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Budbreak date in grapevine is strictly dependent on temperature, and the correct simulation of its occurrence is of great interest since it may have major consequences on the final yield and quality. In this study, we evaluated the reliability for budbreak simulation of two modeling approaches, the chilling-forcing (CF), which describes the entire dormancy period (endo- and eco-dormancy) and the forcing approach (F), which only describes the eco-dormancy. For this, we selected six phenological models that apply CF and F in different ways, which were tested on budbreak simulation of eight grapevine varieties cultivated at different latitudes in Europe. Although none of the compared models showed a clear supremacy over the others, models based on CF showed a generally higher estimation accuracy than F where fixed starting dates were adopted. In the latter models, the accurate simulation of budbreak was dependent on the selection of the starting date for forcing accumulation that changes according to the latitude, whereas CF models were independent. Indeed, distinct thermal requirements were found for the grapevine varieties cultivated in Northern and Southern Europe. This implies the need to improve modeling of the dormancy period to avoid under- or over-estimations of budbreak date under different environmental conditions. [ABSTRACT FROM AUTHOR]

To date, assessing the adaptive measures to climate change effects on cropping systems have generally been based on data from field trials and crop models. This strategy can only explore a restricted number of options with a limited spatial extent. Therefore, we designed a questionnaire that incorporated both qualitative and quantitative aspects of climate change adaptation in the agricultural sector. The questionnaire was distributed to experts from 15 European countries to map both the observed and planned climate adaptive measures in general and for five major crops (wheat, oilseed rape, maize, potato, and grapevine) in six environmental zones (EnZs) across Europe. In northern Europe, changed timing of field operations and introduction of new crops and cultivars were the already observed as the main adaptations to a longer growing season and reduced low-temperature stress under climate change. Farmers in central and southern Europe were mainly changing water and soil management as well as adopting drought-tolerant cultivars to cope with increasing evapotranspiration and higher variability and lower predictability of rainfall. Crop protection, crop insurance, and early warning/forecast systems were considered effective ways to reduce the economic losses from increased climate-related risks and extremes. The risks and associated adaptation measures vary for different crops in different EnZs. Across Europe, changes in field operation practices, fertilisation regime, crop protection, and cultivar selection are expected to be the most prominent adaptive measures under future projected climate change. In southern and central Europe, improved irrigation systems, changing cropping systems, and revised environmental regulations and subsidy schemes are being introduced as part of adaptation planning due to the projected warmer and drier climate. In northern Europe, there are also considerations of changing landscape and environmental regulations to cope with increasing rainfall variability and changing cropping practices due to longer growing seasons. The thorough understanding of the observed and foreseen adaptations in the different zones will be helpful for supporting decision making at both farm and policy levels across Europe. [Display omitted] • Questionnaire questions were distributed to experts from 15 European countries. • The observed and planned adaptive measures to climate change were questioned. • Five major crops were selected in six environmental zones across Europe. • A picture of relevant climate adaptation measures in cropping systems was provided. [ABSTRACT FROM AUTHOR]

Human activities are projected to lead to substantial increases in temperature that will impact northern Europe during winter and southern Europe during summer. Moreover, it is expected that these changes will cause increasing water shortages along the Mediterranean and in the south-west Balkans and in the south of European Russia. The consequences on the European agricultural ecosystems are likely to vary widely depending on the cropping system being investigated (i.e. cereals vs. forage crops vs. perennial horticulture), the region and the likely climate changes. In northern Europe, increases in yield and expansion of climatically suitable areas are expected to dominate, whereas disadvantages from increases in water shortage and extreme weather events (heat, drought, storms) will dominate in southern Europe. These effects may reinforce the current trends of intensification of agriculture in northern and western Europe and extensification and abandonment in the Mediterranean and south-eastern parts of Europe. Among the adaptation options (i.e. autonomous or planned adaptation strategies) that may be explored to minimize the negative impacts of climate changes and to take advantage of positive impacts, changes in crop species, cultivar, sowing date, fertilization, irrigation, drainage, land allocation and farming system seem to be the most appropriate. In adopting these options, however, it is necessary to consider the multifunctional role of agriculture and to strike a variable balance between economic, environmental and economic functions in different European regions. [ABSTRACT FROM AUTHOR]

