Blame Colombus? New skeletal evidence and the paleodemography of the Americas over the millennia. - PowerPoint PPT Presentation

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Blame Colombus? New skeletal evidence and the paleodemography of the Americas over the millennia.

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Title: Blame Colombus? New skeletal evidence and the paleodemography of the Americas over the millennia.


1
Blame Colombus? New skeletal evidence and the
paleodemography of the Americas over the
millennia.
  • Fertility regulator of demographic dynamics in
    the Ancient Americaspaper posted at
    www.hist.umn.edu/
  • rmccaa/paleodem.doc

2
Richard Steckel and Jerome Rose (eds.), The
Backbone of History Health and Nutrition in the
Western Hemisphere (7000 BP 1900 AD), Cambridge
University Press, 2002
  • Largest collection of skeletal microdata ever
    assembled 12,500 skeletons, 65 sites, 7
    millennia
  • Uniform methodology 24 bio-archaeologists, 6
    historians

3
SubjectThe human skeleton.Microdatasource
for studying health, nutrition and demographic
dynamics
4
Outline, 45 slides
  • 1. (10) Bioarcheological evidence on
    paleopathologies and height Ancient America was
    no paradise
  • 2. (15) Paleodemography new method
  • 3. (20) New findings demographic dynamics for 3
    periodsAncient (7000 1500 BP)Classic (1500
    500 BP)Historical (500 100 BP)

5
Blame Columbus? (Title of a New York Times
review of book, but not a concern of the book
itself)
  • 1. Bioarcheological evidence on paleopathologies
    and height Ancient America was no paradise
  • 2. Paleodemography new method
  • 3. Demographic dynamics for 3 periodsAncient
    (7000 1500 BP)Classic (1500 500
    BP)Historical (500 100 BP)

6
4 measures of health and nutrition
  1. Porotic hyperostosis
  2. Degenerative joint disease (limbs, spine)
  3. Dental disease
  4. Stature

7
Hard Times in Ancient Americas
  • Skeletal archaeology shows porotic hyperostosis
    as nearly universal perhaps due to extreme
    dependence on corn.

8
Porotic Hyperostosis a physiological
adaptation to inadequate absorption of oxygen
  • High frequency 1/3 1/12 of adults in these
    communities show signs of extraordinary bone
    remodeling.
  • Worsened over time as the transition to
    sedentary agriculture proceeded (1-3,000 BP),
    physiological conditions deteriorated.
  • No gendered difference A near complete absence
    of sex differentials in pathologies is
    surprising.

9
Degenerative joint disease (DJD)
  • DJD 10-20 of adults of both sexes.
  • From age 20, hard, repetitive work exacted severe
    wear on both sexes, particularly of joints
    required for mobility, manipulation of objects,
    and carrying loads.
  • Genderdifferencesstatisticallysignificantin
    DJD andcranialfractures.

10
Degenerative joint disease, spinepicture
worsens
  • Generally high levels ranging from 25 to 83 for
    adults from the Mesoamerican sitesa ubiquitous
    affliction, principally due to hard labor.
  • Where the means of carrying heavy burdens is
    almost solely the human body, an enormous
    biological cost is exacted from the organism.

11
Shovel shaped incisorsgenetictrait of Native
Americans
12
Severe dental disease was common in societies
based on corn
13
Stature, 3 features stand out
  • 1. Males decline over time in mean height 1 cm.
    per thousand years--due to worsening nutrition?
  • 2. Female stature constant over time even from
    pre-historic period.
  • 3. Males show decreasing stature from north (164
    cm) to south (161 cm).

14
Male stature declines over time confirmed in
Center and South
North ?165 cm no decline
South ?161 cm much decline
Center?162 cm some decline
All ?162 cm accelerating decline
15
Male stature gradient S. (15) to N. (30)
greatest in modern times (1900-1960)
3200-1800 BP ?164 cm b-.25, r2.12
1800-1200 BP ?162 cm b.50, r2.36
1200-500 BP?163 cm b.36, r2.47
100-40 BP ?159 cm b.78, r2.74
Females (lt150 cm) little variation in space or
time.
16
Blame?
  • 1. Bioarcheological evidence on paleopathologies
    and height Ancient America was no paradise
  • 2. Paleodemography new method
  • 3. Demographic dynamics for 3 periodsAncient
    (7000 1500 BP)Classic (1500 500
    BP)Historical (500 100 BP)

