A few weeks ago, as I was rummaging in a drawer in my father’s house, I came across a dozen reels of developed 8-millimetre film. I’d known the reels were in the house somewhere. But, for many years, I’d resolutely put the fact out of my mind. The films contained clips of my family in the late 1950s and early 1960s, not long before my mother became gravely ill. Over the intervening decades, I hadn’t had the heart to look at them.

But, this time, I packed the films into a shoebox and took them to someone who specializes in converting old films into digital form. Within a week, I had all the clips on a DVD and was showing them to my wife and two young children. There I was – three years old – with my mother and father playing on the swing set outside my childhood home near Victoria, learning to swim with my mother, hunting for Easter eggs with her in the field and forest nearby.

It was one of the first occasions that my children had seen images of their grandmother, and the first time I’d seen anything other than a still picture of her since I was 13. Even without sound, the emotional impact was inexpressible. It was as if I’d stepped into a time-travel machine and shot more than 50 years into the past.

We all want to capture happy family moments so we can relive them again in later years. But half a century is a really long time. Will any of today’s family digital recordings last that long? Will today’s children be able to see videos of themselves taken now in, say, 2070? These holidays, as we reach for the digital camera or video recorder, we assume they will – but we’re probably wrong.

I love technology just as much as the next person, but we have a real problem here. Today’s information technology is creating what we might call an Age of Ephemera. Our unprecedented ability to store and transfer gargantuan amounts of information obscures this information’s modern fragility.

Two factors are at play. The first is what people in the business call “media decay.” The physical material we use to store our information changes over time. Some materials deteriorate very slowly: Acid-free paper can last for 500 years, and the lifespan of archival-quality microfilm is about 200 years. But the kind of recordable CD on which most of us store our family photos can be unreadable in as few as five years, because the dyes in the CD’s recording layer fade, especially if the disk is stored in light.

The second and ultimately more serious factor is change in the hardware and software of the recording technology itself. Most of us have had the experience of coming across an old 5.25-inch computer floppy disk, looking at it with amusement – or horror, if it contains important information – then throwing it into a wastebasket because we don’t know anyone with a machine that can read such a thing now. Even if the recording medium hasn’t deteriorated and still contains the data, the technology to translate that data into a useable form – such as words or pictures on a screen – may have largely disappeared.

Many of the information-storage technologies from the middle of the last century were far less vulnerable to these problems. My father’s house also contains boxes of thousands of my mother’s slide photographs of landscapes, wildlife and wildflowers. She used Kodak Ektachrome film and, after nearly 60 years, the colour in the slides is almost as accurate as the day the photos were developed. And I don’t need a complex and long-lost technology to see the photos – just a simple magnifying glass.

Even the device needed to “read” my 8-mm films – an old reel-to-reel projector – is relatively simple. It consists of lenses, sprockets, belts and light bulbs, and it can be maintained and used for decades by an artisan working in a small shop, such as the person I consulted to convert my films into digital form. It’s hard to imagine the same being true in 2070 of an iMac or PC manufactured today.

These problems are all well-known. The solution, we’re told, is to re-record or “migrate” our most important data every few years to new media or new technologies. But there’s a problem with this advice: We’re human. We get distracted, we forget, we get sick, we die. And before we know it, those precious family films and photos locked away in digital form are gone forever.

My advice? Forget about recording videos for your grandchildren to see when they’re adults decades from now. Use your digital camera to take still photographs, have them printed with good inks on high-quality stock, and put them in a photo album – the old-fashioned analog way.

My response to comments left on the Globe and Mail website by readers:

Some people think I’m opposed to new technologies. Nothing could be further from the truth: I’ve written at length about the critical need for more and better technology to solve humankind’s critical problems, especially our energy problems. But I’m not a blind technophile: I think some technologies hurt us as well as benefit us, and which outcome we get depends on whether we use the given technology sensibly.

Of the two problems with information technology I identify in my article—media decay and technology change—the latter is by far the more serious. We can make media that last a long time, and some specialty media today are very stable. But the problem of technology change is inescapable in a competitive capitatlist economy.

This problem itself consist of two sub-problems: first, the complexity of, and second, constant change in, what I call the “interface technology”—that is, the technology that translates the data into a form our eyes can see or ears can hear (that, in other words, “interfaces” between the data and our eyes/ears).

A conventional book needs no interface technology. A 35mm slide needs a magnifying glass. A JPEG data file on a flash drive or a CD needs a phenomenally complex chain of technologies, from the reading device to the monitor that shows the photo. We can’t look at the flash drive and see the image.

The complexity of today’s interface technologies means we’re dependent on a huge array of specialists and subordinate-technologies, all working together seamlessly, to access the data. If something goes wrong with the technology, we usually can’t rely on ourselves to fix the problem. Frankly, this bugs me, because I like my autonomy, and I like to be able to fix the machines that I depend upon (I grew up fixing machines and still do it all the time).

The second sub-problem—constant change in both storage media and interface technologies—means that someone has to make a conscious effort to migrate any given chunk of data at regular intervals to new technologies, and if they EVER forget or make the wrong decision the data can be lost forever.

The combination of 1. high dependency on specialists and 2. the need for regular interventions to preserve data is going to be lethal for a lot of information. It’s interesting that many of the folks here who think we don’t have a problem say something like “As long as people follow certain steps, their data will be secure.” Yes, well, that means the data aren’t secure.

What about storing data in the cloud? To my mind, doing so just further enhances our reliance on outside specialists. And I don’t have any confidence that if I were to leave my data unattended in a cloud for several decades that it would be still there for me to retrieve when I returned, even assuming I could remember how to access it.

I’ll take the box of photos in the basement any time.

We’ll start with a snapshot of the wicked problems we face, with one of my favorite synthesizers, Dr. Thomas Homer-Dixon. He’s the author of “The Ingenuity Gap” and the “The Upside of Down“. Homer-Dixon points out a failure of group consciousness, of our mind as a species.

Episode information: http://www.ecoshock.info/2011/03/wicked-problems-solutions.html

Listen to the podcast:

One of the world’s leading scholars on the intersection of environment, security and crisis, Prof. Thomas Homer-Dixon of the University Waterloo in Canada joins Think Globally Radio this Sunday for an in-depth discussion reflecting his latest thoughts on climate change, cultural transformation and the nature of risk and uncertainty in the modern world.

I am absolutely delighted to be back in Ottawa. In the late 1970s and early 1980s I lived here for five years, and it’s always a joy to return to this city, especially in the spring when the tulips are out.

It’s also an enormous honour to be asked to present the Manion lecture. This lecture provides an opportunity to engage with new ideas – and to test new ideas – before a highly experienced audience. This evening I’m going to talk about the science of complexity and how it might be applied to public policy.

I have been working in complexity science for about 15 years. Until recently, the community of complexity researchers was quite isolated. We consisted of a few clusters of researchers here and there around the world, but for the most part we hadn’t integrated ourselves into a larger worldwide community. Also, our work hadn’t received much attention, partly because we often couldn’t show how complexity science might be used to make the world a better place. Theories of complexity can be very abstract. Their ideas and concepts don’t cohere well; in fact, the body of thinking we call complexity science is largely fragmented into bits and pieces.

But now, exciting projects like the New Synthesis Roundtable led by Mme Jocelyne Bourgon here in Ottawa are taking ideas from complexity science and applying them to the real world – to see how they might help us develop new approaches to public policy and better address the extraordinarily hard problems our societies face today.

As complexity theory has started to receive more attention, it has also started to accumulate critics. There are probably some of you out there in the audience this evening who are grumbling, “This is all just another fad.” I can understand why you might think so. Some people, especially rebellious graduate students I find, are similarly starting to talk about the “cult of complexity.”

My job this evening is to argue that complexity science isn’t a fad. I will offer a brief survey of some core concepts and ideas, and I will make a strong case that the tools and ideas of complex systems theory can give us significant purchase on the new and strange world we’re living in today. Most importantly, they can help us develop new strategies for generating solutions and prospering in this world.

So let’s begin.

We live in a world of complex systems

We need to start thinking about the world in a new way, because in some fundamental and essential respects our world has changed its character. We need to shift from seeing the world as composed largely of simple machines to seeing it as composed mainly of complex systems. Seeing the world as composed mainly of simple machines might have been appropriate several decades ago: we commonly thought of our economy, the natural resource systems we were exploiting, and our societies in general as machines that were analogous, essentially, to a windup clock. Each could be analyzed into parts, with the relations between those parts precisely understood, and each was believed to be nothing more than the sum total of its parts. As a result, we believed we could predict and often precisely manage the behaviour of these systems.

