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Land-use change is increasingly driven by global trade. The term "telecoupling" has been gaining ground as a means to describe how human actions in one part of the world can have spatially distant impacts on land and land-use in another. These interactions can, over time, create both direct and spatially distant feedback loops, in which human activity and land use mutually impact one another over great expanses. In this paper, we develop an analytical framework to clarify spatially distant feedbacks in the case of land use and global trade. We use an innovative mix of multi-regional input-output (MRIO) analysis and stochastic actor-oriented models (SAOMs) for analyzing the co-evolution of changes in trade network patterns with those of land use, as embodied in trade. Our results indicate that the formation of trade ties and changes in embodied land use mutually impact one another, and further, that these changes are linked to disparities in countries' wealth. Through identifying this feedback loop, our results support ongoing discussions about the unequal trade patterns between rich and poor countries that result in uneven distributions of negative environmental impacts. Finally, evidence for this feedback loop is present even when controlling for a number of underlying mechanisms, such as countries' land endowments, their geographical distance from one another, and a number of endogenous network tendencies.

We examine carbon trade imbalances among 172 countries over a 10-year period (2000–2010). A carbon trade imbalance refers to the extent to which the carbon emissions embodied in a country's exports exceeds the emissions embodied in its imports. Although past research has considered how such imbalances coincide with variances in wealth and/or trade patterns, none have considered how such imbalances arise in the context of an evolving network structure. In this paper, we consider trade networks and carbon trade imbalances as co-evolving phenomena, and study these using an innovative combination of multi-regional input–output (MRIO) analysis with stochastic actor-oriented models (SAOMs). Our findings both challenge and support arguments made by ecological unequal exchange theory and the Gravity Model, and highlight the role emerging economies play in shaping network structure and the distribution of carbon trade balances overtime.

We examine distributions of pollution and wealth among countries over a 20 year period. We distinguish between pollution produced within a country and pollution triggered along global supply chains by a country's consumption. We explain pollution and wealth distributions via network characteristics. Our findings show a positive, (log-) linear relationship between a country's network position and both ways of accounting for pollution. In addition, core countries and/or ones with higher numbers and volume of export ties increase their shares of global wealth faster than shares of pollution.

Incentive-based models for network formation link micro actions to changes in network structure. Sociologists have extended these models on a number of fronts, but there remains a tendency to treat actors as homogenous agents and to disregard social theory. Drawing upon literature on the strategic use of networks for knowledge gains, we specify models exploring the co-evolution of networks and knowledge gains. Our findings suggest that pursuing transitive ties is the most successful strategy, as more reciprocity and cycling result from this pursuit, thus encouraging learning across the network. We also discuss the role of network size, global network structure, and parameter strength in actors’ attainment of knowledge resources.

In this article, we track how consumption in the United States, a highly developed “core” country, triggers value added and carbon inequalities around the globe. We consider these two sources of inequality for all commodities and services consumed in the United States, and then for three specific sectors, these being electronics, motor vehicles, and wearing apparel. Our findings show how the production of commodities for U.S. consumption tends to reify inequalities between countries. Larger shares of value added (in comparison to shares of carbon emissions) are generally experienced by more-developed, more-integrated countries, whereas the opposite tendency is experienced in less-developed, less-integrated regions. We note how these between-country differences can depend on the product chains that are analyzed. Our article makes use of a novel combination of social network analysis and multiregional input-output analysis to better capture some intuitive ideas of global trade and its consequences.

We examine carbon emission transfers via trade among countries over a 20-year period. A net transfer of carbon emission means that the emission embodied in a country’s imports exceeds the emission embodied in exports. We consider a number of socio-economic drivers to explain variations in such net transfers across countries. Our findings show a U-shaped curvilinear relationship between countries’ GDP per capita and their net carbon transfer, suggesting that countries are typically heavy net importers of carbon in early phases of economic development, become balanced or even net exporters of carbon in middle stages of development, and then return to being heavy net importers of carbon in later stages of development. We reflect on these findings in the context of ecological modernization (EM) and ecological unequal exchange (EUE) theories, as well as the environmental Kuznets curve (EKC) hypothesis.

