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 future is ours, not to predict, but to create."
- Al Gore, 16th June 2008
Hear, hear. Spoken in the context of climate change, this might be interpreted as a slight against Global Circulation Models used by scientists. Rather, I think this should be interpreted as an indication that Gore understands that we need to move past discussions about whether we can use such models to 'prove' whether climate change is actually happening, and instead act to mitigate against undesired change.
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).
This week's edition of Nature devotes an editorial, a special report and an interview to the subject of tropical rainforests and their deforestation. The articles highlight both the proximate causes and underlying driving forces of tropical deforestation, and the importance of human activity as an agent of change (via fire for example), in these socio-ecological systems.
The editorial considers the economics of rainforest destruction, with regards to global carbon emissions. It suggests that deforestation must be integrated into international carbon markets, to reward those countries that have been able to control the removal of forest land (such as India and Costa Rica). Appropriate accounting of tropical rainforest carbon budgets is required however, and the authors point to the importance of carbon budget modelling and the monitoring of (via satellite imagery for example) change in rainforest areas over large spatial extents. Putting an economic price on 'ecosystem services' is key to this issue, and the editorial concludes:
One of the oddly positive effects of global warming is that it has given the world the opportunity to build a more comprehensive and inclusive economic model by forcing all of us to grapple with our impact on the natural environment. We are entering a phase in which new ideas can be developed, tested, refined and rejected as necessary. If we find just one that can beat the conventional economic measure of gross domestic product, and can quantify some of the basic services provided by rainforests and other natural ecosystems, it will more than pay for itself.
The special report focuses on the efforts of the Brazilian government to curb the rate of deforestation in the their Amazonian forests. The Brazilian police force is blockading roads, conducting aerial surveys and inspecting agricultural and logging operations, to monitor human activities on the ground. Brazilian scientists meanwhile are monitoring the situation from space, and have developed methodologies and techniques that are leading the way globally in the remote monitoring of forests. The Brazilian government is a keen advocate of the sort of economic approaches to the issues of rainforest destruction highlighted in the editorial outlined above, and sees this rigorous monitoring as key to be able to show how much carbon they can save by preventing deforestation.
Halting the removal of forest cannot simply be left to carbon trading alone, however, and local initiatives need to be pursued. To ensure the forest's existence is sustainable, local communities need to be able make money for themselves without chopping down the trees - if they can do this it will be their in their interests NOT to remove forest. But developing this incentive has not been straightforward. For example, some researchers have have suggested that as commodity prices for crops such as soya beans have increased (possibly due to increased demand for corn-based ethanol in the US) deforestation has increased as a result. Although the price of soya beans may be a contributing factor to rainforest removal, Ruth DeFries (who will be visiting CSIS and MSU next week as part of the Rachel Carson Distinguished Lecture Series) suggests that it is not the main driver. Morton et al. found that during for the period 2001-04, conversion of forest to agriculture peaked in 2003. This situation makes it clear that there are both proximate causes and underlying driving forces of tropical deforestation. The Nature special report suggests:
If the international community is serious about tackling deforestation, it will probably need to use a hybrid approach: helping national governments such as Brazil to fund traditional policies for enforcement and monitoring and enabling communities to experiment with a market-based approach.
But how long do policy-makers have to discuss this and get these measures in place? One set of research suggests 55% of the Amazon rainforest could be removed over the next two decades, and the complexity of the rainforest system means that a 'tipping point' (i.e., an abrupt transition) beyond which the system might not recover (i.e., reforestation would not be possible). The Nature interview with Carlos Nobre highlights this issue - the interactions of climate change with soil moisture and the potential for fire indicate that the there is risk of rapid 'savannization' in the eastern to southeastern Amazon as the regional climate changes. When asked what the next big question scientists need to address in the Amazon is, Nobre replies that the role of human-caused fire will be key:
Fire is such a radical transformation in a tropical forest ecosystem that biodiversity loss is accelerated tremendously — by orders of magnitude. If you just do selective logging and let the area recover naturally, perhaps in 20–30 years only a botanist will be able to tell that a forest has been logged. If you have a sequence of vegetation fires going through that area, forget it. It won’t recover any more.
