A MATLAB based orientation analysis of Acheulean handaxe accumulations in Olorgesailie and Kariandusi, Kenya Rift

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Journal of Human Evolution xxx (2013) 1e13

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Journal of Human Evolution

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A MATLAB based orientation analysis of Acheulean handaxe accumulationsin Olorgesailie and Kariandusi, Kenya Rift

Marius J. Walter*, Martin H. TrauthUniversity of Potsdam, Institute of Earth and Environmental Science, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany

a r t i c l e i n f o

Article history:Received 17 January 2012Accepted 12 February 2013Available online xxx

Keywords:Excavation planArtifactFlume channelShape detectionRayleigh test

* Corresponding author.E-mail address: [email protected] (M.J. W

0047-2484/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.jhevol.2013.02.011

Please cite this article in press as: Walter, MOlorgesailie and Kariandusi, Kenya Rift, Jour

a b s t r a c t

The Pleistocene archeological record in East Africa has revealed unusual accumulations of Acheuleanhandaxes at prehistoric sites. In particular, there has been intensive debate concerning whether theartifact accumulation at the Middle Pleistocene Olorgesailie (Southern Kenya Rift) and Kariandusi(Central Kenya Rift) sites were a result of fluvial reworking or of in situ deposition by hominids. We useda two-step approach to test the hypothesis of fluvial reworking. Firstly, the behavior of handaxes in watercurrents was investigated in a current flume and the flow threshold required to reorientate the handaxeswas determined. The results of these experiments suggested that, in relatively high energy and non-steady flow conditions, handaxes will reorientate themselves perpendicular to the current direction.Secondly, an automated image analysis routine was developed and applied to archeological plans fromthree Acheulean sites, two at Olorgesailie and one at Kariandusi, in order to determine the orientations ofthe handaxes. A Rayleigh test was then applied to the orientation data to test for a preferred orientation.The results revealed that the handaxes at the Upper Kariandusi Site and the Olorgesailie Main Site MidTrench had a preferential orientation, suggesting reworking by a paleocurrent. The handaxes from theOlorgesailie Main Site H/6A, however, appeared to be randomly oriented and in situ deposition by theproducers therefore remains a possibility.

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Introduction

The explanation for large concentrations of Acheulean handaxesat East African prehistoric sites has long remained a mystery. Ex-amples are the Early Pleistocene (ca. 1.5 Ma [millions of years ago])Gadeb site in eastern Ethiopia wheremore than 200 handaxes havebeen found (Clark and Kurashina, 1979), the Middle Pleistocene (ca.0.9 Ma) Olorgesailie sites in the Southern Kenya Rift includingabout 200 handaxes in a single site (Isaac, 1977; Potts et al., 1999),and the Upper Kariandusi Site in the Central Kenya Rift with about100 handaxes (Gowlett and Crompton, 1994) (Fig. 1). Different hy-potheses have been proposed in published literature to explainthese unusual accumulations of handaxes. One hypothesis is thatthey accumulated on the floor of an area that was occupied byeither a large group of hominids, or smaller groups of hominidsover a longer period of time (Schick, 1992). An alternative hy-pothesis proposed is that, since the handaxes were included withina fluvial sedimentary sequence, theymay have been transported by

alter).

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.J., Trauth, M.H., A MATLABnal of Human Evolution (201

rivers and subsequently deposited at the individual locations ofthese prehistoric sites (Isaac, 1967, 1977; Binford, 1977; Schick,1992; Petraglia and Potts, 1994; Rapp and Hill, 2006). Both hy-potheses are not mutually exclusive if handaxes from a behavioralaccumulation were transported only a very short distance to theexcavated site (Isaac, 1977; Schick, 1992).

A two-step approach was used to falsify the hypothesis offluvial reworking of stone tools, in which the null hypothesis wasdefined as a random orientation of the handaxes suggesting noreorientation by river currents and possible in situ deposition byhominids. The alternative hypothesis would involve a significantpreferred orientation of the artifacts as a result of fluvial transportand redeposition. The first step involved investigating the re-sponses of handaxes to water-currents in a flume channel, in or-der to determine the flow threshold required to move theartifacts. The second stage involved developing an automatedimage analysis routine and applying it to the original archeo-logical plan from the Olorgesailie and Kariandusi sites. This imageanalysis routine detected artifacts on the basis of their shapes,determined their orientations, and tested the handaxe assem-blages for preferred orientations. Combining the results from bothstages allowed us to speculate on the formation of the handaxeaccumulations.

based orientation analysis of Acheulean handaxe accumulations in3), http://dx.doi.org/10.1016/j.jhevol.2013.02.011

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Figure 1. Photo and excavation plan of high concentrations of Acheulean handaxes atOlorgesailie, Southern Kenya rift. Original excavation plan of Olorgesailie Main Site MidTrench taken from Isaac (1977).

M.J. Walter, M.H. Trauth / Journal of Human Evolution xxx (2013) 1e132

Site descriptions

By applying our automated orientation analysis described laterto published excavation plans, we are able to test for any preferredorientation in the stone tools from three Acheulean prehistoric sitesin the Kenya Rift Valley with high concentrations of handaxes.

Two of the three excavation plans examinedwere from the H/6Aand Mid Trench accumulations at the Olorgesailie Main Site in theSouthern Kenya Rift (Isaac, 1977). The stone tools at the H/6A sitewere embedded in silt and sand layers suggesting a fluvial depo-sitional environment, but it is not clear whether or not the stonetools had been reworked by water currents. A total of 78 shapedtools have previously been exposed, including 38 handaxes. Thehandaxes were tilted in various directions. In addition to the han-daxes, smaller objects such as flakes, teeth, and fish bones were alsoexcavated. A preferred orientation was not measured (Isaac, 1977).

The artifacts from the Mid Trench of the Olorgesailie Main Sitewere embedded in silt and sand, which was overlain by consoli-dated sand (Isaac,1977). Of the 112 shaped tools at this site, 45werehandaxes. The artifacts were not tilted but a preferred orientationwas observed using a chi-squared test. We avoided this type of test,however, since it is too sensitive to the choice of bin boundaries. Nosmaller objects (such as flakes) were reported and there was nofaunal record. Rounding of the artifacts was interpreted to beprobably due to weathering and unlikely to be due to abrasion(Isaac, 1977).

