Risk, uncertainty, and value judgements in science policy

Yesterday my colleagues and I at Michigan State University and Kellogg Biological Station had a reading group to discuss Pielke's The Honest Broker. We read chapters 4-6 for today, which are titled, "4) Values; 5) Uncertainty; and 6) How science policy shapes science in policy and politics."

We talked about whether science is a good tool in making decisions. Certainly it can be good for informing decisions, such as if there's a tornado coming and you need to know whether you should evacuate. Unfortunately, as we saw in one of my previous posts, sometimes scientific assessments of risk and uncertainty do NOT translate well into action. Pielke agrees with this perspective. He thinks that science just adds smoke and mirrors to debates that are really about core values. So unless the situation under debate is one with low uncertainty and highly shared values (a tornado is coming, we should evacuate), we need more recognition of the underlying values of a debate (see: the climate change debate).

Pielke repeatedly refers to two works by Dan Sarewitz, who is one of my professors at Arizona State and regarded by many as a science policy guru. The first article is "How science makes environmental controversies worse" (2004). The second is "Science and Environmental Policy: An Excess of Objectivity" (2000). Both are worth a thorough reading: one thing I've discovered in grad school is that I sometimes read the same article months, or a year, apart, and find revelatory new nuggets of knowledge each time I read it.

The "Excess of Objectivity" book chapter is an insightful commentary on how science can actually impede the political process, by focusing on always disputable and uncertain facts while ignoring underlying value conflicts in highly politicized environmental issues. The “excess of objectivity” refers to the incompatibility of multiple fields of science, and how while each field claims objectivity, they drive controversy and muddy the political waters.

"How science makes environmental controversies worse" makes the same core argument, using a set of different examples from the 2000 election results, to climate change, to genetically modified food (another good case study is the debate over nuclear waste: see this editorial). This discussion reminded me of an article I read during my first weeks of grad school, "Value Judgments and Risk Comparisons. The Case of Genetically Engineered Crops" (2003) by Paul Thompson, who is an environmental and agricultural philosopher at MSU.

I wrote up an analysis of it that I think highlights the issues of value, risk, and uncertainty in environmental controversies pretty well: Thompson focuses on the inherent value judgments that scientists make about genetically engineered (GE) crops and environmental risk. He aims to identify the values behind the GE debate, rather than taking a philosophical or scientific position in the debate. He focuses on a relatively small aspect of this debate, which are claims for and against a comparative evaluation of the environmental risk of GE vs. traditional (non-GE) crops. This is the standard metric used by scientists and federal agencies to assess the risk of GE crops. Thompson’s argument is that risk assessments are inherently based on value-based judgments; the science itself cannot settle a claim about environmental risks.

He shows that the current regulatory system ironically puts the burden of proof on anti-GE activists, who are “in the position of needing to justify special treatment for this class of plants” (emphasize added, Thompson, 2003, p. 11). This gap charges the largely non-scientific public with demonstrating the scientific credibility of their value system, against the grain of the values held by the scientific community, which of course causes further problems on multiple levels. Thompson identifies several other challenges in the regulation of GE crops based on the current framework.

Risk assessments, especially environmental risk assessments, depend on value-based judgments of how much and what types of risk are “acceptable,” despite attempts to scientifically quantify this risk. The definitions of risk by the scientists and activists are essentially incompatible for comparing the risks of GM vs. non-GM crops, or even defining the concept of environmental risk. This highlights very clearly that science, rather than aiding the decision-making process, can complicate and add uncertainty to political debates.

On a related note, I'm headed to Boston today to attend the Science and Democracy Network conference! I'm really excited to talk to like-minded scholars about our work, and make some great connections.

4) Science and Public Value

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A friend of mine asked about my last post on the "co-production" of knowledge, "who then 'owns' the research or is it always a public resource after co-production?”

