CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES IN CHINA
OVER THE LAST MILLENNIUM
DAVID D. ZHANG1 , C. Y. JIM1 , GEORGE C-S LIN1 , YUAN-QING HE2 ,
JAMES J. WANG1 and HARRY F. LEE1
1
Department of Geography, University of Hong Kong, Pokfulam Road, Hong Kong
E-mail: [email protected]
2
CAREERI, Chinese Academy of Science, Lanzhou 730000, Gansu, China
Abstract. In recent years, the phenomenon of global warming and its implications for the future
of the human race have been intensively studied. In contrast, few quantitative studies have been
attempted on the notable effects of past climatic changes upon human societies. This study explored
the relationship between climatic change and war in China by comparing high-resolution paleoclimatic reconstructions with known war incidences in China in the last millennium. War frequencies
showed a cyclic pattern that closely followed the global paleo-temperature changes. Strong and
significant correlations were found between climatic change, war occurrence, harvest level, population
size and dynastic transition. During cold phases, China suffered more often from frequent wars,
population decline and dynastic changes. The quantitative analyses suggested that the reduction of
thermal energy input during a cold phase would lower the land carrying capacity in the traditional
agrarian society, and the population size, with significant accretions accrued in the previous warm
phase, could not be sustained by the shrinking resource base. The stressed human-nature relationship
generated a ‘push force’, leading to more frequent wars between states, regions and tribes, which
could lead to the collapse of dynasties and collapses of human population size. War frequencies varied
according to geographical locations (North, Central and South China) due to spatial variations in the
physical environment and hence differential response to climatic change. Moreover, war occurrences
demonstrated an obvious time lag after an episode of temperature fall, and the three geographical
regions experienced different length of time lags. This research also shows that human population
increases and collapses were correlated with the climatic phases and the social instabilities that were
induced by climate changes during the last millennium. The findings proposed a new interpretation of
human-nature relationship in the past, with implications for the impacts of anomalous global warming
on future human conflicts.
1. Introduction
The relationship between civilization and climatic change is of fundamental importance, so much so that it can facilitate the rise or demise of culture (Cowie, 1998).
It has been a long-standing belief that climatic change would lead to social, cultural
and economic repercussions in human societies. For instance, Hsu (1998) advocated
that micro-changes of temperature exerted notable influences on the fate of human
civilization. Recently, important attempts have been made to use high-resolution
paleo-climatic record to explain several pre-historical cultural breaks in certain
time periods (deMenocal, 2001; Polyad and Asmerom, 2001; Weiss and Bradley,
2001; Wu and Liu, 2002). Extensive documentation has been made in attempts to
Climatic Change (2006) 76: 459–477
DOI: 10.1007/s10584-005-9024-z
c Springer 2006
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assess the causes of wars (e.g., Pruitt and Snyder, 1969; Westing, 1988; Seabury
and Codevilla, 1989; van Evera, 1999; Ge et al., 2002), but none tackled specifically
the climatic change-war relationship. Webster’s (1975) study of pre-historical and
early-historical societies suggested that warfare is an adaptive ecological choice
under the conditions of population growth and resource limitation, although he did
not obtain systematic scientific data to support his thesis. Malthus (1798) and many
ecological studies considered that when a species (including human) population size
exceeded a certain threshold that could not be supported by available resources, the
population would crash. Such a collapse in human population, in Malthus’ view,
was partially achieved by wars. The association between wars and the environment has been recognized by some researchers (Ferguson, 1984; Stranks, 1997;
Suhrke, 1997; Cowie, 1998). However, the existing literature tends to focus on the
social and economic costs of current and future environmental changes. We believe
that learning how past climatic changes had influenced human society is crucial to
understanding the current human-nature situation and predicating the future.
The last three decades witnessed intensive research on past climatic change
around the world. The last 10 years work, in particular, has ushered significant
improvements in high-resolution paleo-climatic reconstructions, using multi-proxy
data networks to reconstruct past climate variations. A focus on the last millennium
showed the global warming trend, from which it has been concluded that the last
century was the warmest (Jones et al., 2001; Mann et al., 2003). It is reckoned that
such refined paleo-climatic records could provide a strong basis to evaluate the
intricate relationship between climatic change, wars and dynastic transitions.
The large land area and geographical variations in China have permitted climate
to express itself explicitly in its varied natural and cultural landscapes, and associated modes of human occupancy and livelihood. The effect of climate has had the
most far-reaching and persistent historical imprints on the country (Chang, 1946).
