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We present a comprehensive, high-quality dataset characterizing soil–vegetation and land surface processes from continuous measurements conducted in two climatically contrasting study regions in southwestern Germany: the warmer and drier Kraichgau region with a mean temperature of 9.7 ∘C and annual precipitation of 890 mm and the cooler and wetter Swabian Alb with mean temperature 7.5 ∘C and annual precipitation of 1042 mm. In each region, measurements were conducted over a time period of nine cropping seasons from 2009 to 2018. The backbone of the investigation was formed by six eddy-covariance (EC) stations which measured fluxes of water, energy and carbon dioxide between the land surface and the atmosphere at half-hourly resolution. This resulted in a dataset containing measurements from a total of 54 site years containing observations with a multitude of crops, as well as considerable variation in local growing-season climates. The presented multi-site, multi-year dataset is composed of crop-related data on phenological development stages, canopy height, leaf area index, vegetative and generative biomass, and their respective carbon and nitrogen content. Time series of soil temperature and soil water content were monitored with 30 min resolution at various points in the soil profile, including ground heat fluxes. Moreover, more than 1200 soil samples were taken to study changes of carbon and nitrogen contents. The dataset is available at https://doi.org/10.20387/bonares-a0qc-46jc (Weber et al., 2021). One field in each region is still fully set up as continuous observatories for state variables and fluxes in intensively managed agricultural fields.

Despite the large body of research surrounding crop growth parameters, there is still a lack of systematic assessments on how harvestable yields of different crop types respond to varying levels of shading. However, with the advent of agrivoltaic systems, a technology that combines energy and food production, shade tolerance of cropping systems is becoming increasingly important. To address this research gap, a meta-analysis with data from two experimental approaches (intercropping and artificial shading with cloths, nets or solar panels) was performed. The aim was to quantitatively assess the susceptibility of different temperate crop types to increasing levels of shading. Crop type specific yield response curves were developed as a function of reduction in solar radiation, estimating relative crop yields compared to the unshaded controls. Only studies that reported reduction in solar radiation and crop yield per area in temperate and subtropical areas were included. The results suggested a nonlinear relationship between achieved crop yields and reduction in solar radiation for all crop types. Most crops tolerate reduced solar radiation up to 15%, showing a less than proportional yield decline. However, significant differences between the response curves of the following crop types existed: Berries, fruits and fruity vegetables benefited from reduction in solar radiation up to 30%. Forages, leafy vegetables, tubers/root crops, and C3 cereals initially showed less than proportional crop yield loss. In contrast, maize and grain legumes experienced strong crop yield losses even at low shade levels. The results provide a set of initial indicators that may be used in assessing the suitability of crop types for shade systems, and thus for agrivoltaic or other dual land-use systems. Detailed yield response curves, as provided by this study, are valuable tools in optimizing the output of annual crop components in these systems.

The present study evaluated the interactive effects of global change and heavy metals on the growth and development of three soybean [Glycine max (L.) Merrill] cultivars and the consequences on yield and food safety. Soybean cultivars (Alim 3.14 from Argentina, and ES Mentor and Sigalia, from Germany) were grown until maturity in heavy metals polluted soils from the Rhine Valley, Germany, at two CO

Agrivoltaic (AV) systems integrate the production of agricultural crops and electric power on the same land area through the installation of solar panels several meters above the soil surface. It has been demonstrated that AV can increase land productivity and contribute to the expansion of renewable energy production. Its utilization is expected to affect crop production by altering microclimatic conditions but has so far hardly been investigated. The present study aimed to determine for the first time how changes in microclimatic conditions through AV affect selected agricultural crops within an organic crop rotation. For this purpose, an AV research plant was installed near Lake Constance in south-west Germany in 2016. A field experiment was established with four crops (celeriac, winter wheat, potato and grass-clover) cultivated both underneath the AV system and on an adjacent reference site without solar panels. Microclimatic parameters, crop development and harvestable yields were monitored in 2017 and 2018. Overall, an alteration in microclimatic conditions and crop production under AV was confirmed. Photosynthetic active radiation was on average reduced by about 30% under AV. During summertime, soil temperature was decreased under AV in both years. Furthermore, reduced soil moisture and air temperatures as well as an altered rain distribution have been found under AV. In both years, plant height of all crops was increased under AV. In 2017 and 2018, yield ranges of the crops cultivated under AV compared to the reference site were −19 to +3% for winter wheat, −20 to +11% for potato and −8 to −5% for grass-clover. In the hot, dry summer 2018, crop yields of winter wheat and potato were increased by AV by 2.7% and 11%, respectively. These findings show that yield reductions under AV are likely, but under hot and dry weather conditions, growing conditions can become favorable.

