Research in the CGIAR: An urgent need for systems analysis and more

integrative research approaches

Anne-Marie IzacCGIAR Consortium

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Livestock and Fish expert workshop on systems analysis for value chain transformationAmsterdam, 19 November 2014

Outline

1. Looking back: 5 key lessons

2. Looking ahead: new research approaches needed - systems analysis and transdisciplinarity

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1. Looking back: five key lessons

• Generic ToC: providing new scientific evidence & improved practices will result in policy changes and adoption of innovations

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1. Looking back: five key lessons

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• Generic ToC: providing new scientific evidence & improved practices will result in policy changes and adoption of innovations

• 1st lesson: ToC: far too simplistic/naive about how science can influence rest of world

Source: R. Rabbinge, 2009 5

1. Five key lessons

• 2nd lesson: interdisciplinary & multi-institutional approaches w/ many partners produced relevant, robust results that mono disciplinary and mono institutional approaches could not have produced

• 3rd lesson: governance and mgt structure need to be aligned with science implemented (inclusive, transparent, accountable)

• Interdisciplinary work still difficult, particularly biophysical x social scientists; governance still issue and partnerships variable

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1. Five key lessons

• 4th lesson: to generate new knowledge, IPGs, essential: baseline/benchmark in multiple sites; understanding of processes at play in ≠ environments, at ≠ spatial-temporal scales before can scale up

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1. Five key lessons

• 4th lesson: to generate new knowledge, IPGs, essential: baseline/benchmark in multiple sites; understanding of processes at play in ≠ environments, at ≠ spatial-temporal scales before can scale up

• Today, scientists struggle with ’baseline analysis’, work at multiple scales, credible scaling up. Realising only now importance of this for RBM.

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1. Five key lessons

• 4th lesson: to generate new knowledge, IPGs, essential: baseline/benchmark in multiple sites; understanding of processes at play in ≠ environments, at ≠ spatial-temporal scales before can scale up

• Today, scientists struggle with ’baseline analysis’, work at multiple scales, credible scaling up. Realising only now importance of this for RBM.

• 5th lesson: flexibility, willingness to learn from mistakes, asking existential questions, re-inventing program: essential to evolve realistic ToC overtime

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2. Looking ahead: main challenge

• Providing more secure, diversified & healthy food grown in more and more difficult conditions, whilst decreasing the environmental footprint of agriculture and decreasing inequalities

• Complex, interconnections, uncertainties, beyond any discipline’s reach. Requires ‘transformative’ integration of many sciences (life, natural, social, human health, mathematical) and perspective of stakeholders

• Inter/multidisciplinary approaches insufficient to promote collaboration and synthesis needed to produce truly innovative solutions to large–scale, complex problems.

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2. Complex, multidimensional challenges

Source: IAASTD, 200811

2. Transdisciplinary approaches to accelerate discovery, innovation, application of innovations

• Change in scientific culture: reality is multidimensional, so is knowledge.

• New ways of thinking, new tools & approaches by working together across disciplines &with stakeholders. Builds upon but transcends reductionism, linear logic.

• Systematic approach, based on overall coherence rather than unity

• Creative “convergence–divergence” process that brings areas of knowledge together into a new system to spin off applications and elements that can in turn be recombined and integrated

• Results in new social distribution of knowledge, understanding processes, reproducibility of innovations in ≠ locations and reproducibility of policy influence

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Source: Izac et al,06

2. More integrative approaches

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Source: Izac et al, 06

2. Looking ahead: research areas that lag behind

• Need to strenghten: – Nutrition, health, food safety – policy research, so based upon robust biophysical x

socio-economic evidence; science-policy interface – NRM in commodity improvement research to

decrease environmental footprint of agriculture, role of ecosystem services in resilience, ‘sustainable intensification’

– research on LT effects of innovations, predicting and monitoring impacts, to better understand processes at play

– research at landscape-regional scales

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In conclusion

• CGIAR’s experience: 5 lessons relevant for all agri research. On essentiality of partnerships; alignment of governance & mgt with research needs; importance of working at ≠ scales, in ≠ countries and of learning from mistakes, re-creating

• Comparative advantage of CGIAR today: capacity to work globally from many sites, across institutions & disciplines to more rapidly design robust options. Ability to take risks, be innovative, as can learn from our mistakes across all research programmes

• Given complexity of challenges ahead, more transformative changes are now needed, more urgently.

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In conclusion, for a new science

• Complex challenges ahead require more integrative and collaborative approaches:

– Using transdisciplinary approaches that transcend disciplinary boundaries, involve stakeholders

– To design truly innovative approaches, better tuned to complexity, uncertainty, constant change, understanding processes at play in scaling up innovations and policy influence

– Re-balancing priorities to squarely address nutrition, health, policy influence, environmental footprint

• Huge, exciting challenge for CGIAR scientists: new type of science needed, new way of conceiving role of research in society

• Recent recognition of this need (e.g., US Academy of Sciences, Special Rapporteur to the UN on the right to food) and of transformative improvements resulting from such approaches (medicine, engineering)

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