Improving productivity of Australian wheat by adapting sowing date and genotype phenology to future climate

Aadaptation of management practices to climate change reflected a shift towards earlier sowing windows or earlier maturity types for australian wheat cultivars. climate change impacts on wheat crops were simulated with a modified version of the agricultural production systems simulator (apsim) for the 2050s (2036–2065) with 33 GCM projections compared to baseline simulations from the 1990s (1976–2005). adaptation options focused on site-level changes in optimum sowing windows and locally best-yielding cultivars out of three spring wheat cultivars with contrasting maturity types and one fast-maturing winter cultivar. in the tested conditions, sowing and cultivar adaptation resulted in sowing dates of spring cultivars shifting to 10 days earlier across the wheatbelt, and earlier maturity types performing better in 20 of the 60 selected locations. this translated in a national shortening of the crop cycle by 14 days and a national yield increase by 4.6% or 116 kg ha−1. [Display omitted] •Adapting sowing dates and crop phenology can increase future Australian wheat yield.•Shift to earlier optimum sowing windows are expected by 2050.•Shift to earlier maturity type could further increase yield in the future.•Heat and drought are expected to become the major limiting factors. With global food demand predicted to grow by 50–80% by 2050, timely strategies are required to best adapt to the projected changes in agriculture. In this study, we illustrated how adaptation strategies not requiring additional inputs (sowing date and genotype choice) could be used to minimise the impact of projected stresses and raise wheat productivity in Australia. Yield and abiotic stresses impacting productivity of wheat crops were quantified in silico for the 1990s (1976–2005) and the 2050s (2036–2065) across the Australian wheatbelt using a modified version of the Agricultural Production Systems sIMulator (APSIM) and 33 Global Circulation Models (GCMs) under the Representative Concentration Pathways (RCP) 8.5. Two adaptation strategies were assessed: adaptation of sowing dates and/or adaptation of cultivars of contrasting phenology (i.e. fast-spring, mid-spring, slow-spring and fast-winter cultivars). For a given cultivar, optimum sowing windows associated with highest long-term yield were projected to shift to earlier dates by 2050 at most locations, with an average shift of 9.6 days for a mid-spring cultivar. Sowing early maturing cultivars enabled further increase in projected yiel