution 55: 803–816.

Readhead ML. 1987. Thermoluminescence dose rate data and dating equations for the

case of disequilibrium in the decay series. Nuclear Tracks and Radiation

Measurements 13(4): 197-207.

Rhodes EJ. 1988. Methodological Considerations in the Optical Dating of Quartz.

Quaternary Science Review 7: 395-400.

57

Roberts R, Bird M, Olley J, Galbraith R, Lawson E, Laslett G, Yoshida H, Jones R,

Fullagar R, Jacobsen G, Hua Q. 1998. Optical and radiocarbon dating at Jinmium

rock shelter in northern Australia. Nature 393: 358–362.

Roberts RG, Galbraith RF, Yoshida H, Laslett GM, Olley JM. 2000. Distinguishing

dose populations in sediment mixtures: a test of single-grain optical dating

procedures using mixtures of laboratory-dosed quartz. Radiation Measurements

32: 459–465.

Rodnight H. 2008. How many equivalent dose values are needed to obtain a

reproducible distribution? Ancient TL 26(1): 3–10.

Rodnight H, Duller GAT, Wintle AG, Tooth S. 2006. Assessing the reproducibility and

accuracy of optical dating of fluvial deposits. Quaternary Geochronology 1: 109–

120.

Shea JJ. 2011a. Stone Tool Analysis and Human Origins Research: Some Advice from

Uncle Screwtape. Current Anthropology 52(1): 1-35.

Shea JJ. 2011b. Homo sapiens Is as Homo sapiens Was. Current Anthropology 52(1):

1–35.

Singarayer JS, Bailey RM. 2003. Further investigations of the quartz optically

stimulated luminescence components using linear modulation. Radiation

Measurements 37:451–458.

Thomsen KJ, Murray AS, Bøtter-Jensen L. 2005. Sources of variability in OSL dose

measurements using single grains of quartz. Radiation Measurements 39: 47-61.

Van Vliet-Lanoë B. 1998. Frost and soils: implications for paleosols, paleoclimates and

stratigraphy. Catena 34: 157-183

Ward S, Stokes S, Bailey R, Singarayer J, Goudie A, Bray H. 2003. Optical dating of

quartz from young samples and the effects of pre-heat temperature. Radiation

Measurements 37: 401-407.

Wilkinson KN, Nahapetyan S. 2009. Geoarchaeological fieldwork in the Razdan Gorge

2009. Unpublished report.

Wilkinson KN, Henk YR. 2011. The Stratigraphy of Lusakert 1: Results from the 2011

Field Season. Unpublished Report.

Wintle, AG, Murray AS. 1997. The Relationship Between Quartz Thermoluminescence,

Photo-Transferred Thermoluminescence, and Optically Stimulated Luminescence.

Radiation Measurements 27(4): 611-624.

58

Appendices

Appendix 1. Summary of rejected grains

OSL21 OSL22 OSL23 OSL24 OSL25

Total # Grains Measured 300 300 1800 1100 1200

TN Signal <3*BG 251 219 1217 555 778

Poor Recycling Ratio 3 14 85 102 63

Depletion by IR 3 10 76 51 30

0 Gy Dose >10% of LN 19 20 133 90 212

No LN/TN Intersection 22 17 139 91 20

Dose Response Curve 2 14 81 77 48

Sum of Rejected Grains 300 294 1731 966 1151

Appendix 2. Water content measurements

Sample ID Sample Mass Wet (g) Sample Mass Dry (g) Mass of Water (g) % Water

OSL20b 44.06 34.47 9.59 27.82

OSL21b 45.02 39.45 5.57 14.12

OSL22b 56.03 46.74 9.29 19.88

OSL23b 80.72 70.87 9.85 13.90

OSL24 48.82 40.37 8.45 20.93

OSL25 30.42 25.69 4.73 18.41

59

Appendix 3. Values for cosmic dose rate

Sample

ID

Depth

(cm)

