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Vulnerability, Risk and Adaptation: A Conceptual Framework


The purpose of this paper is to present a tentative conceptual framework for studies of vulnerability and adaptation to climate variability and change, generally applicable to a wide range of contexts, systems and hazards. Social vulnerability is distinguished from biophysical vulnerability, which is broadly equivalent to the natural hazards concept of risk. The IPCC definition of vulnerability is discussed within this context, which helps us to reconcile apparently contradictory definitions of vulnerability. A concise typology of physically defined hazards is presented; the relationship between the vulnerability and adaptive capacity of a human system depends critically on the nature of the hazard faced. Adaptation by a system may be inhibited by process originating outside the system; it is therefore important to consider “external” obstacles to adaptation, and links across scales, when assessing adaptive capacity.
Vulnerability, risk and adaptation:
A conceptual framework
Nick Brooks
November 2003
Tyndall Centre for Climate Change Research Working Paper 38
Vulnerability, risk and
adaptation: A conceptual
Nick Brooks
Tyndall Centre for Climate Change Research
Centre for Social and Economic Research on the Global Environment (CSERGE)
School of Environmental Sciences
University of East Anglia
Norwich NR4 7TJ
Tyndall Centre Working Paper No. 38
September 2003
The purpose of this paper is to present a tentative conceptual framework for studies of vulnerability and
adaptation to climate variability and change, generally applicable to a wide range of contexts, systems and
hazards. Social vulnerability is distinguished from biophysical vulnerability, which is broadly equivalent
to the natural hazards concept of risk. The IPCC definition of vulnerability is discussed within this
context, which helps us to reconcile apparently contradictory definitions of vulnerability. A concise
typology of physically defined hazards is presented; the relationship between the vulnerability and
adaptive capacity of a human system depends critically on the nature of the hazard faced. Adaptation by a
system may be inhibited by process originating outside the system; it is therefore important to consider
“external” obstacles to adaptation, and links across scales, when assessing adaptive capacity.
1 Introduction
The study of the vulnerability of human and natural systems to climate change and variability, and of their
ability to adapt to changes in climate hazards, is a relatively new field of research that brings together
experts from a wide range of fields, including climate science, development studies, disaster management,
health, social science, policy development and economics, to name but a few areas. Researchers from
these fields bring their own conceptual models to the study of vulnerability and adaptation, models which
often address similar problems and processes using different language. Somehow researchers from all
these different backgrounds must develop a common language so that vulnerability and adaptation
research can move forward in a way that integrates these different traditions in a coherent yet flexible
fashion, allowing researchers to assess vulnerability and the potential for adaptation in a wide variety of
different contexts, and in a manner that is transparent to their colleagues.
The growing body of literature on vulnerability and adaptation contains a sometimes bewildering array of
terms: vulnerability, sensitivity, resilience, adaptation, adaptive capacity, risk, hazard, coping range,
adaptation baseline and so on (IPCC, 2001; Adger et al., 2002; Burton et al., 2002). The relationships
between these terms are often unclear, and the same term may have different meanings when used in
different contexts and by different authors. Researchers from the natural hazards field tend to focus on the
concept of risk, while those from the social sciences and climate change field often prefer to talk in terms
of vulnerability (Downing et al., 2001; Allen, 2003). Social scientists and climate scientists often mean
different things when they use the term “vulnerability”; whereas social scientists tend to view
vulnerability as representing the set of socio-economic factors that determine people’s ability to cope with
stress or change (Allen, 2003), climate scientists often view vulnerability in terms of the likelihood of
occurrence and impacts of weather and climate related events (Nicholls et al., 1999).
The aim of this paper is to present a conceptual framework that may be applied consistently to studies of
vulnerability and adaptation in a wide range of contexts by researchers with different backgrounds,
concerned with the impacts of and responses to climate variability and change within human systems. The
intention is not to redefine terms and introduce an alternative array of equally bewildering terms
(although one new term and qualifying adjectives for existing terms are tentatively suggested). The aim is
rather to explore the concepts of vulnerability, risk and adaptation as they are currently applied, and to
attempt to clarify the relationships between them. Such clarification may be achieved through practices as
simple as the application of an adjective; the confusion arising from different usages of the term
“vulnerability” may be largely overcome by differentiating between “social vulnerability” and
“biophysical vulnerability”, terms that are already commonly used by some members of the research
The paper concentrates on the relationships between biophysical vulnerability, social vulnerability, risk,
adaptive capacity and adaptation. The concept of vulnerability is discussed, and the differences between
biophysical and social vulnerability are summarized. The IPCC definition of vulnerability is examined,
and related to the concepts of social and biophysical vulnerability. Definitions of risk are then examined,
and related to the concepts of vulnerability and hazard. The concept of adaptive capacity is explored at
some length, and emphasis is placed on the hazard-specific nature of adaptive capacity and how this
mediates its relationship with vulnerability. A concise hazard typology is presented, and the implications
of the different timescales associated with different hazards are addressed in terms of the adaptation
process. The concepts of current, future, actual and potential vulnerability are elaborated as a basis for the
quantification of vulnerability and adaptive capacity where this is desirable, for example in integrated
assessment models. Finally the relationship between adaptive capacity and actual adaptation is addressed,
and concerns about the potential misuse of the concept of adaptive capacity are presented. The concept of
adaptation likelihood is tentatively suggested as a means of countering any attempt to use “capacity
building” as a political lever to divert attention away from the large-scale structural factors that often
cause or exacerbate the vulnerability of groups who have no control over such factors.
2 Biophysical versus social vulnerability
Political scientists with a definition are like dogs with a bone: they will continue to gnaw at it while
ignoring more nutritious alternatives (Grant, 2000).
2.1 Biophysical and social vulnerability
There are many different definitions of vulnerability, and it is not the purpose of this paper to review them
all. For a summary of definitions of and approaches to vulnerability the reader is directed to Adger,
(1999). Nonetheless, it is essential to stress that we can only talk meaningfully about the vulnerability of
a specified system to a specified hazard or range of hazards. The term hazard is used throughout this
paper to refer specifically to physical manifestations of climatic variability or change, such as droughts,
floods, storms, episodes of heavy rainfall, long-term changes in the mean values of climatic variables,
potential future shifts in climatic regimes and so on. Climate hazards may be defined in terms of absolute
values or departures from the mean of variables such as rainfall, temperature, wind speed, or water level,
perhaps combined with factors such as speed of onset, duration and spatial extent. Hazards are also
referred to as climate events. Crucially, hazards as described in this paper are purely physically defined. A
disaster as measured in human terms (lives lost, people affected, economic losses) is therefore the
outcome of a hazard, mediated by the properties of the human system that is exposed to and affected by
the hazard. Of the phenomena listed above, floods are particularly problematic, as their magnitude is
mediated by anthropogenic factors such as river engineering and land use. A flood associated with a
heavy rainfall event may be more usefully viewed as a primary impact or outcome of that rainfall event,
just as coastal floods are often the outcome of storm surges. In these cases it is the rainfall event or storm
surge that constitute the principal hazard - whether or not we should include floods in our list of hazards
is debatable. Hazards are discussed in more detail in Sections 3 and 4.
Definitions of vulnerability in the climate change related literature tend to fall into two categories,
viewing vulnerability either (i) in terms of the amount of (potential) damage caused to a system by a
particular climate-related event or hazard (Jones and Boer, 2003), or (ii) as a state that exists within a
system before it encounters a hazard event (Allen, 2003). The former view has arisen from an approach
based on assessments of hazards and their impacts, in which the role of human systems in mediating the
outcomes of hazard events is downplayed or neglected. Climate change impacts studies have typically
examined factors such as increases in the number of people at risk of flooding based on projections of sea
level rise (e.g. Nicholls et al., 1999), and have thus focused on human exposure to hazard rather than on
the ability of people to cope with hazards once they occur. The hazards and impacts approach typically
views the vulnerability of a human system as determined by the nature of the physical hazard(s) to which
it is exposed, the likelihood or frequency of occurrence of the hazard(s), the extent of human exposure to
hazard, and the system’s sensitivity to the impacts of the hazard(s). This view is apparent in the principal
definition of vulnerability in the IPCC Third Assessment Report (TAR) (IPCC, 2001a), discussed in more
detail below. This combined vulnerability, a function of hazard, exposure and sensitivity, may be referred
to as physical or biophysical vulnerability. The term “biophysical” will be used here, as it suggests both a
physical component associated with the nature of the hazard and its first-order physical impacts, and a
biological or social component associated with the properties of the affected system that act to amplify or
reduce the damage resulting from these first-order impacts. Biophysical vulnerability is concerned with
the ultimate impacts of a hazard event, and is often viewed in terms of the amount of damage experienced
by a system as a result of an encounter with a hazard. Jones and Boer (2003) are therefore referring to
biophysical vulnerability when they state that “Vulnerability is measured by indicators such as monetary
cost, human mortality, production costs, [or] ecosystem damage…” These are indicators of outcome
rather than indicators of the state of a system prior to the occurrence of a hazard event.