Great question, and one that scholars have been struggling with especially in light of patents on genes and other biotechnology, such as genetically modified foods. This is generally referred to as "intellectual property" or "intellectual property rights" (IPR). Patents are supposed to protect the inventor and fuel innovation, but the case lately has been an increasingly convoluted fight over patent law, with "patent sharks" prowling for unclaimed discoveries that they can later sue companies for using. The figure below demonstrates some of the craziness in just smart phones:

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But what happens when a drug company asks an indigenous tribe about their medicinal plants, and then goes on to patent and produce the medicinal compound? Or when patients donate their DNA to a study, only to be charged later for a test or treatment because a biotech company has patented the blueprint of the gene that causes cancer? Who should "own" that knowledge?

These are questions that modern governments are dealing with for the first time due to technological advances. Public research organizations are dealing with them as well: for example, the public agricultural research system that is largely responsible for last century's "Green Revolution" now must be more cautious about what agricultural technologies they can use, because of all the patents. Richard Jefferson is someone who understands this problem and is creating innovative solutions that benefit poor countries. He started a company that promotes "open source biology" by patenting discoveries in agricultural science, but then making those discoveries public. Some excerpts from this paper:

Most critically, we must democratize these abilities, both to measure and to respond, in order to diversify agro-ecosystems and environments and decentralize the problem-solving capability. We will achieve this by fostering scientific method and harnessing local knowledge and commitment in communities that have previously been ignored or treated as passive recipients of help. (p. 38)

At the start of the twenty-first century, science is at a critical juncture. Four centuries of inquiry, discovery, and invention have created a base of knowledge that has the potential to provide people everywhere, in all circumstances, with nourishment, improved health, and longer life. But the institutional mechanisms that ostensibly exist to encourage the application of science to practical problems are today hindering that very process. The norms that have evolved around gate-keeping have created new clergy, new impediments and new inefficiencies. Without a systemic change, science’s promise will not be available for those who most need it, and the promise of a truly diverse, robust and fair innovation culture may elude us. (p. 40)

This all boils down to a question of science and the public good. The "social contract of science" is an unspoken agreement that science, in the end, will produce public good. As the environmental movement often points out, science sometimes produces public bads. Or it doesn't produce the hoped-for goods. For example, “there are 6000 patents that invoke ‘plant breeding’ and ‘drought resistance’ yet none of them has yet resulted in an improved commercial variety” (Clark et al., p. 10). Agricultural extension programs do unique boundary work that is affected by both private and public interests. The private sector is crucial to developing new, useful technologies for farmers. Agricultural research institutions must increasingly embrace their role as a mediator between the private realm of gene patents and their goal of developing agricultural technologies for the public good.

More broadly, many of my colleagues at ASU's Consortium for Science, Policy, and Outcomes are working on this issue of science and public value. A recent issue of the journal Minerva featured their work, and a short review is available here. Also, this very-readable report by a British think-tank called Demos takes a Science & Technology Studies perspective on this topic. They tackle head-on provocative questions that I've been exploring throughout this blog:

Science has major social benefits and thus ‘public value’. Yet crucially, as recent controversies have underlined, this value cannot be assumed and taken as automatic, no matter what scientific research is done, or under what conditions. We need therefore to shift from noun to adjective, by asking not only: what is the public value of science? But also, what would public value science look like? (p. 29)

3) Public participation in science: co-production of knowledge

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An important theme of Science & Technology Studies is the "co-production of knowledge." When I first started my graduate studies at ASU, this word threw me for a loop because it packs so much meaning into one phrase, but I guess that's the purpose of academic jargon! The co-production of knowledge means, according to Sheila Jasanoff, "the proposition that the ways in which we know and represent the world (both nature and society) are inseparable from the ways we choose to live in it" (Jasanoff, 2004, p. 2).

Jasanoff's definition incorporates how knowledge shapes both science and social order (sometimes simply described as the co-production of science and policy or society). How we represent knowledge-- through charts and graphs, DNA samples, lie detector tests, brain scans, environmental impact assessments, maps, etc.-- has implications for not just science, but society. For example, a map of climate change vulnerability can show the scientific results of a study, but it also holds implicit values and political implications.

The creators of this climate change vulnerability map chose not to include most developed countries in their assessment, which certainly has impacts of how we view climate change. For example, climate change is sometimes viewed as a problem mostly facing developing countries, and this map reinforces this. Co-production of knowledge and social order goes beyond just media representations of science; it is deeply important for our political system, and how we make decisions based on science.

