Spatial frameworks for robust estimation of yield gaps.

Autor: Rattalino Edreira JI; Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA., Andrade JF; Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA.; Department of Plant Production, University of Buenos Aires, Buenos Aires, Argentina., Cassman KG; Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA., van Ittersum MK; Plant Production Systems Group, Wageningen University, Wageningen, The Netherlands., van Loon MP; Plant Production Systems Group, Wageningen University, Wageningen, The Netherlands., Grassini P; Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA. pgrassini2@unl.edu.
Jazyk: angličtina
Zdroj: Nature food [Nat Food] 2021 Oct; Vol. 2 (10), pp. 773-779. Date of Electronic Publication: 2021 Sep 30.
DOI: 10.1038/s43016-021-00365-y
Abstrakt: 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 Agro-ecological 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.
(© 2021. The Author(s).)
Databáze: MEDLINE
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