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CLIMATE ADAPTATION:
ACTIONS, STRATEGIES AND CAPACITY
FROM AN ACTOR ORIENTED PERSPECTIVE
Stockholm Environment Institute
Oxford Working Paper
Lead authors:1
Tom Downing, Sukaina Bharwani, Stuart Franklin, Cindy Warwick and Gina Ziervogel
SEI Oxford Office
10b Littlegate Street
Oxford OX1 1QT, UK
Tel/Fax: +44 1865 202070/80
[email protected]
Contributing authors:
Mike Bithel, Edmund Chattoe, Mark New, and Richard Washington
Draft: November 2003
Introduction
Adaptation to climate—from present hazards to future changes in climate as both resource and
hazard—is well on the way toward being mainstreamed as part of sustainable resource
management. Many bilateral and international organizations have developed programmes on
climate risk management, including early warning systems, disaster preparedness, vulnerability
assessment, or seasonal climate prediction—important aspects of climate change adaptation.
The literature on specific measures to cope with climatic variability and hazards has been
articulate for some years, and corresponding studies of adaptive capacity are proliferating
(benchmarked against the IPCC, McCarthy et al., 2001, see Adger et al. 2003 for an example of a
broad review). Underlying frameworks, conceptual maps and analytical paradigms are not in
short supply. Although adaptation has a long academic history in social sciences, this literature
rarely reviews historical developments of thinking about cultural adaptation or risk management
(see Abel 1998, Bennett 1976, Ellen 1982, and Henrich 2002 for examples from anthropology).
At the same time, however, adaptation to climate change presents distinct challenges, primarily
due to the complexity of local-global resource management, the time scales involved and the
multi-actor dynamic nature of responding to changes in longer term climatic regimes as well as
episodes of climatic hazard.
This working paper presents an actor-oriented map of adaptation nomenclature. Our intention is
to develop an operational scheme for translating conceptual frameworks of adaptation planning
1
Contributing authors are welcome—let us know if you would like to further develop the working paper, add a case
study or suggest additional hypotheses.
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onto decision making models that are oriented toward stakeholders and institutions. Under the
general rubric of actor-oriented frameworks, the SEI-Oxford office is developing multi-agent
models of responses to climatic variations and climate change (for background on social
simulation see Doran et al. 1994, Dyke 1981, Fischer 2002, Gilbert and Troitzsch 1999, Hegmon
1989, and Kippen 1998). A requirement of such endeavours is a clear language for discussing
adaptation among a multi-disciplinary team and a scheme for treating adaptation with the formal
language of a model.
This actor-oriented perspective of climatic variability and climate change imposes specific
challenges on our search for a concise set of definitions and analytical terms. An analytical
approach should:
• Integrate present risk management and responses to climatic episodes (and other
perturbations) with long term formulation of strategies and resource planning.
• Integrate the formulation of broad strategies with the choice of specific adaptation
actions: strategies are built up from actions; actions inherit attributes of strategies.
• Differentiate between the strategies and actions employed by different actors.
• Link behaviour across geographic scales, so actions at one level are influenced by and
influence actions at a higher or lower scale.
• Link explicitly to the evaluation of actions, including multi-criteria assessment.
• Integrate with rational decision-making (but not rely on optimizing strategies) that can be
represented in formal models.
• Explore the relationship between actors and the evolution of negotiated behaviour or
conflicts; allow actors to learn over time, on their own and as members of institutions or
regimes.
• Generate hypotheses that can be tested in field work and analytical models.
Below, we briefly review existing adaptation terms, including the IPCC Third Assessment
Report, then present our nomenclature. Case studies from ongoing research projects illustrate
how the approach may be used, initially based on field work in Limpopo Province, South Africa.2
We conclude by suggesting the kinds of hypotheses which the actor-oriented approach could test.
Framing Adaptation
Literature on climate adaptation tends to into distinct groups. Most papers include a conceptual
framework or wiring diagramme. For example, the IPCC Third Assessment Report chapter on
adaptation (Smit et al. 2001) includes several flow charts. The Kasperson and Kasperson (2001)
vulnerability/adaptation diagramme suggests geographic scale (local-regional-global),
intersecting with flows from geophysical hazard and socio-economic vulnerability to impacts,
adjustments and adaptations.
While ‘wiring diagrammes’ are proliferating, it is clear that there is no consensus on operational
definitions and much less on analytical approaches. Common conclusions include (paraphrasing
colleagues):
2
An expanded version of this working paper will have case studies from East Anglia as part of a project with the
University of Oxford School of Geography and Environment (funded by the Tyndall Centre) and Orissa District of
India from a project with the National Centre for Agricultural Economics and Policy Research (funded by the U.N.