Cosmic Dr

(Gy/ka)

Error

±

Water

Content (%)

Error

±

Error

±

OSL22 95 0.279 0.022 19.88 2.52 0.13 1.25 0.06

OSL23 80 0.232 0.005 13.90 2.25 0.11 1.11 0.06

OSL24 60 0.237 0.006 20.93 2.05 0.22 1.02 0.05

OSL25 100 0.253 0.016 18.41 2.31 0.09 1.15 0.06

Appendix 4. Synthetic aliquot data

Sample

ID

File Name Grain # Disc# De De Error

±

Corrected

De

Corrected

Error ±

OSL21 27JUL12B1 100 13 296.45 40.67 301.82 41.41

OSL25 25JUN12B1 51 to 100 1 1154.12 243.59 1203.07 253.92

OSL25 25JUN12B1 51 to 100 3 425.1 36.13 443.13 37.66

OSL25 22JUN12B1 1 to 50 3 659.57 92.57 655.48 92.00

OSL24 27JUN12B1 1 to 50 13 469.85 27.74 466.94 27.57

OSL24 27JUN12B1 1 to 50 15 464.26 35.46 461.38 35.24

OSL24 16JUL12B1 100 5 1008.69 90.23 1026.95 91.86

OSL24 16JUL12B1 1 to 50 9 868.85 72.84 863.46 72.39

OSL24 16JUL12B1 51 to 100 5 684.27 68.6 713.29 71.51

OSL24 16JUL12B1 51 to 100 7 481.04 46.35 501.44 48.32

OSL23 20JUL12B1 100 15 447.48 56.45 455.58 57.47

OSL23 20JUL12B1 100 19 641.38 122.68 652.99 124.90

OSL23 20JUL12B1 100 21 862.62 260.05 878.24 264.76

60

OSL23 20JUL12B1 1 to 50 19 357.98 33.22 355.76 33.01

OSL23 20JUL12B1 51 to 100 15 281.54 75.52 293.48 78.72

OSL23 20JUL12B1 51 to 100 21 645.91 146.27 673.30 152.47

OSL23 16JUL12B1 1 to 50 13 758.85 106 754.14 105.34

OSL23 01AUG12B1 1 to 50 1 661.89 81.88 657.78 81.37

OSL23 01AUG12B1 1 to 50 9 637.65 207.73 633.69 206.44

Appendix 5. Fast ratio results

Sample File Disc # Grain # FAST (1 channel) FAST (5 channels)

