- Email: [email protected]
Causality of climate, food production and conflict over the last two millennia in the Hexi Corridor, China
Journal Pre-proof Causality of climate, food production and conflict over the last two millennia in the Hexi Corridor, China
Linshan Yang, Qi Feng, Jan F. Adamowski, Ravinesh C. Deo, Zhenliang Yin, Xiaohu Wen, Xia Tang, Min Wu PII:
S0048-9697(20)30097-8
DOI:
https://doi.org/10.1016/j.scitotenv.2020.136587
Reference:
STOTEN 136587
To appear in:
Science of the Total Environment
Received date:
14 September 2019
Revised date:
6 January 2020
Accepted date:
6 January 2020
Please cite this article as: L. Yang, Q. Feng, J.F. Adamowski, et al., Causality of climate, food production and conflict over the last two millennia in the Hexi Corridor, China, Science of the Total Environment (2018), https://doi.org/10.1016/j.scitotenv.2020.136587
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2018 Published by Elsevier.
Journal Pre-proof
Causality of Climate, Food Production and Conflict over the Last Two Millennia in the Hexi Corridor, China Linshan Yang1, Qi Feng1*, Jan F Adamowski2, Ravinesh C. Deo 3, Zhenliang Yin1, Xiaohu Wen1, Xia Tang1, and Min Wu1 1
of
Key Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, CHINA 2 Department of Bioresource Engineering, Faculty of Agricultural & Environmental Sciences, McGill University, Québec H9X 3V9, CANADA 3 School of Sciences, Centre for Applied Climate Sciences & Centre for Sustainable Agricultural Systems, Institute for Life Sciences and the Environment, University of Southern Queensland, Springfield, QLD 4300, AUSTRALIA
-p
Abstract
ro
Corresponding to Qi Feng ([email protected])
re
The relationship between climate and human society has repeatedly been investigated to
lP
ascertain whether climate variability can trigger social crises (e.g., migration and armed conflicts). In the current study, statistical methods (e.g., correlation analysis and Granger
na
Causality Analysis) are used in a systematic analysis of the potential causality of climate
Jo ur
variability on migration and armed conflicts. Specifically, the statistical methods are applied to determine the relationships between long-term fine-grained temperature and precipitation data and contemporary social conditions, gleaned from historical documents covering the last two millennia in China‘s Hexi Corridor. Results found the region‘s reconstructed temperature to be strongly coupled with precipitation dynamics, i.e., a warming climate was associated with a greater supply of moisture, whereas a cooling period was associated with more frequent drought. A prolonged cold period tended to coincide with societal instability, such as a shift from unification towards fragmentation. In contrast, a prolonged warm period coincided with rapid development, i.e., a shift from separation to unification. The statistical significance of the causality linkages between climate variability, bio-productivity, grain yield, migration and
Journal Pre-proof conflict suggests that climate variability is not the direct causative agent of these phenomena, but that climate-induced production supplements gradually deteriorated following migration and conflicts. A conceptual causal model developed through this study describes the causative pathway of climate variability impacts on migration and conflicts in the Hexi Corridor. Applied to under current conditions, the model suggests that steady and proactive promotion of the nation‘s economic buffering capacity might best address the uncertainty brought on by a range of
of
potential future climate scenarios and their potential impacts.
ro
Keywords: Climate variability; Food production; Migration; Conflict; the Hexi Corridor
-p
1 Introduction
re
The concept that climate change and variability can trigger changes within human society is
lP
not novel. The relationship between climate variability and societal changes has been studied extensively, especially in the context of arid and semi-arid regions where environmental
na
sustainability is extremely fragile (Fang and Liu, 1992; Feng et al., 2019; Meze-Hausken, 2000;
Jo ur
Sarkodie et al., 2019). Those with fewer resources are likely to experience greater exposure to extreme weather events, particularly in developing countries with low income (Ye et al., 2012). Zhang et al. (2008, 2011a) found high resolution paleo-climatic data indicating that climate change and variability have played an important role in human migration and conflicts in the past. In ancient times, humans tended to cope with the adverse impacts of climate variability through migrations to areas with sufficient grass, food, and water (deMenocal and Stringer, 2016; Destek and Sarkodie, 2019). In some instances, when this migration led to the crossing of territorial borders, conflict and warfare ensued (Feng et al., 2019). The connection between climate change and variability and historical human migrations and conflicts has been revealed in studies covering Europe (Lee et al., 2013; Zhang et al., 2011), China (Pei et al., 2016; Ye et al., 2012)
Journal Pre-proof and other locales (Pei and Zhang, 2014). However, the question remains as to how one might systematically identify the processes that dominate a society‘s emergence, resilience and collapse, along with the complex interactions at work between these processes at multi-decadal or greater time scales. Identifying a method to this end would support plausible explanations for these shifts, and in turn, the development of effective policies and strategies to improve a society‘s resilience.
of
To this point, much of the literature investigating climate change and variability as a
ro
motivating factor for migration has considered climate-migration relations at only a very general
-p
level (Meze-Hausken, 2000). Relevant studies have focused mainly on the temporal
re
correspondence between climate and human migration; results are seldom verified with robust
lP
statistical or mathematical methods (Bekun et al., 2019). The cause-effect relationships between climate and human society are sufficiently complex and obscure that simple approaches are
na
insufficient for their analysis. For example, climate variability, specifically drought, is one of
Jo ur
many factors that promote migration (Meze-Hausken, 2000). In many cases, this climate-induced migration is linked to famine, caused by drought. However, not every drought leads to famine, and conversely, not every famine has its roots in drought. Moreover, during a famine, people may cope with scarcity through means other than migration (Sarkodie and Strezov, 2019). Therefore, it is necessary to further clarify the causal linkage between climate and human society by exploring how climate change and variability trigger human social processes. The wide geographic variation in China‘s climate patterns means that there are different impact pathways of climate-related influences on Chinese society. Human migration in different agro-ecological zones is partially a manifestation of changes in climate (Pei et al., 2013). However, large-scale studies performed in China, Europe and North Hemisphere, do not appear
Journal Pre-proof to capture the internal connections and specific factors of influence. Some studies have addressed patterns of migration in different sub-regions; however, most of these were qualitative studies that focused on an individual event (Zheng et al., 2014). Although some studies have investigated human migration in specific regions of China, their temporal span is limited to a few centuries (Pei et al., 2015b); studies on the response of a specific region‘s human social dynamics at the multi-century scale and beyond have not yet been carried out.