Environment Programme).
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•
•
•
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We’ve gone from dumb farmers to clairvoyant farmers, but need to understand smart
farmers and farmer-victims.
We cannot measure adaptive capacity, and therefore have given up on trying to measure
success in adaptation.
What is the adaptation baseline? Is it the thresholds (guardrails) in a coping range? Or is it
the qualitative nature of institutional regimes and their resilience?
If we can’t predict climate change vulnerability, how can we plan adaptation?
Following on from the search for indicators of vulnerability, coarse-level statistical descriptions
and typologies seek to capture relative adaptive capacity. For example, indicators at the country
level might include GDP per capita, literacy and transparency of governance. Such exercises
imply a view of adaptive capacity as the inverse of vulnerability. For example, the Battelle group
have experimented with national adaptive capacity indicators extracted from their global change
model (Moss et al. 2000).
Case studies of specific actors, locales or sectors are increasingly common. Most rely on
qualitative information and institutional analysis, at best weakly linked to formal models or
hypothesis testing. For example, Brooke (2004) progresses from climate scenarios in Costa Rica
to vegetation and land use impacts to a stakeholder-institutional analysis of adaptation regimes in
the Guanacaste region. Various proposals have recommended a systematic analysis of the case
study material in an effort similar to the analysis of land use change by the LUCC programme.
A common definition of vulnerability is the relationships between climate (as hazard or resource)
and impacts, for example as the depth-damage function for flood events. Adding in adaptive
options provides a quasi-empirical form for evaluating adaptive potential. For example, a
benchmark study for the World Bank coupled a catastrophe model of climatic hazards in Central
America with a macro-economic model to explore the role of national savings and international
‘insurance’ in national-level adaptation (Freeman and Warner 2001).
Even from this cursory review of existing approaches it is clear that the prevalent frameworks for
defining adaptation tend to distinguish between:
• The scale of action, whether local actors making specific decisions or institutional
capacity to monitor, learn and respond as and when appropriate.
• The timing of responses, e.g. whether anticipatory or reactionary.
• Effectiveness, whether the maximum potential (including new opportunities) or the
vagaries of real-world action (including maladaptation)
The IPCC TAR provides the benchmark for definitions regarding climate change (see box).
However, additional conceptual work is ongoing, notably through the UNDP Adaptation
Planning Framework (see www.undp.org/cc/apf_outline.htm) Tyndall Centre projects (see
http://www.geog.ox.ac.uk/research/projects/cloud/index.html) the exigencies of the National
Adaptation Programmes of Action (NAPA) exercises (see www.unitar.org/ccp/napaworkshops/ )
and other collective efforts.
The research community has faced the same challenge for vulnerability. To some extent the
major elements of vulnerability have been well characterised for some years—although there is
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continuing confusion about specific definitions and operational vulnerability assessments.
Earlier papers have suggested a formal nomenclature for vulnerability terms (see the Downing
paper in Smith, Klein and Huq 2003).
Adaptation terms defined in IPCC WGII Third Assessment Report
Adaptation
Adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects, which
moderates harm or exploits beneficial opportunities. Various types of adaptation can be distinguished, including
anticipatory and reactive adaptation, private and public adaptation, and autonomous and planned adaptation:
•
•
•
•
•
•
Anticipatory Adaptation—Adaptation that takes place before impacts of climate change are observed.
Also referred to as proactive adaptation.
Autonomous Adaptation—Adaptation that does not constitute a conscious response to climatic stimuli
but is triggered by ecological changes in natural systems and by market or welfare changes in human
systems. Also referred to as spontaneous adaptation.
Planned Adaptation—Adaptation that is the result of a deliberate policy decision, based on an
awareness that conditions have changed or are about to change and that action is required to return to,
maintain, or achieve a desired state.
Private Adaptation—Adaptation that is initiated and implemented by individuals, households or private
companies. Private adaptation is usually in the actor's rational self-interest.
Public Adaptation—Adaptation that is initiated and implemented by governments at all levels. Public
adaptation is usually directed at collective needs.
Reactive Adaptation—Adaptation that takes place after impacts of climate change have been observed.
See also adaptation assessment, adaptation benefits, adaptation costs, adaptive capacity, and maladaptation.
Adaptation Assessment
The practice of identifying options to adapt to climate change and evaluating them in terms of criteria such as
availability, benefits, costs, effectiveness, efficiency, and feasibility.