As I've previously discussed, considering the feedbacks and interactions between systems is important when examining landscape vulnerabilities to fire. Along with colleagues I have examined the potential effects of changing human activity on wildfire regimes in Spain (recently we had this paper published in Ecosystems and you can see more wildfire work here). However, the integrated study of socio-economic and ecological systems is still very much in its infancy. And the processes of landscape change in the northern Mediterranean Basin and the Amazonian rainforest are very different; practically inverse (increases in forest in the former and decreases in the latter). As always, plenty more work needs to be done on these subjects, and with the potential presence of 'tipping points', now is an important time to be doing it.
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.
Engaging the Future: Forecasts, Scenarios, Plans, and Projects (2007) edited by Hopkins, L.D. and Zapata, M.A.
The future is inherently uncertain. In accepting this we should not be fatalistic suggest the authors of Engaging the Future. Rather, as the title of the book suggests, scholars, planners, public officials, and citizens alike should endeavour to engage the future, creating and shaping it via a continuing process of regional and urban planning. The tools available for us to advance this process are forecasts, scenarios, plans, and projects.
The opening chapter by the editors Hopkins and Zapata sets the tone for the volume, highlighting that these tools are ways of representing, manipulating, and assessing ideas about the future. They allow us not simply to think about the future but also to influence it. Predictions, however, are conspicuous by their absence from Hopkins and Zapata's putative toolbox. This, as Moore discusses in chapter 2, is because of an all too frequent over-reliance on quantitative output from models. Moore complains that the emphasis on using numerical predictions about populations, transport demands, and other regional trends can inhibit creativity, stifle debate, and limit policy alternatives, when predicted futures are regarded as inevitable ones. Thus, numerical predictions can suppress uncertainty rather than engaging and dealing with it effectively.
The alternative approach, developed and explored throughout the remaining chapters, is one that is increasingly reflexive, collaborative, democratic, and consensual. Both the tools that will facilitate this approach and their use in (predominantly American) case studies are presented and discussed. In chapter 3 Grant discusses the use of visioning to improve participation in the planning process, highlighting both the advantages (democratic inclusion) and drawbacks (potential munipulation) of such an approach. Myers (chapter 4) introduces the idea of narratives to examine how individual choices will influence future communities, and stresses that, if quantitative data about the future are to be used, they must be embedded within a story that describes community transformations through time. Narratives are also discussed as tools by which to engage and generate 'reflective conversations' between diverse parts of the public (Cummings, chapter 12) and to highlight multiple views and expectations about the future rather than suppressing them (Zapata, chapter 13).
Chapters 5 (Smith), 6 (Avin), 7 (Harwood), and 11 (Deal and Pallathucheril) all focus on the use of scenarios in planning in business, industrial, regional, and local community contexts. In these contexts, scenarios differ from forecasts as they do not assign any probability or likelihood estimates to their feasibility, and so better able to explore nonstationary processes and their normative implications. By generating scenarios using the input from local stakeholders these authors suggest community concerns, perceptions, and values can be integrated into a formal description of possible futures, helping to build the capacity of a community to plan via education, dialogue, and empowerment.
Isserman, Klosterman, and Hopkins (chapters 9, 10, and 14, respectively) continue the emphasis on the continued need for a shift away from a 'technocratic, mystified' approach toward an 'open, participatory' one. Such a philosophy is consistent with the attitude of the need to 'democratise science' that has been forwarded recently in the United Kingdom, particularly by organisations such as the think tank DEMOS. Echoing those debates about experts and the politics of expertise, Klosterman argues that, despite their technical skills, planners cannot claim any special knowledge about the desirability of given futures, or arguably even their probability of occurring, than ordinary citizens with their lived 'experience expertise' about the changing nature of the region. In turn, Hopkins suggests plans should become `living documents' that are negotiated and support continued deliberation by multiple
This broad message of the book - to accept uncertainty and embrace participatory approaches - resonates with contemporary attitudes across other areas of environmental science and management. Adaptive resource management, for example, is a process of 'learning by experimenting', updating policies and management strategies as more is learnt about the system in hand. Likewise, Funtowicz and Ravetz (1993) have argued that a new form of `postnormal' science that embraces uncertainty, individuals' personal values, and dialogue amongst multiple stakeholders is required to solve the environmental problems arising from applications of 'normal', reductionist science.
However, uncertainty is politically undesirable and participation is not a panacea. Accepting uncertainty is disquieting - embracing it is even more of a challenge. Policy makers are often loathe to accept advice based on uncertainty, and where uncertainty is accepted it is often used to delay (tough) decision making. A pertinent example is political unwillingness to address the suggested causes of potential anthropogenic climate change in certain quarters because of the scientific uncertainty in those processes. Participatory approaches demand both the will and the skill to engage with non-planners. Making the planning process more inclusive is likely to slow it, potentially leading to unforeseen (and unwanted) demands on the planning process and remit. Participatory approaches will demand that planners expand their skill set to learn how to incorporate a variety of perspectives and views into their planning process.
