CLIMATE RESEARCHClim Res

Vol. 24: 71–90, 2003 Published June 10

1. INTRODUCTION

Climate change induced by greenhouse gas emis-sions occurs on decadal time scales, over which timesocieties and economies will also change. Climate-change impacts and adaptation will occur not intoday’s, but in a future world. ‘Scenarios’, which areself-consistent, credible storylines of how socio-eco-nomic systems may develop in the future, can be usedto provide the socio-economic backdrop for climate-change studies. In this paper, we report on the devel-opment of socio-economic scenarios (SES) for use in aUK-government-comissioned, model-based integratedassessment of the impacts of climate change uponhydrology, biodiversity, agriculture and the coastal

zone in 2 contrasting English regions: East Anglia andthe North West (the REGIS project). We do not presenthere the actual results of the integrated assessment:these are presented elsewhere (www.ukcip.org.uk/integ_assess/integ_assess.html). The need for socio-economic scenarios for each of the 4 above domains inthe REGIS project emerges because of the role ofsocio-economic change and policy decisions in under-standing the future state of those domains. For ex-ample: • The vulnerability of the coastal zone to climate

change depends upon the standard of protectionprovided and the extent of coastal development—decisions which are socio-economic and related topolicy and politics.

© Inter-Research 2003 · www.int-res.com*Email: simon.shackley@umist.ac.uk

Constructing social futures for climate-changeimpacts and response studies: building qualitativeand quantitative scenarios with the participation of

stakeholders

Simon Shackley1,*, Robert Deanwood2,**

1Tyndall Centre for Climate Change Research, Manchester School of Management, UMIST, Manchester M60 1QD, United Kingdom

2Department of Planning and Landscape, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom

**Present address: Entec UK Ltd, Gables House, Kenilworth Road, Leamington Spa, Warwickshire CV32 6SX, United Kingdom

ABSTRACT: This paper describes the development of socio-economic scenarios, in both qualitativeand quantitative terms, for use in integrated assessment modelling of the impacts of climate changein 2 contrasting English regions: East Anglia and the North West. The need for socio-economic sce-narios is discussed, and the ‘mediating’ role that they play between intellectual debate and policydeliberation is analysed. Four scenarios are constructed for each region: regional enterprise, globalsustainability, regional stewardship and global markets, and we provide the rationale for the socio-economic and policy changes we propose under each scenario. Spatial mapping of 2 of the scenariosin each region is then conducted for 3 illustrative issues (built development, biodiversity and coastalzone), and a sample of non-spatial agricultural variables is inferred. A major focus of the paper is anexamination of the experience of engaging stakeholders in the development of the socio-economicscenarios. We explore, in particular, how stakeholders reconciled a given long-term scenario frame-work with their shorter-term and particular policy-driven requirements.

KEY WORDS: Socio-economic scenarios · Regional climate-change impacts · Stakeholders

Resale or republication not permitted without written consent of the publisher

Clim Res 24: 71–90, 2003

• Crop selection and cultivation practice dependsupon many other variables apart from climate, in-cluding crop yields, crop prices, costs of other inputs,subsidy policies, other environmental restrictions,and so on. Such variables are the result of economictransactions and socio-political decisions.

• The vulnerability of biodiversity to climate change islikely to be influenced by the way in which sites,habitats and species are managed. Such decisionsare partly social, for example, dependent upon avail-able resources. How society in the future will per-ceive and value biodiversity will have an importantinfluence on resources and biodiversity manage-ment.The SESs had to provide 2 distinct types of inputs to

the integrated assessment. Firstly, some quantitativeinputs to numerical models of land use, the coastalzone and hydrology were required from the SESs forthose variables which are dependent upon futuresocio-economic change and policy decisions. Secondly,SESs provided the context for interpreting the resultsof numerical modelling, as was the case for the biodi-versity domain within REGIS.

There is now a considerable literature on scenariosfor use in environmental assessment and policy devel-opment, and a correspondingly vigorous debate inacademia and policy circles concerning their applica-tions (e.g. van der Heijden 1996, Ringland 1998, DTI1999, Yohe et al. 1999, Lorenzoni et al. 2000a,b, IPCC2001, Strzepek et al. 2001, UK Climate Impacts Pro-gramme 2001, VISIONS 2001, Berkhout et al. 2002). Inthis paper we wish to contribute to this debate throughaddressing the following questions: • How can stakeholder communities be included in

the scenario-building process in a way that encour-ages maximal engagement of the stakeholders withthe outputs of research and analysis?

• How can we quantify SESs which are derived from aqualitative development of different storylines andwhat problems are implied by a quantification?

1.1. Why do we need SESs?

The traditional ‘predict and provide’ approach toforesight and forecasting has a distinct benefit overscenarios, which is also its weakness: it provides a sin-gle prediction of the future. The benefit of predictiveforecasting is that it reduces the uncertainty facingdecision-makers. In reality, that may be an illusorybenefit, however, because the prediction is most oftenincorrect (Ascher 1981), resulting in sometimes costlymistakes and bad decisions (e.g. Collingridge 1992,IAPA 1998). The demand for reduction in uncertaintyis best seen as a political and institutional pressure,

which arises from the dominant forms of policy legiti-mation through recourse to scientific knowledge inindustrialised societies, as analysed by Ezrahi (1990).This politico-institutional pressure for certainty issomewhat at odds with the pressure from the scientificcommunity itself to fully acknowledge and explore theproperties of uncertainty.

Scenarios help to open-up to scrutiny by policy-makers and stakeholders the uncertainty of the deci-sion-making context, yet they limit exploration ofuncertainty to a discrete number of possibilities, only asmall number (usually 2 to 4 in past practice) beingconsidered. Scenarios provide what we can term ‘con-strained uncertainty’. Pragmatic considerations favourconstrained uncertainty, namely the organisationaland cognitive barriers to utilising a large number ofdifferent scenarios, especially where there are no sim-ple quantitative indicators for comparison, and wheremultiple agents are engaged in the policy-develop-ment process (though there are a few instances wherelarger numbers have been employed in policy deliber-ation, e.g. Lempert 2000, IPCC 2001). Wider stake-holder participation has become an important objec-tive of policy processes in many countries, and this alsohelps to explain why new approaches to accommodat-ing diverse perspectives and potentially radically dif-ferent futures have become more salient. A discretenumber of suitably differentiated scenarios can permitdiversity whilst allowing the policy process and itsassessment functions and negotiations to be manage-able.

1.2. Independent versus co-evolutionary SESs

Climate-change scenarios are well established, and4 scenarios (high, medium-high, medium-low and low)have become embedded in climate-change impactsresearch in the UK through the agency of the govern-ment’s UK Climate Impacts Programme (UKCIP)(Hulme & Jenkins 1998, McKenzie-Hedger et al. 2000).The UKCIP then commissioned development of SESs,and 4 such scenarios were developed by Berkhout etal. (2001) from a framework derived from internationalresearch performed on behalf of the Intergov-ernmental Panel on Climate Change (IPCC) (UKCIP2001, Berkhout et al. 2002) (see Fig. 1).

There are 2 ways of combining climate change withSESs (see Fig. 2). One is to treat both sets of scenariosas formally independent (Fig. 2, left). The SESs do nottake any account of climate change, and both scenariosets provide separate inputs to the system modelswhich are run at the desired future time point (2050,2080, etc.). The second approach is to allow for interac-tion between climate change and socio-economic

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Shakley & Deanwood: Constructing social futures for climate-change impacts

changes prior to the integrated model run, an ap-proach which has been termed co-evolutionary(Lorenzoni et al. 2000a) (Fig. 2, right). If vulnerablesystems such as water resources are seriously affectedby climatic factors, including (inter alia) climatechange, then this will influence the social and politicalresponse to the protection of those systems not just inthe 2050s or 2080s, but probably much sooner. Theseparticular responses will clearly have a impact uponthe subsequent vulnerability of such systems to climatechange in 50 to 80 yr time. Indeed, coastal protectionpolicy is already partly driven by the perceived directeffects of climate change, with the height of new sea-wall defences in the UK being raised by 4 mm yr–1 inresponse to climate model simulations (MAFF 1999).Co-evolutionary scenarios are clearly more realistic ofsocial systems, which are responsive and will changebecause of the understanding and/or experience ofclimate change and its impacts. Non-climate-changeSESs are, nevertheless, useful for at least the following4 reasons. • Firstly, they are conceptually more straightforward

than fully interactive socio-economic and climate-change scenarios. This is an important considerationwhen working with a wide range of stakeholders,many of whom are not at all familiar with a scenario-based approach to analysis. Interactive scenariosamplify what is already a high degree of complexityand uncertainty. Such complexity and uncertaintymay be justified intellectually, yet it may signifi-cantly hinder the likelihood of effective stakeholderengagement.

