Social « Direction not Destination

Archive for the ‘Social’ Category

Tom Veldkamp: Advances in Land Models

Saturday, January 5th, 2008

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.

This work by James D.A. Millington is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License.

Posted in Ecological, Modelling, Social | Comments Off

What does it mean to 'be' an expert? at RGS-IBG 2008

Wednesday, November 28th, 2007

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.

More conference information here.

This work by James D.A. Millington is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License.

Posted in Academic, Geographic, Political, Social | Comments Off

The Wilderness Ideal

Sunday, August 5th, 2007

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.

Buy on Amazon

This work by James D.A. Millington is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License.

Posted in Academic, Book_Review, Ecological, Economic, Environmental, Landscapes, Philosophical, Photography, Social | Comments Off

Stakeholder Participation and Expertise

Wednesday, July 4th, 2007

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.

This work by James D.A. Millington is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License.

Posted in Academic, Modelling, MyPhD, Social | Comments Off

Alternative Model Assessment Criteria

Sunday, June 24th, 2007

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.

This work by James D.A. Millington is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License.

Posted in Ecological, Economic, Modelling, MyPhD, Social | Comments Off

Recent Twitter Updates

Archive for the ‘Social’ Category

Topics

Archives