Category Archives: Networks

Networks

Cybernetics and philosphy of science

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As a systems scientist I am often frustrated by the narrow analysis of wicked problems. I’ve just started sociologist of Science, Andrew Pickering’s (author of the Mangle of Practice) new book, The Cybernetic Brain: Sketches of Another Future.

In The Cybernetic Brain Pickering aims to reposition systems science as framework for dealing with wicked problems. In the book he explores the work and approaches of British cyberneticians – the well known Ross Ashby and Stafford Beer as well others -arguing that their work shared a worldview that saw nature as full of novelty and not fully comprehensible – a worldview that has had a strong influence on resilience science.

In a review of Pickering’s new book in Science, Performance, Not Control, historian of biology Tara H. Abraham writes:

Why should we care about cybernetics? Pickering sees something vitally important in British cybernetics, and this explains the book’s subtitle. Put simply, cybernetic practice can be seen as a model for future practice. We are increasingly confronted with problems that require different solutions—the “exceedingly complex systems” that modern sciences cannot tackle. There are systems that surprise us, that fall outside of the framework of calculability and prediction. The aspect of cybernetics that is most important and compelling for Pickering is its assumption of an ontology of unknowability. The term captures, for Pickering, what was novel and important about what the British cyberneticians were doing. This unknowability and awesome complexity is not cause for despair—in fact there are ways that scientists can be constructive and creative in tackling such systems—and Pickering’s cyberneticians show us how. The author sees cybernetic science as fundamentally democratic: it forces us to have respect for the other, and it displaces the anthropomorphic stance we have on nature as a result of the dominance of modern sciences. Following political scientist James Scott’s list (2) of “high modernist” projects that “aim at the rational reconstruction of large swathes of the material and social worlds,” Pickering discusses the “dark side” of modernity. Here he includes projects that have had very disastrous consequences, such as the reform of agriculture with its effects on world famine and the effects of industrialization on global warming. It is in combating such projects—and the modernist attitude that fuels them—that Pickering sees the greatest merit in cybernetic ontology. It suggests that there is a way we might act differently. There is enormous value in adopting this different ontological stance, in which the world is not ours for the taking.

Networks

Tom Fiddaman comments on Eric Berlow’s talk

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System dynamics modeller Tom Fiddaman has some useful reflections on food web/network ecologist Eric Berlow’s TED talk, which I posted recently.

In his talk Berlow analyzes a causal loop diagram of the US military’s counterinsurgency efforts in Afghanistan.  On his blog MetaSD, Fiddaman writes :

I’m of two minds about this talk. I love that it embraces complexity rather than reacting with the knee-jerk “eeewww … gross” espoused by so many NYT commenters. The network view of the system highlights some interesting relationships, particularly when colored by the flavor of each sphere (military, ethnic, religious … ). Also, the generic categorization of variables that are actionable (unlike terrain) is useful. The insights from ecosystem simplification are potentially quite interesting, though we really only get a tantalizing hint at what might lie beneath.

However, I think the fundamental analogy between the system CLD [causal loop diagram] and a food web or other network may only partially hold. That means that the insight, that influence typically lies within a few degrees of connectivity of the concept of interest, may not be generalizable. Generically, a dynamic model is a network of gains among state variables, and there are perhaps some reasons to think that, due to signal attenuation and so forth, that most influences are local. However, there are some important differences between the Afghan CLD and typical network diagrams.

In a food web, the nodes are all similar agents (species) which have a few generic relationships (eat or be eaten) with associated flows of information or resources. In a CLD, the nodes are a varied mix of agents, concepts, and resources. As a result, their interactions may differ wildly: the interaction between “relative popularity of insurgents” and “funding for insurgents” (from the diagram) is qualitatively different from that between “targeted strikes” and “perceived damages.” I suspect that in many models, the important behavior modes are driven by dynamics that span most of the diagram or model. That may be deliberate, because we’d like to construct models that describe a dynamic hypothesis, without a lot of extraneous material.

