Category Archives: Networks

Links: writing, activism, First Nations, Arctic, immigration, and walking

A selection of links I found interesting from around the web

1)  How to write about your science from SciDev.Net

2) Rob Hopkins from Transition Towns writes about the tension between creating change and activism in Transition and activism: a response on Transition Culture.

3) How the distant and dispersed people of Canada’s First Nations are using Facebook from Vancouver’s the Tyee.

4) How climate change will increase coastal accessibility but decrease accessibility to the interior of the Arctic by cutting ice roads.  Toronto Globe and Mail reports on new research in Nature Climate Change (doi:10.1038/nclimate1120).

5) Why more immigration means less crime.  The Walrus reports on how immigration lowers crime rates in Canadian communities in an article Arrival of the Fittest.

6) The Globe and Mail reports on how in Toronto carless recent immigrants are producing a more walkable environment.

Three new positions in ecosystem services research at McGill University

We’re looking to hire three new people to join our team working on the role of landscape structure and biodiversity in the provision of ecosystem services. The new positions include a postdoc to work on developing models of ecosystem services, a PhD position in historical ecosystem ecology,  and a (part time) project manager. We’re working in the Montérégie, a lovely agricultural landscape just southeast of Montreal.

For more about the project, check out our website:

Here’s more detail on each of the three positions:

Postdoctoral researcher

We are seeking an outstanding postdoctoral researcher to be a part of a dynamic multi-lab team that is mapping and modeling past, present, and future provision of biodiversity and ecosystem services in the agricultural landscape around Montréal. The primary research project would involve synthesizing historical and current geospatial data to evaluate how landscape configuration effects the provision of ecosystem services in this region. This analysis will inform the development a spatial model of the provision of ecosystem services under different land use/land cover configurations in the greater Montreal region.

A successful candidate will have a PhD in a related field (e.g., Geography, Ecology); experience with ecosystem modeling techniques, including GIS and computer programming; and be familiar with the literature on ecosystem services. The applicant should have a good publication record and a demonstrated ability to work independently and as part of a large team. Capacity to read and speak French is a plus.

The successful applicant would be primarily based in the lab of Dr. Elena Bennett at McGill’s Macdonald Campus, but would also be supervised by the co-PIs on the project, including Dr. Jeanine Rhemtulla (Geography), Dr. Andrew Gonzalez (Biology), and Dr. Martin Lechowicz (Biology). An office on McGill’s downtown campus will also be provided. Salary will be $35,000 per annum plus standard McGill benefits. We encourage applicants of all nationalities to apply.

Applicants should submit a CV, a statement detailing how their research interests align with the focus of the project, and the names and contact information for three references. Start date is targeted for January 2012. Please submit applications by September 1, 2011 to: Elena Bennett (elena dot bennett at mcgill dot ca)

PhD Student in Historical Ecosystem Ecology

We are seeking a PhD student interested in historical ecology, landscape ecology, and ecosystem services to be a part of a dynamic multi-lab team that is mapping and modeling past, present, and future provision of ecosystem services in the agricultural landscape around Montreal. The student’s project would involve examining historical records to estimate past provision of ecosystem services, interpretation of historical air photos and other maps, and modeling relationships between land use, spatial configuration, and ecosystem services through time. There is considerable room for a student to develop their own project within these general parameters.

A successful candidate should have an MSc degree in a related field, experience with GIS, remote sensing, or other ecosystem modeling techniques, and an ability to work independently and as part of a large team. Ability to read and speak French is a plus.

The successful applicant could be a PhD student in either Geography or Natural Resource Sciences at McGill University and would be co-supervised by Dr. Elena Bennett and Dr. Jeanine Rhemtulla. McGill University, located in Montreal, QC, is one of Canada’s top universities and boasts a large international student population.

