The causality analysis of climate change and large-scale human crisis

Climate change drove the route shift of the ancient Silk Road in two distinct ways

Although climate change has convincingly been linked to the evolution of human civilization on different temporal scales, its role in influencing the spatial patterns of ancient civilizations has rarely been investigated. The northward shift of the ancient Silk Road (SR) route from the Tarim Basin (TB) to the Junggar Basin during ∼420-850 CE provides the opportunity to investigate the relationship between climate change and the spatial evolution of human societies. Here, we use a new high-resolution chironomid-based temperature reconstruction from arid China, combined with hydroclimatic and historical datasets, to assess the possible effects of climate fluctuations on the shift of the ancient SR route. We found that a cooling/drying climate in the TB triggered the SR route shift during ∼420-600 CE. However, a warming/wetting climate during ∼600-850 CE did not inhibit this shift, but instead promoted it, because of the favorable climate-induced geopolitical conflicts between the Tubo Kingdom and the Tang Dynasty in the TB. Our findings reveal two distinct ways in which climate change drove the spatial evolution of human civilization, and they demonstrate the flexibility of societal responses to climate change.

Severity of environmental degradation and the impact on quality of life in Africa

Considering the mounting impacts of environmental degradation on the global ecosystem, this study offers an empirical contribution to the debate on whether there exists a significant nexus between environmental degradation and quality of life in Africa. Towards this end, we employ several econometric techniques to account for cross-sectional dependence, causality, and also present results based on IV-Lewbel 2SLS regression. Using a sample of African countries, the results indicate cross-sectional dependence due to spill-over effects from common factors in Africa, while the panel cointegration test affirms that environmental degradation have long-term consequences for quality of life only in sub-Saharan African region. Moreover, our results reveal a unidirectional causality between environmental degradation variables and quality of life at both the continent and sub-Saharan African region levels while a bi-directional causality between these variables are revealed for North Africa. On this evidence, our conjecture is that increased mineral extraction, greenhouse gas emissions, and deforestation, amongst other factors, may be driving this result. Hence, improvement in environmental quality in the continent would have an increasingly beneficial effects on the well-being and survival of the populace. The varied impacts across regions also suggest that policy initiatives toward mitigating the effects of environmental degradation should consider regional dynamics of the continent.

Towards understanding human-environment feedback loops: the Atacama Desert case

The overall trajectory for the human-environment interaction has been punctuated by demographic boom-and-bust cycles, phases of growth/overshooting as well as of expansion/contraction in productivity. Although this pattern has been explained in terms of an interplay between population growth, social upscaling, ecosystem engineering and climate variability, the evoked demographic-resource-complexity mechanisms have not been empirically tested. By integrating proxy data for population sizes, palaeoclimate and internal societal factors into empirical modelling approaches from the population dynamic theory, we evaluated how endogenous (population sizes, warfare and social upscaling) and exogenous (climate) variables module the dynamic in past agrarian societies. We focused on the inland Atacama Desert, where populations developed agriculture activities by engineering arid and semi-arid landscapes during the last 2000 years. Our modelling approach indicates that these populations experienced a boom-and-bust dynamic over the last millennia, which was coupled to structure feedback between population sizes, hydroclimate, social upscaling, warfare and ecosystem engineering. Thus, the human-environment loop appears closely linked with cooperation, competition, limiting resources and the ability of problem-solving. This article is part of the theme issue 'Evolution and sustainability: gathering the strands for an Anthropocene synthesis'.

Exploring the effects of climate change and government stability on internal conflicts: evidence from selected sub-Saharan African countries

Climate change has been linked to water scarcity, land degradation, and food insecurity, exacerbating existing tensions and creating new conflicts in countries with weak political institutions. Despite the critical need for effective conflict management and climate adaptation measures, prior studies failed to emphasize the role climate change plays in civil clashes in conflict-affected countries. In this research, we undertake a comprehensive investigation of the effects of climate change and government stability on internal conflicts in 14 selected SSA nations between 1996 and 2016. The study embraces contemporary heterogeneous panel techniques to address heterogeneity and cross-sectional dependence issues that usually appear in panel data estimates. We employed second-generation unit root tests, such as CADF and CIPS, to determine the order of integration of the variables. In addition, Pedroni and Westerlund cointegration tests confirmed the long-run relationship among the variables. Although temperatures were insignificant, the long-run results of the pooled mean group (PMG) approach suggested that civil conflicts decline when precipitation increases. In addition, the outcomes indicate that environmental degradation and population growth are long-run aggravators of social unrest. The short-run results suggest that rising temperatures exacerbate civil conflicts in the selected SSA countries. However, the study found that government stability lessens internal conflicts in the short run, but not in the long run. The DOLS technique validated the long-run outcomes of the PMG technique. Based on the findings of the study, conflict-prone SSA countries should integrate climate change adaptation and conflict prevention strategies, implement sustainable water resource management practices, and endorse climate-related conflict resolution.

1000 years of population, warfare, and climate change in pre-Columbian societies of the Central Andes

Different Andean societies underwent processes of expansion and collapse during propitious or adverse climate conditions, resource boost or depletion along with population variations. Previous studies have emphasized that demographic collapses of polities in the Central Andes Area were triggered by warfare and the negative impacts of fluctuating climate (droughts) on crop productivity. Nevertheless, the interactions between climatic variability, demography and warfare have been less thoroughly evaluated. We develop population dynamic models to test feedback relationships between population growth, climate change and warfare in the Central Andes, where considerable regional hydroclimate variations have occurred over a millennium. Through population models, we found out that the rise and demise of social polities in the northern coast of the Central Andes appear to be a consequence of climate change. In contrast, for the highlands of Peru and the Titicaca basin, population models suggest that warfare intensity has a negative effect on population growth rates.

Usefulness and limitations of convergent cross sorting and continuity scaling methods for their application in simulated and real-world time series

Causality detection methods are valuable tools for detecting causal links in complex systems. The efficiency of continuity scaling (CS) and the convergent cross sorting (CSS) methods to detect causality was analysed. Usefulness and limitations of both methods in their application to simulated and real-world time series was explored under different scenarios. We find that CS is more robust and efficient than the CSS method for all simulated systems, even when increasing noise levels were considered. Both methods were not able to infer causality when time series with a marked difference in their main frequencies were analysed. Minimum time-series length required for the detection of a causal link depends on intrinsic system dynamics and on the method selected to detect it. Using simulated time series, only the CS method was capable to detect bidirectional causality. Causality detection, using the CS method, should at least include: (i) causality strength convergence analysis, (ii) statistical tests of significance, (iii) time-series standardization, and (iv) causality strength ratios as a strength indicator of relative causality between systems. Causality cannot be detected by either method in simulated time series that exhibit generalized synchronization.

Climate change fostered rise and fall of the Tibetan Empire during 600-800 AD

During the 7-9th century, the Tibetan Empire constituted a superpower between the Tang Empire and Abbasid Caliphate: one that played significant roles in geopolitics in Asia during the Early Medieval Period. The factors which led to the rise and rapid decline of this powerful Empire, the only united historical regime on the Tibetan Plateau (TP), remain unclear. Sub-annual scale precipitation and decadal-scale temperature records of the central TP are presented, indicating that the height of this Empire coincided with a two-century long interval of uncharacteristically warm and humid climate. The ameliorated climate enabled the expansion of arable land and increased agricultural production. The close relationship between the precipitation records and historical events implied that the Empire implemented flexible strategies to tackle the effects of climate changes. This has implications for agricultural production in alpine regions including the TP, in the context of current global warming.

