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mean of the Northern Hemisphere and Southern Hemisphere temperature anomalies
(Mann and Jones
2003
). The values of the coefficient for wars at the global scale are
thus lower than those of the Northern Hemisphere and Southern Hemisphere alone.
We also examined the major types of population checks (i.e., famines, wars, and
epidemics) in the Northern Hemisphere
11
in relation to climate change in AD 800-
1900
12
(Fig.
14.3
)(Zhangetal.
2011b
). Regressions were run to estimate the relative
sensitivity of various population checks to temperature change in the Northern
Hemisphere.
13
Results show that temperature was negative and highly significant
in all regressions (Table
14.3
). A 10 % decrease in temperature produces on average
2.2%, 1.2 %, and 1.1 % increases in famines, wars, and epidemics, respectively,
in the Northern Hemisphere. Although both warming and cooling can shrink land
carrying capacity, the regression results in the previous section and here indicate
that cooling was generally more detrimental to human societies at the hemispheric
and global scales in history.
14.2.2
Population Collapses
As for the connection between climate change and population collapses
14
in
China, five demographic collapses occurred during the last millennium, each with
population losses ranging from over 30 million to 80 million
15
(Fig.
14.1
d) (Zhang
et al.
2006
). These collapses happened in cold phases. On the contrary, all warm
phases experienced fast population growth.
16
The lag times (within a range of 5-50
years) for population collapses were gradually extended from the first to last cold
phases. This could be explained by gradual introduction of new crops, improvement
in food production and storage and irrigation technologies.
11
Our famine time series was derived from Walford (
1970
) and Golkin (
1987
); our war time series
was derived from Kohn (
1999
); and our epidemics series was derived from Cliff et al. (
1998
), Kohn
(
2001
),andXiaoandLiu(
2005
).
12
The centennial climate variability in the Northern Hemisphere was elicited by arithmetically
averaging the 12 most recent and authoritative paleo-temperature reconstructions chosen by the
Intergovernmental Panel on Climate Change (in
ı
C, from the AD 1961-1990 mean) (Jansen et al.
2007
), then smoothed by the 100-year Butterworth low-pass filter to remove fluctuations on time-
scales <100 years (Fig.
14.3
a).
13
The independent variables are time and temperature anomalies in the Northern Hemisphere. Time
(t) presumably represents technology and/or capital accumulation. An attempt is made to eliminate
the trend from the population, using parabolic (t and t
2
), squared (t
2
) and cubic (t
3
) terms (see
Galloway
1986
). The regressions were corrected for autoregressive disturbances using the Prais-
Winsten estimation method. Results show that the various detrending procedures did not affect the
significance of temperature.
14
The term 'population collapse' refers to negative population growth.
15
The calculation of population losses was based on Jiang (
1993
).
16
See footnote no. 3 for the dates of cold and warm phases in China.
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