of
The current researchers selected northwestern China‘s Hexi corridor as the study area, as
ro
similar research has not yet be undertaken in the region. Susceptible to environmental change,
-p
the Hexi corridor is an ecologically fragile, endorheic basin, subject to an inland arid climatic
re
zone (Feng et al., 2015; Feng et al., 2019). The region‘s grassland and agricultural areas draw
lP
upon surface runoff from snowmelt in the northern portion of the Qilian Mountains (Yang et al., 2019a; Yin et al., 2016). The region has been alternately claimed by the southern members of the
na
northern nomadic minorities and the Han people. Conflicts between pastoralists and
Jo ur
agriculturalists have reportedly occurred on a regular basis, making the region one of the scenes for major battles between the armies of ancient China and nomadic minorities (Feng et al., 2019). These violent interactions influenced the characteristics of the populations that migrated due to famine, social unrest, and war (Zhang et al., 2005). The prime focus of the current study was to identify the processes that dominate a society‘s emergence, resilience and collapse, and the complex interactions among these processes in the Hexi Corridor. More specifically this study was undertaken to: (i) investigate the causality of climate variability and human society in the Hexi Corridor, (ii) understand how migration and conflict events are driven by a shift in climate, and (iii) present a framework for social resilience in the face of future climate change. The results presented herein can provide a reference for
Journal Pre-proof decision-makers involved in the successful adaption of human societies to climate change conditions.
2 Materials and method 2.1 Study area Located between 37°17‘–42°48‘ N and 93°23‘–104°12‘E, the Hexi Corridor is a string of
of
oases along the northern edge of the Tibetan Plateau in China‘s Gansu province (Yang et al.,
ro
2011). The corridor is situated in a long, narrow passage stretching for over 1000 km from east
-p
to west and 100–200 km from south to north (Yang et al., 2011). Mountains and deserts limited caravan traffic to a narrow trackway; this meant that relatively small fortifications could control
re
passing traffic in the region. A part of the renowned Ancient Silk Road, in historical times the
lP
Hexi Corridor allowed traders and the military to travel from northern China to Xinjiang and
na
Central Asia (Feng et al., 2019). The geography of the Silk Roads represents a complex interaction between the physical and climatic zones of mountain, the steppes or grasslands, and
Jo ur
the river valleys and oases, often bounded by uninhabitable desert (Figure 1).
The Hexi Corridor harbors typical arid and semi-arid regions with a climate primarily influenced by the prevailing westerly winds. Long-term (1960-2017) mean precipitation ranges from 160 mm y-1 in the East to 40 mm y-1 in the West (Yang et al., 2019b). The montane snowmelt water and surface runoff from the northern portion of the Qilian Mountain feeds the grasslands and agricultural activities (Zhang et al., 2015). With terrain that appeals to both farming and nomadic civilizations, the Hexi Corridor has been at the forefront of the
Journal Pre-proof confrontation and integration of different nationalities residing in vicinity (Fang and Zhang, 2007). Severe ecological crises have proved to be primary bottlenecks for the sustainable development of the Hexi Corridor, and as such, continue to draw the attention of the Chinese nation (Feng et al., 2004; Yang et al., 2017).
2.2 Data
of
2.2.1 Climate data
ro
Temperature series data were reconstructed by combining dendrochronological data from
-p
living trees and archaeological wood. Annual mean temperature data were reconstructed based on indices of tree ring-width from the mid-eastern Tibetan Plateau for a period of approximately
re
2,485 years (Liu et al., 2009). The temperature variations over the mid-eastern Tibetan Plateau
lP
are not only representative of large parts of north-central China, but over such long time scales
na
also correspond closely with those of the entire Northern Hemisphere (Ge et al., 2013). The precipitation data used in the current study have been established from the reconstructed
Jo ur
precipitation series developed by Yang et al. (2014), who compiled data from subfossil, archaeological, and living-tree (Qilian juniper, Sabina przewalskii (Kom.)) samples from the northeastern Tibetan Plateau with an annually resolved and absolutely dated ring-width chronology spanning 3,500 years — one of the longest in the entire world. This chronology represents the changing mean annual precipitation, and is most reliable data for periods over 1,500 years ago (Yang et al., 2011). The current researchers also obtained drought frequency data from records in historical documents to compare with the reconstructed historical climate data (Li et al., 1988).
