Data/hora: 06/06/2024 01:23:36

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	03/11/2022	
Data da última atualização: 	03/11/2022	
Autoria: 	PORTALANZA, D.; HORGAN, F. G.; POHLMANN, V.; CUADRA, S. V.; TORRES-ULLOA, M.; ALAVA, E.; FERRAZ, S.; DURIGON, A.	
Afiliação: 	DIEGO PORTALANZA, UNIVERSIDADE FEDERAL DE SANTA MARIA; FINBARR G. HORGAN, ECOLAVERNA INTEGRAL RESTORATION ECOLOGY, UNIVERSIDAD CATÓLICA DEL MAULE, THE UNIVERSITY OF EDINBURGH; VALERIA POHLMANN, UNIVERSIDADE FEDERAL DE PELOTAS; SANTIAGO VIANNA CUADRA, CNPTIA; MALENA TORRES-ULLOA, ESCUELA SUPERIOR POLITÉCNICA DEL LITORAL; EDUARDO ALAVA, ESCUELA SUPERIOR POLITÉCNICA DEL LITORAL; SIMONE FERRAZ, UNIVERSIDADE FEDERAL DE SANTA MARIA; ANGELICA DURIGON, UNIVERSIDADE FEDERAL DE SANTA MARIA.	
Título: 	Potential impact of future climates on rice production in Ecuador determined using Kobayashi´s 'Very Simple Model'.	
Ano de publicação: 	2022	
Fonte/Imprenta: 	Agriculture, v. 12, n. 1, 1828, Nov. 2022.	
DOI: 	https://doi.org/10.3390/agriculture12111828	
Idioma: 	Inglês	
Conteúdo: 	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 KobayashÍ´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.	
Palavras-Chave: 	Agricultural modeling; Modelagem agrícola; Mudanças climáticas; RCPs; Yield gaps.	
Thesagro: 	Oryza Sativa.	
Thesaurus Nal: 	Climate change; Rice.	
Categoria do assunto: 	--	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1147973/1/AP-Potential-impact-2022.pdf	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (21461-1) - UPC - AP - DD -  -  -  - DIS