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Crop diversification is considered as an important linchpin of the agroecological transition, whereas current dominant cropping systems are known to rely only on a few crops species – like cereals in the European Union (EU). To assess the benefits of crop diversification at large scale, an accurate description of current crop sequences is required as a baseline. However, such a description is lacking at the scale of the EU. Here, we developed the first map of dominant crop sequences in the EU for the period 2012–2018. We used the LUCAS dataset that provides temporally-incomplete land cover information from a stable grid of points covering the whole EU. Eight crop sequence types were identified using hierarchical clustering implemented on LUCAS data, and mapped over EU. We show, in France, that the relative importance of these eight crop sequence types (as estimated from LUCAS data) was highly consistent with those derived from an almost spatially-exhaustive temporally-complete national dataset (the French Land Parcel Identification System) for the same period, thus validating the method and the typology for this country. Land use (i.e. crop production area) derived from our map of dominant crop sequences was also highly consistent with land use reported by official statistics, both at national and EU levels, validating the approach at the EU-scale. This first map of dominant crop sequences in the EU should be useful for future studies dealing with agricultural issues that are sensitive to crop rotations. The map of dominant crop sequences types in the EU derived from our work is available at https://doi.org/10.5281/zenodo.7016986 (Ballot et al., 2022).

Currently, demand for soybean in Europe is mostly fulfilled by imports. However, soybean-growing areas across Europe have been rapidly increasing in response to a rising demand for locally-produced, non-GM soybean in recent years. This raises questions about the suitability of European agro-climatic conditions for soybean production. We used data-driven relationships between climate and soybean yield derived from machine-learning techniques to make yield projections under current and future climate with moderate (RCP 4.5) to intense (RCP 8.5) warming, up to the 2050s and 2090s time horizons. Results suggest that a self-sufficiency level of 50% (100%) would be achievable in Europe under historical and future climate if 4-5% (9-12%) of the current European cropland is dedicated to soybean production. The associated increase in soybean area in Europe would bring environmental benefits, with a potential decrease of nitrogen fertilizer use in Europe by 5-8% (13-18%) and a possible reduction of deforestation in biodiversity hotspots in South America. However, it would also lead to an important reduction in the production of other cultivated species in Europe (e.g. cereals) and a potential increase in the use of irrigation water.

Many assessments of crop yield gaps based on comparisons to actual yields suggest grain yields in highly intensified agricultural systems are at or near the maximum yield attainable. However, these estimates can be biased in situations where yields are below full yield potential. Rice yields in the US continue to increase annually, suggesting that rice yields are not near the potential. In the interest of directing future efforts towards areas where improvement is most easily achieved, we estimated yield potential and yield gaps in US rice production systems, which are amongst the highest yielding rice systems globally. Zones around fourteen reference weather stations were created, and represented 87% of total US rice harvested area. Rice yield potential was estimated over a period of 13–15 years within each zone using the ORYZA(v3) crop model. Yield potential ranged from 11.5 to 14.5 Mg ha −1 , while actual yields varied from 7.4 to 9.6 Mg ha −1 , or 58–76% of yield potential. Assuming farmers could exploit up to 85% of yield potential, yield gaps ranged from 1.1 to 3.5 Mg ha −1 . Yield gaps were smallest in northern California and the western rice area of Texas, and largest in the southern rice area of California, southern Louisiana, and northern Arkansas/southern Missouri. Areas with larger yield gaps exhibited greater annual yield increases over the study period (35.7 kg ha −1 year −1 per Mg yield gap). Adoption of optimum management and hybrid rice varieties over the study period may explain annual yield increases, and may provide a means to further increase production via expanded adoption of current technologies.

The Global Yield Gap Atlas project (GYGA - http://yieldgap.org) has undertaken a yield gap assessment following the protocol recommended by van Ittersum et al. (2013). One part of the activities consists of collecting and processing weather data as an input for crop simulation models in sub-Saharan African countries including Kenya. This publication covers daily weather data for 12 locations in Kenya for the years 1998-2012. The project looked for good quality weather data in areas where crops are pre-dominantly grown. As locations with good public weather data are sparse in Africa, the project developed a method to generate bias corrected weather data from a combination of observed data and other external weather data. The bias corrected weather data consist of daily TRMM rain data and NASA POWER Tmax, Tmin, and Tdew data. These data are corrected based on calibrations with short-term (