But now, increasingly, we live in a world of complex systems, and we have to cope with the vicissitudes of these systems all the time. Earth’s climate is clearly complex. Ecological systems are complex, and we’ve often managed them miserably when we’ve assumed they worked like simple machines – take a look, for example, at what we did to the east-coast fishery. Our economy, especially the global economy, is a complex system. Our energy systems, such as our electrical grids, are increasingly behaving like complex systems. Food systems, information infrastructures, and our societies as a whole all exhibit characteristics of complex systems.

No longer is it appropriate for us to think about the world as equivalent to, or an analog of, a mechanical clock, which one can dismantle and understand completely and which is, ultimately, no more than the sum of its parts. Instead we have to think in a new way.

To do so, we must first ask: What is complexity and what features distinguish complex systems from other kinds of systems? Surprisingly, even some of the world’s leading complexity thinkers have trouble answering this question. They tend to provide a checklist of properties common to complex systems, as I will in a moment. But to a certain extent, understanding complexity requires that one work with complex systems for an extended time and then study in depth the literature on complexity. In this way, one eventually develops an intuition for what complexity is.

Since we don’t have such time this evening, I’ll instead identify some properties that I regard, for the most part, as necessary features of complex systems.

Most complex systems have many components. They also have a high degree of connectivity between their components – an issue I’ll discuss extensively later in my presentation, because we need to unpack it completely. Additionally, complex systems are thermodynamically open. By this I mean that they’re very difficult to bound: we can’t draw a line around them and say certain things are inside the system while everything else is outside. As a result, in terms of their causal relationships with the surrounding world, complex systems tend to bleed out – or ramify or concatenate out – into the larger systems around them. And ultimately the boundary that we draw demarcating what is inside and what is outside is largely arbitrary.

Flowing across this boundary are information, matter, and most importantly energy. The flow of high-quality energy into complex systems allows them to sustain their complexity. In thermodynamic terms, these systems maintain themselves far from equilibrium. If we take away this energy, they start to degrade. The complexity disappears, they become simple, and they fall apart. Keep your mind focused on that point, because I am going to return to it in a few minutes.

The behaviour of complex systems is also non-linear. By this complexity specialists mean something very specific: in a nonlinear system small changes can have big effects, while sometimes big changes in the system don’t have much effect at all. These systems exhibit, therefore, a fundamental disproportionality between cause and effect. In contrast, in a simple machine small changes generally have small effects, while big changes have big effects. This difference in the nature of causality is one of the fundamental ways of discriminating between a simple machine and a complex system.

Finally, we have the characteristic of emergence. Emergence is probably the property that comes closest to being sufficient for complexity: if you see it, you’re very likely dealing with complexity. We have emergence when a system as a whole exhibits novel properties that we can’t understand – and maybe can’t even predict – simply by reference to the properties of the system’s individual components. It’s as if, when we finish putting all the pieces of a mechanical clock together, it sprouts a couple of legs, looks at us, says “Hi, I’m out of here,” and walks out of the room. We’d say “Wow, where did that come from?”

Once we have a list of common characteristics of complex systems, we can then think productively about how we might measure complexity. One method involves developing a computer program or algorithm that accurately describes or predicts the system’s behaviour under different circumstances. The longer the computer program or algorithm, the more complex the system it describes. Specialists call this metric “algorithmic complexity.” Experts have proposed a variety of other metrics of complexity. For our present purposes, the most important point is that by a lot of metrics our world is unquestionably becoming more complex. It’s becoming more connected, we see larger flows of energy into our socio-ecological systems, it’s exhibiting greater non-linearity, and it’s exhibiting lots of emergent surprises – more and more, it seems, all the time.

In this regard, I want to highlight a particularly interesting characteristic of our modern societies that has led to a surge in the number of system components: the rapid dispersion of power. Enormous increases in technological power have fundamentally changed the distribution of political power within our societies. A standard laptop computer today has about as much computational power as was available to the entire American defence department in the 1960s, and in those days a computer of such power would have filled a building about the size of the one we’re sitting in this evening. Today, this power is compressed into a little four-litre box, and these boxes are available to hundreds of millions of people around the planet. These people have at their fingertips, as a result, staggering computational, analytical, information-gathering, and communication capability. For all intents and purposes, this capability has translated into political power – a disaggregation or flattening of the social and political hierarchy – because of the diffusion throughout our societies of the capacity of groups and individuals to express forcefully their political and economic interest. In a sense, this diffusion of power has led to a proliferation of agents, which is equivalent to a rapid increase in the number of components within our societies, and in consequence a rapid increase in societal complexity.

This last point leads us naturally to the question: What, in general, causes complexity to increase?

Sources of complexity

The most straightforward answer is that human beings introduce complexity into their social, economic, and technological systems to solve their problems. The scholar Joseph Tainter has made this point very effectively. He suggests that over time societies encounter problems, and they tend to respond to these problems by creating more complex technologies and institutions.

This is a useful response to the question, but inevitably we can go deeper. In 1994 the economist W. Brian Arthur, one of the world’s most insightful complexity theorists, wrote an article that I regard as one of the foundation pieces of complexity science. He suggested there are really three deep sources of complexity. The first is growth in co-evolutionary diversity. This process applies equally to societies, economies, and ecological and technological systems. Ecological systems offer, perhaps, the clearest illustration. Arthur says each ecological system has a number of niches or ecological roles that may or may not be filled by various species. Niches filled by one or more species are separated by vacant niches. These vacant niches offer resources of various kinds – material, food, energy – and as a result new species evolve to fill those niches. When a new species fills a niche, it automatically creates more niches, which provide further opportunities for the evolution of yet more species. In this way over time, complexity begets complexity.

Arthur shows that this important and interesting process operates within human societies. For instance, it applies to the evolution of technologies like computer systems: we start with relatively simple computers and associated components; then new technologies, such as software packages, and hardware, such as printers and backup systems, are developed to fill the gaps between those entities, thus creating further gaps that yet newer technologies can fill.

A second process Arthur identifies is structural deepening. It’s a very different phenomenon: if growth in co-evolutionary diversity happens at the level of the whole system, structural deepening happens at the level of the individual component or unit within the system. As these components (such as species in an ecological system or firms in an economy) compete with each other, they tend to become more complex in order to break through performance barriers. This idea is similar to Joseph Tainter’s: as a species, firm, or organization confronts problems in its environment, it responds by becoming more complex.

We can see structural deepening at work in many of our technologies. Compare for instance an automobile engine back in the 1960s with one produced today. The modern engine runs much more cleanly, it’s far more efficient, and it has other attributes that make it a great improvement over the earlier version. But back in the 1960s, you might have been able to fix the engine yourself. I would challenge you to do so now. As the world gets more complex – as it structurally deepens – we have become more reliant on specialists to take care of us and to provide essential services.

Finally, Arthur talks about the phenomenon of capturing software, in which larger systems appropriate or capture the grammar that governs the operation of smaller or subordinate systems. Arthur points to the way societies have captured the software – or the fundamental physical grammar – of electricity and have then used electricity in all kinds of marvellous ways to improve people’s lives. But in the process, we have made our world much more complex.

Complexity depends on high-quality energy

I want to turn now to the relationship between energy and complexity, a topic I’ve already mentioned. I’ve noted that over the course of their history human beings have dealt with their problems by developing more complex institutions and technologies. Joseph Tainter has additionally emphasized that as we develop more complex institutions and technologies, our requirement for high-quality energy to build and sustain these institutions and technologies generally rises. Today’s modern cities for instance, exhibit extraordinary complexity from the point of view of, say, somebody in the 19th century, and the energy inputs needed to sustain these urban systems are in many respects beyond belief. (I use the term “high-quality” to refer to the thermodynamic quality of the energy in question. Some forms of energy like natural gas and electricity are very useful for doing work – essentially they can be used for a lot of different purposes – while others, like the ambient heat in our natural surroundings, are not much good for anything. A modern society can’t sustain its complexity with low-quality energy; it needs copious quantities of high-quality energy.)

Now the problem, of course, is that humankind is going through a fundamental energy transition. We’re facing supply constraints for one of humankind’s best energy sources – oil. I want to emphasize the significance of this change in our circumstances. Conventional oil provides 40 percent of the world’s commercial energy and around 95 percent of the world’s transportation energy. It’s literally the stuff the planet’s economy runs on, and in thermodynamic terms it’s very special. Three tablespoons of oil contain as much free energy as would be expended by an adult male labourer in a day. Every time we fill up a standard North American car, we put the equivalent of two years of manual labour into the gas tank. For the last century or so, cheap oil has translated into essentially dozens of nearly free slaves working for each one of us.

