US-IALE 2009: Coupling Humans and Complex Ecological Landscapes
Coupling Humans and Complex Ecological Landscapes is the theme of the 2009 annual conference of US-IALE (U.S. Regional Association, International Association for Landscape Ecology). The conference will be held in Snowbird, Utah, from April 12-16, 2009. Proposals for symposia and workshops are due September 15, 2008; and abstracts are due November 17, 2008.
Several types of financial support for attending and presenting at the conference are available:
(1) the "Sponsored Student Travel Awards Program" of local sponsors (USGS, Utah State University, and Utah Department of Natural Resources),
(4) the 'CHANS Fellows Program' of the new International Network of Research on Coupled Human and Natural Systems (CHANS-Net, supported by NSF, see background papers in Science and Ambio).
US-IALE conferences are particularly students-friendly, with two popular programs -- Lunch with Mentors and NASA-MSU dinner, and a new program -- We'll "Pick Up The Tab!".
More information about the conference is available from the web site.
Previously, I wrote about Orrin Pilkey and Linda Pilkey-Jarvis' book, Useless Arithmetic: Why Environmental Scientists Can’t Predict the Future. In a recent issue of the journal Futures, Jerome Ravetz reviews their book alongside David Waltner-Toews' The Chickens Fight Back: Pandemic Panics and Deadly Diseases That Jump From Animals to Humans. Ravetz himself points out that the subject matter and approaches of the books are rather different, but suggests that "Read together, they provide insights about what needs to be done for the creation of a genuine science of sustainability".
Ravetz (along with Silvio Funtowicz) has developed the idea of 'post-normal' science - a new approach to replace the reductionist, analytic worldview of ‘normal’ science. Post-normal science is a "systemic, synthetic and humanistic" approach, useful in cases where "facts are uncertain, values in dispute, stakes high and decisions urgent". I used some of these ideas to experiment with some alternative model assessment criteria for the socio-ecological simulation model I developed during my PhD studies. Ravetz's perspectives toward modelling, and science in general, shone through quite clearly in his review:
"On the philosophical side, the corruption of computer models can be understood as the consequence of a false metaphysics. Following on from the prophetic teachings of Galileo and Descartes, we have been taught to believe that Science is the sole and certain path to truth. And this Science is mathematical, using quantitative data and abstract reasonings. Such a science is not merely necessary for achieving genuine knowledge (an arguable position) but is also sufficient. We are all victims of the fantasy that once we have numerical data and mathematical argument (or computer programs), truth will inevitably follow. The evil consequences of this philosophy are quite familiar in neo-classical economics where partly true banalities about markets are dressed up in the language of the differential calculus to produce justifications for every sort of expropriation of the weak and vulnerable. ‘What you can’t count, doesn’t count’ sums it all up neatly. In the present case, the rule of models extends over nearly all the policy-relevant sciences, including those ostensibly devoted to the protection of the health of people and the environment.
We badly need an effective critical philosophy of mathematical science. ... Now science has replaced religion as the foundation of our established order, and in it mathematical science reigns supreme. Systematic philosophical criticism is hard to find. (The late Imre Lakatos did pioneering work in the criticism of the dogmatism of ‘modern’ abstract mathematics but did not focus on the obscurities at the foundations of mathematical thinking.) Up to now, mathematical freethinking is mainly confined to the craftsmen, with their jokes of the ‘Murphy's Law’ sort, best expressed in the acronym GIGO (Garbage In, Garbage Out). And where criticism is absent, corruption of all sorts, both deliberate and unaware, is bound to follow. Pseudo-mathematical reasonings about the unthinkable helped to bring us to the brink of nuclear annihilation a half-century ago. The GIGO sciences of computer models may well distract us now from a sane approach to coping with the many environmental problems we now face. The Pilkeys have done us a great service in providing cogent examples of the situation, and indicating some practical ways forward."
Thus, Ravetz finds a little more value in the Useless Arithmetic book than I did. But equally, he highlights that the Pilkeys offer few, rather vague, solutions and instead turns to Waltner-Toews' book for inspiration for the future:
Pilkey's analysis of the corruptions of misconceived reductionist science shows us the depth of the problem. Waltner-Toes’ narrative about ourselves in our natural context (not always benign!) indicates the way to a solution."
Using the outbreak of avian flu as an example of how to tackle complex environmental in the 'risk society' in which we now live, Waltner-Toes:
"... makes it very plain that we will never ‘conquer’ disease. Considering just a single sort of disease, the ‘zoonoses’ (deriving from animals), he becomes a raconteur of bio-social-cultural medicine ...
What everyone learned, or should have learned, from the avian flu episode is that disease is a very complex entity. Judging from TV adverts for antiseptics, we still believe that the natural state of things is to be germ-free, and all we need to do is to find the germs and kill them. In certain limiting cases, this is a useful approximation to the truth, as in the case of infections of hospitals. But even there complexity intrudes ... "
Complexity which demands an alternative perspective that moves beyond the next stage of 'normal' science to a post-normal science (to play on Kuhn's vocabulary of paradigm shifts):
"That old simple ‘kill the germ’ theory may now be derided by medical authorities as something for the uneducated public and their media. But the practice of environmental medicine has not caught up with these new insights.
