Spatial frameworks for robust estimation of yield gaps

• Autores: Rattalino Edreira, Juan Ignacio; Andrade, José Francisco; Cassman, Kenneth; Ittersum, M. K. van; Loon, M. P. van; Grassini, Patricio
• Año de publicación: 2021
• Idioma: inglés
• Tipo de recurso: artículo
• Fuente: Nature Food; Vol.2; 773-779; https://www.nature.com/natfood
• Materia: AGRICULTURAL LAND; AGRICULTURE; ARTICLE; CEREAL; CONTROLLED STUDY; CROP MANAGEMENT; CROP PRODUCTION; FOOD SECURYTY; HARVEST; OUTCOME ASSESSMENT; PERFORMANCE; PREDICTION; SIMULATION; SPATIAL ANALYSIS
• Institución: Universidad de Buenos Aires. Facultad de Agronomía

Fil: Rattalino Edreira, Juan Ignacio. University of Nebraska - Lincoln. Department of Agronomy and Horticulture. Lincoln, NE, USA.
Fil: Andrade, José Francisco. University of Nebraska - Lincoln. Department of Agronomy and Horticulture. Lincoln, NE, USA.
Fil: Cassman, Kenneth. University of Nebraska - Lincoln. Department of Agronomy and Horticulture. Lincoln, NE, USA.
Fil: Ittersum, M. K. van. Wageningen University. Plant Production Systems Group. Wageningen, The Netherlands.
Fil: Loon, M.P. van. Wageningen University. Plant Production Systems Group. Wageningen, The Netherlands.
Fil: Grassini, Patricio. University of Nebraska - Lincoln. Department of Agronomy and Horticulture. Lincoln, NE, USA.
Food security interventions and policies need reliable estimates of crop production and the scope to enhance production on existing cropland. Here we assess the performance of two widely used ‘top-down’ gridded frameworks (Global Agroecological Zones and Agricultural Model Intercomparison and Improvement Project) versus an alternative ‘bottom-up’ approach (Global Yield Gap Atlas). The Global Yield Gap Atlas estimates extra production potential locally for a number of sites representing major breadbaskets and then upscales the results to larger spatial scales. We find that estimates from top-down frameworks are alarmingly unlikely, with estimated potential production being lower than current farm production at some locations. The consequences of using these coarse estimates to predict food security are illustrated by an example for sub-Saharan Africa, where using different approaches would lead to different prognoses about future cereal self-sufficiency. Our study shows that foresight about food security and associated agriculture research priority setting based on yield potential and yield gaps derived from top-down approaches are subject to a high degree of uncertainty and would benefit from incorporating estimates from bottom-up approaches.
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