The oil age began in 1858 in Oil Springs, Ontario with the first commercial discovery of oil, and it will end around the middle of this century – lasting about two centuries all told. This statement doesn’t mean that we are going to run out of oil by 2050; rather, it means we’re going to switch to something else, because oil will become much more expensive than it is now.

By “expensive” I mean energetically expensive. Even now, drillers are going further into more hostile natural environments to drill deeper for generally smaller pools of lower-quality oil. They’re working harder for every extra barrel. The trend is long term, inexorable, and striking. In the 1930s in Texas, drillers got back about 100 barrels of oil for every barrel of energy they invested to drill down into the ground and to pump oil out. Today, the “energy return on investment” (as specialists call it) for conventional oil in North America is 17:1. For the tar sands in Alberta it’s around 4:1; so producers get back about four times the energy they invest. For corn-based ethanol the figure is about 1:1, which means producers put in about as much energy as they get back. Corn-based ethanol is a great subsidy for farmers but a terrible energy technology.

Taking the average energy return on investment of all energy sources in our economy, as we slide down that slope from 100:1 to 17:1 to 4:1 to 1:1, we’re inexorably using a larger and larger fraction of the wealth and capital in our economy simply to produce energy, and we have less left over for everything else we need to do – like solving our increasingly difficult problems. Steadily more expensive energy will have all kinds of effects on our societies, but most fundamentally it will make it progressively harder for us to sustain our societies’ complexity.

I’ll come back to this issue later in my presentation, but first I’d like to address the question: Is rising social, economic and technological complexity a good thing or a bad thing? I would say that it depends on the state of evolution of the complex system in question. Before I elaborate further, I’ll answer the question in brief.

The good and bad sides of complexity

Greater complexity is often a good thing. We wouldn’t be living as we do now if it weren’t for complexity. We are vastly healthier, we live longer, and we have enormously more opportunities, options, and potential in our lives as a result of the complexity we have introduced into our technologies and institutions. As Tainter argues, complexity helps us solve our problems.

Often, too, complexity is a source of innovation because it allows things that would not otherwise be combined to be brought together in unexpected ways. The complexity theorist Stuart Kauffman calls these combinations “autocatalytic sets.” Complex societies are like a big stew: we throw in all kinds of different things, mix them together for a while, and then see what happens. Richard Florida’s theory of innovation in urban areas picks up on this idea: large, diverse, and tolerant cities are engines of innovation, because they allow for countless novel and unexpected combinations of people, ideas, cultures, practices and resources.

Finally, complexity provides us with greater capacity to adapt to change, at least under certain circumstances. To the extent that complexity boosts diversity in a societal system, we have available a wider repertoire of routines, practices, and ideas for adaptation and survival when our external environment changes and new challenges arise. Some people, firms, organizations, groups, or cultures will do well and some of them won’t, but diversity raises the likelihood that at least some components of the social system will prosper in the face of change.

Similarly, if a system has distributed capability and redundancy – as many complex systems do – then if one component of the system is knocked out because of an accident in a technological system, a pathogen in an ecological system, or a fire in a forest, other components can step in to prevent cascading damage to the larger system.

In all the above respects, complexity is a good thing. But inevitably there is another side to the story, and increasingly I think we’re seeing the bad side of complexity. First of all, complexity often causes opacity; in other words, complexity prevents us from effectively seeing what’s going on inside a system. So many things are happening between the system’s densely connected components that it becomes opaque. Complexity also contributes to deep uncertainty. While opacity is a variable that operates in a slice of time – say, the present – uncertainty arises when you try to project the behaviour of a system forward into the future. The further we try to predict into the future, the fewer clues we have about what the system is going to do and how it’s going to behave.

As our world has become more complex, we have, in fact, moved from a world of risk to a world of uncertainty. In a world of risk, we have data at hand that allow us to estimate the probabilities that any given system we are working with will evolve along certain pathways, and we can also estimate the likely costs and benefits associated with evolving along one of those pathways or another. In a world of uncertainty, we simply don’t have a clue what is going to happen. We don’t have the data to estimate the relative probabilities that the system will evolve along one pathway or another; in fact we don’t even know what the possible pathways are. And we certainly can’t estimate the costs and benefits that will accrue to us along different pathways.

This is a world filled with “unknown unknowns.” I find it interesting that members of the military who have seen combat are deeply familiar with this concept. Indeed, it’s in such common use in the US military that people abbreviate it to “unk unks.” From their hard personal experience, soldiers know that surprises happen on the battlefield. Surprises come out of the blue. In his renowned treatise On War, Carl von Clauswitz, the 19th century Prussian military theorist, wrote about “friction” on the battlefield and the “fog of war.” Military people throughout history have known that they can’t plan and predict everything. They have known that in a world of uncertainty and unknown unknowns, we are ignorant of our own ignorance; often, we don’t even know what questions to ask.

Not only are complex systems opaque and uncertain, they also exhibit threshold behaviour. By threshold behaviour I mean a sharp, sudden move or “flip” to a new state. This new state may or may not be a new equilibrium – that is, it may or may not be stable. In the wake of the collapse of Lehman Brothers in September 2008, the world economy certainly flipped somewhere – it clearly exhibited threshold behaviour – but it’s not at all clear that it flipped to any kind of equilibrium, because the crisis continues to unfold today. As we have seen with the world economy, electrical grids, and large fisheries, complex systems exhibit a capacity for sudden, dramatic change.

Not all instances of threshold change are bad. The fall of the Berlin Wall and the subsequent collapse of the Soviet Union were, I would argue, indisputably good things. But to the extent that the sudden change is a surprise, so we’re not ready for it, and to the extent that our existing regime of beliefs, values, rules, institutions, and patterns of behaviour are tightly coupled to the former situation, and we don’t have any clear plans to adapt to the new situation, then threshold change is basically a bad thing.

Complexity can also cause managerial overload. This is basically an issue of information flow. I imagine I’m ringing bells in your heads when I say that today our cognitive capacity is too often exceeded by too many things happening at too high a rate. With email, BlackBerries, iPhones, and the like, we’re all at the convergence point of multiple streams of information, and we’re all juggling five, ten or more tasks or crises simultaneously.

In the last 30 years or so, with the development of fibre optic cables and advanced information switching systems, humankind has increased its ability to move information by hundreds of millions of times. But our ability to process that information in our brains has stayed the same. So waves of information pile up at the doorstep of our cerebral cortex. The proliferation of urgent demands produces decidedly sub-optimal responses like multitasking and superficial information processing, and it sharply increases stress. And if this stress exceeds the coping capacity of a person, organization, or society, it can ultimately lead to systemic breakdown.

Additionally, complexity is a bad thing when it boosts the vulnerability of systems to unexpected interactions and cascading failures. These outcomes result from a combination of dense connectivity and tight coupling between system components. Dense connectivity and tight coupling are often conflated, but they are really distinct phenomena. The former means the system has lots of links between its components. In our modern societies, new information technologies have boosted enormously the number of links between people, organizations and technologies. Tight coupling, on the other hand, means that two events in a given system are separated by a very small physical space or a very short interval of time.

When we link together tightly lots of previously unconnected things, we sharply raise the probability of unexpected interactions. A couple of decades ago, in his marvellous book Normal Accidents, the Yale sociologist Charles Perrow detailed the dangers of unexpected interactions within increasingly densely and tightly coupled systems. Today, Perrow’s warnings seem prescient, especially since humankind is now connecting together entire systems that were previously largely independent. For example, the spike in energy prices in the summer of 2008 showed that the world energy system is not only tightly linked to the world economy (many economists believe that the 2008 energy shock was the precipitating cause of the US recession and, ultimately, the current world economic crisis), but also now to the world food system. Higher oil prices stimulated a rush to biofuel production, which caused huge tracts of land to be switched from food to biofuels; this change in turn caused a surge in basic food prices around the world. Such consequences are exceedingly hard to predict in advance. Once again, we’re in a world of unknown unknowns.

Dense connectivity and tight coupling also raise the probability of cascading failures. Think of a row of dominoes falling over: the dominoes are close enough together that tipping the first one tips all the rest in succession. Cascading failures occur more often now in our modern systems because the sharply higher speed and volume of movement of energy, material and information between components of our economies, societies and technologies has dramatically tightened the physical and temporal proximity of events in these systems.

I use the analogy of a system of cars tailgating each other at high speed on a freeway. The cars are traveling fast and close together, so they cover the distance between themselves in an instant. Then, if one driver is not really paying attention, perhaps because he or she is entering a text message into a BlackBerry while switching lanes (at this point in the presentation I always see a lot of people turn their heads down, because they know who they are), a sideswipe happens and in a flash dozens of cars are piled in a heap.

This image looks a bit like the American economy about a year ago and maybe the global economy in a few weeks or months. I would argue that the resemblance is more than superficial.