The case studies presented in each chapter show how this might be done, offering practical ways to engage this multiplicity of demands and perspectives. In this light, Engaging the Future will be most useful for, or have most impact upon, students and junior planners. Given the emphasis of the book on wider participation in the planning process it should be read by more than just planners and students however. Well-produced with uncomplicated language, useful figures, and a glossary of planning terms, this book will be accessible and valuable both to the policy makers calling upon the services of planners and to the citizens and stakeholders who will be influenced by the outcomes of their actions.
Private Science & Environmental Governance at the AAG
James Porter, a friend of mine from Geography at King's College London, is co-convening a session at the 2008 Association of American Geographers Annual Meeting to address the issue of the increasing contribution of 'private science' to environmental decision-making and knowledge about the world around us. Sounds like it will be an interesting session - if I actually make it to the AAG next year I'll have to swing by.
Submissions for the session are open until October 21st 2007. Abstracts and PIN numbers (obtained by registering your abstract online) should be sent to James Porter (james.porter at kcl.ac.uk) and Leigh Johnson (leighjohnson at berkeley.edu) Conference information here. Submit your abstract and get your PIN here.
Here's the session details and call for papers in full:
Private Science, Environmental Governance & the Management of Knowledge Association of American Geographers Annual Meeting, April 15-19, 2008 Boston, MA
In the US and UK, new forms of market-based, commercially driven, and politically relevant demands are restructuring the context of scientific research and the social norms and values therein. No longer can academic institutions expect the same levels of public support immortalized by Vannevar Bush; in recent decades we have seen the rapid ascent of private science or science for hire to fill the void. Science is now routinely contracted-out to the private sector to produce a range of products from Climate Forecast Predictions, flood modeling outputs, risk assessments, chemical tests, life-style drugs and myriad other products that find their way into public policy and regulatory decision-making. The appeal of this new form of scientific research is its cost-effectiveness, its embrace of strategic ignorance, and its flexibility in allowing clients to guide the design and outcome of the work produced.
Yet, environmental governance is shaped extensively by the use of scientific knowledge. In the context of governing citizens, regulating private enterprise, and guiding development, what happens when nature and science are conceptualized in terms of their commercial potential? Geographers are uniquely positioned to provide theoretical depth and empirical evidence to answer these questions. We seek papers addressing (though not limited to) the following questions:
How are commercial science, modeling, and assessments done in practice? What is lost and equally gained in this process? What is ignored in these new knowledge productions?
These questions open up room to consider the contested practice of translation: who chooses what is to be translated? Who does the translation? Does the quality of translation impact the nature of knowledge, and if so, how? How might unlikely allies become enrolled in the project?
Can we discern a particular set of preferred methodologies or instruments that are consistently deployed in the performance of private science? Are these characteristic of a particular neoliberal mode of governance?
If private science has come to dominate fact-making about nature, does this entail a transformation from the rule of (bureaucratic) experts? How do these new forms of knowledge gain authoritative status, if at all?
What are the implications for the subjects of governance?
"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 the latest issue of Landscape Ecology, Louis Iverson suggests landscape ecologists have a role in poverty relief. Reviewing Sachs' The End of Poverty: Economic Possibilities for our Time, Iverson believes the book 'should motivate additional research and implementation of principles within landscape ecology into this critical arena' and argues that landscape ecologists'can provide expertise to efficiently use funds to the greatest value and to research sustainable, integrated pathways to development'. After discussing several aspects of the current state of the global poverty problem (poverty statistics, water scarcity, Millennium Development Goals, environmental constraints on development), Iverson suggests landscape ecologists can contribute to these issues by;
Modelling the impacts and possible mitigation of climate change on water and agricultural production, especially in the most vulnerable zones with high levels of extreme poverty
Creating innovative, landscape-level systems for efficient water use, agricultural production, and infrastructure in the zones of extreme poverty
Working towards sustainable management of ecosystems, especially fragile ecosystems, that are deteriorating due to human pressures
Assisting in planning for urban growth that also sustains agriculture productivity using appropriate water, soil, and food management systems
Building models of low-cost but sustainable means of protection against natural or technological disasters, especially storms, floods, and droughts (climate-related disasters)
Designing infrastructure and energy improvements in developing countries with maximum positive human impact and minimum negative environmental impact
Working to better understand the diseases of the poor and spatial and temporal relationships of these diseases
Working to understand how over-consumption and excessive wealth contributes to environmental degradation and poverty elsewhere in the global landscape, and propose/model remedial solutions
Developing partnerships with ecologists, economists, landscape architects, wildlife managers, and land managers in developing countries that make a difference
Seeking out students from poor countries who can provide direct linkages to projects back in their home countries
Assisting in land-use and urban planning efforts where practical and feasible, focusing on improving conditions for slum dwellers
Working to help influence decision-makers to realize that investments toward the goals outlined above are well spent and the right thing to do
More inspiration, if it were needed, to continue this field of research...