The complexity of zoonoses reflects the character of our interaction with all those myriads of other species. ... the creatures putting us at risk are not always large enough to be fenced off and kept at a safe distance. ... We can do all sorts of things to control our interactions with them, but one thing is impossible: to stamp them out, or even to kill the bad ones and keep the good ones.
Waltner-Toes is quite clear about the message, and about the sort of science that will be required, not merely for coexisting with zoonoses but also for sustainable living in general. Playing the philological game, he reminds us that the ancient Indo-European world for earth, dgghem, gave us, along with ‘humus’, all of ‘human’, ‘humane’ and ‘humble’. As he says, community by community, there is a new global vision emerging whose beauty and complexity and mystery we can now explore thanks to all our scientific tools."
This global vision is a post-normal vision. It applies to far more than just avian flu - from coastal erosion and the disposal of toxic or radioactive waste (as the Pilekys discuss for example) to climate change. This post-normal vision focuses on uncertainty, value loading, and a plurality of legitimate perspectives that demands an "extended peer community" to evaluate the knowledge generated and decisions proposed.
In all fairness, it would not be easy to devise a conventional science-based curriculum in which Waltner-Toes's insights could be effectively conveyed. For his vision of zoonoses is one of complexity, intimacy and contingency. To grasp it, one needs to have imagination, breadth of vision and humility, not qualities fostered in standard academic training. ... "
This post-normal science won't be easy and won't be learned or fostered entirely within the esoteric confines of an ivory tower. Science, with its logical rigour, is important. It is still the best game in town. But the knowledge produced by 'normal' science is provisional and its march toward truth is seemingly Sisyphean when confronted faced with the immediacy of complex contemporary environmental problems. To contribute to the production a sustainable future, a genuine science of sustainability would do well to adopt a more post-normal stance toward its subject.
The theme of the meeting was the understanding of patterns, causes, and consequences of spatial heterogeneity for ecosystem function. The three keynote lectures were given by Gary Lovett, Kimberly With and John Foley. I found John Foley's lecture the most interesting and enjoyable of the three - he's a great speaker and spoke on a broader topic than the the others; Agriculture, Land Use and the Changing Biosphere. Real wide-ranging, global sustainability stuff. He highlighted the difficulties of studying agricultural landscapes because of the human cultural and institutional factors, but also stressed the importance of tackling these tricky issues because 'agriculture is the largest disturbance the biosphere has ever seen' and because of its large contribution to greenhouse gas emissions.
Presentations I was particularly interested in were mainly in the 'Landscape Patterns and Ecosystem Processes: The Role of Human Societies', 'Challenges in Modeling Forest Landscapes under Climate Change' and 'Cross-boundary Challenges to the Creation of Multifunctional Agricultural Landscapes' sessions.
In the 'human societies' session, Richard Aspinall discussed the importance of considering human decision-making at a range of scales and Dan Brown again highlighted the importance of human agency in spatial landscape process models. In particular, with regards modelling these systems using agent-based approaches he discussed the difficulty of model calibration at the agent level and stressed that work is still needed on the justification and evaluation phases of agent-based modelling.
The 'modeling forest landscapes' session was focused largely around use of the LANDIS and HARVEST models that were developed in and around Wisconsin. In fact, I don't think I saw any mention of the USFS FVS at the meeting whilst I was there, largely because (I think) FVS has large data demands and is not inherently spatial. LANDIS and HARVEST work at more coarse levels of forest representation (grid cell compared to FVS' individual tree) allowing them to be spatially explicit and to run over large time and space extents. We're confident we'll be able to use FVS in a spatially explicit manner for our study area though, capitalising on the ability of FVS to directly simulate specific timber harvest and economic scenarios.
The 'multifunctional agricultural landscapes' session had an interesting talk by Joan Nassauer on stakeholder science and the challenges it presents. Specific issues she highlighted were: 1. the need for a precise, operational definition of 'stakeholder' 2. ambiguous goals for the use of stakeholders 3. the lack of a canon of replicable methods 4. ambivalence toward the quantification of stakeholder results
Other interesting presentations were given by Richards Hobbs and Carys Swanwick. Richard spoke about the difficulties of 'integrated research' and the importance of science and policy in natural resource management. He suggested that policy-makers 'don't get' systems thinking or modelling, and that some of this may be down to the psychological profiles of the types of people that go into policy making. Such a conclusion suggests scientists need to work harder to bridge the gap to policy makers and do a better job of explaining the emergent properties of the complex systems they study. Carys Swanwick talked about the landscape character assessment, which was interesting for me having moved from the UK to the US about a year ago. Whilst 'wilderness' is an almost alien concept in the UK (and Europe as a whole), landscape character is something that is distinctly absent in the new world agricultural landscapes. Carys talked about the use of landscape character as a tool for conservation and management (in Europe) and the European Landscape Convention. It was a refreshing change from many of the other presentations about agricultural landscape (possibly just because I enjoyed seeing a few pictures of Blighty!).
