Category Archives: Regime Shifts

Regime Shifts

Economist on fat tails and finance

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A special report on the future of finance in The Economist Fallible mathematical models: In Plato’s cave:

… although the normal distribution closely matches the real world in the middle of the curve, where most of the gains or losses lie, it does not work well at the extreme edges, or “tails”. In markets extreme events are surprisingly common—their tails are “fat”. Benoît Mandelbrot, the mathematician who invented fractal theory, calculated that if the Dow Jones Industrial Average followed a normal distribution, it should have moved by more than 3.4% on 58 days between 1916 and 2003; in fact it did so 1,001 times. It should have moved by more than 4.5% on six days; it did so on 366. It should have moved by more than 7% only once in every 300,000 years; in the 20th century it did so 48 times.

In Mr Mandelbrot’s terms the market should have been “mildly” unstable. Instead it was “wildly” unstable. Financial markets are plagued not by “black swans”—seemingly inconceivable events that come up very occasionally—but by vicious snow-white swans that come along a lot more often than expected.

This puts VAR in a quandary. On the one hand, you cannot observe the tails of the VAR curve by studying extreme events, because extreme events are rare by definition. On the other you cannot deduce very much about the frequency of rare extreme events from the shape of the curve in the middle. Mathematically, the two are almost decoupled.

The drawback of failing to measure the tail beyond 99% is that it could leave out some reasonably common but devastating losses. VAR, in other words, is good at predicting small day-to-day losses in the heart of the distribution, but hopeless at predicting severe losses that are much rarer—arguably those that should worry you most.

When David Viniar, chief financial officer of Goldman Sachs, told the Financial Times in 2007 that the bank had seen “25-standard-deviation moves several days in a row”, he was saying that the markets were at the extreme tail of their distribution. The centre of their models did not begin to predict that the tails would move so violently. He meant to show how unstable the markets were. But he also showed how wrong the models were.

Modern finance may well be making the tails fatter, says Daron Acemoglu, an economist at MIT. When you trade away and invest in stocks, all sorts of specific risk, in foreign exchange, interest rates and so forth, you make your portfolio seem safer. But you are in fact swapping everyday risk for the exceptional risk that the worst will happen and your insurer will fail—as AIG did. Even as the predictable centre of the distribution appears less risky, the unobserved tail risk has grown. Your traders and managers will look as if they are earning good returns on lower risk when part of the true risk is hidden. They will want to be paid for their skill when in fact their risk-weighted returns may have fallen.

Regime Shifts

Chris Field says rate of climate change faster than estimated

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At the AAAS meetings in Chicago Chris Field gave a presentation that argues that the Pace of Climate Change Exceeds Estimates:

“We are basically looking now at a future climate that’s beyond anything we’ve considered seriously in climate model simulations,” Christopher Field, founding director of the Carnegie Institution’s Department of Global Ecology at Stanford University, said at the annual meeting of the American Association for the Advancement of Science.

Field, a member of the United Nations’ Intergovernmental Panel on Climate Change, said emissions from burning fossil fuels since 2000 have largely outpaced the estimates used in the U.N. panel’s 2007 reports. The higher emissions are largely the result of the increased burning of coal in developing countries, he said.

Unexpectedly large amounts of carbon dioxide are being released into the atmosphere as the result of “feedback loops” that are speeding up natural processes. Prominent among these, evidence indicates, is a cycle in which higher temperatures are beginning to melt the arctic permafrost, which could release hundreds of billions of tons of carbon and methane into the atmosphere, said several scientists on a panel at the meeting.

The permafrost holds 1 trillion tons of carbon, and as much as 10 percent of that could be released this century, Field said. Melting permafrost also releases methane, which is 25 times more potent a greenhouse gas than carbon dioxide.

“It’s a vicious cycle of feedback where warming causes the release of carbon from permafrost, which causes more warming, which causes more release from permafrost,” Field said.

Evidence is also accumulating that terrestrial and marine ecosystems cannot remove as much carbon from the atmosphere as earlier estimates suggested, Field said.

…

While it takes a relatively long time for plants to take carbon out of the atmosphere, that carbon can be released rapidly by wildfires, which contribute about a third as much carbon to the atmosphere as burning fossil fuels, according to a paper Field co-authored.

