Amongst the biodiversity components of agriculture, weeds are an interesting model for exploring management options relying on the principle of ecological intensification in arable farming. Weeds can cause severe crop yield losses, contribute to farmland functional biodiversity and are strongly associated with the generic issue of pesticide use. In this paper, we address the impacts of herbicide reduction following a causal framework starting with herbicide reduction and triggering changes in (i) the management options required to control weeds, (ii) the weed communities and functions they provide and (iii) the overall performance and sustainability of the implemented land management options. The three components of this framework were analysed in a multidisciplinary project that was conducted on 55 experimental and farmer's fields that included conventional, integrated and organic cropping systems. Our results indicate that the reduction of herbicide use is not antagonistic with crop production, provided that alternative practices are put into place. Herbicide reduction and associated land management modified the composition of in-field weed communities and thus the functions of weeds related to biodiversity and production. Through a long-term simulation of weed communities based on alternative (?) cropping systems, some specific management pathways were identified that delivered high biodiversity gains and limited the negative impacts of weeds on crop production. Finally, the multi-criteria assessment of the environmental, economic and societal sustainability of the 55 systems suggests that integrated weed management systems fared better than their conventional and organic counterparts. These outcomes suggest that sustainable management could possibly be achieved through changes in weed management, along a pathway starting with herbicide reduction.

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SummaryWeeds are both harmful for crop production and important for biodiversity, while herbicides can pollute the environment. We thus need new cropping systems optimising all cultural techniques, reconciling agricultural production, herbicide reduction and biodiversity conservation. Here, we show how to (i) develop models quantifying the effects of cropping systems on weed dynamics, (ii) integrate interactions between weeds and other organisms, (iii) predict the impact on production and biodiversity and (iv) use the model for multicriteria evaluation and multiobjective design of cropping systems. Among the existing weed dynamics models, we chose the one closest to our requirements to illustrate these different steps, that is, FLORSYS which predicts multispecific weed dynamics as a function of cultural techniques and pedoclimate. We have illustrated the development of interaction submodels with the example of a crop pathogen whose propagation is increased when infecting grass weeds. To evaluate the weed flora impact, predicted weed densities were translated into indicators of harmfulness (crop yield loss, technical harvest problems, harvest pollution, field infestation, crop disease increase) and biodiversity (weed species richness and equitability, trophic resources for birds, insects and pollinators). Simulations were run over several years and with different weather scenarios (i) to optimise cultural techniques to control harmful weeds, (ii) to analyse the impact of changing agricultural practices (e.g. simplified tillage and rotations, no-till, temporary crops) on weed density, species and trait composition and (iii) to evaluate cropping systems for their ability to reconcile agricultural production and biodiversity, thus identifying levers for designing sustainable cropping systems.

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SUMMARYEnvironmental problems mean that herbicide applications must be drastically reduced and optimized. Models that quantify the effects of crop management techniques on weed dynamics are valuable tools for designing weed management strategies. Indeed, the techniques to be optimized are numerous and diverse, and their effects vary considerably with environmental conditions and the state of the weed flora. In the present study, a mechanistic weed dynamics model,AlomySys, was used to carry outin silicoexperiments in order to: (1) rank crop management components according to the resulting decrease in weed infestation, and (2) study the sensitivity of the major component effects to biophysical field state variables in order to identify indicators and thresholds that could serve for future decision-rules for farmers. The various results were compiled into rules for optimizing timing and other options (tillage tools, herbicide types) for the different crop management techniques. The rules were based on a series of biophysical field state variables, i.e. cumulated rainfall, thermal time, soil moisture and weed densities prior to the operation, in the previous and pre-previous crops. For instance, the first tillage should be delayed until the cumulated rainfall since harvest exceeds 50 mm and be carried out in moist conditions. Mouldboard ploughing is advised if the infestation of the previous crop exceeds 20 weeds/m2and particularly if this exceeds 0·3 times that of the pre-previous crop. Ploughing should occur when the cumulated rainfall since harvest reaches 100–200 mm. The effects of crop succession and long-term effects of management techniques have been studied in a companion paper (Colbachet al. 2012).

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