• By definition, ‘non-climate-change’ SESs provide theextreme case of a society that does not respond at allto the threat of climate change over the next 50 to80 yr. For example, if the SES which maximisesstress upon biodiversity, water, coastlines and agri-cultural systems is combined with a high level ofclimate change, we are likely to have something

approaching the ‘worst-case’ scenario. Knowledge ofpotential extremes is helpful in devising robust poli-cies.

• Such independent scenarios permit a clearer distinc-tion to be drawn between the effects of physical cli-mate change and socio-economic changes (andhence their use clarifies the precise effect of re-sponses at a given point in time; Klein & Nicholls1999). Once multiple time-dependent feedbacks be-tween climate change and socio-economic changeare included, then the relative impact of physical cli-mate change, socio-economic change and socio-eco-nomic/political responses becomes more difficult tountangle (especially if relatively few model runs canbe performed because of resource costs).

• The non-climate SESs are combined with appropri-ate climate-change scenarios in the integrated as-sessment. Hence, the regional enterprise scenariowas combined with the high-climate-change sce-nario, because it is a high-growth, high-fossil-fuel-use scenario. The global sustainability scenario was

73

Fig. 1. The socio-economic scenario (SES) framework (ad-apted from Berkhout et al. 2000, 2001, UK Climate Impacts

Programme 2001, after IPCC 2001)

Fig. 2. Independent (left) and co-evolutionary (right) scenario techniques

Clim Res 24: 71–90, 2003

• combined with the low-climate-change scenario,because it implies a transition to an energy systemwith a lower carbon intensity. Whilst the matching-up of all SESs and climate-change scenarios is notentirely straightforward (Shackley & Wood 2001), itbecomes less viable if socio-economic responses areincluded in the SESs, because changes to carbonintensity should be included in addition to adapta-tion. For these reasons, use of non-climate SESs is a valu-

able first stage and is the approach taken here. A sub-sequent step is the co-evolutionary approach entailingfurther elaboration of the responses and adaptation tothe impacts of climate change within each SES at dis-crete points into the future, in order to permit the effec-tiveness of alternative adjustments and planned re-sponses and policies (as agreed by the stakeholdersand research team) to be explored. In that sense, thework reported on here (and indeed the integratedassessment of the REGIS project) is far from constitut-ing a comprehensive evaluation for decision-making.

1.3. Response to criticism

Before entering into the detail of the paper, weaddress 2 criticisms which were raised by reviewers ofthis paper. Firstly, are these SESs really about climatechange or are they applicable to any forward-lookingdevelopments? The scenario framework could indeedbe applied to a wide range of social, economic, politicaland environmental issues. That is a necessary require-ment because of the need to incorporate potentiallywide-ranging (non-climatic) change in the analysis ofclimate-change impacts. Yet a generic framework suchas provided by the SRES scenarios of the IPCC (2001)or Berkhout et al. (2001) is only the starting point inproducing SESs for an integrated assessment ofregional climate change. The latter task requiresunderstanding and knowledge of the models used,their outputs and sensitivities and especially thosemodel inputs which are required from the SESs. Thescenarios we report on here are therefore highly cus-tomised and the result of an extended interaction withsystem modellers and climate-change specialists.Reporting on the experience of proceeding from thegeneric scenario framework to the specific customisedscenarios is, we hope, a useful contribution to the cli-mate-research literature.

Secondly, it may be asked why we have includeddetails of the SESs themselves in the paper, rather thanfocusing solely on the stakeholder experience. Thefocus of the interactions between ourselves, the stake-holders and the modellers was on the content, struc-ture and rationale of the scenarios themselves—hence

they have the role of mediating devices. It is not reallypossible to understand the process of stakeholderinteraction without some knowledge of what the sub-stantive focus of stakeholder interest actually was,namely the scenarios themselves. It is comparable toundertaking research on how different stakeholdersrespond to policy development, where it would be dif-ficult to analyse such responses without some knowl-edge of what those policies actually are.

1.4. Structure of the paper

Firstly, we provide a qualitative description of thesocio-economic scenarios, and summarise the interpre-tations of them for each region in Tables 1 & 2. We thenproceed to quantifying 2 of the scenarios for eachregion, explaining how this has been done. The quan-tification is only possible when a well-formulated qual-itative interpretation has been undertaken. Section 4focuses upon the experience of working with stake-holders in developing these scenarios. We concludewith some lessons learnt and advice for similar futurescenario development activities.

2. DEVELOPING THE SOCIO-ECONOMICSCENARIOS: QUALITATIVE CHARACTERISATION

The SESs embrace complex societal and economicchange and use this to derive indicators of plausiblefuture states by the 2050s. They do not emergedirectly from current practises per se; rather theyabstract particular forces for change, differentiatingand extrapolating them. Whilst climate-change sce-narios are derived from general circulation models(GCMs) which are constructed according to the inter-pretation of physical processes and the laws whichgovern them, and are reasonably constrained byknown empirical data sets (Shackley et al. 1998), nocomprehensive socio-economic model or equivalentmethodology exists by which to generate SESs, andthere is little accumulated past experience uponwhich to build. This is not to deny that there aresome sectoral or disciplinary models in the social sci-ences which are robust in certain contexts andtimescales (e.g. demographic, economic, land-usemodels: see Yohe et al. (2002) for some applicationsin the climate-change impacts field) but there is noth-ing which combines the many separate interactingstrands which together weave the social fabric: atleast not which would gain the agreement of thewider social-science community. There are, as far aswe can know, an infinite number of possible socio-economic futures, and unfortunately there is no

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Shakley & Deanwood: Constructing social futures for climate-change impacts

(uncontested) socio-economic theory which can iden-tify the likely range in which the future scenario willfall (contra climate-change scenarios). Major ques-tions therefore arise as to the degree of credible dif-ferentiation we can make between the different SESs,and it is difficult to know whether we have robustscenario constituents (in the sense of workingthrough an intellectually defensible process whichproduces a relevant variable), or whether we aremaking educated, but ultimately subjective, guesses.The answer to that question is probably unknowable.

We have used the framework set out in Fig. 1,which has been adapted from Berkhout et al. (2001,2002; who in turn have adapted the IPCC’s SRESframework), by a somewhat different interpretation ofthe top right-hand and top left-hand quadrants(Shackley & Wood 2001). There are 2 key differencesfrom Berkhout et al. (2001). Firstly, we have rede-fined their ‘national enterprise’ and ‘local steward-ship’ scenarios at the regional scale, i.e. ‘regionalenterprise’ and ‘regional stewardship’. This seemednecessary for a regionally focused assessment. Sec-ondly, we have interpreted the top-left hand ‘regionalenterprise’ scenario as a high-growth future, unlikeBerkhout et al., who regard it as a lower-growthfuture. In so doing, we are adopting the more opti-mistic, desired-for future of the regions which isentertained by many regional stakeholders. It is notthe purpose of this paper to discuss the merits or oth-erwise of the framework outlined in Fig. 1. This hasbeen extensively covered elsewhere, reflecting thewidespread use of these scenarios and their closeIPCC antecedents (e.g. IPCC 2001, UK ClimateImpacts Programme 2001, Berkhout et al. 2001, 2002).Our construction of the SESs drew upon the follow-ing:

(1) UKCIP SES report (Berkhout et al. 2001). (2) Discussions within the REGIS team as a whole

(consisting of scientists representing hydrology, cli-mate change, soil science, agricultural resources,coastal systems and biodiversity).

(3) Three regional stakeholder workshops held in1999, which involved approximately 100 stakeholdersfrom the public, private and voluntary sectors, with aprofessional interest in the regions’ environment andsustainable development. We invited all the main bod-ies who operate at the regional and sub-regional scalesthat we felt might have an interest in climate-changeimpacts and successfully attracted most of the keyplayers with a direct regulatory or policy developmentrole (we estimate about 2⁄3 of our key target organisa-tions attended), as discussed elsewhere (Shackley &Deanwood 2002). It was not possible to define a for-mally representative list of regional stakeholderswhich should be included in the consultation process,

because many individuals and groups operate at arange of scales (from local to national); many of thesehave a potential interest in climate-change impacts,and there is a high degree of overlap between organi-sational and professional concern with regional cli-mate-change impacts. The English regions are onlyabout 5 yr old as distinct political entities, and many or-ganisations do not yet have a clear regional presence.Hence, there is no obvious demarcation of a represen-tative body of regional stakeholders. Inevitably, wehad to rely upon good will, general interest and gov-ernment sponsorship of the project in order to attractparticipants.

(4) The spatial development scenarios developed bythe North West Planning Team (NWRA 1999).

(5) The structure plans and regional planning guid-ance for the North West and East Anglia (GOEE 2000,NWRA 2000). (Regional Planning Guidance sets thebroad framework in which more detailed local (struc-ture) plans are articulated.)

(6) The regional economic strategies for the NorthWest and East of England (NWDA 1999, EEDA 1999).

(7) Subsequent discussions with stakeholders fromboth regions on what scenario runs should be exploredwithin REGIS at a workshop in December 1999, involv-ing approximately 20 stakeholders from public, privateand voluntary sectors (e.g. regional water companies,Royal Society for the Protection of Birds, the Environ-ment Agency and English Nature, as well as national-level civil servants).