Last but not least, complexity is sometimes a bad thing because it increases brittleness. To explain why, I need to outline ideas developed by one of the world’s most brilliant ecologists, a Canadian, C.S. or “Buzz” Holling. Holling’s ideas on system brittleness – more specifically on system resilience – fall under the general rubric of Panarchy Theory. I will spend some time this evening unpacking this theory, because it’s staggeringly powerful. Conceptually, this will be the most difficult part of my talk.

Evolution of complex adaptive systems (Panarchy Theory)

Panarchy theory represents the evolution of complex adaptive systems (that is, systems that adjust or adapt to their external environment as that environment changes) in three-dimensional space. This space is defined by the variables, potential, connectivity, and resilience, as you can see in the accompanying figure.

By potential, Holling and his colleagues (now spread around the world in a loose-knit organization called the Resilience Alliance) mean the possibility for novelty within a system. A rough analog would be the system’s information content. By connectivity, they mean something very much like the concept of connectivity I’ve used throughout this presentation. Finally, for Holling and his colleagues, resilience is the capability to withstand shock without catastrophic failure. As one of the New Synthesis documents says, resilient systems are able “to adapt and adjust to unforeseen events, to absorb change, and to learn from adversity.”

The accompanying figure is my own interpretation of this “adaptive cycle.” Specifically, to make it easier for a lay audience to grasp, I’ve reversed the orientation of the resilience variable, which has caused some change in the shape of the three-dimensional loop, but nothing that interferes with the model’s underlying message.

To illustrate the adaptive cycle, let’s take a simple example from Holling. He began his work studying forests, in particular the spruce forests in New Brunswick, because he was interested in understanding outbreaks of spruce budworm. In terms of its potential, connectivity, and resilience, a young forest starts at the rear of the cube, in the far bottom corner. It has relatively low the entire forest genome. The species and organisms are dispersed loosely across the landscape and thus are relatively loosely connected. But precisely because of this loose connectivity, the forest exhibits high resilience.

As the forest grows and moves towards a climax state at the cube’s front, centre, and top, it climbs what panarchy theorists call the adaptive cycle’s “front loop.” It becomes more and more connected, because more species move in, and they develop more relationships among them in terms of flows of material, energy, and fundamental elements (such as carbon, sulphur, nitrogen). As the forest climbs the front loop, potential for novelty also rises: mutations in the forest’s genetic material proliferate; these mutations may not be expressed, but they are available as possibilities of future novelty (which is, I believe, one of Holling’s most penetrating insights). Interestingly, the whole system eventually becomes less resilient too, for reasons I’ll explain shortly.

This model has enormous power to explain the evolution of other kinds of complex adaptive systems, including economies, firms, organizations, institutions, technological systems, and even whole societies. I would suggest, in fact, that it captures many characteristics of today’s global socio-ecological system. We now have to think of humankind’s global society and economy as intimately linked with an ecological system that provides the food, energy, and resources it needs to sustain itself. This global system in its entirety is now very tightly coupled, with both enormous information content and potential for novelty, but nonetheless declining resilience.

What happens at the top of the front loop is a very important part of the adaptive cycle’s story. Eventually, because of the combination of loss of resilience and some proximate trigger – in the case of a forest, perhaps a drought or the outbreak of fire or disease – the system breaks down. At this moment the time-frame shifts: while things have progressed slowly as the forest climbed the front loop – that is, change has been relatively incremental – the breakdown process that begins at the top of the loop (called the omega phase) happens quickly. The system disaggregates or decouples, and connectivity is lost, which allows for the reorganization of the system’s remaining components into new forms. This change in turn allows for the adaptation of the system to a new environment or circumstance.

So breakdown is a vital part of adaptation, an idea that’s by no means foreign to us. As you know, Joseph Schumpeter, the great Austrian economist of the middle 20th century, introduced the idea of “creative destruction.” He argued that modern capitalist economies are extraordinarily innovative precisely because their components constantly go through cycles of breakdown and rejuvenation. When a firm goes bankrupt, its resources, including its human and financial capital, are liberated and reorganized within the economy, aiding the economy’s overall adaptation.

But while we might accept this idea – more or less – within modern capitalist economies, we haven’t accepted it at all within our social or political systems. Instead, when it comes to our societies and political processes, we try to extend the front loop indefinitely; we try to make sure breakdown never happens. Holling and his colleagues say that such practices simply increase the probability of an even more serious crisis – a more catastrophic breakdown – in the future.

In working with the idea of the adaptive cycle, I have concluded that it’s important to add an amendment to Holling’s general idea: as a system moves up the front loop, stresses of various forms build. These stresses accumulate because the system learns to displace a lot of its problems to its external environment – quite simply, it pushes them beyond its boundaries. The system might become increasingly competent at managing everything within its loose boundaries, but it pushes away things it can’t manage well.

Humankind has done something like this with the consequences of its massive energy consumption: we have pushed untold quantities of carbon dioxide into the larger climate system. Now this perturbation of Earth’s climate is rebounding to stress our economies and societies. The same type of phenomenon is visible in our national and global economies: as these economies have grown in recent decades, they have accumulated enormous debts to sustain demand and employment. These debts have essentially externalized to the future the present costs of consumption. Once again, though, the chickens have come home to roost: accumulating debt has recently become a huge stress – in the present – on our economies and societies.

So, while everything may seem to be relatively stable as a system moves up the front loop of the adaptive cycle, underlying stresses – what I’ve come to call “tectonic stresses” – are often worsening.

Causes of declining resilience in complex adaptive systems

And why does resilience fall as a system approaches the top of the front loop? It appears that three phenomena common to all complex systems are at work. The first is a steady loss of capacity to exploit the system’s potential for novelty. A climax forest, for instance, has clusters of species (often including very large organisms) that absorb the majority of matter and energy coming into the forest from the external environment. As a result, very little residual matter and energy is available to support the expression of other possibilities – to support the expression of novelty. Many of the mutations that might have slowly accumulated within the forest’s genetic information don’t have a chance to express themselves.

Canadian society today offers an interesting analogue: health care. This component of our social and economic system is gobbling up an ever-larger fraction of our total resources, leaving fewer resources to support experimentation, creativity, and novelty elsewhere in our society.

The second cause of falling resilience is the declining redundancy of critical components. As a forest approaches its climax stage, redundant components are pruned away. Early in the front loop, a forest might have, say, a dozen nitrogen fixing species, each of which takes nitrogen out of the atmosphere and converts it into a form usable by plants. At its climax stage (at the top of the front loop), the forest has likely pruned away much of this redundancy, so that it has only one or two nitrogen fixers left. As a result, it becomes vulnerable to loss of those particular species and, potentially, susceptible to collapse.

The similarity to processes in our world economy is striking, although the data are somewhat anecdotal. As the world economy has become more integrated, we have seen a steady concentration of production in a relatively small number of firms – analogues of a forest’s nitrogen fixers. Two companies make all large jet liners, three companies make all jet engines, four companies make 95 percent of the world’s microprocessors, three companies sell 60 percent of all tires, two manufacturers press 66 percent of the world’s glass bottles, and one company in Germany produces the machines that make 80 percent of the world’s spark plugs. I think it’s safe to say that redundancy has been pruned from the global economy in the same way that Holling observes in ecological systems.

Third and finally, as a system moves up the front loop, rising connectivity increases the risk of cascading failure, which in turns lowers resilience.

For these three reasons, resilience eventually falls as complex adaptive systems mature. But in our contemporary world, we have something else happening too. As I’ve already noted this evening, our global economic, social, and technological systems need almost inconceivable amounts of energy to maintain their complexity, and the steady supply of this energy is now in question. Our global systems are under rising stress at the same time they’re moving steadily farther from thermodynamic equilibrium. It’s as if we’re pushing a marble up the side of a bowl: we have to expend steadily more energy to keep the marble up the side of the bowl, and if that energy suddenly isn’t available, the marble will roll back down to the bowl’s bottom, which is equivalent to a dramatic loss of complexity.

That’s my brief synopsis of Panarchy Theory. I find the parallel between these ideas and what we’re seeing in our world quite astonishing. I believe Panarchy Theory provides us with tools to understand our situation and think more creatively about the challenges we face.

For instance, earlier I remarked that whether we regard complexity as a good or bad thing depends to an extent on the stage of evolution of the system in question. Now I can explain what I meant in more detail. To an entrepreneurial actor dealing with a system early in its front loop of development – a period in which rising potential and connectivity are producing novel combinations and exciting innovations – complexity might look like a good thing. On the other hand, to a manager trying to keep a system running at the top of the front loop with its staggering connectivity and declining resilience, anticipating a breakdown because the system has become critically fragile, complexity might look like a really bad thing. It’s actually quite difficult to say finally, once and for all, whether complexity is good or bad. We have to say that it depends – on the interests of people involved with the system in question and on the system’s stage of evolution.

