Ecological Intensification Through Pesticide Reduction: Weed Control, Weed Biodiversity and Sustainability in Arable Farming.

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.

Sustainable alternative to irrigated maize monoculture in a maize-dominated cropped area: Lessons learned from a system experiment.

Maize is the most-produced food crop in the world and is grown in intensive rotations or in monoculture (continuous maize) systems. As maize production has expanded massively across the world, many concerns have emerged about its local environmental and other global impacts. Agronomists have designed innovative cropping systems and assessed them using system experiments to make arable systems more sustainable. However, knowledge is still lacking on the sustainability of innovative cropping systems compared to highly intensive systems such as irrigated maize-based monoculture. Here, we present the assessment results of a nine-year system experiment in Alsace, France, developed to compare an innovative system based on a diversified rotation and innovative management practices (three-year rotation of maize/soybean/winter wheat (plus a cover crop) combined with reduced tillage) with a continuous maize reference system. The results cover a six-year assessment period following an initial three-year design period. Classic criteria, such as profitability, workload, pesticide use, fossil energy consumption and nitrate leaching, were assessed along with other less studied criteria, such as pesticide leaching risk, soil structure, soil chemical quality and soil biological activity. Sustainability - which includes environmental, social and economic dimensions - was assessed with the MASC 2.0 method. Overall sustainability was substantially enhanced in the innovative system (5 out of 7 sustainability classes) in comparison with the low level of the reference system (2 out of 7). This was due to a clear improvement in the environmental performance (from 2 out of 5 to 5 out of 5) while social performance was high in both systems (4 out of 5) and economic performance was low (2 out of 5) due to very low contribution to economic development. Nevertheless, the innovative system had a major drawback: lower profitability, especially when scenarios included high maize prices. Furthermore, herbicide use on maize was higher in the innovative system than in the reference one. Avenues for progress, such as encouraging stakeholder participation at the assessment stage or additional innovations such as multiple cropping, are suggested.

An indicator to assess risks on water and air of pesticide spraying in crop fields.

Stakeholders involved in actions to reduce the use and the impacts on the environment or human health of pesticides need operational tools to assess crop protection strategies in regard to these impacts. I-Phy3 brings together all improvements introduced since the first version of the indicator to better meet user's needs and requirements of integrating processes. I-Phy3 was deeply modified to ensure its predictive quality. I-Phy 3 is structured in three levels of aggregation in form of hierarchical fuzzy decision trees designed with the CONTRA method. At the 1st level, five basic subindicators assess the risk of contamination (RC) for the different transfer pathways involved in surface water, ground water and atmosphere contamination: leaching, runoff, drainage, drift, volatilization. At the 2nd level, RC subindicators are aggregated with a toxicity variable (human or aquatic) in a risk indicator. At the 3rd level, the global indicator I-Phy3 results from the aggregation of three risk indicators for groundwater, surface waters and air. I-Phy3 yielded better validation results than its previous versions. This effort to assess the predictive quality of the indicator should be pursued and completed by a feasibility and utility test by end-users. A subindicator on risk of soil contamination is a gap which remains to fill.

Suitability of operational N direct field emissions models to represent contrasting agricultural situations in agricultural LCA: Review and prospectus.

N biogeochemical flows and associated N losses exceed currently planetary boundaries and represent a major threat for sustainability. Measuring N losses is a resource-intensive endeavour, and not suitable for ex-ante assessments, thus modelling is a common approach for estimating N losses associated with agricultural scenarios (systems, practices, situations). The aim of this study is to review some of the N models commonly used for estimating direct field emissions of agricultural systems, and to assess their suitability to systems featuring contrasted agricultural and pedoclimatic conditions. Simple N models were chosen based on their frequent use in LCA, including ecoinvent v3, Indigo-N v1/v2, AGRIBALYSE v1.2/v1.3, and the Mineral fertiliser equivalents (MFE) calculator. Model sets were contrasted, among them and with the dynamic crop model STICS, regarding their consideration of the biophysical processes determining N losses to the environment from agriculture, namely plant uptake, nitrification, denitrification, NH3 volatilisation, NO3 leaching, erosion and run-off, and N2O emission to air; using four reference agricultural datasets. Models' consideration of management drivers such as crop rotations and the allocation of fertilisers and emissions among crops in a crop rotation, over-fertilisation and fertilisation technique, were also contrasted, as well as their management of the mineralisation of soil organic matter and organic fertilisers, and of drainage regimes. For the four agricultural datasets, the ecoinvent model predicted significantly lower values for NH3 than AGRIBALYSE and STICS. For N2O, no significant differences were found among models. For NO3, ecoinvent and AGRIBALYSE predicted significantly higher emissions than STICS, regardless of the fertilisation regime. For both emissions, values of Indigo-N were close to those of STICS. By analysing the reasons for such differences, and the underlying factors considered by models, a list of recommendations was produced regarding more accurate ways to model N losses (e.g. by including the main drivers regulating emissions).