Probably the best way to confirm or deny my hypothesis would be to look at eigenvalue analysis of existing models. I don’t have time to dig into this, but Kampmann & Oliva’s analysis of Mass’ economic model is an interesting case study. In that model, the dominant structures responsible for oscillatory modes in the economy are a real mixed bag, with important contributions from both short and longish loops.

Networks, Visualization

Mapping Australian arid land research

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Ryan McAllister and others use the network mapping methods of Martin Rosvall and Carl T Bergstrom (see previous post) to analyze the research impact of Australian arid lands literature in the paper –  McAllister et al. 2009.  Research impact within the international arid literature: An Australian perspective based on network theory.  Journal of Arid Environments 73(9) 862-871 (doi:10.1016/j.jaridenv.2009.03.014).

The figure below show the different research subfields McAllister et al. identified within arid lands research and the citation links among them.

Figure 4. Linkages between 21 partitions of the Australian arid literature (based on GN-Mod – see Table 7). Location of authoritative-hub articles (from Table 3): “Animal ecology” contains (Buckley et al., 1987) and (Morton and James, 1988), and Stafford Smith and Morton (1990); “Plant ecology” contains (Ludwig and Tongway, 1995), (Mabbutt and Fanning, 1987), (Montaña, 1992) and (Tongway and Ludwig, 1990), and Tongway et al. (1989); and “Geospatial” contains Pech et al. (1986).

Networks, Visualization

Mapping Science

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A nice 2008 PNAS paper Maps of random walks on complex networks reveal community structure (PNAS 105, 1118) [pdf] by Martin Rosvall and Carl T Bergstrom creates  beautiful and informative visualizations of citation networks in science (from 2004 ISI data) using a neat method for visualizing and analyzing complex networks.  Martin Rosvall has a created a website that enables the creation of similar maps of network data.

Figure 3. In Rosvall and Bergstrom 2008. A map of science based on citation patterns. Analysis of 6,128 journals connected by 6,434,916 citations were clustered into 88 modules and 3,024 directed and weighted links.

Figure 4. A map of the social sciences. The journals listed in the 2004 social science edition of Journal Citation Reports (32) are a subset of those illustrated in Fig. 3, totaling 1,431 journals and 217,287 citations.

Networks, Tools

Reading list: Using social network analysis (SNA) in social-ecological studies

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The emergent field that uses social network analysis (SNA) to analyze social-ecological systems and problems in natural resource management is growing. For those interested in reading into this field, I thought I share a reading list I am preparing for a PhD course on SNA that I will give at Arizona State University in connection to the Resilience 2011 Conference. The course is only open for ASU students, but for those interested you read more on my blog In Rhizomia [www.rhizomia.net]. If you are interested in discussing network analysis in social-ecological studies, there is, as I have mentioned before on this blog, an e-list called NASEBERRY that you can join (e-mail me at henrik.ernstson[AT]stockholmresilience.su.se and let me know).

Example of literature on SNA in NRM (to be completed and might change)

This is a selective reading list for those interested in starting to use social network analysis (SNA) in social-ecological studies.

The first good empirical study using social network analysis in the social-ecological field is by Schneider et al. (2003) on collaborative networks in estuary management. Together with Örjan Bodin and Beatrice Crona we summarized a set of arguments for the value of SNA for NRM studies in Bodin, Crona and Ernstson (2006), whereas a summary of empirical studies were made later (Bodin and Crona 2009). Christina Prell, Klaus Hubacek, Mark Reed and others have published on stakeholder selection and social learning (Prell et al. 2009), and Saduiel Ramirez-Sanchez has studied fisheries in Mexico (Ramirez-Sanchez and Pinkerton 2009). A good study for those interested in dynamic policy proceses is by Sandström and Carlsson (2008). An interesting application using 2-mode network analysis was recently made by Andrés Marín and Fikret Berkes on small-scale fisheris in Chile (Marín and Berkes 2010). (In an upcoming book edited by Bodin and Prell several of these authors are contributing with chapters, and some of our chapters might replace some of the articles in the final reading list of the course.)

