Phosphorus (P) is a non-renewable geological macronutrient that plays an essential role in food security. The excessive use of P as a fertilizer and its subsequent diffuse loss leads to the deterioration of water quality, eutrophication, and loss of biodiversity. Ecosystem process-based models are a powerful tool to depict the P cycle, investigate the effects of management practices and climate change, and ultimately assess policy interventions that affect biogeochemical cycles. Of the limited number of P models in agricultural production systems, none have been tested in temperate conditions for periods of decades using long-term field experiments.
The objective of this study is to evaluate the ability of the detailed P submodel from DayCent to: simulate the magnitude and temporal dynamics of P outputs; assess changes in P soil pools from European agricultural long-term experiments; and interpret the main causal factors inducing the differences between the observed vs. the simulated pools and fluxes.
We used data from four long-term experiments to calibrate and test the P submodel of DayCent. The experiments involve five different soils, mineral and organic fertilizer treatments, management intensity levels, various crop rotations, crop residue management, and irrigation.
The DayCent model captured the gross P budget (input minus output) in the four long-term experiments, and it performed well in simulating their soil total P (PTotal) over time. The model application simulated the soil available P (PAvailable) in the same range as the measured data, but the temporal dynamic did not always match the observed trends. P modelling is subject to a wide range of uncertainties with respect to both input data (particularly the unknown initial distribution of the different pool sizes of P and the uncertainty of the measurements) and the representation of processes influencing the P cycle that are not yet accounted for in the model. Despite these uncertainties and calls for further model assessment and developments, the results show that DayCent was capable of satisfactorily predicting the main P fluxes over time under a wide variety of management practices and European site conditions.
The model may be used to assess different scenarios with a changing climate, a change in management or land-use, and to analyse potential feedback between the terrestrial and the climate system. This makes this model a promising tool for assessing policy and practical interventions.