17
PaleodemographyMaterialsskeletons by estimated
age at deathMethodsfit estimated age
distributionto stable models
18
A quick lesson in model life tables (of stable
populations)
  • Stable populations
  • regardless of initial conditions
  • populations subjected to constant birth and death
    rates
  • will evolve to stable age and death structures,
    that is
  • population aged 0, 1, 2, will be the same
    year-after-year as long as birth death rates
    are stable
  • of deaths aged 0, 1, 2, will be the same
    year-after-year

19
So, for the paleodemographer
  • If ancient populations were stable
  • If the recovered skeletons are representative of
    the dying population
  • And if the age at death of the skeletons can be
    estimated
  • Then, we match observed skeletal age distribution
    with those of stable populations to derive
  • Birth and death rates
  • Life expectancy, even age structure

20
How exactly do we do this?2 steps 1.
Materials Age distribution of skeletons
  • Example, Belleville, Ontario. 19th century white
    populationwell preserved

Age 0 5 10 15 20 25 30 35 40 45
Deaths (n) 239 31 12 4 22
11 21 36 31 116
45.7 5.9 2.3 0.8 4.2 2.1
4.0 6.9 5.9 22.1
Cum 45.7 51.6 53.9 54.7 58.9 61.0 65.0
71.9 77.8 100.0
21
How exactly do we do this?2 steps 2. Models
life tables
  • Coale Demeny 1983
  • 25 e0s 20-80 years, at 2.5 year intervals
  • 13 GRRs 1 6 girls, at various intervals
  • 4 Regions North, South, East, West
  • Total 25x13x41300

22
Model West Females level 2,GRRs 0.8 6 e0
22.5 years
Population at age
  • Statistics
  • Population at/to age

Cummulative
deaths at age
  • Deaths at/to age
  • 18 stats for each GRR (see separate pages for
    other e0s and regions)

Cummulative
Other stats
23
  • Question Are age structures of dying
    determined by fertility (within a sheet) or
    mortality (between sheets)?

or mortality (between sheets)?
Between (mortality)?
Answer contrary to common sense, fertility!!!
24
Fertility effects are big
GRR 2 , 3, 4, 5, 6 e0 20
25
Fig. 2. Mortality offers a small target
Mortality effects are smallexcept at young (lt
15) and old ages (60)
GRR 3 e0 20, 30, 40, 50

26
GRR 2, 3, 4, 5, 6e020
GRR 3e020, 30, 40, 50
GRR 2, 3, 4, 5, 6e050
GRR 4e020, 30, 40, 50
27
Three recent advances in paleodemography
  1. Fertility has stronger effects on age
    distributions than mortality.
  2. Proportional hazard models are more robust than
    simple percentages.
  3. Fitting observed skeletal distributions to stable
    populations yield valuable demographic insights.

28
Four innovations here
  1. Use only best age data ages 5-45
  2. Fit all possible modelsGRR (gross reproduction
    ratio) 2-6 daughterse0 (life expectancy at
    birth) 20-50 years
  3. Consider range of good fits, instead of only
    best fitall pretty good fits
  4. Calibrate paleodemographic results against
    historical demographysee next figure

29
Calibrating method skeletal data for 19th
century Belleville, Ontario
30
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31
Calibration of life expectancy, e0 (Belleville)
  • Conventional paleodemography 20.8 years (MAD,
    mean age at death)
  • PH models, using best age data, pretty good fits,
    GRR 3.16, growth rate 236 years (see
    table 4.1)
  • Historical data (parish books, census)36.5 years

thanks to an anonymous reviewer for the idea of
calibrating the method using Belleville.
32
Blame?
  • 1. Bioarcheological evidence on paleopathologies
    and height Ancient America was no paradise
  • 2. Paleodemography new method
  • 3. Demographic dynamics for 3 periodsAncient
    (7000 1500 BP)Classic (1500 500
    BP)Historical (1500 AD 1900)