One of the first urban applications using SNA in social-ecological studies was my study of social movements and the protection of urban ecosystems in Stockholm (Ernstson et al. 2008)(See also connection to cultural framing theory and qualitative data (using ANT) in Ernstson and Sörlin (2009).). This has lead to an articulation of “transformative collective action” in an upcoming chapter (Ernstson accepted). Together with collegues, we used social network theory to understand adaptive governance through synthesizing several urban case studies in Stockholm (Ernstson et al. 2010) that could be useful for all interested in multi-scale governance and social learning. An inspiration for me when it comes to urban areas, social movements and social networks has always bin Mario Diani (see e.g. Diani (1992), Diani and McAdam (2003), and Diani and Bison (2004). More urban social-ecological studies using SNA are forthcoming, partly as a result of when I gave this course in 2009 in Cape Town. Students from that .)

The above mentioned references can serve as entry point to the course (those marked with * below are less central), but should be complemented with the following from the SNA field: the short but effective review by Borgatti et al. (2009), the classic by Granovetter (1973), and the very useful SNA textbook and handbook to UCINET by Hanneman and Riddle (2005) (downloable for free, see below). Other good textbooks are Scott’s (2000) and Degenne and Forsé’s (1999). For those getting serious (!), a must-have is still the SNA “cookbook” by Wasserman and Faust (1994). The exact reading list might however still change.

References
(Those marked with * in the list indicates that you can initially skip these. Those marked with ** have notes at the end).

Bodin, Ö., B. Crona, and H. Ernstson. 2006. Social networks in natural resource management: What is there to learn from a structural perspective? Ecology and Society 11:r2. URL: http://www.ecologyandsociety.org/vol11/iss2/resp2/

Bodin, Ö. and B. I. Crona. 2009. The role of social networks in natural resource governance: What relational patterns make a difference? Global Environmental Change 19:366-374. URL: http://dx.doi.org/10.1016/j.gloenvcha.2009.05.002

Borgatti, S. P., A. Mehra, D. J. Brass, and G. Labianca. 2009. Network analysis in the social sciences. Science 323:892-895. [Longer pre-publication pdf version can be found on Stephen Borgatti’s homepage here.]

Crona, B. and Ö. Bodin. 2006. WHAT you know is WHO you know? Communication patterns among resource users as a prerequisite for co-management. Ecology and Society 11:7. URL: http://www.ecologyandsociety.org/vol11/iss2/art7/

**Degenne, A. and M. Forsé. 1999. Introducing Social Networks. Sage Publications, London. [Review for this book can be found here.]

*Diani, M. 1992. The concept of social movement. Sociological Review 40:1-25.

*Diani, M. and I. Bison. 2004. Organizations, coalitions and movements. Theory and Society 33:281-309.

*Diani, M. and D. McAdam, editors. 2003. Social Movements and Networks: Relational Approaches to Collective Action. Oxford University Press, Oxford.

Ernstson, H. accepted. Transformative collective action: a network approach to transformative change in ecosystem-based management. Page Ch 11 in Ö. Bodin and C. Prell, editors. Social Networks and Natural Resource Management: Uncovering the Social Fabric of Environmental Governance. Cambridge University Press, Cambridge.

Ernstson, H., S. Barthel, E. Andersson, and S. T. Borgström. 2010. Scale-crossing brokers and network governance of urban ecosystem services: The case of Stockholm, Sweden. Ecology and Society:in press.

*Ernstson, H. and S. Sörlin. 2009. Weaving protective stories: connective practices to articulate holistic values in Stockholm National Urban Park. Environment and Planning A 41:1460–1479.

Ernstson, H., S. Sörlin, and T. Elmqvist. 2008. Social movements and ecosystem services – the role of social network structure in protecting and managing urban green areas in Stockholm. Ecology and Society 13:39. URL: http://www.ecologyandsociety.org/vol13/iss2/art39/

Granovetter, M. 1973. The strength of weak ties. American Journal of Sociology 76:1360-1380.

**Hanneman, R. A. and M. Riddle. 2005. Introduction to Social Network Methods. University of California (published in digital form at http://faculty.ucr.edu/~hanneman/), Riverside, CA.

Marín, A. and F. Berkes. 2010. Network approach for understanding small-scale fisheries governance: The case of the Chilean coastal co-management. Marin Policy in press.