The ecosyndemic framework of the global environmental change and the COVID-19 pandemic

The ecosyndemic theory combines the concept of 'synergy' with 'epidemic' and the term "eco" implies the role of the environmental changes. Each of the conditions enhances the negative impacts of the other in an additive way making our society more vulnerable and heightening individual risk factors. In this study, we analyze the mutually reinforcing links between the environment and health from the complexity angle of the ecosyndemic theory and propose the characterization of the COVID-19 pandemic as ecosyndemic. We use the term 'ecosyndemic' because the global environmental change contributes to local-scale, regional-scale and global-scale alterations of the Earth's systems. These changes have their root causes in the way that people interact with the physical, chemical, and biotic factors of the environment. These interactions disturb nature and the consequences have feedbacks in every living organism.

From calcium imaging to graph topology

Systems neuroscience is facing an ever-growing mountain of data. Recent advances in protein engineering and microscopy have together led to a paradigm shift in neuroscience; using fluorescence, we can now image the activity of every neuron through the whole brain of behaving animals. Even in larger organisms, the number of neurons that we can record simultaneously is increasing exponentially with time. This increase in the dimensionality of the data is being met with an explosion of computational and mathematical methods, each using disparate terminology, distinct approaches, and diverse mathematical concepts. Here we collect, organize, and explain multiple data analysis techniques that have been, or could be, applied to whole-brain imaging, using larval zebrafish as an example model. We begin with methods such as linear regression that are designed to detect relations between two variables. Next, we progress through network science and applied topological methods, which focus on the patterns of relations among many variables. Finally, we highlight the potential of generative models that could provide testable hypotheses on wiring rules and network progression through time, or disease progression. While we use examples of imaging from larval zebrafish, these approaches are suitable for any population-scale neural network modeling, and indeed, to applications beyond systems neuroscience. Computational approaches from network science and applied topology are not limited to larval zebrafish, or even to systems neuroscience, and we therefore conclude with a discussion of how such methods can be applied to diverse problems across the biological sciences.

Population, Wars, and the Grand Canal in Chinese History

Throughout Chinese history, the Grand Canal served as a regional infrastructure in facilitating socio-economic and political development. The core regions of each dynasty were located in China’s eastern plain, and the Grand Canal ran from south to north through the plain, connecting northern and southern China. In unison, the areas along the Grand Canal also suffered from frequent wars. The role of the Grand Canal in influencing regional stability has yet to be sufficiently explored in the literature. This study seeks to (1) figure out the spatial distribution of population and wars, and (2) quantitatively measure the relationship between wars, population, and the distance from waterways in the Grand Canal Area in AD752–1910 by using their high-resolution geo-referenced data. Kernel density analysis was employed to serve the first purpose, while Pearson correlation and curve estimation analyses were applied to serve the second. Our results show that the areas surrounding the Grand Canal were densely populated. There was a war hot zone in the Beijing–Luoyang–Nanjing region near the Grand Canal, which shifted gradually over time. The correlation between war and population densities was positive, whereas the correlation between war density and distance from the waterway was negative. Finally, the cubic model captures the non-linear relationship between population, wars, and waterways. The above findings may shed more light on the Grand Canal’s role in influencing regional population and war patterns in historical China, a topic that has received little academic attention. More importantly, they may help advance empirical understanding of the impact of large-scale infrastructure on regional sustainability.

Bucking the trend: Population resilience in a marginal environment

Evaluating the impact of environmental changes on past societies is frequently confounded by the difficulty of establishing cause-and-effect at relevant scales of analysis. Commonly, paleoenvironmental records lack the temporal and spatial resolution to link them with historic events, yet there remains a tendency to correlate climate change and cultural transformations on the basis of their seeming synchronicity. Here, we challenge perceptions of societal vulnerability to past environmental change using an integrated paleoenvironmental and land-use history of a remote upland site in the north of Ireland. We present a high-resolution, multi-proxy record that illustrates extended occupation of this marginal locality throughout the climate oscillations of the last millennium. Importantly, historically-dated volcanic ash markers enable us to pinpoint precisely in our record the timing of major national demographic crises such as the Black Death and the European, Irish and Great (Potato) Famines. We find no evidence that climate downturns or demographic collapses had an enduring impact on the use of the uplands: either the community escaped the effects of these events, or population levels recovered rapidly enough (within a generation) to leave no appreciable mark on the palaeoenvironmental record. Our findings serve to illustrate the spatial complexity of human activity that can enable communities to withstand or quickly bounce back from largescale calamities. In neglecting to consider such local-scale variability in social and economic organization, generalized models of societal collapse risk overplaying the vulnerability of populations to long- and short-term ecological stressors to the detriment of identifying the social constraints that influence a population’s response to change.

Climate change-induced population pressure drives high rates of lethal violence in the Prehispanic central Andes

Understanding the influence of climate change and population pressure on human conflict remains a critically important topic in the social sciences. Long-term records that evaluate these dynamics across multiple centuries and outside the range of modern climatic variation are especially capable of elucidating the relative effect of—and the interaction between—climate and demography. This is crucial given that climate change may structure population growth and carrying capacity, while both climate and population influence per capita resource availability. This study couples paleoclimatic and demographic data with osteological evaluations of lethal trauma from 149 directly accelerator mass spectrometry 14C-dated individuals from the Nasca highland region of Peru. Multiple local and supraregional precipitation proxies are combined with a summed probability distribution of 149 14C dates to estimate population dynamics during a 700-y study window. Counter to previous findings, our analysis reveals a precipitous increase in violent deaths associated with a period of productive and stable climate, but volatile population dynamics. We conclude that favorable local climate conditions fostered population growth that put pressure on the marginal and highly circumscribed resource base, resulting in violent resource competition that manifested in over 450 y of internecine warfare. These findings help support a general theory of intergroup violence, indicating that relative resource scarcity—whether driven by reduced resource abundance or increased competition—can lead to violence in subsistence societies when the outcome is lower per capita resource availability.

Emergence and radiation of distemper viruses in terrestrial and marine mammals

Canine distemper virus (CDV) and phocine distemper virus (PDV) are major pathogens to terrestrial and marine mammals. Yet little is known about the timing and geographical origin of distemper viruses and to what extent it was influenced by environmental change and human activities. To address this, we (i) performed the first comprehensive time-calibrated phylogenetic analysis of the two distemper viruses, (ii) mapped distemper antibody and virus detection data from marine mammals collected between 1972 and 2018, and (iii) compiled historical reports on distemper dating back to the eighteenth century. We find that CDV and PDV diverged in the early seventeenth century. Modern CDV strains last shared a common ancestor in the nineteenth century with a marked radiation during the 1930s-1950s. Modern PDV strains are of more recent origin, diverging in the 1970s-1980s. Based on the compiled information on distemper distribution, the diverse host range of CDV and basal phylogenetic placement of terrestrial morbilliviruses, we hypothesize a terrestrial CDV-like ancestor giving rise to PDV in the North Atlantic. Moreover, given the estimated timing of distemper origin and radiation, we hypothesize a prominent role of environmental change such as the Little Ice Age, and human activities like globalization and war in distemper virus evolution.

