Does Human Migration Affect International Trade? A Complex-Network Perspective

This paper explores the relationships between international human migration and merchandise trade using a complex-network approach. We firstly compare the topological structure of worldwide networks of human migration and bilateral trade over the period 1960–2000. Next, we ask whether pairs of countries that are more central in the migration network trade more. We show that: (i) the networks of international migration and trade are strongly correlated, and such correlation can be mostly explained by country economic/demographic size and geographical distance; (ii) centrality in the international-migration network boosts bilateral trade; (iii) intensive forms of country centrality are more trade enhancing than their extensive counterparts. Our findings suggest that bilateral trade between any two countries is not only affected by the presence of migrants from either countries, but also by their relative embeddedness in the complex web of corridors making up the network of international human migration.     

Inequalities in Global Trade: A Cross-Country Comparison of Trade Network Position,Economic Wealth,Pollution and Mortality

In this paper we investigate how structural patterns of international trade give rise to emissions inequalities across countries, and how such inequality in turn impact countries’ mortality rates. We employ Multi-regional Input-Output analysis to distinguish between sulfur-dioxide (SO2) emissions produced within a country’s boarders (production-based emissions) and emissions triggered by consumption in other countries (consumption-based emissions). We use social network analysis to capture countries’ level of integration within the global trade network. We then apply the Prais-Winsten panel estimation technique to a panel data set across 172 countries over 20 years (1990–2010) to estimate the relationships between countries’ level of integration and SO2 emissions, and the impact of trade integration and SO2 emission on mortality rates. Our findings suggest a positive, (log-) linear relationship between a country’s level of integration and both kinds of emissions. In addition, although more integrated countries are mainly responsible for both forms of emissions, our findings indicate that they also tend to experience lower mortality rates. Our approach offers a unique combination of social network analysis with multiregional input-output analysis, which better operationalizes intuitive concepts about global trade and trade structure.     

Four approaches to guide ecological restoration in Latin America

There is strong upswing in conservation and restoration efforts in Latin America (LA), particularly in the recent decades after several countries have committed to international agreements such as the Aichi targets of the Convention on Biological Diversity, Initiative 20×20, and the Bonn Challenge. To fulfill these agreements, the practice of ecological restoration has to be defined based on ecological knowledge, but also on the specific social, economic, and legal aspects of each country in the region. Here, we give some examples about the national understanding of ecological restoration in 10 countries of LA. We identify difficulties and opportunities to define restoration priorities and needs, and discuss some approaches to cope with economic constraints and agreements, including the potential role of restoration networks in this process. On the basis of the socioecological complexity of these countries and the expectations they have in relation to restoration, we proposed four approaches to guide restoration practice and policy in the region: (1) including biodiversity and ecosystem services approach into ecosystem restoration initiatives; (2) promoting restoration in their frequently human‐modified landscapes; (3) accounting for cost–benefit trade‐offs; and (4) assembling “horizontal” communication frameworks. These approaches should be based at national levels, but adapted to local‐regional levels, in a bottom‐up perspective. We consider that national and international restoration networks in the region can help to overcome difficulties, fostering a solid scientific community, helping to develop national approaches that better match the specific conditions of each country and enhancing communication among different groups of stakeholders.     

International Trade Modelling Using Open Flow Networks: A Flow-Distance Based Analysis

This paper models and analyzes international trade flows using open flow networks (OFNs) with the approaches of flow distances, which provide a novel perspective and effective tools for the study of international trade. We discuss the establishment of OFNs of international trade from two coupled viewpoints: the viewpoint of trading commodity flow and that of money flow. Based on the novel model with flow distance approaches, meaningful insights are gained. First, by introducing the concepts of trade trophic levels and niches, countries’ roles and positions in the global supply chains (or value-added chains) can be evaluated quantitatively. We find that the distributions of trading “trophic levels” have the similar clustering pattern for different types of commodities, and summarize some regularities between money flow and commodity flow viewpoints. Second, we find that active and competitive countries trade a wide spectrum of products, while inactive and underdeveloped countries trade a limited variety of products. Besides, some abnormal countries import many types of goods, which the vast majority of countries do not need to import. Third, harmonic node centrality is proposed and we find the phenomenon of centrality stratification. All the results illustrate the usefulness of the model of OFNs with its network approaches for investigating international trade flows.     