Conversely, the view of vulnerability as a state (i.e. as a variable describing the internal state of a system)
has arisen from studies of the structural factors that make human societies and communities susceptible to
damage from external hazards (Allen, 2003). In this formulation, vulnerability is something that exists
within systems independently of external hazards. For many human systems, vulnerability viewed as an
inherent property of a system arising from its internal characteristics may be termed “social vulnerability”
(Adger, 1999; Adger and Kelly, 1999). For vulnerability arising purely from the inherent properties of
non-human systems or systems for which the term “social” is not appropriate the term “inherent
vulnerability” might be used. Social vulnerability is determined by factors such as poverty and inequality,
marginalisation, food entitlements, access to insurance, and housing quality (Blaikie et al., 1994; Adger
and Kelly, 1999; Cross, 2001). It is social vulnerability that has been the primary focus of field research
and vulnerability mapping projects, which are generally concerned with identifying the most vulnerable
members of society, and examining variations in vulnerability between or within geographical units that
may experience similar hazards (Downing and Patwardhan, 2003). In this formulation, it is the interaction
of hazard with social vulnerability that produces an outcome, generally measured in terms of physical or
economic damage or human mortality and morbidity (Brooks and Adger, 2003). Hence social
vulnerability may be viewed as one of the determinants of biophysical vulnerability.
The nature of social vulnerability will depend on the nature of the hazard to which the human system in
question is exposed: although social vulnerability is not a function of hazard severity or probability of
occurence, certain properties of a system will make it more vulnerable to certain types of hazard than to
others. For example, quality of housing will be an important determinant of a community’s (social)
vulnerability to a flood or windstorm, but is less likely to influence its vulnerability to drought. So,
although social vulnerability is not a function of hazard, it is, to a certain extent at least, hazard specific –
we must still ask the question “vulnerability of who or what to what?” Nonetheless, certain factors such as
poverty, inequality, health, access to resources and social status are likely to determine the vulnerability
of communities and individuals to a range of different hazards (including non-climate hazards). We may
view such factors as “generic” determinants of social vulnerability, and others such as the situation of
dwellings in relation to river flood plains or low-lying coastal areas as determinants that are “specific” to
particular hazards, in this example, flooding and storm surges.
In summary, biophysical vulnerability is a function of the frequency and severity (or probability of
occurrence) of a given type of hazard, while social or inherent vulnerability is not. A hazard may cause no
damage if it occurs in an unpopulated area or in a region where human systems are well adapted to cope
with it. Where biophysical vulnerability is viewed in terms of outcome (damage resulting from the
interaction of hazard and social vulnerability), a system that sustained no net damage from a hazard might
be interpreted post hoc as being “invulnerable” to that hazard.
In this paper the term “social vulnerability” is used in a broad sense to describe all the factors that
determine the outcome of a hazard event of a given nature and severity. Social vulnerability encompasses
all those properties of a system independent of the hazard(s) to which it is exposed, that mediate the
outcome of a hazard event. This may include environmental variables and measures of exposure. For
example the vulnerability of a country to a given hazard occurring over its national territory will be a
function of the percentage of the population living in the area affected by the hazard, but also of the extent
to which individuals and sub-national scale systems within this area are exposed to its first-order impacts.
Exposure and the state of the environment within a system will be socially determined to a large extent.
Exposure will depend on where populations choose to (or are forced to) live, and how they construct their
settlements, communities and livelihoods. Environmental variables will vary in response to human
activity, as populations exploit resources and manage the environment for their benefit in the short or long
term. Social vulnerability as described here therefore encompasses elements of the physical environment
as they relate to human systems, including factors such as topography and river engineering schemes
(which mediate the outcome of flood events), and groundwater reserves (which may mediate the outcome
of a meteorological drought by enabling people to compensate for lack of rain through irrigation).
2.2 IPCC definitions of vulnerability
The IPCC Third Assessment Report (TAR) describes vulnerability as
“The degree to which a system is susceptible to, or unable to cope with, adverse effects of
climate change, including climate variability and extremes. Vulnerability is a function of the
character, magnitude, and rate of climate variation to which a system is exposed, its
sensitivity, and its adaptive capacity.” (IPCC, 2001, p. 995) (IPCC Def. 1)
Exposure is defined in the same report as “The nature and degree to which a system is exposed to
significant climatic variations.” Sensitivity is “the degree to which a system is affected, either adversely
or beneficially, by climate-related stimuli. The effect may be direct (e.g., a change in crop yield in
response to a change in the mean, range or variability of temperature) or indirect (e.g., damages caused by
an increase in the frequency of coastal flooding due to sea level rise).” Adaptive capacity is “The ability
of a system to adjust to climate change (including climate variability and extremes) to moderate potential
damages, to take advantage of opportunities, or to cope with the consequences.”
The above definition may be compared with that given in Chapter 18 of the TAR, cited from Smit et al.
(1999), in which vulnerability is described as the “degree to which a system is susceptible to injury,
damage, or harm (one part - the problematic or detrimental part - of sensitivity)” (IPCC Def. 2).
Sensitivity is in turn described as the “Degree to which a system is affected by or responsive to climate
stimuli” (IPCC, 2001, p. 894).
The two IPCC definitions above are very different, and are not consistent. IPCC Def. 1 views the
vulnerability of a system as a function of its sensitivity, while Definition 2 views vulnerability as a subset
of sensitivity. Vulnerability in IPCC Def. 2 is therefore a subset of one of the determinants of
vulnerability as defined in IPCC Def. 1, making the two definitions contradictory, provided they are
assumed to be describing the same type of vulnerability.
This contradiction further illustrates the principal disagreement over the definition of vulnerability within
the climate change research community, namely whether vulnerability is determined purely by the
internal characteristics of a system, or whether it also depends on the likelihood that a system will
encounter a particular hazard. In other words, whether we use the term “vulnerability” to mean
biophysical or social vulnerability. IPCC Def. 1 clearly refers to biophysical vulnerability, with
“sensitivity” (or at least “the detrimental part of sensitivity”) in IPCC Def. 1 playing an equivalent role to
social vulnerability where human systems are concerned, while IPCC Def. 2 refers only to social or
inherent vulnerability. If we view Def. 1 as a definition of biophysical vulnerability and Def. 2 as a
definition of social vulnerability, the conflict is resolved. It would therefore be prudent for researchers in
future to avoid using the word “vulnerability” without any further clarification, and to specify to which
type of vulnerability they are referring. Such a recommendation does not require terms to be redefined,
and has few or no implications for the way in which analyses of either type of vulnerability are carried
out, but will prevent much of the confusion that has characterized the vulnerability debate to date.
3 Vulnerability and risk
Biophysical vulnerability, as implicitly described in IPCC Def. 1, has much in common with the concept
of risk as elaborated in the natural hazards literature. A number of definitions of risk from a variety of
different sources is presented in Table 1, along with associated definitions of hazard where these are also
given in the source material.
The definitions in Table 1 are probabilistic in nature, relating either to (i) the probability of occurrence of
a hazard that acts to trigger a disaster or series of events with an undesirable outcome, or (ii) the
probability of a disaster or outcome, combining the probability of the hazard event with a consideration of
the likely consequences of the hazard. The various definitions generally present hazard in terms
compatible with the view of hazard elaborated earlier in this paper, although in certain definitions there is
some ambiguity as to whether hazard represents a trigger event or the outcome of such an event. Jones
and Boer (2003) define hazard explicitly in physical terms. Stenchion (1997) and UNDHA (1992)
implicitly define hazard in a similar manner, as an event that might precipitate a disaster but which does
not itself constitute a disaster. Where vulnerability is included in the definition of risk, it is viewed as
distinct from hazard: it is therefore social vulnerability that is being referred to. Risk defined as a function
of hazard and social vulnerability is compatible with risk defined as probability x consequence, and also
with risk defined in terms of outcome. The probability of an outcome will depend on the probability of
occurrence of a hazard and on the social vulnerability of the exposed system, which will determine the
consequence of the hazard.
The ambiguity as to whether it is the probability of occurrence of a hazard, or the probability of a
particular outcome that is being referred to is addressed by Sarewitz et al. (2003). They define event risk
as the “risk of occurrence of any particular hazard or extreme event” and outcome risk as “the risk of a
particular outcome”. They state that outcome risk “integrates both the characteristics of a system and the
chance of the occurrence of an event that jointly results in losses.” Sarewitz et al. (2003) are referring to
social or inherent vulnerability when they “use the word ‘vulnerability’ to describe inherent
characteristics of a system that create the potential for harm but are independent of the probabilistic risk
of occurrence (“event risk”) of any particular hazard or extreme event.”
Outcome risk may therefore be viewed as a function of event risk and inherent or social vulnerability, a
formulation broadly consistent with the definitions of risk in Table 1, as long as we acknowledge the
ambiguities in the definitions of hazard. This definition of outcome risk is also broadly equivalent to the
definition of biophysical vulnerability presented in Section 2.1. Event risk as described by Sarewitz et al.
(2003) is associated with hazard as defined in physical terms, a view consistent with the concept of hazard
as outlined in Section 2.1 and by Jones and Boer (2003).