Aims The general aim of this meta-analysis is to synthesize and summarize the mean response of barley yield variables to elevated CO2 (eCO2) and how temperature and nitrogen (N) affect the CO2-induced yield responses of barley. Methods A meta-analysis procedure was used to analyze five yield variables of barley extracted from 22 studies to determine the effect size and the magnitude concerning eCO2 and its interaction with temperature and N. Results CO2 enrichment increased aboveground biomass (23.8%), grain number (24.8%), and grain yield (27.4%). The magnitude of the responses to eCO2 was affected by genotype, temperature, nitrogen, and CO2 exposure methods. Genotype “Anakin” shows the highest CO2 response of aboveground biomass (47.1%), while “Bambina” had the highest grain number (58.4%). Grain yield response was observed to be higher for genotypes “Alexis” (38.1%) and “Atem” (33.7%) under eCO2. The increase of aboveground biomass and grain yield was higher when plants were grown under eCO2 in combination with higher N (151–200 kg ha−1). The interaction between eCO2 and three different temperature levels was analyzed to identify the impacts on barley yield components. The results revealed that the CO2-induced increase in grain number and grain yield was higher in combination with a temperature level of 21–25 °C as compared to lower levels (2 was higher in growth chambers than in other CO2 exposure methods. Moreover, a higher response of aboveground biomass and grain yield to eCO2 was observed for pot-grown plants compared to field-grown. Conclusions Overall, results suggest that the maximal barley production under eCO2 will be obtained in combination with high N fertilizer and temperature levels (21–25 °C).

We present a comprehensive, high-quality dataset characterising soil-vegetation and land-surface processes from continuous measurements conducted in two climatically contrasting study regions in South West Germany: the warmer and drier Kraichgau region with a mean temperature of 9.7 °C and annual precipitation of 890 mm, and the cooler and wetter Swabian Alp with mean temperature 7.5 °C and annual precipitation 1042 mm. In each region, measurements were conducted over a time period of nine cropping seasons from 2009 to 2018. The backbone of the investigation was formed by six eddy-covariance stations (EC) which measured fluxes of water, energy and carbon dioxide between the land surface and the atmosphere at half-hourly resolution. This resulted in a dataset containing measurements from a total of 54 site*years containing observations with a multitude of crops, as well as considerable variation in local growing season climates. The presented multi-site, multi-year data set is composed of crop-related data on phenological development stages, canopy height, leaf area index, vegetative and generative biomass and their respective carbon and nitrogen content. Time series of soil temperature and soil water content were monitored with 30-min resolution at various points in the soil profile, including ground heat fluxes. Moreover, more than 1,200 soil samples were taken to study changes of carbon and nitrogen contents. The data set was uploaded to the Pangaea database and can be accessed at https://doi.org/10.20387/bonares-a0qc-46jc (for the review process, please refer to the data availability section). One station in each region has now been set up as continuous observatories of state variables and fluxes in intensively managed agricultural fields.