Did Hydro-climatic Extremes, Positive Checks, and Economic Fluctuations Modulate the Epidemics Outbreaks in Late Imperial China?

Empirical research has shown that climate-related variables, the decline in economic well-being, and the mutual reinforcement of positive checks are the primary drivers of epidemic outbreaks in recent human history. However, their relative importance in causing the outbreak of epidemics is rarely examined quantitatively in a single study. I sought to address this issue by analyzing the 1402 epidemic incidents in China between 1841 and 1911, which partially overlaps partly with the Third Pandemic period. Fine-grained historical big data, multiple regression, and wavelet coherence analysis were employed. Statistical results show that economic fluctuations drove the country-wide epidemics outbreaks in China in inter-annual and decadal time scales. Economic fluctuations could cause short-term hardship and long-term impoverishment to the underprivileged social groups since a large portion of the Chinese population lived at the subsistence level in the past. The fluctuations might have sustained the repeated waves of epidemic outbreaks during the Third Pandemic period.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10745-021-00272-7.

Change of extreme snow events shaped the roof of traditional Chinese architecture in the past millennium

As a symbol of civilization and culture, architecture was originally developed for sheltering people from unpleasant weather or other environmental conditions. Therefore, architecture is expected to be sensitive to climate change, particularly to changes in the occurrence of extreme weather events. However, although meteorological factors are widely considered in modern architecture design, it remains unclear whether and how ancient people adapted to climate change from the perspective of architecture design, particularly on a millennium time scale. Here, we show periodic change and a positive trend in roof slope of traditional buildings in the northern part of central and eastern China and demonstrate climate change adaptation in traditional Chinese architecture, driven by fluctuations in extreme snowfall events over the past thousand years. This study provides an excellent example showing how humans have long been aware of the impact of climate change on daily life and learned to adapt to it.

Causality indices for bivariate time series data: A comparative review of performance

Inferring nonlinear and asymmetric causal relationships between multivariate longitudinal data is a challenging task with wide-ranging application areas including clinical medicine, mathematical biology, economics, and environmental research. A number of methods for inferring causal relationships within complex dynamic and stochastic systems have been proposed, but there is not a unified consistent definition of causality in the context of time series data. We evaluate the performance of ten prominent causality indices for bivariate time series across four simulated model systems that have different coupling schemes and characteristics. Pairwise correlations between different methods, averaged across all simulations, show that there is generally strong agreement between methods, with minimum, median, and maximum Pearson correlations between any pair (excluding two similarity indices) of 0.298, 0.719, and 0.955, respectively. In further experiments, we show that these methods are not always invariant to real-world relevant transformations (data availability, standardization and scaling, rounding errors, missing data, and noisy data). We recommend transfer entropy and nonlinear Granger causality as particularly strong approaches for estimating bivariate causal relationships in real-world applications. Both successfully identify causal relationships and a lack thereof across multiple simulations, while remaining robust to rounding errors, at least 20% missing data and small variance Gaussian noise. Finally, we provide flexible open-access Python code for computation of these methods and for the model simulations.

Anthropogenic disturbances caused declines in the wetland area and carbon pool in China during the last four decades

Wetlands are among the natural ecosystems with the highest soil carbon stocks on Earth. However, how anthropogenic disturbances have impacted the quantity and distribution of wetland carbon pool in China is not well understood. Here we used a comprehensive countrywide wetland inventory and Landsat 8 data to document the spatial patterns in China's wetland areas and carbon pools and to understand the underlying causes of their changes from the 1980s to 2010s. We found that the wetland area and carbon pool have decreased from 4.11 × 10⁵  km² and 15.2 Pg C in the 1980s to 2.14 × 10⁵  km² and 7.6 Pg C in the 2010s, respectively. Using the human influence index (HII) as a quantitative measure of anthropogenic disturbance intensity, we found a positive relationship between the HII values and wetland decreases in many regions and across China as a whole-which have increased 17% during the time period-indicating that anthropogenic disturbances have been a major factor causing wetland destruction in recent decades. This study provides new evidence for recent changes in China's wetland carbon pool and emphasizes the importance of mitigating anthropogenic disturbances for wetland conservation.

Rapid greening response of China's 2020 spring vegetation to COVID-19 restrictions: Implications for climate change

The 2019 novel coronavirus pandemic (COVID-19) negatively affected global public health and socioeconomic development. Lockdowns and travel restrictions to contain COVID-19 resulted in reduced human activity and decreased anthropogenic emissions. However, the secondary effects of these restrictions on the biophysical environment are uncertain. Using remotely sensed big data, we investigated how lockdowns and traffic restrictions affected China's spring vegetation in 2020. Our analyses show that travel decreased by 58% in the first 18 days following implementation of the restrictions across China. Subsequently, atmospheric optical clarity increased and radiation levels on the vegetation canopy were augmented. Furthermore, the spring of 2020 arrived 8.4 days earlier and vegetation 17.45% greener compared to 2015-2019. Reduced human activity resulting from COVID-19 restrictions contributed to a brighter, earlier, and greener 2020 spring season in China. This study shows that short-term changes in human activity can have a relatively rapid ecological impact at the regional scale.

Quantifying the Contributions of Environmental Factors to Wind Characteristics over 2000–2019 in China

Global climate change and human activities have resulted in immense changes in the Earth’s ecosystem, and the interaction between the land surface and the atmosphere is one of the most important processes. Wind is a reference for studying atmospheric dynamics and climate change, analyzing the wind speed change characteristics in historical periods, and studying the influence of wind on the Earth-atmosphere interaction; additionally, studying the wind, contributes to analyzing and alleviating a series of problems, such as the energy crisis, environmental pollution, and ecological deterioration facing human beings. In this study, data from 697 meteorological stations in China from 2000 to 2019 were used to study the distribution and trend of wind speed over the past two decades. The relationships between wind speed and climate factors were explored using statistical methods; furthermore, combined with terrain, climate change, and human activities, we quantified the contribution of environmental factors to wind speed. The results show that a downward trend was recorded before 2011, but overall, there was an increasing trend that was not significant; moreover, the wind speed changes showed obvious seasonality and were more complicated on the monthly scale. The wind speed trend mainly increased in the western region, decreased in the eastern region, was higher in the northeastern, northwestern, and coastal areas, and was lower in the central area. Temperature, bright sunshine duration, evaporation, and precipitation had a strong influence, in which wind speed showed a significant negative correlation with temperature and precipitation and vice versa for sunshine and evapotranspiration. The influence of environmental factors is diverse, and these results could help to develop environmental management strategies across ecologically fragile areas and improve the design of wind power plants to make better use of wind energy.