Applicants should submit a CV, a statement of research interests, a copy of their transcripts, and the names and contact information for two references. Start date is targeted for Fall 2012. Please submit applications to: Jeanine Rhemtulla and Elena Bennett (jeanine dot rhemtulla at mcgill dot ca) and (elena dot bennett at mcgill dot ca)

Project Manager (Part Time)

We are seeking an organized, energetic, and enthusiastic project manager for a new project about biodiversity, connectivity, and ecosystem services in the settled landscapes of the greater Montreal region. The project involves a large team of professors and their students (~30 people total) working on both the fundamental and applied aspects of this research. Our project seeks to understand how past and future land use change will affect habitat connectivity, biodiversity, and the provision of multiple ecosystem services. Policy makers and managers often must make decisions with limited rigorous information about how to manage for sustainable landscapes. In order to improve the link between science and decision making our project includes actively engaged partners from local cities, counties, NGOs, as well as regional and provincial government. Our research will improve both the science and decision-making required to manage for sustainable and resilient landscapes.

Project management would include:

  • Managing the activities and people associated with the project and ensure that we are meeting project goals
  • Ensure communication across the researchers involved with the project
  • Management of GIS data central to the project, creation of geodatabases
  • Coordinating and tracking the project budget
  • Maintaining communication with our project partners
  • Identify opportunities for improving and enhancing the project

We seek a project manager who is self-motivated, extremely organized, and has experience running a major research project or managing a research team. Because the project manager would also have a role in managing geodatabases for the project, experience with GIS and geodatabase management is also important. A graduate degree (M.Sc. or PhD) in environmental sciences would be an advantage. The position will involve considerable communication with our local management partners, so the successful applicant must be bilingual (French/English).

We envision a part-time (up to 3 days/week) position with a salary of approximately $20,000 per annum.

Applicants should submit a CV, a statement of interests and experience, and contact information for three references. Start date is targeted for Fall 2011. Please submit applications by July 1, 2011 to: Elena Bennett (elena dot bennett at mcgill dot ca)

Information and communication technologies in the Anthropocene

UPDATED: Slides from the talks at the end of this blogpost

The use of social media for political mobilization during the political uprisings in Northern Africa and the Middle East during 2010 and 2011; digital coordination of climate skeptic networks during “Climategate” in 2010; and the repercussions of hackers in carbon markets the last years. These are all examples of intriguing phenomena that take place at the interface between rapid information technological change, and the emergence of globally spanning virtual networks.

Exactly how information and communication technologies affect the behavior of actors at multiple scales, is of course widely debated. The question is: how do we make sense of these changes, from a wider resilience perspective?

Some of these discussions took place at the 2011 Resilience conference in Arizona in a panel convened by us at the Stockholm Resilience Centre, and with generous support from the International Development Research Centre (IDRC, Canada). Ola Tjornbo from Social Innovation Generation (SIG) at the University of Waterloo, explored some of the opportunites, but also profound challenges, related in trying to design effective virtual deliberation processes. Ola noted that while several success stories related to crowd-sourcing (Wikipedia) and collective intelligence (e.g. Polymath) do exist, we have surprisingly little systematic knowledge of how to design digital decision-making processes that help overcome conflicts of interest related to issues of sustainability. Some if these issues are elaborated by SiG, and you can find videos from an interesting panel on “Open Source Democracy” here.

Richard Taylor from SEI-Oxford presented a rapidly evolving platform for integration and dissemination of knowledge on climate adaptation – weADAPT. This platform combines the strengths of a growing community of climate adaptation experts, a database of ongoing local climate adaptation projects, semantic web technologies, and a Google Earth interface. The visualizations are stunning, and provide and interesting example of how ICTs can be used for scientific communication.

Angelica Ospina from the Centre of Development Informatics at the University of Manchester, showcased some ongoing work on mobile technologies and climate adaptation resilience. As Ospina noted, ICTs can provide some very tangible support for various features of resilience, ranging from self-organization, to learning and flexibility. You can find a working paper  by Angelica here.

