Sylvie Granger

Uncertainty analysis and evaluation of a complex, multi-specific weed dynamics model with diverse and incomplete data sets

Weed dynamics models are needed to test prospective cropping systems but are rarely evaluated with independent data (validated). Here, we evaluated the FlorSys model which quantifies the effects of cropping systems and pedoclimate on multispecific weed dynamics with a daily time step. We adapted existing validation methodologies and uncertainty analyses to account for multi-specific, multi-annual and diverse outputs, focusing on missing input data, incomplete and imprecise weed time series. Field data ranged from entirely monitored cropping system trials to annual snapshots recorded on farm fields by the French Biovigilance-Flore network. FlorSys satisfactorily predicted weed seed bank, plant densities and crop yields, at daily and multi-annual scales, at well monitored sites. It overestimated plant biomass and underestimated total flora density. Missing processes (photoperiod dependency in flowering, crop:weed competition for nitrogen) and inadequately predicted scenarios (weed dynamics in untilled fields, floras with summer-emerging species) were identified. Guidelines for model use were proposed. Weed dynamics models must be validated before using them for cropping system design.Methods were developed to evaluate a mechanistic model with incomplete data sets.Data sets comprise cropping system trials and a farm field survey network.FlorSyss domain of validity and guidelines for simulations were determined.Missing processes necessary for predicting weed dynamics in fields were identified.