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  5. A new convergent science framework for food system sustainability in an uncertain climate

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Article
en
2022

A new convergent science framework for food system sustainability in an uncertain climate

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en
2022
Vol 11 (4)
Vol. 11
DOI: 10.1002/fes3.423

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Pete Smith
Pete Smith

University of Aberdeen

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Gregory N. Sixt
Michael Hauser
Nicole Tichenor Blackstone
+9 more

Abstract

Abstract The complexity and interconnectivity of food systems and climate requires new thinking and research designs that better address the real‐world challenges of securing the resilience and sustainability of human and environmental systems. Central to such an approach is coherent action across sectors and scales. Although inter‐and transdisciplinary approaches are widely discussed, no convergence model exists to detect and prepare for food system vulnerabilities emerging from disruptions in climate systems, or to address the contributions to climate change from food system functions. Convergence research is critical to solving these vexing dynamics by integrating knowledge from multiple scientific domains to inform societal action. Here, we present a new convergent science model that incorporates four key components at the global, national and local level. Through the newly created Food and Climate Systems Transformation Alliance, we are now operationalizing, testing and refining the model to promote science convergence for tackling systemic vulnerabilities in the current food paradigm. Globally, funding relating to climate change and food systems transformation needs to pivot to support the levels of ambition, magnitude of need and complexity of challenges posed.

How to cite this publication

Gregory N. Sixt, Michael Hauser, Nicole Tichenor Blackstone, Alejandra Engler, Jerry L. Hatfield, Sheryl L. Hendriks, Samuel Ihouma, Chandra A. Madramootoo, Renee J. Robins, Pete Smith, Lewis H. Ziska, Patrick Webb (2022). A new convergent science framework for food system sustainability in an uncertain climate. , 11(4), DOI: https://doi.org/10.1002/fes3.423.

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Publication Details

Type

Article

Year

2022

Authors

12

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/fes3.423

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