The third example examined was the handaxe accumulation atthe Upper Kariandusi Site in the Central Kenya Rift. These handaxesalso appear to have been deposited in reworked materials, mainly

Please cite this article in press as: Walter, M.J., Trauth, M.H., A MATLABOlorgesailie and Kariandusi, Kenya Rift, Journal of Human Evolution (201

of sandy pyroclastic origin and contain abundant rounded pumicelapilli (Gowlett and Crompton, 1994). Whereas the handaxes arebelieved to be of Acheulean age, the artifact-bearing unit is prob-ably much younger (Gowlett and Crompton, 1994; Trauth et al.,2005, 2007). The underlying thick diatomite deposit exposed in alarge quarry has been dated at ca. 0.9 Ma (Gowlett and Crompton,1994; Trauth et al., 2007). Faunal remains such as horse teeth havebeen excavated. About 100 fresh handaxes made of obsidian werefound, together with a few heavily abraded trachyte handaxes. Thetrachyte may have been sourced from a nearby rise, located only80 m from the site, but no petrographic analysis has yet beencompleted (Gowlett and Crompton, 1994). No orientation analysishad previously been carried out at this site.

The embedding of artifacts in alluvial sediments raises questionsconcerning their depositional contexts. A variety of criteria havebeen applied to distinguish between primary (undisturbed) andsecondary (disturbed) contexts, such as the sedimentary environ-ments and the rounding, size, and spatial distribution of the arti-facts (Petraglia and Potts, 1994). However, context recognition maybe more complex for lag deposits, in which some material remainsin the place of original deposition, while other material (i.e., lighterand smaller objects) are eroded (Petraglia and Potts, 1994).

Elongated objects have been shown to have a strong tendency todevelop an orientation perpendicular to the water flow, and theirorientation has therefore been used as one of the main criteria foridentifying the influence of water currents on artifact accumula-tions (Isaac, 1977; Shackley, 1978; Clark and Kurashina, 1979;Schick, 1992; Petraglia and Potts, 1994; Dibble et al., 1997;McPherron, 2005; Rapp and Hill, 2006; Benito-Calvo and de laTorre, 2011). The responses of conglomerate clasts to water cur-rents have been extensively studied, but it has been noted thatarcheological material may behave differently due to the unusualmorphologies and size ranges of artifacts (Allen, 1982; Schick, 1986;Petraglia and Potts, 1994; Bridge and Demicco, 2008; Nichols,2009). Experiments with replicas of handaxes in streams alongthe shores of Lake Magadi showed that water flow causes upstreamtilting, transverse reorientation, and sorting of handaxes and flakes(Isaac, 1967). The concentration of artifacts has also been explainedas a kinematic wave effect grouping moving objects along theirflow path (Leopold et al., 1966; Isaac, 1977). Similar results havebeen obtained from flume channel experiments with artifacts, inwhich elongated objects were reoriented perpendicular to thewater flow and smaller objects (i.e., flakes) were separated fromlarger objects (Boaz and Behrensmeyer, 1976; Schick, 1986;Sheppard and Kleindienst, 1996). Schick (1986) noted that elon-gated artifacts became reoriented to a stable position perpendicularto the current flow and retained this orientation while sliding androlling along a flume channel. However, artifact movement wasimpeded by the introduction of a sand bed and upstream tilting ofartifacts occurred due to sediment scour around an artifact (Schick,1986). We also performed several of our own flume channel ex-periments in order to improve our understanding of the interactionbetween artifacts (especially handaxes) and the sediment bed, aswell as to discover the flow threshold required to reorientatehandaxes on a sediment bed in a flume channel.

Design of flume channel experiments

To study the behavior of handaxes under a steady flow, handaxereplicas were placed into a 5 m long, 0.32 mwide and 0.27 m deepflume channel. The handaxes were placed on a bed of mediumsized, well sorted and rounded sand, which is similar to the sedi-ment exposed in the three sites at Olorgesailie and Kariandusi(Isaac, 1977; Gowlett and Crompton, 1994). We used five replicas ofAcheulean handaxes, differing in size and material but very similar


Figure 2. Formation of (a) scour, and (b) sediment ridge (with upstream tilting of theartifact) in the flume channel, under a steady flow of water.

Figure 3. Handaxes with orientations transverse to the current direction, caused by ahigh-energy non-steady water flow.

M.J. Walter, M.H. Trauth / Journal of Human Evolution xxx (2013) 1e13 3

to the artifacts discovered at the Olorgesailie and Kariandusi sites.The largest stone tool was 14.6 cm long and 8.7 cmwide, while thesmallest handaxewas 12.5 cm long and 6.1 cmwide. The length-to-width ratios of the handaxes ranged between 1.68 and 2.27. Four ofthe handaxes were made from flint and the fifth from limestone;their weights ranged from 0.18 to 0.45 kg.

In the first set of experiments, three handaxes were placed on asmooth, flat sediment bed 6.2 cm thick, perpendicular to the flowdirection, parallel to the flow direction with the pointed end up-stream, or parallel to the flow with the pointed end downstream.The initial horizontal and vertical orientations of the handaxesweremeasured using a distance laser. Water was introduced slowlyin order to prevent the handaxes moving before they were fullycovered, and the flow velocity then increased gradually. Water flowwas measured 1.5 cm above the sediment surface, and the waterdepth was kept constant at 7.7 cm. A steady flow of about 0.4 m/swas maintained for about 60 min, and the experiment thenrepeated with a flow velocity of 0.6 m/s for 120 min. Followingcompletion of the experiments the horizontal orientations and tiltangles of the handaxes were again measured using a distance laser,together with the xyz coordinates of the sedimentary structuresthat formed in the channel.

In the second set of experiments, we studied the behavior of thehandaxe replicas in sudden high discharge events, i.e., in extremerunoff events such as those caused by tropical downpours or thecollapse of natural dams. To simulate such events, we dammed thewater and then released a flood wave with a maximum height of4.5 cm above the flat sediment surface and velocities of about0.8m/s (againmeasured 1.5 cm above the sediment surface). Beforethe dammed water was released, three to five handaxes were ori-ented randomly on the sediment surface, far enough apart fromeach other to avoid any collisions (except for one experiment, inwhich the handaxes were arranged very close to each other). Thepositions and orientations of the handaxes weremeasured with thedistance laser, before and after the water release.

Flume channel experiment results

Our experiments produced mixed results, including both hori-zontal and vertical movements of the artifacts, depending on theflow conditions. Despite relatively high velocities of about 0.6 m/s,the handaxes never moved horizontally under steady flow condi-tions, probably due to the strong friction of the sand bed. They did,however, become titled due to the formation of fluvial obstaclemarks. In the 60-minute experiments with current velocities ofabout 0.4 m/s, scours up to 3.6 cm deep formed in the sediment bedupstream of the handaxes. On the downstream side of the han-daxes, sediment ridges up to 2.3 cm above the level of the sand bedformed during the experiments, which together with the scours,caused the artifacts to tilt upstream (Fig. 2).

The erosion and deposition around a handaxe depends on theinitial orientation of the handaxe, producing variations in thedepths of the scours and the heights of the ridges, and hence in thetilting of the artifacts. Handaxes oriented parallel to the currentdirection were tilted by about 10� if their pointed end was down-stream and by about 5� in the reverse orientation. Transverse ori-entations of the handaxes resulted in tilting by about 15� (alwaysmeasured after experiments with durations of 60 min and flowvelocities of about 0.4 m/s). The highest rates of tilting occurred atthe beginning of the experiment, generally decreasing with time asthe handaxe slumped into the scour hole and therefore had lesssurface area exposed to the flow.

