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In our globalized economy, the consumption of goods and services induces economic benefits but also environmental pressures and impacts around the world. Consumption levels are especially high in the current 27 member countries of the European Union (EU), which are some of the wealthiest economies in the world. Here, we determine the global distribution of ten selected environmental pressures and impacts, as well as value added induced by EU consumption from 1995 to 2019. We show that large shares of all analysed environmental pressures and impacts are outsourced to countries and regions outside the EU, while more than 85% of the economic benefits stay within the member countries. But there is also uneven distribution of costs and benefits within the EU. Over the analysed period, pressures and impacts induced by EU consumption largely decreased within the EU but increased outside its borders. We show that Eastern European neighbours of the EU experienced the highest environmental pressures and impacts per unit of GDP associated with EU consumption. The findings of this research add to the discussions on outsourcing environmental pressures and impacts and highlight the need for a reduction of pressures and impacts induced by EU consumption.

Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human–environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.

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.

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.

"What is social structure, and how does it influence the views and behaviors of land managers? In this paper, we unpack the term 'social structure' in the context of current research on institutions, social networks, and their role(s) in resource management. We identify two different kinds of structure, formal and informal, and explore how these link to views of land management and management practice. Formal structures refer to intentionally designed organizations that arise out of larger institutional arrangements; informal ones refer to social networks, based on the communication contacts individuals possess. Our findings show significant correlations between respondents' views regarding land management and their social networks; it is these informal structures that have greater influence on what stakeholders perceive. These findings suggest that stakeholders are less influenced by their particular organizational affiliation or category (e.g., 'conservationist' versus 'farmer'), and more by whom they speak with on a regular basis regarding land management. We conclude with a discussion on the practical implications for resource managers wishing to 'design' participatory management, arguing that, if 'diversity' is the goal in designing such participatory processes, then diversity needs to translate beyond stakeholder categories to include consideration for the personal, social networks surrounding stakeholders."

Adaptive management has the potential to make environmental management more democratic through the involvement of different stakeholders. In this article, we examine three case studies at different scales that followed adaptive management processes, critically reflecting upon the role of stakeholder participation in each case. Specifically, we examine at which stages different types of stakeholders can play key roles and the ways that each might be involved. We show that a range of participatory mechanisms can be employed at different stages of the adaptive cycle, and can work together to create conditions for social learning and favorable outcomes for diverse stakeholders. This analysis highlights the need for greater reflection on case study research in order to further refine participatory processes within adaptive management. This should not only address the shortcomings and successes of adaptive management as a form of democratic environmental governance, but should also unpack the links between science, institutions, knowledge, and power.

International audience; The relationship between network structure and dynamics is one of the most extensively investigated problems in the theory of complex systems of recent years. Understanding this relationship is of relevance to a range of disciplines—from neuroscience to geomorphology. A major strategy of investigating this relationship is the quantitative comparison of a representation of network architecture (structural connectivity, SC) with a (network) representation of the dynamics (functional connectivity, FC). Here, we show that one can distinguish two classes of functional connectivity—one based on simultaneous activity (co-activity) of nodes, the other based on sequential activity of nodes. We delineate these two classes in different categories of dynamical processes—excitations, regular and chaotic oscillators—and provide examples for SC/FC correlations of both classes in each of these models. We expand the theoretical view of the SC/FC relationships, with conceptual instances of the SC and the two classes of FC for various application scenarios in geomorphology, ecology, systems biology, neuroscience and socio-ecological systems. Seeing the organisation of dynamical processes in a network either as governed by co-activity or by sequential activity allows us to bring some order in the myriad of observations relating structure and function of complex networks.