Recent studies have shown strong temporal correlations between past climate changes and societal crises. However, the specific causal mechanisms underlying this relation have not been addressed. We explored quantitative responses of 14 fine-grained agro-ecological, socioeconomic, and demographic variables to climate fluctuations from A.D. 1500-1800 in Europe. Results show that cooling from A.D. 1560-1660 caused successive agro-ecological, socioeconomic, and demographic catastrophes, leading to the General Crisis of the Seventeenth Century. We identified a set of causal linkages between climate change and human crisis. Using temperature data and climate-driven economic variables, we simulated the alternation of defined "golden" and "dark" ages in Europe and the Northern Hemisphere during the past millennium. Our findings indicate that climate change was the ultimate cause, and climate-driven economic downturn was the direct cause, of large-scale human crises in preindustrial Europe and the Northern Hemisphere.climate-driven economy | Granger Causality Analysis | grain price D ebate about the relation between climate and human crisis has lasted over a century. With recent advances in paleotemperature reconstruction, scholars note that massive social disturbance, societal collapse, and population collapse often coincided with great climate change in America, the Middle East, China, and many other countries in preindustrial times (1-5). Although most of these scientists believe that climate change could cause human catastrophe, their arguments are backed simply by qualitative scrutiny of narrow historic examples. More recent breakthroughs came from research adopting quantitative approaches to all known cases of social crisis. These studies show that, in recent history, climate change was responsible for the outbreak of war, dynastic transition, and population decline in China, Europe, and around the world because of climate-induced

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BackgroundThe current World Health Organization (WHO) classification of nasopharyngeal carcinoma (NPC) conveys little prognostic information. This study aimed to propose an NPC histopathologic classification that can potentially be used to predict prognosis and treatment response.MethodsWe initially developed a histopathologic classification based on the morphologic traits and cell differentiation of tumors of 2716 NPC patients who were identified at Sun Yat-sen University Cancer Center (SYSUCC) (training cohort). Then, the proposed classification was applied to 1702 patients (retrospective validation cohort) from hospitals outside SYSUCC and 1613 patients (prospective validation cohort) from SYSUCC. The efficacy of radiochemotherapy and radiotherapy modalities was compared between the proposed subtypes. We used Cox proportional hazards models to estimate hazard ratios (HRs) with 95% confidence intervals (CI) for overall survival (OS).ResultsThe 5-year OS rates for all NPC patients who were diagnosed with epithelial carcinoma (EC; 3708 patients), mixed sarcomatoid-epithelial carcinoma (MSEC; 1247 patients), sarcomatoid carcinoma (SC; 823 patients), and squamous cell carcinoma (SCC; 253 patients) were 79.4%, 70.5%, 59.6%, and 42.6%, respectively (P < 0.001). In multivariate models, patients with MSEC had a shorter OS than patients with EC (HR = 1.44, 95% CI = 1.27–1.62), SC (HR = 2.00, 95% CI = 1.76–2.28), or SCC (HR = 4.23, 95% CI = 3.34–5.38). Radiochemotherapy significantly improved survival compared with radiotherapy alone for patients with EC (HR = 0.67, 95% CI = 0.56–0.80), MSEC (HR = 0.58, 95% CI = 0.49–0.75), and possibly for those with SCC (HR = 0.63; 95% CI = 0.40–0.98), but not for patients with SC (HR = 0.97, 95% CI = 0.74–1.28).ConclusionsThe proposed classification offers more information for the prediction of NPC prognosis compared with the WHO classification and might be a valuable tool to guide treatment decisions for subtypes that are associated with a poor prognosis.

Climate change has been proven to be the ultimate cause of social crisis in pre-industrial Europe at a large scale. However, detailed analyses on climate change and macro-economic cycles in the pre-industrial era remain lacking, especially within different temporal scales. Therefore, fine-grained, paleo-climate, and economic data were employed with statistical methods to quantitatively assess the relations between climate change and agrarian economy in Europe during AD 1500 to 1800. In the study, the Butterworth filter was adopted to filter the data series into a long-term trend (low-frequency) and short-term fluctuations (high-frequency). Granger Causality Analysis was conducted to scrutinize the associations between climate change and macro-economic cycle at different frequency bands. Based on quantitative results, climate change can only show significant effects on the macro-economic cycle within the long-term. In terms of the short-term effects, society can relieve the influences from climate variations by social adaptation methods and self-adjustment mechanism. On a large spatial scale, temperature holds higher importance for the European agrarian economy than precipitation. By examining the supply-demand mechanism in the grain market, population during the study period acted as the producer in the long term, whereas as the consumer in the short term. These findings merely reflect the general interactions between climate change and macro-economic cycles at the large spatial region with a long-term study period. The findings neither illustrate individual incidents that can temporarily distort the agrarian economy nor explain some specific cases. In the study, the scale thinking in the analysis is raised as an essential methodological issue for the first time to interpret the associations between climatic impact and macro-economy in the past agrarian society within different temporal scales.