Climate change and state evolution

Despite the vast evidence on the short-run effects of adverse climate shocks on the economy, our understanding of their long-run impact on institutions is limited. To tackle such a key issue, a vast body of research has focused on ancient societies because of the limited complexity of their economies and their unparalleled experience with environmental and institutional change. Notably, the "collapse archaeology" literature has reported countless correlations consistent with the mantra that severe droughts are bound to trigger institutional crises. This conclusion, however, has been recently challenged by a stream of papers that, building on more detailed data on Bronze Age Mesopotamia and a more credible theory-based empirical strategy, have yielded the following two results. First, severe droughts pushed the elites to grant strong political and property rights to the nonelites to convince them that a sufficient part of the returns on joint investments would be shared via public good provision and, thus, to cooperate and accumulate a culture of cooperation. Second, a more favorable climate allowed the elites to elicit cooperation under less inclusive political regimes as well as a weaker culture of cooperation and, possibly, incomplete property rights. These patterns emphasize the importance of considering the asymmetric effect of droughts and, more generally, combining natural and social sciences for the evaluation of climate-related policies.

The delayed effect of cooling reinforced the NAO-plague connection in pre-industrial Europe

Previous studies on the connection between climate and plague were mostly conducted without considering the influence of large-scale atmospheric circulations and long-term historical observations. The current study seeks to reveal the sophisticated role of climatic control on plague by investigating the combined effect of North Atlantic Oscillation (NAO) and temperature on plague outbreaks in Europe from 1347 to 1760 CE. Moving correlation analysis is applied to explore the non-linear relationship between NAO and plague transmission over time. Also, we apply the cross-correlation function to identify the role of temperature in mediating the NAO-plague connection and the lead-lag relationship in between. Our statistical results show that the pathway from climate change to plague incidence is distinctive in its spatial, temporal, and non-linear patterns. The multi-decadal temperature change exerted a 15-22 years lagged impact on the NAO-plague correlation in different European regions. The NAO-plague correlation in Atlantic-Central Europe primarily remained positive, while the correlation in Mediterranean Europe switched between positive and negative alternately. The modulating effect of temperature over the NAO-plague correlation increases exponentially with the magnitude of the temperature anomaly, but the effect is negligible between 0.3 and -0.3 °C anomaly. Our findings show that a lagged influence from the temperature extremes dominantly controls the correlation between NAO and plague incidence. A forecast from our study suggests that large-scale plague outbreaks are unlikely to happen in Europe if NAO remains at its current positive phase during the earth's future warming.

Towards a rigorous understanding of societal responses to climate change

A large scholarship currently holds that before the onset of anthropogenic global warming, natural climatic changes long provoked subsistence crises and, occasionally, civilizational collapses among human societies. This scholarship, which we term the 'history of climate and society' (HCS), is pursued by researchers from a wide range of disciplines, including archaeologists, economists, geneticists, geographers, historians, linguists and palaeoclimatologists. We argue that, despite the wide interest in HCS, the field suffers from numerous biases, and often does not account for the local effects and spatiotemporal heterogeneity of past climate changes or the challenges of interpreting historical sources. Here we propose an interdisciplinary framework for uncovering climate-society interactions that emphasizes the mechanics by which climate change has influenced human history, and the uncertainties inherent in discerning that influence across different spatiotemporal scales. Although we acknowledge that climate change has sometimes had destructive effects on past societies, the application of our framework to numerous case studies uncovers five pathways by which populations survived-and often thrived-in the face of climatic pressures.

Climate change fostered cultural dynamics of human resilience in Europe in the past 2500 years

Humans possess limited knowledge on what generated cultural dynamics to strengthen human resilience to overcome climate-induced stresses. Although the highly developed mental ability of humans could have enabled significant human resilience in history, no study has empirically explained or has even scientifically confirmed how and when such dynamics arose. To fill the current research gap, this study therefore explores the associations among climatic conditions, the evolutional dynamics of human thinkers and their thoughts, and human ecological-socioeconomic conditions in the past 2500 years in Europe. Results from quantitative modellings and causal analyses confirm that climatic-ecological stresses led to human ecological-socioeconomic crises, and thereby dramatically increased twice of the thinkers' number and their thoughts' impact across different philosophies in truth, knowledge, and ethics for adaptation at multi-decadal to centennial temporal scales, especially in spirituality oriented mentality. The process of the stress-generated cultural dynamics displays some similarities with the stress-induced mutagenesis in organism evolution. Ultimately, climatic-ecological stresses prompt the escalation in the number of thinkers and impacts of their thoughts and flourishing of philosophy. Such stress-regenerated cultural dynamics imply that the current climate change threat may stimulate another thriving phase of cultural selection and lift humans to the next homeostatic plateau of civilization. Findings also extend the cognate scope of psychological, sociological, and civilization studies.

Beyond the social cost of carbon: Negative emission technologies as a means for biophysically setting the price of carbon

The social cost of carbon (SCC) is an estimate of the costs that society will incur because of the emission of one tonne of CO₂. Because of the large uncertainties in the effects of climate change and the subjectivity of the discount rate, estimates of SCC range widely, from - 10.2 to 105 213$ t^-1 in 2010 USD. Despite this range, the SCC has been used or proposed as a basis for a wide variety of policymaking including cost-benefit analysis and carbon taxes. The SCC suffers from several practical and philosophical weaknesses: it is anthropocentric, it neglects the acidification of oceans, it assumes that quantifiable economic variables like GDP are the primary costs that humans will experience from climate change, and it is impossible to quantify objectively. Further, the ethical implications of a carbon pricing policy include both the value of the carbon price, and the use of revenues generated by the policy. Thus, revenue neutral carbon policies as in some SCC-based proposals, are unlikely to be just. Here, we propose that the cost of emerging negative-emission technologies would be an alternative means for setting a carbon price and avoid these philosophical and practical weaknesses.

Maximum Markovian order detection for collective behavior

Many advances have been achieved in the study of collective behavior of animal groups and human beings. Markovian order is a significant property in collective behavior, which reveals the inter-agent interaction strategy of the system. In this study, we propose a method using the time-series data of collective behavior to determine the optimal maximum Markov order of time-series motion data so as to reflect the maximum memory capacity of the interacting network. Our method combines a time-delayed causal inference algorithm and a multi-order graphical model. We apply the method to the data of pigeon flocks, dogs, and a group of midges to determine their optimal maximum order for validation and construct high-order De Bruijn graphs as a stochastic model to describe their interacting relationships. Most temporal network data of animal movements can be effectively analyzed by our method, which may provide a practical and promising solution to detection of the optimal maximum Markovian order of collective behavior.

Impacts of climate variations on crime rates in Beijing, China

Previous studies suggest that climate variability and change impact both violent and property crimes. To investigate the mechanism, time series of crime rates (crime incidents per million people) and climate variables (temperature, relative humidity, rainfall, wind speed and haze) are decomposed into three components- long-term trends, seasonality and daily variations (or "noise"). Based on a 12-year dataset of daily crime (robbery, minimal violent robbery (MVR), assault, rape and homicide) numbers in Beijing, China, the correlation between climate variability and crime rate is examined for each component. The results show that in terms of seasonality, strong positive relations are observed for temperature-to-MVR, temperature-to-assault, temperature-to-rape, and relative-humidity-to-MVR but negative relations for haze-to-MVR, haze-to-assault, and haze-to-rape, which can be explained by Routine Activity Theory. In terms of daily variations, temperature, rainfall and haze are key factors. The correlations are all positive for temperature-to-assault, temperature-to-rape, temperature-to-homicide, rainfall-to-MVR, rainfall-to-robbery and rainfall-to-homicide. However, the relations between haze and crimes are more complicated. Specifically, the correlations are negative for haze-to-MVR and haze-to-robbery, but positive for haze-to-homicide, which can be interpreted by Crime Pattern Theory and also influenced by offenders' bounded rationality.

