Tag Archives: Marten Scheffer

New resilience theory related book Phase Transitions

Ricard Solé, the well known complex systems scientist, has a new book Phase Transitions (here’s Table of Contents). It sounds interesting especially since Solé’s work frequently includes ecological and evolutionary dynamics.  The book looks very similar it is to Marten Scheffer‘s Critical Transitions in Nature and Society – so it will be interesting to see how they differ in approach and content.

The book is the third in Princeton University Press’s Primers in Complex Systems series.  Since phase transitions, critical transitions, and regime shifts are all extremely similar and all relate to resilience I’ll certainly check the book out.

The publisher describes the book:

Phase transitions–changes between different states of organization in a complex system–have long helped to explain physics concepts, such as why water freezes into a solid or boils to become a gas. How might phase transitions shed light on important problems in biological and ecological complex systems? Exploring the origins and implications of sudden changes in nature and society, Phase Transitions examines different dynamical behaviors in a broad range of complex systems. Using a compelling set of examples, from gene networks and ant colonies to human language and the degradation of diverse ecosystems, the book illustrates the power of simple models to reveal how phase transitions occur.

Introductory chapters provide the critical concepts and the simplest mathematical techniques required to study phase transitions. In a series of example-driven chapters, Ricard Solé shows how such concepts and techniques can be applied to the analysis and prediction of complex system behavior, including the origins of life, viral replication, epidemics, language evolution, and the emergence and breakdown of societies.

Written at an undergraduate mathematical level, this book provides the essential theoretical tools and foundations required to develop basic models to explain collective phase transitions for a wide variety of ecosystems.

Resilience 2011 slides and videos

Slides and videos for keynote and invited speaker presentations at Resilience 2011 are now available online.



I didn’t see all of these talks, but those that I did see were good. I particularly recommend Bill Clark, Elinor Ostrom, Carlo Jaegar, and Marten Scheffer’s talks.

Resilience 2011: notes on regime shifts and coupled social-ecological systems

The Resilience 2011 conference was a unique opportunity to meet people and new ways of thinking about resilience. This post is dedicated to the sessions I enjoyed the most, and my research interests biased me towards sessions on regime shifts and coupled social-ecological system analysis.

As PhD student working with regime shifts, it was not surprisingly that the panel on research frontiers for anticipating regime shifts was on my top list. Marten Scheffer from Wageningen University introduced the theoretical basis of critical transitions on social-ecological systems. His talk was complemented by his PhD student Vasilis Dakos on early warnings. Their methods are based on the statistical properties of systems when approaching a bifurcation point. These are gradual increase in spatial and temporal auto-correlation, as well as variability. A perfect counterpoint to these theoretical approaches was offered by Peter Davies from University of Tasmania; who presented the case study of a river catchment in Tasmania. Davies and colleagues introduced Bayesian networks as a method to estimate regime shifts, their likelihood and possible thresholds. Victor Galaz from Stockholm Resilience Centre presented an updated version of his work with web crawlers, exploring how well informed Internet search can give early warnings on, for example, disease outbreaks. Galaz point out the role of local knowledge as fundamental component of the filtering mechanism for early warning systems.  Questions from the audience and organizers were focused on the intersections from theory and practical applications of early warnings.

While Dakos’ technique does not need deep understanding of the system under study, his time series analysis approach does require long time series. On the other hand, Bayesian networks require a deep understanding of the system and their feedbacks in order to make well-informed assumptions to design models. An alternative approach was proposed by Steve Lade from Max Planck Institute in a parallel session, who used generalized models to identify the model’s Jacobian. Although his approach does need a basic knowledge of the system, it is able to identify critical transitions with limited time series, typical of social-ecological datasets in developing countries.

Most of the work on regime shifts is based on state variables that reflect either ecological processes or social dynamics, but rarely both. Thus, I was also interesting in advances on operationalizing the concept of critical transitions to social-ecological systems in a broader sense. I looked for modeling examples where it is easier to track how researchers couple social and ecological dynamics. Here are some notes on the modeling sessions.

J.M. Anderies and M.A. Janssen from Arizona State University (ASU) presented their work on the impact of uncertainty on collective action. They used a multi-agent model based in irrigation experiments (games in the lab). Their work caught my attention because first they capture the role of asymmetries in common pool resources, which is often overlooked. In the case of irrigation systems, it is given by the relative positions of “head-enders” and “tail-enders” with different access to the resource.  Secondly, they used their model to explore how uncertainty both in water variability and shocks to infrastructure affects the evolution of cooperation.

