1. For Best Results Please Download the PowerPoint File to See Animations in the Presentation

2. Guy L. Tasa, PhD and Juliette Vogel, MA
The Use of the Howells’ Craniometric Dataset in Determining Ethnicity in Pacific Northwest Native Crania: Implications for Kennewick Man
Guy L. Tasa, PhD
and Juliette Vogel, MA
Washington Department of Archaeology and Historic Preservation

3. Overview Background on the Howells Dataset Study Questions
Sample and Methods
Results
Discussion
Implications for Studies of Kennewick Man

4. The Howells Craniometric Dataset
Data Compiled Between 1965 and 1980
82 Cranial Measurements
2,524 Human Crania
30 World-Wide Populations
Available Online
Majority of populations date from last 500 years, with exception of Anyang in China ( BC), Egyptian ( BC), Guam (1100 AD), and Zalavar ( AD). Of his 28 world populations, only four are Native American (Arikara, Santa Cruz Chumash, Peruvian, and Greenland Eskimo).

5. Uses of the Howells Craniometric Dataset
Forensic Applications- ancestry estimation for unknown individuals, FORDISC
Bioarchaeological Applications- group relationships, settlement patterns, evolutionary trends
Kennewick Man Analysis

6. Howells’ Populations

7. Study Questions
Do Howells’ four Native American groups (Santa Cruz Chumash, Arikara, Eskimo, and Peruvian) serve as appropriate reference samples for identifying Pacific Northwest individuals as Native?
What implications do the findings have for craniometric analyses of Kennewick Man?

8. Sample
Native American Individuals from the Pacific Northwest (51% measured by Tasa):
Adult
Sex determined
No cranial deformation
At least 10 measurements
179 individuals from OR, WA, CA, and BC
(85 females and 94 males; some as early as 3000 BP, but majority are late precontact to contact)

9. Kennewick Man, Howells’ Native Groups, and Pacific Northwest Sample

10. Methods: Howells and FORDISC
Jantz and Ousley (2005) recommend accepting only those classifications with typicalities >0.05.
FORDISC eliminates Howells’ North and South Maori groups for comparison likely due to their small sample size. Therefore, it only uses 28 out of Howells’ 30 groups. Discriminant function analysis to separate groups and attempt to classify unknowns; measurements for individual are compared to 26 or 28 howells groups depending on sex and the individual is placed in the group of best fit. Typicality- likelihood indiv belongs to selected group; Posterior probability- ranking between groups. Really only useful if indiv is from one of the reference samples, as numerous studies have shown. However, the whole purpose of FORDISC is to try to identify population affinities for individuals whose identities are unknown. What researcher using FORDISC is going to know what population an unknown individual is from? Furthermore, Jantz and Ousley (2005) recommend accepting only those classifications with typicalities > On the other hand, after an analysis of FORDISC’s reliability in re-classifying Howells individuals within their own groups, Elliott and Collard (2009) recommend accepting only those classifications with typicalities of >0.952.
Elliott and Collard (2009) recommend accepting only those classifications with typicalities of >0.952.

11. Methods: Howells and FORDISC
Jantz and Ousley range of acceptable typicality- individual can be at the periphery of a group ellipse (at or below the 95th percentile)
Elliott and Collard range of acceptable typicality- individual should be much closer to the group centroid (at or below the 5th percentile)

12. Methods
Use FORDISC discriminant function analysis to compare Native American individuals to Howells’ populations. How many classified as Native American?
Arikara, Eskimo, Santa Cruz Chumash, Peru
Isolate Native American individuals who meet Jantz and Ousley specifications (>0.05 typicality) as well as those that meet Elliott and Collard criteria (>0.952 typicality)

13. Results: All Typicalities Included
Probability of Howells’ dataset correctly identifying one of the NW individuals as Native American is less than chance (43%)

14. Results: All Typicalities Included, Native Groupings
Of 43% individuals classified as Native American, the majority align with Santa Cruz Chumash

15. Results: All Typicalities Included, Non- Native American Groupings
Of 54% individuals classified as Non-Native American, the majority align with Berg, Norse, and Mokapu
No Pacific NW Native Americans classified as Anyang or Guam

16. Results: Acceptable Typicalities Only (>0.05)
Only 41 out of 179 (23%) individuals had typicalities of 0.05+
Probability of Howells’ dataset correctly identifying one of the NW individuals as Native American is now just slightly better than chance (51%)

17. Results: Acceptable Typicalities Only (>0
Results: Acceptable Typicalities Only (>0.05), Native American Groupings
Of 51% individuals classified as Native American, the majority align with Santa Cruz Chumash and Arikara

18. Results: Acceptable Typicalities Only (>0
Results: Acceptable Typicalities Only (>0.05), Non-Native American Groupings
Of 49% individuals classified as Non-Native American, the majority align with Berg
No Pacific NW Native Americans classified as Anyang, Atayal, Australia, Buriat, Easter Island, Guam, North Japan, Phillipines, Tasmania, Tolai, Zalavar, or Zulu

19. Discussion: Pacific Northwest Native Americans
Out of entire sample of 179,
-Only 41 Native American individuals (23%) meet Jantz and Ousley criteria (>0.05 typicality). Twenty of these individuals were incorrectly classified as Non- Native American.
-Only 21 Native American individuals (12%) reliably classified (>0.05) as Native American, following Jantz and Ousley.
-Only 5 Native American individuals (3%) meet Elliott and Collard criteria
(>0.952). One of these individuals was incorrectly classified as Non-Native American.
-Only 4 Native American individuals (2%) reliably classified (>0.952) as Native American, following Elliott and Collard.
Discriminant function analysis with Howells’ dataset clearly indicates his samples are insufficient for identifying PNW Native Americans as Native American

20. Discussion: Native American Variability
Cavalli-Sforza et al. 1994: genetic markers indicate modern Native Americans express greater internal variability than any other regional group
Jantz 2006, Jantz et al. 2010: genetic variation paralleled by anthropometric variation
Although researchers clearly acknowledge there is a shortage of data to represent this variability, there is still a tendency to misinterpret results of craniometric analyses
This study shows that there is not enough data in Howells four Native groups to make assignments for this group of recent Natives let alone Natives thousands of years old, and especially for just one Native thousands of years old. Any analysis of Kennewick Man that employs such a small geographic and temporal cross-section as a reference for Native variability should be seriously questioned. Some scholars do make an effort to include additional Native populations in their Kennewick analyses (Powell and Rose 1999; Jantz and Spradley 2014), but there is still an incredible dearth of data.

21. Implications for Studies of Kennewick Man
There is not enough data in Howells’ four Native American groups to make assignments for this group of recent Native Americans, let alone Native Americans thousands of years old, and especially for just one Native American thousands of years old.
Some scholars do make an effort to include additional Native American populations in their Kennewick analyses (Powell and Rose 1999; Jantz and Spradley 2014), but there is still an incredible dearth of data. Meaningful conclusions cannot be drawn until there is more data to cover the large temporal and spatial gap between Kennewick Man and modern Native Americans.
Pacific Northwest Native American Sample