The flood experiments, however, produced horizontal move-ment of the handaxes, suggesting that higher current velocities arenecessary to move the objects, having almost half a kilogram. In 13


experiments, 23 out of 30 handaxes were oriented perpendicular tothe current direction (Fig. 3). Scours again formed on the upstreamside of the transversely reoriented handaxes, but they were not asdeep as those formed in the steady-flow experiments. No artifacttilting was observed. Furthermore, handaxes that were arrangedvery close to each other generally moved over much smaller dis-tances. The greatestmovement was achieved by single artifacts thathad been placed perpendicular to the current direction.

In summary, the flume channel experiments clearly showed thata sudden high velocity flow would be required to move the han-daxes, whereas steady flows with typical stream velocities onlyresulted in upstream tilting of the handaxes and were not beresponsible for any preferred orientation of handaxes.

Description of the automated orientation analysis

The image analysis routine described below can be applied toany excavation plan or photo, provided the objects to be analyzedare distinguishable from the background, have distinctive shapes,and do not overlap with each other, and provided the image reso-lution is sufficiently high for the outer boundary of an object toconsist of more than 150 pixels (Fig. S1). The automated orientationanalysis routine is a MATLAB script independent of the operatingsystem used in the experiment (published in the supplementary



material). The script requires MATLAB 7 and the Image ProcessingToolbox 7 from The MathWorks Inc. The automated orientationanalysis was performed on the original excavation plans publishedfor Kariandusi (Gowlett and Crompton, 1994) and Olorgesailie(Isaac, 1977). The excavation plan stored in the TIFF file test.tif

was first imported into MATLAB, transformed into a binary imageusing im2bw, inverted using the logical NOT operator w, and dis-played using imshow as follows:

clear

I ¼ imread(‘test.tif’);

BW ¼ im2bw(I);

BW ¼ wBW;

imshow(BW)

where BW ¼ wBW inverts the image in order to create white out-lines for the handaxes on a black background, which is a require-ment of the bwboundaries function that traces the outlines of theobjects. According to the MATLAB 7 Getting Started Guide andImage Processing User’s Guide (The MathWorks, 2011), bwboun-daries not only analyzes the outermost shapes (parent objects)but also other shapes (child objects) that are completely enclosedby the parent objects. This helps to distinguish adjacent objectswithin the image (Fig. 4a). The bwboundaries function yieldsthe number of parent objects (N), and the adjacency matrix (A)whose rows and columns correspond to the positions of bound-aries stored in the connectivity matrix (B), and the correspondinglabel matrix (L):

[B,L,N,A] ¼ bwboundaries(BW);

The function regionprops stores the centroid location of eachobject in cprp:

cprp ¼ regionprops(L,‘centroid’);

The coordinates for the centroid and pixels of each object, andthe number of pixels are determined within two for loops. Thenumber of times the commands within the first loop are repeatedcorresponds to the number of objects length(B), where B con-tains the coordinates of the pixels defining the boundaries of theobjects. The variable B contains data for both parent and childobjects. Since the objects in the image are best represented by thechild objects, the parent objects are ignored (Fig. 4b). The adjacencymatrix A contains the data of all child objects and their positions in

a b

Boundary of parent cellAdjacent objects

Figure 4. (a) Before the object detection begins, adjacent objects in the image need to be d(red line). The child cell in the figure accurately represents the shapes of adjacent objects. (ccell’s boundary pixels are calculated. The longest vector represents the long axis (blue vecreferred to the web version of this article.)


B; the second for loop checks A for a child object and stores itspositions from B in r2. The coordinates of the boundary pixels(pxl), the number of pixels (npxl) and the centroid (cnt) for eachobject are also stored, as follows:

for r1 ¼ 1: length(B)

for r2 ¼ find(A(:,r1))’

pxl{r2 � N} ¼ B{r2};

npxl(:,r2 � N) ¼ length(pxl{r2 � N});

cnt(:,r2 � N) ¼ cprp(r2).Centroid;

end

end

Excavation plans often contain very small objects, such as thosein the upper left corner of the excavation plan in Fig. 1. We elimi-nated objects having less than 150 boundary pixels from pxl andcnt as they were unlikely to be stone tools and because the smallnumber of pixels could result in large errors when determiningtheir orientations (Fig. S1):

pxl(:,npxl < 150) ¼ [];

cnt(:,npxl < 150) ¼ [];

All objects in the imagewere then labeledwith numerical valuescorresponding to the positions in which they are stored in pxl:

for r ¼ 1 : length(pxl)

text(cnt(1,r)’þ15,cnt(2,r)’,...

[‘Nr.’,num2str(r)],‘Color’,‘b’)

end

After detecting and labeling those objects larger than 150 pixels,their shapes were then determined. The aim was to describe theshapes of the objects by means of the distance from each boundarypixel to the centroid. We first created a variable vec of all vectorsfrom the centroid of a specific object to each pixel on its boundaryby subtracting the xy coordinates of these pixels from the centroidcoordinates (Fig. 4c). The length lng of the vectors in vecwas thencalculated using the function hypot:


vec{:,r} ¼ ones(length(pxl{r}),1)*...

cnt(:,r)’-[pxl{r}(:,2),pxl{r}(:,1)];

lng{:,r} ¼ hypot(vec{r}(:,1),vec{r}(:,2));

end

c

Longest vector

Vectors from centroid to child cell‘s boundary

Boundary ofchild cell

istinguished. (b) Objects are composed of parent (marked by blue line) and child cells) To record the shape of an object, vectors (red) from the object’s centroid to the childtor). (For interpretation of the references to color in this figure legend, the reader is



The longest vector maj in vecwas then found using the functionmax:


[maxlng locmax(r)] ¼ max(lng{r});

maj(r,:) ¼ vec{r}(locmax(r),:);

end

This vector represented both the long axis of a handaxe and itsorientation, which together with the orientations of all otherhandaxes, were used to test whether or not these artifacts had apreferred orientation.

