Distribuição geográfica da Sigatoka Negra da bananeira estimada por modelos de mudanças climáticas globais

Global climatic changes will potentially influence plant diseases and the efficacy of their management options. One of the most likely impacts of climate change will be felt by the geographical distribution of plant diseases. Black Sigatoka is considered the most damaging and costly disease of banan...

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Detalles Bibliográficos
Autores: Jesus Júnior, Waldir Cintra de, Valadares Júnior, Ranolfo, Cecílio, Roberto Avelino, Moraes, Willian Bucker, Vale, Francisco Xavier Ribeiro do, Alves, Fábio Ramos, Paul, Pierce Anderson
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2008
País:Brasil
Institución:Universidade de São Paulo (USP)
Repositorio:Scientia Agrícola (Online)
Idioma:inglés
OAI Identifier:oai:revistas.usp.br:article/22388
Acceso en línea:https://revistas.usp.br/sa/article/view/22388
Access Level:acceso abierto
Palabra clave:Mycosphaerella fijiensis
Musa spp.
global climate change
mudanças climáticas globais
Descripción
Sumario:Global climatic changes will potentially influence plant diseases and the efficacy of their management options. One of the most likely impacts of climate change will be felt by the geographical distribution of plant diseases. Black Sigatoka is considered the most damaging and costly disease of banana. The socio-economic impact of this disease has continued to increase as the pathogen reaches new areas and the disease becomes more difficult to be controled. The objectives of this research were to compare the global geographical distribution of the disease based on maps elaborated using weather data representing: i) current and future periods (2020, 2050 and 2080), ii) Intergovernmental Panel on Climate Change scenarios A2 and B2, iii) predictions based on six different climate change models and the " multimodel ensemble" and, iv) individual months. The " multimodel ensemble" lead to a reduction in the variability of the simulations when compared to the results obtained using the individual models separately. The predictions suggested that, in the future, areas favorable for the development of the Black Sigatoka disease will decrease. This reduction will occur gradually and will be higher for the A2 than for the B2 scenario. Changes in the geographical distribution of the disease will occur from one month to another, with unfavorable areas becoming favorable and vice-versa. However, in spite of these changes, extensive areas will still continue to be favorable for the occurrence of Black Sigatoka.