Author(s) Risk definition
Smith, 1996 (p5) Probability x loss (probability of a specific hazard occurrence)
Hazard = potential threat
IPCC, 2001 (p21) Function of probability and magnitude of different impacts
Morgan and Henrion, 1990
(p1)/Random House, 1966
“Risk involves an ‘exposure to a chance injury or loss’”
Adams, 1995 (p8) “a compound measure combining the probability and magnitude of
an adverse affect”
Jones and Boer, 2003; (also
Helm, 1996)
Probability x consequence
Hazard: an event with the potential to cause harm, e.g. tropical
cyclones, droughts, floods, or conditions leading to an outbreak of
disease-causing organisms.
Downing et al., 2001 Expected losses (of lives, persons injured, property damaged, and
economic activity disrupted) due to a particular hazard for a given
area and reference period
Hazard: a threatening event, or the probability of occurrence of a
potentially damaging phenomenon within a given time period and
Downing et al., 2001 Probability of hazard occurrence
Hazard = potential threat to humans and their welfare
Crichton, 1999 “Risk” is the probability of a loss, and depends on three elements,
hazard, vulnerability and exposure.”
Stenchion, 1997 “Risk might be defined simply as the probability of occurrence of
an undesired event [but might] be better described as the probability
of a hazard contributing to a potential disaster…importantly, it
involves consideration of vulnerability to the hazard.”
UNDHA, 1992 “Expected losses (of lives, persons injured, property damaged, and
economic activity disrupted) due to a particular hazard for a given
area and reference period. Based on mathematical calculations, risk
is the product of hazard and vulnerability.”
Table 1: Definitions of risk and hazard. The definitions of Chrichton (1999), Stenchion (1997) and
UNDHA (1992) are taken from a similar table in Kelman (2003).
The principal difference between the natural hazards risk-based approach and the IPCC biophysical
vulnerability approach is that risk is generally described in terms of probability, whereas the IPCC and the
climate change community in general tend to describe (biophysical) vulnerability simply as a function of
certain variables. Nonetheless, the determinants of both biophysical vulnerability and risk are essentially
the same - hazard and social vulnerability.
The natural hazards community, which emphasizes risk, and the climate change community, which
emphasizes vulnerability, are essentially examining the same processes. However, this has not always
been immediately apparent, due to differences in terminology. Both are ultimately interested in the
physical hazards that threaten human systems, and in the outcomes of such hazards as mediated by the
properties of those systems, described variously in terms of vulnerability, sensitivity, resilience, coping
ability and so on. The separation of vulnerability into social and biophysical vulnerability enables us to
appreciate the compatibility of the risk-based and vulnerability-based approaches. The concept of
biophysical vulnerability addresses the same issues as the concept of risk or, adopting the more precise
terminology of Sarewitz et al. (2003), outcome risk. Both [outcome] risk and biophysical vulnerability are
functions of hazard and social vulnerability, and we may view social vulnerability as equivalent to
sensitivity when we are concerned with human systems. The essential equivalence of [outcome] risk and
biophysical vulnerability as described above is further illustrated by a report from the International
Strategy for Disaster Reduction which separates “risk factors” into two components: “hazard (determines
geographical location, intensity and probability)” and “vulnerability/capacities (determines
susceptibilities and capacities)” (United Nations, 2002, p.66).
The integration of the risk-based and vulnerability-based approaches is desirable if we are to address the
numerous threats that human systems will face in the future as a result of climate variability and change,
and also from non-climate hazards. As stated by Kasperson et al. (2001), “What is essential is to assess
vulnerability as an integral part of the causal chain of risk and to appreciate that altering vulnerability is
one effective risk-management strategy.”
Placing social or inherent vulnerability within the context of risk, and viewing biophysical vulnerability
and risk as broadly equivalent, should go some way towards reducing the confusion associated with
definitions of vulnerability and facilitating better communication between researchers with different
backgrounds, therefore improving the prospects of managing the threats posed by climate variability and
change. Indeed, we could institute a new convention regarding terminology, in which we speak of risk
instead of biophysical vulnerability, and use the word “vulnerability” only to refer to social vulnerability.
However, Grant (2000) follows his statement about political scientists with the following sound advice:
“Let us not let terminology stand in the way of our exploration of process.” We should not distract
ourselves from the very real need to manage risk and reduce vulnerability with arguments over which
formulation of vulnerability is “best”. Indeed, it is hoped that the above discussion has demonstrated that
we need only be more careful and concise with our existing definitions, rather than redefine terms such as
vulnerability and risk. While it is recognised that different contexts require different approaches, it is
essential that researchers working in the same field use a common language.
4 Adaptive capacity, adaptation and vulnerability
The above discussion has gone some way towards developing a conceptual framework of vulnerability
and risk, based on the distinction between social and biophysical vulnerability, and on the equivalence of
biophysical vulnerability and risk. This distinction helps us to make sense of the apparently contradictory
definitions in the IPCC TAR (IPCC, 2001), by associating hazard with climate variation, sensitivity with
social vulnerability, and vulnerability as defined in IPCC Def. 1 with biophysical vulnerability or risk.
However, we have not yet addressed the issue of adaptive capacity, and its relationship to social and
biophysical vulnerability.
Many definitions of adaptive capacity exist (e.g. IPCC, 2001; Burton et al., 2002; Adger et al., 2003);
broadly speaking it may be described as the ability or capacity of a system to modify or change its
characteristics or behaviour so as to cope better with existing or anticipated external stresses. We may
view reductions in social vulnerability as arising from the realization of adaptive capacity as adaptation.
The term adaptation is used here to mean adjustments in a system’s behaviour and characteristics that
enhance its ability to cope with external stresses. Given constant levels of hazard over time, adaptation
will allow a system to reduce the risk associated with these hazards by reducing its social vulnerability.
Faced with increased hazard, a system may maintain current levels of risk through such adaptation;
reductions in risk in the face of increased hazard will require a greater adaptation effort. If hazards
increase dramatically in frequency or severity, a human system may face greater risk despite reduction in
social vulnerability achieved through the implementation of adaptation strategies.
The direct effect of adaptation is therefore to reduce social vulnerability. Whether or not this translates
into a reduction in biophysical vulnerability or risk will depend on the evolution of hazard. In the case of
anthropogenic greenhouse warming and any associated changes in climate, the only certain way of
reducing risk is therefore via a combination of adaptation and mitigation strategies, the purpose of the
latter being to reduce hazards. In the following discussion on adaptive capacity and adaptation, the term
vulnerability will therefore be used to refer to social vulnerability, unless otherwise stated. Where the text
refers to reductions in vulnerability as a result of adaptation, this should be interpreted as social
vulnerability, and by extension to biophysical vulnerability only under conditions of constant hazard.
4.1 Vulnerability and adaptation as hazard-specific
In IPCC Def. 1, biophysical vulnerability is a function of adaptive capacity, which is viewed as distinct
from sensitivity, which we may view in turn as being broadly equivalent to social vulnerability. Given the
broad equivalence of biophysical vulnerability and risk (Section 3), IPCC Def. 1 suggests that if a system
has a high capacity to adapt, it is less “at risk”. However, this definition fails to place risk, vulnerability
(both biophysical and social) and adaptive capacity in a hazard-specific context.
It makes little sense to talk about a system’s vulnerability and adaptive capacity without specifying the
hazard to which it is vulnerable and to which it must adapt. Once we accept that risk, vulnerability and
adaptive capacity are hazard-specific, we must then recognise that there are many different kinds of
climate hazard, operating over a variety of different timescales and requiring a variety of adaptation
responses. A system may have the capacity to adapt to certain types of hazard, but not to others.
Three broad categories of hazard may be identified:
Category 1:
Discrete recurrent hazards, as in the case of transient phenomena such as storms, droughts
and extreme rainfall events.
Category 2: Continuous hazards, for example increases in mean temperatures or decreases in mean
rainfall occurring over many years or decades (such as anthropogenic greenhouse
warming or desiccation such as that experienced in the Sahel over the final decades of the
20th century (Hulme, 1996; Adger and Brooks, 2003).
Category 3:
Discrete singular hazards, for example shifts in climatic regimes associated with changes
in ocean circulation; the palaeoclimatic record provides many examples of abrupt climate
change events associated with the onset of new climatic conditions that prevailed for
centuries or millennia (Roberts, 1998; Cullen et al., 2000; Adger and Brooks, 2003).
Adaptation does not occur instantaneously; a system requires time to realise its adaptive capacity as
adaptation. Adaptive capacity represents potential rather than actual adaptation. A high level of adaptive
capacity therefore only reduces a system’s vulnerability to hazards occurring in the future (allowing the
system time to adapt in an anticipatory manner) or to hazards that involve slow change over relatively
long periods, to which the system can adapt reactively. In other words, adaptive capacity is a determinant
of vulnerability to Category 2 hazards and also of the future vulnerability to anticipated Category 1 and 3
hazards. The damage to a system resulting from a discrete hazard event such as a storm or flood occurring
tomorrow would not be a function of the system’s ability to pursue future adaptation strategies – it is
existing adaptations resulting from the past realization of adaptive capacity that determine current levels
of vulnerability. The likelihood of a system adapting responsively to (as opposed to coping with) a sudden
short-lived event such as a hurricane is negligible.