Journal Pre-proof
2.2.2 Biological Productivity In this study, tree-ring width and grain yield were the two parameters chosen to reflect temporal variation in biological productivity in the Hexi Corridor over the analyzed historical period. Tree-ring Width The growth of trees is closely related to their environment and is therefore strongly affected
of
by climate change and variability. As such, tree-ring width strongly reflects actual changes or
ro
variations in climate and environment (Dixon et al., 1994). Initially adopted to determine net
-p
productivity of forest biomass under different dynamic site conditions, tree-ring chronology
re
methods have been established as valuable in providing detailed annual resolution data (Brienen
lP
and Zuidema, 2006). The selected 2000-year tree-ring width series from the alpine region of northwest China had a resolution of 1 year. Due to the limited impact of human activities on tree
na
growth in the region, the variations in tree ring widths in the dataset reflected changes in biomass
Jo ur
and productivity, making the data series suitable for investigating the effects of climate fluctuations in the study area (Yang et al., 2011). Grain yield
The grain yield data used in the current study was derived from literature data and included the mean production of the region‘s main food crops: corn (Zea mays L.), proso millet (Panicum miliaceum L.), wheat (Triticum æstivum L.), soybeans (Glycine max (L.) Merr.), and rice (Oryza sativa L.). These per unit area yields were obtained from a comprehensive time series encompassing yield data spanning a timeframe from the western Han dynasty to the modern People‘s Republic of China (2 to 1988 Common Era (CE)) (Li, 1992). Food production originally recorded in Chinese units (jin/ha) was converted to international units (kg/ha) for the present
Journal Pre-proof analysis (Fang and Zhang, 2007).
2.2.3 Migration Migration is considered to be a second order climate impact, having its roots in processes directly affected by the climate, e.g. crop growth and agricultural yield, water supply, soil formation, and pest infestation (Meze-Hausken, 2000). For the period of study, the researchers define migration as identified long-distance population movements between large areas (regions
of
or nations), likely to have affected the overall regional or national socioeconomic and
ro
demographic status. Population migration data for the Hexi Corridor was obtained from relevant
-p
literature (Fang and Zhang, 2007; Jiang, 2008). The migratory populations mentioned in this
re
study include those impacted by natural disasters (such as drought, flood, plague, earthquake,
2.2.4 Conflicts
lP
etc.) and those caused by war and other climate factors.
na
Humans and animals often behave similarly in an environment with limited life sustaining
Jo ur
resources – group members often quarrel and kill each other until the remaining resources are sufficient to supply the survivors‘ needs (David, 1975). In the historical domain, a conflict or war is termed an ‗adaptive selection of ecological balance‘, where population growth is constrained by resource limitations. Empirical studies have confirmed that an increase in the imbalance between populations in terms of access to water and soil resources can lead to armed conflicts, especially when these scarcities lead to food shortages. In some cases, war may be the result of a series of social and ideological conflicts, such as religious differences (Zhang et al., 2005). The conflict/war variable encompasses a variety of different types of conflict (e.g., nomad-army clashes, domestic rebellions, interstate warfare and so forth). The conflicts in Hexi Corridor were dominated by nomadic invasions, whereas conflicts categorized as domestic rebellions were
Journal Pre-proof infrequent in the study area. In the current study, the number of wars in the ancient Hexi Corridor were obtained from the detailed war-time records in Chinese Military History (Wang, 1986). These works include all records of violence and conflict from 1,000 BC to 1984 CE, whether they arose over different ideologies, religions, or amongst different ethnic groups. The current researchers counted the number of war events by identifying the war beginnings and war ends. Using this system, a war
of
that continues through several years only counts as one war event.
ro
2.3 Granger Causality Analysis
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Several statistical methods (e.g., correlation analysis and Granger Causality Analysis (GCA))
re
were employed to investigate causality relationships among climate, migration and conflict
lP
parameters. Compared with conventional correlation analysis, Granger Causality Analysis (GCA) is considered to be a far more effective method for establishing a causal relationship and indicating
na
the quantitative strength of relationships among the variables considered (Granger, 1988). GCA
Jo ur
follows an auto-regressive format that accounts for time-lag between variables (Granger, 1988), and allows one to consider how variables are related to values in different phases of antecedent time. The hypothesis that probabilistic causality exists is based on two guiding principles: (i) the cause must precede the effect; and (ii) the causal series should contain unique information about the future effect values (Zhang et al., 2011). Although a significant GCA result does not guarantee that a causal relationship exists, it increases one‘s understanding of relationships between variables and improves one‘s ability to detect significant cause–effect relationships where such a relationship exists. Moreover, the results of GCA must be subjected to a ―reality check‖ wherein a plausible mechanism for a relationship is identified to ensure that the proposed relationship is causal (Feng et al., 2019).
Journal Pre-proof Given two stationary time-series Xt and Yt that have been normalized to a mean of 0 and a standard deviation of 1, we can test a null hypothesis that Yt is not a Granger-cause of Xt. The Granger two-variable causal model is given by (Zhang et al., 2011): 𝑖=𝑛
𝑖=𝑛
(1)
𝑋𝑡 = ∑ 𝑎𝑖 ∙ 𝑋𝑡−𝑖 + ∑ 𝑏𝑖 ∙ 𝑌𝑡−𝑖 + 𝜀𝑡 𝑖=1
𝑖=1
where, t represents a given point in time, t–i represents points 1 to n (i = 1, 2, …, n) before the
of
given time t, ai and bi represent regression coefficients for previous time i, and εt represents an
ro
error term.
-p
Before proceeding to the GCA, the Augmented Dickey-Fuller test was applied to test the stationarity of the time series. This was particularly important because the GCA method adopts
re
an autoregressive approach where the tested data must be stationary. As is common practice in
lP
applying GCA, a difference term (DYt) is calculated for each point in time as the sum of the
na
differences between all pairs of time t:
𝐷𝑌𝑡 = 𝜇 + 𝛿𝑌𝑡−1 + 𝛽1 𝐷𝑌𝑡−1 + 𝛽2 𝐷𝑌𝑡−2 + ⋯ + 𝛽𝑛 𝐷𝑌𝑡−𝑛 + 𝜀𝑡
(2)
Jo ur
where, µ is a regression constant, δ represents the null hypothesis, DYt–i represents the difference between the Y values for the two specified points in time, and βi represents autoregression coefficients for time t. In addition: 𝐷𝑌𝑡 = 𝑌𝑡 − 𝑌𝑡−1
(3)
In the augmented Dickey-Fuller test, the upper bound of the lag length (Lagmax) is given as: 4 𝑇 Lag max = Int [12 ∙ √ ] 100
(4)
The time lag was set in one of two ways: (i) based on theoretical and empirical knowledge of the relationships such as an instantaneous cause linkage (normally set to 1), or (ii) based on a statistical criterion. In the present study, we adopted the Akaike‘s Information Criterion (AIC) to determine the appropriate length of the time lag (Akaike, 1974; Zhang et al., 2011).