Unfortunately the weather during the conference was wet which meant that I didn't get out to see as much of Madison as I would have liked. Despite the rain we did go on the Biking Fieldtrip. And yes, we did get soaked. It was also pretty miserable weather for the other fieldtrip to and International Crane Foundation center and the Aldo Leopold Foundation (more on that in a future blog), but interesting nevertheless.
Other highlights of the conference for me were meeting the former members of CSIS and eating dinner one night with Monica Turner. I also got to meet up with Don McKenzie and some of the other 'fire guys', and a couple of people from the Great Basin Landscape Ecology lab where I visited previously. And now I'm already looking forward to the meeting next year in Snowbird, Utah (where I enjoyed the snow this winter).
I like this video. Less because of the message toward the end about the importance of ensuring western countries continue to train adaptable workforces in an increasingly flat world. More because of how it illustrates the speed and unpredictability of change. In hindsight it might seem obvious that this is how the world should end up - contingency matters in the real world after all. But in these contingent, historical, systems how do we generate a model for the future that we can trust with any useful degree of confidence?
As I mentioned before, the Global Land Project website is experimenting with the use of webcasts to enable the wider network to "participate" and use the GLP webpage as a resource. For example, several presentations are available for viewing from the Third Land System Science (LaSyS) Workshop entitled 'Handling complex series of natural and socio-economic processes' and held in Denmark in October of 2007. One that caught my attention was by Tom Veldkamp, mainly because of its succinct title: Advances in Land Models [webcast works best in IE].
Presented in the context of other CHANS research, Veldkamp used an example from the south of Spain to discuss recent modelling approaches to examine the effects of human decisions on environmental processes and the feedbacks between human and natural systems. The Spanish example examined the interaction of human land-use decision making and soil erosion. A multi-scale erosion model, LAPSUS, represented the interactive natural and human processes occurring olive groves on steep hillslopes; gullying caused by extreme rainfall events and attempts to preserve soils and remove gullies by ploughing. Monte Carlo simulations were used to explore uncertainties in model results and highlighted the importance of path dependencies. As such, another example of the historical dimension of 'open' systems and the difficulties it presents for environmental modellers.
The LAPSUS model was coupled with the well known land use/cover change CLUE model to examine feedbacks between human land use and erosion. The coupled model was used to examine the potential implications of farmers adopting land use practices as a response to erosion. Interestingly, the model suggested that human adaptation strategy modelled would not lead to reduced erosion.
Veldkamp also discusses the issue of validating simulation models of self-organising processes, and suggests that ensemble and scenario approaches such as those used in global climate modelling are necessary for this class of models. However, rather than simply using 'static' scenarios that specify model boundary conditions, such as the IPCC SRES scenarios, scenarios that represent some form of feedback with the model itself will be more useful. Again, this comes back to his point about the importance of representing feedbacks in coupled human and natural systems.
For example, Veldkamp suggests the use of "Fuzzy Cognitive Maps" to generate 'dynamic' scenarios. Essentially, these fuzzy cognitive maps are produced by asking local stakeholders in the systems under study to quantify the effects of the different factors driving change. First, the appropriate components of the system are identified. Next, the feedbacks between these components are identified. Finally, the stakeholders are asked to estimate how strong these feedbacks are (on a scale of zero to one). This results in a semi-quantitative systems model that can be run for several iterations to examine the consequences of the feedbacks within the system. This method is still in development and Veldkamp highlighted several pros and cons:
Pros:
it is relatively easy and quick to do
it forces the stakeholders to be explicit
the emphasis is placed on the feedbacks within the system
Cons:
it is a semi-quantitative approach
often feedbacks are of incomparable units of measurement
time is ill defined
stakeholders are often more concerned with the exact values they put on an interaction rather than the relative importance of the feedbacks
I agree when Veldkamp suggests this 'fuzzy cognitive mapping' is a promising approach to scenario development and incorporation into simulation modelling. Indeed, during my PhD research I explored the use of an agent-based model of land use decision-making to provide scenarios of land use/cover change for a model of forest succession-disturbance dynamics (and which I am currently writing up for publication). 'Dynamic' model scenario approaches show real promise for representing feedbacks in coupled human natural systems. As Veldkamp concludes, these feedbacks, along with the non-linearities in system behaviour they produce, need to be explicitly represented and explored to improve our understanding of the interactions between humans and their environment.
Staying Together... for the Sake of the Environment?
I may be a little behind the times but I have finally begun to digg stuff. From now on if I digg something that I really like or think it is relevant to what I talk about on this blog I'll post it directly from digg. Given the media interest in the most recent paper to come out of CSIS it seems appropriate that this be the first blog from digg:
"A married household actually uses resources more efficiently than a divorced household," said Jianguo Liu, a sustainability expert with Michigan State University. He and fellow researcher Eunice Yu concluded that in 2005, in the United States alone, divorced households could have saved 38 million rooms, 73 billion kilowatt-hours of electricity and 627 billion gallons of water if their "resource-use efficiency" had been comparable to that of married households. Liu's analysis of the environmental impact of divorce appears in this week's online edition of Proceedings of the National Academy of Sciences. Besides the United States, Liu looked at 11 other countries, including Brazil, Costa Rica, Ecuador, Greece, Mexico and South Africa between 1998 and 2002. In the 11, if divorced households had combined to have the same average household size as married households, there could have been a million fewer households using energy and water in these countries. "People have been talking about how to protect the environment and combat climate change, but divorce is an overlooked factor that needs to be considered," Liu said.
