Simulating alfalfa regrowth and biomass in eastern Canada using the CSM-CROPGRO-perennial forage model

Abstract

Alfalfa (Medicago sativa L.) is the predominant forage legume species in Canada and is considered a prioritized option for sustainable cropping under climate change. Crop growth models provide an opportunity to explore the potential impacts of climate change on alfalfa and for evaluating potential adaptation options. For this study, six experimental datasets in eastern Canada were used to parameterize the newly adapted CSM-CROPGRO-Perennial Forage Model (CSM-CROGRO-PFM) in simulating alfalfa regrowth and to identify areas for further model improvement needed for climate change assessments in the northern agricultural regions of North America. Estimated air temperatures under snow cover were used successfully to drive the CSM-CROPGRO-PFM model for simulating alfalfa regrowth in eastern Canada. The simulated values of aboveground biomass across all sites and years were acceptable with a root mean square error (RMSE) of 936 kg dry matter (DM) ha−1 and a normalized RMSE of 24%. A sensitivity analysis of the model revealed that with no change in the number of harvests per year, the simulated annual herbage yield (harvestable biomass) declined with increasing temperature, increased with elevated atmospheric CO2 concentration, and changed little with increased precipitation. However, the increase in the number of harvests made possible by warmer temperatures may increase the simulated annual herbage yield. Although most alfalfa physiological processes were successfully simulated, some additional model functions may be required to further improve the simulation of alfalfa regrowth for climate change studies conducted in Canada. These functions include quantifying plant density decline and its relationship with biomass in post-seeding years, estimating temperatures surrounding alfalfa crowns during the overwintering period, and simulating herbage nutritive attributes.