Future of the human climate niche

We show that for thousands of years, humans have concentrated in a surprisingly narrow subset of Earth’s available climates, characterized by mean annual temperatures around ∼13 °C. This distribution likely reflects a human temperature niche related to fundamental constraints. We demonstrate that depending on scenarios of population growth and warming, over the coming 50 y, 1 to 3 billion people are projected to be left outside the climate conditions that have served humanity well over the past 6,000 y. Absent climate mitigation or migration, a substantial part of humanity will be exposed to mean annual temperatures warmer than nearly anywhere today.

All species have an environmental niche, and despite technological advances, humans are unlikely to be an exception. Here, we demonstrate that for millennia, human populations have resided in the same narrow part of the climatic envelope available on the globe, characterized by a major mode around ∼11 °C to 15 °C mean annual temperature (MAT). Supporting the fundamental nature of this temperature niche, current production of crops and livestock is largely limited to the same conditions, and the same optimum has been found for agricultural and nonagricultural economic output of countries through analyses of year-to-year variation. We show that in a business-as-usual climate change scenario, the geographical position of this temperature niche is projected to shift more over the coming 50 y than it has moved since 6000 BP. Populations will not simply track the shifting climate, as adaptation in situ may address some of the challenges, and many other factors affect decisions to migrate. Nevertheless, in the absence of migration, one third of the global population is projected to experience a MAT >29 °C currently found in only 0.8% of the Earth’s land surface, mostly concentrated in the Sahara. As the potentially most affected regions are among the poorest in the world, where adaptive capacity is low, enhancing human development in those areas should be a priority alongside climate mitigation.

Migration health crisis associated with climate change: A systematic review

BACKGROUND

The empirical assessment of the health outcomes associated with migration caused by climate change is still unclear. However, health outcomes in the early stages are expected to be similar to the health outcomes associated with refugees. The objective of the present study was a systematic review of the health effects of migration caused by climate change.

METHODOLOGY

A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Online databases (PubMed, Scopus, Web of Science, and Google Scholar) were used to identify papers published that evaluated the health effects of migration caused by climate change. The search, article selection, and data extraction were carried out by two researchers independently. All English-language articles on the health effects of migration caused by climate change were included in this study.

RESULTS

An analysis of the complex ways in which climate change influences populations can be facilitated using a three-class classification: compulsory displacement, resettlement planning, and migration. Subsequent to climate changes, other changes, and environmental deficiencies, compulsory displacement may occur in case of inadequacy of compatibility responses. A part of migration-related health outcomes caused by climate change is from displacement from rural to urban areas, especially in developing countries. There is significant documentation on health and livelihood inequalities between migrant groups and host populations in developed countries.

CONCLUSION

If climate change continues in its current direction, it is likely that the number of refugees and crises will increase in the coming decades. Although the domain and the extent of health hazards caused by the displacement of the population associated with climate change cannot be clearly predicted, by reducing global greenhouse gas emissions, along with social and environmental adaptation strategies, migration caused by climate change, health risks and its relevant crises can be greatly reduced.

Causality of climate, food production and conflict over the last two millennia in the Hexi Corridor, China

The relationship between climate and human society has frequently been investigated to 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 Causality Analysis) are used in a systematic analysis of the potential causality of climate 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 conflict suggests that climate variability is not the direct causative agent of these phenomena, but that climate reduced food production which gradually lead to 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 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 potential future climate scenarios and their potential impacts.

Drought and intimate partner violence towards women in 19 countries in sub-Saharan Africa during 2011-2018: A population-based study

BACKGROUND

Drought has many known deleterious impacts on human health, but little is known about the relationship between drought and intimate partner violence (IPV). We aimed to evaluate this relationship and to assess effect heterogeneity between population subgroups among women in 19 sub-Saharan African countries.

METHODS AND FINDINGS

We used data from 19 Demographic and Health Surveys from 2011 to 2018 including 83,990 partnered women aged 15-49 years. Deviations in rainfall in the year before the survey date were measured relative to the 29 previous years using Climate Hazards Group InfraRed Precipitation with Station data, with recent drought classified as ordinal categorical variable (severe: ≤10th percentile; mild/moderate: >10th percentile to ≤30th percentile; none: >30th percentile). We considered 4 IPV-related outcomes: reporting a controlling partner (a risk factor for IPV) and experiencing emotional violence, physical violence, or sexual violence in the 12 months prior to survey. Logistic regression was used to estimate marginal risk differences (RDs). We evaluated the presence of effect heterogeneity by age group and employment status. Of the 83,990 women included in the analytic sample, 10.7% (9,019) experienced severe drought and 23.4% (19,639) experienced mild/moderate drought in the year prior to the survey, with substantial heterogeneity across countries. The mean age of respondents was 30.8 years (standard deviation 8.2). The majority of women lived in rural areas (66.3%) and were married (73.3%), while less than half (42.6%) were literate. Women living in severe drought had higher risk of reporting a controlling partner (marginal RD in percentage points = 3.0, 95% CI 1.3, 4.6; p < 0.001), experiencing physical violence (marginal RD = 0.8, 95% CI 0.1, 1.5; p = 0.019), and experiencing sexual violence (marginal RD = 1.2, 95% CI 0.4, 2.0; p = 0.001) compared with women not experiencing drought. Women living in mild/moderate drought had higher risk of reporting physical (marginal RD = 0.7, 95% CI 0.2, 1.1; p = 0.003) and sexual violence (marginal RD = 0.7, 95% CI 0.3, 1.2; p = 0.001) compared with those not living in drought. We did not find evidence for an association between drought and emotional violence. In analyses stratified by country, we found 3 settings where drought was protective for at least 1 measure of IPV: Namibia, Tanzania, and Uganda. We found evidence for effect heterogeneity (additive interaction) for the association between drought and younger age and between drought and employment status, with stronger associations between drought and IPV among adolescent girls and unemployed women. This study is limited by its lack of measured hypothesized mediating variables linking drought and IPV, prohibiting a formal mediation analysis. Additional limitations include the potential for bias due to residual confounding and potential non-differential misclassification of the outcome measures leading to an attenuation of observed associations.

CONCLUSIONS

Our findings indicate that drought was associated with measures of IPV towards women, with larger positive associations among adolescent girls and unemployed women. There was heterogeneity in these associations across countries. Weather shocks may exacerbate vulnerabilities among women in sub-Saharan Africa. Future work should further evaluate potential mechanisms driving these relationships.

Skeletal evidence for violent trauma from the bronze age Qijia culture (2,300-1,500 BCE), Gansu Province, China

This research explores how social and environmental factors may have contributed to conflict during the early Bronze Age in Northwest China by analyzing violent trauma on human skeletal remains from a cemetery of the Qijia culture (2300-1500 BCE). The Qijia culture existed during a period of dramatic social, technological, and environmental change, though minimal research has been conducted on how these factors may have contributed to violence within the area of the Qijia and other contemporaneous material cultures. An osteological assessment was conducted on 361 individuals (n = 241 adults, n = 120 non-adults) that were excavated from the Mogou site, Lintan County, Gansu, China. Injuries indicative of violence, including sharp- and blunt-force trauma that was sustained ante- or peri-mortem, were identified, and the patterns of trauma were analysed. Violent injuries were found on 8.58% (n = 31/361) of individuals, primarily adult males. No evidence of trauma was found on infants or children. Cranial trauma was found on 11.8% (n = 23/195) of the adult individuals examined. Of these, 43.5% (n = 10/23) presented with severe peri-mortem craniofacial trauma. The high rate of perimortem injuries and their locations indicate lethal intent. This lethality, in addition to the fact that individuals with trauma were predominantly male, suggest intergroup violence such as raiding, warfare, or feuding. Both social and environmental factors may have contributed to this conflict in the TaoRiver Valley, though future systematic archaeological and paleoenvironmental data will be needed to disentangle the many potential causal factors.