In investigating the relationships of climate-war and climate-dynastic cycle, China
would afford an excellent case study. In the course of China’s long history, voluminous documentation in the palace archives of different dynasties, dating back to
880 BC, systematically recorded all major events. This valuable and comprehensive
information repository provided a rich database for our study.
We propose the hypothesis that long-term climatic change has brought significant shifts in land carrying capacity which could be considered as a variable
in history. This view is contrary to the traditional one of Malthus, Darwin and
many ecologists who hold land carrying capacity as a constant. Such capacity
shifts could have influenced the well-being of the humankind socially, economically and culturally not only in pre-historical time but also in recent history of
agricultural societies. In favorable climatic phases, the land carrying capacity increased, the conflict for resources was reduced and the population grew fast. When
climate became unfavorable, resulting in capacity decline, the population size with
much accretions accumulated in the previous favorable period could not be sustained. Therefore, armed conflicts for limited resources largely increased in more
CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES
461
populated areas that could consequently lead to population crash and dynastic collapse. These perceived climate-war and climate-dynasty relationships have never
been substantiated with scientific evidence. In this study, we adopted a new approach to analyze quantitatively the climate-war and war-society relationships at
the macro-scale, by comparing the paleo-climatic series with war, population and
historical sequences. Through this high-resolution comparison, the degree of influence extended by climatic change on wars and historical events may be examined
and our hypothesis tested.
2. Data and Methods
A group of researchers from the Nanjing Academy of Military Sciences has compiled a multi-volume compendium that records exhaustively information on the
wars that took place in China from 800 BC to AD 1911 (Editorial Committee of
China’s Military History, 1985). The book includes an appendix with details of
each war, including its inception year, participants, location, causes, and in most
cases, the number of soldiers or combatants, casualties, proceedings and results.
All of the 1672 wars listed in the authoritative treatise from AD 1000 to 1911 have
been used as the database for this study. To avoid bias associated with different
sources of information, only the reliable variables were used for scientific analysis,
including year of inception, number, participants and location of the wars. Based
on such information, the frequency, participant-type and geographical distribution
of the wars can be calculated with reference to a time series. Some wars without
reliable information on locations were put in an unidentified category. War classification was based on the types of participants, particularly leaders of the two sides
in the armed conflicts. The wars were grouped into rebellion and others (state and
tribal wars).
The times of dynastic changes were based on official records published by
government bodies and historians. The dynasties included those that ruled most
parts of China, and those established by remote tribes that once occupied an area
equivalent to over 10 provinces of the current Chinese territory.
The geographical occurrence of wars helped the assessment of climate-war association. According to the basic principles of physical regionalization of China
(Ren et al., 1985; Zhao, 1986), China is divided into three macro regions for this
study, namely: (1) North China with continental humid, semi-humid, semi-arid and
arid temperate climate influenced by both the monsoons and the westerlies. Its
average annual temperature ranges from very low to 14 ◦ C. Major agriculture products are spring wheat (northern part) and winter wheat (southern part). Economic
activities are mainly pastoral because the relatively low average annual precipitation of 50–750 mm, with over 100 frost days per year. (2) Central China with a
climate dominated by the monsoons, with annual temperature ranging from 14 to
18 ◦ C, and 10–80 frost days per annum. The region has served as China’s major rice
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Figure 1. Physical regionalization and major agricultural products of China.
producing area. (3) South China with a south subtropical and tropical climates and
average annual temperature ranging from 19 to 22 ◦ C. The long growing season
permits double- or triple-cropping in a year. Frost days are less than 10 per annum
(Figure 1).
Briffa and Osborn (2002) chose the five most representative and the latest climate
series of the last millennium in the Northern Hemisphere, including the data from
China, to discuss the differences between the records of various independent studies
(Figure 2a). Despite the diverse sources of data, all five high-resolution climate
records register close matching of warm and cold phases. Such congruence of
data acquired independently by different authorities suggested a high degree of
accuracy with reference to both temperature and timing. These climatic series
provided a reliable basis to investigate the relationships between climatic changes
and historical events in China. The records from AD 1000 to 1980 have been adopted
as the standard climate variations in this study. These records were reconstructed by
using multi-proxy data, including tree ring, coral, ice-core, borehole and historical
document studies. The data were recalibrated by Briffa and Osborn (2002) with
linear regression against the AD 1881–1960 mean annual temperature observations
averaged over the land area north of 20 ◦ N, and the results were smoothed with
a 50-year filter. The recalibrated records were then averaged by us in order to
quantitatively define the boundaries of the cold and warm phases. A cold or warm
phase would be determined if the average temperature change (bold black line,
Figure 2a) has an amplitude exceeding 0.14 ◦ C, in order to get an equal aggregate
duration of cold and warm periods. Six major cycles of ‘warm’ and ‘cold’ phases
have been identified from AD 1000–1911 based on the average reconstruction.