Fires such as the recent deadly blazes in southern Australia have increased in recent years, and that trend is expected to continue, Field said. Warmer weather, earlier snowmelt, drought and beetle infestations facilitated by warmer climates are all contributing to the rising number of fires linked to climate change. Across large swaths of the United States and Canada, bark beetles have killed many mature trees, making forests more flammable. And tropical rain forests that were not susceptible to forest fires in the past are likely to become drier as temperatures rise, growing more vulnerable.

Preventing deforestation in the tropics is more important than in northern latitudes, the panel agreed, since lush tropical forests sequester more carbon than sparser northern forests. And deforestation in northern areas has benefits, since larger areas end up covered in exposed, heat-reflecting snow.

Many scientists and policymakers are advocating increased incentives for preserving tropical forests, especially in the face of demand for clearing forest to grow biofuel crops such as soy. Promoting biofuels without also creating forest-preservation incentives would be “like weatherizing your house and deliberately keeping your windows open,” said Peter Frumhoff, chief of the Union of Concerned Scientists’ climate program. “It’s just not a smart policy.”

Regime Shifts

Elimination of cats drives trophic cascade

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A new paper in the Journal of Applied Ecology (Bergstrom et al (2009). Indirect effects of invasive species removal devastate World Heritage Island, doi: 10.1111/j.1365-2664.2008.01601.x) describes how, on Macquarie Island, an important breeding location for several species of penguin, the elimination of invasive cats in attempt to protect the penguins has triggered a trophic cascade as herbivore populations have boomed defoliating the island.

The study’s lead author Dana Bergstrom, of the Australian Antarctic Division, estimates that nearly 40% has been modified, with 20% having moderate to severe change, and that rabbits have convert vegetation from complex communities to short, grazed lawns or bare ground.

Rabbits caused plant cover to decline starkly on this royal penguin "run" between 2001 (top) and 2007 (bottom). (From BBC)

Rabbits caused plant cover to decline starkly on this royal penguin "run" between 2001 (top) and 2007 (bottom). BBC

Finch Creek on sub-Antartic Macquarie Island. Rabbits have stripped 40% of the island bare of vegetation, scientists say. Photograph: /Australian Antarctic Division

Finch Creek on sub-Antartic Macquarie Island. Rabbits have stripped 40% of the island bare of vegetation, scientists say. Photograph: /Australian Antarctic Division

From the Guardian:

Things began to go wrong on Macquarie Island, halfway between Australia and Antarctica, soon after it was discovered in 1810. The island’s fur seals, elephant seals and penguins were killed for fur and blubber, but it was the rats and mice that jumped from the sealing ships that started the problem. Cats were quickly introduced to keep the rodents from precious food stores. Rabbits followed some 60 years later, as part of a tradition to leave the animals on islands to give shipwrecked sailors something to eat.

Given easy prey, cats feasted on the hapless rabbits and feline numbers quickly grew. The island then lost two endemic flightless birds, a rail and a parakeet. Meanwhile, the rabbits bred rapidly and nibbled the island’s precious vegetation.

By the 1970s, some 130,000 rabbits were causing so much damage that the notorious disease myxomatosis was the latest foreign body introduced to Macquarie, which took the rabbit population down to under 20,000 within a decade.

“The island’s vegetation then began to recover,” Bergstrom says.

But what was good for the vegetation proved bad for the island’s wildlife. With fewer rabbits around, the established cats turned instead to local burrowing birds. By 1985, conservationists deemed it necessary to shoot the cats.

The last cat was killed in 2000, but the conservationists were horrified to see rabbit populations soar. Myxomatosis failed to keep numbers down, and the newly strong rabbit population quickly reversed decades of vegetation recovery. In 2006, the resurgent rabbits were even blamed for a massive landslip that wiped out much of an important penguin colony.

…
The Tasmanian Parks and Wildlife Service intends to fix the island once and for all, and has drawn up plans to eradicate all 130,000 rabbits, along with the estimated 36,000 rats and 103,000 mice that live there.

The move could yet provoke more unexpected side effects, Bergstrom says. “This is the largest island on which this type of eradication program will have been attempted.”

Regime Shifts

Avoiding regime shifts is difficult

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Conservation magazine’s Journal Watch Online returns from a long hiatus to report on an interesting new paper on the problems of detecting regime shifts by resilience researchers Oonsie Biggs, Steve Carpenter, and W.A. “Buz” Brock (2009. Turning back from the brink: Detecting an impending regime shift in time to avert it. PNAS DOI 10.1073/pnas.0811729106).  They write:

Like the stock market, ecosystems can dramatically collapse. But how much advance notice is needed to prevent a natural system meltdown? A paper in Proceedings of the National Academy of Sciences says the answer might be several decades, which means today’s warning systems don’t detect changes nearly far enough in advance.