Prell, C., K. Hubacek, and M. Reed. 2009. Stakeholder Analysis and Social Network Analysis in Natural Resource Management. Society & Natural Resources 22:501-518.

Ramirez-Sanchez, S. and E. Pinkerton. 2009. The impact of resource scarcity on bonding and bridging social capital: the case of fishers’ information-sharing networks in Loreto, BCS, Mexico. Ecology and Society 14:22.

Sandström, A. and L. Carlsson. 2008. The performance of policy networks: the relation between network structure and network performance. Policy Studies Journal 36:497-524.

Schneider, M., J. Scholz, M. Lubell, D. Mindruta, and M. Edwardsen. 2003. Building consensual institutions: networks and the National Estuary Program. American Journal of Political Science 47:143-158.

**Scott, J. 2000. Social Network Analysis. A handbook. 2 edition. Sage Publications, London.

Wasserman, S. and K. Faust. 1994. Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge.

** As textbook, choose either Scott, or Degenne and Forsé. Hanneman and Riddle can also be used as a textbook, but is also an instructive manual for UCINET.

Download Hanneman and Riddle 2005 here (it’s freeware): http://faculty.ucr.edu/~hanneman/nettext/
Or here.

Short about the SNA course in Phoenix

Using Social Network Analysis in (Urban) Social-Ecological StudiesPhD course 6-8 March, 2011 at Arizona State University. Given by Dr Henrik Ernstson, African Centre for Cities, University of Cape Town, & Stockholm Resilience Centre, Stockholm University.

The course will start in January with reading and essay writing and then have three intense days in Phoenix, 6-8 March, 2011. The main aim is to help students to develop their own empirical case studies. I am not sure yet, but I believe the course will only be open to ASU students (having 10 participants).

Through this course you will:
– Learn about social network theory and methods
– Get the chance to develop your own case study
– Attain basic skills in analyzing empirical data with UCINET software
– Discuss how network analysis can be paired with qualitative methods and theories
– Discuss natural resource management and social-ecology from a network perspective

If you are an ASU student, you can apply through sending an e-mail to me (henrik.ernstson[AT]stockholmresilience.su.se).

More information on my blog In Rhizomia (SNA course).

[This post was originally posted on my blog In Rhizomia]

Networks, Visualization

Spread and mutation of panarchy

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The Database of the Self in Hyperconnectivity is a graphic created by Venessa Miemis a Media Studies student, who created the figure for a course project, to communicate different ways people interact with online information (there is also an interactive version).

She used Holling’s adaptive cycle, which she calls a panarchy (but because she misses the x-scale aspect its really an adaptive cyle) to identify contexts in which individuals act, but acknowledges this in a comment discussion.  Its interesting to see resilience thinking ideas pop up in other contexts.

I’m curious to the path by which panarchy moved into media studies (a quick google showed research in tagging classification systems using it) , and I wonder if any of the research on roles of people in environmental management done by Resilience Alliance researchers (e.g. in Panarchy book or Frances Westley, Per Olsson, and Carl Folke‘s work) was carried over with the concept.  However, there are no references and no explanation of how the figure was created, but she does link to an Ecology and Society paper.

