SKULLS

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Geographical variation in size in North American brown bears, Ursus arctos L., as indicated by condylobasal length



www.archive.org/st...t00hall#page/n1/mode/2up

p.10

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The use of the skull in age determination of brown bears:

http://www.bearbiology.co...Vol_3/Zavatsky_Vol_3.pdf

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(AILUROPODA MELANOLEUCA GIANT PANDA BEAR)

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Growth, Sexual Dimorphism, and Geographical Variation of Skull Dimensions of the Brown Bear Ursus arctos in Hokkaido

www.jstage.jst.go.jp/article/jmammsocjapan/17/1/27/_pdf

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ON THE STATUS OF SOME ARCTIC MAMMALS (Robert Rausch)

pubs.aina.ucalgary.ca/arctic/Arctic6-2-91.pdf

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Geographic and genetic boundaries of brown bear (Ursus arctos) population in the Caucasus

1. MARINE MURTSKHVALADZE,
2. ALEXANDER GAVASHELISHVILI,
3. DAVID TARKHNISHVILI

Abstract

The taxonomic status of brown bears in the Caucasus remains unclear. Several morphs or subspecies have been identified from the morphological (craniological) data, but the status of each of these subspecies has never been verified by molecular genetic methods. We analysed mitochondrial DNA sequences (control region) to reveal phylogenetic relationships and infer divergence time between brown bear subpopulations in the Caucasus. We estimated migration and gene flow from both mitochondrial DNA and microsatellite allele frequencies, and identified possible barriers to gene flow among the subpopulations. Our suggestion is that all Caucasian bears belong to the nominal subspecies of Ursus arctos. Our results revealed two genetically and geographically distinct maternal haplogroups: one from the Lesser Caucasus and the other one from the Greater Caucasus. The genetic divergence between these haplogroups dates as far back as the beginning of human colonization of the Caucasus. Our analysis of the least-cost distances between the subpopulations suggests humans as a major barrier to gene flow. The low genetic differentiation inferred from microsatellite allele frequencies indicates that gene flow between the two populations in the Caucasus is maintained through the movements of male brown bears. The Likhi Ridge that connects the Greater and Lesser Caucasus mountains is the most likely corridor for this migration.

Variations in the Caucasian brown bear skulls.










Brown bear skulls (below) from different geographic locations.

From left to right:

Karaginsky Island,
Sakhalin Island (probably subadult),
Ursus arctos pruinosus (The Tibetan Blue Bear)




Below:
Caucasus
Leningrad Oblast
North-East Siberia




Original post made by Warsaw.

[warsaw]

Kamchatka brown bear skull 45,72 cm /27,94 Weight = 10 lbs
I guess that kodiak /coastal brown bear skull could easily exceed 10 lbs
kamchatka&kodiak


"...Next, we weighed the undressed skull; it was 45 pounds, so we assumed that with the paws, etc., the hide had weighed over 200 pounds..."
books.google.pl/books?id=1siT56zv3VEC&pg=PA54&lpg=PA54&dq=Next,%20we%20weighed%20the%20undressed%20skull;%20it%20was%2045%20pounds,%20so%20we%20assumed%20that%20with%20the%20paws,%20etc.,%20the%20hide%20had%20weighed%20over%20200%20pounds&source=bl&ots=6K3cogYkwk&sig=6cU1ffYtbbS7uRQ6mqO-1p_ylQM&hl=pl&ei=U-JXTbCbCovBswbDy52oCw&sa=X&oi=book_result&ct=result&resnum=2&ved=0CCAQ6AEwAQ#v=onepage&q=Next%2C%20we%20weighed%20the%20undressed%20skull%3B%20it%20was%2045%20pounds%2C%20so%20we%20assumed%20that%20with%20the%20paws%2C%20etc.%2C%20the%20hide%20had%20weighed%20over%20200%20pounds&f=false
DISTRIBUTION AND ECOLOGY OF BROWN BEAR IN ROMANIA
Data From Carcass
- Weight of the skull
(gross): 10 kg
- Size of the skull: 36 x 23 cm
Age of the bear: about 15-20 years
- Sex: male
www.bearbiology.com/fileadmin/tpl/Downloads/URSUS/Vol_9/Kalabar_Negrutiu_et_al_Vol_9.pdf

[warsaw]