Increasing air and soil temperatures and changes in precipitation patterns as consequences of climate change will affect crop production in agricultural ecosystems. The combined effects of soil warming and altered precipitation on the productivity and product quality of oil crops are not yet well studied. Winter oilseed rape (OSR) (Brassica napus L., cv. Mercedes) was field-grown under elevated soil temperature (+2.5 &deg, C), reduced precipitation amount (&minus, 25%), reduced precipitation frequency (&minus, 50%) both separately and in combination in order to investigate effects on crop development, seed yield, and seed quality. Soil warming accelerated crop development during early plant growth and during spring. At maturity, however, plants in all treatments were similar in quantitative (aboveground biomass, seed yield) and qualitative (protein and oil content, amino acids, fatty acids) parameters. We observed the long-term effects of the precipitation manipulation on leaf size, leaf senescence and biomass allocation. Seed yield was not affected by the altered climatic factors, perhaps due to adaptation of soil microorganisms to permanent soil warming and to relatively wet conditions during the seed-filling period. Overall, OSR performed well under moderate changes in soil temperature and precipitation patterns, thus, we observed stable seed yield without negative impacts on nutritive seed quality.

Rising demand for solar power generation will lead to increased land use competition, and thus to potential economic and social conflict. A solution to this challenge is to produce food and energy within an agrophotovoltaics (APV) system. Since 2017, governments in Japan, France, Massachusetts (USA), South Korea, and China have introduced policies supporting APV implementation. Governments considering APV implementation – e.g. in India and Germany – for evidence-based policy making are demanding information on how levelized cost of electricity (LCOE) of APV differs from that of conventional ground-mounted photovoltaics (PV), as well as on how additional costs associated with APV installation relate to the benefit of maintaining agricultural activity under APV. Data for a techno-economic price-performance ratio calculation has been retrieved from an inter- and transdisciplinary APV case study in Germany. We observed that the LCOE of APV with €0.0828 kWh−1 is 38% higher than that of ground-mounted PV, resulting in an annual cropland preservation price of €9,052 ha−1 a−1. The annual revenue of potato and winter wheat production under APV resulted in a performance of €10,707 ha−1 a−1 and €1,959 ha−1 a−1 respectively, leading to a beneficial price-performance ratio of 0.85 for potato production and, with a ratio of 4.62, a disadvantageous result for winter wheat. Overall, APV is not necessarily recommended in crop rotating systems. However, in combination with permanent cultures – e.g. berries, fruits, or wine grapes – as the price for these types of applications is lower, while at the same time providing higher performance by optimizing techno-ecological synergies.

The spatial variability of topsoil water content (SWC) is often expressed through the relationship between its spatial mean 〈θ〉 and standard deviation σθ. The present study tests the concept that a reasonably performing land surface model (LSM) should be able to produce σθ–〈θ〉 data pairs that fall into a polygon, spanned by the cloud of observed data and two anchor points: σθ at the permanent wilting point σθ–〈θwp〉 and σθ at saturation σθ–〈θs〉. A state-of-the-art LSM, Noah-MP, was driven by atmospheric forcing data obtained from eddy covariance field measurements in two regions of southwestern Germany, Kraichgau (KR) and Swabian Alb (SA). KR is characterized with deep loess soils, whereas the soils in SA are shallow, clayey, and stony. The simulations series were compared with SWC data from soil moisture networks operating in the two study regions. The results demonstrate that Noah-MP matches temporal 〈θ〉 dynamics fairly well in KR, but performs poorly in SA. The best match is achieved with the van Genuchten–Mualem representation of soil hydraulic functions and site-specific rainfall, soil texture, green vegetation fraction (GVF) and leaf area index (LAI) input data. Nevertheless, most of the simulated σθ–〈θ〉 pairs are located outside the envelope of measurements and below the lower bound, which shows that the model smooths spatial SWC variability. This can be mainly attributed to missing topography and terrain information and inadequate representation of spatial variability of soil texture and hydraulic parameters, as well as the model assumption of a uniform root distribution.