Beforehand, we used the vector-length distributions in vec todistinguish handaxes from all other objects in the excavation plan.The vector-length distributions for the handaxes exhibit a charac-teristic double peak, with the greatest length in each object cor-responding to the sharp end of the handaxe (0�) and the second(smaller) maximum length corresponding to the opposite end ofthe artifact (180� e referring to the orientation relative to thelongest vector) (Fig. 5a). The shortest vectors are then at 90� and270� and are perpendicular to the long axis defined by these twoends. In contrast, objects that are not handaxes typically showrelatively constant or multi-peaked vector-length distributions.Objects with an elliptic shape also have double-peaked vector-length distributions, but both local maxima have the same values(Fig. 5b). The following lines of MATLAB codewere used to calculatethe angles between each of the vectors (vec) of an object and theobject’s longest vector (maj), and to store the results in ang2:

for r1 ¼ 1 : length(pxl)

for r2 ¼ 1 : length(vec{r1})

ang1(r2) ¼ acos(dot(vec{r1}(r2,:), ...

maj(r1,:))/(norm(vec{r1}(r2,:))* ...

norm(maj(r1,:))))*180/pi;

end

ang2{:,r1} ¼ ang1;

ang1 ¼ [];

end

Unfortunately, the resulting angles for the vectors all rangebetween 0� and 180� due to the ambiguity of the oriented versus

a

c

b

0 50 100

0.4

0.5

0.6

0.7

0.8

0.9

1

Orientatio

Leng

th o

f vec

tors

Figure 5. The lengths of the centroid-to-boundary vectors are plotted against their orientatiodifferences between the distributions, which can be used to detect objects of different sha


directional data sensu stricto, and the definition of the inversecosine acos (Fig. 6). More precisely, vectors were pointing eitherright (clockwise, mathematic negative sense) or left (counter-clockwise, positive sense) from the longest vector, as the initialside of the angle corresponding to 0� and the centroid as the origin.The range of the angles was therefore either 0� to �180� for vectorspointing to the right, or 0� to þ180� for vectors pointing to the left.For further calculations, however, it was necessary to convert allvector angles to between 0� and 360� as the terminal side of theangle. We first determined the indexes lmaxang and lminang forthe largest maxang and smallest vectors minang in the ang arrayusing max(ang2{r}) and min(ang2{r}), representing thelongest vector (0�) and the vector pointing in the opposite direction(180� e referring to the orientation relative to the longest vector).For objects with the longest vector pointing toward directionsaround 0� (�90�) (referring to the orientation relative to the ver-tical axis), all angles between lmaxang and lminang were cor-rected by subtracting 360� (Fig. 6). For all other objects, i.e., thosewith the longest vector pointing towards 180� (�90�), all anglesthat did not fall within the range from lminang to lmaxang werecorrected by subtracting 360�:


[maxang lmaxang] ¼ max(ang2{r});

[minang lminang] ¼ min(ang2{r});

if lminang < lmaxang

ang2{r}(lminang:lmaxang) ¼ 360 �...

ang2{r}(lminang:lmaxang);

else

ang2{r}(1:lmaxang) ¼ 360 �...

ang2{r}(1:lmaxang);

ang2{r}(lminang:length(ang2{r})) ¼ ...

360�ang2{r}(lminang:length(ang2{r}));

end

end

Next, we interpolated the length data to obtain lengths forevenly spaced angles from 1� to 360�. The one degree increment,however, should be adjusted to suit the actual resolution of theimage (e.g., if the resolution of the scanned excavation plan is low,we might use 2:2:360 instead of 1:360). If there is no value

abc

150 200 250 300 350

n of vectors to the longest vector

abc

ns relative to the longest vector to record the shape of each object. There are significantpes.


1: 90°

1: 90°2: 45°

2: 135°

3: 0° 3: 180°

4: 45°

4: 135°

6: 135°

6: 45°5: 90°

5: 90°

8: 135°

8: 45°

7: 180° 7: 0°

1 2 3 4 5 6 7 890° 45° 0° 45° 90° 135° 180° 135°

1 2 3 4 5 6 7 890° 45° 360° 315° 270° 225° 180° 135°

Position 0°: 3 < Position 180°: 7

Longest vector points towards directions around 0°. Thus, values in between position 3 and 7 are corrected.

1: 90°

2: 45°

3: 360°

4: 315°

6: 225°

5: 270°

8: 135°

7: 180°

Position in matrix

Orientationof vector

1: 270°

2: 225°

3: 180°

4: 135°

6: 45°

5: 90°

8: 315°

7: 360°

1 2 3 4 5 6 7 890° 135° 180° 135° 90° 45° 0° 45°

1 2 3 4 5 6 7 8

270° 225° 180° 135° 90° 45° 360° 315°

Position 0°: 7 > Position 180°: 3

Calculation of orientation begins at green vector and proceeds to the next vector clockwise.

Longest vector points towards directions around 180°. Thus, values not in between position 3 and 7

are corrected.

Longest vector

Figure 6. Opposing vectors from the same object share the same orientation and hence can not be distinguished. The vectors on one side of the long axis therefore need to becorrected. If the correction is successful, each vector will be ascribed a unique orientation.


Please cite this article in press as: Walter, M.J., Trauth, M.H., A MATLAB based orientation analysis of Acheulean handaxe accumulations inOlorgesailie and Kariandusi, Kenya Rift, Journal of Human Evolution (2013), http://dx.doi.org/10.1016/j.jhevol.2013.02.011

0 50 100 150 200 250 300 350

0.4

0.5

0.6

0.7

0.8

0.9

1

Orientation of vectors to the longest vector

Leng

th o

f vec

tors

0 50 100 150 200 250 300 350

0.8

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6


Leng

th o

f vec

tors

OriginalReconstruction



0 50 100 150 200 250 300 3500.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2


Leng

th o

f vec

tors

Figure 7. The shapes of three objects were reconstructed as described in the text, on the basis of the reference objects in Figure 8. The reconstruction worked best for the handaxe-shaped object (upper plot). In contrast, the reconstructions of the elliptic (middle plot) and circular objects (lower plot) are very different to the original shape, because they do notshare the same characteristic features as the reference objects. They are therefore not identified as handaxes.


Please cite this article in press as: Walter, M.J., Trauth, M.H., A MATLAB based orientation analysis of Acheulean handaxe accumulations inOlorgesailie and Kariandusi, Kenya Rift, Journal of Human Evolution (2013), http://dx.doi.org/10.1016/j.jhevol.2013.02.011


between 359� and 1�, we need to limit our evenly-spaced series ofangular values to 1:359 or 2:2:358. While using the interpolationfunction interp1, the function unique helps by deleting duplicatevalues and sorting the data array. The resulting array (shp1) con-tains 360 rows, one for each degree of a full circle, and as manycolumns as there are objects displayed on the excavation plan. If theimage resolution is too low, the object boundaries will consist of toofew pixels and the interpolationwill be flawed. As stated previously,object boundaries should consist of at least 150 pixels (Fig. S1). TheMATLAB script for the above interpolation is as follows:


