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1000
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Abstract/Summary
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As with any other crop, maize yield is a response to environmental factors such as soil, weather, and management. In a context of climate change, understanding responses is crucial to determine mitigation and adaptation strategies. Crop models are an effective tool to address this. The objective was to present a procedure to assess the impacts of climate scenarios on maize N use efficiency and yield, with the effect of cultivar (n = 2) and planting date (n = 5) as adaptation strategies. The study region was Santa Catarina, Brazil, where maize is cultivated on more than 800,000 ha (average yield: 4.63 t·ha−1). Surveying and mapping of crop land was done using satellite data, allowing the coupling of weather and 253 complete soil profiles in single polygons (n = 4135). A Decision Support System for Agrotechnology Transfer (DSSAT) crop model was calibrated and validated using field data (2004–2010 observations). Weather scenarios generated by Regional Climatic Models (RCMs) were selected according their capability of reproducing observed weather. Simulations for the 2012–2040 period (437 ppm CO2) showed that without adaptation strategies maize production could be reduced by 12.5%. By only using the best cultivar for each polygon (combination of soil + weather), the total production was increased by 6%; when using both adaptation strategies—cultivar and best planting date—the total production was increase by 15%. The modelling process indicated that the N use efficiency increment ranged from 1%–3% (mostly due to CO2 increment, but also due to intrinsic soil properties and leaching occurrence). This analysis showed that N use efficiency rises in high CO2 scenarios, so that crop cultivar and planting date are effective tools to mitigate deleterious effects of climate change, supporting energy crops in the study region.
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