These phases were also reflected in many other climatic reconstructions of China
CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES
463
Figure 2. Climatic changes and incidence of wars in China during the last millennium. (a) Normalized
temperature change records for the last millennium for land areas in the Northern Hemisphere north
of 20 ◦ N: Cowley and Lowery (1997, turquoise line); Jones (1998, dark blue line); Mann (1999, pink
line); Briffa (2000, yellow line); Esper (2002, violet line) and the average of these five normalized
series (bold black line). Cold phases are shaded as gray strips. (b) Frequency of total wars (sky blue
line) and frequency of rebellions (red line). (c) Frequency of wars, in North China (red line); in Central
China (sky blue line); and in South China (bright green line). (d) Dynastic changes and population
size (in million) in China.
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and North Hemisphere (e.g., Zhang et al., 1981; Seabury and Codevilla, 1989;
Wang, 1990; Ge et al., 2002; Mann et al., 2003). The boundaries between warm
and cold phases were delineated at the mean temperature point between minimum
and maximum values of two contiguous phases on the average reconstruction. The
aggregate duration of the cold phases was 459 years and of the warm phases 453
years. The cold phases spanned AD 1110–1152, 1194–1302, 1334–1359, 1448–
1487, 1583–1717 and 1806–1911, and warm phases AD 1000–1109, 1153–1193,
1303–1333, 1360–1447, 1488–1582 and 1718–1805 (Figure 2a). Although a few
paleo-temperature reconstructions have been conducted in China and their changes
basically followed the above constructions, the resolution of such reconstructions
did not reach the annual scale that we achieved in this research. Therefore, we
decided to use the five constructions quoted by Briffa and Osborn (2002) as the
standard paleo-temperature records of the last millennium.
The link between war, climatic change and quantitative harvest information
during the last millennium is very important in testing our hypothesis. Whereas wars
and climatic change are comparatively well documented, it proved very difficult to
obtain records of agricultural production over a long period because most dynasties
in the study period had no proper registry system to collect such data. Fortunately,
records were compiled under the ‘Baojia’ system introduced in China during the
Qing Dynasty (AD 1644–1911), which stored population, harvest and land data
for taxation and other administrative purposes. This valuable archive allowed a
comparison of harvests in China at 66 different localities in AD 1730–1900 (Gong
et al., 1996), which covered a cycle of warm and cold phases for verification of
temperature-change impacts on harvests.
It has been quantitatively proved that shifts in land carrying capacity that followed climatic changes brought cyclic growth and collapse of the Mesopotamian
population (Johson and Gould, 1984), and that long-term climatic changes had
brought fluctuations of population size in mid-latitude countries in the 17th century
(Galloway, 1986). However, no study has been attempted on the long-term time
series of population change in conjunction with the corresponding highly accurate
temperature data. According to our hypothesis and Webster’s (1975) view, population pressure resulting in reduced food supply per capita is another important cause
of wars. The population data were retrieved from Jiang (1993) who reviewed many
population records and studies and provided reliable population fluctuations from
206 BC. We adapted the record from AD 1000 onwards (Figure 2d).
3. Results
3.1.
FREQUENCY OF WARS AND CLIMATIC PHASES
Like climate variations, the war frequency in China demonstrated a cyclic pattern, with a turbulent period followed by a relatively tranquil one (Figure 2b).
CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES
465
War frequencies were summed by decades and grouped into four classes: very
high (>50 wars/10a), high (25–50 wars/10a), moderate (10–25 wars/10a) and low
(<10 wars/10a). Eight out of the ten peaks above the very high and high groups
coincided with cold phases. Three high peaks stood well above others (Figure 2b,
sky blue line), two of which occurred in the coldest phases (c. <−0.5 ◦ C). All cold
phases have one or two high war frequencies. Wars generally occurred with a time
lag of 0–30 years after the initiation of a cold phase. Only two high peaks fell outside the cold phases (the aberrant peaks) and they both occurred in the 16th century.
Although some temperature declines could be observed in this period, they were not
enough to be classified as a ‘cold phase’. Rebellion was the dominant war category
(Figure 2b, red line). The variation of the rebellion frequency is highly correlated
with climatic changes. The aberrant peaks, overshadowed by this correlation, were
mainly brought by nomadic invaders from the north and wars with pirates intruding
from overseas.
