Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

-The evolution of natural ecosystems is controled by a high level of biodiversity, In sharp contrast, intensive agricultural systems involve monocultures associated with high input of chemical fertilisers and pesticides. Intensive agricultural systems have clearly negative impacts on soil and water quality and on biodiversity conservation. Alternatively, cropping systems based on carefully designed species mixtures reveal many potential advantages under various conditions, both in temperate and tropical agriculture. This article reviews those potential advantages by addressing the reasons for mixing plant species; the concepts and tools required for understanding and designing cropping systems with mixed species; and the ways of simulating multispecies cropping systems with models. Multispecies systems are diverse and may include annual and perennial crops on a gradient of complexity from 2 to n species. A literature survey shows potential advantages such as (1) higher overall productivity, (2) better control of pests and diseases, (3) enhanced ecological services and (4) greater economic profitability. Agronomic and ecological conceptual frameworks are examined for a clearer understanding of cropping systems, including the concepts of competition and facilitation, above-and belowground interactions and the types of biological interactions between species that enable better pest management in the system. After a review of existing models, future directions in modelling plant mixtures are proposed. We conclude on the need to enhance agricultural research on these multispecies systems, combining both agronomic and ecological concepts and tools. species mixture / plant mixture / cropping system / agroforestry system / agrobiodiversity / resource sharing / crop model / competition / facilitation

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Achieving sustainable crop production while feeding an increasing world population is one of the most ambitious challenges of this century. Meeting this challenge will necessarily imply a drastic reduction of adverse environmental effects arising from agricultural activities. The reduction of pesticide use is one of the critical drivers to preserve the environment and human health. Pesticide use could be reduced through the adoption of new production strategies; however, whether substantial reductions of pesticide use are possible without impacting crop productivity and profitability is debatable. Here, we demonstrated that low pesticide use rarely decreases productivity and profitability in arable farms. We analysed the potential conflicts between pesticide use and productivity or profitability with data from 946 non-organic arable commercial farms showing contrasting levels of pesticide use and covering a wide range of production situations in France. We failed to detect any conflict between low pesticide use and both high productivity and high profitability in 77% of the farms. We estimated that total pesticide use could be reduced by 42% without any negative effects on both productivity and profitability in 59% of farms from our national network. This corresponded to an average reduction of 37, 47 and 60% of herbicide, fungicide and insecticide use, respectively. The potential for reducing pesticide use appeared higher in farms with currently high pesticide use than in farms with low pesticide use. Our results demonstrate that pesticide reduction is already accessible to farmers in most production situations. This would imply profound changes in market organization and trade balance.

Agriculture is facing up to an increasing number of challenges, including the need to ensure various ecosystem services and to resolve apparent conflicts between them. One of the ways forward for agriculture currently being debated is a set of principles grouped together under the umbrella term "ecological intensification". In published studies, ecological intensification has generally been considered to be based essentially on the use of biological regulation to manage agroecosystems, at field, farm and landscape scales. We propose here five additional avenues that agronomic research could follow to strengthen the ecological intensification of current farming systems. We begin by assuming that progress in plant sciences over the last two decades provides new insight of potential use to agronomists. Potentially useful new developments in plant science include advances in the fields of energy conversion by plants, nitrogen use efficiency and defence mechanisms against pests. We then suggest that natural ecosystems may also provide sources of inspiration for cropping system design, in terms of their structure and function on the one hand, and farmers' knowledge on the other. Natural ecosystems display a number of interesting properties that could be incorporated into agroecosystems. We discuss the value and limitations of attempting to 'mimic' their structure and function, while considering the differences in objectives and constraints between these two types of system. Farmers develop extensive knowledge of the systems they manage. We discuss ways in which this knowledge could be combined with, or fed into scientific knowledge and innovation, and the extent to which this is likely to be possible. The two remaining avenues concern methods. We suggest that agronomists make more use of meta-analysis and comparative system studies, these two types of methods being commonly used in other disciplines but barely used in agronomy. Meta-analysis would make it possible to quantify variations of cropping system performances in interaction with soil and climate conditions more accurately across environments and socio-economic contexts. Comparative analysis would help to identify the structural characteristics of cropping and farming systems underlying properties of interest. Such analysis can be performed with sets of performance indicators and methods borrowed from ecology for analyses of the structure and organisation of these systems. These five approaches should make it possible to deepen our knowledge of agroecosystems for action. (Résumé d'auteur

EFSA requested the Scientific Committee to develop a guidance document on the use of the weight of evidence approach in scientific assessments for use in all areas under EFSA's remit. The guidance document addresses the use of weight of evidence approaches in scientific assessments using both qualitative and quantitative approaches. Several case studies covering the various areas under EFSA's remit are annexed to the guidance document to illustrate the applicability of the proposed approach. Weight of evidence assessment is defined in this guidance as a process in which evidence is integrated to determine the relative support for possible answers to a question. This document considers the weight of evidence assessment as comprising three basic steps: (1) assembling the evidence into lines of evidence of similar type, (2) weighing the evidence, (3) integrating the evidence. The present document identifies reliability, relevance and consistency as three basic considerations for weighing evidence.

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In 2016, France, one of the leading wheat-producing and wheat-exporting regions in the world suffered its most extreme yield loss in over half a century. Yet, yield forecasting systems failed to anticipate this event. We show that this unprecedented event is a new type of compound extreme with a conjunction of abnormally warm temperatures in late autumn and abnormally wet conditions in the following spring. A binomial logistic regression accounting for fall and spring conditions is able to capture key yield loss events since 1959. Based on climate projections, we show that the conditions that led to the 2016 wheat yield loss are projected to become more frequent in the future. The increased likelihood of such compound extreme events poses a challenge: farming systems and yield forecasting systems, which often support them, must adapt.