Potential Impact of Future Climates on Rice Production in Ecuador Determined Using Kobayashi’s ‘Very Simple Model’

Diego Portalanza (), Finbarr G. Horgan, Valeria Pohlmann, Santiago Vianna Cuadra, Malena Torres-Ulloa, Eduardo Alava, Simone Ferraz and Angelica Durigon
Additional contact information
Diego Portalanza: Climate Research Group, Department of Physics, Federal University of Santa Maria, Av. Roraima, 1000, Santa Maria 97105-900, RS, Brazil
Finbarr G. Horgan: EcoLaVerna Integral Restoration Ecology, Bridestown, Kildinan, T56 P499 County Cork, Ireland
Valeria Pohlmann: Faculty of Agronomy, Department of Plant Science, Federal University of Pelotas, Pelotas 96010-610, RS, Brazil
Santiago Vianna Cuadra: Brazilian Agricultural Research Corporation (EMBRAPA), Brasília 70770-901, DF, Brazil
Malena Torres-Ulloa: Escuela Superior Politécnica del Litoral, Facultad de Ciencias de la Vida, Guayaquil 090902, Ecuador
Eduardo Alava: Escuela Superior Politécnica del Litoral, Facultad de Ciencias de la Vida, Guayaquil 090902, Ecuador
Simone Ferraz: Climate Research Group, Department of Physics, Federal University of Santa Maria, Av. Roraima, 1000, Santa Maria 97105-900, RS, Brazil
Angelica Durigon: Climate Research Group, Department of Physics, Federal University of Santa Maria, Av. Roraima, 1000, Santa Maria 97105-900, RS, Brazil

Agriculture, 2022, vol. 12, issue 11, 1-16

Abstract: Rice ( Oryza sativa L.) is the main staple food of more than 50% of the world’s population. However, global production may need to increase by more than 70% before 2050 to meet global food requirements despite increasing challenges due to environmental degradation, a changing climate, and extreme weather events. Rice production in Ecuador, mainly concentrated in lowland tropical plains, declined in recent years. In this paper, we aim to calibrate and validate Kobayashi’s ‘Very Simple Model’ (VSM) and, using downscaled corrected climate data, to quantify the potential impact of climate change on rice yields for Ecuador’s two main rice-growing provinces. The negative impact is expected to be highest (up to −67%; 2946 tons) under the Representative Concentration Pathway (RCP) 8.5, with a lower impact under RCP 2.6 (−36%; 1650 tons) yield reduction in the Guayas province. A positive impact on yield is predicted for Los Ríos Province (up to 9%; 161 tons) under RCP 8.5. These different impacts indicate the utility of fine-scale analyses using simple models to make predictions that are relevant to regional production scenarios. Our prediction of possible changes in rice productivity can help policymakers define a variety of requirements to meet the demands of a changing climate.

Keywords: agricultural modeling; rice; climate change; RCPs; yield gaps (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
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