Using Northern Wisconsin’s sport fishery as a model, University of Wisconsin researchers determined when an ecosystem reaches the brink of an unstoppable shift, then estimated when recovery efforts must start in order to avert collapse. They found that some rapid actions only need short timetables; angling cuts can prevent permanent damage to fisheries even if they’ve been declining for ten years. But other changes, like restoring habitat after too much shoreline development, must start as many as 45 years before ecological health indicators start wobbling.

The problem is, most indicators in today’s early-warning systems can’t detect serious shifts that far out. Even if they could, it might still take policymakers years to enact recovery schemes. Which leads the authors to plea for indicators that work on a longer horizon, and for policy makers to move swiftly once scientists buy them some time.

Regime Shifts

Climate lurches as global game changers

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In response to the Edge.org 2009 annual question, which this year was – What game-changing scientific ideas and developments do you expect to live to see? Laurence Smith, Professor of Geography and Earth & Space Sciences at UCLA, writes about abrupt climate change in West Antarctica and seven other sleeping giants:

We used to think climate worked like a dial – slow to heat up and slow to cool down – but we’ve since learned it can also act like a switch. Twenty years ago anyone who hypothesized an abrupt, show-stopping event – a centuries-long plunge in air temperature, say, or the sudden die-off of forests -would have been laughed off. But today, an immense body of empirical and theoretical research tells us that sudden awakenings are dismayingly common in climate behavior. …

The mechanisms behind such lurches are complex but decipherable. Many are related to shifting ocean currents that slosh around pools of warm or cool seawater in quasi-predictable ways. The El Niño/La Niña phenomenon, which redirects rainfall patterns around the globe, is one well-known example. Another major player is the Atlantic thermohaline circulation (THC), a massive density-driven “heat conveyor belt” that carries tropical warmth northwards via the Gulf Stream. … a THC shutdown nonetheless remains an unlikely but plausible threat. It is the original sleeping giant of my field.

Unfortunately, we are discovering more giants that are probably lighter sleepers than the THC. Seven others – all of them potential game-changers – are now under scrutiny: (1) the disappearance of summer sea-ice over the Arctic Ocean, (2) increased melting and glacier flow of the Greenland ice sheet, (3) “unsticking” of the frozen West Antarctic Ice Sheet from its bed, (4) rapid die-back of Amazon forests, (5) disruption of the Indian Monsoon, (6) release of methane, an even more potent greenhouse gas than carbon dioxide, from thawing frozen soils, and (7) a shift to a permanent El Niño-like state. Like the THC, should any of these occur there would be profound ramifications – like our food production, the extinction and expansion of species, and the inundation of coastal cities.

…the presence of sleeping giants makes the steady, predictable growth of anthropogenic greenhouse warming more dangerous, not less. Alarm clocks may be set to go off, but we don’t what their temperature settings are. The science is too new, and besides we’ll never know for sure until it happens. While some economists predicted that rising credit-default swaps and other highly leveraged financial products might eventually bring about an economic collapse, who could have foreseen the exact timing and magnitude of late 2008? Like most threshold phenomena it is extremely difficult to know just how much poking is needed to disturb sleeping giants.

Regime Shifts

Don Ludwig on the Black Swan

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The applied mathematician and scholar of uncertainty Don Ludwig reflects on the financial crisis, resilience, and The Black Swan:

This is a sort of book review. By now you may have heard of The Black Swan: the impact of the highly inprobable by Nassim Nicholas Taleb published by Random House (2007).

Taleb is from Lebanon, but he prefers to be called a Levantine. He worked as a trader in currencies, and maybe also derivatives. He claims that nothing of importance in finance can be predicted, except its unpredictability. His book will undoubtedly attract attention for its claim of an inevitable financial collapse, like the one we are experiencing.