Erin (AKA travelorphan) has been offline for a while, but on her return from the field she's made several posts to her blog detailing some of her recent work and the events in Sri Lanka.
The Economist today highlighted some recent work by Dr Thomas Elmqvist of Stockholm University. Using a combination of Landsat satellite imagery and interviews and surveys with locals in Madagascar, they examined whether human population densities or land tenure systems were more important for determining patters of tropical deforestation.
"From the Landsat images they were able to distinguish areas of forest loss, forest gain and stable cover. Different parts of Androy exhibited different patterns. The west showed a continuous loss. The north showed continuous increase. The centre and the south appeared stable. Damagingly for the population-density theory, the western part of the region, the one area of serious deforestation, had a low population density.
This is not to say that a thin population is bad for forests; the north, where forest cover is increasing, is also sparsely populated. But what is clear is that lots of people do not necessarily harm the forest, since cover was stable in the most highly populated area, the south.
The difference between the two sparsely populated regions was that in the west, where forest cover has dwindled, neither formal nor customary tenure was enforced. In the north—only about 20km away—land rights were well defined and forest cover increased. As with ocean fisheries, so with tropical forests, everybody’s business is nobody’s business."
Can we predict the future? Orrin Pilkey and Linda Pilkey-Jarvis say we can't. They blame the complexity of the real world alongside a political preference to rely on the predictive results of models. I'm largely in agreement with them on many of their points but their popular science book doesn't do an adequate job of explaining why.
The book is introduced with an example of the failure of mathematical models to predict the collapse of the Grand Banks cod fisheries. The second chapter tries to lay the basis of their argument, providing an outline of underlying philosophy and approaches of environmental modelling. This is then followed by six case studies of the difficulties of using models and modelling in the real world: the Yucca Mountain nuclear waste depository, climate change and sea-level rise, beach erosion, open-cast pit mining, and invasive plant species. Their conclusion is entitled 'A Promise Unfulfilled' - those promises having been made by engineers attempting to apply methods developed in simple, closed systems to those of complex, open systems.
Unfortunately the authors don't describe this conclusion in such terms. The main problems here are the authors' rather vague distinction between quantitative and qualitative models and their inadequate examination of 'complexity'. In the authors' own words;
"The distinction between quantitative and qualitative models is a critical one. The principle message in this volume is that quantitative models predicting the outcome of natural processes on the surface of the earth don't work. On the other hand, qualitative models, when applied correctly, can be valuable tools for understanding these processes." p.24
This sounds fine, but it's hard to discern, from their descriptions, exactly what the difference between quantitative and qualitative models is. In their words again,
Quantitative Models:
"are predictive models that answer the questions 'where', 'when', 'how much'"
p.24
"if the answer [a model provides] is a single number the model is quantitative"
p.25
Qualitative Models:
"predict directions and magnitudes"
p.24
do not provide a single number but consider relative measures, e.g "the temperature will continue to increase over the next century" p.24
So they both predict, just one produces absolute values and the other relative values. Essentially what the authors are saying is that both types of models predict and both produce some form of quantitative output - just one tries to be more accurate than another. That's a pretty subtle difference.
Further on they try to clarify the definition of a qualitative model by appealing to concepts;
"a conceptual model is a qualitative one in which the description or prediction can be expressed as written or spoken word or by technical drawings or even cartoons. The model provides an explanation for how something works - the rules behind some process" p.27.
But all environmental models considering process (i.e. that are not empirical/statistical) are conceptual, regardless of whether they produce absolute or relative answers! Whether the model is Arrhenius' back of the envelope model of how the greenhouse effect works, or a Global Circulation Model (GCM) running on a Cray Supercomputer and considering multiple variables, they are both built on conceptual foundations. We could write down the structure of the GCM, it would just take a long time. So again, their distinction between quantitative and qualitative models doesn't really make things much clearer.
