Fresh fruit, virtual land, and conference ribbons: what can we learn from a network perspective?Kelly Hondula, Natalie Yee ·
Kelly Hondula, Natalie Yee
After learning about how to construct and interpret social network data sets the previous week, the MEES Coupled Human and Natural Systems class spent a week delving into understanding the types of questions that social and natural scientists investigate using network analysis. We explored social networks of communication, global trade networks, and multi-level networks through discussion of three recent publications about the theory and application of social network analysis (Bodin et al 2016, Prell and Lo 2016, Prell et al. 2017). Each of these three frameworks tackled very different types of networks, but each presented opportunities for the class to reflect on how the structure and behavior of networks both influences, and are influenced by, our everyday activities.
1. Social networks of individuals
Perhaps the most ubiquitous conceptualization of networks is of individual people, joined by their communication ties or personal relationships. In this framework, people are the nodes in a network and the links are their relationships, for example how frequently any two individuals contact each other. This is the basis of the approach taken by Jasny et al (2015) to evaluate key actors in the US climate policy network, where they found that high levels of transitivity amplify partisanship when it comes to communicating information about climate change science.
The implications about transitivity in the work by Drs. Prell and Lo (2016) became immediately apparent to our lives as graduate students, as the class wondered whether and how to put into practice the results of this modeling study. One of the surprising findings was that in order to maximize the amount of knowledge gained in forming new ties in a network, pursuing experts was not as successful of a strategy as pursuing a transitive strategy, or seeking out ties with friends of friends.
We imagined how this strategy could play out in the context of a young graduate student navigating a scientific conference: how much time and energy should he or she spend trying to meet luminaries in their field? Should they seek out meetings only with award winners and ribbon-bearers? Is it best to try to get a mutual friend to offer an introduction?
2. Global trade networks
Another framework for network analysis is to investigate connections between geopolitical units like countries through their trade flows. In this type of analysis, countries (or cities, states, or regions) are the nodes in the network, and links represent the existence or magnitude of exports and imports between countries. Even though this network is global in scale, its implications are apparent to consumers based on the selection of produce available in grocery stores. Trends in trade data from the USDA show how increased globalization over recent decades has expanded options for US consumers—our diets are no longer restricted by which foods are in season locally!
Dr. Prell and colleagues used this type of trade network data to identify a positive feedback between a country’s land use patterns and its position in global network hierarchies, where “land exporters” form ties with wealthier countries, and those ties are then reinforced over time to maintain land-intensive export trade flows to wealthy countries. This type of research is emblematic of a field of study that investigates globalization through the flows of “virtual” goods that are embodied in international trade. Although land isn’t physically being transported or shipped overseas, the land dedicated to producing those goods that do get exported can be considered a telecoupling represented by that trade flow. This type of analysis has been applied to investigating virtual water (D’Odorico et al 2010), virtual groundwater (Marston et al 2015), seafood trade (Gephart and Pace 2015), and embodied nutrients (Leach et al 2012).
While it may be easy to recognize globalization’s impact on our choices, as consumers we often have little reliable information about how specific purchasing habits contribute to or reinforce global inequities, injustices, or unsustainable practices with which we might disagree, especially when strapped for time and money. Although price was considered the overriding factor that we use to make purchasing decisions as consumers, many people in the class also identified priorities related to ethical treatment of people and animals in the production of goods, the durability and quality of goods, and other factors that are linked to global inequalities and sustainability practices. Some new practices and technologies can enable consumers to reflect ethical values in consumption patterns, such as voluntary certification schemes and data-based guidelines.
3. Coupled multi-level networks
One of the newest frameworks for network analysis attempts to bring together networks of social and ecological systems. Bodin et al. (2016) proposed using multi-level networks to bridge the perspectives from natural and social sciences to analyze complex social-ecological networks.
One example applying this framework is the work of SESYNC postdoc Steven Alexander, who studies social-ecological networks in the Caribbean. He uses this multi-level approach to relate the trophic structure of fisheries to the communication networks of fishermen, to investigate the relationship between governance and ecological outcomes of fisheries.
An interesting discussion emerged about the various ways that ecological systems can be conceptualized as networks—what are the discrete entities out in nature? Depending on the question and context, it became obvious that there were numerous ways to think about natural systems as networks, beyond species interactions and trophic levels. In fact, one of the earliest conceptualizations of an ecosystem by limnologist RL Lindemann is certainly representative of a network!
For all three frameworks, it was clear that network structures can be both drivers and outcomes of processes in coupled human and natural systems. Although it takes some work to conceptualize the boundaries, entities, and definitions of each network component, a network perspective is a fruitful avenue for investigating the structure and dynamics of these systems.
- Alexander, S., 2015. The ties that bind: Connections, patterns, and possibilities for marine protected areas. UWSpace. http://hdl.handle.net/10012/10025
- Bodin, Ö., Robins, G., McAllister, R., Guerrero, A., Crona, B., Tengö, M. and Lubell, M., 2016. Theorizing benefits and constraints in collaborative environmental governance: a transdisciplinary social-ecological network approach for empirical investigations. Ecology and Society, 21(1).
- D'Odorico, P., Laio, F. and Ridolfi, L., 2010. Does globalization of water reduce societal resilience to drought?. Geophysical Research Letters, 37(13).
- Jasny, L., Waggle, J. and Fisher, D.R., 2015. An empirical examination of echo chambers in US climate policy networks. Nature Climate Change, 5(8), pp.782-786.
- Gephart, J.A. and Pace, M.L., 2015. Structure and evolution of the global seafood trade network. Environmental Research Letters, 10(12), p.125014.
- Leach, A.M., Galloway, J.N., Bleeker, A., Erisman, J.W., Kohn, R. and Kitzes, J., 2012. A nitrogen footprint model to help consumers understand their role in nitrogen losses to the environment. Environmental Development, 1(1), pp.40-66.
- Leach, A.M., Emery, K.A., Gephart, J., Davis, K.F., Erisman, J.W., Leip, A., Pace, M.L., D’Odorico, P., Carr, J., Noll, L.C. and Castner, E., 2016. Environmental impact food labels combining carbon, nitrogen, and water footprints. Food Policy, 61, pp.213-223.
- Lindeman, R.L., 1942. The trophic‐dynamic aspect of ecology. Ecology, 23(4), pp.399-417.
- Marston, L., Konar, M., Cai, X. and Troy, T.J., 2015. Virtual groundwater transfers from overexploited aquifers in the United States. Proceedings of the National Academy of Sciences, 112(28), pp.8561-8566.
- Prell, C. and Lo, Y.J., 2016. Network formation and knowledge gains. The Journal of Mathematical Sociology, 40(1), pp.21-52.
- Prell, C., Sun, L., Feng, K., He, J. and Hubacek, K., 2017. Uncovering the spatially distant feedback loops of global trade: A network and input-output approach. Science of Total Environment. (in press).