MULTI - SCALE INTEGRATED ANALYSIS OF AGROECOSYSTEMS - CHAPTER 1 potx

Advances in AgroecologySeries Editor: Clive A.Edwards Agroecosystem Sustainability: Developing Practical Strategies Stephen R.Gliessman Agroforestry in Sustainable Agricultural Systems L

M U LT I - S C A L E

I N T E G R AT E D

A N A L Y S I S

O F AG R O E C O S Y S T E M S

Advances in Agroecology

Series Editor: Clive A.Edwards

Agroecosystem Sustainability: Developing Practical Strategies

Stephen R.Gliessman

Agroforestry in Sustainable Agricultural Systems

Louise E.Buck, James P.Lassoie, and Erick C.M.Fernandes

Biodiversity in Agroecosystems

Wanda Williams Collins and Calvin O.Qualset

Interactions Between Agroecosystems and Rural Communities

Cornelia Flora

Landscape Ecology in Agroecosystems Management

Lech Ryszkowski

Soil Ecology in Sustainable Agricultural Systems

Lijbert Brussaard and Ronald Ferrera-Cerrato

Soil Tillage in Agroecosystems

Adel El Titi

Structure and Function in Agroecosystem Design and Management

Masae Shiyomi and Hiroshi Koizumi

Ibaraki University, Mito, Japan

Sir Colin R.W.Spedding

Berkshire, England

Moham K.Wali

The Ohio State University, Columbus, OH

MULTI-SCALE INTEGRATEDANALYSIS

Library of Congress Cataloging-in-Publication Data

Giampietro, M (Mario)

Multi-scale integrated analysis of agroecosystems/Mario Giampietro.

p cm (Advances in agroecology)

Includes bibliographical references and index.

ISBN 0-8493-1067-9 (alk paper)

1 Agricultural ecology 2 Agricultural systems I Title II Series.

S589.7.G43 2003

This book contains information obtained from authentic and highly regarded sources Reprinted material is quoted with permission, and sources are indicated A wide variety of references are listed Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials

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Printed on acid-free paper

If a student is not eager, I won’t teach him;

If he is not struggling with the truth, I won’t reveal it to him.

If I lift up one corner and he can’t come back with the other three,

I won’t do it again.

—The Analects, Confucius

Warning to the Potential Reader of This Book

Discussing the implications of a paradigm change in science, Allen et al (2001) said: “A paradigmchange modifies protocols, vocabulary or tacit agreements not to ask certain questions” (p 480) If weagree with this brilliant definition, and therefore if we accept that a scientific paradigm is “a tacitagreement not to ask certain questions,” the next step is to find out why certain questions are forbidden

In general, the questions that cannot be asked from within a scientific paradigm are those challengingthe basic assumptions adopted in the foundations of the relative disciplinary scientific knowledge.The enforcement of this tacit agreement is a must for two reasons First, it is required to preserve thecredibility of the established set of protocols proposed by the relative disciplinary field (what thestudents learn in university classes) Second, it makes it possible for the practitioners of a disciplinaryfield to focus all their attention and efforts only on how to properly run the established set ofprotocols, while forgetting about theoretical issues and controversies In fact, the acceptance of ascientific paradigm prevents any questioning of the usefulness of the established set of protocolsdeveloped within a disciplinary field for dealing with the task faced by the analyst

When dealing with a situation of crisis of an existing scientific paradigm—and many seem to believethat in relation to the issue of sustainability of human progress we are facing one—we should expect thatsuch a tacit agreement will get us into trouble Whenever the established set of protocols (e.g., analyticaltool kits) available for making analysis within disciplinary fields is no longer useful, the number of peoplewilling to ask forbidden questions reaches a critical size that overcomes the defenses provided by academicfilters After reaching that point, criticizing the obsolete paradigm is no longer a taboo In fact, nowadays,several revolutionary statements that carry huge theoretical implications about the invalidity of the foundations

of leading scientific disciplines are freely used in the scientific debate For example, expressions like “themyth of the perpetual growth is no longer acceptable (why?),” “it is not possible to find an optimalsolution when dealing with contrasting goals defined on different dimensions and scales (why?)” and “wecannot handle uncertainty and ignorance just by using bigger and better computers (why?)” in the 1970sand 1980s have been sanguinary battlefields between opposite academic disciplines defending the purity

of their theoretical foundations These expressions are now no longer contested Actually, we can evenfind softened versions of these statements included in the presentation of innovative academic programsand in documents generated by United Nations agencies

This situation of transition, however, generates a paradox In spite of this growing deluge of unpleasantforbidden questions about the validity of the foundations of established disciplinary scientific fields,nothing is really happening to the teaching of protocols within the academic fields under pressure forchange In fact, at this point, the lock-in that is protecting obsolete academic fields no longer worksagainst posing forbidden questions Rather, it works by preventing the generation of answers to these

forbidden questions The mechanism generating this lock-in is simple and conspiracy-free Academicfilters associated with obsolescent disciplinary knowledge do their ordinary work by attacking everydeviance (those who try to find new perspectives) This applies to both those who develop nontraditionalempirical analyses (e.g., putting together data in a different way, especially when they obtain interestingresults) and those who develop nontraditional theories (e.g., putting together ideas in a nonconventionalway, especially when they obtain interesting results) The standard criticism in these cases is that “this isjust empirical work without any sound theory supporting it” or that “this is just theoretical speculationwithout any empirical work supporting it.” When innovative theories are developed to explain empiricalresults, the academic filter challenges every single assumption adopted in the new theory (even though

it is totally neglecting to challenge even the most doubtful assumptions of its own discipline) Finally,whenever the academic filter is facing the unlikely event that (1) a new coherent theory is put forward,(2) this theory can be defended step by step starting from the foundations, (3) experimental data areused to validate such a theory and (4) this theory is useful for dealing with the tasks faced by theanalysts, the unavoidable reaction is always the same: “This is not what our disciplinary field is about.Practitioners of our field would never be interested in going through all of this.”

