205Book reviews / Futures 32 (2000) 203–207

E. SternbergSchool of Architecture & Planning, State University of New York at Buffalo

Hayes Hall, Buffalo, NY 14214, USAE-mail address:ezs@ap.buffalo.edu

0016-3287/00/$ - see front matter 2000 Elsevier Science Ltd. All rights reserved.PII: S0016-3287(99)00076-2

Exploring Environmental Change Using an Integrative Methodby M. Lemon, Gordon and Breach, Amsterdam, 1998, 253 pages, £56, US$90

This interesting and important book is the third in a series exploring ‘Environmen-tal Problems and Social Dynamics’ which has been produced by authors associatedwith the International Ecotechnology Research Centre at Cranfield University. In thework of this centre, ‘a consistent and central theme... lies in the importance of non-linear dynamics and complex systems thinking for understanding and managingchange and in particular the role of knowledge transfer in the process.’ (pvii) Thisparticular study is based on a research project investigating natural resource degra-dation through salination of the aquifer in the Argolid Valley in Greece. The ideaof integrative method was central to the project. At the simplest level this meansthat the actual research programme included qualitative social investigation, socialsurveys, the use of economic data, and biophysical measurement. However, there ismore to the idea of the integrative method than the use of a range of approaches.In the concluding chapter Lemon and Oxley assert the desirability of:

an integrative paradigm through the facilitation of an effective cross disciplinarydialogue. Integrative research, therefore, requires that representatives of singledisciplines retain their distinctive and consistent frames of reference while estab-lishing an effective framework for communicating with each other. (p. 231)

Taken alone, this is not much more than a rather timid argument for the desirabilityof multi-disciplinary practice, and one which is really contradictory to the assertionof the significance of complex systems which is made in the text’s preface and tothe proposal for moving beyond multi-disciplinarity made in Chapter One. However,integrative research is not simply a matter of multidisciplinarity. As the term isunderstood here, it involves an engagement with local populations, not as passivesources of relevant data, but as significant social actors and stakeholders whoseagendas and decision spaces must be understood if the nature of possible changes(the plural is very important) is to be identified and if the findings of research areto be accepted by those directly involved.

The book includes a series of substantively interesting chapters dealing with the

206 Book reviews / Futures 32 (2000) 203–207

complex interaction of agricultural, social, economic and hydrological processes inthe study’s locus. However, it is plainly intended primarily as a demonstration ofperspective and method. A constant theme in the text is that the end result of thiswork can only be ‘exploration as opposed to prediction’. This is identified as theapproach of ‘policy relevant research’ in that it investigates complex situations inorder to identify the options for policy formulation given the potential for a rangeof possible futures and the need to consider, in the context of a general commitmentto sustainability, of appropriate adaptive responses. Policy relevant research is dis-tinguished from simple policy research concerned with the evaluation of policies andthe identification of appropriate policy forms. The latter is top down, linear, andconcerned with the prediction of end states given specific policy interventions. Policyrelevant research is bottom up, working from the disaggregate to the aggregate, anddirected towards the facilitation of adaptability rather than the achievement of a givenend state.

Fundamental to this project is the development of models with the term modelunderstood as ‘a representation of the real world that is capable of generating ques-tions about possible futures rather than providing solutions’ (pvii). Chapters Ten toThirteen of the book deal with the problems of modelling and attempt to generatemodels of this kind. The authors are frank about the difficulties involved, and inparticular about the problems associated with trying to incorporate cultural processesand value systems into mathematically formalised dynamics. They recognise thatmathematical models are seldom (if ever) interactive, tending instead to focus uponone class of phenomena seeing others as just boundary conditions. However, despitethis, the project is essentially one of the construction of mathematically formaliseddynamics as equations and the use of these to generate pictorial representations ofpossible future states.

I agree with much of these authors’ project. They are absolutely right to understandthe world in complex terms and to attempt a multi-method approach to its empiricalinvestigation. However, I don’t think they are going far enough, and in one importantrespect are in serious danger of taking a dangerously wrong turn. That wrong turnis their tentative postmodernist gesture—at several points they seem to be arguingfor the validity of multiple incommensurate perspectives on reality, although in prac-tice the whole approach of the ‘integrative’ method contradicts this position. Inreality the integrative method is firmly part of the modernist project, but one whichasserts the complex character of real world systems and the need to understand theinter-relationships among them. Here, I think the authors would profit from address-ing the arguments for a synthesis of complexity as a scientific ontology and criticalrealism as a philosophical ontology as, for example, advanced by Reed and Har-vey [1,3].

More seriously, and in a spirit of genuine puzzlement, I wonder about the turn tomodels expressed as equations. The book includes an excellent discussion of ‘whatis a model and why do we use them?’ but despite the sophistication and opennessof that section, the equation is still privileged in practice as the appropriate formtowards which modelling strives. This contradiction is characteristic of the work ofthe Cranfield group as a whole. There is an explicit rejection of resort to ‘meta

207Book reviews / Futures 32 (2000) 203–207

methods’ which sits oddly with the arguments of Prigogine, foundational to the Cran-field’s group’s intellectual history. Again, I think a turn to Harvey and Reed (1994)[2] would help, here in terms of their development of Prigogine’s idea of nestedcomplex systems. The meta level is the general character of complex far from equil-ibric systems. The nested conception, which is not an argument for hierarchy, seemsparticularly well suited as at least an analogy for the inter-relationships among naturaland social which were the concern of the project described here. Given the absolutelyappropriate significance which these authors attach to the integration of qualitativematerial in any model, I wonder about the potential of the modelling capacities ofcomputer based qualitative packages, better understood as tools for exploration thananalysis. Cilliers’ important point that technology has taken us beyond theory kicksin here [4]. I am intrigued by the tools for modelling which are part of packageslike NVIVO [5].

Finally, I want to argue against the dismissal of ‘end states’. By all means dismissthe linear predictive approach to the description of end states but there is a developingliterature in urban planning, especially in the journalPlanning and Design(Environment and Planning B)which is using the complexity frame of reference andmodelling procedures, including neural networks and other simulation techniques, inthe exploration of the range of possible end states and of the processes which willproduce one as opposed to another. The Cranfield group’s work has the advantageover most pieces in that tradition of working with real empirical data about the worldas it is. It would be really valuable to adopt the approach of different ‘might bes’with a genuine empirical starting point.To conclude this is a genuinely interesting and provocative book produced by oneof the most important groups working in this frame of reference who are moreoverconcerned with issues of fundamental significance for anyone who is concerned about‘futures’. I recommend it strongly.

David ByrneDepartment of Sociology and Social Policy, University of Durham

Elvet Riverside, Durham, UKReferences

[1] Reed M, Harvey DL. The new science and the old: complexity and realism in the social sciences.Journal for the Theory of Social Behaviour 1992;22:356–79.

[2] Harvey DL, Reed MH. The evolution of dissipative social systems. Journal of Social and EvolutionarySystems 1994;17(4):371–411.

[3] Reed M, Harvey DL. Social science as the study of complex systems. In: Kiel LD, Elliott E, editors.Chaos theory in the social sciences. Ann Arbor: Univ. of Michigan Press, 1996:295–324.

[4] Cilliers P. Complexity and postmodernism. London: Routledge, 1998.[5] See http://www.scolari.co.uk/ for details.

0016-3287/00/$ - see front matter 2000 Elsevier Science Ltd. All rights reserved.PII: S0016-3287(99)00077-4