All posts by Garry Peterson

Prof. of Environmental science at Stockholm Resilience Centre at Stockholm University in Sweden.
Vulnerability

Information and Communication Technologies and Climate Change

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Richard Heeks and Angelica Ospina at the University of Manchester’s Centre for Development Informatics‘ run the blog Notes on ICTs, Climate Change and Development.  Recently Angelica Ospina wrote about ICTs within a Changing Climate:

According to the latest Information Economy Report prepared by UNCTAD [UN conference on trade and development] over the past few years “the penetration rate of mobile phones in the world’s least developed countries (LDCs) has surged from 2 to 25 subscriptions per 100 inhabitants”, and is expected that by 2010 the total number of mobile subscriptions will reach 5 billion. …

But what about the role of these technologies towards climate change mitigation, monitoring and adaptation?

Evidence on these linkages is starting to emerge, suggesting that the role of ICTs towards poverty reduction and the strengthening of local livelihoods is closely connected to their potential in enabling developing country communities to better withstand, recover from, and adapt to the changing conditions posed by climate change –what can, overall, be termed ‘resilience’.

There is still much to learn about the role and potential of ICTs in the climate change field, including their effects in strengthening -or weakening- local responses and strategies to climate change-related effects. However, these technologies are integral to processes of experimentation, discovery and innovation, which are, in turn, essential components of learning and key to enable more effective mitigation measures, monitoring, and local adaptive capacities within vulnerable environments.

Networks, Visualization

Hive plots for visualizing complex networks

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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.

Ideas

Microbiological resilience

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From Microbiology: The new germ theory in Nature news:

…collaborations are linking those exploring the human microbiota in the intestine, skin, mouth and other surfaces with microbial ecologists, such as Banfield, who have already made a career out of studying microbial universes in environments such as soil, ocean water and toxic waste sites.

The human microbiologists need the help. Although work by Relman and many others over the past five years has gone a long way to building up a genetic catalogue of human microbiota — what types of microbes live where — it has also revealed its staggering and previously unappreciated complexity. With hundreds of interacting, coevolving species living in and on every individual, and frustratingly little species overlap between each person’s microbial population, understanding the connection between microbes and health seems more daunting than ever. Researchers want to know what role the body’s microbial inhabitants have in immune function, nutrition, drug metabolism and conditions as diverse as obesity, cancer, autism and multiple sclerosis. But to do so, they have to sort through an avalanche of genetic sequence to find out what microbes are in the community, how they change over the course of a day, a lifetime or after a change in diet, and which functions are served by particular microbes, combinations of microbes or microbial metabolites (see ‘Exploring the superorganism’).

Microbial ecologists are supplying some of the expertise and bio-informatic tools to help make sense of the data mountain. They are also bringing to the human microbial field ecological principles such as colonization, succession, resilience to change, and competition and cooperation between community members. “It’s hard not to think about ecology when you enter the field,” says Jeff Gordon, a leader in gut microbiology at Washington University in St Louis, Missouri. In return, specialists in human microbiology are attracting funding and attention that ecologists have sometimes struggled to find. “The arbitrary and false barriers between environmental and medical microbiology are breaking down,” Gordon says.

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Other collaborations are also exploring how human microbial ecosystems adjust during illness, shifts in diet or after antibiotics. “They’re probably changing all the time in response to all sorts of perturbations,” says Claire Fraser-Liggett, a microbiologist at the University of Maryland School of Medicine in Baltimore, who, in collaboration with Janet Jansson, a soil microbiologist at the University of California, Berkeley, is studying microbiomes associated with the intestinal disorder Crohn’s disease in identical Swedish twins. “Are these communities resilient enough to rebound to where they were before a perturbation like antibiotics? What should we be measuring in order to answer that question? What’s going on in the recovery period? It leads to all these questions that ecologists have been dealing with for decades.”

Ecological concepts are also helping to account for the substantial differences that most studies have found between the microbiota of individuals — even, to a lesser extent, between identical twins. Ecology offered a likely explanation in the form of redundancy. The idea now is that every person’s microbes provide a core set of genes or biological functions, regardless of the specific species encoding them. “If you look at grasslands in different parts of the planet, there’s a common morphology and function,” says Gordon, drawing parallels. “But in different locales, the component species are quite distinct.” Gordon and other researchers hope that more extensive sequencing and analysis of many individuals’ microbiomes will reveal what those core functions are. Relman, meanwhile, has become interested in finding ‘keystone species’, rare species that nevertheless have a vital role in a community, and he is working with a colleague at Stanford, bioengineer Stephen Quake, to sequence the genomes of single microbial cells from the gut.

Cities, Networks

Geoffrey West on Biological and Urban Allometry

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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.

Networks, Visualization

Eric Berlow responds on networks & system analysis

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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.

