Modeling annual grassland phenology along the central coast of California

Grassland phenology is an important component of terrestrial biophysical models, with substantial differences in the cycling of energy, carbon, water, and nutrient fluxes between periods of growth and dormancy. Modeling the phenology of moisture-driven annual grasslands in Mediterranean-type ecosystems (MTEs) remains challenging because although soil moisture is often a direct control on green-up, high rainfall variability during MTE wet seasons makes predicting the optimal time for senescence problematic. For this study, we developed a Mediterranean grassland phenology model (MGPM) to model green-up and senescence for coastal California annual grasslands. Mediterranean grassland phenology model was embedded in an ecohydrologic model, Regional Hydro-Ecologic Simulation System, and simulations of ecosystem fluxes were compared to a simpler fixed-date (i.e., photoperiod) phenology model. Results indicated that a soil water potential threshold was an accurate predictor of grassland green-up initiation. Annual cumulative net primary productivity (NPPcum) was observed to be a good predictor of senescence initiation, with higher levels of NPPcum associated with delayed senescence initiation. We also observed that photoperiod acts as an additional control on senescence initiation, restricting the window of time during which senescence may occur. Long-term peak NPPcum was noted as a potential control on the timing of this photoperiod window. Inclusion of MGPM into biophysical models is expected to improve the representation of annual grasslands and more accurately simulate ecosystem fluxes.