Economic globalisation refers to flows of trade and capital among and between countries. A critical view on economic globalisation is that the historical forces influencing how and when a given country becomes integrated into global trade (and the world economy as a whole) condition the potential paths of development open to that country (e.g., Ref. [1]). Here, trade and other relations between countries act as structural mechanisms enabling wealthier, more core countries to maintain favourable terms of trade, which, in turn, negatively impact less developed, more peripheral ones in a variety of ways [2, 3].

Although research has shown that countries’ world-systems positions can predict levels of pollution and wealth, there has been little research looking at how consumption in the core triggers both pollution and wealth elsewhere in the world economy. In this article, we track how consumption in the United States, a core country, triggers value added and pollution throughout global commodity chains. We track these distributions for all commodities and services consumed in the United States, then for six commodity groupings, and finally for two case studies, “Motor Vehicles” and “Wearing Apparel.” Our findings show how the production of commodities for US consumption tends to reify inequalities in the world-system: Larger shares of value added (in comparison to shares of pollution) are generally prompted within the core, whereas the opposite effect tends to be experienced in the non-core. We also discuss interesting exceptions to these general trends occurring at different levels of analysis. Finally, we draw special attention to China, the elephant in the room that exhibits both core and peripheral characteristics.

Peak Oil, which refers to the maximum possible global oil production rate, is increasingly gaining attention in both science and policy discourses. However, little is known about how this phenomenon will impact economies, despite its apparent imminence and potential dangers. In this paper, we construct a vulnerability map of the U.S. economy, combining two approaches for analyzing economic systems, i.e. input–output analysis and social network analysis (applied to economic data). Our approach reveals the relative importance of individual economic sectors, and how vulnerable they are to oil price shocks. As such, our dual-analysis helps identify which sectors, due to their strategic position, could put the entire U.S. economy at risk from Peak Oil. For the U.S., such sectors would include Iron Mills, Fertilizer Production and Transport by Air. Our findings thus provide early warnings to downstream companies about potential ‘trouble’ in their supply chain, and inform policy action for Peak Oil. Although our analysis is embedded in a Peak Oil narrative, it is just as valid and useful in the context of developing a climate roadmap toward a low carbon economy.

International audience; Spatially diverse trends in population growth, climate change, industrialization, urbanization and economic development are expected to change future food supply and demand. These changes may affect the suitability of land for food production, implying elevated risks especially for resource-constrained, food-importing countries. Wepresent the evolution of biophysical redundancy for agricultural production at country level, from 1992 to 2012. Biophysical redundancy, defined as unused biotic and abiotic environmental resources, is represented by the potential food production of `spare land', available water resources (i.e., not already used for human activities), as well as production increases through yield gap closure on cultivated areas and potential agricultural areas. In 2012, the biophysical redundancy of 75 (48) countries, mainly in North Africa, Western Europe, the Middle East and Asia, was insufficient to produce the caloric nutritional needs for at least 50% (25%) of their population during a year. Biophysical redundancy has decreased in the last two decades in 102 out of 155 countries, 11 of these went from high to limited redundancy, and nine of these from limited to very low redundancy. Although the variability of the drivers of change across different countries is high, improvements in yield and population growth have a clear impact on the decreases of redundancy towards the very low redundancy category. We took a more detailed look at countries classified as `Low Income Economies (LIEs)' since they are particularly vulnerable to domestic or external food supply changes, due to their limited capacity to offset for food supply decreases with higher purchasing power on the international market. Currently, nine LIEs have limited or very low biophysical redundancy. Many of these showed a decrease in redundancy over the last two decades, which is not always linked with improvements in per capita food availability.

Social capital's rise in popularity is a phenomenon many have noted (Kadushin, 2006; Warde and Tampubolon, 2002; Portes, 1998). Although the concept is a relatively old one, it is the works of Bourdieu (1986), Coleman (1988; 1990), and Putnam (1993, 2000) that often get credited for popularizing the concept. These three, while sharing a view that social networks are important for social groups and society, place differing levels of emphasis on the role of networks in building trust or the exchange of various types of resources. In this paper, I briefly revisit these three theorists, and the criticisms each have received, to provide background for discussing recent research on social capital from a social networks approach. The social network approach is then applied to my own case study looking at the relations among not-for-profits, and special attention is given to the unique context of not-for-profits, and how this context might elaborate or challenge current thoughts on social, aka ‘network’ capital. A final discussion is also given to some measurement problems with the network approach to social capital.