Discovering Preferential Patterns in Sectoral Trade Networks

We analyze the patterns of import/export bilateral relations, with the aim of assessing the relevance and shape of “preferentiality” in countries’ trade decisions. Preferentiality here is defined as the tendency to concentrate trade on one or few partners. With this purpose, we adopt a systemic approach through the use of the tools of complex network analysis. In particular, we apply a pattern detection approach based on community and pseudocommunity analysis, in order to highlight the groups of countries within which most of members’ trade occur. The method is applied to two intra-industry trade networks consisting of 221 countries, relative to the low-tech “Textiles and Textile Articles” and the high-tech “Electronics” sectors for the year 2006, to look at the structure of world trade before the start of the international financial crisis. It turns out that the two networks display some similarities and some differences in preferential trade patterns: they both include few significant communities that define narrow sets of countries trading with each other as preferential destinations markets or supply sources, and they are characterized by the presence of similar hierarchical structures, led by the largest economies. But there are also distinctive features due to the characteristics of the industries examined, in which the organization of production and the destination markets are different. Overall, the extent of preferentiality and partner selection at the sector level confirm the relevance of international trade costs still today, inducing countries to seek the highest efficiency in their trade patterns.     

Does governance play a role in the distribution of invasive alien species?

Invasive alien species (IAS) constitute a major threat to global biological diversity. In order to control their spread, a detailed understanding of the factors influencing their distribution is essential. Although international trade is regarded as a major force structuring spatial patterns of IAS, the role of other social factors remains unclear. Despite studies highlighting the importance of strong governance in slowing drivers of biodiversity loss such as logging, deforestation, and agricultural intensification, no study has yet analyzed its contribution to the issue of IAS. Using estimates of governance quality and comprehensive spatiotemporal IAS data, we performed multiple linear regressions to investigate the effect of governance quality upon the distribution of species listed under “100 of the worst” IAS in 38 Eurasian countries as defined by DASIE. Our model suggested that for countries with higher GDP, stronger governance was associated with a greater number of the worst IAS; in contrast, for the lowest GDP countries under analysis, stronger governance was associated with fewer of these IAS. We elucidate how the quality of governance within a country has implications for trade, tourism, transport, legislation, and economic development, all of which influence the spread of IAS. While our findings support the common assumption that strengthening governance benefits conservation interventions in countries of smaller economy, we find that this effect is not universal. Stronger governance alone cannot adequately address the problem of IAS, and targeted action is required in relatively high‐GDP countries in order to stem the influx of IAS associated with high volumes of trade.     

Biological invasions in developing and developed countries: does one model fit all?

There is a strong bias concerning the regions of the globe where research on biological invasions is conducted, with notably lower representation of developing countries. However, in developing countries, effective management strategies to control invasions could be more beneficial in conserving global biodiversity since these countries tend to have larger, highly diverse natural habitats. Lower levels of development are seen as an obstacle to tackling biological invasions, but little thought is given to the advantages of developing countries in dealing with invasive species. We analyzed differences between developed and developing countries regarding the problem of invasive species and their historical and current patterns of international trade, disturbance levels and land use, research and monitoring, control and mitigation, and social awareness. Developed nations have some advantages, especially in levels of social awareness and means for controlling and studying exotics, but developing nations also enjoy important advantages given their lower levels of international trade and the availability of low-cost labor. Also, there is evidence that the process of economic development, which results in more efficient ways to transform landscapes and increases international trade, is strongly associated with increasing rates of biological invasion. Differences in data quality and availability between developed and developing countries make comparative analyses of biological invasions a difficult task. Thus, these differences creates a challenge in forming global strategies to deal with invasions. There have been calls for creating international plans to deal with invasive species, but we believe that it is important first to acknowledge the challenges and understand both the advantages and disadvantages of developing countries.     