Ideas

Clive Hamilton on climate denialism and social-ecological systems and

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Clive Hamilton is an author and Professor of Public Ethics at Charles Stuart University and Centre for Applied Philosophy and Public Ethics in Australia.  He has been writing about the ethics of climate change, and climate denial.

In his interesting talk, Why We Resist the Truth About Climate Change, one of the points he makes is the importance and difference of a social-ecological perspective:

Developments in climate science have revealed a natural world so influenced by human activity that the epistemological division between nature and society can no longer be maintained. When global warming triggers feedback effects, such as melting permafrost and declining albedo from ice-melt, will we be seeing nature at work or human intervention? The mingling of the natural and the human has philosophical as well as practical significance, because the “object” has been contaminated by the “subject”.

Climate denial can be understood as a last-ditch attempt to re-impose the Enlightenment’s allocation of humans and Nature to two distinct realms, as if the purification of climate science could render Nature once again natural, as if taking politics out of science can take humans out of Nature. The irony is that it was Enlightenment science itself, in the rules laid down by the Royal Society, that objectified the natural world, putting it on the rack, in Bacon’s grisly metaphor, in order to extract its secrets. We came to believe we could keep Nature at arms-length, but have now discovered, through the exertions of climate science, something pre- moderns took for granted, that Nature is always too close for comfort.

For more see his book, Requeim for a Species, or his related talk at the UK’s RSA – Facing up to Climate Change.

General

An Algorithm for Discovery

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A decade ago in Science, Paydarfar and Schwartz, neurologists from University of Massachusetts, wrote about an An Algorithm for Discovery (DOI:10.1126/science.292.5514.13).  They suggest that there is a useful algorithm for creating new knowledge that has five steps:

1. Slow down to explore. Discovery is facilitated by an unhurried attitude. We favor a relaxed yet attentive and prepared state of mind that is free of the checklists, deadlines, and other exigencies of the workday schedule. Resist the temptation to settle for quick closure and instead actively search for deviations, inconsistencies, and peculiarities that don’t quite fit. Often hidden among these anomalies are the clues that might challenge prevailing thinking and conventional explanations.

2. Read, but not too much. It is important to master what others have already written. Published works are the forum for scientific discourse and embody the accumulated experience of the research community. But the influence of experts can be powerful and might quash a nascent idea before it can take root. Fledgling ideas need nurturing until their viability can be tested without bias. So think again before abandoning an investigation merely because someone else says it can’ be done or is unimportant.

3. Pursue quality for its own sake. Time spent refining methods and design is almost always rewarded. Rigorous attention to such details helps to avert the premature rejection or acceptance of hypotheses. Sometimes, in the process of perfecting one’s approach, unexpected discoveries can be made. An example of this is the background radiation attributed to the Big Bang, which was identified by Penzias and Wilson while they were pursuing the source of a noisy signal from a radio telescope. Meticulous testing is a key to generating the kind of reliable information that can lead to new breakthroughs.

4. Look at the raw data. There is no substitute for viewing the data at first hand. Take a seat at the bedside and interview the patient yourself; watch the oscilloscope trace; inspect the gel while still wet. Of course, there is no question that further processing of data is essential for their management, analysis, and presentation. The problem is that most of us don’t really understand how automated packaging tools work. Looking at the raw data provides a check against the automated averaging of unusual, subtle, or contradictory phenomena.

5. Cultivate smart friends. Sharing with a buddy can sharpen critical thinking and spark new insights. Finding the right colleague is in itself a process of discovery and requires some luck. Sheer intelligence is not enough; seek a pal whose attributes are also complementary to your own, and you may be rewarded with a new perspective on your work. Being this kind of friend to another is the secret to winning this kind of friendship in return.

Although most of us already know these five precepts in one form or another, we have noticed some difficulty in putting them into practice. Many obligations appear to erode time for discovery. We hope that this essay can serve as an inspiration for reclaiming the process of discovery and making it a part of the daily routine. In 1936, in Physics and Reality, Einstein wrote, “The whole of science is nothing more than a refinement of everyday thinking.” Practicing this art does not require elaborate instrumentation, generous funding, or prolonged sabbaticals. What it does require is a commitment to exercising one’s creative spirit—for curiosity’s sake.

Ideas, Tools

Bridge building ecological theory

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A new book from my former McGill colleague, Michel Loreau is lying on my desk.  I haven’t read From Populations to Ecosystems: Theoretical Foundations for a New Ecological Synthesis yet, but Tadashi Fukami has, and his review is in Science.  He writes:

… Michel Loreau argues that an effective way forward is to give up building a single unified theory of ecology altogether. Loreau (a theoretical ecologist at McGill University) believes that “a monolithic unified theory of ecology is neither feasible nor desirable.” As an alternative approach, he advocates theoretical merging of closely related, yet separately developed subdisciplines.