(8) Face-to-face meetings with 1 regional planner inEast Anglia and 3 regional planners in the North Westin August 2000 and subsequent feedback on the char-acteristics of the ‘planners’ scenario’.

The 4 scenarios—regional enterprise, global sus-tainability, regional stewardship and global markets—are interpreted for the regional scale and describedbelow. In each case, the analysis is organised under 3themes: economy, society and environment. The spec-ulative nature of the scenarios renders them con-tentious and inevitably subject to disagreement; how-ever, they are only illustrative and are deliberatelyintended to demonstrate the potential for divergentfutures. We have designed the scenarios such that theyare evidently distinct but not entirely different fromone another or entirely alien relative to the presentday.

A planners’ scenario was also developed, based onregional planning documents and discussions withplanning officers in the 2 regions. The national meet-ing of regional stakeholders in 1999 requested thatsuch a planners scenario be formulated, in response to3 main criticisms of the UKCIP SESs. • Firstly, that the 4 SESs developed according to Fig. 1

were ‘extremes’, and that in the view of the meeting

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nd

new

del

iber

ativ

e•

Los

t co

asta

l h

abit

ats

rep

lace

d i

nla

nd

• w

ith

hig

her

em

plo

ymen

t•

dem

ocra

tic

pra

ctic

es•

Bio

div

ersi

ty p

olic

y fo

cuse

d o

n p

re-

• W

ater

ch

arg

es a

pp

lied

to

lim

it w

ater

-hu

ng

ry•

Th

e ot

her

‘soc

iety

’ ele

men

ts o

f th

e G

S

• se

rvin

g a

nd

im

pro

vin

g e

xist

ing

an

d•

mod

es o

f fa

rmin

g•

scen

ario

are

rep

eate

d h

ere

• tr

adit

ion

ally

fou

nd

bio

div

ersi

ty a

sset

s •

Org

anic

foo

ds

wil

l b

ecom

e a

maj

or p

art

of

• S

tron

g r

egio

nal

id

enti

ty•

thro

ug

hou

t th

e la

nd

scap

e •

food

su

pp

ly•

‘Gra

nd

exp

erim

ent’

to

recr

eate

pas

t•

‘Ap

pro

pri

ate’

, sm

alle

r-sc

ale

and

gen

eral

lyle

ss•

lan

dsc

ape,

ag

ricu

ltu

re a

nd

bio

div

er-

•co

mp

lex

tech

nol

ogie

s d

evel

oped

wit

h a

foc

us

• si

ty o

f E

ast

An

gli

a•

on s

ust

ain

able

ag

ricu

ltu

re a

nd

lan

d u

se, f

ood

•

pro

cess

ing

, tra

nsp

orta

tion

an

d r

enew

able

• en

erg

y

Tab

le 1

. In

terp

reta

tion

s of

SE

Ss

for

Eas

t A

ng

lia.

EU

: E

uro

pea

n U

nio

n;

ICT

: in

form

atio

n a

nd

com

mu

nic

atio

n t

ech

nol

ogie

s; R

AM

SA

R:

des

ign

ated

coa

stal

bio

div

ersi

ty

pro

tect

ion

sit

es; S

AC

s: s

pec

ial

area

s of

con

serv

atio

n; S

PA

s: s

pec

ial

pro

tect

ion

are

as

Shakley & Deanwood: Constructing social futures for climate-change impacts

the future was more likely to be a combination of ele-ments of the 4 SESs. • Secondly, that the 2050 time horizon was too distant

to be of direct use in contemporary policy making,and that a nearer-term scenario for 2020 was desir-able.

• Thirdly, that the planning process is thinking 15 yrahead through development of structure plans andregional planning guidance, yet none of the UKCIPSESs related particularly well to the changes envis-aged in such ‘real world’ policy deliberation. Thestakeholder group felt that it was important that atleast 1 scenario should reflect the state-of-the-artanalysis within professional planning. We felt that the above points were valuable insights

and accord with social-science understanding of theco-existence of diverse ‘ways of organising’ and modesof rationality, rather than the ‘ideal types’ explored inthe UKCIP SES framework (Thompson et al. 1990,Shackley & Gough unpubl.). Furthermore, engage-ment with real ‘on-the-ground’ decision-makers wasfelt to be facilitated by utilising the longer-term plan-ning trajectory that has been agreed through an ana-lytical and consultative process at the local-to-regionalscale. We also elicited from the planners their ‘vision’(though not their ideal) of each region by the 2050s.The idea here was to obtain a planning-oriented sce-nario which would include the inevitability of socialcomplexity and compromise, according to the plan-ners’ judgement, yet which could also be comparedwith the 4 other SESs. We should emphasise that weare not presenting the planners scenario as more orless likely that the other 4 scenarios. It is, rather, a morehybrid scenario which incorporates elements of severalof the UKCIP SESs from the perspective of the plan-ning profession.

We now present each of the scenarios in turn. Westart with a general description, followed by a moredetailed elaboration for both regions in Tables 1 & 2.Further details can be found in Shackley & Wood(2001).

2.1. Regional enterprise (RE)

In the RE scenario, the UK regions function as semi-autonomous economic units. There is a successful coa-lescence of economic, social and political interests andpatterns of interaction at the regional scale, whichreduces the dependency of the regions upon the tradi-tional centres of power and decision-making (bothpublic and private sector) in London and the SouthEast. The highly successful northern and central Italianregions (such as Emilia Romagna) are a good modelhere (Piore & Sabel 1984, Putnam 1994, Saxenian

77

Sce

nar

io•

Eco

nom

y•

Soc

iety

• E

nvi

ron

men

t

Glo

bal

mar

ket

sR

ein

forc

emen

t of

est

ab-

• E

con

omic

gro

wth

con

sist

entl

y h

igh

er t

han

th

e•

Coa

stal

an

d r

iver

ine

floo

d d

efen

ce w

ill

be

• ‘W

ild

life

gar

den

ing

’ wil

l d

omin

ate

atli

shed

gro

wth

pat

tern

s•

UK

lon

g-t

erm

ave

rag

e ra

te•

pri

vati

sed

wit

h g

over

nm

ent

wit

hd

raw

ing

• se

lect

ed p

opu

lar

site

sd

rive

n b

y th

e g

lob

al m

ark

et•

In g

ener

al, e

con

omy

as f

or R

E, b

ut

wit

h a

• fo

rm i

ts c

urr

ent

role

• W

ater

res

ourc

es s

een

as

mar

ket

able

• st

ron

ger

dis

par

ity

in i

ntr

a-re

gio

nal

dev

elop

-•

Th

is w

ill

incr

ease

vu

lner

abil

ity

to f

lood

ing

•

com

mod

ity,

wit

h t

ran

sfer

s u

sed

to

• m

ent

pat

tern

s•

inp

oore

r ar

eas;

som

e se

ttle

men

ts a

re s

ent

•

mee

t d

efic

it•

Hig

h d

evel

opm

ent

in s

outh

ern

par

t of

reg

ion

• in

to a

neg

ativ

e sp

iral

of

dec

lin

e •

clos

e to

Sou

th E

ast

and

Lon

don

•P

riva

te f

lood

cov

er w

ill

lim

it t

he

exte

nt

of•

Hig

h d

evel

opm

ent

arou

nd

Cam

bri

dg

e (‘

sili

con

• co

asta

l d

evel

opm

ent

• fe

n’)

du

e to

its

glo

bal

ly-c

omp

etit

ive

hig

h t

ech

-•

Pop

ula

tion

gro

ws

in s

elec

ted

par

ts•

nol

ogy

sect

or•

of t

he

reg

ion

; dec

lin

es i

n m

ore

rem

ote

area

s•

Nic

he

dem

and

for

org

anic

foo

ds

and

eco

-•

Str

ong

id

enti

ty a

s ‘g

lob

al c

onsu

mer

’•

tou

rism

wil

l b

e m

et a

t th

e E

uro

pea

n a

nd

• g

lob

al-s

cale

• In

ten

sive

ag

ricu

ltu

re w

ill

con

tin

ue

wh

ere

it•

can

com

pet

e g

lob

ally

• S

hor

t-st

ay t

ouri

sm i

n N

orfo

lk a

nd

Su

ffol

k T

able

1 (

con

tin

ued

)

Clim Res 24: 71–90, 200378

Sce

nar

io•

Eco

nom

y•

Soc

iety

•E

nvi

ron

men

t

Reg

ion

al e

nte

rpri

seD

evel

opm

ent

of s

ucc

essf

ul,

•

Eco

nom

y g

row

s ju

st b

elow

UK

ave

rag

e, b

ut

• P

opu

lati

on g

row

s d

ue

to a

gei

ng

; net

zer

o•

Som

e m

anag

ed r

eali

gn

men

t of

am

ore

self

-con

tain

ed e

con

-•

dec

lin

e h

alte

d•

mig

rati

on a

ssu

med

du

e to

eco

nom

ic

• sm

all

amou

nt

of l

ow-l

yin

g, l

ow-

omic

dev

elop

men

t p

atte

rns

• H

igh

-gro

wth

are

a in

sou

ther

n p

art

of r

egio

n (

arc

• re

new

al•

gra

de

agri

cult

ura

l la

nd

bec

ause

too

and

str

ong

er r

egio

nal

• fr

om M

anch

este

r to

Liv

erp

ool)