Infectious disease transmission and contact networks in wildlife and livestock

The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools.     

Virtual water and water footprints do not provide helpful insight regarding international trade or water scarcity

Many authors have estimated the virtual water content of good and services traded internationally, and many have calculated national water footprints that account for the volumes of virtual water imported and exported. Some authors have suggested that international trade of virtual water has been harmful to selected exporting countries with limited water endowments. Some suggest also that current patterns of international trade should be rearranged to make better use of global water resources. Yet, countries do not actually trade in virtual water. They trade in goods and services for which water is one of many inputs. Wise choices regarding water resources and smart strategies regarding international trade cannot be determined by focusing on water alone. The notions of virtual water and water footprints are not helpful indicators of optimal strategies regarding water resources, particularly when considering issues such as water scarcity or international trade. I describe four perspectives regarding virtual water and water footprints, with the goal of demonstrating the inadequacies of these notions in policy discussions and in efforts to determine the optimal allocation and use of water resources. The four perspectives are: (1) international trade should not be modified or regulated to reflect the virtual water content of traded commodities or water footprints in the countries of trading partners, (2) countries do not save water by engaging in virtual water trade, (3) consumers in one country cannot alleviate water scarcity or improve water quality in other countries, and (4) water footprints are not analogous to carbon or ecological footprints.     

Emergence of Multiplex Communities in Collaboration Networks

Community structures in collaboration networks reflect the natural tendency of individuals to organize their work in groups in order to better achieve common goals. In most of the cases, individuals exploit their connections to introduce themselves to new areas of interests, giving rise to multifaceted collaborations which span different fields. In this paper, we analyse collaborations in science and among movie actors as multiplex networks, where the layers represent respectively research topics and movie genres, and we show that communities indeed coexist and overlap at the different layers of such systems. We then propose a model to grow multiplex networks based on two mechanisms of intra and inter-layer triadic closure which mimic the real processes by which collaborations evolve. We show that our model is able to explain the multiplex community structure observed empirically, and we infer the strength of the two underlying social mechanisms from real-world systems. Being also able to correctly reproduce the values of intra-layer and inter-layer assortativity correlations, the model contributes to a better understanding of the principles driving the evolution of social networks.     

Consistent characterisation factors at midpoint and endpoint relevant to agricultural water scarcity arising from freshwater consumption

Purpose

The shortage of agricultural water from freshwater sources is a growing concern because of the relatively large amounts needed to sustain food production for an increasing population. In this context, an impact assessment methodology is indispensable for the identification and assessment of the potential consequences of freshwater consumption in relation to agricultural water scarcity. This paper reports on the consistent development of midpoint and endpoint characterisation factors (CFs) for assessing these impacts.

Methods

Midpoint characterisation factors focus specifically on shortages in food production resulting from agricultural water scarcity. These were calculated by incorporating country-specific compensation factors for physical availability of water resources and socio-economic capacity in relation to the irrigation water demand for agriculture. At the endpoint, to reflect the more complex impact pathways from food production losses to malnutrition damage from agricultural water scarcity, international food trade relationships and economic adaptation capacity were integrated in the modelling with measures of nutritional vulnerability for each country.

Results and discussion

The inter-country variances of CFs at the midpoint revealed by this study were larger than those derived using previously developed methods, which did not integrate compensation processes by food stocks. At the endpoint level, both national and trade-induced damage through international trade were quantified and visualised. Distribution of malnutrition damage was also determined by production and trade balances for commodity groups in water-consuming countries, as well as dependency on import ratios for importer countries and economic adaptation capacity in each country. By incorporating the complex relationships between these factors, estimated malnutrition damage due to freshwater consumption at the country scale showed good correlation with total reported nutritional deficiency damage.