To summarize: three very different yet complementary perspectives on how ICTs could be harnessed in the Anthropocene: by building new types of virtually supported decision making and collective intelligence processes; linking expert communities and local natural resource management experimentation together; and by exploring the resilience building strengths of decentralized mobile technologies.

Slides from the talks

Victor Galaz (intro)

Ola Tjornbo

Richard Taylor

Steven Johnson on the source of good ideas

Two short videos by science writer Steven Johnson on his book Where good ideas come from: the natural history of innovation.

An animated promotional video for his book:

And him giving a TED talk.

Steve Johnson has posted some of the responses to his ideas on his blog.

I haven’t read the book, but complex systems scientist Cosma Shalizi has a rich review that addresses many of the books strengths and weaknesses.  He introduces the book as:

This is 100-proof American evolutionist, naturalistic liberalism, which is to say, Pragmatism. It is a celebration of the virtues of openness, experimentation (including failed experiments), giving “slow hunches” chances to develop, to serendipitously blending ideas from diverse intellectual backgrounds and disciplines, and the continuity of human culture and thought with processes in the natural world. It’s a view of the social life of the mind, illustrated by engagingly-told anecdotes from the history of science and technology; apt references to a wide range of scholarly studies; long, admiring quotations from Darwin; the natural history of coral reefs and the evolution of sexual reproduction. (The broader history of culture, especially the fine arts, is occasionally alluded to, and there are abundantly merited plugs for his old teacher Franco Moretti’s studies on the evolution of genres and “distant reading”; but mostly it’s a science-and-technology book.) Johnson has painted a crowd scene: good ideas hardly ever come from isolated individuals thinking very hard and having flashes of inspiration; they come from people who are immersed in communities of inquiry, and especially from those who bridge multiple communities. The picture is an attractive one, which I actually think (or perhaps “fervently pray”) has a lot of truth to it.

Impacts of the 2010 tsunami in Chile

UPDATE: Here is a link to a video to Prof. Castilla’s talk (via @sthlmresilience)

03:34 a.m. February 27th 2010. Suddenly, a devastating earthquake and a series of tsunamis hits the central–south coast of Chile. An earthquake so powerful (8.8 on the moment magnitude scale), that not only is the fifth largest recorded on earth, but also moves the city of Buenos Aires in Argentina, 10 feet (!) to the west.

Juan Carlos Castilla from the Pontificia Universidad Católica de Chile, recently visited Stockholm, and gave an update about the tsunamis’ impact on coastal communities. The effects of the tsunami were devastating, and the death toll from the 2-3 tsunamis alone was between 170-200 in the coastal areas of regions VI, VII and VIII. The most noticeable biophysical impact in the region is the elevation of the whole coastal area, ranging from 1.5 to 3 meters. This obviously has had big impacts on the composition of species and vegetation on the coast. The impacts on coastal ecosystems and fisheries is however still unclear.

Based on extensive field studies two months after the disaster, Castilla and his research team noted that only 8-12 (about 6%) of the 200 deceased where from fisherman families. According to Castilla, this low figure can be explained by the existence of strong social networks, and local knowledge passed on from generation to generation. As an artisan fisherman in the study, summarized one shared local saying:

“if an earthquake is so strong you can not stand up: run to the hills”

Luckily, February 27th was a night of full moon. This allowed people to more easily run for protection in the hills. According to Castilla, the combination of full moon, local knowledge, and strong bonds between neighbors, made it possible for members of fishermen communities to rapidly act on the first warning signal: the earthquake. The fact that locals also were taught not to leave the hills after at least a couple of hours after an earthquake, also helped them avoid the following devastating tsunamis. Unfortunately, visitors and tourists in the tsunami affected coastal areas, were not.

Read more:

Marín, A et al. (2010) ”The 2010 tsunami in Chile: Devastation and survival of coastal small-scale fishing communities”, Marine Policy, 2010, 34:1381-1384.