He writes on p. 225:
I spoke about globalization in Chapter 3; it is here, but it is not all for the good: it creates interlocking fragility, while reducing volatility and giving the appearance of stability. In other words, it creates devastating Black Swans [events that are extremely rare and important]. We have never lived before under the threat of a global collapse. Financial institutions have been merging into a smaller number of very large banks. Almost all banks are now interrelated. So the financial ecology is swelling into gigantic, incestuous, bureaucratic banks (often Gaussianized [assuming normal deviations] in their risk measurement) — when one falls, they all fall. [lengthy footnote here, which includes the statement that “Fannie Mae, when I look at their risks, seems to be sitting on a barrel of dynamite”] The increased concentration among banks seems to have the effect of making financial crisis less likely, but when they happen they are more global in scale and hit us very hard. We have moved from a diversified ecology of small banks with varied lending policies, to a more homogeneous framework of firms that all resemble one another. True, we have fewer failures, but when they occur … [no deletion here] I shiver at  the thought. I rephrase here: we will have fewer but more severe crises. The rarer the event, the less we know about its odds. It mean[s] that we know less and less about the possibility of a crisis.

Taleb goes on to mention the power blackout of 2003 as an example of what happens when things are tied too closely together.  Taleb points out that all the experts use Gaussian assumptions for risk analysis, which delivers precisely the wrong answer. Hence I think that it is extremely likely that the favored solution to the world financial crisis will be to tie the financial system even more tightly together, thus ensuring an even bigger collapse next time. It seems to be happening already. There is no sign that Obama has twigged to the hazards of greater financial integration. There is no sign that the experts can learn from collapses: they don’t seem to have learned from past collapses, as Taleb points out.

I think we can learn from Taleb: he writes very forcefully, but exaggerates his points too much. It may be that if we confine ourselves to financial situations, then his statements are valid, even though they are extreme. Taleb seems to have been treated very nastily by the financial establishment: Scholes, Merton & Co. He seems to be both hurt and angry. Perhaps this causes his arrogance as well. I had to grit my teeth to get through to the later chapters, which have most of the substance.

Taleb offers some financial advice:
1. Above all try to protect yourself from the big drops that are coming (have already come). This implies investing a very high percentage in lower risk securities such as government bonds.

2. Try to participate in the big booms that are also sure to come. Taleb advises spreading some stuff in venture capital. In view of the behavior of the Vancouver stock exchange, I should think that it would be necessary to try to avoid scams. See David Baines in the Vancouver Sun for details (e.g.).

What has this to do with ecology?

Buzz Holling has been talking for years about “surprise”, which is just another name for Black Swans. Anyone who has ever looked at ecological data knows that deviations are not Gaussian. Of course, if we drop the Gaussian or some similar assumption, we lose most of statistics, and we lose all of “risk analysis”. So we lose just about all theory. Experts can’t function without theory, so they make unrealistic assumptions, and come up with the wrong answers in Black Swan situations.

Since Black Swans are rare, ordinary experience doesn’t show any, and the experts are confirmed in their misleading assumptions, until the next time.

We can use analogies instead of theory. I recall the raft analogy we used years ago to illustrate resilience: in order to survive on rough seas, we use loose coupling rather than strong coupling. Likewise, we guard against overconfidence: another of Buzz’ favorite themes. Managing for resilience involves guarding against collapses, even though they might be rare: it implies a precautionary principle. In light of the recent financial collapse, this latter point might finally be accepted for ecological management.

Ecological Management, Regime Shifts

Financial resilience – Taleb and Mandelbrot reflect on crisis

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Nassim “Black Swan” Taleb writes on Edge about an unwillingness or consider and remember extreme events leads to financial disaster in The Fourth Quadrant: A map of the limits of statistics.

Statistical and applied probabilistic knowledge is the core of knowledge; statistics is what tells you if something is true, false, or merely anecdotal; it is the “logic of science”; it is the instrument of risk-taking; it is the applied tools of epistemology; you can’t be a modern intellectual and not think probabilistically—but… let’s not be suckers. The problem is much more complicated than it seems to the casual, mechanistic user who picked it up in graduate school. Statistics can fool you. In fact it is fooling your government right now. It can even bankrupt the system (let’s face it: use of probabilistic methods for the estimation of risks did just blow up the banking system).

The current subprime crisis has been doing wonders for the reception of any ideas about probability-driven claims in science, particularly in social science, economics, and “econometrics” (quantitative economics). Clearly, with current International Monetary Fund estimates of the costs of the 2007-2008 subprime crisis, the banking system seems to have lost more on risk taking (from the failures of quantitative risk management) than every penny banks ever earned taking risks. But it was easy to see from the past that the pilot did not have the qualifications to fly the plane and was using the wrong navigation tools: The same happened in 1983 with money center banks losing cumulatively every penny ever made, and in 1991-1992 when the Savings and Loans industry became history.