Ram Bastakoti and colleagues (ASU) complemented the previous talk by bringing Anderies and Janssen insights to the field, particularly to cases in Thailand, Nepal and Pakistan. Batstakoti is studying the robustness of irrigation systems to different source of disturbances including policy changes, market pressure and the biophysical variability associated with resource dynamics. In the following talk, Rimjhim Aggarwal (ASU) presented the case of India, a highly populated country facing a food security challenge in the forthcoming decades; where groundwater levels are falling faster than expected. Aggarwal research explores the tradeoffs among development trajectories. His focus on technological lock-ins and debt traps as socially reinforced mechanism towards undesirable regimes makes his study case a potential regime shift example.

My colleagues from the Stockholm Resilience Centre at Stockholm University also presented interesting work on modeling social-ecological dynamics. Emilie Lindqvist uses a theoretical agent model to explore the role of learning and memory in natural resource management. Her main results point out that long-term learning and memory is essential for coping with abrupt decline or cyclic resource dynamics. On the other hand, Jon Norberg and Marty Anderies presented a theoretical agent model where social capital dynamics are coupled with a typical fishery model. Although their work is still prelimary, it was the only talk that I saw which actually coupled social and ecological dynamics.

Resilience 2011 gave me the opportunity to rethink and learn a lot about regime shifts. Although my main question: how to study regime shifts in coupled social-ecological system remains unsolved, the discussions in the panel sessions gave me some possible ways of tackling it.

The research agenda on regime shifts is strongly developing towards early warnings. Three competing methods arise:

  1. look for signals in spatial and temporal data by examining the statistical properties of a system approaching a threshold: increase in variance and autocorrelation
  2. acquire a deep knowledge of feedback dynamics and apply Bayesian networks to understand and predict potential interacting thresholds
  3. use shallow knowledge of the system to estimate their Jacobian using short time series.

Social and ecological dynamics are hard to couple. It is not only because there are usually studied in different disciplines with different methods. My guess is that the rates of change of their main variables occur at very different rates. As consequence social scientists assume nature dynamics to be constant or as drivers, while natural scientists assume the “social stuff” to be constant as well.

Modelers have started breaking the ice by introducing noise to the external variables (e.g. rainfall variability, political instability, market pressure); or by looking at how memory or social capital at individual level scale up to resource dynamics. However, their main insights remain confined to study cases making difficult to generalize or study the coupling of society with global change trends.

Reviewing Critical Transitions

transcoverEnvironmental historian, John R. McNeill, reviews Marten Scheffer‘s new book on resilience – Critical Transitions in Nature and Society. In the American Scientist he writes:

Like many before him, Marten Scheffer is impressed with parallels between social systems and natural systems. Moreover, he is convinced that problems confronting the human race require something more integrated than the fragmentary knowledge of the various academic disciplines. In short, he seeks to span the famous “two cultures” and to take a long stride toward consilience. Coming from a background in limnology and aquatic ecology, Scheffer is inevitably more at home in some arenas of knowledge than others, and his new book, Critical Transitions in Nature and Society, is mainly about the critical transitions in nature that are of interest to society. An example with which he begins the book is typical: the transformation of the Western Sahara into desert about 5,500 years ago as a result of initially small climate change that built on itself because the drier climate reduced vegetation, thereby heightening albedo.

Part of Scheffer’s aim is to contribute to the study of how well the theory of system dynamics corresponds to real life, in the behavior both of nature and of society. “If we are able to pin down the mechanisms at work,” he says, “this may eventually open up the possibility of predicting, preventing, or catalyzing big shifts in nature and society.” To be able to do so is a long-standing human ambition, which has been given fullest rein in political regimes that have seen utopia just over the horizon and have aimed to get there as soon as possible. In the abstract, such ambition seems laudable. In practice, it has led to many regrettable “big shifts” in nature and society, such as those undertaken in the headiest days of the Soviet Union or Mao Zedong’s rule in China. To date, those most keen on provoking “big shifts” have known far too little, and perhaps cared too little as well, about the possible outcomes of their actions. When results did not conform closely enough to their hopes, they used their powers to try to force society and nature into preferred channels, which led to gulags and environmental disasters. When trying to catalyze big shifts in nature and society, one must really know what one is doing—and that is very, very hard to do.