However, a system’s vulnerability to more gradual, longer-term change will be a function of it’s ability to
adapt incrementally and responsively, and its vulnerability to discrete hazards occurring in the future will
be a function of its ability to anticipate and pre-empt those hazards via appropriate planned adaptation
strategies. The rate at which risk (or biophysical vulnerability) associated with a particular type of hazard
is reduced (or increased) will depend on the timescales associated with the implementation of adaptation
measures (i.e. the realisation of adaptive capacity as adaptation) and also on the timescales associated
with the evolution or occurrence of the hazard in question (in the case of global-scale anthropogenic
climate change the latter will be influenced by global development pathways and the extent to which
mitigation is pursued). In other words, we must ask ourselves whether a system is likely to implement the
necessary adaptation measures in the time available to it in order to reduce risk to a subjectively defined
acceptable level.
For example, global mean sea level is expected to rise by a maximum of around 45 cm by 2050 (Sear et
al., 2001). While many countries are currently vulnerable to a 45 cm sea level rise (assuming no further
adaptation were to occur over the next half-century), for this particular threat we are concerned with
future vulnerability, perhaps assessed in terms of the ability to cope with a given annual or decadal rise in
sea level up until the middle of the twenty first century. The risk posed to a country or coastal zone by sea
level rise will depend on the rate at which it occurs, the system or region’s existing vulnerability, and the
rate at which the system can adapt (c.f. IPCC Def. 1). Existing (social) vulnerability is important as it
constitutes the “baseline” from which any reduction of vulnerability to “acceptable” levels via adaptation
must take place. Risk assessments for sea level rise typically examine the risk associated with a given
increase in sea level assuming current levels of social vulnerability, perhaps modulated by changes in
population density (Nicholls et al., 1999; Parry et al., 2001). A comprehensive assessment of risk would
examine the likelihood of a specific rate of sea level rise over a given period (hazard), and the potential or
likely evolution of a system’s vulnerability to that rise based on current vulnerability and the potential or
likely amount of adaptation over that period.
4.2 Adaptive capacity and current and future vulnerability
Another way of addressing the important issue of timescale is to distinguish between current and future
vulnerability. Current vulnerability, determined by past adaptation and the current availability of coping
options, provides a baseline from which a system’s future vulnerability will evolve. This evolution will be
mediated by the system’s adaptive capacity and the extent to which this capacity is realised as adaptation.
At any given time, we may view a system as exhibiting a certain degree of vulnerability to a specified
hazard, and as having a certain ability or potential to adapt so as to reduce its vulnerability to that hazard
within any given time frame, constrained or modulated by a range of external factors.
If the hazard in question is a particular type of discrete, transient, extreme climatic event, we may speak
in terms of the system’s current vulnerability, a “snapshot” which determines the extent to which it would
be damaged if the event in question occurred immediately. We may also speak of the system’s potential
vulnerability, or the vulnerability it would have at a specified point in the future to a specific hazard as a
result of realizing all its current adaptive capacity through anticipatory adaptation. If we define adaptive
capacity, α, as the potential adaptation per unit time based on existing conditions, and adaptation as
representing a reduction in vulnerability, then potential vulnerability at time t, assessed at time t=0, may
be represented by the following expression:
t = V0 - α0t ………Equation 1
where V0 is current vulnerability (at t=0) and α0 represents current adaptive capacity.
If we assume that adaptation is a function of adaptive capacity only, in other words that all a system’s
adaptive capacity is realised as adaptation, we may represent the actual vulnerability of a system at time t
Vt = V0 - ∫αdt ……….Equation 2
where α represents dynamic adaptive capacity, acknowledging the fact that adaptive capacity will
fluctuate over time as the environmental, political, social and economic factors that determine adaptive
capacity change. Adaptive capacity may also be reduced by the impacts of the very hazards that a system
must adapt to.
The above mathematical formulations allow vulnerability and adaptation studies to be put on a more
quantitative footing where this is deemed to be desirable, for example in terms of integrated assessments
involving modelling components, or where quantification is useful in order to assess the success or failure
of adaptation strategies. Differences in social vulnerability resulting from different development pathways
might be assessed by running models with a suite of different socio-economic scenarios under conditions
of constant hazard. Outcomes measured in terms of mortality and morbidity or economic damage could
then be used to assess the impacts of different modes of development on social vulnerability (assuming
each socio-economic scenario is associated with the same hazard(s)). Of course vulnerability is also
influenced by hazard events through a variety of feedback processes such as the destruction of resources
and the exacerbation of poverty and inequality by climate-related disasters. Such processes should be
accounted for in modelling studies if they are to be of any value.
5 Systems, scales and the constituents of adaptive capacity
The above discussion focuses on the relationship between adaptive capacity and vulnerability, viewing
the former in the broadest possible terms. However, if we wish to assess existing adaptive capacity, we
must understand how it is constituted, and how it is translated into adaptation. In other words, we must
understand the adaptation process. This process will depend on the nature of the systems that are
adapting; for example, the processes via which a household or local community adapts to changes in
climatic conditions will be very different from those via which a nation state adapts. In the former case,
adaptation will be determined by factors such as health and education, access to information, financial
and natural resources, the existence of social networks, and the presence or absence of conflict. In the
latter case, adaptation will depend on relationships between the government, the private sector and civil
society, the regulatory environment and the effectiveness of state institutions, national wealth, economic
autonomy and so on.
The factors that determine whether or not adaptation occurs will operate at a variety of scales, and will
depend on how the “system” being assessed is defined. Different systems are characterized by different
scales (for example spatial scales or scales representing interactions between individuals, groups or
institutions), and different systems will interact with one other; the processes operating within one system
may directly or indirectly affect another system. Examples of such cross-scale linkages include links
between the local and national scale; market intervention at the national or international level may affect
the price of a commodity produced by a household or community, with dramatic consequences for the
latter’s economic status and resulting ability to invest in household or community level adaptation to a
hazard such as drought.
We therefore cannot view systems as closed, nor can we assess a system’s ability to adapt without
considering the role of obstacles to adaptation that might be determined by processes operating outside of
the system in question. Indeed, we might even divide the factors that determine whether or not adaptation
occurs, and to what extent, into “endogenous” and “exogenous” factors. In practice this may represent an
unnecessary complication, given the complex interactions between systems and across scales. However, it
is a useful conceptual division, as it reminds us that in order to facilitate adaptation, we must address not
only those processes operating at the sub-system scale, but also the wider social, economic, political and
environmental contexts within which the system of interest is embedded. There is currently a tendency for
vulnerability and poverty to be addressed solely in terms of “endogenous” factors - the characteristics and
behaviour of vulnerable and poor populations - with little regard to the wider economic and geopolitical
context that often causes or exacerbates poverty and vulnerability (O’Brien and Leichenko, 2000; Pelling
and Uitto, 2001; Singh, 2002). This approach, evident in the current vogue for “capacity building”, may
be interpreted as being to a large extent a result of the desire of researchers and policy makers to avoid
challenging the powerful political and economic vested interests that determine the nature of the
adaptation context, and of the view that it is either undesirable or impossible to question the fundamental
geopolitical and economic contexts within which adaptation must be carried out. There is a danger that
the concepts of adaptive capacity and capacity building will be employed in the same manner as the
concept of social capital has arguably been employed by bodies such as the World Bank, as a justification
for inaction regarding the large-scale structural causes of poverty, inequality and vulnerability (“macro-
relations of power” – Fine, 1999) by emphasizing micro-scale processes as the key to sustainable
development. This is not to say that micro-scale processes are not important, simply that they are not
necessarily sufficient for successful adaptation to occur. For example, migration from rural areas to
vulnerable coastal towns will not be reversed by investment in export agriculture at a sub-national scale if
the resulting produce is worthless because of trade barriers, EU and US agricultural subsidies, and global
price-fixing monopolies. International financial institutions might influence a country’s adaptive capacity
by persuading that country to alter its institutional and economic infrastructure, and divest itself of certain
assets or resources (such as food reserves). Those same institutions might then influence the extent to
which the country in question is able to realize its existing adaptive capacity by influencing national
economic policy in order to achieve outcomes acceptable within the context of the dominant economic
ideology. Other supra-national bodies, international agreements and inter-state conflicts may also
influence the likelihood of adaptation by determining the country’s access to global markets and
Furthermore, theories of adaptive capacity must not fall into the same trap of certain theories of social
capital, and “neglect power and conflict” (Fine, 1999) within human systems and societies. At the system-
scale, whether or not adaptive capacity is realised is sometimes viewed as dependent on “political will”, a
problematic term that tends to view the complex institutions and processes of governance and state-
society interaction as an impenetrable “black box” rather than attempt to explain action or inaction by a
society (O’Riordan et al., 1998; Adger et al., 2002). The factors that determine a society’s “political will”
should themselves be subject to investigation if we are to understand the adaptation process.