We often think of science as a top-down, self-regulating hierarchy of experts. But when science gets used in decision-making, it must conform to the ideals of democracy. Science cannot dictate policy decisions, but can be a useful political tool. Thus, incorporating the "co-production" perspective of science and society can make the role of science more clear in these situations, rather than the muddled role it currently takes. For example, Roger Pielke Jr. shows how the Intergovernmental Panel on Climate Change (IPCC) ignored the "co-production of knowledge" and instead engaged in what he calls "stealth advocacy" of policy. If the IPCC was more upfront about the political implications of their climate change assessments, they would act as more of an "honest broker" of the co-production of science and policy.

Several scholars have examined climate change knowledge from a co-production perspective. Vogel et al. (2007) examine the connections between co-production and science communication. Commenting on many of the topics previously discussed in this blog, they use the case study of food security and climate vulnerability assessments in southern Africa, and how crossing the science-practice boundary through stakeholder engagement resulted in more useful assessments that could be utilized by local organizations and governments. By recognizing the needs of stakeholders, the knowledge gained from these assessments can be used in more democratic ways.

Lemos and Morehouse (2005) look at the case study of NOAA's regional integrated science assessment (RISA) program (coincidentally, the Great Lakes basin now has a GLISA program). The Southwest RISA used a process of stakeholder dialogues to produce a regional assessment of climate change impacts that was relevant and useful to end users. The authors write,

"Co-production of science and policy in the context of integrated assessment activities requires substantial commitment to the three components we have identified: interdisciplinarity, stakeholder participation, and production of knowledge that is demonstrably usable." (Lemos & Morehouse, 2005, p. 66)

In this case, the RISA aimed to produce scientific knowledge about climate change that would be useful for decision-makers like farmers and policy-makers. Without the stakeholder participation, the researchers would not have known how the information would be applied, and how to shape their research based on this. For a more detailed description of other RISA climate change programs, see this report.

For the climate change and agriculture project I'm working on with Michigan State University Extension and Kellogg Biological Station, we are trying to follow the model of stakeholder participation from the start. This is based partly on the work of our colleagues in the Southeast climate RISA and participatory process used to create their AgroClimate website. There are also great examples of using participatory focus groups and community dialogues in forestry and bioethics. Personally, I can tell you that something I've already learned is how important social science research is to this process. The natural sciences can tell us a lot about our world, but social science helps tell us what decision-makers need for knowledge and support. The results are often surprising and definitely eye-opening for those of use entrenched in academia. And this is why co-production of knowledge is important! Recognizing that the process of knowledge production (aka science) is just as important as the end results, and that how the end results are used is often pervasively social and political, STS can lend us some valuable insights for practical results.

Science policy communication failure costs lives

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A recent issue of Science magazine features a news article about seven scientists in Italy who are facing manslaughter charges for not predicting the danger of an earthquake that killed 308 people. The scientists were part of a risk committee of earth scientists who testified that incipient tremors were not evidence of an oncoming earthquake in 2009. According to Science, “They agreed that no one can currently predict precisely when, where, and with what strength an earthquake will strike” (3 June 2011, p. 1135). These are all accurate statements, from a scientific point of view. But the problem lies in translating these statements for decision-makers and stakeholders, which includes people in the town of L’Aquila, Italy.

The lead scientist “maintained that he and his scientific colleagues had a responsibility to provide the ‘best scientific findings’ and that it is ‘up to politicians’ to translate the scientific findings into decisions” (Science, 3 June 2011, p. 1136). This is the linear model of science policy at its worst, literally costing lives because of the mismatch of science and policy risk management paradigms, or as Cash et al. (2006) describe, the “loading dock” model of simply delivering scientific results and hoping that the public sphere will pick them up and use them. To the scientists, risk and uncertainty are quantifiable metrics that are difficult to translate into social action. To decision-makers and the public, risk is a socially mediated, multidimensional value that depends on more than just probabilities. Uncertainty has been a traditional sticking point in earth science and policy topics such as climate change. However, Cash et al. (2006) demonstrate how bringing together scientists and decision-makers from the beginning helped improve the utility of climate models for end-users. They write, “Scientists began to understand that managers were comfortable making decisions under uncertainty, and managers began to understand the concerns scientists had about making scientific claims in the face of uncertainty” (Cash et al., 2006, p. 482). This was clearly not the case with the Italian scientists and decision-makers.