I've been watching Ewan McGregor and Charlie Boorman on their epic motorcycle adventure all the Long Way Down from John O'Groats in Scotland through Europe and Africa to Cape Town, South Africa. It's like a 21st century lads version of Michael Palin's jolly jaunts around the world and follows on from their last trip from London to New York the (wrong) Long Way Round. Another inspirational set of characters to give one itchy feet...
One of the charities they're associated with and raising money for on their trip is UNICEF. On their way through Africa the boys visited places where UNICEF are working, like in Ethiopia where they are still clearing land mines from previous wars and educating local children and families about the dangers that remain.
You can support this work by sponsoring a mile of Ewan and Charlie's route. All of the money raised supports the UNICEF Long Way Down Fund to help children affected by conflict, poverty and HIV/AIDS in Africa. For example, £1 will buy six sachets of peanut butter paste that is used to treat children with malnutrition. Checkout the map - I've sponsored mile 114.
What does it mean to 'be' an expert? at RGS-IBG 2008
That man James Porter is busy at the Geography conferences these days. Alongside organising a session at the 2008 AAG on Private Science & Environmental Governance, he's also organising a session at the 2008 RGS-IBG Annual Meeting on expertise and what it means to be an expert. Details below, abstract submissions are due by 16th January 2008.
I didn't make it to the meeting last year but hope to in 2008...
Call for Papers: (Re)Thinking Expertise: Spaces of Production, Performance and the Politics of Representation RGS-IBG, Annual Meeting, 27 - 29 August 2008 London
What does it mean to 'be' an expert? Although social constructionism has identified similarities between science and other social practices, recently a controversial call for a “Third Wave” of science studies (Collins & Evans, 2002) has drawn attention to the problem of Extension – the infinite regress encountered when looking for techno-scientific advice if we can no-longer tell the difference between expert and lay-knowledge. Expertise has previously been understood to be the unyielding pursuit of authoritative knowledge that is honed through practice and enforced by political and academic institutions. In this sense, the professional identities presented to the outside world are carefully crafted so as to conform and exhibit ideological norms not dissimilar to Merton’s ideals. Such readings, however, arguably present an overly romantic, simplistic, and homogenous rendering of experts and their expertise. What is needed is examination of how experts’ identities are constructed (when and by whom), how they are negotiated between actors and institutions, the historical context in which they are played out, and ultimately how they function (or don’t) instrumentally to serve or suppress certain realities.
Expertise is arguably played out more visibly today than ever before, particularly with reference to the environment. Floods, hurricanes, infectious animal diseases, and a myriad of other concerns are captured graphically and broadcasted nightly into homes across the world. Each event and the subsequent response depicts the experts involved as either heroes or villains of these dramatised pieces – in both cases thrust into the limelight as representatives of their respective fields. Geographers are uniquely positioned to comment on this. They can provide theoretical depth and empirical evidence to shed light on the way expert identities are shaped, the role they serve, the impact on the democratization of knowledge, and the barriers they present to tackling environmental problems. We therefore invite papers addressing (though not limited to) the following questions:
Who constructs the image of environmental experts? How / where are these constructions enacted (i.e. technological, sociocultural, artefacts, etc.)?
Can representations be negotiated? If so, what role have academics played in shaping past perceptions and might hope to play in the future? What agency do these representations have?
What is the effect of these representations? Do they ever coincide or clash with the needs, understandings and views of actors (public, political, etc.)? Where are they successful and unsuccessful?
Do the representations come to in turn alter the landscape and shape an environment which conforms to the possible misguided representation itself? Does this lead to a snowballing of representations and hence crisis where ‘reality’ breaks?
Abstracts should be sent to James Porter (james.porter at kcl.ac.uk) and Joseph Hillier (joseph.hillier at ucl.ac.uk) by 16th January 2008.
"I think fundamentally societies have to make choices as to whether they want more material well being or more tranquillity. Regrettably I think we cannot have both. ... That's what I believe the evidence very conclusively indicates."
"All you can basically know is whether probabilities are increasing or decreasing. We have no capability of looking into to the future and knowing for certain that certain things are going to happen."
In this week's issue of ScienceJack Liu, Director of CSIS (and my boss), and colleagues present a review of recent research on Coupled Human And Natural Systems (CHANS). Using six case studies from around the world the paper discusses these coupled systems with regards spatial, temporal and organisational units, nonlinear dynamics and feedback loops between systems, the importance of history within these sytems, and aspects of their resilience and heterogeneity. We'll be discussing the paper within the center next week so maybe I'll have some more insightful comments then. For now, here's the abstract:
Integrated studies of coupled human and natural systems reveal new and complex patterns and processes not evident when studied by social or natural scientists separately. Synthesis of six case studies from around the world shows that couplings between human and natural systems vary across space, time, and organizational units. They also exhibit nonlinear dynamics with thresholds, reciprocal feedback loops, time lags, resilience, heterogeneity, and surprises. Furthermore, past couplings have legacy effects on present conditions and future possibilities.