OSL25 22JUN12B1 1 2 -1.90 0.49

OSL25 22JUN12B1 1 43 -3.31 3.31

OSL25 22JUN12B1 1 50 -0.84 2.02

OSL25 22JUN12B1 1 70 -2.83 0.77

OSL25 22JUN12B1 1 95 -3.14 3.27

OSL25 22JUN12B1 1 96 -0.62 2.69

OSL25 22JUN12B1 1 100 1 9

OSL25 22JUN12B1 3 4 -1.55 1.29

OSL25 22JUN12B1 3 60 -3.08 1.52

OSL25 22JUN12B1 5 31 4.17 20.42

OSL25 22JUN12B1 5 42 -2.19 1.94

OSL25 22JUN12B1 5 43 -2.60 0.47

OSL25 22JUN12B1 5 65 6.70 26.80

OSL25 22JUN12B1 7 55 -2.54 3.46

OSL25 22JUN12B1 7 59 -2.53 1.24

61

OSL25 22JUN12B1 7 81 -1.43 0.14

OSL25 22JUN12B1 7 95 -1.00 -0.26

OSL25 22JUN12B1 9 9 -1.85 3.36

OSL25 22JUN12B1 9 11 -2.54 0.29

OSL25 22JUN12B1 9 22 -1.4 1

OSL25 22JUN12B1 9 89 -1.63 0.51

OSL25 22JUN12B1 11 12 -0.79 1.14

OSL25 25JUN12B1 1 47 -2.63 0.25

OSL25 25JUN12B1 1 55 -5.17 0.57

OSL25 25JUN12B1 1 81 -3.34 0.24

OSL25 25JUN12B1 1 86 -2.11 -0.23

OSL25 25JUN12B1 1 93 -0.16 4.41

OSL25 25JUN12B1 3 10 -17.67 12.33

OSL25 25JUN12B1 3 29 -2.69 0.49

OSL25 25JUN12B1 3 38 -4.00 12.00

OSL25 25JUN12B1 3 48 -5.00 0.67

OSL25 25JUN12B1 3 66 -1.85 1.62

OSL25 25JUN12B1 3 77 -1.88 1.06

OSL25 25JUN12B1 3 89 -2.11 0.76

OSL25 25JUN12B1 3 92 -3.00 -2.00

OSL25 25JUN12B1 5 94 -3.56 1.01

OSL25 25JUN12B1 7 2 -0.30 4.00

OSL25 25JUN12B1 7 5 -1.60 3.78

OSL25 25JUN12B1 7 17 -3.59 2.31

62

OSL25 25JUN12B1 7 19 -1.30 1.04

OSL25 25JUN12B1 7 20 -4.12 -0.33

OSL25 25JUN12B1 7 29 -1.80 0.90

OSL25 25JUN12B1 7 35 -1.34 1.64

OSL25 25JUN12B1 7 38 -1.92 1.94

OSL25 25JUN12B1 7 42 -1.00 0.25

OSL25 25JUN12B1 7 63 -2.67 1.13

OSL25 25JUN12B1 7 64 0.19 5.14

OSL25 25JUN12B1 7 72 -1.81 -0.69

OSL25 25JUN12B1 11 21 -2.15 3.94

OSL24 27JUN12B1 13 2 -5.37 0.06

OSL24 27JUN12B1 13 3 -2.20 1.30

OSL24 27JUN12B1 13 22 -2.41 1.08

OSL24 27JUN12B1 13 47 -3.30 1.61

OSL24 27JUN12B1 13 51 -5.55 0.93

OSL24 27JUN12B1 13 53 -3.21 0.84

OSL24 27JUN12B1 13 54 -2.11 0.84

OSL24 27JUN12B1 13 58 -0.88 3.63

OSL24 27JUN12B1 13 63 -3.91 0.50

OSL24 27JUN12B1 13 77 -9.36 4.50

OSL24 27JUN12B1 13 84 7.33 -5.67

OSL24 27JUN12B1 13 86 -1.06 0.26

OSL24 27JUN12B1 13 90 -6.58 1.16

OSL24 27JUN12B1 13 96 -2.02 1.05

63

OSL24 27JUN12B1 15 6 -1.24 1.79

OSL24 27JUN12B1 15 10 -1.35 0.73