Gelchich, S et al. “Nagivating transformations in governance of Chilean marine coastal resources”, PNAS, 107(39): 16794-16799.

See Henrik’s post just the days after the Chilean earthquake here.

Seed’s global reset on tipping points and systematic risk

Seed magazine has a special issue on new approaches to interconnected and complex challenges. It also features interesting articles on TEEB and ecological economics, new modes of science, forecasting, tipping points and systematic risk.  As well as,  Carl Folke’s article on resilience, which I mentioned previously.

Economist Ian Goldin writes on On Systemic risks

Systemic risk is the underbelly of globalization and technical change. Intense integration of markets, trade, and finance has accompanied the latest tidal wave of globalization, facilitated by seismic policy shifts, like those associated with the fall of the Soviet Union, the formation of the European Union, and the opening of emerging economies. Between 1980 and 2005, global foreign-investment flows increased 18 times, and trade flows increased more than sevenfold, reflecting unprecedented integration.

… While the term “systemic risk” has historically referred mainly to collapses in finance, recent decades of globalization have created new and broader risks. There has been an exponential increase in the number of nodes and pathways through which materials, capital, information, and knowledge can be transmitted at lightning speeds and with global reach. These networks also have the potential to create and propagate risk. Interconnectedness, networks’ central property, can lead simultaneously to greater robustness and more fragility. Risk can decline as connectivity increases because as risk sharing increases, so does the number of nodes and links. This is true of financial systems, manufacturing services, intellectual property, and ecosystems. However, increased fragility is also a concern. Once a tipping point is triggered past its threshold, connectivity can amplify and spread risk instead of sharing it stably.

Looming systemic risks include pandemics, which may spread more rapidly across a densely connected world, and bio-terrorism risks, which are likely to become increasingly systemic in the 21st century. The ability to produce biological and other weapons of mass destruction is becoming more widespread, especially among non-state actors, due to technological innovation (not least with the development of DNA synthesizers). Increases in population density, urbanization, and the growth of connectivity, both physically and virtually, means that dangerous recipes and panic can be instantaneously transmitted globally. And climate change, a silent tsunami that crept up on us, presents major systemic environmental, social, and economic risks to humanity.

In an article On Early Warning Signs of tipping points ecologist George Sugihara writes:

A key phenomenon known for decades is so-called “critical slowing” as a threshold approaches. That is, a system’s dynamic response to external perturbations becomes more sluggish near tipping points. Mathematically, this property gives rise to increased inertia in the ups and downs of things like temperature or population numbers—we call this inertia “autocorrelation”—which in turn can result in larger swings, or more volatility. In some cases, it can even produce “flickering,” or rapid alternation from one stable state to another (picture a lake ricocheting back and forth between being clear and oxygenated versus algae-ridden and oxygen-starved). Another related early signaling behavior is an increase in “spatial resonance”: Pulses occurring in neighboring parts of the web become synchronized. Nearby brain cells fire in unison minutes to hours prior to an epileptic seizure, for example, and global financial markets pulse together. The autocorrelation that comes from critical slowing has been shown to be a particularly good indicator of certain geologic climate-change events, such as the greenhouse-icehouse transition that occurred 34 million years ago; the inertial effect of climate-system slowing built up gradually over millions of years, suddenly ending in a rapid shift that turned a fully lush, green planet into one with polar regions blanketed in ice.