Complexity of Coupled Human and Natural Systems Jianguo Liu , Thomas Dietz, Stephen R. Carpenter, Marina Alberti, Carl Folke, Emilio Moran, Alice N. Pell, Peter Deadman, Timothy Kratz, Jane Lubchenco, Elinor Ostrom, Zhiyun Ouyang, William Provencher, Charles L. Redman, Stephen H. Schneider, William W. Taylor Science 14 September 2007 Vol. 317. no. 5844, pp. 1513 - 1516 DOI: 10.1126/science.1144004 Also online here`
One evening whilst sitting on a deck overlooking a tranquil lake in the wilds of the UP's northern hardwood forests, I began reading William Cronon's contributions to the volume he edited himself; Uncommon Ground. The book has been around for a decade and more but it is only recently that I came across a copy in a secondhand book store. It seems apt that I considered what it had to say about the 'social construction' of nature in a setting of the type that has long intrigued me. Maybe the view of a landscape which confronted me is another of the reasons I am doing what I am right now. I have had pictures of these large wilderness landscapes on the walls of my mind, and elsewhere, for a while.
Cronon examines "the trouble with wilderness" with reference to the Edenic ideal that underlay it from the beginning. Wordsworth and Thoreau were in bewildered or lost awe of the sublime landscapes they travelled, but by the time John Muir came to the Sierra Nevada the landscape was an ecstasy. Whilst Adam and Eve may have been driven from the garden out into the wilderness, the myth was now 'the mountain as cathedral' and sacred wilderness was a place to worship God's natural world. Furthermore, as the American frontier diminished with time and technology,
"wilderness came to embody the national frontier myth, standing for the wild freedom of America's past and and seeming to represent a highly attractive natural alternative to the ugly artificiality of modern civilization. ... Ever since the nineteenth century, celebrating wilderness has been an activity mainly for well-to-do city folks. Country people generally know far too much about working the land to regard unworked land as their ideal." (p.78)
Cronon suggests that there is a paradox at the heart of the Wilderness ideal, this conception that true nature must also be wild and that humans must set aside areas of the world for it to remain pristine. As Cronon puts it, this paradox is that "The place where we are is the place where nature is not". Taking this logic to its extreme results in the need for humans to kill themselves in order to preserve the natural world;
"The absurdity of this proposition flows from the underlying dualism it expresses. ... The tautology gives us no way out: if wild nature is the only thing worth saving, and if our mere presence destroys it, then the sole solution to our own unnaturalness, the only way to protect sacred wilderness from profane humanity, would seem to be suicide. It is not a proposition that seems likely to produce very positive or practical results." (p.83)
I'll say. But Cronon is not saying that protected wilderness areas are themselves undesirable things, of course not. His point is about the idea of Wilderness. As a response he suggests that rather than thinking of nature as 'out there', we need to learn how to bring the wonder we feel when in the wilderness closer to home. We need to abandon the idea of the tree in the garden as artificial and the tree in the wilderness as natural. If we see both trees as natural, as wild, then we will be able to see nature and wildness everywhere; in the fields of the countryside, between the cracks in the city pavement, and even in our own cells.
"If wildness can stop being (just) out there and start being (also) in here, if it can start being as humane as it is natural, then perhaps we can get on with the unending task of struggling to live rightly in the world - not just in the garden, not just in the wilderness, but in the home that encompasses both" (p.90)
Sitting on that deck looking out over the lake it was clear that landscapes such as the one I was in aren't the idealised, pristine, wilderness that they may be portrayed as in books, photographs and travel brochures. Just as in studying its nature I have come to understand a little better the uncertainties of the scientific method that is supposed to bring facts and truth, so I think have come to better understand the place of human needs within these 'wild' landscapes. As naive as it is to think that science might offer the absolute truth (it can't, but it is still the best game in town to understand the world around us), thinking humans are inseparable from nature seems equally foolish.
In the introduction to a book on natural resource economics (which has mysteriously vanished from my bookshelf), an author describes a similar situation. As a young man he wanted to study the environment in order that he might save it from destructive hands of humans. But in time he came to realise this was unrealistic and that better would be to study the means by which humans use the 'natural world' to harvest and produce the resources we need to live. Economics is concerned with the means by which we allocate, and create value from, resources. Just as it is important to understand how 'nature' works, it is also important to understand how a world in which humans are a natural component works, and how it can continue to function indefinitely.
Landscape Ecology and Ecological Economics have grown out of this understanding. Whilst theories and models about the natural world independent of humans remain necessary, increasingly important are theories and models that consider the interaction between the social, economic and biophysical components of the natural world. These tools might help us get on with the task of living sustainably in the place which humans should naturally call home.
The problems of equifinality and affirming the consequent suggest alternative criteria by which to validate or evaluate socio-ecological simulation models (SESMs) will be useful. In my last post in this series I suggested that trust and practical adequacy might be useful additional criteria. In light of the 'risk society'-type problems facing the systems that SESMs represent, and the proposed post-normal science approaches to examine and resolve them, the participation of local stakeholders in the model validation process seems an important and useful approach to ensure and improve model quality. If local stakeholders are to accept decisions and policies made based upon results from simulation models they will need to trust a model and, by consequence, the modeller(s).