At first glance, this case provokes outcry from scientists afraid of losing the public’s trust and being put on trial, literally. While it may be presumptuous to actually put scientists on trial for a failure to dialogue with decision-makers, this puts into question the implicit “social contract of science” that has justified basic scientific research since the end of WWII. Sheila Jasanoff told a group of ASU graduate students last spring that, “Scientists have become arrogant, and have not explained to the people why they deserve support... The Enlightenment was not a historical event. It is a process, a mission, a continuous duty to explain yourself” (personal communication, 11 February 2011; not an exact quote, but very close). Jasanoff lays out an alternative claim to the linear model of science policy that she calls “technologies of humility” (2003). In contrast to calls for “more science” to reduce uncertainty, Jasanoff writes that, “what is lacking is not just knowledge to fill the gaps, but also processes and methods to elicit what the public wants, and to use what is already known” (2006, p. 240). The abstract of her paper states, “governments should reconsider existing relations among decision-makers, experts, and citizens in the management of technology. Policy-makers need a set of ‘technologies of humility’ for systematically assessing the unknown and the uncertain” (Jasanoff, 2003, p. 223). Jasanoff and other Science and Society scholars have been writing about the failures of the linear science policy model in predicting risk since the 1980s, when the risk-management paradigm began to crumble in the wake of seemingly “unpredictable” human-technology-based disasters like Chernobyl. Today we face critical policy issues from climate change to toxic chemicals that fundamentally depend upon and understanding of environmental science, but just understanding the science is not enough. We need a new model of science policy that incorporates the needs of decision-makers and stakeholders from the start, not after it’s too late.

Sources:

Cartlidge, E. (3 June 2011). “Quake Experts to Be Tried For Manslaughter.” Science, 332, p. 1135-1136.

Cash, D.W., Borck, J.C., & Patt, A.G. (2006). “Countering the Loading-Dock Approach to Linking Science and Decision Making.” Science, Technology, & Human Values, 31, p. 465-494.http://sciencepolicy.colorado.edu/students/envs_5100/Cashetal2006.pdf

Jasanoff, Sheila (2003). “Technologies of Humility: Citizen Participation in Governing Science.” Minerva, 41. 223-244.http://sciencepolicy.colorado.edu/students/envs_5100/jasanoff2003.pdf

Further reading:

Sarewitz, D., Pielke, Jr., R.A., & Byerly, R. (editors) (2000). Prediction: Science, Decision Making and the Future of Nature. Washington, DC: Island Press. Available at: Google books, Amazon.com

Bioethics and community dialogues

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Today you get a break from climate change in favor of bioethics. I had the chance to learn from some distinguished bioethics scholars from MSU and the University of Michigan, so I’d like to share some of what I learned!

The theme of today’s “words of wisdom” session was community engagement in genetics policy. We often think of elite scientists and policy-makers as the ones who set health policy, but scholars (including philosophers and social scientists) are increasingly realizing the importance of engaging the public in these science policy issues. This goes beyond just educating the public (remember the “loading dock” model from my last blog?). Some engagement models that I learned about are called “rational democratic deliberation,” “community-based participatory research,” and “community-based dialogues.”

Including community members in a dialogue process about genetic policy was spurred by Francis Collins, who led the Human Genome Project and is now the head of the National Institutes of Health. Collins realized that research on genetics also needed to incorporate the “ethical, legal, and social implications” of this research and how it is used in society. The bioethics researchers at UM and MSU specifically wanted to elucidate some common moral values about reproductive technologies and policies, such as whether genetic testing should be mandatory. First they wanted to hear from a representation of diverse value perspectives on genetic policy, including Right to Life and disability advocates. They held community dialogues on the genetics policy issues and said that even these polarized views has respectful discussions.