My interpretation of Panarchy Theory also suggests that we can expect significant breakdowns in major global systems. That statement sounds apocalyptic, and I have received a lot of grief over the years for making such statements. But I receive less grief now than I did ten years ago – which is maybe why I am speaking to you now.

Effective government in a world of complex adaptive systems

At this point, you might ask: In a world of rising complexity, uncertainty, and potential for systemic breakdown, how can we possibly govern?

The challenge, I believe, is difficult, but not insurmountable. There are many things we can do to govern our societies and the world more effectively. First of all, we need to be able to identify when we’re dealing with a complex system or problem. I don’t mean to suggest this evening that we should jettison all our previous paradigms of system management. Sometimes thinking of the world as a simple machine – or of a particular problem as the consequence of a system that operates like a simple machine – is entirely appropriate. Sometimes a Newtonian, reductionist, push-pull model of the world should guide our problem solving. But we must learn how to discriminate between simple and complex problems, which means we must have the intuition to recognize complexity when we encounter it.

When it comes to dealing with complex systems that are critically important to our well being, one of our first aims should be to increase as much as possible their resilience. As I’ve explained, systems that are low in resilience – that are brittle – are likely to suffer from cascading failure when hit by a shock. Such failures can overwhelm our personal, organizational and societal coping capacity, so that we can’t seize the opportunities for deep and beneficial change that might accompany a shock. Boosting the resilience of our critical complex systems helps ensure that we have enough residual coping capacity to exploit the potential for change offered by crisis.

Resilient systems almost always use distributed problem solving to explore the landscape of possible solutions to their problems (what complex systems theorists call the “fitness landscape”). We can infer, therefore, that if we’re to address effectively the complex problems our societies face, we need to flatten and decentralize our decision-making hierarchies and move our capacity to address our problems outwards and downwards to as many agents and units in our society as possible. It turns out that the dispersion of political power throughout our societies that we’ve seen recently is good, because this dispersion, if properly exploited, can aid distributed problem solving.

In short, the general public must be involved in problem solving. Innovation and adaptation should be encouraged across our population as a whole. Governance – as opposed to government – involves the collaborative engagement of the public in addressing common problems. And this engagement should involve lots of what Buzz Holling has wonderfully called “safe-fail experiments.” Such experiments are generally small; if they don’t work, they don’t produce cascading failures that wipe out significant chunks of larger systems that are vital to our lives. I will return to these ideas shortly.

If we want to boost our resilience and prepare for crisis, we also need to generate scenarios for breakdown. We need to look into the abyss a bit – to think about how breakdown might happen and what its consequences could be. Doing so will help us make more “robust” plans for a highly uncertain and non-linear future. Robust decision making involves developing plans that should work under a wide range of future scenarios. The plans aren’t tightly tailored to, or specified for, a particular possible future; instead, we intend that they’ll produce satisfactory outcomes across many different futures. They are, in short, robust across a number of possibilities.

We’re in a world of unknown unknowns and have only the most threadbare understanding of what might happen – even just a couple of years in the future. But we can still use our imaginations effectively. Whatever happens in the future probably won’t map precisely onto any one scenario we develop now, but events might ultimately resemble a combination of two or three of our scenarios. We need capacity to respond that can be applied across many different scenarios.

Although it’s not part of the conventional understanding of robust decision making, I would argue that this approach should also include preparing ourselves to exploit the opportunities created by crisis and breakdown, as I mentioned before. We can’t always prevent breakdown, nor should we want to. People responsible for managing our public affairs, especially those in our public services, don’t want to acknowledge this reality, because they believe their job is to make sure that breakdown and crisis never happen. Alas, significant, even severe, breakdown is going to be part of our future. Instead of denying this fact or desperately trying to figure out how to keep breakdown from ever occurring, our public managers should think about what our societies can do at moments of crisis to produce deep and beneficial change.

These are moments of high contingency and fluidity, when people are scared, worried, and looking for answers, and when conventional wisdom and conventional policies have lost credibility. We’re going to be much better off if we think now about what we’re going to do then, than if we produce ad hoc responses only when the crisis is upon us.

Governing to increase resilience

I’m going to propose a few possible scenarios. (This is where I indulge the apocalyptic side of my temperament.) Only a decade ago, these scenarios would have seemed entirely implausible; today they seem, unfortunately, much more realistic. I’m going to focus particularly on three circumstances in which a proximate shock leads to a cascading failure in a tightly coupled, brittle system.

First, Israel and Iran go to war. Israel’s fighter bombers attack Iran’s nuclear facilities, crossing Saudi airspace to get there and back. Iran responds by launching missiles at Saudi oil installations and by blocking the Straits of Hormuz – immediately taking 17 million barrels of oil a day (about 20 percent of global consumption) off the world market. In Canada, because of gaps in our domestic pipeline network that prevent Alberta oil from being shipped east, much of Ontario and Quebec experience an absolute shortage of fuel. Within two weeks of the beginning of the crisis, 30 to 50 percent of the gasoline stations in central Canada close – curtailing food shipments, emergency services, and all economic activity.

What is your response going to be? I don’t just mean your emergency response – your coping response – but your larger, longerterm response. How are you going to use the crisis as an opportunity to begin the hard process of reconfiguring Canada’s energy supply system to make it more resilient?

Here’s a second scenario: terrorists launch a major radiological attack in Washington, D.C., American officials believe the attackers have come from Canada, so they close the US-Canada border – not just for a few days but for weeks. What is your response going to be? How are you going to use the incident as a chance to reconfigure the Canadian economy so that it’s more resilient and more self-sufficient in a future where trade and intercourse could suddenly be curtailed again?

And finally, a third scenario – one that’s not even on the margins of conversation at the moment, yet is also quite plausible. Because of climate change, China experiences three consecutive years of drought. The result is a 20 percent shortfall in the country’s grain production. After China has exhausted its reserves, it enters the international grain market to buy 100 million tonnes of grain. But only 200 million tonnes of grain are available on the international market annually, so the Chinese intervention produces a sudden doubling or tripling of core food prices around the world. The consequences include major violence in developing countries and a significant political crisis in Canada.

What are you going to do? How can Canada reconfigure its food production system so that it’s more resilient? Fundamentally, this would involve making it more autonomous, because resilience is largely about boosting autonomy. I don’t mean complete autonomy. I’m not talking about autarky, but rather about loosening the coupling between our critical systems, such as our food system, and the rest of the world.

This point brings me directly to the contentious question of how much connectivity we want in our critical complex systems. I have concluded that resilient systems exhibit what I call “mid-range coupling.” They aren’t too disconnected, and they aren’t too tightly connected; they’re somewhere in the middle, as you can see in the accompanying figure.

There was a common perception in the 1990s that regardless of what variable you’d like to maximize on the left axis of this figure – well-being, prosperity, or resilience as I have here – the relationship between connectivity and that variable was more or less reflected by a line from the figure’s bottom left to its top right. In other words, most people believed that the greater the connectivity within and between our societies and within and between our critical systems, the better off we all were. In the tough intervening years we’ve learned, though, that beyond a certain point – beyond the middle of the range – connectivity actually starts to produce negative consequences of the kinds I have described this evening, including unexpected interactions, rising potential for cascading failure, and declining resilience overall.

When connectivity is low, increasing it can improve things. In a loosely connected agricultural region, for instance, greater internal connectivity allows sub-regions that suddenly can’t grow food to reach out to the rest of the system to get the food they need. But if the overall agricultural system becomes too tightly connected, it will become increasingly vulnerable to cascading failures in which a shock, like the sudden emergence of a pathogen, spreads from its entry point throughout the entire system.

Leadership in a world of rising complexity

I’m going to focus the concluding portion of my presentation on how we lead in a world of rising complexity. This issue has been at the heart of the New Synthesis project.

I have to admit that I’m now treading in somewhat unfamiliar territory. But in reading the documentation for the New Synthesis project, I came to understand that our public service confronts a problem of “entanglement” of principles of compliance with measurements of performance. Increasingly we are using objectified measures of how people perform within our public services as a way of establishing firm control over their actions. This entanglement of compliance and performance appears to be instilling a culture of fear within our public services.

I was quite struck by this quotation from the project’s documentation:

In an environment where ‘what gets measured gets attention’ and where trust is low, complex services are difficult to manage. Instead of focusing on the whole issue and program, public officials aim to avoid censure by concentrating on those specific aspects that are being measured. When employees are motivated to save face and seek out the maximum score in this way, at the expense of tackling the complex issues in an innovative way, an optimal environment, consisting of supportive behaviour and operating autonomy, which is a key to effectiveness, is lost.