With this sandy foundation the authors examine suggest that the problem is that the real world is just too complex for the quantitative models to be able to predict anything. So what is this 'complexity'? According to Pilkey and Pilkey-Jarvis;
"Interactions among the numerous components of a complex system occur in unpredictable and unexpected sequences." p.32
So, models can't predict complex systems because they're unpredictable. hmm... A tautology no? The next sentence;
"In a complex natural process, the various parameters that run it may kick in at various times, intensities, and directions, or they may operate for various time spans".
Okay, now were getting somewhere - a complex system is one that has many components in which the system processes might change in time. But that's it, that's our lot. That's what complexity is. That's why environmental scientists can't predict the future using quantitative models - because there are too many components or parameters that may change at any time to keep track of such that we couls calculate an absolute numerical result. A relative result maybe, but not an absolute value. I don't think this analysis quite lives up to it's billing as a sub-title. Sure, the case-studies are good, informative and interesting but I think this conceptual foundation is pretty loose.
I think the authors' would have been better off making more use of Naomi Oreskes' work (which they themselves cite) by talking about the difference between logical and temporal prediction, and the associated difference between 'open' and 'closed' systems. Briefly, closed systems are those in which the intrinsic and extrinsic conditions remain constant - the structure of the system, the processes operating it, and the context within which the system sits do no change. Thus the system - and predictions about it - are outside history and geography. Think gas particles bouncing around in a sealed box. If we know the volume of the box and the pressure of the gas, assuming nothing else changes we can predict the temperature.
Contrast this with an 'open' system in which the intrinsic and extrinsic conditions are open to change. Here, the structure of the system and the processes operating the system might change as a result of the influence of processes or events outside the system of study. In turn, where the system is situated in time and space becomes important (i.e. these are geohistorical systems), and prediction becomes temporal in nature. All environmental systems are open. Think the global atmosphere. What do we need to know in order to predict the temperature in the future in this particular atmosphere? Many processes and events influencing this particular system (the atmosphere) are clearly not constant and are open to change.
As such, I am in general agreement with Pilkey and Pilkey-Jarvis' message, but I don't think they do the sub-title of their book justice. They show plenty of cases in where quantitative predictive models of environmental and earth systems haven't worked, and highlight many of the political reasons why this approach has been taken, but they don't quite get to the guts of why environmental models will never be able to accurately make predictions about specific places at specific times in the future. The book Prediction: Science, Decisions Making, and the Future of Nature provides a much more comprehensive consideration of these issues and, if you can get your hands on it, is much better.
I guess that's the point though isn't it - this is a popular science book that is widely available. So I shouldn't moan too much about this book as I think it's important that non-modellers be aware of the deficiencies of environmental models and modelling and how they are used to make decisions about, and manage, environmental systems. These include:
the inherent unpredictability of 'open' systems (regardless of their complexity)
the over-emphasis of environmental models' predictive capabilities and expectations (as a result of positivist philosophies of science that have been successful in 'closed' and controlled conditions)
the politics of modelling and management
the need to publish (or at least make available) model source code and conceptual structure
an emphasis on models to understand rather than predict environmental systems
any conclusions based on experimentation with the model are conclusions about the structure of the model not the structure of nature
I've come to these conclusions over the last couple of years during the development of a socio-ecological model, in which I've been confronted by differing modelling philosophies. As such, I think the adoption of something more akin to 'Post-Normal' Science, and greater involvement of the local publics in the environments under study is required for better management. The understanding of the interactions of social, economic and ecological systems poses challenges, but is one that I am sure environmental modelling can contribute. However, given the open nature of these systems this modelling will be more useful in the 'qualitative' sense as Pilkey and Pilkey-Jarvis suggest.
When 'what is best' doesn't align with 'what I want', making the right decision is hard. We need to find ways of working out how make these options align as closely as possible.
Jared Diamond's point in Collapse is that the fate of contemporary society is in our own hands. I read and wrote about the introductory chapter to a while ago. Eventually I did read the whole book, though as Michael Kavanagh points out;
"You could read the introduction and the last few chapters and get the point. But then you'd miss out on what Jared Diamond does best: tell stories."
