Fig 1.
Location of the Wadi el-Jilat sites.
A close up of the Wadi el-Jilat gorge includes an overview of the individual site locations.
Table 1.
Categories of soil samples from Wadi el-Jilat sites used for the geochemical and phytolith analysis in this study.
Fig 2.
Average measurements in ppm for all samples within WJ13 per context category for the following chemical elements: (A) P, (B) K, (C) Mg and (D) Mn.
Fig 3.
PCA biplot for the geochemical results, WJ7.
The first component is driven by Mg, Si, Ti, Fe, S, Zr, K and P, and the second component by Ca, Sr and Rb. The third component is driven by Cl.
Fig 4.
PCA biplot for the geochemical results, WJ13.
The first component is driven by Ti, Si, Fe, K, Al, Zr and Nb. The second component is driven by Mg, Ba, Sr and Ca, and the third by Cr, P, Rb, Cl and negatively by V.
Table 2.
Associations between chemical elements and anthropogenic related activities found in earlier studies and, where applicable, anomalies found at the Wadi el-Jilat sites [after 29, p.271-7).
Fig 5.
A) Ratio of monocot to dicot per context category at WJ7; B) Plant part ratio per context category at WJ7; C) Silica aggregate and phytolith count ratio per context category at WJ13.
Fig 6.
PCA biplot for the phytolith results, WJ7.
The first component is driven by monocots, unidentified and degraded phytoliths, leaf, leaf/stem, Pooideae and single-cell phytoliths. The second component is driven by weight percent, Chloridoideae and negatively by burnt phytoliths. The third component is driven by Panicoideae, leaf/husk and weight percent.
Fig 7.
PCA biplot for the phytolith results, WJ13.
The first component is driven by the variables monocots, leaf and leaf/stem, the second is negatively driven by dicots and single-cell phytoliths. The third component is driven by number of phytoliths per gram and multi-cell phytoliths.
Fig 8.
Decision tree created for WJ13 based on the geochemical results, including the categories: Deposit, hearth, bedrock feature, activity area, fill and background.
38% of cases were correctly classified. The numbers within each subset (or tree node) represent the amount of instances that are found within the subset. In cases where two numbers appear within the tree node, the first number indicates the ‘correct’ instances and the second reflects the ‘incorrect’ instances falling within the subset (i.e. samples having categories which agree or disagree with the category represented in the node). The numbers appearing between the tree nodes and the variables represent the splitting point, i.e. the value that split the instances according to those containing values of this variable that are smaller, larger or are equal to this number.
Fig 9.
Decision tree created for WJ13 based on the phytolith results, including the categories: Deposit, hearth, bedrock feature, activity area, fill and background.
21% of cases were correctly classified. The numbers within each subset (or tree node) represent the amount of instances that are found within the subset. In cases where two numbers appear within the tree node, the first number indicates the ‘correct’ instances and the second reflects the ‘incorrect’ instances falling within the subset (i.e. samples having categories which agree or disagree with the category represented in the node). The numbers appearing between the tree nodes and the variables represent the splitting point, i.e. the value that split the instances according to those containing values of this variable that are smaller, larger or are equal to this number.
Fig 10.
Decision trees created for WJ7 based on the geochemical analysis (left) and phytolith counts (59% and 46% of cases correctly classified, respectively).
The numbers within each subset (or tree node) represent the amount of instances that are found within the subset. In cases where two numbers appear within the tree node, the first number indicates the ‘correct’ instances and the second reflects the ‘incorrect’ instances falling within the subset (i.e. samples having categories which agree or disagree with the category represented in the node). The numbers appearing between the tree nodes and the variables represent the splitting point, i.e. the value that split the instances according to those containing values of this variable that are smaller, larger or are equal to this number.
Fig 11.
Flowchart illustrating the use of decision trees and Bayesian calculation to combine the results of the soil analyses.
Table 3.
Overview of the classification of samples from WJ13 in the field, the results of the application of the probability model, and proposed reclassification based on the results of the geochemical and phytolith analyses.
The prior probability was set at 0.5, the weight of the results of the geochemical and phytolith analyses was set at 0.38 and 0.21 (respectively) to reflect the amount of correctly classified cases in the decisions trees.
Fig 12.
A) PCA biplot for WJ13 based on the geochemical analysis results; B) PCA biplot for WJ13 based on the geochemical analysis results after the change in the categories of some of the samples after the application of the Bayesian based model.
Fig 13.
A plan of early and middle phases at Wadi el-Jilat 13, before (top) and after (bottom) the reclassification of samples.
Fig 14.
A plan of late phase at Wadi el-Jilat 13, before (top) and after (bottom) the reclassification of samples.