Adaptation Benefits
The avoided damage costs or the accrued benefits following the adoption and implementation of adaptation
measures.
Adaptation Costs
Costs of planning, preparing for, facilitating, and implementing adaptation measures, including transition costs.
Adaptive Capacity
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.
Source: IPCC. 2001. Climate Change 2001: Impacts, Adaptation and Vulnerability. Annex B: Glossary of Terms
(http://www.grida.no/climate/ipcc_tar/wg2/index.htm).
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An actor-oriented nomenclature
Here we propose a set of specific notations derived from the formal requirements of representing
adaptation in agent-based social simulation. The nomenclature represents a continuum from an
adaptation action to strategies, which are related to adaptive capacity and adaptive potential.
Before describing the terms in detail:
• An adaptation action is a specific response that an actor can implement.
• An adaptation strategy is a set of actions that an actor can chose from.
• Adaptive capacity is the super set of adaptive strategies, that is the combined set of
actions that exist within the domain of an individual actor.
• Adaptive potential is the ability of actors in a system to create new strategies and actions.
An adaptation action (Xa,i) is an action (i) that can be implemented by an actor (a). It
corresponds to the notion of a measure in greenhouse gas inventories. An action is a specific
action that exists at present and could be implemented. For example, changing the planting date
is an action in cropping systems. Each action (Xa,i) includes several attributes, such as:
• information required to enact the action, such as market forecasts,
• resources required to enact the action, including financial, labour and materials,
• expected outcome (which may be a complex function), and
• linkages to other actors (an action may require approval by other actors).
The adaptation actions that are actually chosen and implemented at a given point of time form a
subset of Xa,i. This might be denoted as X*a,i.
An adaptation strategy (Aa,j) is the set of adaptation actions, defined as:
Aa,j = {Xa,1, … Xa,n}
The adaptation strategy, formulated by an actor (a), consists of the specific actions (Xa,i)
available to the actor. As a strategy, however, Aa,j includes attributes of a systemic nature. The
main feature of a strategy is to include explicit goals or objectives that guide the choice of which
actions to implement. These strategies are ‘real’—they have been identified by the actors, they
are composed of specific actions that can be implemented, and they can be communicated to
other actors (although it is not necessary that every actor knows what other actors will do).
An actor is likely to have more than one strategy (j). For example, if the regulatory regime (at a
higher level of decision making) moves toward a market economy, then the actor may adopt
strategy (Aa,1) whereas a common property regime would imply strategy (Aa,2). There might be
some overlap in the elements of each strategy, however different rules would govern their
implementation.
Adaptation strategies (and by implication the adaptation actions) available to a specific actor
depends on social networks. For instance, if the actor is isolated from information, markets and
materials and constrained to decision making in the current season, then the adaptation strategies
are those in practice in the local area. However, most actors have access to wider networks, at
least to the district and probably the national level. At the global level the pool of strategies and
actions would be quite large for every sector. Whether they are ‘available’ to the local
community depends on processes of technology transfer, innovation and diffusion, and lead
entrepreneurs who demonstrate the local case for the strategy and/or action.
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The nature of decision making at the strategic level is less clear than for individual actions within
a strategy. For instance, if a farmer decides to improve her crop yields, the available tools are
known and choices can be represented as problems in economic, cultural or social network
decision making. However, farmer decision making regarding investment in off-farm
employment is likely to be more complex and situated in the social, economic and political
environment. Negotiation processes are inherent to resolving the choice the strategies and the
rules by which actions are implemented within each actors’ strategy.
The domain of adaptation actions and strategies is represented by the matrix:
Da =
Aa,1 = { Xa,1, … Xa,n }
Aa,2 = { Xa,1, … Xa,n }
…
Aa,n = { Xa,1, … Xa,n }
With a subset comprising those actions actually implemented (e.g., X*a,n).
Adaptive capacity (A’) is related to the set of adaptive strategies:
A’ = {Aa,1, … Aa,n}
That is, the macro-level attributes of actors capacity to adapt (whether wealth, information, role
in social institutions or other factors) can be related to the set of strategies that an actor has
available. For the moment, we leave open whether A’ relates to specific actors (with a subscript,
a) or is a property of an institution or resource management regime (represented as a collection of
actors).
This notation leads to a specific hypothesis. If Aa,i = Ø (there are no adaptation actions in the set)
then adaptive capacity is low. Or more generally, the number of identified strategies (j in Aa,j) by
a group of stakeholders (their portfolio) is often suggested as a measure of adaptive capacity.