Inferring causal relationship in coordinated flight of pigeon flocks

Collective phenomenon of natural animal groups will be attributed to individual intelligence and interagent interactions, where a long-standing challenge is to reveal the causal relationship among individuals. In this study, we propose a causal inference method based on information theory. More precisely, we calculate mutual information by using a data mining algorithm named "k-nearest neighbor" and subsequently induce the transfer entropy to obtain the causality entropy quantifying the causal dependence of one individual on another subject to a condition set consisting of other neighboring ones. Accordingly, we analyze the high-resolution GPS data of three pigeon flocks to extract the hidden interaction mechanism governing the coordinated free flight. The comparison of spatial distribution between causal neighbors and all other remainders validates that no bias exists for the causal inference. We identify the causal relationships to establish the interaction network and observe that the revealed causal relationship follows a local interaction mode. Interestingly, the individuals closer to the mass center and the average velocity direction are more influential than others.

Climate and society in long-term perspective: Opportunities and pitfalls in the use of historical datasets

Recent advances in paleoclimatology and the growing digital availability of large historical datasets on human activity have created new opportunities to investigate long-term interactions between climate and society. However, noncritical use of historical datasets can create pitfalls, resulting in misleading findings that may become entrenched as accepted knowledge. We demonstrate pitfalls in the content, use and interpretation of historical datasets in research into climate and society interaction through a systematic review of recent studies on the link between climate and (a) conflict incidence, (b) plague outbreaks and (c) agricultural productivity changes. We propose three sets of interventions to overcome these pitfalls, which involve a more critical and multidisciplinary collection and construction of historical datasets, increased specificity and transparency about uncertainty or biases, and replacing inductive with deductive approaches to causality. This will improve the validity and robustness of interpretations on the long-term relationship between climate and society. This article is categorized under: Climate, History, Society, Culture > Disciplinary Perspectives.

A Granger causality analysis of groundwater patterns over a half-century

Groundwater depletion in many areas of the world has been broadly attributed to irrigation. However, more formal, data-driven, causal mechanisms of long-term groundwater patterns have not been assessed. Here, we conducted the first Granger causality analysis to identify the “causes” of groundwater patterns using the rice-producing parishes of Louisiana, USA, as an example. Trend analysis showed a decline of up to 6 m in groundwater level over 51 years. We found that no single cause explained groundwater patterns for all parishes. Causal linkages were noted between groundwater and area harvested, number of irrigation wells, summer precipitation totals, and drought. Bi-directional linkages were noted between groundwater and rice yield, suggesting feedback between both time series. Causal linkages were absent between groundwater and many drivers where significant correlations were noted, highlighting the importance of using robust causal relationships over illusive correlations to detect the cause. These results advance our understanding of groundwater dynamics and can reveal a key connection between food and groundwater.

The ecology of empire The dynamics of strategic differentiation-integration in two competing Western European biocultural groups

We tracked the relative integration and differentiation among life history traits over the period spanning AD 1800-1999 in the Britannic and Gallic biocultural groups. We found that Britannic populations tended toward greater strategic differentiation, while Gallic populations tended toward greater strategic integration. The dynamics of between-group competition between these two erstwhile rival biocultural groups were hypothesized as driving these processes. We constructed a latent factor that specifically sought to measure between-group competition and residualized it for the logarithmic effects of time. We found a significantly asymmetrical impact of between-group competition, where the between-group competition factor appeared to be driving the diachronic integration in Gallic populations but had no significantly corresponding influence on the parallel process of diachronic differentiation in Britannic populations. This suggests that the latter process was attributable to some alternative and unmeasured causes, such as the resource abundance consequent to territorial expansion rather than contraction.

Modeling Future Projections of Temperature-Related Excess Morbidity due to Infectious Gastroenteritis under Climate Change Conditions in Japan

BACKGROUND

Climate change has marked implications for the burden of infectious diseases. However, no studies have estimated future projections of climate change–related excess morbidity due to diarrhea according to climate change scenarios.

OBJECTIVES

We aimed to examine temperature-infectious gastroenteritis associations throughout Japan and project temperature-related morbidity concomitant with climate change for the 2090s.

METHODS

Weekly time series of average temperature and morbidity for infectious gastroenteritis cases in the period 2005-2015 were collated from the 47 Japanese prefectures. A two-stage time-series analysis was adopted to estimate temperature-infectious gastroenteritis relationships. Time series of present and future average daily temperature fluctuations were projected for the four climate change scenarios of representative concentration pathways (RCPs) according to five general circulation models. Excess morbidity for high and low temperatures and the net change in the period 1990–2099 were projected for each climate change scenario by assuming the absence of adaptation and population alterations.

RESULTS

In the period 2005–2015, 11,529,833 infectious gastroenteritis cases were reported. There were net reductions in temperature-induced excess morbidity under higher emission scenarios. The net change in the projection period 2090-2099 in comparison with 2010–2019 was [Formula: see text] (95% empirical confidence interval [eCI]: [Formula: see text], 0.5) for RCP2.6, [Formula: see text] (95% eCI: [Formula: see text], [Formula: see text]) for RCP4.5, [Formula: see text] (95% eCI: [Formula: see text], [Formula: see text]) for RCP6.0, and [Formula: see text] (95% eCI: [Formula: see text], [Formula: see text]) for RCP8.5, and the higher the emissions scenario, the larger the estimates reductions. Spatial heterogeneity in the temperature-morbidity relationship was observed among prefectures (Cochran Q test, [Formula: see text]; [Formula: see text]).

CONCLUSIONS

Japan may experience a net reduction in temperature-related excess morbidity due to infectious gastroenteritis in higher emission scenarios. These results might be because the majority of temperature-related diarrhea cases in Japan are attributable to viral infections during the winter season. Further projections of specific pathogen-induced infectious gastroenteritis due to climate change are warranted. https://doi.org/10.1289/EHP4731.

Detecting interaction networks in the human microbiome with conditional Granger causality

Human microbiome research is rife with studies attempting to deduce microbial correlation networks from sequencing data. Standard correlation and/or network analyses may be misleading when taken as an indication of taxon interactions because "correlation is neither necessary nor sufficient to establish causation"; environmental filtering can lead to correlation between non-interacting taxa. Unfortunately, microbial ecologists have generally used correlation as a proxy for causality although there is a general consensus about what constitutes a causal relationship: causes both precede and predict effects. We apply one of the first causal models for detecting interactions in human microbiome samples. Specifically, we analyze a long duration, high resolution time series of the human microbiome to decipher the networks of correlation and causation of human-associated microbial genera. We show that correlation is not a good proxy for biological interaction; we observed a weak negative relationship between correlation and causality. Strong interspecific interactions are disproportionately positive, whereas almost all strong intraspecific interactions are negative. Interestingly, intraspecific interactions also appear to act at a short timescale causing vast majority of the effects within 1-3 days. We report how different taxa are involved in causal relationships with others, and show that strong interspecific interactions are rarely conserved across two body sites whereas strong intraspecific interactions are much more conserved, ranging from 33% between the gut and right-hand to 70% between the two hands. Therefore, in the absence of guiding assumptions about ecological interactions, Granger causality and related techniques may be particularly helpful for understanding the driving factors governing microbiome composition and structure.