Bioethicists are especially aware of the legacy of distrust of genetic research in minority communities, because of past injustices such as the Tuskegee experiments, the eugenics movement, and a more recently uncovered story of Henrietta Lacks. So the bioethicists decided that they didn’t just want diverse interests represented in their discussions; the next step was to bring together communities of color for dialogues. The bioethicists worked with existing African American and Latino community-based organizations (CBOs), and they let the CBOs choose who would participate, where they would hold the sessions, etc. The existing organizational structure of the CBOs also meant that people could more easily decide who and what to advocate once the dialogue sessions were done (the groups actually met with policy-makers in Washington, DC). Information from all of the dialogue sessions was written into academic and policy reports, and community representatives were involved in the writing and review process. A full report of their study is located here, but you need a journal subscription to access it.

One of the great things about these public dialogues about science policy is that people often change their views once they start to consider the complexity of the situation, and to form rational moral values even on highly controversial topics. But there are certainly challenges to this process: issue advocacy and deeply entrenched political polarization can hinder the dialogue process, community dialogue groups can lack legitimacy and credibility in policy settings (or fail to distinguish themselves from other “interest groups”), and especially when working with communities of color, project administrators must be constantly aware of issues of equality between the participants and academic researchers.

The question that I was left with (and that I asked and we briefly discussed) was how to bring this information back to scientists. The community dialogues obviously brought up a lot of discussion about what directions and limits there should be to genetic research: especially with regards to stem cells, cloning, biotechnology and prenatal genetics. It wasn’t really the purpose of this study to bring the dialogue results back to scientists, or to have the community groups involved in shaping scientific agendas, but this seems like an area ripe to explore in the future. “Molding the pipeline into a loop” is a good example of this.

Currently, community members and issue advocates are represented on grant/research review boards and bioethics committees for public research. There is a general faith, even in marginalized communities, that investing in more public research, in combination with government regulations on the limits of research, will result in societal benefits. But some science policy and STS scholars warn about what might happen when advocates don’t see results. What do you think? To apply this to my work with MSU Extension/Kellogg Biological Station, what would happen if we find out that climate models aren’t useful to farmers, or that we can’t solve the problem of climate change using science? This is hypothetical- but we have certainly realized that there are limits to science, unintended consequences, and that stakeholders face a variety of opportunities and constraints in actually using scientific information for decision-making.

2) Science-practice and science-policy boundaries

Image source: Alice Rose Bell, 2010.

My first few posts have been focused on science for decision-making and innovation. This next section will highlight the role of mediators between the spheres of science and policy, or what STS scholars refer to as “boundary organizations.” Like my first post, this will be a brief review of the literature, and in later posts I’ll look at specific examples of boundary organizations at work.

The concept of “boundary organizations” is extremely relevant to- you guessed it- agriculture extension work! The traditional model of extension, of course, is the top-down, “loading dock,” basic-to-applied research model. But complex problems like climate change pose new challenges for scientists, farmers, and extension educators. This is why some scholars are working to reshape this model. Extension is a mediator between science, policy, and stakeholders. It is not simply a provider of information, but rather a decision support system. Incorporating feedback from farmers and other stakeholders is important to the mission of university extension programs, and critical for addressing global challenges of the 21st century.

David H. Guston, William Clark, Terry Keating, David Cash, Susanne Moser, Clark Miller, Charles Powers. (2000). “Report of the Workshop on Boundary Organizations in Environmental Policy and Science.” Global Environmental Assessment Project. http://www.hks.harvard.edu/gea/pubs/huru1.pdf

• In 2001, the journal Science, Technology, & Human Values ran a special issue on so-called “boundary organizations” (see end of this blog for full references). Dave Guston is renowned scholar of political science and science policy theory. His idea of boundary organizations is that the realms of science and policy are not entirely separate; there are actors who span and negotiate between the two. This report contains a summary of all of the articles published in that journal. Many of the examples of “boundary spanners” deal with issues related to agriculture and climate change. David Cash shows extension’s role in negotiating water use in the U.S. High Plains states. He discusses the history of extension and multiple scales of the science/policy interface in this case. Clark Miller studies the politics of climate science. In this paper he argues that the international “climate regime” doesn’t fit neatly into the boundary organization model, and instead he proposes the term “hybrid management” for the function of organizations like the IPCC.