Kavanagh is right; as I've talked about before here storytelling is an important way of understanding the world. William Cronon has suggested narratives of global change that offer hope are needed for us to tackle the (potential) problems that contemporary society faces. Most of Diamond's stories about the fate of previous societies don't offer much hope however - most collapsed and the only modern example of positive action on the environment is Iceland. Diamond's identifies five contributing factors to societal collapse:
"... climate change, hostile neighbours, trade partners (that is, alternative sources of essential goods), environmental problems, and, finally, a society's response to its environmental problems. The first four may or may not prove significant in each society's demise, Diamond claims, but the fifth always does. The salient point, of course, is that a society's response to environmental problems is completely within its control, which is not always true of the other factors. In other words, as his subtitle puts it, a society can "choose to fail."
Diamond emphasises the need for individual action - for a bottom-up approach to make sure that we choose not to fail. Kavanagh suggests the implications is that
"in a world where public companies are legally required to maximize their profits, the burden is on citizens to make it unprofitable to ruin the environment -- for an individual, a company, or a society as a whole."
Others suggest more dramatic action is needed however. Richard Smith suggests that this 'market meliorist strategy' won't be enough. Smith contrasts the bottom-up decision-making of the New Guinea villages that Diamond uses as a potential model for contemporary decision-making with that of contemporary capitalist society. Whereas the New Guinea villages' decision-making process takes into account everyone's input:
"...we do not live in such a 'bottom-up' democratic society. We live in a capitalist society in which ownership and control of the economy is largely in the hands of private corporations who do not answer to society. In this system, democracy is limited to the political sphere. ...under capitalism, economic power is effectively monopolized by corporate boards whose day-to-day requirements for reproduction compel their officers to systematically make 'wrong' decisions, to favour the particular interests of shareholders against the general interests of society."
Smith's solution? As the global issues contemporary society faces are so interconnected and international, international governance by a "global citizenry" is required. Critics to this approach are likely to be many, but whether it will be enough for individual consumers to "make it unprofitable to ruin the environment", or whether the we develop a "global citizenry", the ultimate question here seems to be 'Are we prepared to change our lifestyles to ensure the survival of our contemporary (global) society'?
With the "End of Tradition" in western societies (i.e. life is no longer lived as fate in these societies) maybe the future of society really is in our hands as Diamond suggests. On the other hand, as Beck points out, as contemporary problems are due to dispersed causes (e.g. individuals driving their car to work everyday) responsibility is rather easily evaded and some form of global decision-making would be useful. To me the latter seems unlikely - those with power are unlikely to give it up easily. The 'global' institutions we currently have are frequently undermined by the actions of individual states and leaders. The power to change society and lifestyles (in the west at least) now lies with individuals. But with power comes a responsibly which, on the whole, currently we individuals are shirking.
The changes my and the next generation will need to make will have to go further than simply throwing our glass, paper and plastic in different boxes. There are small ways in which we can save ourselves money whilst helping the environment and they all add up. But sea changes in lifestyle are likely to be required. Governments will not make people do that, and have no right in a democracy. They can cajole via taxation (if they do it right) but they can't force people to change their lifestyles. People must make those changes themselves because they want to make it profitable to sustain contemporary society. The problem is it's very difficult to do what's best when it doesn't align with what you want. It can hurt. Findings ways of making the two align will become increasingly important. Often the two will not align and it will be necessary to take individual responsibility by accepting there will be a degree of pain. But once this responsibility has been accepted, the next step can be taken - working to minimise the pain whilst ensuring people get as close to what they want as possible.
Inevitably, I think modelling may have something to offer here. Just as Diamond uses evidence of historical environmental, technological and social change to discuss and tell stories about past problems we might use models to discuss and tell stories about potential problems we might face in the future. Simulation models, if appropriately constructed, offer us a tool to reconstruct and examine uncertain landscape change due to environmental, technological and social change in the future. Further, simulation models offer the opportunity to examine alternative futures, to investigate traps that might lie in wait. Just as we should learn from past histories of landscape change (as Diamond suggests), we should be able to use simulation models to construct future histories of change in our contemporary landscapes.
These alternative 'model futures' are unlikely to be realised exactly as the model says (that's the nature of modelling complex open systems), and may not contain the details some people might like, but if they are useful to get people around a table discussing the most sustainable ways of managing their consumption of natural resources then they can't be a bad thing. Modelling offers insight into states of potential future environmental systems given different scenarios of human activity. At the very least, models will provide a common focus for debate on, and offer a muse to inspire reflection about, how to align 'what I want' with ,'what is best'.