Journal Pre-proof
3 Results and Discussion 3.1 Characteristics of climate variations The temperature profile of the reconstructed data showed four main periods and a significant degree of variation. The period between 0–380 CE was characterized by decadal to centennial variability around the average. It was a period of shifts from cold to warm conditions. The prominent warming period between 380 CE and 1100 notably showed temperatures above
of
average, i.e., over the 700-year period, temperatures of the Tibetan Plateau showed a high
ro
inter-annual to multi-decadal variability within the amplified temperature signal, something not
-p
apparent in the other records (Liu et al., 2009). During this period three short cold periods
re
occurred, namely: around 470 CE, 700 CE, and 1020 CE. Meanwhile, the Medieval Warm
lP
Period from 800–1100 CE was characterized by the warmest conditions to have occurred over the last 2,000 years. A cooler stage from 1100–1800 CE with below average temperatures was
na
also evident, with several short warm stages, the Little Ice Age period between 1400–1920 CE
Jo ur
(Ge et al., 2013) and the present rapidly warming stage after 1920. The present rapid warming stage is the warmest period of the last 1,000 years. A study of the chronology displayed a statistical association with the multi-decadal and longer-term variability of reconstructed mean temperatures over the last two millennia. Interestingly, the variations in precipitation were not as evident as those seen for temperature, but did correspond with variations in temperature over the long-term. Warm periods corresponded to the wet periods, while cold periods corresponded to periods of drought. This suggests that further large-scale warming may be associated with even greater moisture supply in the region.
Journal Pre-proof
3.2 Response of climate variability to bio-productivity, migration and conflict The current researchers adopted a dual approach involving a quantitative and macro-historical method to explore the climate-agriculture and production-migration-conflict relationships over the last 2,000 years (Figure 2) in the Hexi Corridor. To more easily describe the response relationships between climate variability and the respective variables, the obviously cold and
of
warm periods were partitioned with temperature anomalies above or below ±0.2ζ℃ based on
ro
the low-pass filtered temperature series for the Qilian Mountains (Figure 2, marked with blue
-p
and red boxes, respectively). The warm period was designated as: W1 (830-1000 CE, average
re
temperature = +1.61ζ℃), while the cold phases were identified as C1 (290 to 400 CE, average
lP
temperature = -0.47℃) and C2 (1550 to 1740 CE, average temperature = -0.84℃). Within the Hexi Corridor over the last 2,000 years, fluctuations in tree ring width, grain yield, migration and
na
conflicts correspond very well with those of temperature (Figure 2).
Jo ur
The warm period corresponded to a golden age, a period of rapid development and shift from separation to unification. After the first warm phase, W1, the climate was likely the warmest in the Hexi Corridor over the last 2,000 years, with an average temperature of +1.61ζ℃. This stage coincided with the flourishing Tang and Song Dynasties. During this period, the warm and humid climate was conducive to bio-production, and there was a reduction in the number of migration events and wars relative to the cold phases. It is intriguing to note that the collapse of the Tang Dynasty around 907 CE coincided with a dramatic reduction in temperatures. This period also corresponds with the decline in the Classic Mayan civilization (900 CE); a decline said to relate to extensive and prolonged drought events (Yancheva et al., 2007). Mesoamerican droughts have been found to coincide with cold Northern Hemisphere temperatures; similar patterns have been
Journal Pre-proof confirmed by large-scale, temperature reconstructions for the mid-eastern Tibetan Plateau. Although the actual downfall of dynasties may not be directly related to a deterioration in climate, evidence suggests that these declines are an indirect effect of the cold temperatures (Zhang et al., 2008).
Linshan Yang, Qi Feng, Jan F. Adamowski, Ravinesh C. Deo, Zhenliang Yin, Xiaohu Wen, Xia Tang, Min Wu PII:
S0048-9697(20)30097-8
DOI:
https://doi.org/10.1016/j.scitotenv.2020.136587
Reference:
STOTEN 136587
To appear in:
Science of the Total Environment
Received date:
14 September 2019
Revised date:
6 January 2020
Accepted date:
6 January 2020
Please cite this article as: L. Yang, Q. Feng, J.F. Adamowski, et al., Causality of climate, food production and conflict over the last two millennia in the Hexi Corridor, China, Science of the Total Environment (2018), https://doi.org/10.1016/j.scitotenv.2020.136587
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2018 Published by Elsevier.