Cash, D.W. et al. (2003). “Knowledge systems for sustainable development.” Proceedings of the National Academy of Sciences. http://www.pnas.org/content/100/14/8086.full.pdf+html

• This article ties together some of the theoretical concepts on boundary organizations presented by Guston and others with a set of case studies of global environmental development. The authors represent both STS and “sustainability science” scholars, led by W.C. Clark. It also discusses science policy communication, in which they identify salience, legitimacy, and credibility as the main themes in providing useful information.

Cash, D.W., Borck, J.C., & Pratt, A.G. (2006). “Countering the Loading-Dock Approach to Linking Science and Decision Making.” Science, Technology, & Human Values, 31, p. 465-494. http://sciencepolicy.colorado.edu/students/envs_5100/Cashetal2006.pdf

• David Cash has another great example of boundary organizations and how they work. He proposes four mechanisms for them to work: convening (bringing people together), translation (communicating between different audiences, for example, science and the public), collaboration (working on a project with multiple interests represented), and mediation (finding mutual ground in conflicts). The “loading-dock approach” is a poor model of communication: it involves just getting the data out there, but not doing any follow up or getting any feedback. Cash et al. use the case study of communicating climate forecasts to show how participation from stakeholders is crucial to the 2-way communication between science and decision-makers. This is sometimes referred to as the “co-production” of knowledge (although other STS scholars use to work co-production in a different way, meaning the co-evolution of scientific knowledge and social systems/order).

Breuer, Norman, Clyde Fraisse, and Peter Hildebrand (2009). “Molding the pipeline into loop.” Journal of Service Climatology.

http://www.journalofserviceclimatology.org/articles/2009/Breuer-2009-JSC.pdf

• Our friends down south are blazing the path for extension’s role in helping farmers adapt to the impacts of climate change. This particular article describes how they used participatory dialogue with farmers and extension educators to create a website to provide information about regional crop outlooks based on climate forecasts. They call this a decision support system. For more information, see their 2010 report here. And for more comments on why agricultural extension needs to move beyond the linear model, read John Gerber's 1994 article here.

[Full articles from the STHV 2001 issue that have free access:]

Guston, David (2001). “Boundary Organizations in Environmental Policy and Science: An Introduction.” Science, Technology, & Human Values 26. http://www.cspo.org/_old_ourlibrary/documents/boundaryorgs.pdf

Cash, David W. (2001). “‘In Order to Aid in Diffusing Useful and Practical Information’: Agricultural Extension and Boundary Organizations.” Science, Technology, & Human Values 26. http://belfercenter.ksg.harvard.edu/files/In%20order%20to%20aid%20in%20diffusing%20useful%20and%20practical%20information%202000-10.pdf

Miller, Clark (2001). “Hybrid Management: Boundary Organizations, Science Policy, and Environmental Governance in the Climate Regime.” Science, Technology, & Human Values 26. http://www.cspo.org/_old_ourlibrary/documents/hybrid_management.pdf

I hope this blog post on boundary organizations was useful to you! If you have any questions, recommendations, or if something from the articles is not clear, please leave me a comment!

Agricultural innovation: the threat of global climate change

Image source: Josh Haner/New York Times

A front-page feature of the New York Times this weekend is all about global food and the predicted impacts of climate change. The need for innovation in a warming, higher-CO2 planet was one of the key themes. The take-home message was that the impacts of climate change will be worse for agriculture than previously predicted. Extreme weather events, such as floods, droughts and increased weather variability are potential "deal breakers" for entire crops. The more gradual aspects of climate change, such as average temperature increase and sea level rise, may be more manageable, but disasters exacerbate crop losses through a convergence of environmental and economic factors.

So what do disasters have to do with innovation? According to the New York Times and many others, we need to innovate crops that can withstand these weather extremes. The article states,

Leading researchers say it is possible to create crop varieties that are more resistant to drought and flooding and that respond especially well to rising carbon dioxide. The scientists are less certain that crops can be made to withstand withering heat, though genetic engineering may eventually do the trick.