Cities, Design, Ecosystem services, General, Networks, Visualization

Resilience meets architecture and urban planning

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by Matteo Giusti [contact: matteo.giusti [at] gmail.com]
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Does resilience thinking and architecture really mix? The answer is a clear “yes” if you ask urban planner Marco Miglioranzi, and Matteo Giusti, Master student at the Stockholm Resilience Centre. Together with the German based firm of architects N2M, they have developed two projects led by resilience concepts. Their first work, based on social-ecological systems, was preselected in the EuroPan10 competition. The second one, “A Resilient Social-Ecological Urbanity: A Case Study of Henna, Finland” with an emphasis on urban resilience, has been published by the German Academy for Urban and Regional Spatial Planning (DASL) and also featured by HOK –  a renowned global architectural firm.
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The project proposes a wide range of theoretical solutions based on urban resilience which find practical application in Henna’s (Finland) urban area. Governance networks, social dynamics, metabolic flows and built environment are separately analyzed to ultimately restore, and maintain over time, the equilibrium between human demands and ecological lifecycles.
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But the project also challenges current urban planning practices as it states the city’s  future requirements to be unknown. As a result, it identifies “the development-process as a dynamic flow instead of a static state”. Time scale for urban planning is therefore included within an evolving spatial design.
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Diagram of the parametric cell structure: reversible space layer (upper left) and reversible building layer (right)The project description elaborates: “As a result, the planning is not static anymore. It is not a blueprint, not a collection of architectural elements to create an hypothetic Henna out of the current mindsets and needs, but a multitude of tools, methods, opportunities, options, to define a sustainable developing strategy to meet future’s demands. We keep an eye on time, its complexity and we humbly admit we cannot foresee future; we can only provide guiding principles from current scientific understanding to define a social ecological urbanity capable of sustainably moving on with unique identity.”
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All these theoretical premises ends up in Henna’s planning. This includes an energetic smart grid based primarily on Enhanced Geothermal Systems (EGS); community-managed greenhouse areas to enhance food local self- reliance; low-diluted sewage system to reduce water consumption; efficient reuse of municipal solid waste to reach the Zero waste goal; and a problem solving centre to analyze ever-changing social ecological demands. Time is included in space, people in their natural environment, urban services in ecological processes. An harmonious cycle of growth and decays.
Networks, Vulnerability

Homer-Dixon on Risk, Uncertainty and Crises

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Think Globally Radio recently posted a number of great interviews. Here is one interesting one with political scientist, and renown author Thomas Homer-Dixon from University of Waterloo (Canada) – one of the world’s leading scholars on the intersection of environment, security and crisis.

Direct link to the interview can be found here.

Ecological Management, Networks, Visualization

Livelihood landscapes – disentangling occupational diversity for natural resource management

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A special contribution from Josh Cinner, from the ARC Centre of Excellence for Coral Reef Studies (see previous posts on his work here and here) and Örjan Bodin from the Stockholm Resilience Centre on their recent paper, Livelihood diversification in tropical coastal communities: a network-based approach to analyzing ‘livelihood landscapes’, which appeared in the August 11, 2010 issue of PLoS ONE, and is available free online.  They write:

In many developing countries, an individual household will often engage in a range of economic sectors, such as fishing, farming, and tourism. These diverse ‘livelihood portfolios’ are thought to help to spread risk and make households more resilient to shocks in a particular sector. Whether and how local people engage in multiple occupations has important implications for how people use and manage natural resources and is of particular relevance to people involved in managing natural resources. But for scientists, donors, and policy makers, unraveling the complexity of livelihoods in developing countries has been extremely challenging.

In our recent paper in PLoS ONE, we developed a novel method for exploring complex household livelihood portfolios.  We used a network-based approach to examine how the role of natural resource-based occupations changes along spectra of socioeconomic development and population density in 27 communities across 5 western Indian Ocean countries (see Fig. 1).

Figure 1. Kenyan livelihood landscape maps at various scales of social organization: a) Shela, Kenya; b) an aggregation of peri-urban sites in Kenya; c) an aggregation of rural sites in Kenya; d) all sites in Kenya.

In Figure 1 the links between occupations are indicated by arrows. The size of a node indicates the relative involvement in that occupational sector (larger node means more people are involved). The direction of the arrows indicates the priority of ranking. Thus an arrow into an occupation indicates that the occupation was ranked lower than the occupation the arrow came from. The thickness of the arrows corresponds to the proportion of households being engaged in the, by themselves, higher ranked occupation that are also engaged in the lower ranked occupation. The proportion of the node that is shaded represents the proportion of people that ranked that occupation as a primary occupation.

We found:

  • an increase in household-level specialization with development for most (but not all) occupational sectors, including fishing and farming, but that at the community-level, economies remained diversified.
  • We also found that households in less developed communities often share a common occupation, whereas that patterns is less pronounced in more developed communities. This may have important implications for how people both perceive and solve conflicts over natural resources.

Finally, our network-based approach to exploring livelihood portfolios can be utilized for many more types of analyses conducted at varying scales, ranging from small villages to states and regions.