The merging (or bridge-laying) Loreau advocates involves translating different “languages” used in the mathematical models developed separately in various subdisciplines into a common language so that the subfields can talk to one another. Although this approach does not yield a truly unified theory, it helps, Loreau argues, to “generate new principles, perspectives, and questions at the interface between different subdisciplines and thereby contribute to the emergence of a new ecological synthesis that transcends traditional boundaries.” Taking this tack, one gets a sense that the problem with specialization in subdisciplines can be solved by theoretical bridging without having to trade specificity for generality.

An elegant example of the author’s approach can be seen in the work conducted by him and his colleagues over the past decade or so that merges two major subdisciplines of ecology, community ecology and ecosystem ecology. Loreau devotes much of the book to recounting this body of research. He starts by summarizing essential elements of the mathematical models developed in the two subdisciplines. He then discusses how the two sets of models, though developed separately and with apparently distinct sets of equations, can be merged by basing the two on a common currency: the mass and energy budgets of individual organisms. Once this translation is accomplished, new models that simultaneously consider the composition of coexisting species (the focus of traditional community ecology) and the flow of materials through functional compartments of ecosystems (the focus of traditional ecosystem ecology) can be built and analyzed. These allow one to study reciprocal influences between species composition and material flows in the ecosystem.

As Loreau acknowledges, his is not the first book to advocate this type of theoretical merging. In particular, the approach he presents resembles that laid out in an influential 1992 book by Donald DeAngelis (3). What makes Loreau’s contribution novel and creative is his successful application of the merging approach to understanding the functional consequences of biodiversity loss, the topic that has received perhaps greater attention than any other ecological issue over the past two decades because of its broad social implications.

Ecosystem services

Four PhD positions in sustainability and biodiversity

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My colleague Joern Fischer is offering four new PhD positions at Leuphana University Lueneburg. He writes:

Expressions of interest are being sought for four new PhD positions, for commencement in 2011 (details to be negotiated). Please register your interest and send your CV to Joern Fischer (Joern.Fischer@uni.leuphana.de , also see https://sites.google.com/site/joernfischerspage/). Do not send complete applications at this stage.

The project
Unprecedented global change poses an urgent challenge to humanity because it threatens ecosystems and human well- being, especially in poor countries. We will implement a transdisciplinary research agenda to foster sustainable development in ancient agricultural landscapes in Central Romania. The area is fascinating because ancient agricultural practices without machinery or artificial fertilisers have maintained unusually high biodiversity, from large carnivores to rare orchids. Following its recent inclusion in the European Union, Central Romania now faces a delicate balancing act between the aspirations of local people for greater economic prosperity and the region’s unique heritage values. You will be part of a team involving natural scientists, social scientists and regional stakeholders. We will map biodiversity and the ecosystem services generated by it, and will identify formal and informal institutions that can provide leverage points for enabling sustainable land use practices.

The project is funded through a Sofja Kovalevskaja Award by the Alexander von Humboldt Foundation (through funds by the German Federal Ministry of Education and Research). Visit https://sites.google.com/site/landscapefutures/Home

PhD 1: The future of birds and large carnivores
Primary focus: ecology. This component will gather data on birds and large carnivores, will map their distribution, quantify habitat relationships, and analyse likely changes under different scenarios of future development. Methods will include field surveys, statistical modelling, and GIS applications.

PhD 2: The future of plants and butterflies
Primary focus: ecology. The study area is exceptionally rich in plants and butterflies. This component will gather original field data, will map the distribution of the groups, quantify habitat relationships, and analyse likely changes under different development scenarios. Methods will include field surveys, statistical modelling, and GIS applications.

PhD 3: Cultural ecosystem services and historical changes
Primary focus: social sciences, humanities. This component will analyse land use changes since the middle ages, and will quantify the cultural benefits that people derive from nature. The possible impacts of different future trajectories on the provision of cultural ecosystem services will be assessed. Methodology will be broad and flexible, potentially including literature reviews, analysis of historical sources (e.g. old maps), interviews and workshops with local people, and GIS analysis. Experience with some of these methods, and ability to speak Romanian, will be advantages.

PhD 4: Changes in institutional arrangements
Primary focus: social sciences. This component will analyse informal and formal institutions, and their dynamic changes in the past – with a particular emphasis on recent changes since Romania joined the European Union. How can institutional arrangements foster the sustainable development of the region? Methods are flexible, including participatory methods with local people, and analysis of official policy documents (e.g. regarding EU agri-environment schemes).
This well-funded project includes collaborative links with St. Andrews University, Cambridge University, the Stockholm Resilience Centre, and the Mihai Eminescu Trust (Romania). All components will be theoretically grounded in a shared conceptual framework of ecosystem services, resilience theory, and social-ecological systems analysis. The research team will also involve more senior scientists who will focus on other, complementary aspects.

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.