[B I J] ¼ unique(ang2{r});

shp1(:,r) ¼ interp1(real(B),lng{r}(I),1:360);

end

Excavation plans typically include objects of many differentshapes and sizes, many of which are not handaxes but other typesof artifact, or even rock fragments with no sign of having beenworked by hominids. Only those objects that resembled the objectsstudied in the flume channel were considered in the statisticalanalysis. Before using the distribution of an object’s vector lengthsas our criterion for identifying handaxes, we normalized the objectsto a standard size by dividing the length of the vectors in eachobject by the length of its longest vector. The longest vector of allobjects then had a length of one and all other vectors were shorterthan one (Fig. 5). The normalized vector lengths were then stored inshp2:

for r ¼ 1 : size(shp1,2)

shp2(:,r) ¼ shp1(:,r)./max(shp1(:,r));

end

The automated identification of handaxes is carried out bycomparing the shapes of objects with the reference shapes of

Figure 8. Object detection results. The black vector in each shape represents its long axis. Ththe reference shapes. All of the illustrated objects are from an excavation plan of the Olorgeobjects, green outlines indicate objects whose orientations were measured, and red outlinesfrom the mean reference object. The italicized numbers are the outputs of the dis variablevalue the greater the similarity to the mean reference object. (For interpretation of the refarticle.)


visually identified handaxes. If the shape of a particular type ofobject does not vary very much, a single reference shape can beused; otherwise more than one reference is required in order toreflect the range of variations in shape (Fig. 8). No more than fivereference shapes are usually required to cover the range of possibleobject shapes.

As an example, let us assume that five objects have been reliablyidentified as handaxes, such as the objects with reference numbers(refs) of 1, 4, 9, 12 and 13 in Fig. 8. These handaxes have featuresin common such as the double-peaked vector length distributions,as discussed above, but also show differences in shape that areconsidered to be acceptable variations around the mean referenceshape. Themean reference shape (mref) is the average shape of thefive handaxes in shp2:

refs ¼ [1 4 9 12 13];

mref ¼ sum(shp2(:,refs),2)./length(refs);

The mean reference shape (mref) is then subtracted from theshape (shp2) of every object in the excavation plan in a for loop,creating the normshp array of shape differences. The differencesbetween the visually identified handaxes and the mean referenceshape (mref) are stored in normref. All objects in normshp thatare equal to the mean reference shape (mref) within the range ofnormref are considered to be handaxes.

for r ¼ 1 : size(shp2,2)

normshp(:,r) ¼ shp2(:,r) � mref;

end

normref ¼ normshp(:,refs);

Next, we calculated the inner product of the differences(normref), which is the difference between the shapes ofthe reference handaxes and the mean reference shape, and theshape differences of all objects (normshp), to determine the

e orientation of the long axis was only recorded for those objects with similar shapes tosailie Main Site Mid Trench published by Isaac (1977). Blue outlines indicate referenceindicate objects whose orientations were ignored because their shapes are too different, representing the difference in shape from the mean reference object. The lower thiserences to color in this figure legend, the reader is referred to the web version of this



similarity (sim) between these objects and each normalizedreference:

for r ¼ 1 : size(normshp,2)

sim(:,r) ¼ normref’*normshp(:,r);

end

In our example with five reference handaxes, we now have fivesim values for each object, representing the similarity between theobject and the five reference shapes. A high similarity between theobject and any one of the five references suggests that they sharemost of the characteristic features, e.g., a distinct peakedness of thesharp point. Since this particular reference shape closelymatches theshape of the object, it can be used as a model for the object underinvestigation. We can in turn reconstruct the shape of each objectaccording to the properties of the inner product by summing up thenormalized shapes of the five references, each weighted by the cor-responding similarity (sim) (Fig. 7). The actual discrimination ofhandaxes from all other objects is based on a threshold Euclidiandistance between the reconstructed shapes and the original shapesof the object, as the reconstruction process works best for objectswith similar shapes to the reference shapes. This calculation is per-formed using two nested for loops. The first loop multiplies thesimilarity value (sim) of each object by the corresponding referenceshape (normref). In the second loop, the results of this multiplica-tion (pjc1) for each object are added together to create the recon-structed shape (pjc2). In the final step, the Euclidean distance (dis)between the reconstructed and original shapes can be determined.

for r1 ¼ 1 : size(normshp,2)

for r2 ¼ 1 : size(normref,2)

pjc1(:,r2) ¼ sim(r2,r1)*normref(:,r2);

end

pjc2(:,r1) ¼ sum(pjc1,2);

dis(:,r1)¼(norm(pjc2(:,r1)�normshp(:,r1)))

ˇ

2;

end

An object with a Euclidian distance (dis) below a certainthreshold value is regarded as a handaxe (Fig. 8). Besides handaxes,this shape detection can be applied on a variety of objects (Fig. 9;Fig. S2). If only a single reference was chosen, the threshold valueneeds to be set by the user ([II,JJ] ¼ find(dis <¼ ?)). Ifmore than one reference was chosen, the threshold value can bechosen by the user or can be determined automatically by theimage analysis routine: in addition to calculating the distance be-tween the reconstructed and original object shapes, we can alsocalculate the same differences between the reconstructed andoriginal reference shapes (dis(refs)). The maximum difference(max(dis(refs))) between these reference shapes is an appro-priate threshold value for our automated handaxe detection. Thelocations of handaxes with differences (dis) below max(dis(-

refs) are stored in JJ:

[II,JJ] ¼ find(dis <¼ max(dis(refs)));

We then calculated the orientation of those objects in JJ reli-ably identified as handaxes. The flume channel experiments clearlyindicated that handaxes move into a preferred orientationperpendicular to the current direction. We therefore determinedthe angle between the long axis (maj) of each handaxe and duenorth (nth). The north vector (nth) for each object was calculatedby subtracting the xy coordinates of the object’s centroid from thecoordinates of a second point defined by the same x coordinate asthe centroid, but having a y coordinate of one. The angle betweenmaj and nth was calculated in a similar way to the calculation ofang2 above. This calculation yielded ambiguous results, depending


onwhether the angles were counted in clockwise or anti-clockwisedirections. Using a if loop, we identified those vectors pointing tothe right of the centroid and corrected their angles by subtracting180�:

for r ¼ 1 : length(JJ)

nth ¼ [cnt(1,JJ(r))’;1] � cnt(:,JJ(r));

ort(r) ¼ acos(dot(nth,maj(JJ(r),:))/...