In rainfed crop production, root zone plant-available water holding capacity (RZ-PAWHC) of the soil has a large influence on crop growth and the yield response to management inputs such as improved seeds and fertilisers. However, data are lacking for this parameter in sub-Saharan Africa (SSA). This study produced the first spatially explicit, coherent and complete maps of the rootable depth and RZ-PAWHC of soil in SSA. We compiled geo-referenced data from 28,000 soil profiles from SSA, which were used as input for digital soil mapping (DSM) techniques to produce soil property maps of SSA. Based on these soil properties, we developed and parameterised (pedotransfer) functions, rules and criteria to evaluate soil water retention at field capacity and wilting point, the soil fine earth fraction from coarse fragments content and, for maize, the soil rootability (relative to threshold values) and rootable depth. Maps of these secondary soil properties were derived using the primary soil property maps as input for the evaluation rules and the results were aggregated over the rootable depth to obtain a map of RZ-PAWHC, with a spatial resolution of 1 km2. The mean RZ-PAWHC for SSA is 74 mm and the associated average root zone depth is 96 cm. Pearson correlation between the two is 0.95. RZ-PAWHC proves most limited by the rootable depth but is also highly sensitive to the definition of field capacity. The total soil volume of SSA potentially rootable by maize is reduced by one third (over 10,500 km3) due to soil conditions restricting root zone depth. Of these, 4800 km3 are due to limited depth of aeration, which is the factor most severely limiting in terms of extent (km2), and 2500 km3 due to sodicity which is most severely limiting in terms of degree (depth in cm). Depth of soil to bedrock reduces the rootable soil volume by 2500 km3, aluminium toxicity by 600 km3, porosity by 120 km3 and alkalinity by 20 km3. The accuracy of the map of rootable depth and thus of RZ-PAWHC could not be validated quantitatively due to absent data on rootability and rootable depth but is limited by the accuracy of the primary soil property maps. The methodological framework is robust and has been operationalised such that the maps can easily be updated as additional data become available., Highlights • Rootable depth & root zone plant-available water holding capacity mapped for SSA • Average rootable depth is 96 cm and associated RZ-PAWHC is 74 mm. • Rootable volume reduced by a third due to restrictive aeration, sodicity, bedrock • Accuracy rootable depth map cannot be validated due to lack of data on rootability. • Robust framework; maps can be updated as extra data become available.

tReducing plant growth to limit their susceptibility to diseases has been proposed as a way to reducepesticide use, but reducing crop growth may have detrimental effect on yield. In this paper, we test thehypothesis of a trade-off between maintaining grape yield and reducing grapevine susceptibility to pow-dery mildew (Erysiphe necator) and grey mould (Botrytis cinerea), two major diseases of the grapevine(Vitis vinifera L.). Grapevine susceptibility to these two diseases was measured by relevant features ofgrapevine vegetative development identified in previous studies: leaf biomass at flowering for powderymildew and pruning mass for grey mould. Data were collected during a 3-year field experiment in a vine-yard located in the south of France, in which pests and disease were controlled by spraying pesticides. Thetwo pathogens studied in this paper were chosen because they differ in terms of their biology (biotrophvs necrotroph) and their interaction with the grapevine (the highest grapevine susceptibility occurs earlyin the cycle for powdery mildew and late in the cycle for grey mould), in order to give genericity to theresults. Results confirmed the hypothesis of a trade-off between maintaining grape yield and reducinggrapevine susceptibility to both pathogens through reduced vegetative growth, but provided evidencethat win–win situations (high yield, low susceptibility) do exist. Moreover, we found a synergy betweenreducing grapevine susceptibility to powdery mildew and grey mould. These results suggest opportuni-ties to reduce fungicide use when a win–win situation occurs as the risk of yield and quality losses maybe lower in those years. Inter-annual variation in water stress at flowering was found to be a key driverof the balance between grape yield and grapevine susceptibility to both pathogens through their effecton the source–sink balance of the grapevine. Water stress at flowering appeared as a relevant indicatorto inform the probability of occurrence of a win–win situation. Our results suggest that it could also beused to adapt management practices like irrigation, cover cropping or a combination of both, to reacha win–win situation. The relevance of these findings to vineyards in similar semi-arid environments is discussed.

Maintaining grapevine productivity with limited inputs is crucial in Mediterranean areas. Apart from water, nitrogen (N) is also an important limiting factor in grape growing. The effects of N deficiency on grapevine growth were investigated in this study. Two-year-old Vitis vinifera L.cv. Shiraz plants grafted on 110 R were grown in pots placed outside and exposed to various N supplies (0, 0.6, 1.2, 2.4 and 12 g plant–1) under well-watered conditions. At veraison, plants were harvested and organs separately dried, weighed and analysed for N. During plant growth, the length of the primary and secondary axes and the number of leaves on them were recorded. The N content of leaves was also analysed at three phenological stages (flowering, bunch closure and veraison). All growth processes were inhibited by N deficiency in an intensity-dependent manner. Quantitative relationships with N supply were established. Vegetative growth responded negatively to N stress when comparing control N supply with no N supply: primary axis elongation (–61%), leaf emergence on the primary axis (–47%), leaf emergence on the secondary axis (–94%) and lamina area expansion (–45%). Significant differences on the plant N status were observed from flowering onwards which might be useful for managing fertilisation.