Obviously, the analysis of this mechanism of lock-in—very effective in preventing the discussion ofpossible answers to forbidden questions—has a lot to do with the story that led to the writing of thisbook This is why I decided to begin with this preface warning potential buyers and readers This bookrepresents an honest effort to do something innovative in the field of the integrated analysis ofsustainability of agricultural systems, that is, an honest effort to answer a few of the forbidden questionsemerging in the debate about sustainability This book reflects a lot of work and traveling to visit themost interesting groups that are doing innovative things related to this subject in various disciplinaryand interdisciplinary fields I wrote this book for those who are not happy with the analytical toolsactually used to study and make models about the performance of farming systems, food systems andagroecosystems, and especially for those interested in considering various dimensions of sustainability(e.g., economic, ecological, social) simultaneously and willing to reflect in their models the nonequivalentperspectives of different agents operating at different scales

The mechanism that generated the writing of this book is also simple There is an old Chinesesaying (quoted by Röling, 1996, p 36) that puts it very plainly: “If you don’t want to arrive where youare going, you need to change direction.”

What does this mean for a scientist or practitioner changing direction? In my interpretation of theChinese saying, this means going back to the foundations of the disciplinary knowledge that has beenused to develop the analytical tools that are available and in use at the moment and trying to see whether

it is possible to do things in an alternative way When I started my journey many years ago, as a scientistwilling to deal with the sustainability of agriculture, I had to swim in a sea of complaints about theinadequacy of reductionism, the lack of holism and the need of a paradigm shift in science This ocean ofcomplaints was linked to the acknowledgment of a never-ending list of failures of the applications of theconventional approach in relation to the sustainability of agriculture in both developed and developingcountries However, in spite of all of these complaints, when looking at scientific papers dealing with thesustainability of agriculture, in the vast majority of cases I found models that were based on the same oldset of tools (e.g., statistical tests and differential equations) These models were applied to an incrediblediversity of situations, always looking for the optimization of a function assumed to represent a valid(substantive) formal definition of performance for the system under investigation

Since I was then and still am convinced that I am not smarter than the average researchers of thisfield, I was forced to realize that if I wanted to arrive in a different place, I had to change the path I was

on Otherwise, I would have joined the party of optimizers already jammed at the end of it When youtake a wrong path and want to get on another one, you must go back to the bifurcation where youmade the bad turn This is why I decided to go back to the theoretical foundations of the analyticaltools I was using, to try to see if it were possible to develop an alternative set of tools useful to analyze

in a different way the complex nature of agroecosystems Then I found out that the new field ofcomplex systems theory implied the rediscovery of old epistemological issues and new ways of addressingthe challenge implied by modeling

This book is an attempt to share with the reader what I learned during this long journey The text

is organized in thr ee parts:

Reality. After acknowledging that there is a problem with reductionism when dealing withthe sustainability of agroecosystems (in Chapter 1), the remaining four chapters provide newvocabulary, narratives and explanations for the epistemological predicament entailed bycomplexity Chapter 2 starts by looking at the roots of that predicament, focusing on theneglected distinction between the perception and representation of reality Additional conceptsrequired to develop an alternative narrative are introduced and illustrated with practicalexamples in Chapter 3 The resulting challenge for science when used for governance in theface of uncertainty and legitimate contrasting values is debated in general terms in Chapter 4.Finally, an overview of the problems associated with the development of scientific proceduresfor participatory integrated assessment is discussed in Chapter 5

This part introduces a set of innovative concepts derived from various applications of complexsystems thinking These concepts can be used to develop a tool kit useful for handling multi-scale integrated analysis of agroecosystems In particular, three key concepts are introducedand elaborated on in the three chapters making up this second part:

1 Chapter 6—Multi-scale mosaic effect

2 Chapter 7—Impredicative loop analysis

3 Chapter 8—Unavoidable necessity of developing useful narratives to surf complex time

ecosystems. This part presents a tool kit based on the combined use of the previous threeconcepts to obtain a multi-scale integrated analysis of agroecosystems This third part is organizedinto three chapters:

1 Chapter 9—Bridging disciplinary gaps across hierarchical levels

2 Chapter 10—Bridging changes in societal metabolism to the impact generated on theecological context of agriculture

3 Chapter 11—Benchmarking and tailoring multi-objective integrated analysis across levelsAfter having put the cards on the table with this outline, I can now move to the warning for potentialreaders and buyers: Who would be interested in reading such a book? Why?

This is not a book for those concerned with being politically correct, at least according to thedefinitions adopted by existing academic filters This book is weird according to any of the conventionalstandards adopted by reputable practitioners This is scientific research in agriculture that is not aimed at

producing more and better Rather, this is research aimed at learning how to define what better means for a

given group of interacting social actors within a given socioeconomic and ecological context Within thisframe, the real issue for scientists is that of looking for the most useful scientific problem structuring

It should be noted that hard scientists who use models to individuate the best solution (a solution

that produces more and better than the actual one) are operating under the bold assumption that it is always possible to have available: (1) a win-win solution, that is, that more does not imply any negative side effects and (2) a substantive formal definition of better that is agreed to by all social actors and that

can be used without contestation as an input to the optimizing models According to this boldassumption, the only problem for hard scientists is that of finding an output generated by the modelthat determines a maximum in improvement for the system

If we were not experiencing the tragic situation we are living in (malnutrition, poverty and environmentalcollapse in many developing countries associated with bad nutrition, poverty and environmental collapse

in many developed countries), this blind confidence in the validity of such a bold assumption would belaughable After having worked for more than 20 years in the field of ecological economics, sustainabledevelopment and sustainable agriculture in both developed and developing countries, I no longer,unfortunately, find the blind confidence in the validity of this bold assumption amusing

• Part 1 : Science for Governance:The Clash of Reductionism against the Complexity of

• Part 2 : Complex Systems Thinking: Daring to Violate Basic Taboos of Reductionism.