Journal Pre-proof
Causality of Climate, Food Production and Conflict over the Last Two Millennia in the Hexi Corridor, China Linshan Yang1, Qi Feng1*, Jan F Adamowski2, Ravinesh C. Deo 3, Zhenliang Yin1, Xiaohu Wen1, Xia Tang1, and Min Wu1 1
of
Key Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, CHINA 2 Department of Bioresource Engineering, Faculty of Agricultural & Environmental Sciences, McGill University, Québec H9X 3V9, CANADA 3 School of Sciences, Centre for Applied Climate Sciences & Centre for Sustainable Agricultural Systems, Institute for Life Sciences and the Environment, University of Southern Queensland, Springfield, QLD 4300, AUSTRALIA
-p
Abstract
ro
Corresponding to Qi Feng ([email protected])
re
The relationship between climate and human society has repeatedly been investigated to
lP
ascertain whether climate variability can trigger social crises (e.g., migration and armed conflicts). In the current study, statistical methods (e.g., correlation analysis and Granger
na
Causality Analysis) are used in a systematic analysis of the potential causality of climate
Jo ur
variability on migration and armed conflicts. Specifically, the statistical methods are applied to determine the relationships between long-term fine-grained temperature and precipitation data and contemporary social conditions, gleaned from historical documents covering the last two millennia in China‘s Hexi Corridor. Results found the region‘s reconstructed temperature to be strongly coupled with precipitation dynamics, i.e., a warming climate was associated with a greater supply of moisture, whereas a cooling period was associated with more frequent drought. A prolonged cold period tended to coincide with societal instability, such as a shift from unification towards fragmentation. In contrast, a prolonged warm period coincided with rapid development, i.e., a shift from separation to unification. The statistical significance of the causality linkages between climate variability, bio-productivity, grain yield, migration and
Journal Pre-proof conflict suggests that climate variability is not the direct causative agent of these phenomena, but that climate-induced production supplements gradually deteriorated following migration and conflicts. A conceptual causal model developed through this study describes the causative pathway of climate variability impacts on migration and conflicts in the Hexi Corridor. Applied to under current conditions, the model suggests that steady and proactive promotion of the nation‘s economic buffering capacity might best address the uncertainty brought on by a range of
of
potential future climate scenarios and their potential impacts.
ro
Keywords: Climate variability; Food production; Migration; Conflict; the Hexi Corridor
-p
1 Introduction
re
The concept that climate change and variability can trigger changes within human society is
lP
not novel. The relationship between climate variability and societal changes has been studied extensively, especially in the context of arid and semi-arid regions where environmental
na
sustainability is extremely fragile (Fang and Liu, 1992; Feng et al., 2019; Meze-Hausken, 2000;
Jo ur
Sarkodie et al., 2019). Those with fewer resources are likely to experience greater exposure to extreme weather events, particularly in developing countries with low income (Ye et al., 2012). Zhang et al. (2008, 2011a) found high resolution paleo-climatic data indicating that climate change and variability have played an important role in human migration and conflicts in the past. In ancient times, humans tended to cope with the adverse impacts of climate variability through migrations to areas with sufficient grass, food, and water (deMenocal and Stringer, 2016; Destek and Sarkodie, 2019). In some instances, when this migration led to the crossing of territorial borders, conflict and warfare ensued (Feng et al., 2019). The connection between climate change and variability and historical human migrations and conflicts has been revealed in studies covering Europe (Lee et al., 2013; Zhang et al., 2011), China (Pei et al., 2016; Ye et al., 2012)
Journal Pre-proof and other locales (Pei and Zhang, 2014). However, the question remains as to how one might systematically identify the processes that dominate a society‘s emergence, resilience and collapse, along with the complex interactions at work between these processes at multi-decadal or greater time scales. Identifying a method to this end would support plausible explanations for these shifts, and in turn, the development of effective policies and strategies to improve a society‘s resilience.
of
To this point, much of the literature investigating climate change and variability as a
ro
motivating factor for migration has considered climate-migration relations at only a very general
-p
level (Meze-Hausken, 2000). Relevant studies have focused mainly on the temporal
re
correspondence between climate and human migration; results are seldom verified with robust
lP
statistical or mathematical methods (Bekun et al., 2019). The cause-effect relationships between climate and human society are sufficiently complex and obscure that simple approaches are
na
insufficient for their analysis. For example, climate variability, specifically drought, is one of
Jo ur
many factors that promote migration (Meze-Hausken, 2000). In many cases, this climate-induced migration is linked to famine, caused by drought. However, not every drought leads to famine, and conversely, not every famine has its roots in drought. Moreover, during a famine, people may cope with scarcity through means other than migration (Sarkodie and Strezov, 2019). Therefore, it is necessary to further clarify the causal linkage between climate and human society by exploring how climate change and variability trigger human social processes. The wide geographic variation in China‘s climate patterns means that there are different impact pathways of climate-related influences on Chinese society. Human migration in different agro-ecological zones is partially a manifestation of changes in climate (Pei et al., 2013). However, large-scale studies performed in China, Europe and North Hemisphere, do not appear
Journal Pre-proof to capture the internal connections and specific factors of influence. Some studies have addressed patterns of migration in different sub-regions; however, most of these were qualitative studies that focused on an individual event (Zheng et al., 2014). Although some studies have investigated human migration in specific regions of China, their temporal span is limited to a few centuries (Pei et al., 2015b); studies on the response of a specific region‘s human social dynamics at the multi-century scale and beyond have not yet been carried out.
of
The current researchers selected northwestern China‘s Hexi corridor as the study area, as
ro
similar research has not yet be undertaken in the region. Susceptible to environmental change,
-p
the Hexi corridor is an ecologically fragile, endorheic basin, subject to an inland arid climatic
re
zone (Feng et al., 2015; Feng et al., 2019). The region‘s grassland and agricultural areas draw
lP
upon surface runoff from snowmelt in the northern portion of the Qilian Mountains (Yang et al., 2019a; Yin et al., 2016). The region has been alternately claimed by the southern members of the
na
northern nomadic minorities and the Han people. Conflicts between pastoralists and
Jo ur
agriculturalists have reportedly occurred on a regular basis, making the region one of the scenes for major battles between the armies of ancient China and nomadic minorities (Feng et al., 2019). These violent interactions influenced the characteristics of the populations that migrated due to famine, social unrest, and war (Zhang et al., 2005). The prime focus of the current study was to identify the processes that dominate a society‘s emergence, resilience and collapse, and the complex interactions among these processes in the Hexi Corridor. More specifically this study was undertaken to: (i) investigate the causality of climate variability and human society in the Hexi Corridor, (ii) understand how migration and conflict events are driven by a shift in climate, and (iii) present a framework for social resilience in the face of future climate change. The results presented herein can provide a reference for
Journal Pre-proof decision-makers involved in the successful adaption of human societies to climate change conditions.
