Abstract

Integrated Weed Management (IWM) is necessary to reduce environmental damages by herbicides. The modifications required for IWM in cropping systems can result in unexpected side-effects, e.g. an increased risk of bioagressors other than weeds, either because the new cropping systems favour these bioagressors or because they favour weeds that are potential bioagressor hosts, thus increasing the contagion risk for crops. To evaluate these risks, the present case study worked with two model pests, a grass-weed species (blackgrass, Alopecurus myosuroides Huds.) and a soil-borne cereal pathogen (Gaeummanomyces graminis (Sacc.) von Arx et Olivier var. tritici Walker, responsible for take-all disease) which strongly interact and depend on cropping systems. For each pest, a model quantifying the effects of cropping systems in interaction with pedoclimatic conditions on pest dynamics was chosen from literature (AlomySys for weed dynamics, TakeAllSys for disease incidence) and linked with a new interaction model predicting the effect of one bioagressor on the other. A simulation study was then carried out, testing a herbicide-intensive reference system identified in farm surveys and a series of IWM systems combining several modifications (e.g. mouldboard ploughing, mechanical weeding, delayed sowing) to compensate for herbicide reductions. Each scenario was simulated over 27 years and repeated 20 times, with randomly chosen weather series from two different pedoclimates. The best IWM systems were more efficient than the herbicide-intensive reference system to control the grass weed. In the case of weed-free simulations, none of the IWM systems increased disease incidence, and the best systems even slightly reduced it. Integrating the reduction in weed seed production due to the disease in the simulations did not significantly change the simulation outcome, irrespective of the tested cropping system. Conversely, when the role of weed in disease transmission was taken into account, disease incidence in cereals crops considerably increased, particularly when past non-host crops in the rotation were infested by the weed. Nevertheless, the best IWM systems presented negligible weed-induced disease increase. The present results can be extrapolated to similar pest types (e.g. with propagules surviving in soil and negligible dispersal between fields). The modelling and simulation approach were easily feasible thanks to the availability of consistent models of cropping system effects on the two pests and experimental data on their interaction.

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