Boone & Crocked Record Book Pennsylvania only, first 50 2008


1. 23 7/16 Lycoming, PA Picked Up PA Game Comm. 1987 2

2. 23 3/16 Fayette, PA Andrew Seman, Jr. Andrew Seman, Jr. 2005 3

3. 22 15/16 Monroe, PA Jeremy Kresge Jeremy Kresge 2004 5

4. 22 14/16 Carbon, PA Brian J. Coxe Brian J. Coxe 2003 *

5. 22 13/16 Luzerne, PA Joseph E. Mindick Joseph E. Mindick 1998 8

6. 22 13/16 Bedford, PA Jesse L. Ritchey Jesse L. Ritchey 2006 8

7. 22 12/16 Pike, PA Douglas Kristiansen Douglas Kristiansen 2003 11

8. 22 11/16 Bradford, PA Chad M. Reed Chad M. Reed 1991 12

9. 22 9/16 Huntington, PA Raymond K. Pruss Raymond K. Pruss 2001 *

10. 22 9/16 Jefferson, PA Frank A. Rottman B&C National Collection 1991 17

11. 22 9/16 Carbon, PA Joseph M. Legotti Joseph M. Legotti 1991 17

12. 22 8/16 Schuylkill, PA Elwood W. Maurer Elwood W. Maurer 1997 24

13. 22 8/16 Monroe, PA Thomas Q. Vasey Thomas Q. Vasey 1995 24

14. 22 6/16 Huntingdon, PA Paul W. Carothers, Jr. Paul W. Carothers, Jr. 2001

15. 22 6/16 Bedford, PA James E. Deneen James E. Deneen 1995 34

16. 22 6/16 Lycoming, PA John C. Whyne John C. Whyne 1983 34

17. 22 5/16 Mifflin, PA Jonas D. Glick Jonas D. Glick 2007

18. 22 4/16 Centre, PA Joel J. Kuhns Joel J. Kuhns 2005 41

19. 22 3/16 Lebanon, PA Lynn Horst Lynn Horst 2004 49

20. 22 3/16 Lycoming, PA Toby L. Hiestand Toby L. Hiestand 2006 49

21. 22 3/16 Potter, PA Ronald H. Landis Ronald H. Landis 2005 49

22. 22 2/16 Columbia, PA Robert J. Maciejewski Robert J. Maciejewski 2003 60

23. 22 1/16 Monroe, PA William Graver William Graver 2004 76

24. 22 1/16 Pike, PA Thomas J. Young, Jr. Thomas J. Young, Jr. 2003 76

25. 22 Lackawanna, PA Daniel J. Gregorsky Daniel J. Gregorsky 2003 85

26. 22 Lycoming, PA Steve D. Flook Steve D. Flook 2002 85

27. 22 Tioga, PA Ronald E. Andrus Ronald E. Andrus 1994 85

28. 22 Lycoming, PA John T. Zerbe John T. Zerbe 1997 85

29. 22 Lycoming, PA Clarence G. Eppley Clarence G. Eppley 1992 85

30. 21 15/16 Cambria, PA Frank J. Mehalko, Sr. Frank J. Mehalko, Sr. 1992 118

31. 21 15/16 Schuylkill, PA Glen J. Hendricks Glen J. Hendricks 1998 118

32. 21 15/16 Clearfield, PA Dwayne B. DeLattre Dwayne B. DeLattre 1987 118

33. 21 15/16 Indiana, PA Donald L. Stear Donald L. Stear 2006 118

34. 21 14/16 Luzerne, PA Adrian C. Robbins Adrian C. Robbins 1989 141

35. 21 14/16 Lackawanna, PA Jeff J. Kozar Jeff J. Kozar 1998 141

36. 21 14/16 Monroe, PA Scott H. Mosier Scott H. Mosier 2001 141

37. 21 13/16 Luzerne, PA Earl J. Cichy, Jr. Earl J. Cichy, Jr. 2002 161

38. 21 13/16 Lycoming, PA Scott L. Cummings Scott L. Cummings 2001 161

39. 21 13/16 Bedford, PA John W. Colliflower, Sr. John W. Colliflower, Sr. 2000 161