2 Materials and method 2.1 Study area Located between 37°17‘–42°48‘ N and 93°23‘–104°12‘E, the Hexi Corridor is a string of
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oases along the northern edge of the Tibetan Plateau in China‘s Gansu province (Yang et al.,
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2011). The corridor is situated in a long, narrow passage stretching for over 1000 km from east
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to west and 100–200 km from south to north (Yang et al., 2011). Mountains and deserts limited caravan traffic to a narrow trackway; this meant that relatively small fortifications could control
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passing traffic in the region. A part of the renowned Ancient Silk Road, in historical times the
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Hexi Corridor allowed traders and the military to travel from northern China to Xinjiang and
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Central Asia (Feng et al., 2019). The geography of the Silk Roads represents a complex interaction between the physical and climatic zones of mountain, the steppes or grasslands, and
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the river valleys and oases, often bounded by uninhabitable desert (Figure 1).
The Hexi Corridor harbors typical arid and semi-arid regions with a climate primarily influenced by the prevailing westerly winds. Long-term (1960-2017) mean precipitation ranges from 160 mm y-1 in the East to 40 mm y-1 in the West (Yang et al., 2019b). The montane snowmelt water and surface runoff from the northern portion of the Qilian Mountain feeds the grasslands and agricultural activities (Zhang et al., 2015). With terrain that appeals to both farming and nomadic civilizations, the Hexi Corridor has been at the forefront of the
Journal Pre-proof confrontation and integration of different nationalities residing in vicinity (Fang and Zhang, 2007). Severe ecological crises have proved to be primary bottlenecks for the sustainable development of the Hexi Corridor, and as such, continue to draw the attention of the Chinese nation (Feng et al., 2004; Yang et al., 2017).
2.2 Data
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2.2.1 Climate data
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Temperature series data were reconstructed by combining dendrochronological data from
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living trees and archaeological wood. Annual mean temperature data were reconstructed based on indices of tree ring-width from the mid-eastern Tibetan Plateau for a period of approximately
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2,485 years (Liu et al., 2009). The temperature variations over the mid-eastern Tibetan Plateau
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are not only representative of large parts of north-central China, but over such long time scales
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also correspond closely with those of the entire Northern Hemisphere (Ge et al., 2013). The precipitation data used in the current study have been established from the reconstructed
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precipitation series developed by Yang et al. (2014), who compiled data from subfossil, archaeological, and living-tree (Qilian juniper, Sabina przewalskii (Kom.)) samples from the northeastern Tibetan Plateau with an annually resolved and absolutely dated ring-width chronology spanning 3,500 years — one of the longest in the entire world. This chronology represents the changing mean annual precipitation, and is most reliable data for periods over 1,500 years ago (Yang et al., 2011). The current researchers also obtained drought frequency data from records in historical documents to compare with the reconstructed historical climate data (Li et al., 1988).
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2.2.2 Biological Productivity In this study, tree-ring width and grain yield were the two parameters chosen to reflect temporal variation in biological productivity in the Hexi Corridor over the analyzed historical period. Tree-ring Width The growth of trees is closely related to their environment and is therefore strongly affected
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by climate change and variability. As such, tree-ring width strongly reflects actual changes or
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variations in climate and environment (Dixon et al., 1994). Initially adopted to determine net
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productivity of forest biomass under different dynamic site conditions, tree-ring chronology
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methods have been established as valuable in providing detailed annual resolution data (Brienen
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and Zuidema, 2006). The selected 2000-year tree-ring width series from the alpine region of northwest China had a resolution of 1 year. Due to the limited impact of human activities on tree
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growth in the region, the variations in tree ring widths in the dataset reflected changes in biomass
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and productivity, making the data series suitable for investigating the effects of climate fluctuations in the study area (Yang et al., 2011). Grain yield
The grain yield data used in the current study was derived from literature data and included the mean production of the region‘s main food crops: corn (Zea mays L.), proso millet (Panicum miliaceum L.), wheat (Triticum æstivum L.), soybeans (Glycine max (L.) Merr.), and rice (Oryza sativa L.). These per unit area yields were obtained from a comprehensive time series encompassing yield data spanning a timeframe from the western Han dynasty to the modern People‘s Republic of China (2 to 1988 Common Era (CE)) (Li, 1992). Food production originally recorded in Chinese units (jin/ha) was converted to international units (kg/ha) for the present
Journal Pre-proof analysis (Fang and Zhang, 2007).
2.2.3 Migration Migration is considered to be a second order climate impact, having its roots in processes directly affected by the climate, e.g. crop growth and agricultural yield, water supply, soil formation, and pest infestation (Meze-Hausken, 2000). For the period of study, the researchers define migration as identified long-distance population movements between large areas (regions
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or nations), likely to have affected the overall regional or national socioeconomic and
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demographic status. Population migration data for the Hexi Corridor was obtained from relevant
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literature (Fang and Zhang, 2007; Jiang, 2008). The migratory populations mentioned in this
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study include those impacted by natural disasters (such as drought, flood, plague, earthquake,
2.2.4 Conflicts
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etc.) and those caused by war and other climate factors.
