Regionalization of Maize Responses to Climate Change Scenarios, N Use Efficiency and Adaptation Strategies (original) (raw)

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 CO 2) 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 CO 2 increment, but also due to intrinsic soil properties and leaching occurrence). This analysis showed that N use efficiency rises in high CO 2 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.