• R

etir

emen

t to

Cu

mb

ria

incr

ease

s p

opu

-•

exp

ensi

ve t

o p

rote

ct, b

ut

cult

ura

l,id

enti

ty•

Su

bsi

dy-

dep

end

ent

hil

l-fa

rmin

g d

ies

away

• la

tion

th

ere

• to

uri

sm a

nd

his

tori

cal

area

s p

ro-

• H

orti

cult

ure

an

d d

airy

th

rive

th

rou

gh

su

cces

sfu

l•

Incr

ease

d d

eman

d f

or t

ouri

sm, e

.g. s

hor

t-•

tect

ed•

reg

ion

al b

ran

din

g•

stay

mar

ket

• T

arg

et a

reas

for

man

aged

rea

lig

n-

• R

egio

nal

pac

kag

es t

o p

rese

rve

som

e h

ill-

farm

ing

• L

ocal

ised

pre

ssu

res

for

coas

tal

dev

elop

-•

men

t co

uld

be

Sol

way

Fir

th a

nd

•

as a

way

of

life

• m

ent,

e.g

. bet

wee

n L

iver

poo

l an

d B

lack

-•

Mor

ecam

be

Bay

• U

pla

nd

s m

ain

ly u

sed

for

rec

reat

ion

an

d l

eisu

re•

poo

l, b

ut

over

all

less

th

an E

ast

An

gli

a•

Su

rplu

s w

ater

fro

m t

he

reg

ion

is

• ra

ther

th

an f

arm

ing

, how

ever

•

bec

ause

of

less

vib

ran

t g

row

th a

nd

sm

alle

r•

exp

orte

d t

o ot

her

par

ts o

f E

ng

lan

d•

Em

erg

ence

of

new

hig

h-t

ech

nol

ogy

sect

ors

• p

opu

lati

on c

han

ge

• w

hic

h s

uff

er f

rom

wat

er s

hor

tag

es•

(bio

tech

, mat

eria

ls, n

anot

ech

nol

ogie

s)•

Dev

elop

men

t oc

curs

th

rou

gh

out

the

• R

ule

s co

veri

ng

des

ign

ated

nat

ure

• re

gio

n, p

arti

cula

rly

alon

g t

ran

spor

t•

con

serv

atio

n a

reas

are

rel

axed

• co

rrid

ors

Nor

th-S

outh

an

d E

ast-

Wes

t•

wh

ere

they

sta

nd

in

th

e w

ay o

f•

Rel

ativ

ely

hig

h d

evel

opm

ent

pre

ssu

res

• m

ajor

new

dev

elop

men

t in

th

e•

pro

mot

es u

rban

reg

ener

atio

n, t

hou

gh

• so

uth

ern

met

rop

olit

an p

art

of t

he

• p

ock

ets

of b

lig

ht

rem

ain

• re

gio

n (

thou

gh

not

in

th

e ru

ral

• S

tron

g r

egio

nal

id

enti

ty•

nor

th)

• P

riva

tely

fin

ance

d n

atu

re r

eser

ves

• em

erg

e: ‘w

ild

life

gar

den

ing

’

Glo

bal

su

stai

nab

ilit

yS

ust

ain

able

dev

elop

men

t •

Eco

nom

ic g

row

th i

nit

iall

y lo

wer

, bu

t th

en r

ever

ts•

New

coa

stal

dev

elop

men

t is

not

per

mit

ted

• W

ater

res

ourc

es s

een

fro

m a

nat

io-

wit

hin

glo

bal

an

d E

U•

to l

ong

-ter

m U

K a

vera

ge

• C

onso

lid

atio

n, i

mp

rove

men

t an

d b

ette

r•

nal

per

spec

tive

, th

e ai

m b

ein

g a

n

spat

ial,

pol

itic

al a

nd

soc

ial

• S

tron

g e

mp

has

is o

n m

ovin

g t

owar

ds

low

-in

ten

sity

• p

lan

nin

g o

f th

e u

rban

coa

stli

ne

is i

nst

ead

• eq

uit

able

sh

arin

g o

f th

e re

sou

rce

fram

ewor

ks

• an

d o

rgan

ic f

arm

ing

•ad

van

ced

• ac

cord

ing

to

nee

d

• O

lder

‘mat

ure

’ man

ufa

ctu

rin

g s

ecto

r ad

apts

its

elf

• S

tron

g i

den

tity

as

‘res

pon

sib

le E

uro

pea

n’

• W

ater

-ric

h r

egio

ns

are

exp

ecte

d t

o •

to i

nn

ovat

ion

aro

un

d s

ust

ain

able

tec

hn

olog

ies

• p

rovi

de

wat

er t

o w

ater

-poo

r •

reg

ion

s th

rou

gh

a n

ew n

atio

nal

• w

ater

net

wor

k

Reg

ion

al s

tew

ard

ship

Att

enti

on to

en

viro

nm

enta

l •

Eco

nom

ic g

row

th c

onsi

sten

tly

low

er th

at th

e U

K’s

• M

ore

coh

esiv

e u

rban

com

mu

nit

ies

emer

ge

• P

rote

ctio

n o

f bio

div

ersi

ty a

nd

up

lan

dim

pac

ts o

f al

l as

pec

ts o

f •

lon

g-t

erm

ave

rag

e ra

te•

as m

ore

hom

e-w

ork

ing

, com

mu

tin

g d

e-•

lan

dsc

ape

is m

ajor

pol

icy

obje

ctiv

eec

onom

y an

d s

ocie

ty w

ith

• U

pla

nd

far

min

g p

rese

rved

th

rou

gh

reg

ion

al s

ub

-•

crea

ses,

res

urg

ence

of

loca

l n

etw

ork

s,•

Dai

ry f

arm

ing

su

bje

ct t

o m

ore

con

-p

arti

cula

r at

ten

tion

to

the

• si

die

s b

ut

far

few

er l

ives

tock

per

hec

tare

• cl

ub

s, e

tc. (

hig

her

soc

ial

cap

ital

)•

trol

s on

sil

age

and

eff

luen

t d

is-

loca

l an

d r

egio

nal

sca

les

• S

tron

g l

ocal

mar

qu

es f

or a

gri

cult

ura

l p

rod

uce

• L

ocal

op

pos

itio

n (

NIM

BY

ism

) w

ill

not

be

• ch

arg

e•

wou

ld e

mer

ge

•su

ffic

ien

t to

pre

ven

t m

anag

ed r

eali

gn

men

t•

Lim

ited

op

por

tun

itie

s fo

r m

anag

ed•

Exp

ansi

on i

n l

ocal

an

d s

ust

ain

able

tou

rism

•w

her

e se

en a

s b

ein

g i

n i

nte

rest

s of

th

e•

real

ign

men

t b

ecau

se o

f ex

ten

t •

‘Ap

pro

pri

ate’

, sm

alle

r-sc

ale

and

gen

eral

ly l

ess

•re

gio

n’s

en

viro

nm

ent

• of

coa

stal

dev

elop

men

t•

com

ple

x te

chn

olog

ies

dev

elop

ed, w

ith

a f

ocu

s on

• T

he

oth

er e

lem

ents

of

‘soc

iety

’ for

RS

in

• N

ever

thel

ess,

th

ere

wil

l b

e a

slow

• u

pla

nd

an

d d

airy

far

min

g, t

reat

men

t of

con

tam

i-•

Eas

t A

ng

lia

are

rep

eate

d h

ere

• re

esta

bli

shm

ent

of l

owla

nd

wet

-•

nat

ed l

and

, urb

an e

nvi

ron

men

t an

d r

enew

able

• S

tron

g r

egio

nal

id

enti

ty•

lan

ds

and

mos

ses

alon

g c

oast

lin

e,•

ener

gy

• w

ith

now

-ext

inct

lak

es, p

ond

s an

d•

hab

itat

s re

-em

erg

ing

Tab

le 2

. In

terp

reta

tion

s of

SE

Ss

for

the

Nor

th W

est.

Def

init

ion

s as

in

Tab

le 1

, exc

ept

NIM

BY

ism

: Not

In

My

Bac

k Y

ard

rea

ctio

n

Shakley & Deanwood: Constructing social futures for climate-change impacts

1996). Economic development in those regions appearsto have been a function of a strong regionalism, whichhas cultivated flexible and competitive economic part-nerships and supply-chains within the region, espe-cially between smaller companies. This vision of theregion is certainly one which is widely shared amongstpolicy makers at the regional scale, as indicated inregional economic strategies (EEDA 1999, NWDA1999). Use of this scenario allows the consequences forregional water, biodiversity, the coastal zone and agri-culture of the implementation of many policy makers’own desired futures to be explored.