Assessment of pesticides volatilization potential based on their molecular properties using the TyPol tool.

Following treatment, amounts of pesticides can reach the atmosphere because of spray drift, volatilization from soil or plants, and/or wind erosion. Monitoring and risk assessment of air contamination by pesticides is a recent issue and more insights on pesticide transfer to atmosphere are needed. Thus, the objective of this work was to better understand and assess pesticides emission potential to air through volatilization. The TyPol tool was used to explore the relationships between the global, soil and plant volatilization potentials of 178 pesticides, and their molecular properties. The outputs of TyPol were then compared to atmospheric pesticide concentrations monitored in various French regions. TyPol was able to discriminate pesticides that were observed in air from those that were not. Clustering considering parameters driving the emission potential from soil (sorption characteristics) or plant (lipophilic properties), in addition to vapor pressure, allowed better discrimination of the pesticides than clustering considering all parameters for the global emission potential. Pesticides with high volatilization potential have high total energy, and low molecular weight, molecular connectivity indices and polarizability. TyPol helped better understand the volatilization potential of pesticides. It can be used as a first step to assess the risk of air contamination by pesticides.

A spatiotemporal dataset for integrated assessment and modelling of crop-livestock integration with the MAELIA simulation platform.

The general purpose of the primary and secondary data available in this article is to support an integrated assessment of scenarios of crop-livestock integration at the territorial level i.e. of exchanges between arable and livestock farms. The data is a result of a research collaboration between the scientist from INRAE, agricultural advisers from Chamber of Agriculture of Pays de la Loire (CRAPL) and a collective of five arable and two livestock farmers located in the district of Pays de Pouzauges (Vendée department, western France). All participants formed part of the DiverIMPACTS project (https://www.diverimpacts.net/) that aims to achieve the full potential of diversification of cropping systems for improved productivity, delivery of ecosystem services and resource-efficient and sustainable value chains in Europe. The first dataset corresponds to the inputs of MAELIA (http://maelia-platform.inra.fr/), a spatial agent-based simulation platform that was used to support an iterative design and assessment of scenarios to redesign cropping systems. The second dataset corresponds to the outputs of MAELIA simulations and the associated indicators at the farm, group and territory level. The data comprise multiple shape and csv files characterizing the edaphic-climatic heterogeneity of the territory and cropping systems, farmers' crop management rules (IF-THEN rules) and general information about the farms (e.g. crops, agricultural equipment, average crop yields). Data is reported for the baseline situation and three exchange scenarios containing different innovative cropping systems co-designed by scientists, agricultural advisers and the farmers. The data presented here can be found in the Portail Data INRA repository (https://doi.org/10.15454/3ZTCF5) and were used in the research article "Fostering local crop-livestock integration via legume exchanges using an innovative integrated assessment and modelling approach: MAELIA" [1].

Annotation data about multi criteria assessment methods used in the agri-food research: The french national institute for agricultural research (INRA) experience.

This data article contains annotation data characterizing Multi Criteria Assessment (MCA) Methods proposed in the agri-food sector by researchers from INRA, Europe's largest agricultural research institute (INRA, http://institut.inra.fr/en). MCA can be used to assess and compare agricultural and food systems, and support multi-actor decision making and design of innovative systems for crop production, animal production and processing of agricultural products. These data are stored in a public repository managed by INRA (https://data.inra.fr/; https://doi.org/10.15454/WB51LL).

Current and previous spatial distributions of oilseed rape fields influence the abundance and the body size of a solitary wild bee, Andrena cineraria, in permanent grasslands.