The geographical distribution of these historical wars (Figure 2c) depicted an
interesting pattern. In warm and humid South China, war frequency variations were
less sensitive to temperature changes. War outbreaks in North China were closely
associated with cold phases, and war frequencies remained at a relatively constant
higher level in AD 1300–1600. Six of the seven highest war peaks in Central China
occurred in cold phases, and they all closely followed cold phases. When cold
phases started, wars in North China immediately broke out, except the cold phases
in the 14th and 19th centuries when China was ruled by northern nomadic tribes
(respectively, Mongol and Manchu). In contrast, high war frequencies in Central
China generally had a 10–30 year time lag behind the highs of North China, and a
20–50 year time lag after the cold phases started.
The wars ushered notable societal changes that could eventually induce the
collapse and establishment of dynasties in AD 1000–1911 (Figure 2d). All dynastic changes during the study period basically occurred in cold phases with high
war frequencies, except the Yuan Dynasty collapse and the establishment of Ming
and Xixia Dynasties (Figure 2d and Table I). Of the six cold phases in the last
millennium, five had experienced dynasty collapse.
3.2.
STATISTICAL ANALYSIS
To refine the analysis, the number of wars in each phase was calculated and the
ratios of wars in warm and cold phases were compared (Table II). The results show
a pattern consistent with the above observation. Although wars could be induced
by other underlying causes and their response to temperature change had a time
lag (cf. Section 3.1), the correlation analysis between temperature anomaly and
war frequency still revealed notable associations between climatic change and war
occurrence. Pearson’s correlation coefficients between war frequency and temperature anomalies have been computed at three different time scales: phase, decade
and annual.
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TABLE I
Relationships between climatic phases, wars and dynastic changes
Year (AD)
Average
temperature
anomaly (◦ C)
Climatic
phases
Number
of wars
1000–1109
−0.252
Warm
135
1.23
1110–1152
−0.368
Cold
93
2.16
1153–1193
−0.315
Warm
41
1.00
1194–1302
−0.419
Cold
252
2.31
1303–1333
−0.362
Warm
33
1.07
1334–1359
1360–1447
−0.454
−0.345
Cold
Warm
90
189
3.46
2.15
1448–1487
1488–1582
−0.461
−0.392
Cold
Warm
89
208
2.23
2.19
1583–1717
−0.534
Cold
266
1.97
1718–1805
−0.413
Warm
72
0.82
1806–1912
−0.456
Cold
204
1.93
War
ratios
Dates of dynastic
changes (AD)
Establishment of Jin (1115),
collapses of North Song (1127)
and Liao (1125) dynasties
Establishment of Great Mongol
(1206) and Yuan (1271), collapses
of Jin (1234), South Song (1279)
Establishment of Ming and collapse
of Yuan (1368)
Establishment of Qing (1636) and
collapse of Ming (1645)
Establishment of the Republic of
China and collapse of Qing (1911)
TABLE II
Number of wars and ratio of wars in cold and warm phases in different war categories
Cold phases (459 years)
Warm phases (453 years)
Ratio of wars (cold/warm phases)
Total wars
Rebellions
Others
North
Central
South
994
678
1.47
536
275
1.95
69
53
1.30
351
278
1.25
462
237
1.95
116
110
1.06
The phase scale calculation could determine whether war outbreak was related to low or average temperature anomalies. In each phase, the highest war
frequency, the lowest temperature and average temperature anomalies were included in the calculation. The results showed that the highest frequencies of total war, rebellion war and Central China war were significantly correlated with
both the lowest and average temperature anomalies of the phases (Table III). The
correlations at the decade scale were computed between the number of wars in
each decade and the lowest and average temperature anomalies with 0–30 year
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TABLE III
Pearson’s correlation coefficients
Total wars
Rebellions
Others
North
Central
South
Between average temperature anomalies and the highest war
frequencies in each climatic phase
−0.693∗
−0.686∗
−0.014
−0.511
−0.666∗
−0.525
−0.707∗
∗
Between the lowest temperature anomalies and the highest
war frequencies in each climatic phase
−0.707∗
−0.084
−0.516
−0.697∗
−0.576
Significant at 0.05 level (two tailed).