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Humans and animals often behave similarly in an environment with limited life sustaining
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resources – group members often quarrel and kill each other until the remaining resources are sufficient to supply the survivors‘ needs (David, 1975). In the historical domain, a conflict or war is termed an ‗adaptive selection of ecological balance‘, where population growth is constrained by resource limitations. Empirical studies have confirmed that an increase in the imbalance between populations in terms of access to water and soil resources can lead to armed conflicts, especially when these scarcities lead to food shortages. In some cases, war may be the result of a series of social and ideological conflicts, such as religious differences (Zhang et al., 2005). The conflict/war variable encompasses a variety of different types of conflict (e.g., nomad-army clashes, domestic rebellions, interstate warfare and so forth). The conflicts in Hexi Corridor were dominated by nomadic invasions, whereas conflicts categorized as domestic rebellions were
Journal Pre-proof infrequent in the study area. In the current study, the number of wars in the ancient Hexi Corridor were obtained from the detailed war-time records in Chinese Military History (Wang, 1986). These works include all records of violence and conflict from 1,000 BC to 1984 CE, whether they arose over different ideologies, religions, or amongst different ethnic groups. The current researchers counted the number of war events by identifying the war beginnings and war ends. Using this system, a war
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that continues through several years only counts as one war event.
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2.3 Granger Causality Analysis
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Several statistical methods (e.g., correlation analysis and Granger Causality Analysis (GCA))
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were employed to investigate causality relationships among climate, migration and conflict
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parameters. Compared with conventional correlation analysis, Granger Causality Analysis (GCA) is considered to be a far more effective method for establishing a causal relationship and indicating
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the quantitative strength of relationships among the variables considered (Granger, 1988). GCA
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follows an auto-regressive format that accounts for time-lag between variables (Granger, 1988), and allows one to consider how variables are related to values in different phases of antecedent time. The hypothesis that probabilistic causality exists is based on two guiding principles: (i) the cause must precede the effect; and (ii) the causal series should contain unique information about the future effect values (Zhang et al., 2011). Although a significant GCA result does not guarantee that a causal relationship exists, it increases one‘s understanding of relationships between variables and improves one‘s ability to detect significant cause–effect relationships where such a relationship exists. Moreover, the results of GCA must be subjected to a ―reality check‖ wherein a plausible mechanism for a relationship is identified to ensure that the proposed relationship is causal (Feng et al., 2019).
Journal Pre-proof Given two stationary time-series Xt and Yt that have been normalized to a mean of 0 and a standard deviation of 1, we can test a null hypothesis that Yt is not a Granger-cause of Xt. The Granger two-variable causal model is given by (Zhang et al., 2011): 𝑖=𝑛
𝑖=𝑛
(1)
𝑋𝑡 = ∑ 𝑎𝑖 ∙ 𝑋𝑡−𝑖 + ∑ 𝑏𝑖 ∙ 𝑌𝑡−𝑖 + 𝜀𝑡 𝑖=1
𝑖=1
where, t represents a given point in time, t–i represents points 1 to n (i = 1, 2, …, n) before the
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given time t, ai and bi represent regression coefficients for previous time i, and εt represents an
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error term.
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Before proceeding to the GCA, the Augmented Dickey-Fuller test was applied to test the stationarity of the time series. This was particularly important because the GCA method adopts
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an autoregressive approach where the tested data must be stationary. As is common practice in
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applying GCA, a difference term (DYt) is calculated for each point in time as the sum of the
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differences between all pairs of time t:
𝐷𝑌𝑡 = 𝜇 + 𝛿𝑌𝑡−1 + 𝛽1 𝐷𝑌𝑡−1 + 𝛽2 𝐷𝑌𝑡−2 + ⋯ + 𝛽𝑛 𝐷𝑌𝑡−𝑛 + 𝜀𝑡
(2)
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where, µ is a regression constant, δ represents the null hypothesis, DYt–i represents the difference between the Y values for the two specified points in time, and βi represents autoregression coefficients for time t. In addition: 𝐷𝑌𝑡 = 𝑌𝑡 − 𝑌𝑡−1
(3)
In the augmented Dickey-Fuller test, the upper bound of the lag length (Lagmax) is given as: 4 𝑇 Lag max = Int [12 ∙ √ ] 100
(4)
The time lag was set in one of two ways: (i) based on theoretical and empirical knowledge of the relationships such as an instantaneous cause linkage (normally set to 1), or (ii) based on a statistical criterion. In the present study, we adopted the Akaike‘s Information Criterion (AIC) to determine the appropriate length of the time lag (Akaike, 1974; Zhang et al., 2011).
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3 Results and Discussion 3.1 Characteristics of climate variations The temperature profile of the reconstructed data showed four main periods and a significant degree of variation. The period between 0–380 CE was characterized by decadal to centennial variability around the average. It was a period of shifts from cold to warm conditions. The prominent warming period between 380 CE and 1100 notably showed temperatures above
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average, i.e., over the 700-year period, temperatures of the Tibetan Plateau showed a high
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inter-annual to multi-decadal variability within the amplified temperature signal, something not
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apparent in the other records (Liu et al., 2009). During this period three short cold periods
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occurred, namely: around 470 CE, 700 CE, and 1020 CE. Meanwhile, the Medieval Warm
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Period from 800–1100 CE was characterized by the warmest conditions to have occurred over the last 2,000 years. A cooler stage from 1100–1800 CE with below average temperatures was
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also evident, with several short warm stages, the Little Ice Age period between 1400–1920 CE
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(Ge et al., 2013) and the present rapidly warming stage after 1920. The present rapid warming stage is the warmest period of the last 1,000 years. A study of the chronology displayed a statistical association with the multi-decadal and longer-term variability of reconstructed mean temperatures over the last two millennia. Interestingly, the variations in precipitation were not as evident as those seen for temperature, but did correspond with variations in temperature over the long-term. Warm periods corresponded to the wet periods, while cold periods corresponded to periods of drought. This suggests that further large-scale warming may be associated with even greater moisture supply in the region.
