Impact of climate variability and extreme rainfall events on sugarcane yield gap in a tropical Island.

The increasing incidence and intensity of extreme climate events are a major threat to global crop production. Sugarcane represents the main source of sugar and ethanol in tropical and sub-tropical regions. Here, we assessed the impacts of climatic variability and extreme events on sugarcane yield gaps in Reunion Island which is characterised by extreme spatial contrasts in climate, and is regularly subjected to cyclones or drought. We combined a process-based crop model with spatial databases of soil, climate and management data, to predict the annual sugarcane yield in each field over the whole island from 1998 to 2018. Simulated yields were compared to actual sugarcane yields from sugar producers in five agro-climatic zones. Extreme climate indices were calculated for extreme daily rainfall, temperature and drought, and their influence on yield gap was assessed using a Principal Component Analysis (PCA). The average total yield gap (YGT, i.e. the difference between potential sugarcane yield and actual yield, Mg ha-1) over Reunion Island was 96 Mg ha-1, explained by 34% throw crop management and hazards. YG due to crop management reached 65 Mg ha-1 with increasing rainfall and nitrogen mineralization rate and up to 88 Mg ha-1 with increasing temperature and radiation. Yield gap was correlated with the first axis of the PCA, highlighting how extreme rainfall induced increase in YGT. The actual yield loss was defined as the difference between the actual yield from sugarcane producers in a given year and the highest yield obtained during the whole studied period in the same zone. The annual actual yield loss increased by 0.6 Mg ha-1 per rainfall days higher than 29 mm d-1 along the annual crop cycle. Using this approximation, average actual yield loss due to heavy rain was estimated as 5.5 Mg ha-1 but it was higher than 10 Mg ha-1 for 25% of years in the East coast region. Our results highlight the need for improving sugarcane crop yield response to extreme rain in process-based crop models, in order to better assess climate change impacts in future.