TABLE IV
Pearson’s correlation coefficients
Time lag (year)
0
10
20
30
0
10
20
30
∗
Total wars
Rebellions
Others
North
Central
Between average temperature anomalies and number of wars in each decade
−0.179
−0.229∗
0.030
−0.090
−0.214∗
−0.223∗
−0.268∗
−0.010
−0.133
−0.274∗
∗
−0.200
−0.252
0.026
−0.076
−0.271∗
0.122
−0.204
0.096
0.024
−0.225∗
South
−0.065
−0.043
−0.065
−0.106
Between the lowest temperature anomalies and number of wars in each decade
−0.177
−0.240∗
0.052
−0.090
−0.220∗
−0.071
∗
∗
−0.213
−0.268
0.029
−0.137
−0.260∗
−0.042
−0.200
−0.258∗
0.036
−0.083
−0.275∗
−0.051
∗
−0.090
−0.114
−0.203
0.109
0.300
−0.223
Significant at 0.05 level (two tailed).
time lags. The numbers of rebellions and wars in Central China were significantly
correlated with the lowest and average temperature anomalies for most time lag
durations (Table IV). The number of total wars is significantly correlated only
with both anomalies at the 10-year time lag. Such differences also appeared in
the annual scale correlation analysis. Each year’s war counts were significantly
correlated with temperature anomalies in the categories of total war, rebellion
and Central China war for 0–30 year time lag (Table V). It is very interesting
that North China wars, not correlated with temperature anomalies at phase and
decade scales, were significantly correlated with annual temperature anomalies at
5-, 10- and 15-year time lags. The highest correlation coefficients for different time
lags varied with war categories. For rebellion, total war and Central China war,
most correlated time lags were 10–15 years, comparing with North China war at
5–10 years.
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TABLE V
Pearson’s correlation coefficients between annual temperature anomalies and annual war records
Time lag (year)
Total wars
Rebellions
Others
North
Central
South
0
5
10
15
20
25
30
−0.115∗∗
−0.143∗∗
−0.153∗∗
−0.152∗∗
−0.142∗∗
−0.117∗∗
−0.091∗∗
−0.156∗∗
−0.178∗∗
−0.191∗∗
−0.192∗∗
−0.180∗∗
−0.162∗∗
−0.145∗∗
0.026
0.009
0.008
0.012
0.013
0.030
0.050
−0.060
−0.086∗∗
−0.086∗∗
−0.073∗∗
−0.052
−0.021
0.012
−0.133∗∗
−0.160∗∗
−0.179∗∗
−0.183∗∗
−0.178∗∗
−0.163∗∗
−0.151∗∗
−0.034
−0.024
−0.021
−0.023
−0.033
−0.042
−0.046
∗∗
Significant at 0.01 level (two tailed).
4. Analysis and Discussion
4.1.
WAR FREQUENCY AND TEMPERATURE CHANGES
In the last millennium, the high degree of match between war frequencies and cold
phases, and the significant correlations between temperature anomalies and war
numbers, could not have happened simply by accident or chance. It is believed that
the reduction of thermal energy input in cold periods was the root cause of social
unrest and uprising. In the ‘Little Ice Age’, many places around the world experienced famine (Ponte, 1976; Bryson and Murray, 1977) and witnessed large-scale
population migration (Hsu, 1998) literally in search of food. As an overwhelmingly
agrarian society, China’s main source of livelihood was agriculture. Traditional agriculture was very much dictated by the whims of climate and weather conditions.
Any reduction of thermal energy input would trim agriculture production. According to Gong et al. (1996), agricultural yields in China in AD 1840–1890 (cold phase)
was reduced by 10–25% in comparison with AD 1730–1770 (warm phase), because
the cold periods shortened the growing season and increased frost days and cold
spells.
Significant yield reduction caused by cooling was also evidenced by the history
of rice cultivation in the middle and lower reaches of the Yangtze River. Double
cropping of rice started in Tang Dynasty (AD 618–906), as an innovation in agricultural technology, and was further developed in the late 15th century in Ming Dynasty
(AD 1368–1643). The double cropping, however, failed in AD 1620–1720 because
of the colder weather, and thereafter in AD 1720–1800 it recovered and dominated
the region again. In the 19th century, double cropping in the region failed again despite the government’s promotion of the techniques (Yin et al., 2003). In the region,
all previous periods of double cropping successes coincided with warm phases,
and at present the system is functioning well. Our quantitative study sought to use
records across a long time frame to determine whether variations in agricultural
CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES
469
Figure 3. Temperature anomalies and harvest variations in China during AD 1730–1910. Temperature
anomalies (bold black line) correspond to the right Y-axis; while autumn and summer harvest records
(cross- and circle-dotted lines) correspond to the left Y-axis. Harvest records are expressed in terms of
indexes to exceptionally good historical harvests (max. = 10) and smoothed by the Butterworth lowpass filter. Correlation coefficient between temperature anomalies and the autumn (summer) harvest
indexes in China during AD 1730–1850 is 0.854 (0.764), P < 0.01.
production were correlated with temperature changes. The AD 1730–1850 records
demonstrated that the average summer and autumn harvests in China also followed
congruently the temperature changes (Figure 3).