2.1.1. Economy. The regional economy grows atslightly above the long-term average rate. Agriculturewill become more exposed to market forces and coulddecline as a result, although there would be supportwhere this promotes regional cohesiveness. Technol-ogy development is promoted within the region,though strong links remain with outside sources oftechnological innovation.

2.1.2. Society. A high degree of devolution toregional government will facilitate considerably moreregional networks, policy and decision-making andpolitical involvement than is currently the case.

2.1.3. Environment. A greater awareness of the roleof the environment as a regional economic asset and afundamental part of quality of life is characteristic.

2.2. Global sustainability (GS)

Here the global approaches to achieving sustainabledevelopment take precedence over regional responses(cf. the RS scenario below). The World is seen as aninterconnected whole, functionally and morally, with aconcentration on the wider impacts of individualactions.

2.2.1. Economy. The economy grows at a slightlylower rate than the long-term average. A reformulatedEU Agricultural Policy encourages growth of the mostsuitable crops locally in the context of the Europeanlandmass. Development patterns reflect a desire to con-serve greenfield resources, and cities become substan-tially more compact than at present, their charactertransformed through city greening, new public trans-portation systems and the establishment of pedestrian-oriented enclaves. Nevertheless, some new greenfieldsettlements are developed where these can demon-strate a high degree of self-containment and the en-hancement of the landscape into which they are placed.Environmental externalities will be more comprehen-sively included in economic costs, at a relatively lowlevel agreed within global trading regimes. TechnologyR&D will be directed towards sustainable productionand consumption and will be accessible globally.

79

Sce

nar

io•

Eco

nom

y•

Soc

iety

•E

nvi

ron

men

t

Glo

bal

mar

ket

sR

ein

forc

emen

t of

est

ab-

• E

con

omic

gro

wth

sim

ilar

to

the

UK

lon

g-t

erm

• O

utw

ard

mig

rati

on f

rom

eco

nom

ical

ly•

Lim

ited

res

ourc

es g

o to

bio

div

ersi

tyli

shed

gro

wth

pat

tern

s•

aver

age

rate

•d

epre

ssed

are

as•

pro

tect

ion

–‘w

ild

life

gar

den

ing

’d

rive

n b

y th

e g

lob

al m

ark

et•

Dev

elop

men

t is

pat

chy,

wit

h s

tron

g g

row

th i

n•

Net

ou

twar

d m

igra

tion

fro

m r

egio

n a

s a

• S

acri

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Clim Res 24: 71–90, 2003

2.2.2. Society. The degree of popular awareness ofglobal development and sustainability issues is high.Sustainability considerations will lead to conflict overindividual choices (such as a desire to find a higherquality of life in the countryside but being restricted bythe environmental impacts and associated costs oftravel).

2.2.3. Environment. Biodiversity and water re-sources—and priorities for conservation and improve-ment—are analysed at the European and globalscales. Coastal protection policy is directed towardsthe most vulnerable regions considered in a nationalcontext. There is some restoration of coastal salt marshand freshwater habitats given that such habitats arekey to the survival of internationally important popula-tions of migratory bird species. Tidal barrages forrenewable energy generation and storage of fresh-water will be evaluated in both regions (e.g. Wash,Mersey, Wyre, Morecambe Bay), though controversyover environmental impacts will delay any firm deci-sion.

2.3. Regional stewardship: RS

Here the emphasis is on recognising and conservingregional assets, accepting that this might result in asignificantly reduced level of economic growth andeven a contraction of the economy. A more all-embrac-ing way of living is accepted which recognises theimportance of local community, quality of life and thevalue of local natural assets.

2.3.1. Economy. The economy grows more slowlythan in any other of the scenarios. Environmentalexternalities are incorporated into economic costs at arelatively high level through a combination of nationaland regional economic instruments. There are signifi-cant support packages for local industries which bene-fit environmental integrity (such as renewable energy,clean technologies and sustainable agricultural meth-ods). The development of small businesses and co-operatives serving local demand will be encouraged aspart of more community-focused ways of living. The(relatively-limited) regional technology R&D which isdirected towards sustainable production and lifestyleswill also flourish, and somewhat bring down the costsof, e.g. locally sourced organic foods and biofuels.Extension of global markets into the regions will belimited through imposition of trade tariffs aimed atcharging importers the full costs of environmentalexternalities. This will limit the availability of technolo-gies developed outside of the region, thereby increas-ing costs and slowing-down the implementationof existing and new technologies (including moresustainable ones).

2.3.2. Society. Policy making will involve extensivepublic consultation, including surveys, focus groups,citizens panels and juries, and possibly even refer-enda. Policy comes to reflect as far as possible localand regional concerns, which will tend to turn policyattention ‘inwards’ to valuing and conserving theregions’ stock of assets. This focus on the region is nota denial of global problems and issues, but rather amanifestation of the slogan: ‘think globally, act locally’.

2.3.3. Environment. The landscape setting, coast-line, agriculture, hydrology and biodiversity resourceswill be seen as priorities for enhancement to build backthe stock of environmental capital which has beeneroded since industrialisation. The lower level of eco-nomic growth limits the resources available for expen-sive response measures (such as hard coastal defence)and in any case soft engineering approaches and man-aged realignment which ‘work with nature’ are pre-ferred. There is scepticism of ‘technological fixes’ asthe solution to environmental problems and a prefer-ence for regionally and community-oriented behav-ioural and participative responses. Drainage of landwill be slowly phased-out as river and coastal defencesare realigned, and as the most highly vulnerable set-tlements in the flood plain are abandoned and theirresidents relocated. The aim of biodiversity policy willbe ‘nature in the countryside’, rather than wildlife gar-dening (cf. the RE scenario). Short rotation willow cop-pice and other biomass for bio-fuels and combustion inlocal combined heat and power facilities, with furtherbenefits for amenity and rural diversification, willexpand, though extensive afforestation will be limitedfor reasons of ecological diversity and landscapeappearance.

2.4. Global markets (GM)

A global market orientation is one based on the pur-suit of high and sustained growth within a global con-text.

2.4.1. Economy. The economy grows at slightlyabove the average rate, but is patchy, with high andlow rates within different parts of the regions. Certainareas within the regions will be subject to particularlyintense development pressures, with consequences forlocal land-uses, water resources, the coastline and bio-diversity. Meanwhile, other areas will suffer fromunder-investment and neglect, as global capital flowsreadily between currently favoured localities. Floodprotection will cease to be a standard component ofinsurance policies, and cover will become much moreexpensive for those households in flood-risk areas.Technology R&D will be driven by global marketopportunities, with little regard for sustainability.

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Shakley & Deanwood: Constructing social futures for climate-change impacts

2.4.2. Society. Intense competition in a deregulatedeconomy will encourage migration to seek work anddisrupt community links to places and people.

2.4.3. Environment. In the high growth areas, therewill be significant exploitation of environmentalresources to meet the overriding demands of globalcapital (and with very little internalization of externalcosts). Strategic economic decisions will override localinterests, although there will be recognition of the eco-nomic value of some environmental resources for theleisure and tourism industries.

2.5. Planners’ 2020 commitments and 2050’s vision

The scenarios for development by 2020 are based onthe projections of Regional Planners for housing devel-opment over the next 20 yr, and informal discussionswith regional planning teams. The projections are basedon figures for housing commitments contained in thedraft Regional Planning Guidance for East Anglia(GOEE 2000) and for the North West (NWRA 2000) andreflect pressures for development. These commitmentsare location specific but are not necessarily a guide as tothe type of development which will be permitted (interms of density for example) or the extent of future de-velopment beyond the 15 yr time frame of the planningguidance. Whilst we have been able to use some of thenumbers for population flows and new household num-bers provided in draft Regional Planning Guidance,therefore, we have had to speculate on where preciselysuch development might take place. This we have donethrough face-to-face discussions with members of the re-gional planning teams responsible for production of theRegional Planning Guidance in both East Anglia and theNorth West. We view the numbers provided not as ‘pro-jections’ but as an additional scenario based on ‘dynam-ics as usual’, as moderated by planning. We have thenattempted to create a scenario for the 2050s from theplanners’ scenario for 2020, largely through a reinforce-ment of the trends to 2020. Again, this has been achievedthrough discussions with regional planning officials, in-cluding feedback on our first draft scenarios for 2020 and2050.

2.5.1. East Anglia. The Cambridgeshire sub-regionis the centrepiece of development activity up tothe 2020s, based on the explosive growth of theknowledge-based economy here. The rapid develop-ment of adjacent Peterborough further enhances thevibrancy of this part of the region. New solutions forhousing will be well advanced by the end of the 2020s,particularly new settlements surrounding Cambridge.However, the constraints of infrastructure capacity,water resources and health services will begin to biteduring this period, and significant investment dilemmas

will appear. Rural depopulation in the less accessibleeast and north east of the region is likely to remain aproblem. Nevertheless, the allocation of significant hous-ing growth to Norwich and towns such as Thetford andDereham reflects the desire to meet latent demand forhousing and help stimulate economic growth. The fur-ther expansion of the Cambridgeshire sub-region em-phasises the importance of nationally and internationallycompetitive areas, and the role of this part of the regionin the European growth arc.