The global financial meltdown illustrates the phenomenon of critical slowing and spatial resonance. Leading up to the crash, there was a marked increase in homogeneity among institutions, both in their revenue-generating strategies as well as in their risk-management strategies, thus increasing correlation among funds and across countries—an early warning. Indeed, with regard to risk management through diversification, it is ironic that diversification became so extreme that diversification was lost: Everyone owning part of everything creates complete homogeneity. Reducing risk by increasing portfolio diversity makes sense for each individual institution, but if everyone does it, it creates huge group or system-wide risk. Mathematically, such homogeneity leads to increased connectivity in the financial system, and the number and strength of these linkages grow as homogeneity increases. Thus, the consequence of increasing connectivity is to destabilize a generic complex system: Each institution becomes more affected by the balance sheets of neighboring institutions than by its own. The role of systemic risk monitoring, then, could simply be rapid detection and dissemination of potential imbalances, much as we allow frequent underbrush fires to burn in order to forestall catastrophic wildfires. Provided that these kinds of imbalances can be rapidly identified, maybe we will need no regulation beyond swift diffusion of information. Having frequent, small disruptions could even be the sign of a healthy, innovative financial system.

Further tactical lessons could be drawn from similarities in the structure of bank payment networks and cooperative, or “mutualistic,” networks in biology. These structures are thought to promote network growth and support more species. Consider the case of plants and their insect pollinators: Each group benefits the other, but there is competition within groups. If pollinators interact with promiscuous plants (generalists that benefit from many different insect species), the overall competition among insects and plants decreases and the system can grow very large.

Relationships of this kind are seen in financial systems too, where small specialist banks interact with large generalist banks. Interestingly, the same hierarchical structure that promotes biodiversity in plant-animal cooperative networks may increase the risk of large-scale systemic failures: Mutualism facilitates greater biodiversity, but it also creates the potential for many contingent species to go extinct, particularly if large, well-connected generalists—certain large banks, for instance—disappear. It becomes an argument for the “too big to fail” policy, in which the size of the company’s Facebook network matters more than the size of its balance sheet.

Scale-crossing brokers: new theoretical tools to analyze adaptive capacity

Social network structure for ecosystem governance.

Social network structure matters for adaptive capacity. A key position are 'scale-crossing brokers' that link actors interacting with ecosystem processes at different ecological scales.

Together with colleagues from Stockholm University we have just published an article in Ecology and Society called:

Scale-crossing brokers and network governance of urban ecosystem services: the case of Stockholm

Henrik Ernstson, Stephan Barthel, Erik Andersson and Sara T. Borgström, Ecology and Society 2010: 15 (4), 28.

The article synthesizes empirical studies of urban ecological management in Stockholm. However, it also contributes to the theoretical discussions on adaptive governance of social-ecological systems (e.g. special issue in Global Environmental Change, Folke et al. 2005, Duit and Galaz, 2008). As such, the article is of interest for studies in marine, forest and agricultural systems.

Here I present some key theoretical ideas. (See also blog at Stockholm Resilience Centre.).

Framework for assessing adaptive capacity – linking ecological processess and social network structure

The article builds a theoretical framework that links ecological processes to social network structures to assess the adaptive capacity of ecosystem governance. In effect, the article pushes present theorizations in at least three aspects: 1) spatial complexity, 2) the role of social network structure, and 3) how to handle cross-scale interactions.

1) Spatial complexity

First, it builds a framework to more explicitly account for spatial complexity (and thus the complexity of the ‘resource’ in question). This is primarily done through empirically focus on the ecological processes of seed-dispersal and pollination, which are processes important for the re-generation and resilience of local ecosystems in the fragmented urban landscape of Stockholm.

2) Social network structure as intermediate variable

Second, the paper ‘looks’ beyond individual actors and their direct ties to others (often the case in the literature on for instance ‘bridging organizations’). Instead, actors that interact with ecological processes are seen as embedded in patterns of communication and social relations. This means that the paper acknowledges ‘social network structure’ and how this intermediate variable (not individual, not institution) mediates the agency of single actors, and the performance of the whole network to respond to change.

To capture social dynamics we take the idea from sociology that, just as ecological patches are part of greater scale patterns, social actors are part of emergent social network structures that constrain and shape social dynamics (Wasserman and Faust 1994). […] social network patterns are consequently an outcome of localized interactions between pairs of actors, and no actor can fully control the emergent structure. [This] allows for human agency, but an agency constrained and mediated through the network structure itself (Emirbayer and Goodwin 1994).