Yield reduction would trigger famine, tax revolt and a weakening of state power.
The deficit in livelihood resources was aggravated by the population expansion
accumulated in the previous warm period. Thus rebellions and state wars were likely
to erupt during the cold phases. It is notable that rebellions were predominantly
mobilized by peasants in the cold phases. The three highest peaks of war frequency
actually represented three of the most notable peasant rebellion periods in Chinese
history, namely Taiping, Mingmo, Yuanmo rebellions. Comparing Figure 3 with
Figure 2, we found that the outbreak of Taiping rebellion occurred when harvests
fell to a critical level. A significant consequence of this rebellion was the reduction
of China’s total population from 440 million in AD 1850 (the year of Taiping
rebellion outbreak) to 360 million in AD 1865. Such a population crash would
shrink greatly the agrarian workforce and left a serious carry-over effect on harvest
level. Even though the climate became warmer after the rebellion, agricultural
production remained low for some time (Figure 3).
The time lags of high war frequencies in cold phases and of war occurrences
in decadal and annual scales have important implications on the bearing capacity
of society, which could be explained in two ways. The first is that the reduction
of livelihood resource would not immediately generate social unrest because the
storage of agricultural products could sustain people for some time, so was the
state power. The second explanation is due to the development of a better social
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organization which could provide a cushion to prolong the lag-time from the first
to the last cold phases in the millennium.
The correlation analysis provided a quantitative expression of the wartemperature relationship. It is not surprising that the highest war frequency, average
temperature and lowest temperature anomalies were significantly correlated in the
categories of the total war, rebellion and Central China war at the phase scale.
This is due to the fact that prolonged cooling had exhausted the stored livelihood
resources and eventually brought wars. We did not expect that the temperature
anomaly shifts at the decadal and annual scales were significantly associated with
wars. This is because the temperature anomaly series is averaged and smoothed
values and many short-term climate extremes could not be shown in the curve.
However, even without the influence of temperature extremes, the correlation analyses at the short-term scale still verified that war number is significantly correlated
with the trend of Northern Hemisphere temperature changes.
4.2.
GEOGRAPHICAL PATTERN OF WARS
The geographical distribution of wars lent further supports to our hypothesis
(Figure 2c). In humid tropical and subtropical South China, the influence of cooling
in cold phases on agricultural production might have a subdued effect on resource reduction because of rich endowment in heat and moisture in the coastal region. Even
if cooling were severe enough to affect cropping, the more flexible farming system
in the South, with a wide range of domesticated species, could adopt alternative
crops. Therefore, human reaction to cooling in South China had not been so sensitive
and severe. In contrast, the climate in Central China is controlled by the monsoons:
cold-dry air masses move in from Siberia in the winter and warm-humid marine air
masses come in from the southeast and southwest in the summer. Although the cold
phases reduced agricultural yield, the outbreak of wars generally demonstrated a
delay after the cold period started because, unlike North China, surplus farm products could be stored to serve as a buffer in difficult times. Besides, the better heat
and water resources there allowed the hardship and associated dissatisfaction of the
society to take some incubation time to reach its breaking point. In other words,
the high war frequencies clearly echoed more stringent resource conditions. This
observation also explained why the cold phase in mid-15th century did not cause a
very high war frequency. This cold phase was very brief (39 years), preceded by a
rather long warm phase (84 years) with good harvest. It should be noted that many
studies of China’s paleo-climate indicated that the cold periods were dominated
by winter monsoons from Siberia and hence were drier than warm periods (An,
2000; Li et al., 2000). Thus cold periods could have imposed a double jeopardy in
terms of coldness and dryness, bringing a highly stressed condition for agriculture.
However, precipitation changes in China were more complicated in terms of its
regionality and amplitude than temperature changes and further studies are needed.
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TABLE VI
Pearson’s correlation coefficients between annual temperature anomalies and annual war records of
North China during the period without northern tribe occupation
Time lag (year)
0
5
10
15
20
25
30
Pearson’s correlation −0.208∗∗ −0.238∗∗ −0.233∗∗ −0.222∗∗ −0.217∗∗ −0.201∗∗ −0.183∗∗
coefficients
∗∗
Significant at 0.01 level (two tailed).