Conclusions

The model allows the establishment of consistent CFs at the midpoint and endpoint for agricultural water scarcity resulting from freshwater consumption. The complex relationships between food production supply and nutrition damage can be described by considering the physical and socio-economic parameters used in this study. Developed CFs contribute to a better assessment of the potential impacts associated with freshwater consumption in global supply chains and to life cycle assessment and water footprint assessments.

     

Network cohesion,group size and neocortex size in female-bonded Old World primates

Most primates are intensely social and spend a large amount of time servicing social relationships. In this study, we use social network analysis to examine the relationship between primate group size, total brain size, neocortex ratio and several social network metrics concerned with network cohesion. Using female grooming networks from a number of Old World monkey species, we found that neocortex size was a better predictor of network characteristics than endocranial volumes. We further found that when we controlled for group size, neocortex ratio was negatively correlated with network density, connectivity, relative clan size and proportional clan membership, while there was no effect of neocortex ratio on change in connectivity following the removal of the most central female in the network. Thus, in species with larger neocortex ratios, females generally live in more fragmented networks, belong to smaller grooming clans and are members of relatively fewer clans despite living in a closely bonded group. However, even though groups are more fragmented to begin with among species with larger neocortices, the removal of the most central individual does cause groups to fall apart, suggesting that social complexity may ultimately involve the management of highly fragmented social groups while at the same time maintaining overall social cohesion. These results emphasize a need for more detailed brain data on a wider sample of primate species.     

Entropy-Based Analysis and Bioinformatics-Inspired Integration of Global Economic Information Transfer

The assessment of information transfer in the global economic network helps to understand the current environment and the outlook of an economy. Most approaches on global networks extract information transfer based mainly on a single variable. This paper establishes an entirely new bioinformatics-inspired approach to integrating information transfer derived from multiple variables and develops an international economic network accordingly. In the proposed methodology, we first construct the transfer entropies (TEs) between various intra- and inter-country pairs of economic time series variables, test their significances, and then use a weighted sum approach to aggregate information captured in each TE. Through a simulation study, the new method is shown to deliver better information integration compared to existing integration methods in that it can be applied even when intra-country variables are correlated. Empirical investigation with the real world data reveals that Western countries are more influential in the global economic network and that Japan has become less influential following the Asian currency crisis.     

Large-Scale Land Acquisition and Its Effects on the Water Balance in Investor and Host Countries

This study examines the validity of the assumption that international large-scale land acquisition (LSLA) is motivated by the desire to secure control over water resources, which is commonly referred to as ‘water grabbing’. This assumption was repeatedly expressed in recent years, ascribing the said motivation to the Gulf States in particular. However, it must be considered of hypothetical nature, as the few global studies conducted so far focused primarily on the effects of LSLA on host countries or on trade in virtual water. In this study, we analyse the effects of 475 intended or concluded land deals recorded in the Land Matrix database on the water balance in both host and investor countries. We also examine how these effects relate to water stress and how they contribute to global trade in virtual water. The analysis shows that implementation of the LSLAs in our sample would result in global water savings based on virtual water trade. At the level of individual LSLA host countries, however, water use intensity would increase, particularly in 15 sub-Saharan states. From an investor country perspective, the analysis reveals that countries often suspected of using LSLA to relieve pressure on their domestic water resources—such as China, India, and all Gulf States except Saudi Arabia—invest in agricultural activities abroad that are less water-intensive compared to their average domestic crop production. Conversely, large investor countries such as the United States, Saudi Arabia, Singapore, and Japan are disproportionately externalizing crop water consumption through their international land investments. Statistical analyses also show that host countries with abundant water resources are not per se favoured targets of LSLA. Indeed, further analysis reveals that land investments originating in water-stressed countries have only a weak tendency to target areas with a smaller water risk.     