3) Cross-scale interactions and scale-crossing brokers

Third, the paper pushes the understanding of what it would mean for a set of identifiable actors to handle cross-scale interactions in social-ecological systems. This is done through developing a network model of how certain actor groups engage in ecological processes at different scales through their social practice, and to theorize a key network position called ‘scale-crossing broker’ (building on Burt’s notion of brokers):

Thus, by accounting for the structure of social networks between actor groups, and how they link to ecological scales, our resulting model consists of actor groups interacting both with each other and with ecosystem processes at different spatial scales, and at spatially separate sites [see figure at top].

A final central aspect of our model is the network position of scale-crossing broker [which is defined] as a social network position that links otherwise disconnected social actor groups which, through their social practices, interact with ecosystem processes at different ecological (and spatial) scales and at different physical sites.

In relation to the discussion on how governance systems can cope with slow changes on one hand, and rapid changes on the other, our answer indicates that we must look for this in the social network structure that links various actors across scales. In that sense, the scale-crossing broker becomes “a crossroad for possibilities” and could facilitate the “switching” between supporting localized social learning processes (in times of slow change), and centralized collective action (in times of rapid change):

Scale-crossing brokers can be seen as agents for nurturing the emergence of a purposeful social network structure, and for switching between a centralized collective action mode and a decentralized mode of social learning among a diverse set of local autonomous actor groups.

Assessing governance systems

As such, the scale-crossing broker becomes an analytical lens to use when assessing empirical governance systems. Upcoming research should thus aim to measure the extent to which you can find scale-crossing brokers in a particular system. Another such assessment tool lies in our conceptualization of a meso-scale in governance in the form of ‘city-scale green networks’ (see figure below).

In conclusion, and apart from its empirical findings not touched upon in this blog, the paper can be seen as bringing new theoretical ideas on how to discuss and analyze social-ecological complexity and adaptive capacity. For more information see the paper itself, the blog-post at Stockholm Resilience Centre, or my own blog In Rhizomia.

The article is part of a special issue in Ecology and Society on social network analysis and natural resource management.

Governance of complex ecological processes

Fig. 4. The figure demonstrates how one could identify the city scale green networks of pollination and seed dispersal in a particular area of Stockholm (suggested here by using digital mapping and ecological network analysis (cf. Andersson and Bodin 2008)). Note how certain local green areas are shared between the two city scale green networks, which give rise to network overlap (purple areas with bold vertical lines in city scale green network 2). Furthermore, it is suggested that midscale managers can take responsibility for particular city scale green networks. Taken as a whole, the figure demonstrates how particular ecosystem services can be viewed as embedded both in the physical landscape and within social networks of local actor groups (managing local green areas), scale-crossing brokers, and municipal to regional actors.

Hive plots for visualizing complex networks

Martin Krzywinski from British Columbia Genome Sciences Centre proposes a new type of network layout to reduce ‘hairball’ mess of standard network visualizations Hive Plots – Linear Layout for Network Visualization, in which nodes are located on on radially distributed linear axes based on network structural properties and edges are drawn as curved links.  I hope there is an R package in the works.

Geoffrey West on Biological and Urban Allometry

Santa Fe Institute physicist Geoffrey West giving a talk about the allometry (scaling rules) of animals, organizations and cities (his work has been on resilience science before) – based on his great work with ecologists James Brown and Brian Enquist.

In an interview with the Santa Fe Reporter, West was asked “Was studying the networks within organisms what led you to study networks between organisms, ie cities?  West replied:

Exactly. It’s obvious that a city, or even a company, has network structure. Not even at the social level, just at the physical level, a city has roads and gas stations and pipelines, which are networks. But it also has something more abstract and, in some cases, something more sophisticated than in biology. And that is networks of social interactions, which are where things like information and knowledge are being translated.