It appears that financial institutions earn money on transactions (say fees on your mother-in-law’s checking account) and lose everything taking risks they don’t understand. I want this to stop, and stop now— the current patching by the banking establishment worldwide is akin to using the same doctor to cure the patient when the doctor has a track record of systematically killing them. And this is not limited to banking—I generalize to an entire class of random variables that do not have the structure we thing they have, in which we can be suckers.

And we are beyond suckers: not only, for socio-economic and other nonlinear, complicated variables, we are riding in a bus driven a blindfolded driver, but we refuse to acknowledge it in spite of the evidence, which to me is a pathological problem with academia. After 1998, when a “Nobel-crowned” collection of people (and the crème de la crème of the financial economics establishment) blew up Long Term Capital Management, a hedge fund, because the “scientific” methods they used misestimated the role of the rare event, such methodologies and such claims on understanding risks of rare events should have been discredited. Yet the Fed helped their bailout and exposure to rare events (and model error) patently increased exponentially (as we can see from banks’ swelling portfolios of derivatives that we do not understand).

Are we using models of uncertainty to produce certainties?

…So the good news is that we can identify where the danger zone is located, which I call “the fourth quadrant”, and show it on a map with more or less clear boundaries. A map is a useful thing because you know where you are safe and where your knowledge is questionable. So I drew for the Edge readers a tableau showing the boundaries where statistics works well and where it is questionable or unreliable. Now once you identify where the danger zone is, where your knowledge is no longer valid, you can easily make some policy rules: how to conduct yourself in that fourth quadrant; what to avoid.

…

Now it lets see where the traps are:

First Quadrant: Simple binary decisions, in Mediocristan: Statistics does wonders. These situations are, unfortunately, more common in academia, laboratories, and games than real life—what I call the “ludic fallacy”. In other words, these are the situations in casinos, games, dice, and we tend to study them because we are successful in modeling them.

Second Quadrant: Simple decisions, in Extremistan: some well known problem studied in the literature. Except of course that there are not many simple decisions in Extremistan.

Third Quadrant: Complex decisions in Mediocristan: Statistical methods work surprisingly well.

Fourth Quadrant: Complex decisions in Extremistan: Welcome to the Black Swan domain. Here is where your limits are. Do not base your decisions on statistically based claims. Or, alternatively, try to move your exposure type to make it third-quadrant style (“clipping tails”).

Below I’ve redrawn Taleb’s figure.  His article provides a fuller picture.Taleb's quadrants

Similarly, Scientific American reprints Benoit Mandelbrot’s 1999  How Fractals Can Explain What’s Wrong with Wall Street:

Individual investors and professional stock and currency traders know better than ever that prices quoted in any financial market often change with heart-stopping swiftness. Fortunes are made and lost in sudden bursts of activity when the market seems to speed up and the volatility soars. Last September, for instance, the stock for Alcatel, a French telecommunications equipment manufacturer, dropped about 40 percent one day and fell another 6 percent over the next few days. In a reversal, the stock shot up 10 percent on the fourth day.

The classical financial models used for most of this century predict that such precipitous events should never happen. A cornerstone of finance is modern portfolio theory, which tries to maximize returns for a given level of risk. The mathematics underlying portfolio theory handles extreme situations with benign neglect: it regards large market shifts as too unlikely to matter or as impossible to take into account. It is true that portfolio theory may account for what occurs 95 percent of the time in the market. But the picture it presents does not reflect reality, if one agrees that major events are part of the remaining 5 percent. An inescapable analogy is that of a sailor at sea. If the weather is moderate 95 percent of the time, can the mariner afford to ignore the possibility of a typhoon?

Ecosystem services, Regime Shifts

Bamboo, rats, and famine

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Many species of bamboo flower and then die in synchronized cycles. These cycles have substantial ecological impacts, and in post cyclone Burma appear to be contributing to famine.  From the Guardian Cyclone, starvation – now plague of rats devastates Burmese villages

Four months after Cyclone Nargis devastated Burma, another natural disaster has struck the country. This time the ruling military regime has had 50 years to prepare for it, yet it has still proved unable and unwilling to respond.

The disaster, known in Burma as maudam, is caused by a cruel twist of nature. Once every 50 years or so the region’s bamboo flowers, producing a fruit. The fruit attracts hordes of rats, which feed on its seeds. Some believe the rich nutrients in the seeds cause the rodents to multiply quickly, creating an infestation. After devouring the seeds, the rats turn on the villagers’ crops, destroying rice and corn. In a country once known as the rice bowl of Asia, thousands of villagers are on the brink of starvation.