Due to a perceived 'crisis of trust' in science over the last 20 years, Wilsdon and Willis suggest "scientists have been slowly inching their way towards involving the public in their work" and that we are now on the cusp of a new phase of public engagement that takes it 'upstream'. This widely used, but somewhat vague term, is used to refer to the early involvement of the lay public in the processes of scientific investigation. As such, engagement is 'upstream' nearer the point at which the research and development agenda is set, as opposed to the 'downstream' end at which research results are applied and the consequences examined (see Figure 1).
Figure 1 Public participation in the scientific research process. Recently it has been suggested that public engagement with the scientific process needs to move 'upstream' nearer the point at which the research agenda is set. After Jackson et al
Whereas previously the theory of the 'public understanding of science' was a deficit model suggesting that the public would trust science 'if only they understood it', the contemporary shift is towards and engagement and dialogue between science and society. The implication of this new turn is that the public will trust science 'if only they are involved in the process itself'. Recently, Lane et al. advocated this move upstream for forms of environmental modelling that address issues and concerns of rural populations. This position has been criticised as devaluing the worth of science, for patronising the public, and being a mask for political face-saving or insurance.
Regardless of other areas of science, in the case of developing simulation models for socio-ecological systems the participation of the public does not result in the first two of these criticisms. Engaging with local stakeholders to ensure a model is both built on a logically and factually coherent foundation and to ensure it examines the appropriate questions and scenarios is of great value to the modelling process and should improve representation of the empirical system. Contributing to successful iterations of this process, local stakeholders will gain both trust and understanding. However, the inclusion of local stakeholders in the modelling process does raise the issue of expertise.
With parallels in the three phases Wilsdon and Willis have suggested, Collins and Evans have suggested we are entering a third wave in the sociology of science. This third wave demands a shift from an emphasis on technical decision-making and truth to expertise and experience. Collins and Evans suggest there are three types of expert in technical decision-making (i.e. decision-making at the intersection of science and politics); 'No Expertise', 'Interactional Expertise', and 'Contributory Expertise'.
Individuals possessing interactional expertise are able to interact 'interestingly' with individuals undertaking the science, but not to contribute to the activities of science itself (contributory expertise). Brian Wynne's well-known study of the (inadequate) interaction between Cumbrian sheep farmers and UK government scientists investigating the ecological impacts of the Chernobyl disaster is a prime example of a situation in which two parties possessed contributory expertise, but neither interactional expertise. As a result, the 'certified' expertise of the government scientists was given vastly more weight than the 'non-certified' expertise of the farmers (to the detriment of the accuracy of knowledge produced). Such non-certified expertise might also be termed 'experience-based' expertise, arising as it does from the day-to-day experiences of particular individuals.
The importance of considering non-certified, contributory experience is particularly acute for SESMs. Specifically, local stakeholders are likely to be an important, if not the primary, source of knowledge and understanding regarding socio-economic processes and decision-making within the study area. Furthermore, the particular nature of the interactions between human activity and ecological (and other biophysical) processes within the study area will be best understood and incorporated into the simulation model via engagement with stakeholders. This local knowledge will be vital to ensure the logical and factual foundations of the model are as sound as possible.
Furthermore, engagement with local stakeholders will highlight model omissions, areas for improved representation, and guide application of the model. It provides an opportunity to enlighten experts as to the 'blind spots' in their knowledge and questions. As such, the local stakeholders become an 'extended peer community', lending alternative forms of knowledge and expertise to the model (and research) validation process than that of the scientific peer community. This knowledge and expertise may be less technical and objective than that of the scientific community, but this nature does not necessarily reduce its relevance or utility to the modelling of a system that contains human values and subjects.
I pursued this idea of stakeholder participation in the modelling I undertook for my PhD. Early in the development of my agent-based model of land use decision-making, local stakeholders were interviewed with regards to how they made decisions and their understanding about landscape dynamics. Upon completion of model construction I went to talk with stakeholders about the model as they offered the prime source of criticism about the model representation of their decision-making activities. By engaging with these stakeholders a form of qualitative, reflexive model validation was performed that overcame some of the problems of a more deductive approach.
Given the discussion in the previous posts regarding the nature of socio-ecological systems, equifinality and relativism in environmental modelling, how should we go about assessing the worth and performance of our simulation models of human-environment systems?
Simulation models are tangible manifestations of a modellers’ ‘mental model’ of the structure of the system being examined. Socio-Ecological Simulation Models (SESMs) may be thought of as logical and factual arguments made by a modeller, based on their mental model. If the model assumptions hold, these arguments should provide a cogent and persuasive indication of how system states may change under different scenarios of environmental, economic and social conditions. However, the resulting simulation model, based upon a logical and factually coherent mental model, is unlikely to be validated on these two criteria (logic and fact) alone.