• Part 3 : Complex Systems Thinking in Action: Multi-Scale Integrated Analysis of

Agro-Sustainability, when dealing with humans, means the ability to deal in terms of action with theunavoidable existence of legitimate contrasting views about what should be considered an improvement.Winners are always coupled to losers To make things more difficult, nobody can guess all the implications

of a change If this is the case, then how can this army of optimizers know that their definition of what

is an improvement (the one they include in formal terms in their models as the function to beoptimized) is the right one? How can it be decided by an algorithm that the perspectives and values ofthe winners should be considered more relevant than the perspectives and values of the losers?Sustainability means dealing with the process of “becoming.” If we want to avoid the accusation ofworking with an oxymoron (sustainable development), we should be able to explain what in ourmodels remains the same when the system becomes something else (in a sustainable way) That is, weshould be able to individuate in our models what remains the same when different variables, differentboundaries and emerging relevant qualities will have to be considered to represent the issue ofsustainability in the future Optimizing models either maximize or minimize something within a formal(given and not changing in time) information space

When dealing with a feasible trajectory of evolution, the challenge of sustainability is related to theability to keep harmony among relevant paces of change for parts (that are becoming in time), which aremaking up a system (that is becoming in time), which is coevolving with its environment (that is becoming

in time) This requires the simultaneous perception and representation of events over a variety of time scales The various paces of becoming of parts, the system and the environment are quite differentfrom each other Can this cascade of processes of becoming and cross-relations be studied using reduciblesets of differential equations and traditional statistical tests? A lot of people working in hierarchy theoryand complex systems theory doubt it This book discusses why this is not possible

space-These fundamental questions should be taken seriously, especially by those who want to deal withsustainability in terms of hard scientific models (by searching for a local maximum of a mathematicalfunction and for significance at the 0.01 level) It is well known that when dealing with life, hard scienceoften tends to confuse formal rigor with rigor mortis In this regard, the reductionist agenda is wellknown To study living systems, we first have to kill them to prevent adjustment and changes during theprocess of measurement The rigorous way, for the moment, provides only protocols that require reducingwholes into parts and then measuring the parts to characterize the whole Is it possible to look at therelation of wholes and parts in a new way? Can we deal with chicken-egg paradoxes, when the identity

of the parts determines the identity of the whole and the identity of the whole determines the identity

of the parts? Obviously, this is possible This is how life, languages and knowledge work This bookdiscusses why and how this can be done in multi-scale integrated analysis of agroecosystems

Finally, there is another very interesting point to be made Are these forbidden questions aboutscience new questions? The obvious answer is not at all These are among the oldest and most debatedissues in human culture Humans can represent in their scientific analyses only a shared perceptionabout reality, not the actual reality Models are simplified representations of a shared perception ofreality Therefore, by definition, they are all wrong, even though they can be very useful (Box, 1979).But to take advantage of their potential usefulness—in terms of a richer understanding of the reality—

it is necessary to be aware of basic epistemological issues related to the building of models The realtragedy is that activities aimed at developing this awareness are considered not interesting or even not

“real science” by many practitioners in hard sciences On the contrary, this is an issue that is consideredvery seriously in this book From this perspective, complex systems theory has merit to have put back

on the agenda of hard scientists a set of key epistemological issues debated in disciplines such as naturalphilosophy, logic and semiotics, which, until recently, were not viewed as hard enough

It is time to reassure those potential readers who got scared by the outline and the ensuing discussion.What does all of this have to do with a multi-scale integrated analysis of agroecosystems? Well, the point

I have been trying to make so far is that it has a lot to do with multi-scale integrated analysis of agroecosystems

In the last 20 years, I have been generating a lot of numbers about the sustainability of agriculturalsystems by studying this problem from different perspectives (technical coefficients, farming systems,global biophysical constraints, ecological compatibility) and using various sets of variables (energy, money,water, demographics, sociality) In the beginning, this was done by following intuitions about how to do

things in a different way Later on, after learning about hierarchy theory, postnormal science and complexsystems theory (especially because of the gigantic contributions of Robert Rosen), I realized that it waspossible to back up these intuitions with a robust theory This made possible the organization of thevarious pieces of the mosaic into an organic whole This is what is presented in Part 2 of this book Part

2 provides new approaches for organizing data and examples of applications of multi-scale integratedanalysis of agroecosystems to real cases The results presented in Part 3, in my view, justify the length andheterogeneity of issues presented in Parts 1 and 2 In spite of this, I understand that cruising Parts 1 and 2

is not easy, especially for someone not familiar with the various issues discussed in the first eight chapters

On the other hand, this can be an occasion for those not familiar with these topics to have a generaloverview of the state of the art and reference to the literature

There is a standard predicament associated with scientific work that wants to be truly interdisciplinary.Experts of a particular scientific field will find the parts of the text dealing with their own field toosimplistic and inaccurate (an uncomfortable feeling when reading about familiar subjects), whereasthey will find the parts of the text dealing with less familiar topics obscure and too loaded with uselessand irrelevant details (an uncomfortable feeling when reading about unfamiliar subjects) This explainswhy genuine transdisciplinary work is difficult to sell As readers we are all bothered when forced tohandle different types of narratives and disciplinary knowledge Nobody can be a reputable scholar inmany fields To this end, however, I can recycle the apology written by Schrödinger (1944) about theunavoidable need of facing this predicament:

