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Climate variability impacts on rice production in the Philippines

Changes in crop yield and production over time are driven by a combination of genetics, agronomics, and climate. Disentangling the role of these various influences helps us understand the capacity of agriculture to adapt to change. Here we explore the impact of climate variability on rice yield and...

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Detalles Bibliográficos
Autores principales: Stuecker, Malte F., Tigchelaar, Michelle, Kantar, Michael B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6084865/
https://www.ncbi.nlm.nih.gov/pubmed/30091991
http://dx.doi.org/10.1371/journal.pone.0201426
Descripción
Sumario:Changes in crop yield and production over time are driven by a combination of genetics, agronomics, and climate. Disentangling the role of these various influences helps us understand the capacity of agriculture to adapt to change. Here we explore the impact of climate variability on rice yield and production in the Philippines from 1987–2016 in both irrigated and rainfed production systems at various scales. Over this period, rice production is affected by variations in soil moisture, which are largely driven by the El Niño–Southern Oscillation (ENSO). We found that the climate impacts on rice production are strongly seasonally modulated and differ considerably by region. As expected, rainfed upland rice production systems are more sensitive to soil moisture variability than irrigated paddy rice. About 10% of the variance in rice production anomalies on the national level co-varies with soil moisture changes, which in turn are strongly negatively correlated with an index capturing ENSO variability. Our results show that while temperature variability is of limited importance in the Philippines today, future climate projections suggest that by the end of the century, temperatures might regularly exceed known limits to rice production if warming continues unabated. Therefore, skillful seasonal prediction will likely become increasingly crucial to provide the necessary information to guide agriculture management to mitigate the compounding impacts of soil moisture variability and temperature stress. Detailed case studies like this complement global yield studies and provide important local perspectives that can help in food policy decisions.