In summary, the extent to which adaptation occurs will be decided by processes operating at a range of
scales, and some of these will be different from the scale at which the system of interest is defined. The
view of adaptive capacity as something “inherent” in a system is likely to lead to an emphasis on
processes operating at the system and sub-system scale, and to a neglect of larger-scale processes, an
outcome that will be convenient for certain ideologically-based groups and institutions. The issue of scale
leads us to think more carefully about our definition of adaptive capacity: will a system with high
adaptive capacity automatically adapt? In other words, is adaptive capacity “self-realising”? For this to be
the case, the definition of adaptive capacity must encompass all the processes that determine whether or
not adaptation takes place, and to what extent, including those associated with different scales and
systems, representing the environmental, economic and geopolitical context in which the system of
interest is embedded. Perhaps a more appropriate term would be adaptation likelihood. While use of the
term “adaptive capacity” often leads to debate as to where “inherent” capacity ends and external obstacles
to adaptation begin, the term “adaptation likelihood” more naturally encompasses determinants at
different scales.
However, there is resistance to the introduction of new terms into what is already a terminology-heavy
field. It is left to the reader to decide whether they will continue to use the term “adaptive capacity”, or
adopt the term “adaptation likelihood” in future analysis and discussion. If the former approach is
adopted, the importance of definition is once again emphasized. Just as communications should state
whether the subject of discussion is biophysical vulnerability (risk) or social vulnerability, so they should
also specify whether the term adaptive capacity is used to mean inherent capacity determined at and
below the system scale, or all the factors that influence the adaptation process, including external
obstacles that may frustrate the adaptation process even if those undertaking it have both the willingness
to adapt and access to the necessary resources.
The above considerations of systems and scales have important implications for the quantification and
modelling of adaptive capacity. Equations 1 and 2 above are based on a definition of adaptive capacity
including determinants at different scales (adaptation likelihood); Vt diverges from Vp
t only as a result of
changes in α occurring in response to changes in environmental, political, social and economic
conditions. If these conditions remained constant Vp
t and Vt would be equivalent. This would not be the
case if α represented determinants at and below the system scale only; even if prevailing environmental,
political and socio-economic conditions remained constant, Vp
t would deviate from Vt by an amount
determined by the extent to which the realisation of adaptive capacity was impeded by external factors,
and Equation 2 would require an additional term to represent this effect.
6 Conclusions
This paper has developed a conceptual framework of risk, vulnerability and adaptive capacity that
synthesises a variety of approaches. By distinguishing between social and biophysical vulnerability we
can resolve the apparent conflict between different formulations of vulnerability in the climate change
literature. By acknowledging the broad equivalence between biophysical vulnerability and the natural
hazards concept of risk, we can place the study of social vulnerability within a risk management
framework. Within this framework, the risk posed to a human system by a particular type of hazard will
be a function of the severity and probability of occurrence of the hazard and the way in which its
consequences are likely to be mediated by the social vulnerability of the human system in question. Risk
may be quantified in terms of outcome, for example in terms human mortality and morbidity and/or
economic losses. This may be post hoc for a particular event or set of events, or in terms of likely or
anticipated outcome. Alternatively, risk may be assessed probabilistically as the likelihood of a particular
outcome. Social vulnerability, on the other hand, is more likely to be measured in terms of predictive
variables representing factors such as economic well being, health and education status, preparedness and
coping ability with respect to particular hazards and so on.
The adaptive capacity of a human system represents the potential of the system to reduce its social
vulnerability and thus to minimise the risk associated with a given hazard. While many factors will
determine a system’s capacity to adapt to a variety of existing or anticipated hazards, other aspects of
adaptive capacity will be hazard-specific. The nature of the hazards faced by a human system, and the
timescales associated with them, will determine the nature of its adaptive capacity and of appropriate
adaptation strategies.
Future studies of vulnerability, adaptive capacity and adaptation will be of greater utility to the wider
research community if those undertaking them ask themselves the following questions at the outset:
1. Are we principally concerned with biophysical or social vulnerability?
2. What the principal hazards with which we are concerned and how do they affect the adaptation
process and the relationship between vulnerability and adaptive capacity?
3. Are we defining adaptive capacity at the system and sub-system level only, or does our definition
include the “exogenous” factors that facilitate or inhibit the realisation of sub-system capacity?
These simple steps should go some way towards ensuring greater synergy between actual vulnerability
assessments and more theoretical work, and enhancing communication between researchers from
different backgrounds.
Adams, J. (1995) Risk, University College London Press, London, pp 228.
Adger, W. N., Khan, S. R. and Brooks, N. (2003) Measuring and enhancing adaptive capacity,
Adaptation Policy Framework: A Guide for Policies to Facilitate Adaptation to Climate
Change, UNDP, in review, see
Adger, W. N. and Brooks, N. (2003) Does environmental change cause vulnerability to natural disasters?
In Pelling (ed.), Natural Disasters and Development in a Globalising World, 19-42.
Adger, W. N., Huq, S., Brown, K., Conway, D. and Hulme, M. (2003) Adaptation to climate change in
the developing world, Progress in Development Studies, in press.
Adger, W. N., Huq, S., brown, K., Conway, D. and Hulme, M. (2002) Adaptation to climate change:
Setting the Agenda for Development Policy and Research, Tyndall Centre for Climate Change
Research Working Paper 16.
Adger, W. N. (1999) Social Vulnerability to Climate Change and Extremes in Coastal Vietnam, World
Development, 27 (2), 249-269.
Adger, W. N. and Kelly, P. M. (1999) Social vulnerability to climate change and the architecture of
entitlements, Mitigation and Adaptation Strategies for Global Change, 4, 253-266.
Allen, K. (2003) Vulnerability reduction and the community-based approach, in Pelling (ed.), Natural
Disasters and Development in a Globalising World, 170-184.
Blaikie, P., Cannon, T., Davis, I., Wisner, B. (1994) At Risk: Natural Hazards, People’s Vulnerability,
and Disasters. Routledge, London, 333–352.
Brooks, N. and Adger, W. N. (2003) Country level risk measures of climate-related natural disasters
and implications for adaptation to climate change, Tyndall Centre Working Paper 26:
Burton, I., Huq, S., Lim, B., Pilifosova, O. and Schipper, E. L. (2002) From impacts assessment to
adaptation priorities: the shaping of adaptation policies, Climate Policy, 2, 145-159.
Burton, I., Kates, R. W. and White, G. F. (1993) The Environment as Hazard, New York, The
Guildford Press.
Cash, D. W. and Moser, S. C. (2000) Linking global and local scales: designing dynamic assessment and
management processes, Global Environmental Change, 10(2), 109-120.
Clark, W. C., Jäger, J., Corell, R., Kasperson, R., McCarthy, J. J., Cash, D., Cohen, S. J., Desanker, P.,
Dickson, N. M. Epstein, P., Guston, D. H., Hall, J. M., Jaeger, C., Janetos, A., Leary, N., Levy,
M.A., Luers, A., MacCracken, M., Melillo, J., Moss, R., Nigg, J. M., Parry, M. L., Parson, E. A.,
Ribot, J. C., Schellnhuber, H-J., Seielstad, G. A., Shea, E., Vogel, C., Wilbanks, T. J. (2000)
Assessing Vulnerability to Global Environmental Risks, Belfer Center for Science &
International Affairs.
Crichton, D. (1999) The risk triangle, in Ingleton, J. (ed.), Natural Disaster Management, Tudor Rose,
London, pp 102-103.
Cross, J. A. (2001) Megacities and small towns: different perspectives on hazard Vulnerability,
Environmental Hazards, 3, 63–80.
Cullen, H. M., deMenocal, P. B., Hemming, S., Hemming, G., Brown, F. H., Guilderson, T. and Sirocko,
F. (2000) ‘Climate change and the collapse of the Akkadian empire: Evidence from the deep-sea’,
Geology, 28 (4), 379-382.
Downing, T. E. and Patwardhan, A. (2003) Vulnerability assessment for climate adaptation, Adaptation
Policy Framework: A Guide for Policies to Facilitate Adaptation to Climate Change, UNDP,
in review, see
Downing, TE, Butterfield, R, Cohen, S, Huq, S, Moss, R, Rahman, A, Sokona, Y and Stephen, L (2001)
Vulnerability Indices: Climate Change Impacts and Adaptation, UNEP Policy Series, UNEP,
Fine, B. (1999) The developmental state is dead – long live social capital? Development and Change,
30, 1-19.
Frich, P., Alexander, L. V., Della-Marta, P., Gleason, B., Haylock, M., Klein Tank, A. M. G. and
Peterson, T. (2002) Observed coherent changes in climatic extremes during the second half of the
twentieth century, Climate Research, 19, 193-212.
Grant, W. (2000) Globalisation, big business and the Blair government, Centre for the Study of
Regionalization and Globalisation Working Paper No. 58/00, University of Warwick, UK.
Helm, P. (1996) Integrated risk management for natural and technological disasters, Tephra, 15 (1), 4-13.
Hulme, M. (1996) ‘Recent climatic change in the world's drylands’, Geophysical
Research Letters, 23, 61-64.
IPCC (2001) Climate change 2001: Impacts, Adaptation and Vulnerability, Summary for
Policymakers, WMO.