A lot of the narrative about how agriculture can respond to a changing climate relies on this scientific concept: using plant breeding and biotechnology for better, more resilient crops. Plant breeding, or selecting crops based on the positive traits of the parent generations, led to some of the fundamental advances in crop science during the past century. Check out this graphic for a synopsis of the gains made in food production during the Green Revolution (coincidentally, produced by a colleague of mine at ASU). In fact, during the "Green Revolution" that started in the 1940s and continued to very recently, some plant breeders were international celebrities, especially in the science policy and international development circles. However, other economic and political factors pushed for more fertilizer, mechanized labor, and irrigation. Without these "packages" of technologies, the better seeds alone would not have done much.

So what are some fundmental lessons we can learn from innovation during the Green Revolution to apply to innovation in a post-normal climate?

1) Agricultural innovations are shaped by a variety of factors, not just "fundamental breakthroughs." These include private industry, public agricultural research, economic, and political factors. Two famous Green Revolution agricultural economists, Hayami and Ruttan, studied the agricultural history of the U.S. and Japan and created a theory called the "induced innovation hypothesis." This hypothesis explains how technological change is based on economic factors of supply and demand, rather than spontaneous discoveries (Ruttan, 2006a). For example, Hayami and Ruttan demonstrated how agricultural technologies in Japan were based on a “biological” innovation track, while the United States was more focused on “mechanical” innovations (Ruttan, 2006a). Factors such as availability of land and cost of inputs (fertilizer, labor, and mechanical power) influenced the technological trajectory of each country (Ruttan, 2006a). Institutional factors (policy, research systems, and other social rules and organizations) also play a role in innovation, and these institutions respond to supply and demand forces to innovate themselves (Ruttan & Hayami, 1984; Ruttan, 2006b).

2) Supply and demand factors will likely influence how different agricultural innovation systems respond to climate change. However, unlike most agricultural inputs, “climate is not priced, so it is difficult to provide clear examples of climatic inducements to agricultural research based on price signals” (Easterling, 1996, p. 19). Although climate does not have a market price, prevailing policies seek to reduce greenhouse emissions. Therefore climate mitigation will require farmers to adapt to these economic limits as well as a changing climate (Smith & Olesen, 2010).

3) Let's not view plant breeding and biotechnology as a panacea to climate change. There are many other factors in global agriculture that are not related to climate change. Improved plant varieties can be difficult to translate into direct benefits, especially in developing countries, because farmers must use new management techniques and buy into the higher-input system. This is why extension education is critical for agricultural development, in all parts of the world. In parts of sub-Saharan Africa, farmers would just benefit from using more fertilizer, which is the main barrier to higher crop yields (Vitousek et al., 2009). However, fertilizer prices are exorbitantly high (Otsuka & Kijima, 2010). Thus, technology is not the easy answer that we wish it were. Otsuka and Kijima write that, "we should not overlook the fact that rice yield increased by roughly 50% and non-rice yield increased by nearly 100% in SSA over the last three decades since around 1970 despite the absence of major technological breakthroughs" (Otsuka & Kijima, 2010, p. ii66). Even in the Green Revolution, it was not a straightforward path from science to technology to application.

Sources:

Easterling, W.E. (1996). Adapting North American agriculture to climate change in review. Agricultural and Forest Meteorology, 80, l-53.

Gillis, J. (4 June 2011). "A Warming Planet Struggles to Feed Itself." New York Times.

Otsuka, K. & Kijima, Y. (2010). Technology Policies for a Green Revolution and Agricultural Transformation in Africa. JOURNAL OF AFRICAN ECONOMIES, VOLUME 19, AERC SUPPLEMENT 2, p. ii60–ii76 doi:10.1093/jae/ejp025

Ruttan, V.W. (2006a). Is War Necessary for Economic Growth? Military Procurement and Technology Development. New York: Oxford University Press.

Ruttan, V.W. (2006b). Social science knowledge and induced institutional innovation: an institutional design perspective. Journal of Institutional Economics, 2(3), 249-272.