The period to the 2050s is likely to see continuedurban expansion, notably in the existing centres ofeconomic activity (Peterborough, Cambridge, Nor-wich, the A14 road Corridor and along the A11 andA12 road routes from the region into Greater London).Limited scope for ‘brownfield’ development meansthat, building on trends evident by the 2020s, consider-able attention will have to be paid to the developmentof new settlements. The tide of rural depopulation willhave been halted by this time, using developments ininformation and communication technologies (ICT) toestablish new patterns of rural working and living.Dilemmas over further road development is likely to bea critical issue by this time, as areas without good com-munication links slip further behind those which arewell connected inter-regionally and internationally.

2.5.2. North West. The pattern of development pro-posed in the North West to the 2020s is one of modestgrowth centred on existing settlements. The north-south axis is the focus for much growth, particularlylinking the towns and cities spanning the M6. Theintegrity of the Green Belt is respected with only rela-tively minor revisions to its current boundaries. Therationale for higher urban densities along with thereuse of derelict and brownfield land is driving currentthinking, with considerable areas of vacant land(notably in East Manchester) awaiting redevelopment.A difficult balance is being sought, however, betweenthe urgency of regeneration and the desire of people(and builders) for specific kinds of property, ideally ingreenfield locations. The development of the philoso-phy and practice of city greening will be central to therealisation of the planners’ aspirations of reversing thetide of urban out-migration. Complex commuting pat-terns will still characterise the next 20 yr, reinforced bythe success of some ‘hot spots’ within the region (suchas Chester and Warrington) and the availability ofcheaper housing immediately outside the region (prin-cipally North Wales).

By the 2050s, a halt to out-migration from the region isexpected combined with a significant urban renaissancewhich attracts people back into the urban cores. Some ofthese could be second homes but the growth of ICT islikely to stimulate even more complex patterns of work-ing and living. Travel patterns are likely to be different,

81

Clim Res 24: 71–90, 2003

based on restrictions, cost and the potential for home-working. The region will reach for a higher Europeanprofile, and the development of stronger trading linksboth with adjacent regions and across Europe based onsignificantly increased rail, and possibly air, freight ca-pacity. The structure of industry and agriculture is likelyto be significantly different, with substitution of uplandagriculture by land stewardship and management forbiodiversity, tourism and recreation.

3. QUANTIFICATION OF THE SOCIO-ECONOMICSCENARIOs

The variables which needed to be quantified in theSESs as inputs to sectoral models are outlined inTable 3. Space precludes a detailed analysis of howquantification was progressed for each variable; in-stead we will focus on the derivation of the scenarios ofdevelopment for the 2 scenarios which were requestedby the integrated assessment modellers: RE and GS.We should stress that the precise numbers are in-formed guesses which are illustrative of the particularscenario in question; they have been derived by judge-ment based on literature review and iteration withexperts and stakeholders.

3.1. Spatial variables for urbanisation

The spatial patterns of urbanisation are illustratedfor today, and in more detail for the North West for

the RE, GS and planners’ scenarios (Fig. 3). A 5 × 5km grid is used as the basic mapping unit into whichvalues for current urban, forest and protected area(RAMSAR, SAC and SPAs) coverage are apportioned,this being the size of the grid used to map the cli-mate-change scenario variables. These values arethen adjusted according to the qualitative thinkingbehind the RE and GS scenarios for the year 2050.The scenarios were formulated such that the differ-ences are visible both compared to today and forcomparison of each scenario. Ordnance Survey mapsand discussion with regional experts were used to tryto ensure that the changes are credible and physi-cally plausible. Hence extensive development alongmany parts of the North Norfolk coastline has notbeen proposed under RE, since there are physicallimitations due to the lack of suitable land for build-ing between the salt marshes and the higher groundthat rises behind the coastline. Likewise, new settle-ments have not been put on top of the Pennine Hills,since there would be major logistical obstacles tosuch development and a lowland development ismuch more feasible. The scenarios were presented tothe national stakeholder workshop (item 7 in Section2) for discussion and agreement that they should beutilised. As noted above (item 8), the planners’ sce-narios were also agreed with a representative of theregional planning teams. Such ‘agreement’ reflecteda broad consensus that the scenarios were ‘goodenough for the job’, rather than in most cases a pro-active engagement and confirmation (a point towhich we will return).

82

Indicator Spatial resolution Use in REGIS

Spatial indicators∆ urban areas (%) As fine as possible To estimate area available for agriculture

and as habitats. Sub-indicators are popu-lation, number of households, and densityof development

∆ total agricultural area (%) As fine as possible To define the limits of the farm model runs

∆ non-agricultural area, e.g. woodland, As fine as possible To estimate potential habitatsamenity (%)

∆ agri-environment areas, e.g. NVZ, NSA, As fine as possible To modify the farm model management ESA (%) inputs

Non-spatial indicators

∆ crop prices (%) (all major crops) UK Input to farm model

∆ crop yields (%) (all major crops) UK Input to farm model

∆ price of chemical inputs (%) UK Input to farm model + water model

∆ land cultivated organically UK Input to farm model

∆ set-aside (%) UK Input to farm model

∆ subsidy (%) (all major crops + livestock) UK Input to farm model

Table 3. Summary of scenario indicators which required quantification. Source: Mark Rounsevell, University of Louvain. NVZ:Nitrate Vulnerable Zone; NSA: Nitrate Sensitive Area; ESA: Environmentally Sensitive Area

Shakley & Deanwood: Constructing social futures for climate-change impacts

3.2. Changes in population and number ofhouseholds

Under RE there is an expansion of already attractivesuburban areas (principally to the south of Manchester inthe case of the North West and around Cambridge, Nor-wich and Peterborough in the case of East Anglia) alongwith the development of new and expanded towns and

villages as satellites to these attractive areas. Economicgrowth under RE is pursued through capitalising on as-sets such as Manchester airport in the North West andnodes of high-tech industrial growth in East Anglia. Newdevelopment is spread out across both regions under RE,unlike the more spatially concentrated growth and de-cline associated with GM (not shown here). GS presentsa much less extreme development pattern with lower

83

Fig. 3. Current urbanisation patterns (a) in the North West and East Anglia and in more detail for (b) current conditions, (c) theNorth West planners’ 2020, (d) RE and (e) GS scenarios in the North West. Shading: percentage of the grid square occupied by

built-up land

a)

d) e)

b) c)

Clim Res 24: 71–90, 2003

growth, concentrated more around ex-isting population centres. However, rel-atively limited development of free-standing settlements which help to takepressure away from suburban growth isstill a feature of scenarios for both theNorth West and (more so) East Angliaunder GS. This is consistent with our in-terpretation of GS as both requiring,and more accepting of, developmentoutside of existing built-up areas thanthe RS scenario, provided that nation-ally significant assets are not threat-ened. The population and householdnumbers for RE and GS are shown inTable 4.

The population numbers were obtained for GS byapplying the notion of stabilization at today’s levels(which is consistent with long-term stabilisation of theglobal population having allowed for current demo-graphic trends). For RE, we assumed that economicgrowth creates a net influx of people into the NorthWest and East Anglia as the need for new employeesgrows, and as more people choose to retire in theregion. The percentage increase in population in theNorth West is smaller than for East Anglia, however,because of: (1) a lower economic growth rate in the for-mer than in the latter; and (2) the existing population inthe former is likely to be able to provide sufficientfuture workers for the North West region (due to analready high unemployment rate and the occurrenceof declining sectors which will over time release part ofthe workforce for retraining).

The current trend in household numbers was extrap-olated forward to 2050, using the government’s owndata and projections up to 2020. Deviation from thistrend was then conducted as illustrated in Fig. 4. Inpractice, the number of new households was decidedby using an iterative method in which the trendtowards a lower number of occupants per householdwas extrapolated and deviation from this trend wasexecuted for the RE and GS scenario. Under GS, thereis a reasonably strong focus on community and family,and the average number of persons per household con-sequently stabilises at current values (2.4 personshousehold–1). (We actually increased the number ofpersons per household under RS, reflecting an evenstronger focus on community than under GS). UnderRE there is a strong acceleration of the current trendtowards single-occupancy with an average of 1.5 per-sons household–1. This is a consequence of greateraffluence and more individually oriented lifestyles.