North China, where the main sustenance was grazing, was sensitive to cooling
which could reduce short-term production and trigger long-term loss of ecosystem
productivity due to land degradation and desertification. In addition, unlike crop
produce, the pastoral animal resources could not be stored for a long time. Thus
in the north the onset of a cold period would soon be followed by wars. This
phenomenon was reflected in the changes of correlation coefficients of different
time lags, showing that the significant war reactions to cooling were five years
earlier than Central China. Many wars involved the invasion of desperate nomadic
people from the grasslands in Mongolia to the fertile land in Central China. It could
be noted, however, that the cold-warm ratio of wars in North China is not higher
than that of Central China, and the correlation between temperature anomaly and
war number is only significant in 5–15 year time lags at the annual scale, although
most of the high frequencies occurred in cold phases. At the time when the whole
China or part of Central China was ruled by northern nomadic tribes (South Song,
Yuan and Qing Dynasties), which covered more than 500 years and over half of the
study period, people in the north could freely shift to the south or acquired their
livelihood from the south, thus the war frequency in North China was reduced in
the cold phases (respectively in the 13, 14, 17 and 19th centuries). This point could
be corroborated by the fact that wars in North China had lost their leading role in
the countrywide uprisings occurring in cold phases in the 14 and 19th centuries
(Figure 2c). At the annual scale correlation analysis, if we disregard the occupation
years, the correlation between temperature anomaly and war number in North China
was more significantly correlated with the temperature anomaly than other areas
(Table VI).
4.3.
POPULATION AND TEMPERATURE CHANGES
Five demographic collapses occurred during the last millennium, each with population losses ranging from over 30 million to 80 million (Figure 2d). These collapses
happened in cold phases and coincided with high war frequencies and dynastic
changes. On the contrary, all warm phases had fast population growth. Ecologists
and population biologists have long used the logistic model of population dynamics
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DAVID D. ZHANG ET AL.
to understand the cause-effect relationship between carrying capacity and population size (Hopfenberg, 2003). The model, embodying the ideas of Malthus and
Darwin, considered that the population growth before industrialization presented a
sigmoidal or S-shaped curve and the land carrying capacity for supporting humans
was a constant. Therefore, human population collapses in history were generally
explained by the population exceeding the limit imposed by carrying capacity. Our
analysis, however, showed that such population collapses were initiated by the reduction of land carrying capacity, not by population growth per sec. In cold phases,
the threshold of land carrying capacity was reduced and the population accrued in
the previous warm phase was trimmed by cultural responses to natural changes,
namely the attrition of war, famine and dynastic change. In warm phases, the
threshold of land carrying capacity was raised and the population growth quickly
rebounded to catch up with the elevated limit. Such fast population growth undoubtedly created the underlying condition for the next population crash in a cold
phase. Such crashes were explained by the impacts of famine, war and epidemics
(Malthus, 1798). However, it seemed that war was the major and root cause of
periodic population crashes in China.
In the last millennium, 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. Such developments, coupled with a mild
climate, trade, urbanization and possibly the improvement of social organization,
led to a population surge in the 18th century. This may imply that technological
advancements since the 18th century have increased the land carrying capacity to
a certain degree and reduced the climate-dependence of human population.
The climatic reconstructions also showed a gradual cooling trend since AD 1000
and before the 20th century. Such climatic impact on bio-productivity forced people
in the north to migrate towards the south. Chang (1946) indicated that southward
movement of the population from the less to the more favorable climatic regions
was the major internal migration trend of China in historical times. Since the inception of the Song Dynasty (AD 960), China’s economic and cultural centers had
shifted southward particularly to the fertile land of the Yangtze River Delta (Central
China), as the northern wheat and pastoral regions could not support a population as
dense as the rice region. Since then over 60% of the Chinese population lived in the
Central and South. This shift reflected human response to the gradual global cooling
trend from the 1000s to 1900s, which was followed by global warming since 1900s.
Fang (1992) identified two waves of southward migration in China in the last millennium, namely in AD 1000–1300 and AD 1630–1900. All three long cold phases
in the last millennium fell into these two periods. From early 1900s until recently,
a reverse movement towards the north, mainly from the over-populated Shandong
and Henan Provinces to the relatively sparsely populated Northeast China, reduced slightly the population share of south China in 1984 to 57% of the national
total.
CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES
4.4.
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DYNASTIC CYCLES AND CLIMATIC CYCLES
The philosopher Mencius (374–288 BC) perceptively observed that a period of order was perforce followed by a period of disorder. The Chinese believed generally
that a minor disturbance was expected every thirty years and a major one every one
hundred years (Hsu, 1995). Interestingly, during the last millennium the cold phases
of the average reconstruction could be divided into long ones each lasting 105–133
years and short ones about 25–43 years. The major disorders often coincided with
the collapse of dynasties. Western scholars have described this phenomenon as
‘dynastic cycle’, the study of which has engendered a host of economic, evolution
and development explanations of Chinese history (Hartwell, 1967; Elvin, 1973;
RWGCRST, 1979). As observed in Figure 2d, the start and end of a cycle were
basically associated with cold periods during the last millennium. The established
cyclic theories attempted to explain the up-down pattern as the consequence of
social evolution or internal mismanagement. However, none of the existing theories has ever presented systematic evidence to sustain the hypothetical elaboration.