A scientist is supposed to have a complete and thorough knowledge, at first hand, of somesubjects and, therefore, is usually expected not to write on any topic of which he is not alife master This is regarded as a matter of noblesse oblige For the present purpose I beg torenounce the noblesse, if any, and to be the freed of the ensuing obligation My excuse is

as follows: We have inherited from our forefathers the keen longing for unified, all-embracingknowledge The very name given to the highest institutions of learning reminds us thatfrom antiquity to and throughout many centuries the universal aspect has been the onlyone to be given full credit But the spread, both in width and depth, of the multifariousbranches of knowledge during the last hundred odd years has confronted us with a queerdilemma We feel clearly that we are only now beginning to acquire reliable material forwelding together the sum total of all that is known into a whole; but, on the other hand,

it has become next to impossible for a single mind fully to command more than a small

specialized portion of it I can see no other escape from this dilemma (lest our true who aim

be lost for ever) than that some of us should venture to embark on a synthesis of facts andtheories, albeit with second-hand and incomplete knowledge of some of them—and atthe risk of making fools of ourselves

To make the life of the reader easier, the text of the first eight chapters has been organized into twocategories of sections:

1 General sections that introduce main concepts, new vocabulary and narratives using practicalexamples and metaphors taken from normal life situations

2 Technical sections that get into a more detailed explanation of concepts, using technicaljargon and providing references to existing literature

The sections marked “technical” can be glanced through by those readers not interested in exploringdetails In any case, the reader will always have the option to go back to the text of these sections later

In fact, when dealing with a proposal for moving to a new set of protocols, vocabulary and tacitagreements not to ask certain questions, one cannot expect to get everything in one cursory reading of

a book Actually, the goal of the first eight chapters is to familiarize the reader with new terms, newconcepts and new narratives that will be used later on to propose innovative analytical tools Thismeans that the structure of this book implies a lot of redundancy The same concepts are first introduced

in a discursive way (Part 1), reexplored using technical language (Part 2) and then adopted in thedevelopment of procedures useful to perform practical applications of multi-scale integrated analysis

of agroecosystems (Part 3) Because of this, the reader should not feel frustrated by the high density ofthe information faced when reading some of the chapters in Parts 1 and 2 for the first time

References

Allen, T.F.H., Tainter, J.A., Pires J.C and Hoekstra T.W., (2001), Dragnet ecology, “just the facts ma’am”: The

privilege of science in a post-modern world, Bioscience, 51, 475–485.

Box, G.E.P., 1979 Robustness is the strategy of scientific model building In R.L.Launer and G.N.Wilkinson (Eds.) Robustness in Statistics Academic Press, New York pp 201–236.

Röling, N., (1996), Toward an interactive agricultural science, Eur J Agric Educ Ext., 2, 35–48.

Schrödinger, E., (1944), What Is Life? based on lectures delivered under the auspices of the Dublin Institute for

Advanced Studies at Tr inity College, Dublin, February 1943, available from The Book Page:

http://home.att.net/~p.caimi/schrodinger.html

As discussed in a convincing way by Aristotle, it is not easy to individuate a single direct cause of agiven event—i.e the writing of a book—since, in the real world, several causes (material, efficient,formal and final) are always at work in parallel Because of this, it is not easy for me to start the list ofpeople to be included in the acknowledgments from one given point Crucial to the writing of thisbook was a vast array of people that is impossible to handle in a linear way Therefore, I will start such

a list from the category of efficient cause (those who were instrumental in generating the process) Thisdictates starting with two key names associated with my choice of dedicating my life to research in thisfield—David Pimentel and Gian-Tommaso Scarascia Mugnozza

In the six years spent at Cornell University with Professor Pimentel, I learned how to sense theexistence of hidden links, when considering biophysical, economic, social and ecological issues in agriculturesimultaneously I learned from him how to follow the prey (looking for hard data to prove the existence

of these links), even when this requires putting together scattered clues and going for creative investigation.The lessons I got in this field were invaluable But the most important lesson was in another dimension:the human side That is, following his example, I understood that, to do this job, one has to work hard andforget about trying to be politically correct Even when building up your career you must resist the sirens’

song of cosí fan tutte You must keep going your own way, no matter what.

Professor Scarascia Mugnozza not only pushed me into the world of agriculture, but made itpossible for me to engage in a nomadic “learning path,” stabilized now for more than a decade, byfacilitating international contacts and supporting my applications for funding

Next, I would like to acknowledge the vital input of Wageningen University In particular, I recall thedemiurgic intervention of Niels Röling, who came up (over an Italian dinner) with the idea of thewriting of such a book As we were in a restaurant, the recipe came out pretty clear: one thirdepistemology, one third complex system theory and one third examples of real applications to thesustainability of agriculture During my first seminar at Wageningen, Herman van Keulen did the rest byposing the following question: “You seem to believe that it is possible to establish a link between thevarious changes in indicators defined across different scales But how can you establish a bridge acrossnonequivalent descriptive domains?” This question has been very important to me for two reasons: (1)this was the first time in my life that I found someone who understood perfectly what I was talkingabout when discussing Multi-Scale Integrated Analysis and (2) this question made me aware that myfirm belief in the possibility of establishing a link across nonreducible indicators (something I had done

in the past just following intuition) was not at all obvious to other people Actually, when confrontedwith such a direct question in public, I was not able to offer a systemic explanation of my approach.Finally, the last key element in Wageningen was the enthusiasm for complexity shown at that time byHans Schiere My brief visit there (5 months) was to explore the possibility of using new conceptsderived from this field for improving analytical models of sustainable development At that time, I had

a few discussions with Schiere about the problem of boundary definition in modeling On one ofthose occasions I was asked: “Can you prove that it is impossible to find and use a unique “substantive”boundary definition for a given system?” When I was finally able to answer such a question in a verysimple and direct way I realized that this book was finished

The third and last item under the efficient-cause category is the input I received from University at Madison Tim Allen and Bill Bland invited me to work on the application of complexsystem thinking to the development of analytical tools related to agroecology It was during that periodthat the various pieces of the puzzle were put together into the first draft of this book

