Symposium on Knowledge Systems for

Sustainable Development:Mobilizing Research and

Development for Decision-Making

American Association for the Advancement of Science Annual Meeting

18 February 2007, San Francisco

Knowledge Systems for Sustainable Development:Report of an international study on mobilizing R&D

to support decision making for sustainability

Project leaders: William C. Clark and Nancy Dickson, Harvard UniversityGilberto C. Gallopín, Economic Commission for Latin America and the CaribbeanLouis Lebel, Chiang Mai UniversityPamela Matson, Stanford University

Researcher team:Lee Addams, Columbia UniversityJames Buizer, Arizona State UniversityDavid Cash, Massachusetts Executive Office of Environmental AffairsCharunee Chirangworapot, Chiang Mai UniversityPo Garden, Chiang Mai UniversityKathy Jacobs, University of ArizonaAmy Luers, Union of Concerned ScientistsDavid Mánuel-Navarrete, Economic Comm. for Latin America and the CaribbeanEllen McCullough, Food and Agriculture Organization of the UNGeorge Saliba, University of ArizonaNicole Szlezák, Harvard UniversityDrinya Totrakool, Chiang Mai UniversityLorrae van Kerkhoff, Australian National University

The problem we explored• Growing recognition that development "is built not merely

through the accumulation of physical capital and human skill, but on a foundation of information, learning and adaptation” (World Bank), and that successfully “navigating a transition toward sustainable development will be an especially knowledge-intensive activity” (NRC, ICSU)

• In general, however, relevant knowledge remains underproduced, underutilized and unevenly distributed…– eg. How to accommodate 3B more people in cities, sustainably

• …while even the knowledge that does exist is seldom integrated into systems that can support decision, action – eg. persistent mortality due to indoor air pollution from cook stoves

• But there are exceptions. This study therefore sought to answer the question “What makes some knowledge systems more effective than others in harnessing science and technology to achieve the goals of sustainable development?”

The approach we took• Attempt to understand the systems involved in

mobilizing R&D to support decisions, action…– networks of actors, organizations, and objects that

perform a number of knowledge-related functions that link knowledge and know-how with action.

– included are the incentives, financial resources, institutions, and human capital that give such systems capacity to do their work, and the intention to focus such work in some arenas rather than others.

• Oriented through general review of experience with knowledge systems in agriculture, health, energy, etc

• Focused through a set of empirical case studies exploring a range of issues, scales and regions– developing and applying a common set of questions and

research protocols– iterating between field work and conceptualization

The Cases we Studied

• Water management: – Yaqui Valley, Mexico; Ceará, Brazil; Ping River Basin,

Thailand; Upper San Pedro River, Arizona• Short-term climate forecasts:

– Pacific, Southern Africa• Fisheries:

– Yaqui Valley and Thailand• Agriculture:

– Pampas in Argentina, Yaqui Valley, CGIAR• Health:

– Global Fund to Fight AIDS, TB and Malaria

The conclusions we’ve reached:Today’s presentations

• Linking knowledge with action for sustainability– William C. Clark, Kennedy School of Government, Harvard Univ.

• Multiple epistemologies of knowledge for sustainability– Gilberto C. Gallopín, Economic Commission for Latin America

and the Caribbean• Governing knowledge systems for sustainability

– Louis Lebel, Unit for Social and Environmental Research, Chiang Mai University

• Research actors in knowledge systems: Perspectives from the inside– Pamela Matson, School of Earth Sciences, Stanford University

• Discussants– James Buizer, Office of the President, Arizona State University– Kathy Jacobs, Arizona Water Institute, University of Arizona

Project conclusions onLinking knowledge with action for

sustainabilityWilliam C. Clark, Harvard University

• Case studies revealed many different barriers that inhibited effective mobilization of R&D to support decision making

• Three, however, stand out:– Mutual incomprehension between scientists, decision

makers– Fragmentation of the knowledge system– Inflexibility in a world of ignorance and surprise

• Diagnosis (Why is there a problem?)– Scientists and practitioners have different perceptions of

problems, solutions, and reliable knowledge– Usable knowledge must be perceived by both scientists and

decision makers to be salient, credible, legitimate (SCL)

• Process prescription (What needs to change?)– Reject pipe-line models of one way knowledge transfer– Promote co-production of usable knowledge

• Institutional implementation (How to do it?)– Boundary-spanning institutions that

• co-produce ‘boundary objects’ (maps, models, standards)…• that are perceived to be salient, credible, legitimate by all• through processes of dual accountability to scientists & practitioners

1) Mutual Incomprehension(square pegs for round holes)

A Boundary-spanning Object…

• Diagnosis (Why is there a problem?)– Sustainability often a public good (weak market tests)– Principal-agent issues (optimize parts, not whole)

• Process prescription (What needs to change?)– Systems integration

• identify missing nodes, links; • construct incentives to complete them

• Institutional implementation (How to do it?)– Project-oriented management accountable for results– Adopting supply chain perspective to get all parts– Implement via task teams outside normal structures

2) Fragmentation (system less than sum of its parts)

Project oriented management

Research

Solution/ Problem(re)definition

Diffusion(large scale)

Development(translation)

Adoption (small scale)

Farmers benefiting

from forecasts

Basic research on climate forecasting

Development of decision

support tools for farmers

Initial field testing, revisionLarge scale

deployment of decision

support system

• Diagnosis (Why is there a problem?)– Absence of forums to learn from others’ experience– Incentives to hide failures, not to learn from them– Willful ignorance and motives to block learning

• Process prescription (What needs to change?)– From knowledge systems to learning systems

• Institutional implementation (How to do it?)– Adaptive management institutions, with capacity for

• experimentation (“safe spaces” for “safe failure”)• reflection (evaluations and metrics that reward learning)• response (stable resources, flexible structures and rules)

3) Inflexibility(static systems, dynamic challenges)

Summary

• Lessons for Linking Knowledge with Action– Miscommunication Boundary-spanning institutions– Fragmentation project management to integrate– Inflexibility Adaptive management fostering social learning

• But … – This has been the simplest manager’s / technician’s view of

knowledge systems for sustainability– Our project also grappled with the fact that such knowledge

systems need to entrain different kinds of knowledge, leading us into questions of epistemology (Gallopin)

– and do so in contexts where the power to determine what knowledge gets to the table and what is done with it is unequally distributed, leading to questions of governance (Lebel)

– Finally, we tried to reflect on our own learning as knowledge institutions in conducting this study (Matson)