So Scheffer seems more cheerful about the future of the Social-Eco-Earth-System at the end of writing his book than I am after reading it. But his premise—that hope lies with integrated eco-social science rather than our traditional isolated silos of knowledge—is surely correct. Perhaps we are on the edge of a happy tipping point after which science enters a state in which depth is not unduly esteemed over breadth, in which integrated study of complex systems becomes the norm, in which our insight into real-world eco-social systems grows and grows to formerly unimaginable levels. If so, Scheffer may be right to be optimistic. But there are some powerful attractors working against it.

Responses to Early Warning Signals for Critical Transitions paper

The recent paper by Marten Scheffer and other resilience researchers paper Early Warning Signals for Critical Transitions (doi:10.1038/nature08227) has been reported in a number of places including Time, USA Today, and Wired.  While many newspapers just reprint the press release, several articles add something.

A USA Today article Predicting tipping points before they occur quotes Brian Walker:

“This is a very important paper,” says Brian Walker, a fellow at the Stockholm Resilience Center at the University of Stockholm in Sweden.

“The big question they’re trying to answer is, how the hell do you know when it’s coming? Is there any way you can get an inkling of a looming threshold, something that might be a warning signal that you’re getting to one of the crucial transition points?”

Wired magazine article Scientists Seek Warning Signs for Catastrophic Tipping Points quotes several sceptical scientists:

“It’d be very nice if it were true that there were precursors for tipping points in all these diverse systems. It’d be even nicer if we could find these precursors. I want to believe it, but I’m not sure I do,” said Steven Strogatz, a Cornell University biomathematician who was not involved in the paper.

The difficulty of early detection is especially pronounced with markets. Computer models can replicate their bubble-and-crash behavior, but real markets — buffeted by political and social trends, and inevitably responding to the very act of prediction — are much cloudier.

“It is hard to find clear evidence of bifurcations and transitions, let alone find an early warning system to detect an upcoming crash,” said Cars Homme, an economic theorist at the University of Amsterdam.

The most promising evidence of useful early warning signs comes from grasslands, coral reefs and lakes. Vegetation-pattern-based early warning signs have been documented in several regions, and transition theory is already being used to guide land use in parts of Australia.

The U.S. Geological Survey is currently hunting through satellite imagery for signals of impending desertification at two sites in the Southwest. They’ve studied desertification there by painstakingly measuring local conditions and experimentally setting fires, removing grasses and controlling the fall of water. But so far, the vegetation patterns that indicated tipping points in the Kalahari haven’t shown up here, though this may be due to poor image quality rather than bad theory. The researchers are now looking for signals in on-the-ground measurements of vegetation changes.

“These things aren’t going to be foolproof. There will be false positives and false negatives, and people need to be aware of that,” said Carpenter. “There’s still a great deal of basic research going on to understand the indicators better. We’re still in the early days. But why not try? The alternative is to get repeatedly blindsided. The alternative is not appealing.”

Time magazine in Is There a Climate-Change Tipping Point? quotes co-author Steve Carpenter:

So, how do we know that change is at hand? The Nature researchers noticed one potential signal: the sudden variance between two distinct states within one system, known by the less technical term squealing. In an ecological system like a forest, for example, squealing might look like an alternation between two stable states — barren versus fertile — before a drought takes its final toll on the woodland and transforms it into a desert, at which point even monsoons won’t bring the field back to life. Fish populations seem to collapse suddenly as well — overfishing causes fluctuations in fish stocks until it passes a threshold, at which point there are simply too few fish left to bring back the population, even if fishing completely ceases. And even in financial markets, sudden collapses tend to be preceded by heightened trading volatility — a good sign to pull your money out of the market. “Heart attacks, algae blooms in lakes, epileptic attacks — every one shows this type of change,” says Carpenter. “It’s remarkable.” 

In climate terms, squealing may involve increased variability of the weather — sudden shifts from hot temperatures to colder ones and back again. General instability ensues and, at some point, the center ceases to hold. “Before we reached a climate tipping point we’d expect to see lots of record heat and record cold,” says Carpenter. “Every example of sudden climate change we’ve seen in the historical record was preceded by this sort of squealing.”

The hard part will be putting this new knowledge into action. It’s true that we have a sense of where some of the tipping points for climate change might lie — the loss of Arctic sea ice, or the release of methane from the melting permafrost of Siberia. But that knowledge is still incomplete, even as the world comes together to try, finally, to address the threat collectively. “Managing the environment is like driving a foggy road at night by a cliff,” says Carpenter. “You know it’s there, but you don’t know where exactly.” The warning signs give us an idea of where that cliff might be — but we’ll need to pay attention.