(norm(nth)*norm(maj(JJ(r),:))))*180/pi;

if cnt(1,JJ(r)) < pxl{JJ(r)}(locmax(JJ(r)),2)

ort(r) ¼ abs(180 � ort(r));

end

end

Finally, the orientation of each handaxe relative to north wasdisplayed on the excavation plan (Fig. 8).

for r ¼ 1 : length(JJ)

text(cnt(1,JJ(r))þ15,cnt(2,JJ(r))þ.15,[num2str(ort(r)),‘�’],‘Color’,‘r’)

end

In an ideal situation, the algorithm would detect all handaxe-shaped objects and record the orientations of their long axes.Orientation data need to be modified before calculating measuresof central tendency and dispersion because an oriented object hastwo opposing directions. An appropriate way to overcome thisstatistical problem of oriented data is to double all values, thusmaking them independent of the directional sense (Davis, 2002). Asan example, let us assume an object that is oriented southeast-northwest (i.e., its orientation can be given by either one of twodirections, 135� or 315�). By doubling the data, angles of 270� and630� are obtained, which need to be corrected for a full circle bysubtracting 360�, resulting in the similar value of 270�. Hence, todetermine the statistics we used the doubled data, but we halvedthese data to calculate the mean direction.

ortrad1 ¼ (pi*ort/180);

ortrad2 ¼ 2*ortrad1;

The modified data was then tested for a uniform distributionbetween 0 and 2p using a Rayleigh test. This test compares themean resultant length (Rm) of the orientation data to a critical valuewith a significance level of 0.05 (Mardia and Jupp, 2000; Davis,2002; Trauth, 2010).

x_1 ¼ sum(sin(ortrad2));

y_1 ¼ sum(cos(ortrad2));

Rm ¼ 1/length(ortrad2).*(x_1.

ˇ

2 þ y_1.

ˇ

2).

ˇ

0.5

If the mean resultant length exceeds the critical value, the nullhypothesis of uniform distribution can be rejected, thereby indi-cating the existence of a preferred orientation. If this is the case, aU-test needs to be performed to test the data for a von-Mises dis-tribution, which is actually testing for a unimodal distribution(Fisher, 1996; Jones, 2006). Using both tests together is a powerfultool for detecting preferred orientations. For bimodal or multi-modal distributions (due, for example, to shoreline or aeolianprocesses) a different statistical test is required, e.g., Rao’s spacingtest (Batschelet, 1981; Allen, 1982; Nichols, 2009).

Results of the orientation analyzes on the excavation plans

The two Olorgesailie sites investigated did not have a sufficientnumber of handaxes exposed to provide a statistically valid


Figure 9. Photos of stone tools were distinguished from the background and recognized by applying the introduced image analysis routine. Objects that were successfullyrecognized are marked in green, while those marked in red were not recognized because their shapes were too different from the reference object, which is marked in blue. Thenumbers within or beneath the objects are the outputs of the dis variable, representing the difference in shape from the reference object. A low number means a high level ofsimilarity to the reference object. Photos reproduced with permission from http://lithiccastinglab.com (a þ d), http://millenniareproductions.com (b), and http://wikimedia.org(c). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)


sample size. We therefore increased the number of orientationmeasurements by including measurements for other elongatedobjects that behave in a similar way to handaxes under flowingwater (Boaz and Behrensmeyer, 1976; Allen, 1982; Nichols, 2009),to increase the sample size for the final orientation analysis. Theresults of the orientation analyzes were the same whethermeasuring only handaxe-shaped objects or handaxe-shaped plusother elongated objects (Fig. S3). Hence by analyzing the orien-tation of 45 handaxe-shaped or 75 handaxe-shaped and elon-gated objects from the Olorgesailie Main Site Mid Trench with aRayleigh test, we were able to reject the null hypothesis of arandom orientation of the handaxes (Fig. 10). The U-Test per-formed on the directional data suggested that the data followed avon-Mises distribution. Both tests together indicated that therewas a preferred southwest to northeast orientation to the stonetools, with a random dispersion around this direction (Fig. 10).


Although the sample size of 30 handaxe-shaped or 61 handaxe-shaped and elongated objects at the Olorgesailie Main Site H/6Awas relatively small, both tests also provided us with very clearresults from this location. Since the Rayleigh test showed a sig-nificant difference between the mean resultant length and thecritical value, we were unable to reject the null hypothesis andconcluded that the handaxes were in fact randomly distributed(Fig. 10).

The automated orientation analysis measured the orientation of95 objects in the excavation plan from Kariandusi. Based on theresults of a Rayleigh and U-Test, the null hypothesis of a uniformdistribution for the handaxes can be rejected (Fig. 10). Hence, thereseems to be a significant preferred orientation to the stone tools atthis site. Unfortunately there are no cardinal directions indicated onthe excavation plan and wewere therefore unable to determine theexact direction of this preferred orientation.


http://lithiccastinglab.com

http://millenniareproductions.com

http://wikimedia.org

15 20

30°

210°

60°

240°

90°270°

120°

300°

150°

330°

180°

0°

61

0.1128

0.2212

Cannot reject uniformity hypothesis

95

0.5291

0.1773

Reject uniformity hypothesis

Measurements: 75

Mean resultant length: 0.2291

Critical value: 0.1995

Conclusion: Reject uniformity hypothesis

Olorgesailie Main Site H/6A Upper Kariandusi SiteOlorgesailie Main Site Mid Trench

10 20 30 40

30°

210°

60°

240°

90°270°

120°

300°

150°

330°

180°

0°

10 20 30

30°

210°

60°

240°

90°270°

120°

300°

150°

330°

0°

Preferred O

rientation

Figure 10. Rose diagrams showing the orientation statistics for handaxes from three prehistoric sites: The Olorgesailie Main Site Mid Trench, the Olorgesailie Main Site H/6A, andthe Upper Kariandusi Site. The results of a Rayleigh test suggests that the stone tools at the Olorgesailie Main Site Mid Trench and the Upper Kariandusi Site are preferentiallyoriented, whereas the artifacts at the Olorgesailie Main Site H/6A are not.


Discussion and conclusions

The results of flume channel experiments with handaxe rep-licas, together with statistical analyzes of stone tool orientations inexcavation plans, have contributed to an improved understandingof the Acheulean handaxe concentrations at three prehistoric sitesin Kenya.

In the first step of our investigations, we performed flumechannel experiments with handaxe replicas of similar sizes,weights, and surface characteristics to genuine handaxes. Wherethese experiments failed to produce any preferred orientation inthe stone tools, no automated orientation analysis was requiredand no conclusions could be drawn regarding possible fluvial or insitu deposition. In the first experiments, current velocities below0.6 m/s were unable to transport the handaxes when placed on asediment surface. However, scours formed due to erosion of sedi-ment upstream of the stone tools, with the eroded sedimentforming centimeter-scale sediment ridges downstream of thehandaxes. These fluvial obstacle marks caused handaxes to be tiltedrather than beingmoved horizontally, as also observed by Euler andHerget (2012) in similar experiments. Increasing the current ve-locity simply increased the degree of tilting of the handaxes andtheir burial in sediment.