Potential net primary production footprint of agriculture: A global trade analysis

Agriculture is one of the most important sources of biomass for human society but increasingly contributes to anthropogenic degradation of ecosystems through negative impacts on biodiversity, ecosystem integrity, climate change, and ecosystem services. Here we estimate NPP_pot agricultural footprint, that is, the level of appropriation of potential net primary production (NPP_pot) by global cropland and human‐made pastures from the consumer responsibility (footprint) perspective and reveal the role of international trade. To quantify the NPP_pot agricultural footprint, we utilize environmentally extended multi‐regional input–output analysis to attribute the terrestrial potential NPP altered by global cropland and human‐made pastures to the final consumers responsible for pulling the supply chains. We identify the NPP_pot of geographically specific cropland area of 186 agricultural crops in 236 countries and we track each of those crops through the global web of international trade and supply chains to the point of final consumption. We show that human society appropriates 20% (13 petagrams of carbon per year) of global potential net primary production by the transformation of natural ecosystems into cropland and human‐made pastures. International trade accounts for 23% of global NPP_pot footprint of agriculture. While the two and half billion people living in China and India (the two countries with lowest NPP_pot agricultural footprint per capita) appropriate about 16% of the global NPP_pot agricultural footprint of cropland and human‐made pastures, the same share is appropriated by only 360 million people living in countries with the highest per capita footprint.     

Community Evolution in International Migration Top1 Networks

Focusing on each country’s topmost destination/origin migration relation with other countries, this study builds top1 destination networks and top1 origin networks in order to understand their skeletal construction and community dynamics. Each top1 network covers approximately 50% of the complete migrant network stock for each decade between 1960 and 2000. We investigate the community structure by implementing the Girvan-Newman algorithm and compare the number of components and communities to illustrate their differences. We find that (i) both top1 networks (origin and destination) exhibited communities with a clear structure and a surprising evolution, although 80% edges persist between each decade; (ii) top1 destination networks focused on developed countries exhibiting shorter paths and preferring more advance countries, while top1 origin networks focused both on developed as well as more substantial developing nations that presented a longer path and more stable groups; (iii) only few countries have a decisive influence on community evolution of both top1 networks. USA took the leading position as a destination country in top1 destination networks, while China and India were the main Asian emigration countries in top1 origin networks; European countries and the Russian Federation played an important role in both.     

On the robustness of update schedules in Boolean networks

Deterministic Boolean networks have been used as models of gene regulation and other biological networks. One key element in these models is the update schedule, which indicates the order in which states are to be updated. We study the robustness of the dynamical behavior of a Boolean network with respect to different update schedules (synchronous, block-sequential, sequential), which can provide modelers with a better understanding of the consequences of changes in this aspect of the model. For a given Boolean network, we define equivalence classes of update schedules with the same dynamical behavior, introducing a labeled graph which helps to understand the dependence of the dynamics with respect to the update, and to identify interactions whose timing may be crucial for the presence of a particular attractor of the system. Several other results on the robustness of update schedules and of dynamical cycles with respect to update schedules are presented. Finally, we prove that our equivalence classes generalize those found in sequential dynamical systems.     

Shared Cultural History as a Predictor of Political and Economic Changes among Nation States

Political and economic risks arise from social phenomena that spread within and across countries. Regime changes, protest movements, and stock market and default shocks can have ramifications across the globe. Quantitative models have made great strides at predicting these events in recent decades but incorporate few explicitly measured cultural variables. However, in recent years cultural evolutionary theory has emerged as a major paradigm to understand the inheritance and diffusion of human cultural variation. Here, we combine these two strands of research by proposing that measures of socio-linguistic affiliation derived from language phylogenies track variation in cultural norms that influence how political and economic changes diffuse across the globe. First, we show that changes over time in a country’s democratic or autocratic character correlate with simultaneous changes among their socio-linguistic affiliations more than with changes of spatially proximate countries. Second, we find that models of changes in sovereign default status favor including socio-linguistic affiliations in addition to spatial data. These findings suggest that better measurement of cultural networks could be profoundly useful to policy makers who wish to diversify commercial, social, and other forms of investment across political and economic risks on an international scale.