If you go back to biology, another way of saying it is that—let’s just think of mammals. The fact that the whale is in the ocean and the elephant has a big trunk and the giraffe has a long neck and we walk on two feet and the mouse scurries around, these are all superficial characteristics. And in terms of their functionality, their physiological design, their organization, their life history, the essence of what they are, they’re actually all scaled versions of one another. We are, at some 90 percent level, just a scaled-up mouse. And the question is, is that true of cities? Is New York just a scaled-up San Francisco, which is a scaled-up Boise, which is a scaled-up Santa Fe, even though they look completely different?

So what we did is look at all this data, everything from number of gas stations to length of electrical cables to number of patents they produce to number of police and crimes and spread of AIDS disease and wages, everything you could lay your hands on, and ask, ‘If you look at those functions of city size (population), is there some systematic progression?’ And to our amazement, actually, there is. So, in some average way, Santa Fe is a scaled-down New York City.

Eric Berlow responds on networks & system analysis

In his TED talk Eric Berlow presented a causal loop diagram (CLD) of the US army’s Afghanistan Counter-Insurgency (COIN) strategy and then used its network structures and features to simplify it.

I am interested in combining network and systems analysis to better understand complex systems, so it was great to get Eric Berlow‘s repsonse to Tom Fiddaman’s comments on his analysis of an US Army causal loop diagram talk.  My PhD student Juan Carlos Rocha, is working on analyzing ecological regime shifts using network approaches and both Eric’s and Tom’s comments provide useful ideas.

Tom Fiddaman wrote:

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.

Eric Berlow responds:

I only wish that I had more time to discuss these important issues in the 3 min time frame (I think it took me more than 3 min to read the comment itself). You articulate extremely well the difference between a network with consistently defined nodes and links and a CLD which reads basically like a brainstormed mind map. The Afghan COIN diagram is clearly the latter.

In our 2009 PNAS paper [Berlow, E. L., J. A. Dunne, N.D. Martinez, P.B. Stark, R.J. Williams, and U. Brose. 2009. Simple prediction of interaction strengths in complex food webs. Proceedings of the National Academy of Sciences 106: 187-191.], as well as Brose et al. 2005 Ecology Letters [Brose, U., E. L. Berlow, and N. D. Martinez. 2005. Scaling up keystone effects from simple to complex ecological networks. Ecology Letters. 8: 1317-1325.], we see some interesting examples in food webs where the spheres of influence remain remarkably ‘local’ to the node of interest. We also observed that the more complex the network (more species and associated links) the easier it was to predict how the removal of one species will change the abundance of another. One mechanism by which that could occur is if perturbations dampen with distance. That dampening may be due to an accumulated inefficiency of energy transfer in long paths (as you suggest). However other results suggest it is not that straightforward. The patterns we observe also may be due to the increased likelihood that a long path will contain one weak link that truncates the effect. And the more complex the web, the more chances multiple long paths from species A to species B cancel each other out. We are currently exploring these options, among others, to see if there is a more general theory of when and how more complexity leads to simpler predictions. Identifying, or successfully predicting, when it does NOT is also extremely interesting and important.

My talk had two goals. One was to stimulate discussion about whether or when our food web results (‘localization of influence’) might apply to other networks. For example, the longer the path in this Afghanistan CLD, the more likely it will include a node that is very difficult to change. So you might expect, on average, truncation of influence with distance. I do not know, but it is worth exploring. It is also interesting (as an aside) that this simple structural analysis honed in on what many experts agree are core issues that must be addressed to achieve the stated goal. My second, and perhaps more important, goal was to communicate to a broad audience (broader than I ever imagined actually!) the more general, conceptual message that often it is only by embracing the true complexity of a problem that core simple issues emerge. I think this point generally rings true but is very under-appreciated and under-applied.

In retrospect, it was probably not very smart on my part to try and make 2 points in a 3 min talk! I apologize for any confusion. Thanks for the insightful discussion.