A Journal of Sustainable Human Development
Vol. 7, No. 9, September 2011|
Luis T. Gutiérrez, Editor
Are We Entering an Era of Concatenated Global Crises?
Duan Biggs, Reinette (Oonsie) Biggs, Vasilis Dakos,
Robert J. Scholes and Michael Schoon
This article was originally published in
Ecology and Society, 16(2): 27, 2011.
REPRINTED WITH PERMISSION
The risk of an escalation in number and intensity of crises arising from
accelerating human-induced global change is an issue of substantial
concern to policy makers (MA 2005, IPCC 2007, Battisti and Naylor 2009,
Rockström et al. 2009). In particular, there is evidence to suggest
that large magnitude disturbances may become increasingly coupled in
time and space, leading to concatenated global crises (MA 2005, Adger et
al. 2009, Rockström et al 2009). An escalation in global shocks, and
particularly concatenated global shocks, are likely to have especially
large impacts on the world’s poor and jeopardize efforts to
substantively reduce global poverty in the 21st century (WRI 2008, UNDP
2010, World Bank 2010).
Disasters such as recent flooding in Pakistan and China, unprecedented
fires in Russia, and hurricane Katrina, which had damage costs of over
US$250 Billion (Comfort 2005), are recent examples of ‘natural
disasters’ that particularly affected the poor. There is now substantial
evidence that the frequency of such events is likely to increase
because of human-induced global change, including climate change,
land-cover conversion, and increased global connectivity (MA 2005, IPCC
2007). If such events also become more concatenated, their impacts are
likely to be worsened. For instance, the impacts of recent flooding in
northeastern Australia increased vulnerability of affected areas to the
impacts of cyclone Yasi.
Growing global connectivity increases the potential for crises to
spread, synchronize, and interact in novel ways as social-ecological
systems (SESs) around the world become increasingly connected (Young et
al. 2006, Peters et al. 2008). The global number of internet users grew
by 362% from 360 million in 2000 to 1.67 billion in 2009 (International
Telecommunications Union 2009), and has been an important factor in the
spread of political dissent, for example in North Africa. International
tourism arrivals grew from 25 million in 1950 to just under 700 million
in 2002, and over 900 million in 2007 (World Tourism Organization
2008), but then dropped worldwide during the 2008 financial crisis. In
biotic systems, the spread of alien invasive species is accelerating
(McGeogh et al. 2010), particularly in association with increased
movement of goods and people around the globe.
This paper provides a synthetic summary of the mechanisms through which
large magnitude disturbances are increasingly coupled in time and space,
leading to concatenated crises. Concatenated crises are disturbances,
i.e., shocks, that emerge near simultaneously, spread rapidly, and
interact with each other across the globe. We analyze the food price
crisis of 2008, an interaction between the oil price spike of 2007,
pro-biofuel policies, and reactionary protectionism, as an example of a
globally coupled crisis in which origin and effects stemmed from far
removed parts of the world and diverse economic sectors, and
particularly affected the poor. Finally, we discuss recent advances in
resilience thinking, specifically how advances in detecting regime
shifts and in governance thinking can build resilience to concatenated
Two mechanisms may lead to enhanced concatenation of crises. First,
global drivers are becoming increasingly dominant over local drivers as
determinants of the dynamics of SESs. This increases pressures
experienced by a SES; many failures are attributed to ‘multiple
stresses,’ acting additively or even multiplicatively. Importantly, it
also leads to synchronous changes across systems in different parts of
the globe, increasing the scale of disasters. Second, increased
connectivity can enable local disturbances to propagate faster, turning
local disasters into global crises. Increased connectivity also means
there is a higher risk of management responses in one system
unintendedly precipitating undesirable change in far removed systems.
Powerful global-scale drivers
Global-scale processes are increasingly important drivers of change.
Examples include climate change (IPCC 2007), ocean acidification (Orr et
al. 2005), invasive species (McGeogh et al. 2010), pandemics such as
the extinction of amphibians due to the Chytrid fungus (Berger et al.
1998), and the globalization of agricultural commodity markets (Adger et
al 2009). Global drivers on their own, or in combination with local
drivers, can put sufficient pressure on local ecosystems to result in
collapse of the delivery of local ecosystem services on which the poor
often directly depend. For example, increasing temperatures and lower
rainfall thought to be associated with global-scale greenhouse gas
emissions add extra pressure to ecosystems in southeastern Australia
(Murphy and Timbal 2008) that have already suffered extensive
degradation due to local pressures. These combined global and
local-scale pressures have jeopardized commercial crop production and
water quality in several areas and led to bankruptcy of farmers
(Pengelly and Fishburn 2002).