Climate change, involving changes in mean climate and climatic variability, is expected to severely affect agriculture and there is a need to assess its impact in order to define the appropriate adaptation strategies to cope with. In this paper, we projected a scenario of European agriculture in a +2°C (above pre-industrial levels) world in order to assess the potential effect of climatic change and variability and to test the effectiveness of different adaptation options. For this purpose, the outputs of HadCM3 General Circulation Model (GCM) were empirically downscaled for current climate (1975-2005) and a future period (2030-2060), to feed a process-based crop simulation model, in order to quantify the impact of a changing climate on agriculture emphasising the impact due to changes in the frequency of extreme events (heat waves and drought). The same climatic dataset was used to compare the effectiveness of different adaptations to a warmer climate strategies including advanced or delayed sowing time, shorter or longer cycle cultivar and irrigation. The results indicated that both changes in mean climate and climate variability affected crop growth resulting in different crop fitting capacity to cope with climate change. This capacity mainly depended on the crop type and the geographical area across Europe. A +2°C scenario had a higher impact on crops cultivated over the Mediterranean basin than on those cultivated in central and northern Europe as a consequence of drier and hotter conditions. In contrast, crops cultivated in Northern Europe generally exhibited higher than current yields, as a consequence of wetter conditions, and temperatures closer to the optimum growing conditions. Simple, no-cost adaptation options such as advancement of sowing dates or the use of longer cycle varieties may be implemented to tackle the expected yield loss in southern Europe as well as to exploit possible advantages in northern regions. [ABSTRACT FROM AUTHOR]

Risks can generally be described as the combination of hazard, exposure and vulnerability. Using this framework, we evaluated the historical and future development of risk of fire and wind damage in European forestry at the national level. Fire risk is expected to increase, mainly as a consequence of an increase in fire hazard, defined as the Fire Weather Index in summer. Exposure, defined as forest area, is expected to increase slightly as a consequence of active afforestation and abandonment of marginal agricultural areas. Adaptation options to fire risk should therefore aim to decrease the vulnerability, where a change in tree species from conifers to broadleaves had most effect. Risk for wind damage in forests is expected to increase mainly as a consequence of increase in exposure (total growing stock) and vulnerability (defined by age class and tree species distribution). Projections of future wind climate indicate an increase in hazard (storminess) mainly over Western Europe. Adaptation options should aim to limit the increase in exposure and vulnerability. Only an increase in harvest level can stop the current build-up of growing stock, while at the same time it will lower vulnerability through the reduction of the share of old and vulnerable stands. Changing species from conifers to broadleaves helps to reduce vulnerability as well. Lowering vulnerability by decreasing the rotation length is only effective in combination with a high demand for wood. Due to data limitations, no forecast of future fire area or damaged timber amount by storms was possible. [ABSTRACT FROM AUTHOR]

This paper reviews the knowledge on effects of climate change on agricultural productivity in Europe and the consequences for policy and research. Warming is expected to lead to a northward expansion of suitable cropping areas and a reduction of the growing period of determinate crops (e.g. cereals), but an increase for indeterminate crops (e.g. root crops). Increasing atmospheric CO2 concentrations will directly enhance plant productivity and also increase resource use efficiencies.In northern areas climate change may produce positive effects on agriculture through introduction of new crop species and varieties, higher crop production and expansion of suitable areas for crop cultivation. Disadvantages may be an increase in the need for plant protection, the risk of nutrient leaching and the turnover of soil organic matter. In southern areas the disadvantages will predominate. The possible increase in water shortage and extreme weather events may cause lower harvestable yields, higher yield variability and a reduction in suitable areas for traditional crops. These effects may reinforce the current trends of intensification of agriculture in northern and western Europe and extensification in the Mediterranean and southeastern parts of Europe.Policy will have to support the adaptation of European agriculture to climate change by encouraging the flexibility of land use, crop production, farming systems etc. In doing so, it is necessary to consider the multifunctional role of agriculture, and to strike a variable balance between economic, environmental and social functions in different European regions. Policy will also need to be concerned with agricultural strategies to mitigate climate change through a reduction in emissions of methane and nitrous oxide, an increase in carbon sequestration in agricultural soils and the growing of energy crops to substitute fossil energy use. The policies to support adaptation and mitigation to climate change will need to be linked closely to the development of agri-environmental schemes in the European Union Common Agricultural Policy.Research will have further to deal with the effect on secondary factors of agricultural production, on the quality of crop and animal production, of changes in frequency of isolated and extreme weather events on agricultural production, and the interaction with the surrounding natural ecosystems. There is also a need to study combined effects of adaptation and mitigation strategies, and include assessments of the consequences on current efforts in agricultural policy to develop a sustainable agriculture that also preserves environmental and social values in the rural society. [Copyright &y& Elsevier]