Whereas a steady current with velocities typical of rivers inrelatively flat basins such as the paleo-Olorgesailie and Kariandusibasins (where most of the modern relief is much younger than 0.9Ma, e.g., Trauth et al., 2003, 2007) was clearly unable to movehandaxes weighing up to almost half a kilogram in a horizontaldirection, high-energy non-steady flowsmoved the same handaxeshorizontally by more than a meter within a few seconds, alsocausing significant rotation of the stone tools. The preferredorientation of the long axis of the handaxes following completionof the experiment was perpendicular to the current vector. Clearlyonly high discharge events in rivers could have produced sufficientshear stress to overcome the friction between handaxes and theunderlying sediment and move the stone tools from abandoned


hominid living areas. The transport distances are certainly differentin nature. Here, it depends on the frequency and magnitude of highdischarge events until a sediment cover over the handaxes hasformed that will protect them from further erosion. The sedimentcover may form during times of low discharge, in which handaxesare not transported, but silt and sand are transported and eventu-ally deposited on the handaxes.

Glynn Isaac made similar observations for concrete handaxereplicas placed in channels near Lake Magadi, in the SouthernKenya Rift not far from the Olorgesailie site (Isaac, 1967). Thesehandaxe replicas were only moved under flash flood conditions.After three flash floods in two years, the handaxe replicas weretransported over 72 m along the course of the river bed. Thisdemonstrated that stone tools can be transported by rivers overlarge distances in a relatively short period of time (Isaac, 1967).Artifact tilting can be used as a possible criterion with which todistinguish between flash flood deposits, and a lag situation inwhich a stream had enough energy to erode smaller and lighterobjects (e.g., flakes) while heavier objects were left behind andreoriented into stable positions. Tilting of artifacts does not occurduring flash floods, but steady discharge rates may produce tiltingin lag deposits, as observed in our flume channel experiments.From these results, we conclude that handaxe accumulations on asand bed in which the artifacts exhibit a preferred orientation butno tilting can be explained by sudden high velocity flows such asflash floods following heavy thunderstorms (Isaac, 1967).

We used an automated orientation analysis to detect preferredorientations in handaxe accumulations (interpreted to have beendue to sudden high velocity flows) at the Olorgesailie and Kar-iandusi prehistoric sites. We used typical Acheulean handaxes as areference object, but other elongated objects such as pebbles, fossilbones, or different types of stone tools, can be also used to detectpreferred orientations. The quality of such an analysis, however,depends on the choice of the reference object, which needs to havea distinct shape and well-understood behavior in a water-current.Additional requirements for the analyzes are that the orientations



of the handaxes have been accurately recorded on the excavationplans and that they were not displaced between their depositionand excavation. The present-day displays of the handaxes at theKariandusi and Olorgesailie prehistoric sites and museumscertainly do not reproduce the original orientations of thehandaxes.

The results of the orientation analysis and the different geologicsettings of the sites combine to suggest that the concentrations ofhandaxes at Olorgesailie and Kariandusi are the result of differentprocesses. The handaxes at the Olorgesailie Main Site Mid Trenchshow a preferred southwestenortheast orientation and hencesuggest reworking by a southeast-northwest oriented river(assuming that the preferred orientation of the long axes of thehandaxes is perpendicular to the current vector). Though our ex-periments and those of Isaac (1967) indicate that sudden highdischarge events, such as flash floods, cause reorientation of han-daxes, the sedimentary record of the site dominated by well-sortedsilts and sands does not show any evidence of such events. Apossible explanation for this inconsistency is that the preferredorientation of the artifacts formed during a relatively short highvelocity event without transport of major volumes of sedimentfrom a larger source area. After such an event, the river’s transportcapacity would be back to normal, hence, transporting only silt andsand that would eventually cover the handaxes (thereby protectingthem from further erosion). This interpretation is in agreementwith the results obtained by Isaac (1977), who suggested that ar-tifacts from this site were transported only a short distance from anearby source.

The situation at the Upper Kariandusi Site is similar to that at theOlorgesailie Main Site Mid Trench location, with the handaxes alsobeing embedded in fluvial deposits and exhibiting a preferredorientation. In contrast to Olorgesailie, however, the sediments atthe Upper Kariandusi Site also include pebbles (Gowlett andCrompton, 1994), indicating a more dynamic fluvial environmentthat could easily have transported objects as large as handaxes. Thecharacter of the sediments, the absence of tilting of the handaxesand their strong preferred orientation suggests that the artifactswere transported by a high discharge event such as a flash flood.The difference in abrasion between trachyte and obsidian artifactsand a possible nearby source for the trachyte could, however,indicate a difference inweathering or lag deposit. Alternatively, thedifference can be explained by a combination of processes inwhichartifacts were transported to a site where other artifacts had beenpreviously deposited and remained in situ, because they wereburied by sediment to greater extent that redeposition could notoccur anymore. Hence, there has clearly been a reorientation ofartifacts, but the degree of transport remains uncertain.

In contrast to the two previous sites, the random distribution oforientations in our analysis of the Olorgesailie Main Site H/6A didnot suggest any reworking and redeposition of the stone tools. Thetilting of the handaxes, the abundance of smaller objects such asflakes, and fine-grained sediments support this result. The randomdistribution and tilting of the handaxes at this location requiresfurther analysis to explain the accumulation of stone tools,assuming that the excavation plans are precise with respect to theorientation of the stone tools. As a possible interpretation, thehandaxes could have been moved and rotated randomly afterhaving been transported to, and deposited in, this location, eitherby erosional/depositional process other than rivers, for example byanimals (including hominids). A second interpretation of the site isthat it is the result of reworking by a river with relatively lowcurrent velocities that was able to move but not rotate handaxes. Athird interpretation of the handaxe concentrations follows the fa-vorite place hypothesis of Schick (1992). According to this hy-pothesis, the handaxes would have been produced by a small group


of hominids that revisited the same location from time to time andthus produced the handaxe concentration over a long period oftime (Schick, 1992).

The reason for revisiting the same location could be the prox-imity of a site to a river or large freshwater lake (Trauth et al., 2005,2007). Both a river or lake are likely to have provided water andfood for hominids over wetter climatic episodes lasting up to tenthousand years, (i.e., about a half precessional cycle), with the riverand the lake probably disappearing during intervening dry epi-sodes (Trauth et al., 2005, 2007). Rift lakes are sensitive to relativelymoderate climatic fluctuations, and the resulting fluctuations in thesize of such lakes may have led to fluctuations in the local hominidpopulations (who would have required different strategies to findfood), and even to human migrations (Trauth et al., 2010). Suchlake-shore environments can change quite frequently in the courseof climate fluctuations, affecting the availability to hominids ofwater, seasonal food resources, and trees for shelter. The largergroups of hominids that may have gathered during wetter climaticperiods would have come under pressure during less favorableconditions, possibly resulting in severe depletion of vital resourcesand migrations of hominids to refuges such as the Olorgesailie andKariandusi basins. Large groups of stone tool makers could there-fore have occupied the area for a relatively short period of time, asdescribed in the congregation hypothesis (also introduced bySchick, 1992).