Speleothems from the Middle East: An Example of Water Limited Environments in the SISAL Database

The Middle East (ME) spans the transition between a temperate Mediterranean climate in the Levant to hyper-arid sub-tropical deserts in the southern part of the Arabian Peninsula (AP), with the complex alpine topography in the northeast feeding the Euphrates and Tigris rivers which support life in the Southeastern Fertile Crescent (FC). Climate projections predict severe drying in several parts of the ME in response to global warming, making it important to understand the controls of hydro-climate perturbations in the region. Here we discuss 23 ME speleothem stable oxygen isotope (δ18Occ) records from 16 sites from the SISAL_v1 database (Speleothem Isotope Synthesis and Analysis database), which provide a record of past hydro-climatic variability. Sub-millennial changes in ME δ18Occ values primarily indicate changes in past precipitation amounts the result of the main synoptic pattern in the region, specifically Mediterranean cyclones. This pattern is superimposed on change in vapor source δ18O composition. The coherency (or lack thereof) between regional records is reviewed from Pleistocene to present, covering the Last Glacial Maximum (~22 ka), prominent events during deglaciation, and the transition into the Holocene. The available δ18Occ time-series are investigated by binning and normalizing at 25-year and 200-year time windows over the Holocene. Important climatic oscillations in the Holocene are discussed, such as the 8.2 ka, 4.2 ka and 0.7 ka (the Little Ice Age) Before Present events. Common trends in the normalized anomalies are tested against different climate archives. Finally, recommendations for future speleothem-based research in the region are given along with comments on the utility and completeness of the SISAL database.

Equilibrium dynamics of European pre-industrial populations: the evidence of carrying capacity in human agricultural societies

Human populations tend to grow steadily, because of the ability of people to make innovations, and thus overcome and extend the limits imposed by natural resources. It is therefore questionable whether traditional concepts of population ecology, including environmental carrying capacity, can be applied to human societies. The existence of carrying capacity cannot be simply inferred from population time-series, but it can be indicated by the tendency of populations to return to a previous state after a disturbance. So far only indirect evidence at a coarse-grained scale has indicated the historical existence of human carrying capacity. We analysed unique historical population data on 88 settlements before and after the Thirty Years War (1618-1648), one the longest and most destructive conflicts in European history, which reduced the population of Central Europe by 30-50%. The recovery rate of individual settlements after the war was positively correlated with the extent of the disturbance, so that the population size of the settlements after a period of regeneration was similar to the pre-war situation, indicating an equilibrium population size (i.e. carrying capacity). The carrying capacity of individual settlements was positively determined mostly by the fertility of the soil and the area of the cadastre, and negatively by the number of other settlements in the surroundings. Pre-industrial human population sizes were thus probably controlled by negative density dependence mediated by soil fertility, which could not increase due to limited agricultural technologies.

Detecting intermittent switching leadership in coupled dynamical systems

Leader-follower relationships are commonly hypothesized as a fundamental mechanism underlying collective behaviour in many biological and physical systems. Understanding the emergence of such behaviour is relevant in science and engineering to control the dynamics of complex systems toward a desired state. In prior works, due in part to the limitations of existing methods for dissecting intermittent causal relationships, leadership is assumed to be consistent in time and space. This assumption has been contradicted by recent progress in the study of animal behaviour. In this work, we leverage information theory and time series analysis to propose a novel and simple method for dissecting changes in causal influence. Our approach computes the cumulative influence function of a given individual on the rest of the group in consecutive time intervals and identify change in the monotonicity of the function as a change in its leadership status. We demonstrate the effectiveness of our approach to dissect potential changes in leadership on self-propelled particles where the emergence of leader-follower relationship can be controlled and on tandem flights of birds recorded in their natural environment. Our method is expected to provide a novel methodological tool to further our understanding of collective behaviour.

Climate change and vector-borne diseases of public health significance

There has been much debate as to whether or not climate change will have, or has had, any significant effect on risk from vector-borne diseases. The debate on the former has focused on the degree to which occurrence and levels of risk of vector-borne diseases are determined by climate-dependent or independent factors, while the debate on the latter has focused on whether changes in disease incidence are due to climate at all, and/or are attributable to recent climate change. Here I review possible effects of climate change on vector-borne diseases, methods used to predict these effects and the evidence to date of changes in vector-borne disease risks that can be attributed to recent climate change. Predictions have both over- and underestimated the effects of climate change. Mostly under-estimations of effects are due to a focus only on direct effects of climate on disease ecology while more distal effects on society's capacity to control and prevent vector-borne disease are ignored. There is increasing evidence for possible impacts of recent climate change on some vector-borne diseases but for the most part, observed data series are too short (or non-existent), and impacts of climate-independent factors too great, to confidently attribute changing risk to climate change.

Pre-industrial plague transmission is mediated by the synergistic effect of temperature and aridity index

Background

Although the linkage between climate change and plague transmission has been proposed in previous studies, the dominant approach has been to address the linkage with traditional statistical methods, while the possible non-linearity, non-stationarity and low frequency domain of the linkage has not been fully considered. We seek to address the above issue by investigating plague transmission in pre-industrial Europe (AD1347–1760) at both continental and country levels.

Methods

We apply Granger Causality Analysis to identify the casual relationship between climatic variables and plague outbreaks. We then apply Wavelet Analysis to explore the non-linear and non-stationary association between climate change and plague outbreaks.

Results

Our results show that 5-year lagged temperature and aridity index are the significant determinants of plague outbreaks in pre-industrial Europe. At the multi-decadal time scale, there are more frequent plague outbreaks in a cold and arid climate. The synergy of temperature and aridity index, rather than their individual effect, is more imperative in driving plague outbreaks, which is valid at both the continental and country levels.

Conclusions

Plague outbreaks come after cold and dry spells. The multi-decadal climate variability is imperative in driving the cycles of plague outbreaks in pre-industrial Europe. The lagged and multi-decadal effect of climate change on plague outbreaks may be attributable to the complexity of ecological, social, or climate systems, through which climate exerts its influence on plague dynamics. These findings may contribute to improve our understanding of the epidemiology of plague and other rodent-borne or flea-borne infectious diseases in human history.

Electronic supplementary material

The online version of this article (10.1186/s12879-018-3045-5) contains supplementary material, which is available to authorized users.