Ruttan, V.W. and Hayami, Y. (1984). Toward a theory of induced institutional innovation. Journal of Development Studies, 20(4), 203-223.

Smith, P. & Olesen, J.E. (2010). Synergies between the mitigation of, and adaptation to, climate change in agriculture. Journal of Agricultural Science, 148, 543-552.

Vitousek, P.M. et al. (2009). Nutrient imbalances in agricultural development. Science 324, 1519-1520.

The importance of innovation: stories of sugar beets and soybeans

Sugar beets: not the prettiest sight. Image source.

In my last post I highlighted the "myth" of the linear model of science policy, and how this impedes progress in energy policy and ultimately making climate models applicable to local settings (i.e. science for decision-making). An alternative to the linear model is a more nuanced view of innovation. The "innovation approach" is a possible solution to the policy gridlock over climate change and energy. Innovation has been historically important to economic growth in the U.S., and is a more politically palatable solution (investing in clean energy technologies) than setting limits on greenhouse gas emissions. The Breakthrough Institute has some great scholarship on this topic, so check out them and their blog.

So how does innovation actually work? I've already implied that it doesn't follow the linear model of basic to applied research. Interestingly, on Tuesday I had the pleasure of attending a U.S. Senate Agricultural Committee Field hearing at MSU's campus. Many of the speakers called for renewed investment in "basic research," especially at the university. There is certainly a place for basic research at universities, because they often take on more risky research projects than the private sector. For example, I learned that MSU is the only place that researches sugar beet genetics. Sugar beets are an economically important crop to Michigan farmers, and MSU research, coupled with outreach by MSU Extension, is an important asset for improving the productivity of sugar beets.

As you can see from this video (here's the related article), private and public partnerships can yield "sweet success" for farmers. Involving end-users, such as farmers, can improve the social outcomes of scientific research through what Dan Sarewitz and Roger Pielke, Jr. call "reconciling the supply and demand of science." Download their article, which overviews many of the issues I've discussed on this blog, here.

Innovations aren't just serendipitous discoveries in the lab. They are often discovered and shaped by user-needs and preferences, by available technology, and market prices (such as energy, raw materials, market demand, and financing options). Scholars are now investigating the role of climate in inducing technological innovations in agriculture. One of the best examples of this is a study published in 2001 by John Smithers and Alison Blay-Palmer (download here).

These authors aim to open the "black box" of climate-induced technological innovation in the Canadian soybean industry. They link several innovations in soybeans to climate-related factors since the 1970s. Improvements in technology helped farmers manage the risk of normal climate variation (not necessarily related to climate change) and of adapting soybeans to new climates while the growing region expanded. One of the most important innovations in soybeans is the development improved crop varieties from plant breeding, for example, cold-tolerant crops.

Contrary to much of the technological optimism in agriculture towards climate change, the authors list some biological and economic constraints to future climate-induced innovations, specifically the limits of biotechnology and plant breeding. Plant breeding for new crops takes several years, and it can be difficult to predict future local climate conditions. They also list the narrow focus on crop yields as a possible constraint to innovation, as new varieties of crops for future climates may not have higher yields, but rather will help farmers adapt to new conditions. This is why it's important to involve farmers in the research decision process; because it is ultimately up to them whether to adopt a new crop.

The authors also discuss the prospects of public and private research (and the need for alliances), patents and intellectual property rights, and changing markets. In the past, public-private research partnerships had lower transaction costs, but these have risen because of gene patents that are often held by private companies. Addressing these barriers is crucial to future agricultural innovations for a changing climate.

They conclude with the provocative question, “Which adaptations seem likely given the current scientific limits and institutional constraints on innovation, and the competing influence of various other innovation needs in agriculture and society?” (Smithers & Blay-Palmer, 2001, p. 193). Climate change adaptation in agriculture is embedded in a complex social, political, economic, and technological system in which researchers, extension educators, and farmers must make decisions.

Source: Smithers, John and Alison Blay-Palmer. Technology innovation as a strategy for climate adaptation in agriculture. Applied Geography 21 (2001): 175–197.