Grapevine yield formation extends over two consecutive years (seasons 1 and 2). The inflorescence formation (around flowering in season 1) is crucial as it is involved in the formation of both the bunch number per vine and the berry number per bunch in season 2, that account for about 60% and 30% of year-to-year yield variation of grapevine, respectively. Light, temperature, water and nitrogen availability are known to affect this early stage. The aims of this work were to determine the critical periods during which inflorescence formation is sensitive to water and nitrogen stress and quantify their effects on it. To address these issues, we used a 3-year (2010–2012) field experiment (cv. Shiraz) in combination with a water balance simulation model (WaLIS) and a 6-year field experiment (cv. Aranel). In both experiments, different treatments were applied to create a gradient of water and nitrogen supply (treatments involved cover cropping, irrigation and fertilization). The grapevine yield and its components were recorded. Water and nitrogen status of grapevine were monitored throughout the season. Inflorescence formation was sensitive to water and nitrogen stress during a critical period that occurred between 400 and 700 °Cd after budburst in season 1. Bud fertility (number of bunches per shoot) and berry number per bunch in season 2 were significantly correlated with the fraction of transpirable soil water (FTSW), predawn leaf water potential and leaf nitrogen content at that time for both cultivars. Water and nitrogen stress during the critical period of season 1 determined 65–70% of grapevine yield in season 2. Our results show that the maximum yield that can be reached in season 2 is determined during the critical period of season 1 and they provide clues to estimate it. These results may help grape growers to adapt their practices (i) in season 1 to ensure a sufficient maximum yield for season 2 and (ii) to actually obtain the targeted yield in season 2 depending on the maximum yield determined in season 1.

Sustainable development of agriculture in Europe relies on the design of innovative cropping systems able to achieve high productive performance (quantity and quality) with low use of pesticides, while remaining compatible with socio-economic (e.g. labour use) and other environmental objectives (e.g. energy use). Over the last decade, this has led to the emergence of inter-disciplinary research activities driven by system’s analysis and design methodologies. Designing such multifunctional cropping systems requires to develop new knowledge on the relationships between the structure of agroecosystems, the processes involved in plants and pest/disease interactions and how they influence the productive performances of the system and the trade-offs with the other agroecosystem’s services. Designing a “pest suppressive or less susceptible” agroecosystem with less chemical inputs generally leads to complexify its structure (e.g. more plants species in rotation and or association) and put emphasis on poorly known processes such as the interaction between plant vigor and the trade-off between pest/diseases susceptibility on one side and yield formation on the other side. Conceptual models have been developed to integrate existing knowledge from various disciplines, as well as expert knowledge, in order to analyze how the various cropping techniques, including pesticides and genotypes, can be combined in an operational Technical System (TS), in order to manipulate the process involved in plant productivity and pest/disease control to reach the set of objectives fixed for a given context (a farm in a soil/climate and a supply chain). Analysis and management indicators are essential tools to provide information, under field conditions, on the agroecosystem processes and properties in order to guide the design process and support decisions for the management of the TS. Prototyping methodologies have been developed to conceptualize these innovative TS, test them in system’s experiments, evaluate them with a set of assessment indicators and adjust them to reach a targeted compromise among agroecosystem’s services in a progress loop. In return this design oriented approach yields new knowledge on the emerging properties of the agroecosystem and new questions on poorly understood processes or components, which can be further used to prioritize research objectives and conduct analytical experiments. Simulation models can contribute to the approach at various steps and their role and nature will be discussed on the basis of processes to be simulated, affordable uncertainty and available data for their parameterization/evaluation. Specific questions arise from this field-based approach on how to integrate it at farm and landscape scales and how to ensure farmer’s and stakeholder’s involvement in the design/assessment process in order to increase the probability of adoption of these TS by farmers. We will illustrate these concepts, methods and new knowledge on the example of vineyards with results and research questions emerging from the EcoViti network in France