Propagation of shocks and management responses through increasing global connectivity
Increased connectivity enables local-scale processes to propagate
upward, generating impacts at continental to global scales (Peters et
al. 2008). Disease epidemics are especially sensitive to connectivity.
The spread of bubonic plague (‘Black Death’) in the 14th century was by
local spatial diffusion, which effectively confined it to Europe. In
contrast, growing connectivity in the age of air travel means that
disease epidemics that previously might have died-out locally are now
propagated around the globe, as in the case of the SARS and H1N1
outbreaks (Fraser et al. 2009, Vespignani 2009). Thus, if global
pandemics are to be contained in the modern era, a highly effective
system of early disease detection and rapid response is required.
Socioeconomic systems are also susceptible to rapid contagion. The
potential for the propagation of crises to distant SESs can, on their
own, or in combination with global and local pressures push those
systems below a critical level of service delivery. For example, the
global financial crisis of 2008 propagated from failures in the U.S.
housing market to the banking sector in the developed world, ultimately
affecting availability of credit globally and impacting the poor in both
developed and developing regions. In particular, although this crisis
primarily affected banking sectors in high income countries, it
substantially exacerbated levels of unemployment and poverty in low and
middle income countries (Brunnermeier 2009, McCawley 2009, World Bank
Greater connectivity and enhanced feedbacks between systems furthermore
increases risk that management responses in one region become drivers of
change in others. As impacts of global drivers and propagated
disturbances increase, decision makers take action to mitigate the
impacts of these crises in their constituencies. In a highly coupled
world, actions in one region may add pressures to systems in other
regions and create, or contribute to, crisis conditions elsewhere. For
example, Adger et al. (2009) show how incentives for increased coffee
production in Vietnam had the intended effect of increased well-being
for some in Vietnam, but led to a reduction in global coffee prices,
decreasing livelihood security of communities dependent on coffee
production in Mexico.
The food price crisis of 2007 to 2008 is an excellent example of how
policy responses by individual countries, combined with powerful global
drivers in highly coupled systems, ultimately affected the entire globe.
Between 2004 and 2008, the price of staples such as rice increased by
255% and wheat by 81% before falling again (Figure 1; Headey and Fan
2008). The increased food prices resulted in effective food shortages,
as poorer people were no longer able to afford food, and to food riots
in a number of countries (Figure 2), ultimately affecting over 100 million
people worldwide. Prior to 2004, the real prices of staple foods had
declined for nearly three decades and were at an all-time low (Headey
and Fan 2008). However, from 2004 to 2008, the price of petroleum, coal,
and natural gas increased by an average of 127% (Headey and Fan 2008).
Energy forms a large component of food production and transport costs.
In 2003, the EU enacted pro-biofuel production policies (the USA
followed in 2005), partly in response to the rising energy price, but
also in response to security concerns and to some extent to mitigate
climate change. From 2007 to 2008, the resulting conversion of land from
food to biofuel production exacerbated inflationary pressure on global
food prices, already higher from increasing energy and fertilizer costs.
Some authors also point to the effect of droughts in key production
regions in reducing food supplies as an additional cause of the price
escalation (Garber 2008, Mitchell 2008). In dealing with the emerging
food price crisis, a number of countries, starting with India but
ultimately including Egypt, Vietnam, Argentina, Russia, India, and
China, enacted food export restrictions, bans, and taxes, which further
restricted food supply and exacerbated price increases at the global
scale (Beattie 2008). For rice in particular, the export bans played a
major role in the upsurge in price (Headey and Fan 2008). Moreover,
globally connected financial markets have allowed the development of
commodity derivatives including food. Investments in commodity
derivatives are used as a hedge because returns in the commodity sector
are relatively uncorrelated with returns to other assets (FAO 2010).
Although commodity derivatives were not the cause of the food price
crisis, the derivative markets have probably amplified price volatility
(Headey and Fan 2008, FAO 2010).
Figure 1. International prices of rice and wheat from 1983 to 2008 per ton in US$ and timeline of key
events in the food price crisis (Headey and Fan 2008, IRRI 2010).
The food price crisis illustrates how a series of concatenated global
crises interacted with different policy responses in a diverse range of
countries to propagate the crisis throughout a highly connected global
system. Rising energy prices were the global driver that underpinned the
crisis. The national-scale pro-biofuel policies, a policy response from
powerful high income countries, contributed to the increase of food
prices globally. Food export restrictions were a response by decision
makers in middle and low income countries to try to avert crises within
their constituencies. However, the highly coupled nature of global food
markets resulted in drastic price increases because of the export
restrictions. The result was food shortages and riots in many low income
countries in the Caribbean, Africa, and Asia (Figure 2).