HOSUT wheat, enhanced in grain sucrose transport, has a superior performance for yield-related traits, partially phenocopies effects from CO2 enrichment, and benefits more from high N fertilization., Crop yield stability must be ensured under future climate conditions such as elevated CO2 and high temperatures. We tested ‘HOSUT’, a winter wheat line expressing a grain-targeted sucrose transporter of barley in response to combinations of CO2 enrichment, a heat wave, and high nitrogen fertilization. Compared with wild-type Certo, HOSUT had a superior performance for grain yield, aboveground biomass, and ears per plant, obviously due to transgene activity in developing grains and young vegetative sinks. HOSUT grains were larger and contained more endosperm cells. HOSUT and high CO2 effects similarly improved phenological and yield-related traits. Significant HOSUT–CO2 interactions for biomass of stems, ears, grain yield, nitrogen yield, and grain number revealed that Certo was promoted by CO2 enrichment, whereas HOSUT responded weakly. CO2 enrichment strongly reduced and HOSUT effects weakly reduced grain nitrogen, storage proteins, and free amino acids. In contrast to CO2 enrichment, HOSUT effects did not impair grain micronutrient concentrations. Significant HOSUT–nitrogen fertilization interactions for ear biomass, grain yield, grain number per plant, and harvest index indicated that HOSUT benefited more from additional nitrogen. The heat wave decreased aboveground and ear biomass, grain yield, harvest index, grain size, and starch and water use, but increased grain sucrose concentration.

Elevated carbon dioxide (eCO2) is well known to stimulate plant photosynthesis and growth. Elevated carbon dioxide&rsquo, s effects on crop yields are of particular interest due to concerns for future food security. We compiled experimental data where field-grown wheat (Triticum aestivum Linnaeus) was exposed to different CO2 concentrations. Yield and yield components were analyzed by meta-analysis to estimate average effects, and response functions derived to assess effect size in relation to CO2 concentration. Grain yield increased by 26% under eCO2 (average ambient concentration of 372 ppm and elevated 605 ppm), mainly due to the increase in grain number. The response function for grain yield with CO2 concentration strongly suggests a non-linear response, where yield stimulation levels off at ~600 ppm. This was supported by the meta-analysis, which did not indicate any significant difference in yield stimulation in wheat grown at 456&ndash, 600 ppm compared to 601&ndash, 750 ppm. Yield response to eCO2 was independent of fumigation technique and rooting environment, but clearly related to site productivity, where relative CO2 yield stimulation was stronger in low productive systems. The non-linear yield response, saturating at a relatively modest elevation of CO2, was of large importance for crop modelling and assessments of future food production under rising CO2.

International audience; AbstractThe expansion of renewable energies aims at meeting the global energy demand while replacing fossil fuels. However, it requires large areas of land. At the same time, food security is threatened by the impacts of climate change and a growing world population. This has led to increasing competition for limited land resources. In this context, the combination of photovoltaics and plant production — often referred to as agrophotovoltaic (APV) or agrivoltaic systems — has been suggested as an opportunity for the synergistic combination of renewable energy and food production. Although this technology has already been applied in various commercial projects, its practicability and impact on crop production have hardly been investigated. In this review, we give a short summary of the current state of the art and prospective opportunities for the application of APV systems. In addition, we discuss microclimatic alterations and the resulting impacts of APV on crop production. Our main findings are that (1) crop cultivation underneath APV can lead to declining crop yields as solar radiation is expected to be reduced by about one third underneath the panels. However, microclimatic heterogeneities and their impact on crop yields are missing reference and thus, remain uncertain. (2) Through combined energy and crop production, APV can increase land productivity by up to 70%. (3) Given the impacts of climate change and conditions in arid climates, potential benefits are likely for crop production through additional shading and observed improvements of water productivity. (4) In addition, APV enhances the economic value of farming and can contribute to decentralized, off-grid electrification in developing and rural areas, thus further improving agricultural productivity. As such, APV can be a valuable technical approach for more sustainable agriculture, helping to meet current and prospective needs of energy and food production and simultaneously sparing land resources.

Agrivoltaic (AV) systems increase land productivity through the combined production of renewable energy and food. Although several studies have addressed their impact on crop production, many aspects remain unexplored. The objective of this study was to determine the effects of AV on the cultivation of celeriac, a common root vegetable in Central Europe. Celeriac was cultivated in 2017 and 2018 as part of an organically managed on-farm experiment, both underneath an AV system and in full-sun conditions. Under AV, photosynthetic active radiation was reduced by about 30%. Monitoring of crop development showed that in both years, plant height increased significantly under AV. Fresh bulb yield decreased by about 19% in 2017 and increased by about 12% in 2018 in AV, but the changes were not significant. Aboveground biomass increased in both years under AV, but only increased significantly in 2018. As aboveground biomass is a determinant of root biomass at harvest in root vegetables, bulb yields may be further increased by a prolonged vegetation period under AV. Compound analysis of celeriac bulbs did not show any clear effects from treatment. As harvestable yields were not significantly reduced, we concluded that celeriac can be considered a suitable crop for cultivation under AV.