ABSTRACT. We investigated the relationship between a 2000-year history of nomadic migration and climate change in historical China. By using updated data and statistical methods, the study solved several unanswered questions from past research about the relationship between climate change and the nomadic migration, especially over the long term and on a large spatial scale. The study used correlation analysis, multiple regression analysis, and Granger causality analysis to quantitatively verify the following causal pathway: climate change → nomadic migration → conflicts between pastoralists and agriculturalists. In the long term, precipitation was a statistically more influential factor on nomadic migration than temperature in historical China. How climate change affects the migration of nomadic minorities in the long term is theoretically explained based on the Push-Pull model as well as statistical evidence.

Aim The long-term cyclical patterns of China's geopolitical shifts are of great interest to scholars and the public, but to date there has been no satisfactory explanation for the alternating occupancy patterns of the country's pastoral and agrarian polities. We fill this gap by differentiating the agroecological settings of these polities over time and quantitatively analysing the relationships between climate change and historical geopolitical variations.Location China.Methods Our dataset comprised 38 palaeohydroclimate reconstructions, the historical boundaries of China's empire and the changes in its size, and 1028 wars and 2737 battle locations over the past 2300 years. China-wide precipitation during the period was reconstructed using the 'weighted composite plus scale' method. Timeseries analyses were performed to identify the strength of the associations between climate change and the geopolitical variables. Granger causality analysis and wavelet analysis were performed to verify the hypothesized causal links. Wavelet analysis was also used to identify the possible interactions (i.e. frequencies, significance, consistency and synchrony) between the signal components of the climatic and geopolitical variables at different temporal scales. ResultsChina's mean precipitation fell into three multicentennial cycles. The geopolitical variables corresponded to those cycles in the imperial era. The spatialtemporal frequencies of the boundaries and size of the agriculturalist empires and its frontiers with pastoralist empires were regulated by the long-term (lowfrequency) precipitation fluctuations at the multicentennial scale. Wars of aggression were an important explanatory factor driving the land-occupancy patterns of the two ecoempires under climate change, and caused most of the territorial shifts. Short-term (high-frequency) geopolitical changes were not associated with climate change.Main conclusions Precipitation-induced ecological change was an important factor governing the macrogeopolitical cycles in imperial China. Long-term territorial expansion favoured the polity (agriculturalist or pastoralist) that was better adapted to the changing ecological conditions in the country's heartland.

Only a small number of quantitative studies have investigated the short-and longterm impacts of climate variations on society during Europe's pre-industrial era. Accordingly, there is a lack of research clearly comparing the consequences of climate variation (short-term) and climate change (long-term). This study focuses on the close relationship between climate variations and the dynamics of the agrarian economy in Europe during the period of 1500 to 1800 AD. ARX modeling was applied to analyze the relationship between climate and past agrarian economies, on large spatial and long temporal scales. Both short-and long-term findings are provided, based on statistical analysis, as well as the empirical study of the 17th century economic crisis as a case analysis. The negative climatic variations in the short-term caused grain prices to increase. Grain prices were affected for up to 25 yr by a period of climatic variation due to the price stickiness. The immediate and long-term effects of climate variations over the study period can add up to significantly influence agrarian economies. Climate change occurs when climate variations last for more than 30 yr. The accumulated effect of climate change on the agrarian economy ultimately resulted in an economic crisis in pre-industrial Europe.

Our understanding on the spatial-temporal patterns of climatic variability over the last few millennia in the East Asian monsoon-dominated northern China (NC), and its role at a macro-scale in affecting the prosperity and depression of Chinese dynasties is limited. Quantitative high-resolution, regionally-synthesized palaeoclimatic reconstructions as well as simulations, and numerical analyses of their relationships with various fine-scale, numerical agro-ecological, social-economic, and geo-political historical records during the period of China's history, are presented here for NC. We utilize pollen data together with climate modeling to reconstruct and simulate decadal-to centennial-scale variations in precipitation or temperature for NC during the last 2200 years (-200-2000 AD). We find an overall cyclic-pattern (wet/warm or dry/cold) in the precipitation and temperature anomalies on centennial-to millennial-scale that can be likely considered as a representative for the entire NC by comparison with other related climatic records. We suggest that solar activity may play a key role in driving the climatic fluctuations in NC during the last 22 centuries, with its quasi ~100, 50, 23, or 22-year periodicity clearly identified in our climatic reconstructions. We employ variation partitioning and redundancy analysis to quantify the independent effects of climatic factors on accounting for the total variation of 17 fine-grained numerical Chinese historical records. We quantitatively illustrate that precipitation (67.4 %) may 3 have been more important than temperature (32.5 %) in causing the overall agro-ecological and macro-geopolitical shifts in imperial China with NC as the central ruling region and an agricultural heartland over the last 2200 years.