Looking at this situation from the outside, I have been struck by the fact that the culture of compliance now dominating the public service reduces the possibility and potential for experimentation. We need to reform that culture. Our public-service leaders need to be constantly probing the critical systems we depend upon to determine patterns in the changing solution landscape. They can’t know exactly what will happen in these systems in the future, so they should engage in interventions to gather information. They can use small safe-fail experiments as probes to help everyone – leaders and the public alike – learn how the landscape is changing.

More generally, leaders should be “gardeners” who create conditions for experimentation and for – as Mel Cappe argued many years ago – creative failure. At the moment, it seems, there’s very little possibility for creative failure in our public service. In fact the very idea probably sends shivers up your spine. You might think: “Wow, that would be terrific, but how can we possibly do it?”

Actually, I’m not sure that the public service is the best advocate for experimentation within its own ranks. You’ll always appear self-serving, because you’ll always appear to be trying to loosen the constraints upon yourselves and your organizations. It’s really up to people like me to tell the general public that the popular obsession with governmental efficiency and with ensuring that government be error-free is producing exactly the opposite of what everyone wants. We’re getting a timid, risk-averse, conservative and conventional public service with crippled morale, whereas we desperately need a creative, nimble, flexible public service that can help lead a creative, flexible, innovative, and resilient society.

People like me have to make that case to the public, because people like me don’t appear to have a particular interest one way or the other.

I’ll finish with one last related and important point. The public not only needs to understand the importance of experimentation within the public service; it needs to engage in experimentation itself. To the extent that the public explores the solution landscape through its own innovations and safe-fail experiments, it will see constant experimentation as a legitimate and even essential part of living in our new world. To the extent that the public understands the importance of – and itself engages in – experimentation, it will be safer for all of you in the public service to encourage experimentation in your organizations.

Ultimately, the public must acknowledge a basic fact of life, something everyone learns the hard way in their personal lives: we learn more from failure than from success, and failure can be the most creative process of all if we take the right lessons from it.

Ultimately, then, we have a critical task of education. All Canadians must understand that we now live in a world that is, in its deepest essence, complex and turbulent. And all Canadians must accept that we can prosper in that world only if all sectors – public, private, and non-governmental – are constantly engaged in collaborative experiments in new ways of living.

Thank you very much.

Physics was the master science of the 20th century. Ecology will be the master science of the 21st century.

What do I mean by master science? A master science is, in part, the dominant scientific discipline of a historical epoch. It is the prototypical science of the time – the discipline that people think of first when they consider science. It’s also likely to have produced the most spectacular discoveries and technologies. More importantly, a master science generates and orders the concepts through which society understands itself and its relation to its surroundings.

Arguably, chemistry was the master science of the 18th and 19th centuries. From Antoine Lavoisier’s discovery of oxygen’s role in combustion, through Friedrich August Kekulé’s dream about benzene rings, to Alfred Nobel’s invention of dynamite, chemistry – emerging from the centuries-old practice of alchemy – produced the bulk of scientific breakthroughs during this period. It also generated the technologies of metallurgy and warfare – especially for guns, both large and small – which determined the rise and fall of the great modern empires.

In the 17th century, Isaac Newton laid the foundation for the ascendancy of physics. Although Newton’s ideas were enormously sophisticated, they nevertheless assumed that the universe resembled a machine. This machine’s behaviour was, Newton maintained, governed by laws that could be stated in precise mathematical formulae, making it predictable and potentially manageable. This notion of a law-governed, mathematically tractable, machine-like universe resonated within societies in the throes of the early Industrial Revolution, because everywhere machines were reordering economies, production processes and social relations. During the 18th and 19th centuries, physics also provided critical breakthroughs bearing on these machines’ motive power. Sadi Carnot’s analysis of the efficiency of steam engines, which laid the foundations for modern thermodynamics, was one such example.

Read the complete article from ‘Alternatives Magazine’.

Whether from economic collapse, terrorism, climate change, pandemic, energy scarcity, or the widening gap between rich and poor, he believes breakdown is inevitable. And if we won’t change our ways till we crash, it’s up to us to make sure breakdown doesn’t spiral into total collapse.

Q&A with Terrence McNally: http://temcnally.podomatic.com/entry/2009-03-26T12_24_45-07_00

Listen to the podcast:

In 2006, THOMAS HOMER DIXON, author of Canada’s #1 bestseller, THE UPSIDE OF DOWN, wrote, “September 11th and Katrina won’t be the last time we walk out of our cities.”

Whether from economic collapse, terrorism, climate change, pandemic, energy scarcity, or the widening gap between rich and poor, he believes breakdown is inevitable. And if we won’t change our ways till we crash, it’s up to us to make sure breakdown doesn’t spiral into total collapse.

Check out the book title. Today “down” is everywhere we look. Okay, there’s the “Catastrophe.” I’ll talk with HOMER DIXON in search of the “Creativity, and The Renewal…”

To listen to the interview, follow this link:  http://temcnally.podomatic.com/entry/2009-03-26T12_24_45-07_00

Thomas Homer-Dixon
CIGI Chair of Global Systems, Balsillie School, Waterloo
Centre for Environment and Business, University of Waterloo

Introduction

The author has more than two decades of experience studying the relationship between various forms of environmental stress and national and international security. This experience includes nearly a decade leading three large international research projects — involving over one hundred experts across a dozen countries — that laid down the first systematic understanding of the links between environmental stress and subnational violent conflict in poor countries.

More recently, the author’s research has focused on complex threats to global security — including climate change and energy scarcity — and the determinants of societal responses to these threats. For over two decades he has written about the political, social, and economic consequences of anthropogenic climate change and its policy implications.

This paper draws on this body of research to argue that the most common “state-centric” concerns about the effect of climate change on the Arctic — including the concerns about how climate change might influence sovereignty, resource access, territorial integrity, and the balance of power among states – are exaggerated. These concerns are grounded in a set of assumptions that may have been appropriate for 19th and 20th century world affairs but are entirely inappropriate as a basis for addressing the 21st century’s challenges. Indeed, these state-centric concerns divert policy attention away from far more critical issues, including the larger climate consequences of Arctic ice loss, such as more rapid melting of the Greenland icecap, invigoration of carbon-cycle positive feedbacks, and potentially dramatic changes in precipitation patterns much farther south affecting global food production.

The paper offers an alternative set of assumptions as a starting point for the analysis of climate change’s implications for the Arctic and Canada.

Climate Change and the Arctic: Key Characteristics

Any complete analysis of the implications of climate change for the Arctic should begin with the best estimates of the magnitude, distribution, and temporal characteristics of climate change for the region, including a detailed account of the latest results for the Arctic of the world’s best general circulation models. The NRTEE should ensure that such information forms a basis for its analysis and policy recommendations.

Two characteristics of climate change, with special implications for the Arctic and Canadian Arctic policy, are worth noting: positive feedbacks and nonlinear response.

Positive Feedbacks:

In coming years, developments in the Arctic, including loss of summertime sea ice and destabilization of the Greenland ice sheet, are likely to be so dramatic that they will drive global climate policy. Because of a number of positive feedbacks — including the ice-albedo feedback (see Figure 1) — warming is disproportionately pronounced in the Arctic, where it is happening about twice as fast as warming elsewhere.

Figure 1: The Ice-Albedo Feedback

The Earth’s climate system, both its physical and biological components, contains many feedbacks. One of the most significant recent advances in climate science has been an improved understanding of the relative balance between positive (self-reinforcing) and negative (self-equilibrating) feedbacks. Research now indicates that the climate system’s positive feedbacks outnumber and, in their aggregate force, strongly outweigh its negative feedbacks.¹ James Hansen and colleagues write:

Palaeoclimate data show that the Earth’s climate is remarkably sensitive to global forcings. Positive feedbacks predominate. This allows the entire planet to be whipsawed between climate states. One feedback, the ‘albedo flip’ property of ice/water, provides a powerful trigger mechanism. A climate forcing that ‘flips’ the albedo of a sufficient portion of an ice sheet can spark a cataclysm. . . . Recent greenhouse gas (GHG) emissions place the Earth perilously close to dramatic climate change that could run out of our control, with great dangers for humans and other creatures.²

Climate scientists have successfully incorporated into their climate models many feedbacks that operate directly on the temperature of air or water, like the ice-albedo feedback. But they have made less progress incorporating feedbacks that operate on the atmosphere’s concentrations of greenhouse gases or that affect the cycle of carbon between air, land, oceans, and organisms. Unfortunately, these feedbacks may ultimately be far more important for the stability of the planet’s climate system.