Jones, R. and Boer, R. (2003) Assessing current climate risks Adaptation Policy Framework: A Guide
for Policies to Facilitate Adaptation to Climate Change, UNDP, in review, see
Jones, R. and Mearns, L. (2003) Assessing future climate risks, Adaptation Policy Framework: A
Guide for Policies to Facilitate Adaptation to Climate Change, UNDP, in review, see
Kasperson, R. E., Kasperson, J. X. and Dow, K. (2001) Vulnerability, equity, and global environmental
change, in Kasperson, J. X. and Kasperson, R. E. (eds.), Global Environmental Risk, United
Nations University Press and Earthscan, 247-272.
Kelman, I. (2003) Defining risk, Flood Risk Net Newsletter, Issue 2, Winter 2003.
Morgan, M. G. and Henrion, M. (1990) Uncertainty: A Guide to Dealing with Uncertainty in
Quantitative Risk and Policy Analysis, Cambridge University Press, pp 332.
Nicholls, R. J., Hoozemans, F. M. J. and Marchand, M. (1999) Increasing flood risk and wetland losses
due to global sea-level rise: regional and global analyses, Global Environmental Change, 9,
O’Brien, K. L. and Leichenko, R. M. (2000) Double exposure: assessing the impacts of climate change
within the context of economic globalization, Global Environmental Change, 10, 221-232.
O'Riordan, T., Cooper, C. L., Jordan, A., Rayner, S., Richards, K. R., Runci, P. and Yoffe, S. (1998)
Institutional frameworks for political action. In Rayner, S. and Malone, E. (eds.) Human Choice
and Climate Change: Volume 1 The Societal Framework. Battelle Press: Washington DC pp.
Parry, M., Arnell, N., and McMichael, T. (2001) Millions at risk: defining critical climate change threats
and targets, Global Environmental Change, 11 (3), 181-183.
Pelling, M. and Uitto, J. I. (2001) Small island developing states: natural disaster vulnerability and global
change, Environmental Hazards, 3, 49–62.
Random House (1966) The Random House Dictionary of the English Language, Stein, J. (ed.),
Random House, New York.
Roberts, N. (1998) The Holocene: An Environmental History, Oxford, Blackwell
Sarewitz, D., Pielke, R. and Keykhah, M. (2003) Vulnerability and risk: some thoughts from a political
and policy perspective, submitted to Risk Analysis.
Sear, C., Hulme, M., Adger, N. and Brown, K. (2001) The Impacts of Global Climate Change on the
UK Overseas Territories: Issues and Recommendations - A Summary Report, Natural
Resources Institute and Tyndall Centre for Climate Change Research
Singh, S. (2002) Contracting Out Solutions: Political Economy of Contract Farming in the Indian Punjab,
World Development, 30, 9, 1621-1638.
Smit, B. and Pilifosova, O. (2001) Adaptation to climate change in the context of sustainable
development and equity, Climate Change 2001: Impacts, Adaptation and Vulnerability.
Contribution of Working Group II to the Third Assessment report of the
Intergovernmental Panel on Climate Change, WMO/UNEP, 877-912.
Smit, B., Burton, I., Klein, R. J. T. and Wandel, J. (2000) An anatomy of adaptation to climate change
and variability, Climatic Change, 45, 223-451.
Smit, B., Burton, I., Klein, R. J. T. and Street, R. (1999) The science of adaptation: a framework for
assessment, Mitigation and Adaptation Strategies for Global Change, 4, 199-213.
Smith, K. (1996) Environmental Hazards, Routeledge, London, pp 389.
Stenchion, P. (1997) Development and disaster management, Australian Journal of Emergency
Management, 12 (3), 40-44.
United Nations (2002) Risk awareness and assessment, in Living with Risk, ISDR, UN, WMO and Asian
Disaster Reduction Centre, Geneva, 39-78.
UNDHA (1992) Internationally Agreed Glossary of Basic Terms Related to Disaster Management,
United Nations Department of Humanitarian Affairs, Geneva.
The trans-disciplinary Tyndall Centre for Climate Change Research undertakes integrated research
into the long-term consequences of climate change for society and into the development of
sustainable responses that governments, business-leaders and decision-makers can evaluate and
implement. Achieving these objectives brings together UK climate scientists, social scientists,
engineers and economists in a unique collaborative research effort.
Research at the Tyndall Centre is organised into four research themes that collectively contribute
to all aspects of the climate change issue: Integrating Frameworks; Decarbonising Modern
Societies; Adapting to Climate Change; and Sustaining the Coastal Zone. All thematic fields
address a clear problem posed to society by climate change, and will generate results to guide the
strategic development of climate change mitigation and adaptation policies at local, national and
global scales.
The Tyndall Centre is named after the 19th century UK scientist John Tyndall, who was the first to
prove the Earth’s natural greenhouse effect and suggested that slight changes in atmospheric
composition could bring about climate variations. In addition, he was committed to improving the
quality of science education and knowledge.
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Complex Systems Management Centre (Cranfield University)
Energy Research Unit (CLRC Rutherford Appleton Laboratory)
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Recent Working Papers
Tyndall Working Papers are available online at
Mitchell, T. and Hulme, M. (2000). A
Country-by-Country Analysis of Past
and Future Warming Rates, Tyndall
Centre Working Paper 1.
Hulme, M. (2001). Integrated
Assessment Models, Tyndall Centre
Working Paper 2.
Berkhout, F, Hertin, J. and Jordan, A. J.
(2001). Socio-economic futures in
climate change impact assessment:
using scenarios as 'learning machines',
Tyndall Centre Working Paper 3.
Barker, T. and Ekins, P. (2001). How High
are the Costs of Kyoto for the US
Economy?, Tyndall Centre Working Paper
Barnett, J. (2001). The issue of 'Adverse
Effects and the Impacts of Response
Measures' in the UNFCCC, Tyndall Centre
Working Paper 5.
Goodess, C.M., Hulme, M. and Osborn, T.
(2001). The identification and evaluation
of suitable scenario development
methods for the estimation of future
probabilities of extreme weather
events, Tyndall Centre Working Paper 6.
Barnett, J. (2001). Security and Climate
Change, Tyndall Centre Working Paper 7.
Adger, W. N. (2001). Social Capital and
Climate Change, Tyndall Centre Working
Paper 8.
Barnett, J. and Adger, W. N. (2001).
Climate Dangers and Atoll Countries,
Tyndall Centre Working Paper 9.
Gough, C., Taylor, I. and Shackley, S.
(2001). Burying Carbon under the Sea:
An Initial Exploration of Public
Opinions, Tyndall Centre Working Paper 10.
Barker, T. (2001). Representing the
Integrated Assessment of Climate
Change, Adaptation and Mitigation,
Tyndall Centre Working Paper 11.
Dessai, S., (2001). The climate regime
from The Hague to Marrakech: Saving
or sinking the Kyoto Protocol?, Tyndall
Centre Working Paper 12.
Dewick, P., Green K., Miozzo, M., (2002).
Technological Change, Industry
Structure and the Environment, Tyndall
Centre Working Paper 13.
Shackley, S. and Gough, C., (2002). The
Use of Integrated Assessment: An
Institutional Analysis Perspective,
Tyndall Centre Working Paper 14.
Köhler, J.H., (2002). Long run technical
change in an energy-environment-
economy (E3) model for an IA system:
A model of Kondratiev waves, Tyndall
Centre Working Paper 15.
Adger, W.N., Huq, S., Brown, K., Conway,
D. and Hulme, M. (2002). Adaptation to
climate change: Setting the Agenda for
Development Policy and Research,
Tyndall Centre Working Paper 16.
Dutton, G., (2002). Hydrogen Energy
Technology, Tyndall Centre Working Paper
Watson, J. (2002). The development of
large technical systems: implications
for hydrogen, Tyndall Centre Working
Paper 18.
Pridmore, A. and Bristow, A., (2002). The
role of hydrogen in powering road
transport, Tyndall Centre Working Paper
Turnpenny, J. (2002). Reviewing
organisational use of scenarios: Case
study - evaluating UK energy policy
options, Tyndall Centre Working Paper 20.
Watson, W. J. (2002). Renewables and
CHP Deployment in the UK to 2020,
Tyndall Centre Working Paper 21.
Watson, W.J., Hertin, J., Randall, T., Gough,
C. (2002). Renewable Energy and
Combined Heat and Power Resources in
the UK, Tyndall Centre Working Paper 22.
Paavola, J. and Adger, W.N. (2002). Justice
and adaptation to climate change,
Tyndall Centre Working Paper 23.
Xueguang Wu, Jenkins, N. and Strbac, G.
(2002). Impact of Integrating
Renewables and CHP into the UK
Transmission Network, Tyndall Centre
Working Paper 24
Xueguang Wu, Mutale, J., Jenkins, N. and
Strbac, G. (2003). An investigation of
Network Splitting for Fault Level
Reduction, Tyndall Centre Working Paper
Brooks, N. and Adger W.N. (2003). Country
level risk measures of climate-related
natural disasters and implications for
adaptation to climate change, Tyndall
Centre Working Paper 26
Tompkins, E.L. and Adger, W.N. (2003).
Building resilience to climate change
through adaptive management of
natural resources, Tyndall Centre Working
Paper 27
Dessai, S., Adger, W.N., Hulme, M., Köhler,
J.H., Turnpenny, J. and Warren, R. (2003).