That is, the existence of a range of options that could be implemented is a measure of adaptive
capacity.
A better measure of adaptive capacity would be the potential effectiveness of the different
strategies. For instance, a generalised risk assessment might be used to estimate the outcomes of
a number of stresses and shocks and to estimate the resilience of actors.
However, an unresolved issue is how to measure the effectiveness of adaptive capacity. For
adaptation actions and actor-specific strategies, we can default to criteria defined by the actors
themselves in choosing the specific actions. For instance, a threshold of food self-sufficiency
may be desirable and guide the choice of crops grown by smallholders.
The measures of adaptive capacity among a set of actors is more difficult. It is likely to include
notions of resilience (e.g., livelihood security), reward (e.g., economic costs and benefits), social
networks (e.g., maintenance of family obligations) and opportunities (e.g., successfully managing
a transition from farming to wage labour).
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Adaptive potential (A”) is one step removed from adaptive capacity (A’). It links the systemic
driving forces of socio-institutional change (income, technology, etc.) to actor/stakeholder
adaptive capacity. Adaptive potential includes the ability to innovate, whether creating new
strategies and actions or to find existing ones outside the actor’s customary network. A” is the
relationship between system properties and the adaptive capacity (specific sets of strategies) of
actors/stakeholders. Thus, we see A” as a system property not uniquely related to specific
stakeholders (and does not have the subscript, a).
Modelling adaptive potential might be implemented as a matrix of transfer coefficients, but it is
by no means clear what functions are suitable and could be validated. A first step is to take
socio-economic reference scenarios and construct plausible linkages to actors’ adaptive capacity.
This can be qualitative—some options would not be available—as well as quantitative—the
outcome of some options depends on system behaviour, such as the regulated price of water for
abstraction.
What are some salient features of the proposed notation?
First, it is possible to translate the generic framing of adaptation into actor-oriented models. For
instance, it is relatively straight-forward to propose specific actions for an agent to draw upon on
in a multi-agent model.
Secondly, specific hypotheses can be formulated. These might relate to the number of actions or
strategies, the attributes of the actions, or the intersection of strategies between competing or
cooperating agents.
Third, the nomenclature does not relate to a specific stimulus. That is, we have proposed a
generic way of implementing adaptation planning in a model. It would be relatively simple to
add a leading superscript, say (c) to denote climate change. In practise it might be more difficult
to distinguish between adaptive actions relating to a specific stimulus from an actor-oriented
planning framework that integrates across stresses to achieve some goal (albeit as a satisficing
decision maker).
Fourth, the confusion in the IPCC terminology is apparent. In the IPCC glossary, adaptation is
the elasticity between exposure to a stimulus and its consequences. It implies something that can
be measured (and a baseline established) and is ongoing (actual). However, adaptation also can
be the expected value of an elasticity in the future (based on expectations of a stimulus and its
response). And, adaptive capacity is a system property of potential ability, neither actual nor
related to specific threats. This corresponds more closely to our adaptive potential (A”).
However, the IPCC includes climatic variability, so it is wider than climate change adaptation.
The IPCC definitions cover a wide range of ground. Should all possible future adaptation be
discounted to a present value? Are adaptations related to every climatic stimulus? How is
adaptation negotiated when different stimulus suggest conflicting responses? It is hard to define
counter-examples of what would not be adaptation or adaptive capacity (as long as it has some
benefit in terms of resource management and human welfare).
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The IPCC includes various types of adaptation. But these are no more than a catalogue of
specific characteristics, both for the types of specific actions as well as for the systemic
processes. They would be attributes of the classes of Xa,i and Aa,i noted above. It is possible to
relate aspects of the IPCC definitions to the above notation (see Table 1).
The conflation of adaptation to climatic variability and (longer run) climate change can be framed
as a hypothesis:
• Adaptive capacity to climate variability (e.g., the set of strategies related to drought)
increases adaptive capacity to climate change (e.g., a change in the frequency, magnitude
and duration of drought in 2050).
This is one of the hypotheses in our modelling of seasonal climate prediction and climate change
adaptation in Limpopo Province.
Scale is embedded in this nomenclature. From the actions of individuals to meta-level properties
of adaptive capacity and potential is an increasing scale of abstraction and psycho-social
organisation. However, it is not evident that actors are only individuals nor that adaptive
potential is necessarily systemic. Institutions (and organisations) can act – a financial system can
raise interest rates. Equally, actors inherit some of the properties of institutions to which they
belong (and are active in constructing and changing those properties). The progression from Xa,i
to A’’ is not simply geographic.