Wisconsin-Getting to the formal cause, I would like to begin the list of people who were instrumental inshaping my understanding of complexity with someone I never managed to meet: Robert Rosen In

my view, Rosen, who died in 1998, was one of the greatest scientists of the last century Hopefully, he

will get due recognition in this century In this book, I tried to build on his deep understanding of thelink between basic epistemological issues and basic principles of a theory of complex systems.Continuing with those I was lucky enough to work with, I can organize the list according to topics:

• Epistemology, Science for Governance, and Post-Normal Science—Silvio Funtowicz(who I visited at the Joint Research Center of the European Commission in Ispra in relation

to writing this book), Jerome Ravetz, Martin O’Connor and Niels Röling (who opened for

me the doors of Soft-Systems Methodology developed by Checkland) I now consider allfriends as well as mentors

• Multi-criteria Analysis, Societal Multi-criteria Evaluation applied to Ecological Economics—Joan Martinez-Alier and Giuseppe Munda (with whom I visited for 2 years atthe Universitat Autonoma de Barcelona in Spain) I learned from them many of the ideasexpressed in Chapter 5 A few paragraphs of that chapter are based on a technical reportwritten with Giuseppe in 2001

• Complex Systems Theory and Hierarchy Theory—Tim Allen (the 5 months spent withhim in Madison accelerated my brain more than if it had been placed in a Super ProtonSynchrotron), James Kay, David Waltner-Toews and Gilberto Gallopin Again, it is a honor for

me to consider all these people friends (none of us will ever forget the first meeting of the

“Dirk Gently group” of holistic investigators in 1995)

• Energy Analysis and Thermodynamics Applied to Sustainability Analysis—The listincludes Kozo Mayumi (the co-author of Chapters 6, 7 and 8), who is another fraternal friendwith whom I have been working now for a decade Together we developed the concept ofmulti-scale integrated analysis of societal metabolism In this category I have to mention againMartin O’Connor, then James Kay and Roydon Frazer, two exquisite theoreticians interpretingthe concept of rigor in the correct way (avoiding sloppiness, but at the same time daring toviolate taboos when needed) Bob Ulanowicz is another important pioneer in this field fromwhom I got the main idea of the four-angle model for the analysis across hierarchical levels ofmetabolic systems Vaclav Smil, another guru of the analysis of energy and food security,proved to be a very amiable and collaborative person The list continues with Joseph Tainter,one of the few nonhard scientists who is perfectly comfortable with handling these scientificconcepts when dealing with the sustainability of human societies Last but not least, SergioUlgiati, Bob Herendeen and Sylvie Faucheux, other friends or colleagues with whom I havebeen interacting in this field for many years now

• Multi-Scale Integrated Analysis of Agroecosystems—This 11 st begins with Tiziano Gomiero(co-author of Chapter 11), who a few years ago decided to do his Ph.D on this approach, andsince then has never stopped working on it Gianni Pastore and Li Ji were very active in 1997during the first development of the method, when processing a dataset gathered in a 4-yearproject in China I had several discussions about theory and applications with Bill Bland of theAgroecology program at the University of Madison Finally, I would like to acknowledgevarious researchers involved in a project in South-East Asia with whom I am collaboratingnow (and hopefully in the future): H.Schandl, C.Grünbühel, N.Schulz, S.Thongmanivong,B.Pathoumthong, C.Rapera and Le Trong Cuc

Moving now to the material cause: Many people helped in different ways during the actual writing,preparation and correction of the manuscript The list includes: Sandra Bukkens, Nicola Cataldi, Maurizio

Di Felice, Stefan Hellstrand, Joan Martinez-Alier, Igor Matutinovic, Alfredo Mecozzi, David Pimentel,Stefania Sette, Sigrid Stagl and Sergio Ulgiati Sylvia Wood, at CRC Press, also contributed

Finally, there is an unwritten rule about the layout of acknowledgment sections: They all finish with

a reference to family and friends This is where the final cause enters into play In this case, particularmention is really due to my wife, Sandra Bukkens, who has contributed both indirectly and directly in

a substantial way to this book Indirectly, she sustained the burden associated with the running of ourhousehold for the last 5 years, a period during which our family moved six times across four differentcountries And more directly, before this nomadic madness, she contributed by co-authoring with meseveral published papers dealing with related topics A few of these are quoted and used in this book

as sources of tables and figures

Mario Giampietro’s interdisciplinary background began as a chemical engineer His undergraduatedegree was in biological sciences and his Master’s degree in food system economics He received hisPh.D from Wageningen University

Dr Giampietro is the director of the Unit of Technological Assessment at a governmental researchInstitute in Italy (INRAN—National Institute of Research on Food and Nutrition) He was VisitingScholar (from 1987 to 1989 and from 1993 to 1994) and Visiting Professor (1995) at Cornell University;Visiting Fellow at Wageningen University (1997); Visiting Scientist at the Joint Research Center of theEuropean Commission of Ispra, Italy (1998), Visiting Professor at the Ph.D Program of EcologicalEconomics at the Universitat Autonoma Barcelona, Spain (1999 and 2000); Visiting Fellow at theUniversity of Wisconsin-Madison (2002) He is one of the organizers of the Biennial InternationalWorkshop “Advances in Energy Studies” held in Portovenere (Italy) since 1996

Dr Giampietro serves on the editorial boards of Agriculture Ecosystems and Environment (Elsevier),

Population and Environment (Kluwer), Environment, Development and Sustainability (Kluwer) and International Journal of Water (Interscience) He has published more than 100 papers and book chapters in the fields

of ecological economics, energy analysis, sustainable agriculture, population and development, andcomplex systems theory applied to the process of decision making in view of sustainability