Realistic estimation of grain nitrogen (N; N in grain yield) is crucial for assessing N management in crop rotations, but there is little information on the performance of commonly used crop models for simulating grain N. Therefore, the objectives of the study were to (1) test if continuous simulation (multi-year) performs better than single year simulation, (2) assess if calibration improves model performance at different calibration levels, and (3) investigate if a multi-model ensemble can substantially reduce uncertainty in reproducing grain N. For this purpose, 12 models were applied simulating different treatments (catch crops, CO 2 concentrations, irrigation, N application, residues and tillage) in four multi-year rotation experiments in Europe to assess modelling accuracy. Seven grain and seed crops in four rotation systems in Europe were included in the study, namely winter wheat, winter barley, spring barley, spring oat, winter rye, pea and winter oilseed rape. Our results indicate that the higher level of calibration significantly increased the quality of the simulation for grain N. In addition, models performed better in predicting grain N of winter wheat, winter barley and spring barley compared to spring oat, winter rye, pea and winter oilseed rape. For each crop, the use of the ensemble mean significantly reduced the mean absolute percentage error (MAPE) between simulations and observations to less than 15%, thus a multi–model ensemble can more precisely predict grain N than a random single model. Models correctly simulated the effects of enhanced N input on grain N of winter wheat and winter barley, whereas effects of tillage and irrigation were less well estimated. However, the use of continuous simulation did not improve the simulations as compared to single year simulation based on the multi-year performance, which suggests needs for further model improvements of crop rotation effects. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) content can greatly affect soil quality by determining and maintaining important soil physical conditions, properties and soil functions. Management practices that maintain or enhance SOC affect soil quality and may favour the capacity of soils to sequester further organic carbon. Nevertheless, the effectiveness of these measures depends upon both the soil characteristics and the current SOC content. This study defines an indicator of soil potential stability (n-potential) allowing the most effective practices in terms of soil stability and capacity to store organic carbon to be selected. By relating the clay content to SOC content, the n-potential indicates the “potential” presence of non-complexed clay (NCC) in soils, enabling the soil stability and its capacity to store carbon (C) to be inferred. In this work, we classify soils of European regions based on five n-potential categories (i.e. >20; 15–20; 10–15; 5–10; <5). By relating the information provided by the n-potential to the specific texture of the analysed soils, priority actions (i.e. protecting the existing soil stability or promoting soil aggregate formation) that should be adopted are identified. Our findings show that the selection of the appropriate SOC management practices can greatly contribute improving soils of European regions in terms of quality and capacity to store organic carbon. The n-potential contributes to the understanding of the physical consequences on soils arising from implementation of SOC management practices. This can guide the development of policies promoting the application of such practices, and can help farmers to select the practices that are most effective in maintaining or increasing of SOC content and soil stability. [ABSTRACT FROM AUTHOR]

Abstract: We compared the performance of eight widely used, easily accessible and well-documented crop growth simulation models (APES, CROPSYST, DAISY, DSSAT, FASSET, HERMES, STICS and WOFOST) for winter wheat (Triticum aestivum L.) during 49 growing seasons at eight sites in northwestern, Central and southeastern Europe. The aim was to examine how different process-based crop models perform at the field scale when provided with a limited set of information for model calibration and simulation, reflecting the typical use of models for large-scale applications, and to present the uncertainties related to this type of model application. Data used in the simulations consisted of daily weather statistics, information on soil properties, information on crop phenology for each cultivar, and basic crop and soil management information. Our results showed that none of the models perfectly reproduced recorded observations at all sites and in all years, and none could unequivocally be labelled robust and accurate in terms of yield prediction across different environments and crop cultivars with only minimum calibration. The best performance regarding yield estimation was for DAISY and DSSAT, for which the RMSE values were lowest (1428 and 1603kgha−1) and the index of agreement (0.71 and 0.74) highest. CROPSYST systematically underestimated yields (MBE – 1186kgha−1), whereas HERMES, STICS and WOFOST clearly overestimated them (MBE 1174, 1272 and 1213kgha−1, respectively). APES, DAISY, HERMES, STICS and WOFOST furnished high total above-ground biomass estimates, whereas CROPSYST, DSSAT and FASSET provided low total above-ground estimates. Consequently, DSSAT and FASSET produced very high harvest index values, followed by HERMES and WOFOST. APES and DAISY, on the other hand, returned low harvest index values. In spite of phenological observations being provided, the calibration results for wheat phenology, i.e. estimated dates of anthesis and maturity, were surprisingly variable, with the largest RMSE for anthesis being generated by APES (20.2 days) and for maturity by HERMES (12.6). The wide range of grain yield estimates provided by the models for all sites and years reflects substantial uncertainties in model estimates achieved with only minimum calibration. Mean predictions from the eight models, on the other hand, were in good agreement with measured data. This applies to both results across all sites and seasons as well as to prediction of observed yield variability at single sites – a very important finding that supports the use of multi-model estimates rather than reliance on single models. [Copyright &y& Elsevier]