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3.2 Response of climate variability to bio-productivity, migration and conflict The current researchers adopted a dual approach involving a quantitative and macro-historical method to explore the climate-agriculture and production-migration-conflict relationships over the last 2,000 years (Figure 2) in the Hexi Corridor. To more easily describe the response relationships between climate variability and the respective variables, the obviously cold and
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warm periods were partitioned with temperature anomalies above or below ±0.2ζ℃ based on
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the low-pass filtered temperature series for the Qilian Mountains (Figure 2, marked with blue
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and red boxes, respectively). The warm period was designated as: W1 (830-1000 CE, average
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temperature = +1.61ζ℃), while the cold phases were identified as C1 (290 to 400 CE, average
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temperature = -0.47℃) and C2 (1550 to 1740 CE, average temperature = -0.84℃). Within the Hexi Corridor over the last 2,000 years, fluctuations in tree ring width, grain yield, migration and
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conflicts correspond very well with those of temperature (Figure 2).
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The warm period corresponded to a golden age, a period of rapid development and shift from separation to unification. After the first warm phase, W1, the climate was likely the warmest in the Hexi Corridor over the last 2,000 years, with an average temperature of +1.61ζ℃. This stage coincided with the flourishing Tang and Song Dynasties. During this period, the warm and humid climate was conducive to bio-production, and there was a reduction in the number of migration events and wars relative to the cold phases. It is intriguing to note that the collapse of the Tang Dynasty around 907 CE coincided with a dramatic reduction in temperatures. This period also corresponds with the decline in the Classic Mayan civilization (900 CE); a decline said to relate to extensive and prolonged drought events (Yancheva et al., 2007). Mesoamerican droughts have been found to coincide with cold Northern Hemisphere temperatures; similar patterns have been
Journal Pre-proof confirmed by large-scale, temperature reconstructions for the mid-eastern Tibetan Plateau. Although the actual downfall of dynasties may not be directly related to a deterioration in climate, evidence suggests that these declines are an indirect effect of the cold temperatures (Zhang et al., 2008).
The cold periods generally coincided with social instability, the downfall of dynasties and a
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process of separation. For instance, during the long-term C1 cold phase (290 to 400 CE, average
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temperature = -0.47℃, the ―Five Hu‖ period of the Eastern Jin dynasty), famine in Mongolia led, on five occasions, to migrations of large populations of nomadic Mongols, leading, in turn, to a
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period of disorder. These migrations became invasions, leading to warfare and eventual conquest
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of north China by the nomads. Colder and longer than C1, the second cold phase (C2; 1550 to
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1740 CE, average temperature = -0.84℃), dubbed the ―Little Ice Age‖ in Europe, struck a huge blow to China's agriculture and became a prelude to war (e.g. the conflict in the middle of Ming
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dynasty, 1500 CE). Zheng et al. (2014) suggest that the northern minorities invaded frequently
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during this period, especially during the Tatar era. The period from 1640-1700 CE was the coldest of the Little Ice Age; this period coincides with the Qing Army entering the Shanhai Pass to set up their ruling regime. During this same period famine occurred frequently, possibly contributing directly to the peasant rebellions of the late Ming dynasty (Zheng et al., 2014). The situation improved significantly with the introduction of more cold-resistant crops (such as potato, corn), to supplement the less hardy cereal crops, such as wheat and rice. The adverse effects of the short-term cooling episode in W1 are reflected by fluctuations in the study variables (such as tree ring width, grain yield, migration and conflicts) for annual and decadal units. The intervals of cold temperature coincide with the decline of bio-productivity and grain yield, and an increase in the number of migrations and conflicts within this region, while
Journal Pre-proof the intervals of warm temperature coincide with an upswing of bio-productivity and grain yield, and a decrease in migration and conflicts (Figure 2).
3.3 Relationship between climate variability and human society Cross correlations performed to verify the statistical relationships among the climate variability, bio-productivity and social activities (Table 1, Figure 3), revealed highly significant (r > 0.75) cross-correlations between temperature series, grain yield and tree ring width.
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However, the precipitation series showed a weaker cross-correlation (r < 0.31) with tree ring
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width and grain yield data.
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process of separation. For instance, during the long-term C1 cold phase (290 to 400 CE, average
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temperature = -0.47℃, the ―Five Hu‖ period of the Eastern Jin dynasty), famine in Mongolia led, on five occasions, to migrations of large populations of nomadic Mongols, leading, in turn, to a
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period of disorder. These migrations became invasions, leading to warfare and eventual conquest
re
of north China by the nomads. Colder and longer than C1, the second cold phase (C2; 1550 to
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1740 CE, average temperature = -0.84℃), dubbed the ―Little Ice Age‖ in Europe, struck a huge blow to China's agriculture and became a prelude to war (e.g. the conflict in the middle of Ming
na
dynasty, 1500 CE). Zheng et al. (2014) suggest that the northern minorities invaded frequently
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during this period, especially during the Tatar era. The period from 1640-1700 CE was the coldest of the Little Ice Age; this period coincides with the Qing Army entering the Shanhai Pass to set up their ruling regime. During this same period famine occurred frequently, possibly contributing directly to the peasant rebellions of the late Ming dynasty (Zheng et al., 2014). The situation improved significantly with the introduction of more cold-resistant crops (such as potato, corn), to supplement the less hardy cereal crops, such as wheat and rice. The adverse effects of the short-term cooling episode in W1 are reflected by fluctuations in the study variables (such as tree ring width, grain yield, migration and conflicts) for annual and decadal units. The intervals of cold temperature coincide with the decline of bio-productivity and grain yield, and an increase in the number of migrations and conflicts within this region, while
Journal Pre-proof the intervals of warm temperature coincide with an upswing of bio-productivity and grain yield, and a decrease in migration and conflicts (Figure 2).
3.3 Relationship between climate variability and human society Cross correlations performed to verify the statistical relationships among the climate variability, bio-productivity and social activities (Table 1, Figure 3), revealed highly significant (r > 0.75) cross-correlations between temperature series, grain yield and tree ring width.
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However, the precipitation series showed a weaker cross-correlation (r < 0.31) with tree ring
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width and grain yield data.
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