Improving the predictions of leaf photosynthesis during and after short-term heat stress with current rice models

In response to increasing global warming, extreme heat stress significantly alters photosynthetic production. While numerous studies have investigated the temperature effects on photosynthesis, factors like vapour pressure deficit (VPD), leaf nitrogen, and feedback of sink limitation during and after extreme heat stress remain underexplored. This study assessed photosynthesis calculations in seven rice growth models using observed maximum photosynthetic rate (P_max ) during and after short-term extreme heat stress in multi-year environment-controlled experiments. Biochemical models (FvCB-type) outperformed light response curve-based models (LRC-type) when incorporating observed leaf nitrogen, photosynthetically active radiation, temperatures, and intercellular CO₂ concentration (C_i ) as inputs. Prediction uncertainty during heat stress treatment primarily resulted from variation in temperatures and C_i . Improving FVPD (the slope for the linear effect of VPD on C_i /C_a ) to be temperature-dependent, rather than constant as in original models, significantly improved C_i prediction accuracy under heat stress. Leaf nitrogen response functions led to model variation in leaf photosynthesis predictions after heat stress, which was mitigated by calibrated nitrogen response functions based on active photosynthetic nitrogen. Additionally, accounting for observed differences in carbohydrate accumulation between panicles and stems during grain filling improved the feedback of sink limitation, reducing C_i overestimation under heat stress treatments.