First, the problems of equifinality suggest that there are multiple logical model structures that could be implemented for any particular system. Second, accurate mimetic reproduction of an empirical system state by a model may be the most persuasive form of the factual proof of a model in many eyes, but the dangers of affirming the consequent make it impossible to prove temporal predictions in models of open systems are truly accurate. Simulation models may be based on facts about empirical systems, but their results cannot be taken as facts about the modelled empirical system.
Thus, some other criteria alongside the logical and factual criteria will be useful to evaluate or validate a SESM. A third and fourth criteria, for environmental simulation models that consider the interaction of social and ecological systems at least, are available by specifically considering the user(s) of a model and its output. These criteria are closely linked.
My third proposed criterion is the establishment of user trust in the model. Trust is used here in the sense of ‘confidence in the model’. If a person using a model or its results does not trust the model it will likely not be deemed fit for its intended purpose. If confidence is lacking in the model or its results, confidence will consequently be lacking in any knowledge derived, decision made, or policy recommended based upon the model. Thus, the use of trust as a criterion for validation is a form of ‘social validation’, ensuring that user(s) agree the model is a legitimate representation of the system.
The fourth criteria by which a model might achieve legitimacy and receive a favourable evaluation (i.e. be validated), is the provision of some form of utility to the user. This utility will be termed ‘practical adequacy’. If a model is not trusted then it will not be practically adequate for its purpose. However, regardless of trust, if the model is not able to address the problems or questions set by the user then the model is equally practically inadequate.
The addition of these two criteria, centred on the model user rather than the model itself, suggests a shift away from falsification and deduction as model validation techniques, toward more reflexive approaches. The shift in emphasis is away from establishing the truth and mimetic accuracy of a model and toward ensuring trust and practical adequacy. By considering trust and practical adequacy, validation becomes an exercise in model evaluation and reclaims its more appropriate meaning of ‘establising a model’s legitimacy’.
From his observation of experimental physicists and work on the 'experimenter’s regress', Collins has arrived at the view that there is no distinction between epistemological criteria and social forces to resolve a scientific dispute. The position outlined previously seems to imply a similar situation for models of open, middle-numbered systems where modellers are required to resort to social criteria to justify their models due the inability to do so convincingly epistemologically. This is not necessarily an idea that many natural scientists will sit comfortably with. However, the shift away from truth and mimetic accuracy should not necessarily be something modellers would object to.
First, all modellers know that their models are not true, exact replications of reality. A model is an approximation of reality – there is no need to create a model system if experimentation on the existing empirical system is possible. Furthermore, accepting the results of a model are not ‘true’ (i.e. in the sense that they are perfect predictions of the future) in no way requires the model be built on incorrect logic or facts. As Hesse notes in criticism of Collins, whilst the resolution of scientific disputes might result from a social decision that is not forced by the facts, “it does not follow that social decision has nothing to do with objective fact”.
Second, regardless of truth and mimetic accuracy, modellers have several options to build trust and ensure practical adequacy scientifically. Ensuring models are logically coherent and not factually invalid (i.e. criteria one and two) will already have come some way to make a scientific case. Furthermore, the traditions of scientific methodological and theoretical simplicity and elegance can be observed, and the important unifying potential across theories and between disciplines that modelling offers can be emphasised. Thus, regardless of the failures of epistemological methods for justifying them, socio-ecological and other environmental simulation models must be built upon solid logical and factual foundations;
“The postmodern world may be a nightmare for … normal science (Kuhn 1962), but science still deserves to be privileged, because it is still the best game in town. … [Scientists] need to continue to be meticulous and quantitative. But more than this, we need scientific models that can inform policy and action at the larger scales that matter. Simple questions with one right answer cannot deliver on that front. The myth of science approaching singular truth is no longer tenable, if science is to be useful in the coming age.” (Allen et al. p.484)
Post-normal science highlights the importance of finding alternative ways for science to engage with both the problems faced in the contemporary world and the people living in that world. As they have been defined here, SESMs will inherently address questions that will be of concern to more than just scientists, including problems of the ‘risk society’. From a modelling perspective, a post-normal science approach highlights the need to build trust in the eyes of non-scientists such that understanding is fostered.
Further, it emphasises the need for SESMs to be practically adequate such that good decisions can be made promptly. It also implies that the manner in which a ‘normal’ scientist will go about assessing the trustworthiness or practical adequacy of a model (such as the methods described above) will differ markedly from that of a non-scientist. For example, scientific model users will often, but not always, have also been the person to develop and construct the model. In such a case the model will be constructed to ensure the model is practically adequate to address their particular scientific problems and questions.
When the model is to be used by other parties the issue of ensuring practical adequacy will not be so straight-forward, and particularly so when the user is a non-scientist. In such situations, the modeller needs to ask the question ‘practically adequate for what’? The inhabitants of the study areas investigated will have a vested interest in the processes being examined and will themselves have questions that could be addressed by the model. In all probability many of these questions will be ones that the modeller themselves has not considered or, if they have, may not have considered relevant. Further, the questions asked by local stakeholders may be non-scientific – or at least may be questions that environmental scientists are not used to attempting to answer.