History meets palaeoscience: Consilience and collaboration in studying past societal responses to environmental change

History and archaeology have a well-established engagement with issues of premodern societal development and the interaction between physical and cultural environments; together, they offer a holistic view that can generate insights into the nature of cultural resilience and adaptation, as well as responses to catastrophe. Grasping the challenges that climate change presents and evolving appropriate policies that promote and support mitigation and adaptation requires not only an understanding of the science and the contemporary politics, but also an understanding of the history of the societies affected and in particular of their cultural logic. But whereas archaeologists have developed productive links with the paleosciences, historians have, on the whole, remained muted voices in the debate until recently. Here, we suggest several ways in which a consilience between the historical sciences and the natural sciences, including attention to even distant historical pasts, can deepen contemporary understanding of environmental change and its effects on human societies.

Impact of climate variability and change on crime rates in Tangshan, China

Studies examining the relation between climate and human conflict often focus on the role of temperature and have diverging views on the significance of other climatic variables. Using a 6-year (from 2009 to 2014) dataset of crime statistics collected in a medium size city of Tangshan in China, we find strong, positive correlations between temperature and both violent and property crimes. In addition, relative humidity is also positively correlated with Rape and Minimal Violent Robbery (MVR). The seasonal cycle is a significant factor that induces good correlations between crime rates and climatic variables, which can be reasonably explained by the Routine Activity theory. We also show that the combined impacts of temperature and relative humidity on crime rates can be reasonably captured by traditional heat stress indices. Using an ensemble of CMIP5 global climate change simulations, we estimate that at the end of the 21st century the rates of Rape (violent crime) and MVR (property crime) in Tangshan will increase by 9.5±5.3% and 2.6±2.1%, respectively, under the highest emission scenario (Representative Concentration Pathway 8.5). The gross domestic product (GDP) is also shown to be significantly correlated with MVR rates and the regression results are strongly impacted by whether GDP is considered or not.

Holocene fluctuations in human population demonstrate repeated links to food production and climate

We consider the long-term relationship between human demography, food production, and Holocene climate via an archaeological radiocarbon date series of unprecedented sampling density and detail. There is striking consistency in the inferred human population dynamics across different regions of Britain and Ireland during the middle and later Holocene. Major cross-regional population downturns in population coincide with episodes of more abrupt change in North Atlantic climate and witness societal responses in food procurement as visible in directly dated plants and animals, often with moves toward hardier cereals, increased pastoralism, and/or gathered resources. For the Neolithic, this evidence questions existing models of wholly endogenous demographic boom-bust. For the wider Holocene, it demonstrates that climate-related disruptions have been quasi-periodic drivers of societal and subsistence change.

Scale-dependent climatic drivers of human epidemics in ancient China

A wide range of climate change-induced effects have been implicated in the prevalence of infectious diseases. Disentangling causes and consequences, however, remains particularly challenging at historical time scales, for which the quality and quantity of most of the available natural proxy archives and written documentary sources often decline. Here, we reconstruct the spatiotemporal occurrence patterns of human epidemics for large parts of China and most of the last two millennia. Cold and dry climate conditions indirectly increased the prevalence of epidemics through the influences of locusts and famines. Our results further reveal that low-frequency, long-term temperature trends mainly contributed to negative associations with epidemics, while positive associations of epidemics with droughts, floods, locusts, and famines mainly coincided with both higher and lower frequency temperature variations. Nevertheless, unstable relationships between human epidemics and temperature changes were observed on relatively smaller time scales. Our study suggests that an intertwined, direct, and indirect array of biological, ecological, and societal responses to different aspects of past climatic changes strongly depended on the frequency domain and study period chosen.

Winter amplification of the European Little Ice Age cooling by the subpolar gyre

Climate reconstructions reveal a strong winter amplification of the cooling over central and northern continental Europe during the Little Ice Age period (LIA, here defined as c. 16th–18th centuries) via persistent, blocked atmospheric conditions. Although various potential drivers have been suggested to explain the LIA cooling, no coherent mechanism has yet been proposed for this seasonal contrast. Here we demonstrate that such exceptional wintertime conditions arose from sea ice expansion and reduced ocean heat losses in the Nordic and Barents seas, driven by a multicentennial reduction in the northward heat transport by the subpolar gyre (SPG). However, these anomalous oceanic conditions were largely decoupled from the European atmospheric variability in summer. Our novel dynamical explanation is derived from analysis of an ensemble of last millennium climate simulations, and is supported by reconstructions of European temperatures and atmospheric circulation variability and North Atlantic/Arctic paleoceanographic conditions. We conclude that SPG-related internal climate feedbacks were responsible for the winter amplification of the European LIA cooling. Thus, characterization of SPG dynamics is essential for understanding multicentennial variations of the seasonal cycle in the European/North Atlantic sector.

Relationship between ancient bridges and population dynamics in the lower Yangtze River Basin, China

It has been suggested that population growth dynamics may be revealed by the geographic distribution and the physical structure of ancient bridges. Yet, this relationship has not been empirically verified. In this study, we applied the archaeological records for ancient bridges to reveal the population growth dynamics in the lower Yangtze River Basin in late imperial China. We investigated 89 ancient bridges in Yixing that were built during the Ming and Qing dynasties (AD1368-1911). Global Position System information and structure (length, width, and span) of those bridges was measured during our field investigations. Their distribution density was calculated by ArcGIS. The historical socio-economic dynamics of Yixing was inferred from the distribution and structure of ancient bridges. Based on the above information, the population growth dynamics in Yixing was projected. Our results show that 77 bridges were built in Yixing during the Qing dynasty, which is 6.41 times more than the number built during the Ming dynasty. In the Ming dynasty, bridges were built on pivotal routes; in the Qing dynasty, bridges were scattered across various places. Over the period, the density distribution of bridges shifted northwestward, while the average length and width of bridges decreased. The increasing number of bridges corresponded to population growth, largely attributable to massive clan migration from northern China during the Little Ice Age. The shift in the density distribution of bridges corresponded to the formation of settlements of large clans and the blossoming of Yixing Teapot handicrafts. The scattering and the reduction in average length and width of bridges was due to the dispersal of population and the associated formation of small settlements in the latter period. Our approach is innovative and robust, and could be employed to recover long-term historical population growth dynamics in other parts of China.

Climate Change and Collective Violence

Climate change is causing increases in temperature, changes in precipitation and extreme weather events, sea-level rise, and other environmental impacts. It is also causing or contributing to heat-related disorders, respiratory and allergic disorders, infectious diseases, malnutrition due to food insecurity, and mental health disorders. In addition, increasing evidence indicates that climate change is causally associated with collective violence, generally in combination with other causal factors. Increased temperatures and extremes of precipitation with their associated consequences, including resultant scarcity of cropland and other key environmental resources, are major pathways by which climate change leads to collective violence. Public health professionals can help prevent collective violence due to climate change (a) by supporting mitigation measures to reduce greenhouse gas emissions, (b) by promoting adaptation measures to address the consequences of climate change and to improve community resilience, and

Climate and marriage in the Netherlands, 1871-1937

Environmental factors such as climate variability can place significant constraints on demographic behavior in a range of settings. However, few studies investigate the relationships between demography and climate in historical contexts. Using longitudinal individual-level demographic data from the Historical Sample of the Netherlands (HSN) and climate and economic data from 1871-1937, we examine the effects of climate variability on marriage. This analysis reveals that marriage increases with negative environmental conditions such as cold temperatures, riverine flooding, and high rye prices. These findings are not consistent with a Malthusian narrative of marriage behavior, or with the expectation that environmental constraints were stronger in the historical past.