The energy balance of eddy covariance (EC) measurements is typically not closed. This so-called energy balance closure (EBC) problem has been a long-standing issue in micrometeorology. It is a main challenge in evaluating and interpreting EC flux data. EBC is crucial for validating and improving regional and global climate models. To investigate the reasons behind EBC more closely for agro-ecosystems, we analysed EC measurements from two climatically contrasting regions (Kraichgau (KR) and Swabian Jura (SJ)) in southwest Germany. Data were taken at six fully equipped EC sites from 2010 to 2017. The gap in EBC was quantified by ordinary linear regression, by the energy balance ratio (EBR) between turbulent fluxes and available energy, and by the residual energy term. In order to examine potential reasons for differences in EBC, we compared the EBC under varying environmental conditions and investigated a wide range of possible controls. Statistical analyses were conducted for the whole data set to test the effects of different regions, years, sites and crops on EBC. We also investigated whether EBC was a function of buoyancy, friction velocity, or atmospheric stability. The time-variable footprints of all EC stations were estimated based on data measured in 2015, complemented by micro-topographic analyses along the prevailing wind direction. The lowest mean annual energy balance gap was 17 % in KR and 13 % in SJ. Highest EBRs were commonly measured for winds originating from the prevailing wind direction. The variation of EBC was higher in winter than in summer. The measurement site exerted a statistically significant effect on EBC, but not crop or region. The spread of EBR distinctly narrowed under unstable atmospheric conditions, strong buoyancy, and high friction velocities. Smaller footprint areas led to better EBC due to increasing homogeneity. Flow distortions of winds that first travelled past the back head of the anemometer affected EBC negatively.

The energy balance of eddy covariance (EC) flux data is normally not closed. Therefore, at least if used for modeling, EC flux data are usually post-closed, i.e. the measured turbulent fluxes are adjusted so as to close the energy balance. At the current state of knowledge, however, it is not clear how to partition the missing energy in the right way. Eddy flux data therefore contain some uncertainty due to the unknown nature of the energy balance gap, which should be considered in model evaluation and the interpretation of simulation results. We propose to construct the post-closure method uncertainty band (PUB), which essentially designates the differences between non-adjusted flux data and flux data adjusted with the three post-closure methods (Bowen ratio, latent heat flux (LE) and sensible heat flux (H) method). To demonstrate this approach, simulations with the NOAH-MP land surface model were evaluated based on EC measurements conducted at a winter wheat stand in Southwest Germany in 2011, and the performance of the Jarvis and Ball–Berry stomatal resistance scheme was compared. The width of the PUB of the LE was up to 110 W m–2 (21% of net radiation). Our study shows that it is crucial to account for the uncertainty of EC flux data originating from lacking energy balance closure. Working with only a single post-closing method might result in severe misinterpretations in model-data comparisons.

Data from three Swedish open-top chamber and four German FACE experiments were combined to derive response functions for elevated CO2 (eCO2) effects on Cd, Zn, Mn, protein, grain yield, grain mass and grain number of wheat. Grain yield and grain number were increased by ∼6% and ∼7%, respectively, per 100 ppm CO2; the former effect was linked to plant nitrogen status. Grain mass was not influenced by eCO2, whereas Cd concentration was reduced. Unlike Zn, Mn and protein, effects on Cd yield were not related to effects on grain yield. Yields of Mn, Zn and (weakly) protein were positively affected by eCO2. For protein, grain yield, grain mass and grain number, the results were consistent among the FACE and OTC experiments. A key conclusion was that yields of essential nutrients were enhanced (Mn > Zn > protein), although less than grain yield, which would not be expected from a simple dilution model.