Dividing the population by the number of personsper household for each scenario and region provides uswith the number of households. We have checkedthat the number of new proposed dwellings is consis-tent with the spatial area developed under each sce-nario in the 5 × 5 km grid squares. In order to do this,we have had to make an assumption about the densityat which development occurs. We have assumed thatunder RE the density of development (number ofhouseholds per hectare) is lower than under GS, sinceRE implies higher levels of affluence and stronger mar-ket values. In such a scenario, people are more likely tochoose to live in larger plots, with larger houses andgardens than under GS, where the need for moredense habitation will be accepted on environmentaland socio-economic cost grounds. The assumptions wehave made about density of development are as fol-lows:• That there will be a mix of development densities in

both RE and GS within the current developmentdensity range of 15 to 50 dwellings hectare–1.

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Scenario East Anglia North West

Baseline: population (millions) 2.12 6.89 GS: population 2.12 6.70RE: population 2.50 7.20Baseline: persons per household 2.40 2.40GS: persons per household 2.40 2.40RE: persons per household 1.70 1.70Baseline: households 0.90 2.70GS: households 0.90 2.80RE: households 1.47 (63% increase) 4.24 (57% increase)

Table 4. Changes in population and households under RE and GS by 2050. Source of baseline figures: GOEE (2000), NWRA (2000), ONS (2001)

Fig. 4. Planners’ projections of household growth in both regions to 2020 (solid line) and scenario-based projections

to 2050

Shakley & Deanwood: Constructing social futures for climate-change impacts

• For RE, it is assumed that there will be greater devel-opment of suburban and outlying areas, which willbe of a lower density (25 dwellings hectare–1).

• For GS, conversely, it is assumed that there will behigher rates of development within the current enve-lope of the built-up area, with attendant higher den-sities (35 dwellings hectare–1).

3.3. Biodiversity

The patterns of change in biodiversity designationsare rather more complex, given that those areas of par-

ticular merit are already likely to have attracted pro-tected status, often being the remnants of once farmore extensive habitats (Fig. 5). Re-creation of suchareas is likely to be extremely difficult for ecologicaland landscape reasons, but there are notable opportu-nities in respect of coastal wetland habitats and theEast Anglian Fens. Under GS it is envisaged thatextensive areas of farmland would be deliberately letback to the influence of tidal flooding as part of habitatre-creation; under RE this would happen to a muchlesser extent, and where it does it would be for reasonssuch as the development of eco-tourism enterprises(see Fig. 5).

85

Fig. 5. Current biodiversity patterns (a) in the North West and East Anglia and in more detail for East Anglia (b) under currentconditions and using (c) RE and (d) GS scenarios. Shading: percentage of the grid square occupied by a designated bio-

diversity site

a)

b)

c) d)

Clim Res 24: 71–90, 2003

3.4. Coastal development

New coastal development under RE will be pro-tected by the construction of new defences built to1990 standards and will not include the present yearlyincrement to account for climate-change induced sea-level rise. An increase of 2 mm yr–1 is permitted fornew East Anglian defences (as at present) to takeaccount of land subsidence. It is assumed that existingdefences will be replaced if necessary by 2050 andmaintained at the standard specified in 1990. Theredid not seem to be any good reason why the level offlood defence would increase or decrease from presentunder RE. The 5 × 5 km grid squares were too coarse toallow for the influence of private-sector led coastalflood defences (as in the qualitative scenario) to beincluded in the mapped scenario. Under GS, there is afull implementation of the official Shoreline Manage-ment Plans (SMPs) for both regions by 2050, reflectingthe adoption of modest thinking on sustainable coast-lines (as opposed to the more radical approach antici-pated under RS). The SMPs imply selected managedretreat and the levels of protection can be quantifiedspatially from the documentation of the Plans.

3.5. Non-spatial scenario variables for agriculture

The general change in crop and produce prices,yields and costs of chemical inputs are as shown inTable 5 (the actual percentage changes from the cur-rent baseline for each crop and form of produce for2020 and 2050 can be found in the full REGIS reportat www.ukcip.org.uk/integ_assess/integ_assess.html).As a general principle, a range of values greater andless than current values have been selected, sinceallowing for change in both directions is (1) quite cred-ible given future potential technical, socio-economicand policy changes and (2) more robust than assumingthat future change is unidirectional.

Under GM and RE, crop prices will decrease, therationale being that a fully functioning (global) marketshould reduce inefficiencies in production, increaseyields and hence force down prices. Paul Waggonerhas used a simple model to suggest that crop priceswill fall by 0.5% yr–1 to 2050 which apparently matches

the 1900–1984 fall of world prices for main agriculturalproducts (Waggoner 2000, pers. comm.). Under, RS wesee an increase in prices as environmental policieskick-in (reduction in chemical inputs etc.) and as amore regional focus reduces access to global state-of-the-art technology and practices. Subsidy levels arereduced but are not removed altogether in order tosupport regional producers. The RS prices are higherthan for GS, because the latter takes a wider-scale per-spective, which results in fewer and less onerous envi-ronmental policies in East Anglia and the North Westrelative to those in place in RS.

As for crop yields, innovation is high under GM asglobal biotechnology develops quickly, leading to thehighest increases in yield (which helps to explainlower prices despite increases in demand from anexpanding, more affluent population). Under RE thereis also promotion of innovation, though less access tothe best global technologies and practices, leading tosomewhat smaller yield increases than under GM. GSsees a modest increase in yields to 2020s, as R&Dalready underway bears fruit—though not so much asin GM because much of that R&D underway over thenext decade or so is regarded as promoting less-sustainable forms of agriculture. However, by 2050s,the pace of innovation has speeded up, as the R&Dfunded globally comes to reflect the promotion of sus-tainable development—crop yields correspondinglygo up. This could include ‘sustainable’ uses of biotech-nology and GMO (genetically modified organisms), forexample, and major innovation in organic cultivation.Finally, under RS, yields remain pretty much what theyare today as a result of stricter environmental policiesand limited resources available for R&D on sustainableagriculture. Sustainability under RS is defined in termsof lower yields in any case, so none of this is regardedas a problem but as part of the solution.

Yields were calculated for each crop individually.This is necessary because agricultural land use asdetermined by the IMPEL land-use model (Rounsevell1999) employed is very sensitive to yield changes ifthere are differences between crops. There may bevery little land-use change observed under climate-change scenarios if the same percentage yield changeis imposed on all crops because the model works bycomparing the gross margins between crops. The

86

Change variable GM RE GS RS

Crop prices relative to current baseline Lower Slightly lower Slightly higher Higher Crop yields relative to current baseline Much higher Higher Slightly higher Slightly lower Costs of chemical inputs relative to current baseline Slightly lower Slighly higher Higher Much higher

Table 5. General approach towards quantification of agricultural variables

Shakley & Deanwood: Constructing social futures for climate-change impacts

method for obtaining changes in yields (followingadvice from Paul Waggoner 2000, pers. comm.) was asfollows: • Establish the trend in crop yield using the longest

data set of yield for a given crop in the UK (over100 yr for wheat, 30 yr for most other crops) (usingNix 1970–1999).

• Extrapolate the best-fit line into the future.• Deviate from the best-fit line according to the think-

ing above. Some examples of the historic change in yields and

the deviations from the best-fit line are illustrated inFigs. 6 & 7. The size of the changes in yield are slightlyconservative relative to the judgement of a number ofexperts (e.g. Dyson 1996, Waggoner 1997). More pes-simistic viewpoints, e.g. those of Brown & Kane (1994),who suggest that yields may only increase by approxi-mately 10% over the next 50 yr, are reflected in RS.

Under GM, competition, consolidation and econ-omies of scale push down the prices of fertilisers, nitro-gen and phosphorus inputs. Under RE prices risebecause of the lack of global economies of productionand/or the need to purchase these specialised productsfrom other regions which can charge a premium.Prices go up even more under GS and RS as a result ofenvironmental taxation of pesticides and other chemi-cal inputs. The prices are relatively higher for RS thanfor GS because global production (and associatedeconomies of scale) can still occur in the latter; also alarger number of local habitats are more protectedunder RS than under GS.

4. DISCUSSION

We now return to the 2 questions we put forward inthe introduction, tackling them in reverse order. • How can we quantify SESs which are derived from a

qualitative development of different storylines andwhat problems are implied by a quantification?

With a carefully articulated qualitative interpretationof the scenarios, it was possible to proceed to a plausi-ble and reasonably internally consistent quantificationfor some, if not all, variables required in the integratedassessment. This task was facilitated by having 4 con-trasting scenarios to consider, which allowed charac-terisation and subsequent quantification by a compar-ative approach. There was some reluctance amongstthe stakeholder sample to proceed with quantificationof the qualitative scenarios. This related to the highlyjudgemental and potentially arbitrary character ofquantification, as illuminated above for levels of newdevelopment and biodiversity. Each of the individualqualitative scenarios can entertain a fairly wide rangeof development patterns because of the latitude for dif-

ferent interpretations of what each scenario implies.However, when a particular quantified developmenttrajectory is selected, as above, the precise interpreta-tion of the scenario is further narrowed down. Quan-tification is also in danger of implying some greaterdegree of realism and accuracy to stakeholders thancan possibly exist, i.e. if it is (incorrectly) perceived asbeing the output of some theoretically derived andempirically confirmed model, rather than the productof informed guesses, iteration and consultation. It is forreasons such as these that many stakeholders and pol-icy makers who surveyed the scenarios before theywere used accepted that quantified scenario descrip-tions were necessary for the integrated assessment butdid not appear to be entirely content with the precisedetails of the scenarios.

