Grant: Canada Research Chairs
University of British Columbia
$200,000.00
Data science for sustainable global food systems
EF 2022-23
Résumé
Transitioning to a sustainable global food system is a major challenge for the 21st century. We need to reduce existing hunger and malnutrition, while feeding an additional 2 billion people expected by 2050, at the same time as reducing agriculture's environmental footprint, and making agriculture more climate resilient. Many, competing, solutions have been proposed to address this challenge, and a contentious debate ranges between those in favor of increasing food production through sustainable intensification, and the use of precision agriculture and genetic engineering versus those favoring food sovereignty and agroecological production methods. I propose that a potential reason for this debate is because the conversations remain global and abstract, bereft of local contexts, and looking for panaceas. To overcome these issues, I propose to develop data and analytical tools to explore food system sustainability solutions that are context-dependent, system integrated, and embrace a diversity of options. I plan to do this by: 1) developing critical new global and regional agricultural land use data sets using previously developed data fusion methods: 2) using systematic reviews and meta-analyses to examine the effectiveness of alternate farming systems; 3) exploring locally-effective and context-dependent farming system interventions by further developing a purposely-built web-based tool, and 4) develop regional-scale scenario models to explore integrated food system solutions. Through this research, I hope to identify pathways toward sustainable and climate-resilient food systems that explicitly consider local and regional contexts, embrace a diversity of farming and food system solutions, and examine integrated solutions.
Programme
Canada Research Chairs
Bénéficiaire
Emplacement
British Columbia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
CRC-2021-00053
Name nom
Ramankutty, Navin
Department département
UBC School of Public Policy and Global Affairs and Institute for Resources, Environment, and Sustainability
Organization id
2
Institution établissement
University of British Columbia
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2021
Award amount
200000
Program id
CRC
Program name en
Canada Research Chairs
Program name fr
Chaires de recherche du Canada
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
9998
Committee name en
Canada Research Chair Selection Committee
Committee name fr
Comité de sélection des Chaires de recherche du Canada
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
9999
Research subject group en
Not available
Research subject group fr
Non disponible
Research subject en
Not available
Research subject fr
Non disponible
Installment
inst:1;4
Partie
4
Nb partie
4
Application title
Data science for sustainable global food systems
Application summary
Transitioning to a sustainable global food system is a major challenge for the 21st century. We need to reduce existing hunger and malnutrition, while feeding an additional 2 billion people expected by 2050, at the same time as reducing agriculture's environmental footprint, and making agriculture more climate resilient. Many, competing, solutions have been proposed to address this challenge, and a contentious debate ranges between those in favor of increasing food production through sustainable intensification, and the use of precision agriculture and genetic engineering versus those favoring food sovereignty and agroecological production methods. I propose that a potential reason for this debate is because the conversations remain global and abstract, bereft of local contexts, and looking for panaceas. To overcome these issues, I propose to develop data and analytical tools to explore food system sustainability solutions that are context-dependent, system integrated, and embrace a diversity of options. I plan to do this by: 1) developing critical new global and regional agricultural land use data sets using previously developed data fusion methods: 2) using systematic reviews and meta-analyses to examine the effectiveness of alternate farming systems; 3) exploring locally-effective and context-dependent farming system interventions by further developing a purposely-built web-based tool, and 4) develop regional-scale scenario models to explore integrated food system solutions. Through this research, I hope to identify pathways toward sustainable and climate-resilient food systems that explicitly consider local and regional contexts, embrace a diversity of farming and food system solutions, and examine integrated solutions.