OSL24 27JUN12B1 15 14 -3.30 2.74

OSL24 27JUN12B1 15 23 -1.11 0.86

OSL24 27JUN12B1 15 25 -2.01 0.39

OSL24 27JUN12B1 15 62 -1.70 1.02

OSL24 27JUN12B1 15 90 -2.03 0.55

OSL24 27JUN12B1 15 92 -2.44 3.56

OSL24 27JUN12B1 15 97 -2.17 0.65

OSL24 27JUN12B1 15 100 -3.89 0.67

OSL24 27JUN12B1 17 1 -3.17 0.91

OSL24 27JUN12B1 17 11 -1.21 0.36

OSL24 27JUN12B1 17 20 -1.91 0.19

OSL24 27JUN12B1 17 28 -1.83 -0.56

OSL24 27JUN12B1 17 50 -1.71 1.14

OSL24 27JUN12B1 17 56 -5.04 2.04

OSL24 27JUN12B1 17 59 -2.55 1.40

OSL24 27JUN12B1 17 63 -7.68 -0.03

OSL24 27JUN12B1 17 66 -33.50 -0.17

OSL24 27JUN12B1 17 73 -1.88 1.19

OSL24 27JUN12B1 17 80 -9.00 -38.00

OSL24 27JUN12B1 17 81 -3.30 4.07

OSL24 27JUN12B1 17 100 -3.02 0.16

OSL24 27JUN12B1 19 13 -2.04 0.48

64

OSL24 27JUN12B1 19 16 -3.55 0.18

OSL24 27JUN12B1 19 20 -4.23 0.84

OSL24 27JUN12B1 19 26 -3.92 1.38

OSL24 27JUN12B1 19 39 -3.36 0.91

OSL24 27JUN12B1 19 73 -0.76 2.15

OSL24 27JUN12B1 19 74 -4.52 0.41

OSL24 27JUN12B1 19 90 0.38 9.75

OSL24 27JUN12B1 19 95 -4.04 3.64

OSL24 27JUN12B1 19 96 -3.62 0.04

OSL24 27JUN12B1 21 9 -7.96 0.20

OSL24 27JUN12B1 21 23 0.00 -3.20

OSL24 27JUN12B1 21 24 -5.64 6.45

OSL24 27JUN12B1 21 36 -5.33 2.33

OSL24 27JUN12B1 21 54 -5.00 14.00

OSL24 27JUN12B1 21 64 -1.42 0.26

OSL24 27JUN12B1 21 94 -3.81 4.11

OSL24 27JUN12B1 23 1 -2.14 0.59

OSL24 27JUN12B1 23 3 -1.53 1.38

OSL24 27JUN12B1 23 7 -3.46 0.81

OSL24 27JUN12B1 23 27 -4.58 0.19

OSL24 27JUN12B1 23 31 -7.20 1.02

OSL24 27JUN12B1 23 32 -3.91 1.59

OSL24 27JUN12B1 23 33 -2.15 0.88

OSL24 27JUN12B1 23 46 -2.34 1.20

65

OSL24 27JUN12B1 23 51 -2.84 1.50

OSL24 27JUN12B1 23 53 48.00 -22.00

OSL24 27JUN12B1 23 55 -8.68 -0.78

OSL24 27JUN12B1 23 62 -2.88 1.78

OSL24 27JUN12B1 23 63 -3.76 1.03

OSL24 27JUN12B1 23 68 -4.34 0.68

OSL24 27JUN12B1 23 70 -3.85 0.26

OSL24 27JUN12B1 23 72 -1.53 1.04

OSL24 27JUN12B1 23 84 -5.95 0.18

OSL24 27JUN12B1 23 88 -1.43 0.98

OSL24 16JUL12B1 1 5 -4.95 0.08

OSL24 16JUL12B1 1 10 -3.76 -0.27

OSL24 16JUL12B1 1 12 -3.46 0.67

OSL24 16JUL12B1 1 15 -3.79 1.10

OSL24 16JUL12B1 1 25 -4.85 -0.17

OSL24 16JUL12B1 1 35 -2.72 0.91

OSL24 16JUL12B1 1 38 -3.67 0.18

OSL24 16JUL12B1 1 57 -1.25 3.00