• Model errors were similar for predicted potato yield at ambient and elevated CO 2 concentration. • Models with least calibration error provided the most accurate response to elevated CO 2. • Top performing models were representative of three different model structural groups. • Four models outperformed the ensemble mean and median for more than half of the datasets. • More data on yield response to elevated CO 2 under field conditions is still needed. A multi-model inter-comparison study was conducted to evaluate the performance of ten potato crop models to accurately predict potato yield in response to elevated CO 2 (Ce) when calibrated with ambient CO 2 data (Ca). Experimental data from seven open-top chambers (OTC) and free-air−CO 2 -enrichment (FACE) facilities across continental Europe were used. Model ensemble percent errors averaged over all datasets for simulated yields were 26.5 % for Ca and 27.2 % Ce data. Metrics such as Wilmott's index of agreement (IA) and root mean square relative error (RMSRE) ranged broadly among individual models and locations, such that four of the ten models outperformed the median or mean of the ensemble for about half of the Ce datasets. These top performing models were representative of three different model structural groups, including radiation use efficiency, transpiration efficiency, or leaf-level based approaches. Relative response to an increase in CO 2 was more accurately modeled than absolute yield responses when averaged across all locations, and within 3.3 kg ppm−1 (or 5%) of observed values. Specific targets in the model structure needed for improvement were not identified due to large and inconsistent variation in the accuracy of yield predictions across locations. However, models with the lowest calibration errors tended to be top performers for Ce predictions as well. Such results suggest calibration is at least as important as model structure. Where possible, modelers using potato models to estimate Ce responses should use Ce calibration data to improve confidence in such predictions. [ABSTRACT FROM AUTHOR]

Food security relies on the resilience of staple food crops to climatic variability and extremes, but the climate resilience of European wheat is unknown. A diversity of responses to disturbance is considered a key determinant of resilience. The capacity of a sole crop genotype to perform well under climatic variability is limited; therefore, a set of cultivars with diverse responses to weather conditions critical to crop yield is required. Here, we show a decline in the response diversity of wheat in farmers' fields in most European countries after 2002-2009 based on 101,000 cultivar yield observations. Similar responses to weather were identified in cultivar trials among central European countries and southern European countries. A response diversity hotspot appeared in the trials in Slovakia, while response diversity "deserts" were identified in Czechia and Germany and for durum wheat in southern Europe. Positive responses to abundant precipitation were lacking. This assessment suggests that current breeding programs and cultivar selection practices do not sufficiently prepare for climatic uncertainty and variability. Consequently, the demand for climate resilience of staple food crops such as wheat must be better articulated. Assessments and communication of response diversity enable collective learning across supply chains. Increased awareness could foster governance of resilience through research and breeding programs, incentives, and regulation., Competing Interests: The authors declare no conflict of interest., (Copyright © 2019 the Author(s). Published by PNAS.)

Understanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropping systems (1984-2009) and drivers of climate change impacts to 2050. Results reveal that for the current genotypes and mix of irrigated and rainfed production, climate change would lead to yield losses for grain maize and gains for winter wheat. Across Europe, on average heat stress does not increase for either crop in rainfed systems, while drought stress intensifies for maize only. In low-yielding years, drought stress persists as the main driver of losses for both crops, with elevated CO 2 offering no yield benefit in these years.