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A tool for determining duration of mortality events in archaeological assemblages using extant ungulate microwear.

Rivals F, Prignano L, Semprebon GM, Lozano S - Sci Rep (2015)

Bottom Line: The seasonality of human occupations in archaeological sites is highly significant for the study of hominin behavioural ecology, in particular the hunting strategies for their main prey-ungulates.We propose a new tool to quantify such seasonality from tooth microwear patterns in a dataset of ten large samples of extant ungulates resulting from well-known mass mortality events.The tool is tested on a selection of eleven fossil samples from five Palaeolithic localities in Western Europe which show a consistent classification in the three categories.

View Article: PubMed Central - PubMed

Affiliation: Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.

ABSTRACT
The seasonality of human occupations in archaeological sites is highly significant for the study of hominin behavioural ecology, in particular the hunting strategies for their main prey-ungulates. We propose a new tool to quantify such seasonality from tooth microwear patterns in a dataset of ten large samples of extant ungulates resulting from well-known mass mortality events. The tool is based on the combination of two measures of variability of scratch density, namely standard deviation and coefficient of variation. The integration of these two measurements of variability permits the classification of each case into one of the following three categories: (1) short events, (2) long-continued event and (3) two separated short events. The tool is tested on a selection of eleven fossil samples from five Palaeolithic localities in Western Europe which show a consistent classification in the three categories. The tool proposed here opens new doors to investigate seasonal patterns of ungulate accumulations in archaeological sites using non-destructive sampling.

No MeSH data available.


Related in: MedlinePlus

Coefficient of Variation versus Standard Deviation for the training set.Circles represent seasonal or shorter events; squares stand for longer events; triangles correspond to events separated in time. Datapoints correspond to sub-samples of dataset (#1) (Rangifer tarandus (Qamanirjuaq, Canada), yellow); dataset (#3b) (Antilocapra americana (pronghorn) from Lamont and Rawlins (Wyoming, USA)); dataset (#4) (Odocoileus hemionus (Cache La Poudre River, Colorado, USA), orange); dataset (#5) (Cervus elaphus (Isle of Rum, Scotland), blue).
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f5: Coefficient of Variation versus Standard Deviation for the training set.Circles represent seasonal or shorter events; squares stand for longer events; triangles correspond to events separated in time. Datapoints correspond to sub-samples of dataset (#1) (Rangifer tarandus (Qamanirjuaq, Canada), yellow); dataset (#3b) (Antilocapra americana (pronghorn) from Lamont and Rawlins (Wyoming, USA)); dataset (#4) (Odocoileus hemionus (Cache La Poudre River, Colorado, USA), orange); dataset (#5) (Cervus elaphus (Isle of Rum, Scotland), blue).

Mentions: In order to test the utility of combining SD and CV measures, we extracted (from the largest modern datasets) sub-samples corresponding to each one of the three scenarios described above, and calculated SD and CV for all of them. Figure 5 shows the obtained values in a bidimensional map, where scenarios are identified by symbols (see the figure’s caption for details).


A tool for determining duration of mortality events in archaeological assemblages using extant ungulate microwear.

Rivals F, Prignano L, Semprebon GM, Lozano S - Sci Rep (2015)

Coefficient of Variation versus Standard Deviation for the training set.Circles represent seasonal or shorter events; squares stand for longer events; triangles correspond to events separated in time. Datapoints correspond to sub-samples of dataset (#1) (Rangifer tarandus (Qamanirjuaq, Canada), yellow); dataset (#3b) (Antilocapra americana (pronghorn) from Lamont and Rawlins (Wyoming, USA)); dataset (#4) (Odocoileus hemionus (Cache La Poudre River, Colorado, USA), orange); dataset (#5) (Cervus elaphus (Isle of Rum, Scotland), blue).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4663483&req=5

f5: Coefficient of Variation versus Standard Deviation for the training set.Circles represent seasonal or shorter events; squares stand for longer events; triangles correspond to events separated in time. Datapoints correspond to sub-samples of dataset (#1) (Rangifer tarandus (Qamanirjuaq, Canada), yellow); dataset (#3b) (Antilocapra americana (pronghorn) from Lamont and Rawlins (Wyoming, USA)); dataset (#4) (Odocoileus hemionus (Cache La Poudre River, Colorado, USA), orange); dataset (#5) (Cervus elaphus (Isle of Rum, Scotland), blue).
Mentions: In order to test the utility of combining SD and CV measures, we extracted (from the largest modern datasets) sub-samples corresponding to each one of the three scenarios described above, and calculated SD and CV for all of them. Figure 5 shows the obtained values in a bidimensional map, where scenarios are identified by symbols (see the figure’s caption for details).

Bottom Line: The seasonality of human occupations in archaeological sites is highly significant for the study of hominin behavioural ecology, in particular the hunting strategies for their main prey-ungulates.We propose a new tool to quantify such seasonality from tooth microwear patterns in a dataset of ten large samples of extant ungulates resulting from well-known mass mortality events.The tool is tested on a selection of eleven fossil samples from five Palaeolithic localities in Western Europe which show a consistent classification in the three categories.

View Article: PubMed Central - PubMed

Affiliation: Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.

ABSTRACT
The seasonality of human occupations in archaeological sites is highly significant for the study of hominin behavioural ecology, in particular the hunting strategies for their main prey-ungulates. We propose a new tool to quantify such seasonality from tooth microwear patterns in a dataset of ten large samples of extant ungulates resulting from well-known mass mortality events. The tool is based on the combination of two measures of variability of scratch density, namely standard deviation and coefficient of variation. The integration of these two measurements of variability permits the classification of each case into one of the following three categories: (1) short events, (2) long-continued event and (3) two separated short events. The tool is tested on a selection of eleven fossil samples from five Palaeolithic localities in Western Europe which show a consistent classification in the three categories. The tool proposed here opens new doors to investigate seasonal patterns of ungulate accumulations in archaeological sites using non-destructive sampling.

No MeSH data available.


Related in: MedlinePlus