Science for governance—The new challenge for scientists dealing with the sustainability of

agriculture in the new millennium

The development of agriculture in the 21st century is confronting academic agricultural programswith the need for handling new typologies of trade-offs and social conflicts These multiple trade-offsare associated nowadays with the concept of multifunctionality of land uses

In fact, it should be noted that this is nothing new Throughout the history of humankind theagricultural sector has always been multifunctional and at the basis of social conflicts Because of this,until a recent past (say before 1900) (1) the perception of the agricultural sector (the criteria ofperformance), (2) the representation of the agricultural sector (the attributes of performance) and (3)the regulation of agricultural activities (selection and evaluation of policies and laws based on theselected set of criteria and attributes) have always been based on the simultaneous consideration ofvarious perspectives and dimensions of analysis In modern jargon we can say that in the past (e.g., inpreindustrial times) the development of agriculture was always driven by policies that were selectedand evaluated considering both long-term and short-term effects in relation to different dimensions

of analysis (political, social, economic, ecological) Land was perceived as a source of food for survival,

as well as a required asset to sustain soldiers Depending on the location, land was also seen as crucial tocontrolling trade In addition to that, land always had a sacred dimension to anchor cultural values(people tend to associate their cultural identity with familiar landscapes, their homeland) Finally, inrelation to the ecological dimension, land was often confused with nature and therefore considered asthe given context within which humans have to play their part in the larger process of life

If this is true, how is it that academic agricultural programs perceive the concept of multifunctionalland use and the relative need of addressing multiple trade-offs and dimensions to be new? To answerthis question, it is important to realize the deep transformations that the period of colonies first and themassive process of industrialization later induced in the metabolism of social systems in Europe and inother developed countries In these privileged spots, economic growth could dramatically expand,escaping, at least in the short term, local biophysical constraints This special situation was able tochange in a few decades the codified perception about the role of the agricultural sector Fossilenergy-based inputs and imports were used to offset bottlenecks in the natural supply of productioninputs In this situation, the choice of considering (perceiving, representing and regulating) agriculture

as just a set of economic activities aimed at producing goods and profit—while neglecting otherdimensions—was very rewarding

This change in the perception of agriculture in Western academic programs in the past decades wasassociated with a rapid economic growth in developed countries and a rapid demographic growth indeveloping countries During this rapid transition, those operating in the developed world learned thatintroducing major simplifications in the codified way of perceiving, representing and regulating agriculturecould generate comparative advantages for their economies, at least in the short term That is, byignoring the constraints imposed by the old set of cultural values (e.g., the sacredness of land) and byignoring ecological aspects (e.g., the necessity to maintain human exploitation within the limits required

by eco-compatibility), farmers and those investing in farming could take out much more food fromthe same unit of land and at the same time could increase their operative profits In this way, developedsocieties were able to support more “soldiers” per unit of land It should be noted, however, that afterthe industrial revolution the social role of preindustrial soldiers was replaced by nonagricultural workers.That is, the fraction of the workforce invested in operating machines was able to achieve an economicreturn per hour of labor much higher than that generated by farmers To make things tougher foragriculture, the large variety of economic activities expressed by industrial societies implied that thevery same land could be invested in alternative and more profitable uses Modern economic sectors

(both in production and in consumption) are competing with old-style agricultural practices for theuse of the available endowment of human activity and land In this situation, workers invested in justproducing food or land invested in just keeping low the ecological stress associated with food production(e.g., fallow) involves a high opportunity cost in developed countries In other words, old-style agriculturalpractices were the losers in the definition of priorities when deciding the new development strategiesfor modern economies As a consequence, for more than five decades now, technical progress inagriculture has been driven by two simple goals:

1 Maximizing biophysical productivity: reducing the number of human workers and the amount

of space required to produce food, so that these valuable resources can become available toother economic activities that give higher returns

2 Maximizing economic performance: the high opportunity cost of capital in developed countriesrequires reaching levels of return on investment comparable with those achieved in othersectors

These two goals, when combined, tend to generate a mission-impossible syndrome In fact, the goal ofmaximizing the biophysical productivity in terms of higher throughput per hectare and per workertranslates into the need for massive investments of capital per worker On the other hand, a largedifference in the opportunity cost of production factors such as land and labor—required in largequantities in the agricultural sector compared with other economic sectors—translates into lowcompetitiveness of developed farmers on the international market (in relation to farmers operating indeveloping countries) In developed countries with enough land (e.g., the United States or Canada),the second goal was still achievable, at least before the third millennium On the contrary, in otherdeveloped countries with high population densities (e.g., European countries or Japan), the secondgoal soon became impossible without subsidies As soon as the downhill slope of subsidies was taken,the definition of the goal of maximizing economic performance changed dramatically

At that point, the goal of maximizing economic performance in developed and crowded countriesbecame that of reducing the fraction of total available economic capital that must be invested in theagricultural sector In developed countries, the capital has a high economic opportunity cost This impliesthat the agricultural sector with a high requirement of capital per worker and a low economic return oninvestments is forced to continuously compress the number of workers to handle this double task Thesolution to this dilemma can be obtained by (1) increasing the ratio of capital per worker to capital perunit of land, while at the same time (2) reducing both the number of workers and the land in production.Obviously, the pace of reduction of the number of workers and the area of land in production has to befaster than the pace of growth of the required amount of capital per worker and per unit of land.After having taken such a suicidal path for the sustainability of agriculture, many in developedcountries were forced to recognize the original capital sin The effects of the drastic simplificationsadopted to perceive, represent and regulate agriculture, seen simply as another economic sector that isjust producing commodities, became crystal clear (at least to those willing to see it) The decision toadopt a mechanism of monitoring and control based mainly on money (e.g., the implementation ofagricultural policies in the 1960s and 1970s based mainly on economic analysis) was reflecting such ahidden simplification Basing the evaluation of policies mainly on economic terms resulted in missingfor decades a lot of relevant information referring to additional dimensions of agriculture Theseneglected dimensions (e.g., ecology—health of ecosystems and cultural and social dimension—health