A third problem arises where process-based modelsrequire scenario inputs to which they are highly sensi-tive. These inputs may sometimes be interactive, as isthe case with crop yield and price, but the scenarioapproach does not provide a method for ensuring con-sistency between these variables. Quantified scenariosare in danger of driving a sophisticated model, whichrequires precise and internally consistent inputs, withcrude and inconsistent values. This problem arose with

87

Fig. 6. Historical trend in wheat yields in the UK and scenar-ios projections (tonnes ha–1) 1885–1999. Source of trend data:

MAFF (www.maff.gov.uk/esg/datasets/datasets.htm)

Fig. 7. Historical trend in barley yields in the UK and scenar-ios projections (tonnes ha–1) 1948–1999. Source of trend data:

MAFF (www.maff.gov.uk/esg/datasets/datasets.htm)

Clim Res 24: 71–90, 2003

the IMPEL model (Rounsevell 1999), which does notinclude a feedback between crop yield and price. Wetherefore had to ‘improvise’ a feedback within eachscenario by calculating the gross margins for scenariocombinations of yield and price for each crop, and thenchecking that the value was within the range of histor-ical variability of the gross margin for that crop in thatregion (using Nix [1970–1999], University of Manches-ter Farm Business Unit [1986–1998] and Murphy[1998]). If the change in the gross margins is outside ofthe envelope provided by the historical data set, thenthe crop prices were adjusted to bring the gross mar-gins back within the historical range. (Note that thisdoes not limit the effects of climate change upon thegross margins in the integrated assessment.) This is avery crude approximation of a complex economic feed-back and implicitly makes questionable assumptions,e.g. about the effects of climate change in other partsof the world upon crop yields and prices. In such cases,it may be more appropriate to replace scenario inputswith model-based inputs (where such models areavailable) which generate the values of the variablesby a (more or less adequate) representation of a pro-cess (e.g. Parry et al. 1998, Parry & Livermore 1999,Strzepek et al. 2001, Yohe et al. 2002). This assumes,however, that such numerical models can representcomplex socio-economic processes in the long term.Expert opinion is sharply contrasting on the long-termperformance of socio-economic models (Ascher 1981,IAPA 1998, Rayner & Malone 1998). • How can stakeholder communities be included in

the scenario-building process in a way that encour-ages maximal engagement of the stakeholders withthe outputs of research and analysis?

Our experience suggests that direct stakeholderinvolvement in scenario construction is an importantmechanism for engagement with research. Somecare has to be taken in identifying who is thestakeholder client, since some regional stakeholdersare more locally oriented and others more nationallyoriented. A representative of upland sheep farmers inCumbria (say) is likely to have a very different takeon scenario development than a regional Environ-ment Agency official. Our SES development wasinformed more by the regionally to nationally orientedstakeholders, who were interested in a cross-sectoralregional assessment, than by the more local andsectorally based concerns. A more bottom-up methodof scenario construction, in which the axes of changeare themselves elicited through on-the-ground stake-holder dialogue, is likely to be most effective whenmore local and more sectorally oriented analyses arerequired.

Most of our stakeholder sample were not familiarwith scenario planning approaches, but after an initial

period of discussion, most of them accepted the legiti-macy of the approach (receiving reassurance from theuse of similar scenario approaches by the UK govern-ment, the water industry, the IPCC and major busi-nesses such as Royal Dutch Petroleum/Shell). Thepotential of scenarios was most evident at a rathergeneral level of ‘opening minds’ and allowing individ-uals in various organisations to engage in a wider-ranging analysis and debate than is conventionallyachieved within policy. More specifically, scenariosoperated as effective ‘mediating’ devices or ‘boundaryobjects’ (Star & Griesemer 1989) between intellectualdebate and policy deliberations, especially where mul-tiple stakeholders with divergent perspectives areengaged. This is because scenarios were able to ac-commodate the politico-institutional pressure for con-straining uncertainty within limits and the epistemo-logical recognition of uncertainty. The diverse policyactors we worked with were prepared to compromiseto some extent on the detail of their preferred futureoption by agreeing to the use of the SESs in the assess-ment. We speculate that this was because they wishedto contribute to, and have influence on, the project as awhole. Hence, whilst each policy actor might prefer todraw up their own future scenario, they may agree toconsideration of a smallish number of sufficiently dis-tinct scenarios as the price for moving policy beyondtraditional predict and forecasting methods and havingmore influence in policy development.

When it comes to more detailed and specific policydeliberation and formulation, the problems of uncer-tainty and complexity are not avoided by using sce-narios; they are instead highlighted by the widerange of values and outcomes illustrated. Decision-makers frequently have to take some decision atsome point in time, and the pressure to limit uncer-tainty becomes pronounced at these decision nodes(Schon 1982, Ezrahi 1990, Jasanoff 1990). (Wheredecision-makers wish to put off a decision on how torespond to climate change, then the uncertainty ofscenarios may be emphasised, and this has been wit-nessed in the way that water companies have usedclimate-change scenarios [Shackley et al. 2001].) Theperceived need for greater certainty may helpexplain the pressure for a ‘dynamics as usual’ sce-nario (our ‘planners’ scenario’) to be reintroduced intothe scenario mix that we initially presented to thestakeholders, i.e. this scenario was perhaps perceivedby a number of stakeholders as being ‘more credible’than the other 4, at least up to 2020. One of ourstakeholders also proposed taking the 2 scenariocases we examined, which constituted a ‘worse’ and a‘better’ case, adding up the outcomes for specificvariables of interest and dividing by 2, the assump-tion being that the average would be a more realistic

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indication of what will actually happen! This isanother strategy by which to attempt to reintroducegreater certainty within the scenarios framework.These manoeuvres may be criticised from a ‘purist’notion of scenarios and their application, which main-tains that ‘dynamics as usual’ ceases to be meaning-ful in the medium to long term. Yet, such criticismfails in our view to appreciate the need to accommo-date the needs of stakeholders and policy-makers forat least 1 shorter-term scenario, which incorporatessignificant elements of already planned-for social andeconomic change. In addition, provision of ‘ideal-type’ scenarios, as provided for by the UKCIP SESframework, does not allow for an aggregated or com-bined scenario incorporating aspects of those differ-ent ideal types, e.g. elements of global markets com-bined with elements of regional development, globaland regional sustainability. The request for moreaggregate scenarios is not only theoretically robust(Shackley & Gough unpubl.), but also more likelyto engage practitioners who deal with contradictoryrationalities in their everyday work. The rathersingle-minded futures envisaged in the UKCIP SESsare, arguably, insufficiently flexible to permit theiruse as ‘boundary objects’. Quantification of aggregatescenarios would be more difficult, however, since theclear unidirectional change indicated by an ideal-type would be sullied. Nor do aggregate scenariossignificantly limit the challenge of decision-makingunder uncertainty, since they should still represent awide range of future potential changes.

The capacity of stakeholders to contribute to thedevelopment, characterisation and use of scenariosdepends upon their own past experience of using sce-narios and their back-up resources (time and person-nel). To move beyond the fairly straightforwardapproach to stakeholder engagement adopted here,whereby a smallish number of story lines are used toconstruct reasonably accessible and transparent sce-narios which are presented to, and commented uponby, the stakeholders in a number of stages, wouldprobably require a significantly greater allocation ofresources both on the part of the stakeholders and theresearch team. With more resources, it would be feasi-ble for stakeholders representing an appropriate rangeof different socio-cultural perspectives to develop sce-narios and to take ‘ownership’ of them (rather thananalysts applying a top-down framework). A more vig-orous defence (and reluctance to dilute the essence) ofdifferent scenarios may well then result. The outcomewould no doubt be less tidy than using a single frame-work, but the dialogue between competing scenarioswould perhaps be more influential in helping policymaking become more robust to uncertainty and com-plexity.

Acknowledgements. We acknowledge funding from the UKgovernment (MAFF and DETR, now both DEFRA) and UKWater. Special thanks go to Diana Wilkins, other members ofthe REGIS steering committee, all other members of the‘REGIS’ project team, Paul Waggoner of the ConnecticutAgricultural Experiment Station and the stakeholders whoconsented to be interviewed or who attended workshops, inparticular Margaret Gough (SCEALA), Ian Ling (NWRA),Peter Fox and Paul Stainer (Environment Agency). RobertNicholls (University of Middlesex), Mark Rounsevell (Univer-sity of Louvain), Eric Audsley and Janet Annetts (SilsoeResearch Institute), deserve special thanks.

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Editorial responsibility: Hans von Storch,Geesthacht, Germany

Submitted: August 25, 2002; Accepted: January 13, 2002Proofs received from author(s): April 3, 2003