Some of these carbon-cycle feedbacks will operate mainly in Earth’s high latitudes. For instance, warming is causing large areas of permafrost to melt in Alaska, Canada, and Siberia. As this permafrost melts, its organic matter starts to rot, releasing carbon dioxide and methane (molecule for molecule, methane traps far more heat in the atmosphere than carbon dioxide). In September and early October this year, Russian research expeditions along the northern coast of Siberia found evidence that large quantities of methane were being released from methane hydrates under the seabed, perhaps as a result of warmer coastal waters and surface runoff from Siberia.

Warming is also propelling a widening beetle infestation this has killed enormous tracts of pine forest in Alaska and British Columbia. This latter infestation may soon spread across the Rocky Mountains into the vast boreal forest that extends east across Canada to Newfoundland. Dead and dying forests are vulnerable to wildfires that could emit staggering quantities of carbon. Recent research shows that between 2000 and 2020, the beetle infestation in British Columbia will cause almost a billion tons of carbon dioxide to be released into the atmosphere, five times the annual emissions of the gas from the entire Canadian transportation fleet.³

Other positive feedbacks in the carbon cycle involve the oceans. Each year, the oceans and land currently take up about half the carbon dioxide that humans emit into the atmosphere. As oceans warm, they absorb less carbon dioxide, partly because the gas dissolves less readily in warmer water, and partly because warming will reduce the mixing between deep and surface waters that provides nutrients to carbon dioxide-absorbing plankton. And when oceans take up less carbon dioxide, warming will worsen.

Policymakers do not, for the most part, grasp the implications of positive feedbacks in Earth’s climate. Yet they are an urgent concern, because once they begin operating forcefully, warming could become its own cause, accelerating to such a degree that humankind cannot stop it even with severe cuts in greenhouse gas emissions.

Nonlinear Response:

Nor do policymakers grasp the implications of nonlinear climate change. Paleoclimatological evidence drawn from ice cores, coral, sediments and the like indicate that the climate does not always respond linearly to perturbations. Flows of energy within the atmosphere and oceans on occasion undergo wholesale reorganization. Because, in large part, of the operation of feedbacks, Earth’s climate system likely has multiple discrete equilibria. A shift to a new equilibriium, should it occur, would not be reversible in a time frame relevant to human civilization.

Developments over the last two summers in the Arctic illustrate the potential nonlinear behavior of Earth’s climate system. Although the total area of ice in September fluctuates from year to year, in the last two decades it has generally declined, almost certainly because of carbon-driven global warming. During the summer of 2007, the ice cap shrank at a record-breaking pace; at its minimum it was almost 39 percent smaller than the average from 1979 to 2000. This past summer it was down about 33 percent from the average (see Figure 2)

Figure 2: 2007-08 Arctic Sea-Ice Melting: Divergence from Trend

A couple of years' dramatic melting may be a random event. But the ice loss of recent years puts the Arctic decades ahead of model predictions, indicating that climate change may be worse than expected. Indeed, the extraordinary loss of sea ice during the summers of 2007 and 2008 suggest that we may in fact be witnessing the first nonlinear "flip" in a major feature of Earth's climate system — the cyrosphere — as a result of anthropogenic climate change.

Although media and policy attention have focused on the direct effects of sea-ice loss on sovereignty, resource extraction, and transportation in the Arctic basin itself, the consequences of this loss will almost certainly extend around the world. Scientists do not have a precise understanding of these consequences, but there are reasons for great concern. The area above the Arctic Circle represents nine percent of the surface area of the planet above the Equator. As this region loses sunlight-reflecting ice and gains sunlight-absorbing open water, energy circulation across the northern half of the planet will also shift.

Scientists are worried, in particular, about the effect on Hadley cell circulation. In the northern hemisphere, this circulation consists of three important cycles between the equatorial region and the pole (see Figure 3). The polar cell derives much of its force from the sinking of cold dense air at the top of the planet. Loss of the Arctic sea ice, and warming of the sea and atmosphere at the North Pole could cause the polar cell to break down, affecting the jet streams that travel along the interface zone between the polar and Ferrel cell. This could in turn alter storm tracks, rainfall patterns and food production much further south.

Figure 3: Northern Hemisphere Hadley Cell Circulation

The Greenland ice sheet also appears to be especially sensitive to small changes in the Arctic's energy balance. Sea-ice loss will probably set off much faster melting of the ice sheet and thus faster sea-level rise.

The ice sheet is the second largest mass of ice in the world, after that in Antarctica. If Greenland were to melt entirely, sea levels would rise by seven metres. During the last interglacial period 125,000 years ago, when temperatures were roughly what they are likely to be at the end of this century, much of the Greenland ice sheet melted, and sea levels were four to six metres higher than they are right now.

The 2007 IPCC report estimated sea-level rise this century at 20 to 60 centimetres – or somewhere around half a metre. However, climate scientists now recognize that the models of ice sheet melting that underpinned the IPCC estimate were radically inadequate. These "static" models did not take into account the movement of large amounts of meltwater, through vertical cracks called moulins, from the surface of the ice sheets to their bottom. The millions of tonnes of water flowing may lubricate the movement of glaciers and increase the speed of glacial movement into the ocean; they also transfer an enormous amount of heat to the bottom, helping to melt the ice sheets from the bottom up.

In the fall of 2007, Robert Corell, chairman of the Arctic Climate Impact Assessment, the principle synthetic report on the state of the Arctic climate, commented on the Ilulissat glacier in northwest Greenland. "We have seen a massive acceleration of the speed with which these glaciers are moving into the sea," he wrote. "The ice is moving a 2 metres and hour on a front 5 kilometres long and 1,500 metres deep." He had flown over the glacier and seen "gigantic" holes in it through which vast quantities of melt water were falling. "I first looked at this glacier in the 1960s, and there were no holes. [Now] there are hundreds of them.”⁴

In light of these and other recent development, a consensus is emerging among climate scientists that oceans will rise by at least a metre this century and that they could plausibly rise two metres. A change of this magnitude would have staggering effects on coastal areas of Canada – on residential areas in British Columbia (especially on the municipalities of Delta and Richmond in the Lower Mainland) and on the ports of Vancouver, St John’s, and Halifax. With a two metre rise, concerns about rebuilding infrastructure and moving populations inland will – in a few decades – become real, even urgent.

Policymakers must keep in mind that the melting of the planet’s great ice sheets, such as that covering Greenland, is likely to be a nonlinear phenomenon. At some indeterminate point in the future, when the conditions have reached a threshold point, the rate of melting will probably jump dramatically, as appears to happening with sea-ice loss in the Arctic. Moreover, once rapid melting of the Greenland ice sheet begins, it is almost certain to be irreversible.

Policy Gaps and Considerations for Policy Development

The climate’s positive feedbacks and its likely nonlinear response to perturbations have significant implications for Canadian Arctic policy. But these implications are rarely acknowledged or understood because policymakers, scholars, and media commentators who consider the topic are largely captive of an outdated causal ontology and theory of international relations.⁵

Outdated Ontology:

Specifically, a mechanistic ontology — or at least vestigial features of such an ontology — informs virtually all discussion of climate change’s implications for the Arctic. This ontology assumes that both natural and social systems have relatively easily discernible boundaries, that the behavior of such systems is an additive consequence of the behavior of their parts, that effect is proportional to cause, that it is possible to discriminate among multiple causes in terms of their causal power, and that the “gold standard” of explanation involves the identification of a single, necessary and sufficient cause of a given phenomenon.

When it comes to the interactions between climate and human societies, these assumptions are wholly invalid. A mechanistic ontology is inappropriate for investigation of the processes within climate-society systems, because these systems are fundamentally “complex.” They are characterized by causal openness, emergent properties, disproportionality of cause and effect (i.e., nonlinear behavior, as we have seen earlier in this paper), and causal interaction (synergy).

Within such systems, events have no necessary and sufficient causes, small perturbations can have enormous consequences, and causal paths are highly contingent.

Misplaced Emphasis on State-centric Concerns:

Commentators and analysts do not often consider the implications for foreign policy of phenomena in the natural world, like climate change and resource stress. When they do, their common adherence to a mechanistic ontology usually leads them to emphasize these changes’ consequences for state power (see Figure 4). A mechanistic ontology grounds a realist theory of international relations – in which the international system is conceived as a consisting of a finite number of discrete and clearly bounded states seeking to maximize their individual power. By this view, climate change and resource stress operate largely independently of other factors; they bear on states’ interests only to the extent that they affect states’ economic and political power; and they have implications for states’ security only to the extent that they influence the risk of interstate conflict.