The last three cycles of flowering occurred in 1862, 1911 and 1958, and each time they were followed by a devastating famine. The current maudam is proving just as disastrous.

The same sequence of events – bamboo flowering, fruit, rats, and then famine – occurred earlier this year in the mountains of Bangladesh.

Regime Shifts, Visualization

Algal Bloom along the Coast of China

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There has been a lot of news coverage of the large coastal algal bloom at China’s Olympic sailing site in Qingdao. The Chinese government claims the bloom is now under control.

NASA’s Earth Observatory has published some remote sensed images of the bloom from MODIS:
MODIS comparison of algal bloom

On June 28, 2008, the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua satellite captured these images of Qingdao and the bay of Jiaozhou Wan. The top image is a natural-color image similar to what a digital camera would photograph. The bottom image is a false-color image made from a combination of light visible to human eyes and infrared light our eyes cannot see. In this image, vegetation appears vibrant green, including the strips of algae floating in the bay and in the nearby coastal waters.

These images show the bay at the beginning of a local cleanup effort. (Daily images of the area are available from the MODIS Rapid Response Team.)

Regime Shifts

The long history of human-environment interactions in China

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In a recent paper, JA Dearing and colleagues (J. Paleolimnology 40: 3-31) use paleolimnological techniques to explore the long-term history of the region around Erhai Lake in Yunnan Province. Lake sediment cores (which can explain catchment vegetation, flooding, soil erosion, sediment sources and metal workings) are complemented by independent regional climate time-series from speleothems, archaeological records of human habitation, and a detailed documented environmental history. The authors integrate these data to “provide a Holocene scale record of environmental change and human–environment interactions.”

They use these data to ask:

  • “How sensitive are the studied environmental system processes to climate and human drivers of change?”
  • “Can we observe long-term trajectories of socio-environmental interactions, or periods of social collapse and recovery?”

The authors identify a number of points at which there were major changes in the human interaction with the landscape, including ~9000 cal year BP, when sediment records show a ‘human-affected environment’, ~4800 cal year BP, when major deforestation for grazing led to the extirpation of forest species and some functional units, and ~2000 cal year BP at the introduction of paddy field irrigated farming, and ~1600 cal year BP at which point surface erosion and gullying were caused by increased exploitation of mountain slopes. They go on to suggest that these records indicate several major ‘periods’ in human-environment interactions in this area:

The earliest of these cases probably represents the dispersion of the population away from the established sedentary agricultural units on alluvial fans to the more inhospitable margins of the lake and the valleys. This perhaps signifies the end of the ‘nature dominated’ phase (Messerli et al.) where society could cause significant modification of the landscape but was still vulnerable to the main risks of drought and flood (though the evidence for climate determinism is weak). In contrast, the introduction of irrigation is associated with a trend of weakening monsoon intensity, increasing numbers of centennial scale dry phases, and population growth. It represents an agrarian society in transition, using technological innovation to raise carrying capacities without increasing greatly the vulnerability to drought or flood. The third period is linked to natural population growth, inward migration and metal extraction brought about by the rise of Nanzhao/Dali as a major center”

The authors then ask at what stage of the adaptive cycle the modern Erhai socio-ecological system exists:

At Erhai, the slow processes of weathering and soil accumulation, in association with vegetation cover held fairly constant by a benign early-mid Holocene climate, were interrupted by fast processes of anthropogenic modification of vegetation. For many centuries, this concatenation of ‘slow–long’ and ‘fast–short’ processes led to a resilient land use-soil system (cf. Gunderson and Holling). But increasing perturbations led to system failure, and we can observe that the late Ming environmental crisis represents the end of the last release phase. Thus, the modern landscape may be approaching a conservation phase (K) characterised by minimum resilience.

Dearing and colleagues explore the meanings of this research for current sustainability and conclude that the main threat to the region is high magnitude-low frequency flooding of the agricultural plain and low terraces, which is exacerbated by:

  1. continued use of high altitude and steep slopes for grazing and cultivation that generate high runoff from unprotected slopes and maintain active gully systems, particularly in the northern basins;
  2. reduction or poor maintenance of paddy field systems, engineered flood defences, river channels and terraces; [and]
  3. increased intensities of the summer monsoon.

This fascinating paper is an excellent example of how historical data sources can be integrated to provide a new perspective on social and ecological change over long periods of time.