Wild bees are essential pollinators whose survival partly depends on the capacity of their environment to offer a sufficient amount of nectar and pollen. Semi-natural habitats and mass-flowering crops such as oilseed rape provide abundant floristic resources for bees. The aim of this study was to evaluate the influences of the spatial distribution of semi-natural habitats and oilseed rape fields on the abundance and the mean body size of a solitary bee in grasslands. We focused on a generalist mining bee, Andrena cineraria, that forages and reproduces during oilseed rape flowering. In 21 permanent grasslands of Eastern France, we captured 1 287 individuals (1 205 males and 82 females) and measured the body size of male individuals. The flower density in grasslands was quantified during bee captures (2016) and the landscape surrounding grasslands was characterized during two consecutive years (2015 and 2016). The influence of oilseed rape was tested through its distribution in the landscape during both the current year of bee sampling and the previous year. Bee abundance was positively influenced by the flower density in grasslands and by the area covered by oilseed rape around grasslands in the previous year. The mean body size of A. cineraria was explained by the interaction between flower density in the grassland and the distance to the nearest oilseed rape field in the current year: the flower density positively influenced the mean body size only in grasslands distant from oilseed rape. A. cineraria abundance and body size distribution were not affected by the area of semi-natural habitats in the landscape. The spatial distribution of oilseed rape fields (during both the current and the previous year) as well as the local density of grassland flowers drive both bee abundance and the mean value of an intraspecific trait (body size) in permanent grasslands. Space-time variations of bee abundance and mean body size in grasslands may have important ecological implications on plant pollination and on interspecific interactions between pollinators. Specifically, a competition between bee species for nesting sites might occur in oilseed rape rich landscapes, thus raising important conservation issues for bee species that do not benefit from oilseed rape resources.

Predictive quality of 26 pesticide risk indicators and one flow model: A multisite assessment for water contamination.

Stakeholders need operational tools to assess crop protection strategies in regard to environmental impact. The need to assess and report on the impacts of pesticide use on the environment has led to the development of numerous indicators. However, only a few studies have addressed the predictive quality of these indicators. This is mainly due to the limited number of datasets adapted to the comparison of indicator outputs with pesticide measurement. To our knowledge, evaluation of the predictive quality of pesticide indicators in comparison to the quality of water as presented in this article is unprecedented in terms of the number of tested indicators (26 indicators and the MACRO model) and in terms of the size of datasets used (data collected for 4 transfer pathways, 20 active ingredients (a.i.) for a total of 1040 comparison points). Results obtained on a.i. measurements were compared to the indicator outputs, measured by: (i) correlation tests to identify linear relationship, (ii) probability tests comparing measurements with indicator outputs, both classified in 5 classes, and assessing the probability i.e. the percentage of correct estimation and overestimation (iii) by ROC tests estimating the predictive ability against a given threshold. Results showed that the correlation between indicator outputs and the observed transfers are low (r<0.58). Overall, more complex indicators taking into account the soil, the climatic and the environmental aspects yielded comparatively better results. The numerical simulation model MACRO showed much better results than those for indicators. These results will be used to help stakeholders to appropriately select their indicators, and will provide them with advice for possible use and limits in the interpretation of indicator outputs.

Reconciling pesticide reduction with economic and environmental sustainability in arable farming.

Reducing pesticide use is one of the high-priority targets in the quest for a sustainable agriculture. Until now, most studies dealing with pesticide use reduction have compared a limited number of experimental prototypes. Here we assessed the sustainability of 48 arable cropping systems from two major agricultural regions of France, including conventional, integrated and organic systems, with a wide range of pesticide use intensities and management (crop rotation, soil tillage, cultivars, fertilization, etc.). We assessed cropping system sustainability using a set of economic, environmental and social indicators. We failed to detect any positive correlation between pesticide use intensity and both productivity (when organic farms were excluded) and profitability. In addition, there was no relationship between pesticide use and workload. We found that crop rotation diversity was higher in cropping systems with low pesticide use, which would support the important role of crop rotation diversity in integrated and organic strategies. In comparison to conventional systems, integrated strategies showed a decrease in the use of both pesticides and nitrogen fertilizers, they consumed less energy and were frequently more energy efficient. Integrated systems therefore appeared as the best compromise in sustainability trade-offs. Our results could be used to re-design current cropping systems, by promoting diversified crop rotations and the combination of a wide range of available techniques contributing to pest management.