Figure 4: The Policy Consequences of Underlying Systems Ontologies

But research over the last twenty years on how natural factors, including resource scarcities and various forms of environmental stress, affect political and social behavior shows that these factors hardly every operate in isolation.⁶ Rather, they interact synergistically with other ecological, institutional, economic, and political variables to produce a broad range of effects — some of which might bear directly on states’ interests, but many of which do not. These latter effects, including impacts on household livelihoods, may nevertheless have enormous implications for human well-being.

This research has also shown that, to the extent that environmental stress affects states’ interests, causation is almost always indirect. This stress does not directly cause conflict between states; instead it causes various forms of social dislocation — including widening gaps between rich and poor, weakening of governance, and deeper ethnic cleavages — that in turn make subnational conflict in the form of insurgency, ethnic clashes, rebellion, and urban criminality more likely.

Climate change may have implications for global security, therefore, but they are not the implications commonly cited by foreign policy analysts and commentators. By weakening rural economies, boosting unemployment, and dislocating people’s lives in vulnerable poor countries, climate change will increase the frustrations and anger of hundreds of millions of people. Especially in Africa, but also in some parts of Asia and Latin America, it will undermine already frail governments – and make challenges from violent groups more likely – by reducing government revenues, increasing the economic clout of rent-seeking elites, overwhelming bureaucracies with problems, and revealing how incapable these governments are of helping their citizens.

In this light, the concern about the potential national security implications of climate change in the Arctic — including concern about conflicts over shipping lanes and sub-seabed oil and gas resources — is wildly misplaced. Analysts’ reliance on a realist theory of international relations that’s grounded in a mechanistic ontology encourages them to highlight implications of Arctic climate change that are of secondary and tertiary importance to humankind, and even to Canada. Access to the Northwest Passage and to reserves of oil and natural gas in the Arctic basin will seem trivial in a world whipsawed by climate shifts resulting from loss of Arctic sea ice. Policymakers need to focus on what is really important, not on what fits their 20th century worldview.

A recent excellent example of this misplaced focus was the excitement surrounding the release of the US Geological Survey’s findings on the magnitude of petroleum resources in the Arctic basin.⁷ The USGS report, which appeared on July 23 this year, was accompanied by a breathless podcast and press release headlined “90 Billion Barrels of Oil and 1,670 Trillion Cubic Feet of Natural Gas Assessed in Arctic.”⁸ Newspapers and magazines were subsequently full of uninformed and uncritical commentary about the prospects for game-changing oil and gas discoveries in the Arctic, with the advent of open water in the Arctic basin. Much of this commentary also included hand-wringing about the risks of conflict between countries over access to these resources in an increasingly energy-scarce world.

The attention given the release of these USGS results, and the types of commentary that accompanied their release, clearly reflected both commentators’ and analysts’ underlying realist and state-centric assumptions about the nature of world order: oil and gas are essential for economic prosperity, national security, and state power, and states and firms will do what is necessary to obtain them, even in remote and inhospitable parts of the world. The implicit, and astonishing, corollary was that in an increasingly oil-scarce, loss of Arctic sea ice was a good thing, because it would make accessible petroleum resources heretofore beyond humankind’s reach.

But the ease with which the USGS report fitted within the prevailing state-centric worldview meant that virtually no analysts looked closely at the report’s underlying data and methodology. Virtually no one pointed out that the total petroleum resource that the USGS estimates to exist in the Arctic would satisfy less than three years of current global oil consumption and less than 16 years of current world gas consumption. Nor did they point out that — in an world of melting and shifting sea ice, more violent Arctic storms, and a surge of icebergs from disintegrating Greenland glaciers – exploring and extracting Arctic petroleum resources might be much more, not less, difficult than it is today.

It also turns out that the USGS has a very poor track record predicting petroleum discovery with the kind of probabilistic methodology it used for the Arctic basin. In 2000, for instance, the USGS used the same methodology to calculate that Earth’s original endowment of recoverable oil was probably around 3 trillion barrels, which, if correct, means we still have more than 2 trillion barrels left.^<9 This estimate was widely cited and incorporated into the forecasts of the International Energy Agency in Paris, the U.S. Energy Information Administration, and even Saudi Arabia’s own estimates of its reserves.

We can already gauge the accuracy of this forecast, because it predicted global oil discovery would average about 24 billion barrels a year between 1995 and 2025. But during the first 12 years of this period — that is, till 2007 – average discovery has been only about 6 billion barrels a year, or about a quarter of the predicted amount.

The flaws in the USGS methodology would be obvious to a first-year undergraduate statistics major. Take for instance the estimate for “West Greenland-East Canada” in the recent Arctic assessment. On the basis of extremely limited geological and seismic evidence, the report estimates there is a 95 percent probability that at least one barrel of oil exists in the region, a 50 percent probability that 0.26 billion barrels exist, and a 5 percent probability that 34.5 billion barrels exist. Astonishingly, the USGS then averages across these already very soft figures to produce a “mean” estimate for the region of 7.265 billion barrels. It then adds this number to the estimates achieved the same way for other Arctic regions to create a total figure for expected oil resources in the Arctic.

Even if the USGS’s individual probabilistic estimates for the West Greenland-East Canada region are valid, and there is little reason to think they are, averaging across them produces a grossly misleading result. Indeed, the probability of 7.265 billion barrels existing in the region, even assuming that the underlying estimates are correct, is about 1 in 10. But statistically illiterate commentators were impressed by the apparent precision of figures estimated to three decimal places and took them as fact.

In the view of this paper’s author, even with rapid loss of Arctic sea ice in coming decades, the Arctic basin will not see an enormous expansion of oil and gas exploration. While there may be aggressive exploration, especially for natural gas, in some regions, such as the Beaufort Sea and the seas north of Scandinavia and western Siberia, it will remain on the periphery of the basin and will be constrained by its enormous expense. In light of the difficulties of exploration and extraction, little will occur off either coast of Greenland.

As a result, disputes between countries around the Arctic basin over the delineation of territorial boundaries and rights to exploit sub-seabed resources will remain muted. They will certainly not be central security concerns of any of these nations.

Similarly, while there may be increased shipment of freight and raw materials through the Arctic basin as sea ice vanishes, contemporary commentators are vastly overestimating the significance of these new routes. Sea conditions are likely to remain treacherous for much of the basin, because of drifting chunks or residual ice and very large storms over warming water. Given that there are virtual no safe-harbor ports, mariners and shipping companies will probably conclude that the risk of using routes through the basin generally outweighs any saving in time and fuel.

An Alternative Perspective:

As Figure 4 indicates, a complex-systems ontology grounds a very different view of the implications of Arctic climate change for the world. The focus shifts to the implications of Arctic changes for flows of energy and matter through the biosphere and other global physical systems, for economic production (including, especially, food production) worldwide, and ultimately for societal stability around the planet.

Canadian policy makers should shift their attention and resources commensurately. While policymakers, wedded to an outmoded worldview, fret about what Arctic climate change might do to national power directly in the basin, human well-being could be devastated around the world by cascading consequences of shifts in the Arctic’s energy balance. Ironically, these changes could – in the end – do far more damage to state-centric world order and even to states’ narrowly defined interests than any interstate conflicts we might see happen in the newly blue waters of the Arctic.

¹ M. Scheffer, V. Brovkin, and P. Cox, ‘Positive Feedback between Global Warming and Atmospheric CO2 Concentration Inferred from Past Climate Change’ (2006) 33 Geophysical Research Letters L1072.

² James Hansen, et al. “Climate and Trace Gases,” Phil. Trans. R. Soc. A 365 (2007): 1925-54.

³ W.A Kurz, et al. “Mountain pine beetle and forest carbon feedback to climate change,” Nature 452 (24 April, 2008): 987-90.

⁴ As quoted in P. Brown, “Melting Ice Cap Triggering Earthquakes,” The Guardian, 8 September 2007.

⁵ The Merriam-Webster Online Dictionary defines “ontology” as “a particular theory about the nature of being or the kinds of things that have existence.” See http://www.merriam-webster.com/dictionary/ontology.

⁶ For example, see Thomas Homer-Dixon, Environment, Scarcity, and Violence (Princeton: Princeton University Press, 1989).

⁷ United States Geological Survey, Circum-Arctic Resource Appraisal: Estimates of Undiscovered Oil and Gas North of the Arctic Circle, USGS Fact Sheet 2008-3049 (July 2008).

⁸ http://www.usgs.gov/corecast/details.asp?ID=87

⁹ USGS World Energy Assessment Team, U.S. Geological Survey World Petroleum Assessment 2000 available at
http://greenwood.cr.usgs.gov/energy/WorldEnergy/DDS-60/. See also Thomas Ahlbrandt et al., “Future Oil and Gas Resources of the World,” Geotimes (June 2000): 24–25.