Table 1. Adaptation nomenclature and related characteristics
Xa,i
Timing
Reaction to a stimulus
(at least a forecast of the
stimulus)
Aa,j
Anticipatory, designed
to cover a range of
stimulus
A’
Autonomous in the
sense that it triggers an
adaptive strategy and
choice of Xi, or
structural and
anticipatory
Meta-level property
A”
Actor
Individual actor or
organisation, dominated
by private
implementation
May be common to
many stakeholders,
close links to public
sector, e.g., through
regulation
As for As,i but often
developed by a group of
stakeholders, e.g., a
public/private
partnership
Determinates
Decision modes,
information, human and
financial resources
Property of institutions
Resources (human,
financial, social) are
important
As above, but more
emphasis on strategic
planning
Broader attributes of
stakeholders and
institutions, related to
strategic planning,
human and social capital
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An example: Food security in South Africa
This section illustrates the notation and typology with an example from South Africa.3 Rural
farming households in Limpopo Province employ a number of adaptation strategy sets in their
challenging environment. Some strategy sets focus on agricultural-related activities, whilst
others focus on off-farm means of securing a livelihood. For example, households might have
strategy sets that concentrate on on-farm agronomy, whilst other strategy sets might concentrate
on household consumption and expenditure and how to interact and use the market. Livestockrelated strategies, off-farm income, migration and the use of common resources are other types of
strategy sets. Different households may have different strategy sets, and rely on them to differing
degrees. Some households might employ a number of strategy sets with equal emphasis, while
other households might focus on a single strategy. Over time it is likely that households will alter
their strategy sets and the relative emphasis on one or another. Within each strategy set a number
of actions contribute to the success of the strategy. Some household might pursue many actions
that relate to the strategy set, whilst others might specialise in a few key actions.
Our example from Limpopo Province focuses on a village that have dryland fields, common
grazing land and shares in a community irrigation scheme. They are relatively poor households,
but grow a mixture of food and market crops and generally have quite good access to local and
even regional markets. For instance, if the irrigation water is adequate, many households grow
tomatoes for sale to juice processors in the region. Our field work and modelling, using agentbased social simulation, has focused on the use of seasonal climate forecasts. Table 2 shows three
strategy sets typical in this region and a range of actions that fall within each set (based on field
interviews over the past three years).
Table 2. Rural household strategy sets and actions
On-farm agronomy
Change cropping density
Adjust planting date
Invest in irrigation
Plant more land
Strategy sets (Aa,j)
Household consumption &
expenditure
Eat grain stores rather than
saving seed for planting the
following year*
Eat livestock
Sell chicken eggs rather than
eating them*
Buy new uniforms for children
Fertilise more in wet year
Send sick household members
to the clinic
Plant marketable plants
rather than subsistence
crops*
Eat fewer meals per day or
week
Market trading
Determine what is in demand in
the market*
Negotiate with traders to sell
produce
Access market information about
prices
Take produce to market (instead
of selling on-farm)
Take produce to regional market
(with larger number of
consumers) rather than local
market
* Action that bridges between two (or more) strategy sets.
3
Additional case examples are being compiled, and contributing authors are welcome too.
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Each of these strategy sets is affected by climate variability in some way, whether directly or
indirectly. By assessing the actions within each strategy set, it is possible to start to determine
how the climate might affect adaptation actions and so influence household strategies.
Understanding how and when strategy sets change is critical to understanding present adaptation
and future adaptive capacity.
Each action and strategy set has a number of attributes that help assess the likelihood of the
action being followed and its outcome. Above, we suggested that key attributes of actions
include:
• resources required to enact the action,
• expected outcome, and
• linkages to other actors
A number of actions fall within the on-farm agronomy strategy set for the emerging farmers of
Limpopo Province. For example, planting drought resistant varieties, increasing the diversity of
crop types, adjustment of planting dates or increasing fertilizer use are all actions that could
contribute to pursuing on-farm agronomy as a livelihood strategy set (see Table 3). A matrix of
qualitative ratings (low, medium and high in terms of cost or effectiveness) for each of the
attributes is included in the table. The ratings are shown for a wet year and a dry year—evidently
farmers have different strategies to manage risk and the expected outcomes are contingent upon
the nature of the season (as well as other factors).
An intensification strategy based on fertilizer application has low information requirements and
low to medium requirements for resources or community action. However, the outcome is
strongly affected by whether there is enough moisture (whether through rainfall or irrigation) to
increase yields substantially. There are also linkages to market strategies—a modest increase in
irrigated yield is valuable in a dry year.