Moreover they neglected the influence of environment or climate as a direct causal
mechanism. Skinner (1985) provided a diagram to show regional cycles of development of North China and Southeast Coast based on documentary records. Our
study found that the three episodes of economic decline of North China in the
last millennium were associated the three longest cold phases which also experienced the highest war occurrences. In contrast, the economy of Southeast Coast
was basically expanding during these three periods. The shift of economic centers
in China was explained by opening of trade, change of politic center and foreign
invasion. The development cycles were incorporated into the dynastic cycles, the
movement of which depended on the military power, administrative efficiency and
fiscal strength and stability (Skinner, 1985). Skinner also mentioned about putative
links between climatic cycles and cycles of economic prosperity and indicated that,
if such speculations were borne out in future research, the long-term cycles of climate could help to explain the long-term cycles of Chinese economic activity. Our
findings suggested that climatic change was closely associated with war frequency
because the shortage of livelihood resources in cold periods could trigger wars. The
outbreak of wars would further weaken state power, eventually leading to dynastic
collapse. It can be noted that the three long cold phases in the last millennium had
brought about the collapse of the three longest dynasties: Song, Ming and Qing.
Therefore, the climatic cycles should be incorporated in the cyclic theories in future
studies.
5. Conclusion
Climatic change has played a very important role in Chinese history in the last millennium. When global cooling occurred, the war number increased significantly
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DAVID D. ZHANG ET AL.
because of shrinking livelihood resources exacerbated by the large population accretion in the previous warm phase. High war frequency caused the collapse of
dynasties and population. The impacts of cooling varied in the three major geographical regions of China. In North China, cooling would generate social unrest
very quickly because of its dominant pastoral practice. War frequency in South
Chin had little correlation with cooling due to its humid subtropical and tropical climate where small temperature decline could hardly affect yields from the
predominant arable agriculture. The outbreak of wars in Central China responded
closely to cooling, but with a very obvious time lag of generally 10–20 years.
Such delays reflected the cushion effect of crop food storage for a certain period of
time.
The findings of this study could raise issues of theoretical and empirical significance. Traditional wisdom would explain the fundamental causes of wars as
economic, political, ethnic, and recently also environmental. None of these reasons deals specifically the contribution of climatic change. Our research indicated
that climatic change indeed played a very important role in the switch of dynasties and the associated societal evolution, and was the major underlying cause of
wars and cyclic population variations in long-term scale. Analyzing the relationship
between population size and temperature variations also showed that human population growth followed closely the shifting limit of land carrying capacity, including
periods when the capacity was augmented rapidly by technological advancement.
With the lack of a safety margin in good times, the onset of bad times associated
with cooling would bring fast responses expressed as population shrinkage. Therefore, the risk of population collapse due to climatic change still exists in the modern
era.
Currently, the issue of global warming has attracted much research inquiries and
attention. It must be pointed out that, unlike the ‘warm phase’ we discussed above,
the global warming is an unprecedented warming event in the last two millennia
(Mann, 2003; Moberg et al., 2005). As a rather novel climate extreme opposite to
cooling, the increase in global temperature could similarly incur hazards to smallscale farming that still supports most people around the world. In addition, the
humankind and the Earth’s ecosystems have never experienced such a magnitude
of warming in the last two millennia, and it is possible that the global temperature
will continue to rise in the near future. We are still uncertain as to the extent human
impacts could influence natural changes. Further research is needed to assess the
possible armed conflicts as a response to the underlying global warming trend, and
especially that the human population has reached such a dangerously high level
in a world with stressed resource supply. Even if food supply problem would not
arise in highly developed societies, the shortage of other essential resources due
to climatic change, such as fresh water, land area, energy and minerals, plus the
endless demand for a higher standard of living, would very likely trigger armed
conflicts among human societies.
CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES
475
Acknowledgments
We would like to thank the supports from the RGC grant (HKU7243/04H) of the
HKSAR Government and the Outstanding Researcher Award from the University
of Hong Kong, Dr. K.R. Briffa for providing paleo-climatic reconstructions, and
Miss Angel K.Y. Ng for the identification of war locations.
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(Received 6 August 2005; accepted 18 August 2005)