OSL24 16JUL12B1 1 58 -4.08 1.76

OSL24 16JUL12B1 1 61 -1.30 1.80

OSL24 16JUL12B1 1 62 -0.35 3.00

OSL24 16JUL12B1 1 74 -3.00 1.17

OSL24 16JUL12B1 1 78 -3.18 1.03

OSL24 16JUL12B1 3 1 4.00 -4.33

66

OSL24 16JUL12B1 3 22 -3.20 2.00

OSL24 16JUL12B1 3 23 -2.49 4.18

OSL24 16JUL12B1 3 31 0.90 8.24

OSL24 16JUL12B1 3 41 -1.71 1.71

OSL24 16JUL12B1 3 63 -3.71 0.71

OSL24 16JUL12B1 3 68 -3.67 2.73

OSL24 16JUL12B1 3 71 -2.78 2.21

OSL24 16JUL12B1 3 73 -1.60 0.63

OSL24 16JUL12B1 3 80 -2.92 0.88

OSL24 16JUL12B1 3 83 -4.58 0.36

OSL24 16JUL12B1 3 94 -2.91 1.63

OSL24 16JUL12B1 3 96 -2.97 1.38

OSL24 16JUL12B1 3 98 -1.78 1.34

OSL24 16JUL12B1 5 19 -4.15 2.41

OSL24 16JUL12B1 5 21 -0.93 1.46

OSL24 16JUL12B1 5 22 -1.16 1.32

OSL24 16JUL12B1 5 23 -5.32 4.32

OSL24 16JUL12B1 5 31 -15.25 6.63

OSL24 16JUL12B1 5 38 -6.22 0.07

OSL24 16JUL12B1 5 55 -1.68 1.07

OSL24 16JUL12B1 5 63 -2.88 0.75

OSL24 16JUL12B1 5 65 -4.58 0.17

OSL24 16JUL12B1 5 69 -3.05 0.51

OSL24 16JUL12B1 5 77 -1.22 1.28

67

OSL24 16JUL12B1 5 83 -1.05 0.78

OSL24 16JUL12B1 5 96 -3.46 1.04

OSL24 16JUL12B1 5 98 -3.83 0.33

OSL24 16JUL12B1 7 14 -1.78 1.33

OSL24 16JUL12B1 7 25 -3.04 1.39

OSL24 16JUL12B1 7 34 -3.66 0.24

OSL24 16JUL12B1 7 37 -5.53 0.01

OSL24 16JUL12B1 7 38 -2.56 2.33

OSL24 16JUL12B1 7 39 -2.24 2.99

OSL24 16JUL12B1 7 47 -2.00 0.71

OSL24 16JUL12B1 7 52 -6.39 4.17

OSL24 16JUL12B1 7 73 -4.11 11.00

OSL24 16JUL12B1 7 74 -1.00 -6.00

OSL24 16JUL12B1 7 75 -3.43 0.43

OSL24 16JUL12B1 7 82 -4.38 0.21

OSL24 16JUL12B1 7 84 -2.37 1.11

OSL24 16JUL12B1 9 15 -3.35 0.26

OSL24 16JUL12B1 9 16 -2.41 1.90

OSL24 16JUL12B1 9 27 -2.57 2.17

OSL24 16JUL12B1 9 28 -1.86 2.00

OSL24 16JUL12B1 9 43 -1.06 0.31

OSL24 16JUL12B1 9 52 -2.23 2.95

OSL24 16JUL12B1 9 62 -2.49 0.76

OSL24 16JUL12B1 9 76 9.18 -8.73

68

OSL22 27JUL12B1 7 20 -2.58 0.72

OSL22 27JUL12B1 7 37 -6.89 0.07

OSL22 27JUL12B1 7 90 -3.81 0.11

OSL22 27JUL12B1 9 8 -8.14 4.29

OSL22 27JUL12B1 9 9 -6.02 -0.62

OSL22 27JUL12B1 9 75 -6.51 0.95

OSL23 16JUL12B1 11 3 -1.46 1.76

OSL23 16JUL12B1 11 14 -2.23 1.53

OSL23 16JUL12B1 11 28 -1.00 1.00

OSL23 16JUL12B1 11 40 -5.04 1.49

OSL23 16JUL12B1 11 44 -2.13 1.32