Table 3. Example of on-farm agronomy in Limpopo Province
Strategy set: On-farm agronomy
Action: Increase fertilizer application
Expected outcome
Information required to enact
Resources needed
Increase yield
Knowledge of how fertilizer
increases yield
Expected rainfall--if too heavy will
wash away fertilizer, if not enough
then might be a waste to invest in
fertilizer when yields will be
constrained by moisture
Money or fertilizer
Improve soil
conditions
Ratings
Wet:
Dry:
H
L
L
L
Ability to transport
fertilizer to field
M
L
Linkages to other
actors
Information source
about fertilizer
Source of money to
buy fertilizer
L
L
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Other factors might also be considered when assessing the role of each action within the strategy
set. For example:
• Does pursuing the action have a long-term or short-term goal?
• Is the goal of pursuing the action in anticipation of poor yields, for example or a reaction
to other driving forces, such as the availability of resources?
• Is a change in actions or strategies a function of local changes, such as a new extension
officers who supports the use of fertilizer, or institutional forcing, such as subsidies for
fertilizer use.
The analysis of each strategy set, and the actions within it, can help to establish a baseline of
adaptation strategies. With a baseline of current practice, subsequent analysis can focus on
adaptive capacity and adaptive potential. These more complex measures require an assessment
of the circumstances under which actions and strategies shift so that households can respond or
adapt more effectively to the environmental stimuli.
Further methodological considerations
The framework proposed above is not (as yet) a complete analytical protocol. Three further
considerations are necessary:
• How do actors make decisions about the choice of strategies and actions?
• How can scenarios of global change relate to actor-specific adaptation?
• What is the relationship between the hierarchy of adaptation and the wider set of criteria
often proposed in the literature?
• What formal hypotheses about adaptation emerge from this preliminary analysis?
Choice and decision making
The adaptation nomenclature suggested here aids in describing the range of choice and clarifying
at what level of decision making (when, by whom, in response to what) key choices are made. In
modelling adaptation an algorithm is required to replicate the real-world decisions of actors.
Within agent based simulation this is a topic of ongoing debate and development (e.g., , Conte
and Casterlfranchi 1995, D’Andrade 1995, Kippen 1998).
At this stage, we offer the outline of a strategy rather than specific solutions.
It is possible to construct agents that have access to complete knowledge about the range of
choice and their expected outcomes and make optimising judgements. This might provide insight
into some aspects of adaptation potential but is unlikely to capture the more interesting aspects of
‘real world’ behaviour.
At other end of the spectrum, an approach to decision making might be based on ‘grounded
reality’ and ‘stylised facts’. Choices made by real actors are observed and replicated through a
relatively simple rule-based engine. For instance, a sequence of scenarios might be presented to
individuals or groups and their responses entered into a data base. Rules relating the conditions
of the scenarios can then be developed and incorporated into a model. Such an approach is in
progress in Limpopo project described above. While analytically tractable, such rule bases are
often static, constrained to relatively simple choices, and appropriate for the kinds of problems
where historical conditions and choices are relevant guides to behaviour.
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More sophisticated approaches require resolving some elements of internal decision making and
the influence of other actors. Representation of individual goals and objectives could filter the
range of choice. Actions that are successful might be endorsed, or weighted more strongly in
subsequent decision making. A weighting of what other actors are doing can be achieved,
discriminating perhaps among similar actors or those with greater authority.
From scenarios to actions
The overwhelming majority of global change scenarios are static visions of future conditions
derived from broad trends in environment, economies, technology and society (e.g., Raskin et al.
2002). These ‘driving forces’ are often assumed to apply across scales—geographically to local
communities, economically to livelihoods and socially to individual decision making (see
Warwick et al. 2003 for a discussion of scale in water scenarios).
Table 4 maps common driving forces onto the hierarchy of adaptation proposed here.
Immediately apparent from the connections is that global scenarios tend to focus on the
conditions of adaptive capacity and the implied decision making in the choice of strategies. For
instance, environmental attitudes are presumed to influence household proclivity to adopt say
organic farming rather than commercial, high-input farming. Fewer and perhaps weaker
connections are made to specific actions and to the global range of potential adaptive responses.
Also, it is difficult to make a direct connection between population growth (or size) and specific
levels of the adaptation framework.
Included in the table is a suggestion of how climate information links to the levels of adaptation.