The use and improvements in technical approaches (such a spatial error matrices from pixel-by-pixel model assessment) will remain useful and necessary in the future. Here however, I have emphasised potential alternative methods for model validation (assessment) might be useful to utilise the additional information and knowledge which is available from those actors driving change in a socio-ecological system. In other words, there is information within the system of study that is not utilised for model assessment by simply comparing observed and predicted system states. This information is present in the form of local stakeholders’ knowledge and experience.
Let's go Lansing Lugnuts that is. Last night I went to my first Minor League Baseball game. I've been to a couple of Major League games before, but on a nice summers' evening it was about time to find out more about what goes on in the lower echelons of the game that has always intrigued me. When I was about 8 my uncle brought me back a Red Socks baseball and pennant from a business trip. Maybe that got it started. One of my favourite writers Stephen Jay Gould was a huge baseball fan and used the apparent extinction of the .400 batting average as an adroit metaphor in one of his books to discount the idea of evolutionary progress with humans at the pinnacle in. And of course there are the parallels with cricket.
The lower levels of professional sport rarely get heard above the din and clamour for the biggest and best teams. The FA Premiership is now the richest football league in the world and followed avidly by many fans around the world. Its transition from a league with a reputation of violence and hooliganism to one of the most marketable sporting brands in the world has come via a change in attitude and facilities. I have a vivid memory from one of my first trips to a Bristol City game in the late 1980's (again, I must have been about 8 - I hasten to add City are not, unfortunately, in the Premiership). I needed to use a bathroom so Dad took me to the 'Gents' where I was confronted simply by a 10 foot wall painted black with a gutter of urine running along the bottom. The smell was 'colourful' as was the language around me. It was intense to say the least. How this experience has effected me later personal development I can only guess - Mum certainly didn't approve of me going along. But the violent and abusive behaviour that once embodied watching the game is no longer tolerated and the terraces have been replaced by more manageable and comfortable rows of covered seating (and more hygienic toilets).
Apparently a similar change has occurred in the minor leagues of baseball. In the game programme was a piece about the rise in popularity of Minor League games. Season attendances in every season since 2000 have been placed in the top 10 since the leagues began and in 2006 the current record was set at 41.7 million fans. That's more than the NBA, and more than the NFL and NHL combined, each year. Fifth Third Field in Dayton Ohio has sold out every game since it opened in 2000. But the continuing growth has come since the 1990's and a similar attitude toward the game as has changed football in the UK. And the programme article described a lady faced by a similar toilet experience as my childhood one - it's certainly not like that now. The emphasis has shifted toward entertainment and whilst the minor league game hasn't changed, the crowds have. In family-friendly America this means kids. And lots of 'em.
So whilst the high pitched screaming wasn't so good for my ears, the $9 seat in the third row along the first base line was good for my wallet and got me close to those 90 mph pitches. I have got to say though, even with my uneducated eye, the quality of play wasn't quite up there with, say, the SF Giants. The Lugnuts gave up 4 runs in the first inning and it wasn't looking good. But then South Bend gave up 5 in the second and from there on we cruised to victory (8-5). Highlights from 'the game' for me included a Lugnuts batter snapping his bat over his knee (golfer style) after he struck out with the bases loaded, and the genius sack race 'run' by some 'hefty' women from the crowd between 8th and 9th innings. I was less impressed that they wouldn't refill my plastic beer glass when buying a second and that I HAD to have a new one. Grrr...
Regardless of the quality of play it was a good night. And seemingly the growth of Minor League Baseball is good for the cities in which the teams are located. Oldsmobile Park is leading the much needed regeneration of the waterfront area of downtown Lansing. After the game, the fireworks reflected in the windows of the old Ottawa Power Station (above) that has lain empty for over a decade. Regeneration is needed in Michigan of all places in the States, where the decline of the American auto industry has hit hard. With manufacturing in sharp decline the state and the city need to turn to alternative industries for income and regeneration. The dollars spent in the stadium are now helping to boost the local economy, and give this part of town something to build around for the future. So, let's go nuts!
Models that consider human activity are particularly difficult to ‘close’ because of their consideration of ‘interactive’ kinds. Ian Hacking highlights the distinction between the classification of ‘interactive’ and ‘indifferent’ kinds. Different kinds of people are 'interactive kinds' because people are aware and can respond to how they are being classified. Hacking contrasts the interactive kinds that are often studied in the social sciences with the indifferent kinds of the natural sciences. Indifferent kinds - such as trees, rocks, or fish - are not aware that they are being classified by an observer. This indifference to classification means their behaviour does not change because of it [but see my point at the end of this post].
The representation of interactive kinds potentially results in a ‘looping effect’ that has implications for model closure and validation – socioecological simulation models have the potential to feedback into, and therefore transform, the systems they represent via the conscious awareness of local stakeholders using the model or its results (or participating in the modelling process). If this transformation occurs it is likely that the model will be a less accurate representation of the empirical system than previously. Such a situation implies that a simulation model of a socioecological system may never truly represent that system (if it used by those it represents). Therefore in the case where a model is to be used by those being represented (for decision-making for example) I'd suggest that an iterative modelling process would be most appropriate to ensure continued utility.
[If anyone has any thoughts on how Hacking's kinds relate to the whole Schrödinger's Cat problem I'm all ears - interactive or indifferent?]