Figure 2. The interactive effects of global drivers and national-scale policy responses led to the food price
crisis of 2007 to 2008 with origins and impacts in far removed regions and sectors of the globe. The
crisis was exacerbated by droughts in key production regions.
The food price crisis also illustrates how vulnerable low income
communities are often most seriously affected by global crises. The
population groups most vulnerable to higher food prices are those that
spend a large proportion of their income on food, and have few coping
strategies on which to rely (Brinkman et al. 2009, Yngve et al. 2009).
The 2007-2008 food price crisis was followed shortly by the global
financial crisis that reduced exports, economic growth, levels of
employment, and government budgets for social support in many low and
middle income countries (Brinkman et al. 2009). Although food prices
dropped as a result of financial crisis, the Food and Agriculture
Organization’s Cereal Price Index was still 50% higher in January 2009
than in 2005. Simulations suggest that an additional 457 million people
are therefore at risk of hunger and malnutrition (Brinkman et al. 2009).
Agricultural production provides a good example of how humans aim to
suppress natural variation, for example in water availability and pest
outbreaks, to create a stable environment for economic activity. The
tendency to reduce natural variation in a highly connected world creates
further possibilities for the emergence of entirely novel crises.
The compounding effect of suppressing natural variation
Humanity’s tendency to damp down natural variation can reduce the
buffering capacity of SESs to shocks. The policy of suppressing small
wildfires, for instance in the western USA and southeast Australia, has
led to large, high-impact conflagrations because of the build-up of fuel
(Minnich 2001, Janssen et al. 2004). Repeated insecticide application
has been associated with periodic outbreak of insect plagues (Ludwig et
al. 1978). This is because ecosystem components and suites of species
that are adapted to extreme values of environmental conditions are
competitively disadvantaged when those conditions are not experienced,
and are progressively lost from the system. Hence, in the first example,
plant communities become dominated by nonfire adapted species, which
are overwhelmed by the intensity of the eventual fire. In the second
example, when insecticides fail, the natural mechanisms that limit
insect outbreaks are no longer effective. In an analogous case, the
canalization and structural modification of river systems have increased
the amplitude and frequency of severe floods as the natural buffering
capacity against floods is reduced or removed (Criss and Shock 2001).
Paradoxically, we tame the environment to promote stability but this
taming may sow the seeds for later larger crises. The reduced buffering
capacity of SESs to shocks increases the risk of transgressing dangerous
thresholds; increased connectivity then propagates the failure
The emergence of novel crises
The food price crisis was a global emergency that stemmed from powerful
global drivers, high levels of connectivity, and reactive national
policies. We may be able to predict, and mitigate against, the
re-emergence of similar crises. However, complex systems of
interdependent networks can also behave in unexpected ways leading to
outcomes that are difficult, or close to impossible, to predict
(Vespignani 2009, Buldyrev et al. 2010). In addition, it is very
challenging to detect the approach of a critical threshold in a SES
without actually crossing it (Biggs et al. 2009, Scheffer et al. 2009).
Timely and accurate prediction of large-scale system collapses resulting
from concatenated crises, in which the transgression of critical
thresholds, interconnectivity, and reduced buffering capacity to shocks
interact, may be beyond our capacity, and once they emerge, our response
strategies may be inadequate for such unprecedented situations.
How can humanity deal with the uncertainty implicit in an era of novel
concatenated crises? We propose the following research areas to further
The answers to these questions are currently unclear, except in
unhelpfully general terms. Some of the uncertainty may be reducible
through research and by applying advances in network theory and analysis
(e.g., Buldyrev et al. 2010) and web-based tools for monitoring (e.g.,
Galaz et al. 2010). However, other aspects of the uncertainty
surrounding concatenated crises are probably irreducible, because they
result from fundamentally unpredictable processes. As society
increasingly confronts such situations, there is a need to evolve
responses suited to the realities of complex systems.
- Which local systems are particularly vulnerable to the pressures imposed by global drivers?
- Which thresholds may exist at regional to global-scale (planetary boundaries,
sensu Rockström et al. 2009) that may lead to propagating crises?
what circumstances are the effects of crossing local-scale thresholds
likely to propagate upward and outward, because of connectivity and
- What types of management response at local and regional scales are likely to have undesirable consequences for other regions?
types of actions can contain the spread of shocks once they occur
(sensu Vespignani 2009), and at what scales are they effective?