In carrying out specific actions, operational forecasts are possibly important. Outcomes of the
chosen actions feedback into subsequent the choice of strategies and actions. The choice of
strategies and longer term development of capacity and potential are related to risk management.
A key requirement for actor-oriented scenarios would be to resolve the flow of information and
range of responses from potential to actions. That is, scenarios should make explicit which actors
have access to global domains of potential responses and which actors are responsible for
translating the global toolkit into locally available and suitable actions. The timing of such
processes will be critical—not all actors readily will have the ability to increase their range of
strategies or actions.
Translating adaptation criteria to actors
Adaptation to climate change (and climatic variability and hazards) has received significant
attention in the literature for at least a decade. Early work, summarised in the IPCC TAR (Smit
et al. 2001) presented a range of typologies and lists of criteria by which to judge adaptation
responses. How do these criteria relate to the actor-oriented approach proposed here?
An early (and convenient) typology of attributes of adaptation was compiled in a CICERO/World
Bank project (Ringius et al., 1996, Downing et al. 1997). The attributes and criteria from this
typology are matched against the levels of adaptation in
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Table 5. The focus on actors and stakeholders maps onto the decision making in actions and
strategies. Attributes of specific actions (such as the timing of costs and benefits) fits within the
attributes of actions. Most of the attributes and criteria are relevant to strategy sets and adaptive
capacity. However, few of the criteria suggested in existing typologies really address the longer
term domain of adaptive potential and the ability to learn and adopt new strategies. Apparently,
most typologies assume (quite rightly) that presently available coping strategies are sufficient and
the barriers are not new technologies but the social, economic and institutional framework for
adopting successful strategies.
Table 4. Mapping global scenarios onto adaptation actions
Driving forces
Adaptation
Climate information
Forecast Outcome
Risk
Notes
Population
Economy
Actions (X)
‘Downscaled’ from larger
conditions, logic of
decision making, and
trends and status of
economy, institutions and
environment
Technology
Governance &
institutions
Strategies (A)
Environmental
attitudes
Health
Capacity (A’)
Central to ‘top-down’
scenarios, link to strategies
Potential (A’’)
Not strongly connected
except through technology
Preferences &
modes of decision
making
Environment &
resources
Inferred from capacity,
strong links to economy,
governance, environment
Notes: Climate information relates to: Forecast of a climatic event or outcome in operational
decision making; the outcome or impact of climatic events; and longer term risk management
anticipating potential climate states.
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Priority stakeholder
Is there a stakeholder or vulnerable group that
should be given priority for targeting adaptive
strategies?
Resource conflicts
Are there conflicts over resource use between
or among different stakeholders? Would such
conflicts affect the ability to design and
implement specific adaptive strategies?
Multiple benefits
Does the adaptation have benefits for a
number of objectives and stakeholders?
Specificity to predicted climate change
Does the adaptation only have benefits if
climate changes in the expected direction?
Effectiveness
How effective is the adaptation in coping with
the expected climate change? Is there a critical
threshold beyond which the response will not
be effective
2. Resilience and purposeful
adaptation
Effective adaptive response
build upon present
capabilities to enhance
resilience to climatic
variations. Beyond this level
of response, purposeful
adaptation may be justified in
some sectors and for some
projects.
3. Strategic
Does the action have a role in
developing institutional
capacity or in planning future
responses?
4. Timing
There is a gap between the
implementation of adaptation
strategies and the realization
of their benefits.
Facilitating adaptation
Many of the most cost-effective adaptive
response have yet to be identified. In such
cases, fundamental research and stimulation of
innovation may be warranted.
Development pathways
The role of adaptation in shaping future
development needs to be assessed. Costly
response now may limit investment and
constrain development. This is a general
issue, but may apply for specific projects and
activities.
Matching planning horizon
What is the planning horizon required to
design and implement the adaptation? For
how long is the adaptation useful?
Irreversible impacts
Matching the timing of an adaptive response
and its benefits may need to consider the
possibility of irreversible impacts and option
values.
√
√
√
Potential
1. Stakeholder analysis
Adaptive responses are
specific to or most
appropriate for certain
stakeholders
Capacity
Specific Criteria
Strategy
Attribute
Action
Table 5. Adaptation criteria and actors
√
√
√
√
√
√
√
√
√
√
Adaptation working paper
5. Cost benefit
Economic evaluation of
projects is well-defined,
although contentious issues
of discount rates, valuing
environmental quality, and
equity remain.
6. Constraints for adoption
Adaptations will only be
effective if they are widely
adopted, with relatively
efficient means of
dissemination and
maintenance.