OSL23 16JUL12B1 11 48 -9.62 1.75

OSL23 16JUL12B1 11 64 5.00 143.00

OSL23 16JUL12B1 11 69 -2.72 1.44

OSL23 16JUL12B1 11 71 -2.08 0.92

OSL23 16JUL12B1 11 75 2.33 -2.33

OSL23 16JUL12B1 13 9 -1.54 1.00

OSL23 16JUL12B1 13 12 -5.74 0.50

OSL23 16JUL12B1 13 14 -1.86 6.57

OSL23 16JUL12B1 13 16 -2.54 1.13

OSL23 16JUL12B1 13 26 -5.09 0.42

OSL23 16JUL12B1 13 29 -4.66 0.97

OSL23 16JUL12B1 13 30 3.00 -1.00

OSL23 16JUL12B1 13 33 -3.21 3.36

69

OSL23 16JUL12B1 13 37 -5.88 0.88

OSL23 16JUL12B1 13 40 -2.22 0.72

OSL23 16JUL12B1 13 50 -2.77 0.68

OSL23 16JUL12B1 13 100 -1.00 3.00

OSL23 16JUL12B1 15 12 -3.59 3.19

OSL23 16JUL12B1 15 33 -0.92 0.95

OSL23 16JUL12B1 15 43 -1.69 1.48

OSL23 16JUL12B1 15 50 -3.54 5.15

OSL23 16JUL12B1 15 57 -2.50 2.93

OSL23 16JUL12B1 15 61 -3.10 5.03

OSL23 16JUL12B1 15 63 -9.24 1.22

OSL23 16JUL12B1 15 76 -3.63 0.08

OSL23 16JUL12B1 15 77 -2.21 0.93

OSL23 16JUL12B1 15 100 -5.20 1.72

OSL23 16JUL12B1 17 2 -3.32 2.35

OSL23 16JUL12B1 17 48 -4.50 0.60

OSL23 16JUL12B1 17 99 -6.40 0.10

OSL23 20JUL12B1 13 82 -16.00 5.00

OSL23 20JUL12B1 15 82 -4.43 1.13

OSL23 20JUL12B1 21 43 -0.31 4.63

OSL23 20JUL12B1 21 99 -1.80 1.60

OSL23 20JUL12B1 23 19 -2.48 1.61

OSL23 20JUL12B1 23 23 -2.83 2.08

OSL23 20JUL12B1 23 77 -3.04 0.15

70

OSL23 20JUL12B1 25 73 -3.51 1.41

OSL23 20JUL12B1 25 93 -1.00 0.97

OSL23 20JUL12B1 25 96 -3.57 0.47

OSL23 20JUL12B1 27 12 -4.76 5.12

OSL23 20JUL12B1 27 60 -3.62 1.09

OSL23 01AUG12B1 1 2 -3.58 0.76

OSL23 01AUG12B1 1 13 -0.11 5.00

OSL23 01AUG12B1 1 25 -0.99 3.69

OSL23 01AUG12B1 1 56 -2.75 2.75

OSL23 01AUG12B1 1 62 -3.31 2.17

OSL23 01AUG12B1 1 72 -2.21 0.49

OSL23 01AUG12B1 1 89 -7.88 1.30

OSL23 01AUG12B1 3 6 -2.48 1.89

OSL23 01AUG12B1 3 11 -2.56 -0.11

OSL23 01AUG12B1 3 13 -2.00 1.54

OSL23 01AUG12B1 3 91 -2.48 1.25

OSL23 01AUG12B1 5 2 -1.35 1.90

OSL23 01AUG12B1 5 25 -1.41 0.92

OSL23 01AUG12B1 5 53 -2.28 2.00

OSL23 01AUG12B1 7 30 11.33 -9.17

OSL23 01AUG12B1 7 42 0.05 3.86

OSL23 01AUG12B1 7 61 -4.49 -0.21

OSL23 01AUG12B1 9 18 97.00 -47.00

OSL23 01AUG12B1 9 63 -22.50 16.00

71

OSL23 01AUG12B1 9 79 -4.61 -0.16

OSL23 01AUG12B1 11 6 -3.56 0.27

OSL23 01AUG12B1 11 17 -1.00 2.33