Defining and experiencing dangerous
climate change, Tyndall Centre Working
Paper 28
Brown, K. and Corbera, E. (2003). A Multi-
Criteria Assessment Framework for
Carbon-Mitigation Projects: Putting
“development” in the centre of
decision-making, Tyndall Centre Working
Paper 29
Hulme, M. (2003). Abrupt climate
change: can society cope?, Tyndall
Centre Working Paper 30
Turnpenny, J., Haxeltine A. and O’Riordan,
T. (2003). A scoping study of UK user
needs for managing climate futures.
Part 1 of the pilot-phase interactive
integrated assessment process (Aurion
Project). Tyndall Centre Working Paper 31
Xueguang Wu, Jenkins, N. and Strbac, G.
(2003). Integrating Renewables and CHP
into the UK Electricity System:
Investigation of the impact of network
faults on the stability of large offshore
wind farms, Tyndall Centre Working Paper
Pridmore, A., Bristow, A.L., May, A. D. and
Tight, M.R. (2003). Climate Change,
Impacts, Future Scenarios and the Role
of Transport, Tyndall Centre Working Paper
Dessai, S., Hulme, M (2003). Does climate
policy need probabilities?, Tyndall Centre
Working Paper 34
Tompkins, E. L. and Hurlston, L. (2003).
Report to the Cayman Islands’
Government. Adaptation lessons learned
from responding to tropical cyclones by
the Cayman Islands’ Government, 1988
– 2002, Tyndall Centre Working Paper 35
Kröger, K. Fergusson, M. and Skinner, I.
(2003). Critical Issues in Decarbonising
Transport: The Role of Technologies,
Tyndall Centre Working Paper 36
Ingham, A. and Ulph, A. (2003)
Uncertainty, Irreversibility, Precaution
and the Social
Cost of Carbon, Tyndall Centre Working
Paper 37
Brooks, N. (2003). Vulnerability, risk and
adaptation: A conceptual framework,
Tyndall Centre Working Paper 38
... This is because exposure (a component of vulnerability) to hazards like floods is determined by the probability of occurrence of the hazards (e.g. flood risk) and the sensitivity of the people or systems to the impact of the hazard (Brooks 2003), which is dependent on their adaptive capacity and which consequently influences their resilience. ...
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Rapid urbanisation is contributing to increasing societal vulnerability to disaster. This study aimed at exploring the perception on flood risk and ascertaining the determinants of disaster preparedness among residents in flood-prone urban communities. Descriptive statistics and discriminant regression model were employed on primary data collected from 240 urban households across five communities at risk of flooding in the study area. The results showed that most households had low awareness of flood risk and exhibit low levels of adaptive capacity, having adopted little or no measures to deal with disaster floods. Also, awareness of flood risk was observed to discriminate the most between the two groups of adopters and nonadopters of flood preventive and management measures (proxy for disaster preparedness), followed by flood risk perception, age, location and household size. Contribution: The study suggests an integrated approach (a combination of preventive, protective and control measures) by all stakeholders, including government and other relevant bodies, increasing public awareness of flood risk and its attending effects for greater responsiveness, supporting communities in regular clearing of drainage areas and strictly regulating the construction of buildings, particularly in flood prone areas.
... Adaptive capacity is a complex and evolving concept (Adams, 2021;Brown and Westaway, 2011), which can essentially be viewed as the ability of people to cope with stressors, either anticipated or realised (Brooks, 2003;Smit and Wandel, 2006). Adaptive capacity encompasses mechanisms that allow for recovery, minimisation of harm and benefiting from stressors, thereby offsetting negative impacts on people's welfare (Grothmann and Patt, 2005). ...
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Households within tropical coastal communities face a multitude of stressors related to environmental, social and economic change. To minimise negative impacts on households, a priority is to understand and if possible build adaptive capacity to enable adjustment to both extant, and anticipated stressors. Adaptive capacity may not be equally distributed across households due to social differences and inequalities, including gender. In this study we sought to understand whether the factors underlying adaptive capacity differ between men-and women-headed households across three marine protected areas (MPAs) in Zanzibar, Tanzania. Adaptive capacity was significantly higher in men-headed households compared to women-headed households between different MPAs as a whole, however significant differences were not found for men and women-headed households within the MPAs. The factors underlying adaptive capacity were investigated through boosted regression trees, a relatively novel approach within the field, and found to be similar between men and women counterparts. These factors were agency, material conditions, low ecosystem dependence, education, occupational multiplicity and needs satisfaction (i.e. a poverty indicator) which was singularly important in women-headed households. While the factors themselves were similar in men and women-headed households, gendered differences were found regarding differing levels in the identified factors. Accordingly, the processes that underly the differences found should be addressed within initiatives seeking to understand and build adaptive capacity.
... Such changes could be either long-term changes in climate conditions, or changes in climate variability, which includes the magnitude and frequency of occurrence of extreme climatic events (O'Brien et al, 2004). Adaptive capacity is defined as the ability of a system to adjust its behavior and characteristics to enhance its ability to cope with external stress (Brooks, 2003). It is considered ''a function of wealth, technology, education, information, skills infrastructure, access to resources, and stability and management capabilities'' (IPCC, 2001). ...
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The nature of various ecologies partly determines how vulnerable regions and localities are to climate change. In developing countries, the low level of technological innovations required to adapt effectively and high reliance on nature for livelihood make certain areas more vulnerable than others. The study investigates the vulnerabilities of the three major ecological zones (Lowland rainforest, Freshwater Swamp, and Mangrove Swamp) in Delta State of the Niger Delta Region to climate change. The Principal Component Analysis (PCA) was used to analyze exposure, sensitivity, and adaptive capacity indicators. Temperature and rainfall data used as the indicators for exposure were downloaded from NASA’s website and UCI CHRS’s data portal respectively and spanned from the year 1981 to 2019 for temperature and 2000 to 2019 for rainfall. PCA for sensitivity and adaptive capacity was carried out using thirty (30) sensitivity indicators and thirteen (13) adaptive capacity indicators, which were derived from the administration of 4,000 copies of questionnaire to rural residents of 10 selected Local Government Areas (LGAs) in Delta State. These were used to generate vulnerability scores (Z-scores), which served as measures of vulnerability, for the components – exposure, sensitivity, and adaptive capacity. The results showed that Warri North Local Government Area and Warri Southwest Local Government Area (both located in the Mangrove Swamp ecology) were the most vulnerable in terms of temperature, with Z-Scores of 3.096 and 2.681 respectively. In terms of rainfall, the results indicated that most LGAs located in the Freshwater Swamp were the most exposed to increased rainfall. In terms of sensitivity, Burutu and Patani LGAs located in the Mangrove Swamp and Ndokwa East LGA located in the Freshwater Swamp were the most sensitive to climate change. Burutu and Patani LGAs (which are both in the Mangrove Swamp) had the highest vulnerability based on low adaptive capacity. Overall, Patani and Burutu LGAs (both in the Mangrove Swamp ecological zone) were the most vulnerable to climate change. The study recommends that climate change interventions be delivered across communities in the Niger-Delta Region based on variations of the indicators of vulnerability.
... Here, flood risk is defined in terms of the risk to humans and the human society and is seen as a product of the severity and probability of occurrence of flood hazards and the vulnerability of the population/system (Brooks 2003). Factors influencing the severity of the hazards are depth and duration of inundation, velocity, rate of rising, frequency of occurrence, and season (Kumar and Balamurugan 2018;Panneerselvam et al. 2021b). ...
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Climate change is the foremost challenge faced by humans in this century. The threat of flooding, as a repercussion of climate change and growing impervious surfaces, is increasing day by day. Global climate change and hydrological extremes with high intensity and frequency have resulted in an upsurge in health risks. It is essential to integrate climate change, flooding, and health risks to develop a systematic adaptation strategy. Kannagi Nagar, located on the outskirts of Chennai city, Tamil Nadu, India, was chosen as the study area to assess the health risks due to climate change and flooding. During monsoons, the study area would transform into an island as it is located on the banks of the Buckingham Canal. Trash is littered throughout the area because there is little regard for environmental hygiene and sanitation. Local socioeconomic, demographic, and ecological conditions prevailing in the study area are also the drivers of the outbreak of diseases. In this study, the severities of floods due to climate change are assessed to identify the health risks. The health impacts on different age groups are analysed. This study shows the essential role of a health promotion agency and emphasizes that there is an urgent need for ongoing support and development work to reduce the health hazards in that area.KeywordsClimate changeFloodingHealth risk assessment
... Here, flood risk is defined in terms of the risk to humans and the human society and is seen as a product of the severity and probability of occurrence of flood hazards and the vulnerability of the population/system (Brooks 2003). Factors influencing the severity of the hazards are depth and duration of inundation, velocity, rate of rising, frequency of occurrence, and season . ...