In perennial crops such as grapevine, there is a considerable risk of soil degradation caused by mechanization. Organic farming may increase traffic and result in more intensive soil structure degradation, especially on wet soil. Soil structure was observed in 69 soil profiles from 12 vineyards (Languedoc-Roussillon, Bordeaux, Provence, Burgundy, Rhone Valley) to study the relationships between permanent soil characteristics (texture, stoniness, waterlogging), cultivation practices (technical operations, traffic, farm equipment) and soil structure. Compaction zones were identified in soil profiles viewed perpendicularly to the grapevine rows. The percentage of compacted area and a score for compaction intensity were assessed in the top 0.5 m of the soil profile in three soil compartments defined by the distance from the grapevine row: (1) 0 to 0.2 m (2) 0.2 m to 0.5 m and (3) 0.5 m to the middle of the inter-row. Most soil profiles exhibited considerable compaction: 75% of the soil profiles were compacted in compartments 2 or 3. Intensity correlated with depth of compaction in compartment 2 – the deeper the compaction, the greater the compaction intensity. Four types of soil profiles could be identified, depending on the location of compacted zones and of their intensity of compaction. The factors that determined the types of soil profiles were as follows: soil vulnerability to compaction, use of moderating practices (practices that limit the risk of compaction) and traffic geometry. A statistical analysis resulted in a decision tree that provides a useful basis to choose cultivation practices that limit damage to or improve soil structure.

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Observing spatial and temporal variations of marine biodiversity from non-destructive techniques is central for understanding ecosystem resilience, and for monitoring and assessing conservation strategies, e.g. Marine Protected Areas. Observations are generally obtained through Underwater Visual Censuses (UVC) conducted by divers. The problems inherent to the presence of divers have been discussed in several papers. Video techniques are increasingly used for observing underwater macrofauna and habitat. Most video techniques that do not need the presence of a diver use baited remote systems. In this paper, we present an original video technique which relies on a remote unbaited rotating remote system including a high definition camera. The system is set on the sea floor to record images. These are then analysed at the office to quantify biotic and abiotic sea bottom cover, and to identify and count fish species and other species like marine turtles. The technique was extensively tested in a highly diversified coral reef ecosystem in the South Lagoon of New Caledonia, based on a protocol covering both protected and unprotected areas in major lagoon habitats. The technique enabled to detect and identify a large number of species, and in particular fished species, which were not disturbed by the system. Habitat could easily be investigated through the images. A large number of observations could be carried out per day at sea. This study showed the strong potential of this non obtrusive technique for observing both macrofauna and habitat. It offers a unique spatial coverage and can be implemented at sea at a reasonable cost by non-expert staff. As such, this technique is particularly interesting for investigating and monitoring coastal biodiversity in the light of current conservation challenges and increasing monitoring needs.

Accurate estimation of a crop’s yield potential (Yp) is critical to addressing long-term food security via identification of the exploitable yield gap. Due to lack of field data, efforts to quantify crop yield potential typically rely on crop models. Using the ORYZA rice crop model, we sought to estimate Yp of irrigated rice for two widely used rice varieties (M-206 and CXL745) in three major US rice-producing regions that together represent some of the highest yielding rice regions of the world. Three major issues with the crop model had to be addressed to achieve acceptable simulation of Yp; first, the model simulated leaf area index (LAI) and biomass agreed poorly for all direct-seeded systems using default settings; second, cold-induced sterility and associated yield losses were poorly simulated for environments with a large diurnal temperature variation; lastly, simulated Yp was sensitive to the specified definition of physiological maturity. Except for the simulation of cold-induced sterility, all issues could be remedied within the existing model structure. In contrast, simulation of cold-induced sterility posed a continuing challenge to accurate simulation—one that will likely require changes to ORYZA's formulation. Estimates of Yp from the modified model were validated against large multi-year data sets of experimental yields covering the majority of US rice production areas. Validation showed the adjusted model simulated Yp well, with most top yields falling within 85% of Yp for both varieties (77% and 78% observed yields within 15% of Yp for CXL745 and M-206 respectively). Maximum estimated Yp was 14.3 (range of 8.2–14.5) and 14.5 (range of 8.7–15.3) t ha‐1 for the Southern US and CA, respectively.

In France, since 1 January 2020, the law has established non-treatment distances of 3 to 20 metres between homes and areas where plant protection products are applied. To understand the impact of such a measure on agricultural areas in mainland France, we calculated the agricultural areas within 10, 50, 100 and 150 metres of homes using the Cesbio OSO database, then the RPG and BD TOPO.; En France depuis le 1er janvier 2020, la loi instaure des distances de non traitements allant de 3 à 20 mètres entre les habitations et les zones d’épandages de produits phytosanitaires. Pour comprendre l’impact d’une telle mesure sur les surfaces agricoles en France métropolitaine, nous avons calculé les surfaces agricoles à moins de 10, 50, 100 et 150 mètres des habitations avec la base de données OSO du Cesbio, puis avec le RPG et la BD TOPO.