33
Paleodemography new methods, surprising
results Fertility, the key
  • Fertility an important regulator of American
    demographic dynamics
  • Lowest fertility ancient times (1500 BP),
    GRR2.2
  • Higher fertility middle period (1500BP
    1500AD), GRR2.9
  • Highest fertility domesticated animals (horse,
    Plains Indians, 1500 AD-1900), GRR3.2
  • Last five hundred years large ethnic
    differentials, GRRNative Americans
    2.8-2.9African Americans 3.1-3.3European
    Americans 2.4-2.6

34
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35
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36
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37
Paleodemography new methods, surprising
results Mortality (pooled)
  • Life expectancy estimates, e0 contingent upon a
    good estimate of growth rate
  • Highest e0 ancient times (1500 BP), 34 years
  • Lowest e0 middle period (1500-500), 23 years
  • Modern large ethnic differentials in e0 Native
    Americans e0 22-23 yearsAfrican Americans
    e0 21-29 yearsEuropean Americans e0 30-36
    years

38
Three conclusions
  • Great variations in fertility
  • Ancient times,
  • low pressure demographic regime
  • fertility was a brake on population growth
  • Classic times,
  • high pressure demographic system
  • higher fertility, low life expectancy
  • mortality was the brake on pop. growth

39
Three conclusions
  • 2. Agriculture was the caboose of demographic
    change, not the engine
  • Agriculture seems to have evolved as a response
    to demographic pressure
  • Rather than propelling demographic
    transformations.
  • Why? Because in classic times demographic
    transformations occurred in all settlement types.

40
Three conclusions
  • 3. Modern period fundamental demography of
    native peoples did not change with the clash of
    biospheres
  • Paleodemographic method is insensitive to
    demographic catastropheunless a mass grave is
    found
  • Underlying fundamentals persisted for almost a
    thousand years (til 1800)

41
Postscript Blame Colombus?
  1. Demographic catastrophe was realthe debate is
    about magnitude and cause(s)
  2. Magnitude extinction for many smaller
    populations (e.g, Tainos) 1/3-3/4 loss for
    larger populations (Aztecs).
  3. Cause(s) the great debatedisease?
    War/pacification/exploitation? Both?
  4. Varied place-to-place Hispaniola
    exploitation, not disease

42
Blame Colombus? Hispaniola, certainly!!
  • Case of Hispaniola, see
  • Bartolome de Las Casas, Brief Account of the
    Destruction of the Indies (1596), or
  • Massimo Livi-Bacci, Return to Hispaniola,
    February 2003, Hispanic American Historical
    Review

43
Blame Colombus? Hispaniola, certainly!!
  • Disease?
  • First smallpox epidemic, 1518 (25 years after
    contact, colonization).
  • Evidence of other introduced diseases in first
    decades is scant (non-existent?).
  • Malaria and Yellow fever (cited by Wilford, NYT)
    17th- 18th centuries

44
Blame Colombus? Hispaniola, certainly!!
  • Exploitation?
  • ML-B tribute imposed by Colon at the end of
    1495 to the caciques of the pacified Tainos
    every native of 14 years or more was required to
    pay every three months one Flanders hawks bell
    full of gold

45
Blame Colombus? Hispaniola, certainly!!
  • Exploitation?
  • Fragile communitiescongregated
  • Little agricultural surplus
  • All work devoted to food production
  • Unaccustomed to forced labor for building, gold
    mining.
  • Insatiable demand by Christians for gold, slaves,
    servants, sex

46
Demographic catastrophe and its causes viruses,
Black Legend and the social context of epidemics
(Mexico)
Alonso de Zorita (1565) ...and it is
certain that from the day that D. Hernando
Cortes, the Marquis del Valle, entered this
land...the natives suffered many deaths, and many
terrible dealings, robberies and oppressions were
inflicted on them, taking advantage of their
persons and their lands, without order, weight
nor measure ...the people diminished in great
number, as much due to excessive taxes and
mistreatment, as to illness and smallpox, such
that now a very great and notable fraction of the
people are gone, and especially in the hot
country.
47
Blame Colombus??The debate continues
see next issues of Revista de Indias and
Hispanic American Historical Review
48
Thank you paper postedwww.hist.umn
.edu/rmccaa/paleodem.doc
othersHealth nutrition /mxbioarc.docAztec
household family /nacolhist.htmSmallpox
catastrophe /vircatas/vir6.htm
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