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Initial investment by stakeholders
The initial investment by stakeholders may be
a constraint, either because of poverty and
lack of credit among some stakeholder or
because the expected return is low compared
to other economic investments. The
difference between public and private
objectives and economic decision making may
be important in such cases.
Timing of benefits
The return on investment depends on the
timing of the benefits. Most of the strategies
suggested under a resilient development
scenario would have fairly immediate
benefits. Those that depend on long term
climate change would have a stream of future
benefits that might be very low in the near
future. Both social and market discounting
tend to reduce the present value of future
benefits.
Realization of benefits
The benefits may not accrue to the stakeholder
that makes the investment. The beneficiaries
are future generations, or other present social
and economic groups. This is a common
problem of equity in public interventions in
resource management. A common issue is
coping with climatic hazards is public liability
and financing (through taxation) of vulnerable
populations.
Information
Information about the strategy, its utility and
means of implementing it may be lacking.
Also, available information may not be
communicated effectively.
Technical development
The adaptation may not be technically
reliable, or it may require a level of technical
development that is not available for all
stakeholders.
Natural resources and environment
Agroclimatic, land use and other resource
constraints may limit adaptation options.
Social, cultural and political barriers
Many of the most significant barriers to
innovation are institutional, encompassing the
social norms of behaviour, cultural means of
communication and decision making, and
political processes of empowerment and
participation.
07/04/2004
√
√
√
√
√
√
√
√
√
√
√
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Hypotheses regarding adaptation measures and strategies
What hypotheses emerge from this framework? While we maintain that the context (of
adaptation capacity, A’) is essential, we can use the terms introduced above to suggest
hypotheses in ways that further case studies and model results might begin to resolve:
1. If Aa,i = Ø (there are no adaptation actions in the set) then adaptive capacity is low. That
is, the existence of a strategy without specific actions also identified (along with their
attributes for decision making) does not contribute greatly to adaptive capacity. An
example might be a move to organic farming for export of specialist crops without the
farmer knowing what is required in order to achieve the strategy.
2. The number of identified strategies (j in Aa,j) by a group of stakeholders (their portfolio, a
measure of diversification) is a measure of resilience and adaptive capacity. That is, the
existence of a range of options that could be implemented is a measure of adaptive
capacity.
3. Alternatively, a small number of actions or strategies, if successful historically, indicates
specialisation and a shift from survival to integration in market economies. Such
specialisation is a measure of adaptive capacity. Having a large number of strategies
practiced by an actor competes for managerial expertise, skill and resources.
4. Information on seasonal climate forecasts (or climatic variability and longer run change)
is of greater benefit with a larger number of actions available to the actor.
5. Adaptive capacity is not simply the number of strategies but some weighting of their
likelihood of success.
6. Most critical for long term climate change is learning and adoption of strategies that
already exist but are not available in the immediate network of the actor.
7. Changing the emphasis or priority of strategies requires or responds to factors at the
community or national level (or beyond).
Such hypotheses can be translated into statements that can be tested in formal models with
support from field work.
Conclusions
This working paper has put forward a formal notation and hierarchy of adaptation terms. It draws
upon an actor-oriented approach and the demands of agent-based social simulation. The
framework clarifies some conflicts in existing terms and provides a strong link to formal research
and models of adaptive behaviour.
A formal framework of this sort opens up a set of empirical tests for further research. For
example:
• How similar are actions (X) across actors and environments?
• How effective are actions in response to climatic threats? What might an aggregate
response curve look like? Are there areas where the anticipated effects are beyond present
coping ranges?
• How effective are actions across multiple stresses?
• Are there synergies in strategies and actions for different stresses?
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We conclude that an actor-oriented approach is possible as a bridge between qualitative, in-depth
field work and formal testing of system properties of resilience and adaptive capacity. Fully
implementing such a system would provide richer scenarios of future threats and a platform for
interactive exploration of behaviour.
Acknowledgements
The stimulus for this working paper initially has been two projects of the SEI and School of
Geography and Environment at the University of Oxford, funded in part by the Tyndall Centre.
The Cloud project is exploring the utility of seasonal climate outlooks in adaptation to climate
change in South Africa. An integrated regional project on adaptation by farmers focuses on the
linkages between land and water management in East Anglia. Collectively, we have benefited
from many discussions with colleagues around the world. Of particular note have been the
meetings of the AIACC project (including the vulnerability and adaptation course in Trieste),
UNDP Adaptation Planning Framework process, Tyndall cluster meetings and UNEP side events
at UNFCCC conferences.
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