of communities) are now slashing back on those in charge of determining agricultural policies Evenworse is the situation of developing countries where the societal context of agriculture is completelydifferent from that of the developed world In these countries there is less capital available for agriculturalactivities in the face of a growing demand for services and investments in the development of othereconomic activities Moreover, the meager capital left to agriculture has to be used to deal with adramatic reduction of land per capita Obviously, in this situation, the challenge of developing newtechnologies and new policies for agricultural development is becoming harder and harder to tackle.Because the context of agriculture in developing countries is totally different from that in developedcountries, we should expect that the idea of transferring either technologies that were generated in

developed countries (e.g., hightech genetically modified organisms (GMOs)) or policy tools (e.g., fullmarket regulation) to developing countries to tackle their problems is, in general, a recipe for failure.The scale of the global transformation implied by the oil civilization has now reached a point atwhich a simplified perception of agriculture that involves ignoring important dimensions of sustainabilitycan no longer be held without facing important negative consequences The perception that humans

have passed this critical threshold is indicated by the widespread use of the buzzword globalization to

indicate that something new is happening As observed by Waltner-Toews and Lang (2001), the scale ofhuman activity on this planet has reached a point that no longer leaves room for externalizations(shortcuts providing temporary comparative advantage to those deciding to use them) to the global

economy In terms of pollution, the term globalization means that “what goes around comes around.” In terms of international development, the term globalization means that increasing someone’s profit because

of favorable terms of trade implies impoverishing someone else That someone else, sooner or later, willrequire assistance Ignoring negative side effects on the environment in the long term (the key to thedramatic success of Western science and technology in the last century) no longer pays The environment

will sooner or later present the bill, and it will be a very high one Put another way, the term globalization

means acknowledging that sooner or later (the sooner the better) we will have to go back to theancient practice of integrating the goal of economic growth with a set of additional goals such asequity, environmental compatibility and respect for diversity of cultures and values This will requirelooking for wise solutions, rather than for optimal solutions

This new situation, which is challenging the conventional ideological paradigms of perpetual growth,

is generating an additional dose of stress for human societies Social systems are facing a continuous need

of fast adjustments of their established rules and “truths.” Human societies all over the planet are forced tolearn how to make tough calls to find the right compromise between too much and too little technicalprogress This is the back door through which the concept of multifunctionality of agriculture wasrediscovered by the high-tech society Within the army of scientists fully dedicated to maximizing andoptimizizing, those who are meditating on the various dilemmas associated with the issue of sustainabilityare discovering that many additional goals have to be considered when dealing with the sustainability ofhuman development That is, the two goals of economic growth and technical progress have to beconsidered as members of a larger family of goals that include respect for ecological processes, moreequity for the present generation, respect for the rights of future generations and protection of culturaldiversity to arrive at deeper and more basic procedural issues such as learning how to define quality of lifewhen operating in a multi-cultural setting In spite of the fact that these goals are becoming more andmore important in the choice of sound policies for agricultural development, the scientific capability ofsupplying useful representations and structuring of these sustainability dilemmas is far behind the demand.Niels Röling (2001) characterizes the need of a total rethinking of the performance of agriculture

as the need for stipulating a new social contract among the actors of the food system (farmers,consumers, industry, scientists, administrators and their constituencies) This new social contract should

be about how to use and distribute common resources in relation to an agreed-upon (1) set ofactivities judged as needed and admissible in the food systems and (2) set of indicators of performanceused for discussing and implementing what should be considered a desirable food system This newsocial contract requires considering shared goals, legitimate contrasting views about positive results andnegative side effects of human actions; discussing the validity of available analytical tools, which can beused to characterize the performance of the food system in relation to different attributes of performanceand generating viable procedures able to guarantee quality in decision processes (quality has to do withcompetence, fairness, transparency and the ability to learn and adapt)

This sudden change in the terms of reference of agriculture is challenging the conventional codifiedknowledge associated with the production of food and fibers Such knowledge, religiously preserved

in the various departments of agricultural colleges, is nowadays just one of the many pieces of informationrequired for solving the puzzle The puzzle is the necessity of continuously updating both the definitionand regulation of agricultural activities in a fast-changing social context This updating is getting moreand more difficult because of (1) the speed at which new social actors, social dynamics and technicalprocesses emerge at different scales and (2) the increasing awareness of the crucial and growing role

that the ecological dimension plays in a discussion about sustainability For these reasons, the challenge

of finding new analytical tools that can be used to deal with the sustainability of agricultural development

is extremely important within both the developed and developing worlds

The very idea of multifunctional land uses requires the adoption of the concept of multi-criteriaanalysis of performance This, in turn, requires a previous definition, at the social level, of an agreed-upon problem structuring A problem structuring can refer to the decision of how to represent thesystem under analysis (e.g., when dealing with a simple monitoring of its characteristics) or of whatscenarios should be considered (e.g., when discussing potential policies) By a given problem structuring,

I mean the individuation of:

1 A set of alternatives to be considered feasible and acceptable (the agreed-upon option space)

2 A set of indicators reflecting legitimate but contrasting perspectives found among thestakeholders (the relevant attributes of the system and the direction of change that should beconsidered an improvement or a worsening—a multi-criteria space)

3 A set of nonreducible models useful for understanding and simulating different types ofcausal relations (a multi-objective, multi-scale integrated representation of changes in relevantattributes) in relation to the set of alternatives and the set of indicators

4 The gathering of enough data to be able to run the models and discuss the pros and cons ofdifferent options in relation to the set of relevant criteria