Humanity needs to learn to live within dynamic, diverse, and
interconnected systems. Society’s ability to deal with crises will be
enhanced by our capacity to learn from experiences elsewhere and in the
past (Pahl-Wostl 2006, Chapin et al. 2010). For example, awareness of
the consequences of government inaction during the Great Depression of
1929 to 1933 enabled a concerted policy response by governments during
the recent financial crisis (Wolf 2009). The EU’s reduction in
incentives for biofuels in response to the 2007-2008 food price crisis
is another example of adaptive learning. Similarly, an increased
tolerance of noncrisis level variation in SESs can reduce the risk of
collapse when a system is exposed to larger shocks. Moreover,
successfully coping with small disturbances has been shown to increase
the resilience of individuals, organizations, and communities to later
crises (van Praag 2003, Cioccio and Michael 2007).
Recent developments in understanding how systems behave when they are
close to transitions may offer new tools in dealing with the increased
potential of unexpected changes. There is evidence of a variety of
statistical signals prior to critical transitions (Scheffer et al.
2009). Systems close to a threshold appear increasingly volatile
(Carpenter and Brock 2006) and correlated (Ives 1995), both in time
(Held and Kleinen 2004) and in space (Dakos et al. 2010). Although these
signals do not provide the precise location of a threshold, they do
give an indication of the proximity to a regime shift (van Nes and
The same increased connectivity that promotes the concatenation of
crises also provides unprecedented opportunities to learn about emerging
problems and coordinate a response. For example, the World Health
Organization uses web-crawlers to collect data that can help detect the
outbreak of an epidemic (Weir and Mykhalovskiy 2006). Similar approaches
can be combined with the early warning methods mentioned above, to
provide tools that may prevent the spread of concatenated crises in
ecosystems and SESs (Galaz et al. 2010).
There is increasing evidence that a polycentric approach to governance
builds adaptive capacity and creates more robust institutional
arrangements to unexpected disturbances (Anderies et al. 2007, Ostrom
2010). In a polycentric approach, multiple governing bodies at a variety
of scales have jurisdiction over specific issues and geographic regions
(Ostrom et al. 1961). The combination of autonomy and the interaction
with other governing bodies provides opportunities for experimentation
and learning across multiple issues, arenas, and scales. Multiple
independent governance arrangements provide both a diversity of
approaches to a crisis and the redundancy to recover in cases of failure
(Folke et al. 2005). Such flexibility and opportunities for learning
contrast with top-down bureaucratic structures, designed to minimize
change. Building networks of organizations committed to a process of
continual inquiry, informed action, and adaptive learning is a more
flexible and more robust strategy to cope with disasters than the
standard practice of establishing greater control over possible threats
through inward focused administrative structures (Comfort 2005).
However, polycentric systems of governance, while improving the capacity
for experimentation and learning, still require two further shifts from
traditional governance models for effective response to increasingly
complex crises. The first shift requires individual jurisdictions to
take advantage of the findings from across a polycentric system and
allow for adaptive policy making. Decision makers, whether bureaucrats
or businesspeople, politicians or the public, too often retain a
perspective that views experimentation and revision based on new
information as an acknowledgement of error and poor judgment, rather
than as the only means of working through complex, nearly intractable
problems. The second shift requires a diagnostic approach to governance
(Ostrom 2007). Similar to diagnostics in medicine, this approach
systematically looks at a framework comprised of large numbers of
relevant variables that affect patterns of interaction and outcome for a
situation without necessarily analyzing every causal relationship.
Instead, in response to living in an ever changing complex system that
is only incompletely understood, the focus is on ongoing analysis,
experimentation, and adaptation rather than on finding ideal solutions
and one-stop fixes.
In conclusion, we argue that the interaction of strong global drivers,
increased potential for the propagation of disturbances across systems,
and the heightened likelihood of policy responses in one region
affecting other regions can lead to a concatenation of crises.
Scientific capacity for the early detection of dangerous and potentially
propagating crises needs to be advanced, as does understanding and
awareness of feedbacks and interdependencies that can lead to impacts
spreading to other systems. Globally coherent strategies for the
management of large crises, supported by a mind-set that uses crises as
an opportunity for learning, are required.
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Duan Biggs - ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Australia
Reinette (Oonsie) Biggs - Stockholm Resilience Centre, Stockholm University, Sweden
Vasilis Dakos - Department of Aquatic Ecology & Water Quality Management, Wageningen University
Robert J. Scholes - CSIR Natural Resources and the Environment, Pretoria, South Africa
Michael Schoon - School of Human Evolution and Social Change, Arizona State University
"Human development, if not engendered, is endangered."|
UN Human Development Report, 1995
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