Acknowledgments

This project was funded by grants to M.H. Trauth by the GermanResearch Foundation (DFG). The authors would like to thank theGovernment of Kenya (Research Permits MOST 13/001/30C 59/10,59/18 and 59/22), the Kenyan Ministry of Water and Irrigation, andthe University of Nairobi for research permits and support. We arealso grateful to the staff at Kariandusi and Olorgesailie for theirinterest and discussions during the visits to the prehistoric sites.The concept for this research was inspired by a visit to Kariandusiand Olorgesailie in 2010 during a summer school funded by theVolkswagen Foundation, led by M.H. Trauth and colleagues, inwhich M.J. Walter participated as a student. Funds for the flumechannel experiments were also provided by the DFG through theGraduate School of the University of Potsdam (GRK1364: ‘ShapingEarth’s Surface in a Variable Environment: Interactions betweenTectonics, Climate and Biosphere in the African-Asian monsoonalregion’). We thank Rick Potts for inspiring discussions, whichsignificantly contributed to our work. We thank Ed Manning forprofessional proofreading of the manuscript. M.J. Walter would liketo acknowledge Thomas Euler at the Geography Institute of theUniversity of Bonn and the Beuth Hochschule für Technik in Berlinfor allowing him to perform flume channel experiments, and tothank Rudolf Walter for creating the excellent handaxe replicas.

Appendix A. Supplementary data

Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.jhevol.2013.02.011.

References

Allen, J.R.L., 1982. Sedimentary Structures. Their Character and Physical Basis.Elsevier, Amsterdam.

Batschelet, E., 1981. Circular Statistics in Biology. Academic Press, London.Benito-Calvo, A., Torre, I. de la, 2011. Analysis of orientation patterns in Olduvai Bed

I assemblages using GIS techniques: implications for site formation processes.J. Hum. Evol. 61, 50e60.

Binford, L.R., 1977. Olorgesailie deserves more than the usual book review.J. Anthropol. Res. 33, 493e502.





Boaz, N.T., Behrensmeyer, A.K., 1976. Hominid taphonomy: transport of humanskeletal parts in an artificial fluviatile environment. Am. J. Phys. Anthropol. 45,53e60.

Bridge, J.S., Demicco, R.V., 2008. Earth Surface Processes, Landforms and SedimentDeposits. Cambridge University Press, Cambridge.

Clark, J.D., Kurashina, H., 1979. An analysis of earlier stone age bifaces fromGadeb (Locality 8E), northern Bale highlands, Ethiopia. S. Afr. Archaeol. Bull. 34,93e109.

Davis, J.C., 2002. Statistics and Data Analysis in Geology, third ed. John Wiley andSons, New York.

Dibble, H.L., Chase, P.G., McPherron, S.P., Tuffreau, A., 1997. Testing the reality of a‘living floor’ with archaeological data. Am. Antiq. 62, 629e651.

Euler, T., Herget, J., 2012. Controls on local scour and deposition induced by ob-stacles in fluvial environments. Catena 91, 35e46.

Fisher, N.I., 1996. Statistical Analysis of Circular Data. Cambridge University Press,New York.

Gowlett, J., Crompton, R., 1994. Kariandusi: Acheulean morphology and the ques-tion of allometry. Afr. Archaeol. Rev. 12, 3e42.

Isaac, G.L., 1967. Toward the interpretation of occupation debris: some experimentsand observations. Kroeber Anthropol. Soc. Pap. 37, 31e57.

Isaac, G.L., 1977. Olorgesailie: Archeological Studies of a Middle Pleistocene LakeBasin in Kenya. University of Chicago Press, Chicago.

Jones, T.A., 2006. MATLAB functions to analyze directional (azimuthal) dataeI:single-sample inference. Comput. Geosci. 32, 166e175.

Leopold, L.B., Emmett, W.W., Myrick, R.M., 1966. Channel and hillslope processes ina semiarid area, New Mexico. U.S. Geol. Surv. Prof. Paper 352-G, 193e252.

Mardia, K.V., Jupp, P.E., 2000. Directional Statistics, second ed. John Wiley and Sons,Chichester.

McPherron, S.J.P., 2005. Artifact orientations and site formation processes from totalstation proveniences. J. Archaeol. Sci. 32, 1003e1014.

Nichols, G., 2009. Sedimentology and Stratigraphy, second ed. John Wiley and Sons,Chichester.


Petraglia, M.D., Potts, R., 1994. Water flow and the formation of Early Pleistoceneartifact sites in Olduvai Gorge, Tanzania. J. Anthropol. Archaeol. 13, 228e254.

Potts, R., Behrensmeyer, A.K., Ditchfield, P., 1999. Paleolandscape variation and earlyPleistocene hominid activities: members 1 and 7, Olorgesailie Formation,Kenya. J. Hum. Evol. 37, 747e788.

Rapp, G.R., Hill, C.L., 2006. Geoarchaeology, second ed. Yale University Press,New Haven.

Schick, K.D., 1986. Stone Age Sites in the Making: Experiments in the Formation andTransformation of Archaeological Occurrences. In: BAR International Series 319.(Oxford).

Schick, K.D., 1992. Geoarchaeological analysis of an Acheulean site at Kalambo Falls,Zambia. Geoarchaeology 7, 1e26.

Shackley, M.L., 1978. The behaviour of artefacts as sedimentary particles in afluviatile environment. Archaeometry 20, 55e61.

Sheppard, P.J., Kleindienst, M.R., 1996. Technological change in the earlier andmiddle stone age of Kalambo Falls (Zambia). Afr. Archaeol. Rev. 13, 171e196.

The MathWorks, 2011. Getting Started Guide and Image Processing Toolbox User’sGuide. The MathWorks Inc, Natick.

Trauth, M.H., 2010. MATLAB Recipes for Earth Sciences, third ed. Springer Verlag,Berlin.

Trauth, M.H., Deino, A., Bergner, A.G.N., Strecker, M.R., 2003. East African climatechange and orbital forcing during the last 175 kyr BP. Earth Planet. Sci. Lett. 206,297e313.

Trauth, M.H., Maslin, M.A., Deino, A., Strecker, M.R., 2005. Late Cenozoic moisturehistory of East Africa. Science 203, 2051e2053.

Trauth, M.H., Maslin, M.A., Deino, A., Strecker, M.R., Bergner, A.G.N., Dühnforth, M.,2007. High- and low-latitude forcing of Plio-Pleistocene African climate andhuman evolution. J. Hum. Evol. 53, 475e486.

Trauth, M.H., Maslin, M.A., Deino, A., Junginger, A., Lesoloyia, M., Odada, E.,Olago, D.O., Olaka, L., Strecker, M.R., Tiedemann, R., 2010. Human evolution andmigration in a variable environment: the amplifier lakes of Eastern Africa.Quatern. Sci. Rev. 29, 2981e3348.


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A MATLAB based orientation analysis of Acheulean handaxe accumulations in Olorgesailie and Kariandusi, Kenya Rift