In this new framework, the scientists are just another class of nonequivalent-observers, part of a givensociety As such, they have to learn, together with the rest of the society, how to perceive and represent

in a more effective way the performance of a multifunctional agriculture

To face such a challenge, scientists have to learn how to put their old wine (sound reductionistanalytical tools) into new bottles to address new types of problems Their new goal is no longer that offinding optimal solutions—Optimal for whom? Optimal for how long? Optimal in relation to whichcriteria? Who is entitled to decide about these questions? Rather, scientists are asked to help differentsocial actors negotiate satisfying compromises about how to use their land, human time, technologyand financial resources in relation to noncomparable types of costs and benefits (e.g., social, economic,ecological, individual gain or stress) that are expected (but with large doses of uncertainty) to beassociated with different policy choices

In human affairs, to be able to solve a problem one has, first of all, to be willing to admit that such

a problem exists in the first place The second step is to try to understand the nature of the problem in

a way that can help the finding of solutions An evident sign of crisis in the conventional scientificparadigm, when dealing with sustainability, is represented by the fact that the necessity of a paradigmshift is much clearer for the general public than for the community of politicians and scientists givingthem advice Often the sustainability predicament currently experienced by humankind is ignored (oreven denied) in the analyses provided by many conventional academic disciplines and in the strategicplanning of large national and international institutions Common people, on the contrary, are forced

to watch, in their daily life and every night in the news, the growing and widespread crumbling ofecological and social fabrics all over the planet In front of this emotional stress, they are not receivingconvincing explanations that current trends of environmental deterioration and uncontrolled growth

of either population or aspirations are not just the result of a temporary crisis, but the challenge for thestability of any political process in the next century The implications of this in terms of science forgovernance are at least twofold:

1 The scientific capability of providing useful representations and structuring of these newsustainability problems

2 The political capability of providing adequate mechanisms of governance

This book deals with only the first of these two implications However, the dual nature of this challengeimplies that when dealing with the issue of sustainability, society is trapped in a chicken-egg paradox:(1) scientists cannot provide any useful input without interacting with the rest of society and (2) therest of society cannot perform any sound decision making without interacting with the scientists In

general, these concerns have not been considered relevant by “hard” scientists in the past Thus, thegoal of improving the quality of a decision-making process was not considered to belong to the realm

of scientific investigation On the other hand, the new nature of the problems faced in this thirdmillennium implies that very often, when deciding on facts that can have long-term consequences, weare confronting issues “where facts are uncertain, values in dispute, stakes high and decisions urgent”(Funtowicz and Ravetz, 1991; Ravetz and Funtowitz, 1999)

Funtowicz and Ravetz coined the expression “postnormal science” to indicate this new predicamentfor scientific activity Whenever scientists are forced by stakeholders to tackle specific problems at agiven point in space and time, they can face a mission impossible according to the terms of reference

of normal science There are problems and situations in which risk (defined as an assessment based onprobabilities) cannot be assessed (e.g., potential environmental problems of large-scale application ofGMOs are associated with uncertainty and ignorance) There are other situations (e.g., whenever theyare told “to fix Chicago in 30 days”) in which scientists are facing (1) events that do not make possiblerepetitions in experiments and (2) a flow of questions from the stakeholders that would require a flow

of scientific answers at a rate not compatible with the development of a sound scientific understanding.When operating in a normal mode, scientists are used to having the privilege of picking up the bestexperimental setting for studying what they want to study, and in doing so, they can take all the timethey need to work out robust answers

In a situation of postnormal science, scientific rigor does not always coincide with sound science

On the contrary, using risk assessment (e.g., using frequencies or estimated probabilities to assess risks)

in cases in which one deals with irreducible uncertainty and genuine ignorance should be consideredsloppy science That is, the use of sophisticated statistical tests providing a significance of 0.01 shouldnot be confused with sound science when used in situations in which they do not make any sense(Giampietro, 2002) In this situation, those who refuse to sell fake rigorous science in exchange forpower and academic recognition can find themselves marginalized in the debate over the future of ourdevelopment To make things worse, this situation enables the establishment of ideological filters based

on pseudo-scientific rigor to avoid confronting unpleasant realities The denial of the existence of aproblem of global warming related to the accumulation in the atmosphere of greenhouse emissions is

a well-known example of this fact When dealing with a complex reality and large-scale problems (e.g.,global warming) there is always some rigorous test that can be found to challenge the evidencesupplied by the adverse side But a broken clock indicating the exact time twice a day is much lessuseful for decision making than a clock that slows down a second every year and therefore never givesthe exact time during any day for the following months When dealing with large-scale issues, it ismuch better to have a sound understanding of the big picture, even if details are missing, than a veryaccurate picture of just one piece of the puzzle, which can only be studied rigorously when considered

in pieces and held out of context

This book wants to answer three questions crucial for scientists willing to be effective in thedevelopment of a science that can be more useful for governance in relation to the issue of sustainability

of agriculture:

Part 1: What is the role that scientists working in the field of sustainability of agriculture shouldplay in this process?

Part 2: Can we develop different scientific analyses using complex systems thinking?

Part 3: What alternative analytical tool kits can be developed for integrated analysis of systems?

agroeco-References

Funtowicz, S.O and Ravetz, J.R., (1991), A new scientific methodology for global environmental issues In: R.

Costanzam (Ed.) Ecological Economics, Columbia, New York, pp 137–152.

Giampietro, M, (2002), The precautionary principle and ecological hazards of genetically modified organisms,

AMBIO, 31, 466–470.

Ravetz, J.R and Funtowicz, S.O., Guest Eds., (1999), Futures, (Vol 31) Special issue dedicated to postnormal

science.

Röling, N., (2001), Gateway to the Global Garden: Beta/Gamma Science for Dealing with Ecological Rationality, Eighth

Annual Hoper Lecture, 8 Centre for International Programs, University of Guelph, Ontario.

Waltner-Toews, D and Lang, T., (2000), The emerging model of links between agriculture, food, health, environment

and society, Global Change Hum Health, 1, 116–130.