40. 21 13/16 Carbon, PA Robert F. Kulp Robert F. Kulp 1983 161

41. 21 12/16 Pike, PA William A. Savacool William A. Savacool 2007

42. 21 12/16 Pike, PA Jeffrey N. Lee Jeffrey N. Lee 1998 190

43. 21 12/16 Clarion, PA Travis Schill Travis Schill 2003 190

44. 21 12/16 Sullivan, PA James L. Knosp James L. Knosp 2004 190

45. 21 11/16 Tioga, PA Gerald L. Everhart, Jr. Gerald L. Everhart, Jr. 2004 226

46. 21 11/16 Luzerne, PA Gerard E. Dessoye Gerard E. Dessoye 1997 226

47. 21 11/16 Huntingdon, PA Marty W. Snyder Marty W. Snyder 1998 226

48. 21 11/16 Bradford, PA Eugene A. Smiley Eugene A. Smiley 2006 226

49. 21 11/16 Huntingdon, PA Richard James Richard James 2005 226

50. 21 10/16 Schuylkill, PA Steven T. Razzano Steven T. Razzano 2005 262

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Biomechanical Consequences of Rapid Evolution in the Polar Bear Lineage

Abstract

The polar bear is the only living ursid with a fully carnivorous diet. Despite a number of well-documented craniodental adaptations for a diet of seal flesh and blubber, molecular and paleontological data indicate that this morphologically distinct species evolved less than a million years ago from the omnivorous brown bear. To better understand the evolution of this dietary specialization, we used phylogenetic tests to estimate the rate of morphological specialization in polar bears. We then used finite element analysis (FEA) to compare the limits of feeding performance in the polar bear skull to that of the phylogenetically and geographically close brown bear. Results indicate that extremely rapid evolution of semi-aquatic adaptations and dietary specialization in the polar bear lineage produced a cranial morphology that is weaker than that of brown bears and less suited to processing tough omnivorous or herbivorous diets. Our results suggest that continuation of current climate trends could affect polar bears by not only eliminating their primary food source, but also through competition with northward advancing, generalized brown populations for resources that they are ill-equipped to utilize.




www.plosone.org/article/fetchObjectAttachment.action?uri=info%3Adoi%2F10.1371%2Fjournal.pone.0013870&representation=PDF

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The dish-shaped or "concave" face of the brown bear:


Grizzly Bear Skulls & Snouts


The skulls of Black Bears and Grizzly Bears are shaped quite differently
o

The face of a Black Bear slopes downward gently into the muzzle
o

The grizzly bear’s snout is quite different
o

Grizzlies have a dish-shaped or "concave" face
o

While a Black Bear has a broad straight face with a long snout




Source: BC Gov
wlapwww.gov.bc.ca/wld/documents/grzzlybear.pdf


Source: Bear Aware
wlapwww.gov.bc.ca/eeeb/info/bearaware/home/pg/index.htm







Site source: www.bearaware.bc.ca/bears/bears_content_grizzly3bbb.html




Kodiak brown bear.





Manchurian brown bear.

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[warsaw]

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Skull size-age data collected as a result of the regulation changes clearly demonstrated that age structure of the male bear population has a direct impact on the number of large bears available to hunters. On Kodiak, over 90% of male bears have the potential to reach skull sizes exceeding 68 cm, and over half of the bears can attain trophy size if they live long enough. Therefore, when managing for a population that retains a segment of large males, it is important to establish regulations that consider survival rates of adult males as well as productive females. During this study, hunting regulations for Kodiak bears were crafted to distribute harvest throughout the archipelago and reduce hunter efficiency. While season dates included times when hide quality was at its peak, they are also set to afford protection to females that have longer denning periods. Prohibiting harvest of maternal females and their dependent cubs further protected productive females.






The number of trophy males in the population is calculated by multiplying the percentage of > 10-year old males that are projected to have 71 cm (28”) or greater total skull sizes (input variable) by the projected number of males that are at >10 years old, based on a life table. The life table is derived from the initial male population multiplied by the estimated male survival rates (subadult plus adult rates). In making these calculations we assumed: 1) there is a consistent percentage of > 10 year old males that have >71 cm skull sizes and that percentage can be gleaned from harvest data; 2) cementum age data are accurate; and, 3) there is a direct relationship between male bear age and the percentage of trophy-sized bears, and an inverse linear relationship of the number of males available in each age category (i.e., fewer bears in older age categories).

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Alaska Peninsula Brown Bear:




Leland P. Glenn (1980).