Hydrological modelling is an essential tool, in this century, for effective planning and management of water resources. Ground observations serve as the backbone of hydrological models in which inadequate field data obtained from a watershed have become a challenge to the research community for proper management of the watershed. Despite several progresses in the models, the heterogeneity of watersheds limits the measurement of hydrological parameters, resulting in uncertainty and affecting the applicability and confidence of the models. In this chapter, a detailed survey has been carried out to address the development in the hydrological models over the decades and the reliability of different models. Summarising the calibration and uncertainties of the hydrological models, adopting datasets obtained through space technology is highly recommended, and new approaches need to be developed with the integration of information technology, statistics, and space inputs to overcome the limitations.KeywordsHydrological modelsCalibrationUncertaintyUngauged stationsHydrological advances
... Here, flood risk is defined in terms of the risk to humans and the human society and is seen as a product of the severity and probability of occurrence of flood hazards and the vulnerability of the population/system (Brooks 2003). Factors influencing the severity of the hazards are depth and duration of inundation, velocity, rate of rising, frequency of occurrence, and season . ...
The hydrological cycle (HyC) is affected by several factors, but climate and land use/land cover (LU/LC) are the most influential ones. This chapter has tried to show some satellite-based land use/land cover feature extraction methods that are useful for climate studies. Several literature works have claimed that climate is more influential than land use. Land use has an impact on several components of the hydrological cycle. This chapter provides a perspective on climate change, urbanization, land degradation, and other disasters and also on the usage of land use/land cover features in the study of the hydrological cycle. The anomaly in solar radiation due to greenhouse gas (GHG) emissions and its impact on climatic factors and the hydrological cycle with its implication in food production is briefed. Some of the global measurement missions for precipitation and land surface temperature (LST) are also discussed. To investigate the influence of land use/land cover on the hydrological cycle, identification of a particular class or all land use classes of a particular region may be essential. This chapter uses the synoptic view of satellite data and attempts to exercise certain indices to identify certain classes and classification algorithms to classify land use classes. This work has also experimented with certain classification algorithms to delineate some land use/land cover features and has also pointed out some limitations in the application of indices. This chapter discusses the factors that influence the hydrological cycle and highlights the usage of satellite data in regional studies.KeywordsHydrological cycleLand use/land coverClimateUrbanization and greenhouse gases
... Some, for instance, emphasize "vulnerability" as a core component of extreme event research. As Brooks (2003) notes, social scientists typically think of vulnerability in terms of the "set of socio-economic factors that determine people's ability to cope with stress or change," whereas climate scientists tend to view vulnerability as the "likelihood of occurrence and impacts of weather and climate related events." These differences in terms of research interest and natural/physical domains make one wonder whether scholars from these separate fields are studying specific subtypes of a more general phenomena (i.e., extreme events) or phenomena that are altogether different. ...
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The term “extreme event” is commonly used to describe high-impact, unanticipated natural events, like floods, tsunamis, earthquakes, and volcanic eruptions. It first appeared in the scientific literature in the 1950s and has since spread to disciplines as diverse as economics, psychology, medicine, and engineering. The term is increasingly being applied to the study of historical, prehistorical, and deep-time events across a broad range of scales, and it is widely acknowledged that such events have had profound impacts on the Earth’s biodiversity and cultures. Understandably, then, how people think about, define, and study extreme events varies considerably. With extreme events expected to become more frequent, longer lasting, and more intense in the coming decades as a result of global warming, the differing extreme event definitions—both across and within disciplines—is likely to lead to confusion among researchers and pose significant challenges for predicting and preparing for extreme events and their impacts on natural and social systems. With this in mind, we conducted a systematic quantitative review of 200 randomly selected, peer-reviewed “extreme event” research papers (sourced from Web of Science, accessed January 2020) from the biological, societal, and earth sciences literature with the aim of quantifying several pertinent features of the research sample. On the one hand, our analysis found a great deal of variability among extreme event papers with respect to research interests, themes, concepts, and definitions. On the other hand, we found a number of key similarities in how researchers think about and study extreme events. One similarity we encountered was that researchers tend to view extreme events within a particular temporal context and quite often in terms of rates of change. Another similarity we encountered was that researchers often think of and study extreme events in terms of risks, vulnerabilities, and impacts. The similarities identified here may be useful in developing a common and comprehensive definition of what constitutes an extreme event, and should allow for more comparative research into extreme events at all spatio-temporal scales which, we predict, will provide important new insights into the nature of extreme events.
... Adger (2006) recurre al término de sensibilidad con la misma definición anterior. Está dada por las características y las circunstancias del sistema, que lo hacen más o menos frágil a los efectos dañinos que podría producir una amenaza particular (Brooks, 2003) y constituye el antónimo de robustez (Urruty, Tailliez-Lefebvre & Huyghe, 2016). Resistencia indica el grado de dificultad de cambiar el sistema frente a un impacto y puede asimilarse al anterior (Walker, Holling, Carpenter & Kinzig, 2004). ...
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Hailstorms are one of the main threats to the sustainability of agricultural systems in Mendoza, which generate a disturbance factor for production forecasts; although they constitute events of random nature, the spatial distribution and the levels of intensity (and damage) acquire differential aspects depending on the allocation. The goal of the present work was to evaluate the economic losses in crops and determine the frequency and magnitude of extreme phenomena, resorting as primary source of data the records of complaints of these disasters. The economic losses attributable to the impact of "mangas de piedra" were calculated from this information of observational nature, and the phenomena in each campaign were then classified as extreme and very extreme, due to their relative level of losses. This work allowed qualifying the different departments according to their risk and the occurrence of extreme events, as well as the behavior of each campaign from 1993 to 2019, which will contribute to the generation of trend models of these phenomena. These models will be useful for the formulation of management strategies of climate risk and territorial planning. Copyright:
Himalayan agriculture households face an increased risk of vulnerability due to its harsh intrinsic social and environmental factors. And the changing climatic conditions are further enhancing the vulnerability of these systems. To improve adaptation strategies and policy formulation, the impact of climate change on a household level needs to be accessed. However, comprehending the role of social and environmental factors in vulnerability assessments to climate change has received little attention on a household level. To integrate the knowledge available in the scientific literature, we performed a systematic review of peer-reviewed literature available on household vulnerability assessment (n = 21, focusing on research conducted in the Himalayas region). We evaluated the available literature according to (1) bibliometric features of selected studies and (2) the dynamic of vulnerability assessment. Most of the articles reviewed by us assessed vulnerability utilizing statistical assessment methods. The number of studies incorporating both social and environmental aspects has increased in recent years. Almost 50% of the studies focused on a single stressor, i.e., climate change for vulnerability. Holistic approaches and multi-level assessment are mostly lacking, as studied to combinedly assess both social and environmental factors. KeywordsHousehold vulnerabilityAgricultureSystematic reviewHimalaya
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This paper considers synergisms between the impacts of two global processes, climate change and economic globalization. Both processes entail long-term changes that will have differential impacts throughout the world. Despite widespread recognition that there will be “winners” and “losers” with both climate change and globalization, the two issues are rarely examined together. In this paper, we introduce the concept of double exposure as a framework for examining the simultaneous impacts of climate change and globalization. Double exposure refers to the fact that certain regions, sectors, ecosystems and social groups will be confronted both by the impacts of climate change, and by the consequences of globalization. By considering the joint impacts of the two processes, new sets of winners and losers emerge.
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Adaptation to climate variability and change is important both for impact assessment (to estimate adaptations which are likely to occur) and for policy development (to advise on or prescribe adaptations). This paper proposes an "anatomy of adaptation" to systematically specify and differentiate adaptations, based upon three questions: (i) adapt to what? (ii) who or what adapts? and (iii) how does adaptation occur? Climatic stimuli include changes in long-term mean conditions and variability about means, both current and future, and including extremes. Adaptation depends fundamentally on the characteristics of the system of interest, including its sensitivities and vulnerabilities. The nature of adaptation processes and forms can be distinguished by numerous attributes including timing, purposefulness, and effect. The paper notes the contribution of conceptual and numerical models and empirical studies to the understanding of adaptation, and outlines approaches to the normative evaluation of adaptation measures and strategies.
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This is the final report from Tyndall research project IT1.16 (Estimating future probabilities of extreme weather events; Scenario development methods for the estimation of future probabilities of extreme weather events).
Under the United Nations Framework Convention on Climate Change (UNFCCC), adaptation has recently gained importance, yet adaptation is much less developed than mitigation as a policy response. Adaptation research has been used to help answer to related but distinct questions. (1) To what extent can adaptation reduce impacts of climate change? (2) What adaptation policies are needed, and how can they best be developed, applied and funded? For the first question, the emphasis is on the aggregate value of adaptation so that this may be used to estimate net impacts. An important purpose is to compare net impacts with the costs of mitigation. In the second question, the emphasis is on the design and prioritisation of adaptation policies and measures. While both types of research are conducted in a policy context, they differ in their character, application, and purpose. The impacts/mitigation research is orientated towards the physical and biological science of impacts and adaptation, while research on the ways and means of adaptation is focussed on the social and economic determinants of vulnerability in a development context. The main purpose of this paper is to demonstrate how the national adaptation studies carried under the UNFCCC are broadening the paradigm, from the impacts/mitigation to vulnerability/adaptation. For this to occur, new policy research is needed. While the broad new directions of both research and policy can now be discerned, there remain a number of outstanding issues to be considered.