Reliable regional climate projections need improved land-surface-atmosphere models in which land-surface exchange, in particular the role of the vegetation, is well represented. To get a better understanding of the land-surface exchange and as a data basis for model development, parameterization and validation, long-term eddy-covariance measurements were performed over agricultural landscapes in two regions of Southwest Germany with different regional climate: near the northern Upper Rhine Valley with a mild climate and on the Swabian Jura, a low mountain range plateau where the climate is colder and wetter. At each study site we installed three eddy-covariance weather stations and monitored the soil water regime as well as the crop development. We describe the characteristics of the study sites, the experimental field work and data processing. The dynamics of water vapor and energy fluxes over winter wheat, winter oilseed rape and silage maize were evaluated for the time period from 2009 to 2011. The accuracy of the measured energy and matter fluxes limited by statistics and instrumental noise error was better than 10 %. Energy fluxes and albedo were closely linked to crop development. The albedo increased and decreased with LAI. Albedo values up to 0.28 were measured over flowering oilseed rape. The winter crops developed faster in the milder climate. The daily average of latent heat flux was about 10–20 Wm−2 higher and that of sensible heat flux about 5–15 Wm−2 lower there in comparison with the colder climate. Differences between both regions with regard to the turbulent fluxes are assigned to be mainly due to differences in vapor pressure deficit. Actual and prevailing weather conditions had a large impact on energy fluxes so that notable differences of flux dynamics were observed not only between the regions but also at one site for the same crop in different years. The observed long-term flux dynamics are discussed with respect to phenology, regional climate and the impact of prevailing weather conditions.

In agricultural production, land-use decisions are components of economic planning that result in the strategic allocation of fields. Climate variability represents an uncertainty factor in crop production. Considering yield impact, climatic influence is perceived during and evaluated at the end of crop production cycles. In practice, this information is then incorporated into planning for the upcoming season. This process contributes to attitudes toward climate-induced risk in crop production. In the literature, however, the subjective valuation of risk is modeled as a risk attitude toward variations in (monetary) outcomes. Consequently, climatic influence may be obscured by political and market influences so that risk perceptions during the production process are neglected. We present a utility concept that allows the inclusion of annual risk scores based on mid-season risk perceptions that are incorporated into field-planning decisions. This approach is exemplified and implemented for winter wheat production in the Kraichgau, a region in Southwest Germany, using the integrated bio-economic simulation model FarmActor and empirical data from the region. Survey results indicate that a profitability threshold for this crop, the level of "still-good yield" (sgy), is 69 dt ha-1 (regional mean Kraichgau sample) for a given season. This threshold governs the monitoring process and risk estimators. We tested the modeled estimators against simulation results using ten projected future weather time series for winter wheat production. The mid-season estimators generally proved to be effective. This approach can be used to improve the modeling of planning decisions by providing a more comprehensive evaluation of field-crop response to climatic changes from an economic risk point of view. The methodology further provides economic insight in an agrometeorological context where prices for crops or inputs are lacking, but farmer attitudes toward risk should still be included in the analysis.

Elevated carbon dioxide (eCO2) stimulates wheat grain yield, but simultaneously reduces protein/nitrogen (N) concentration. Also, other essential nutrients are subject to change. This study is a synthesis of wheat experiments with eCO2, estimating the effects on N, minerals (B, Ca, Cd, Fe, K, Mg, Mn, Na, P, S, Zn), and starch. The analysis was performed by (i) deriving response functions to assess the gradual change in element concentration with increasing CO2 concentration, (ii) meta-analysis to test the average magnitude and significance of observed effects, and (iii) relating CO2 effects on minerals to effects on N and grain yield. Responses ranged from zero to strong negative effects of eCO2 on mineral concentration, with the largest reductions for the nutritionally important elements of N, Fe, S, Zn, and Mg. Together with the positive but small and non-significant effect on starch concentration, the large variation in effects suggests that CO2-induced responses cannot be explained only by a simple dilution model. To explain the observed pattern, uptake and transport mechanisms may have to be considered, along with the link of different elements to N uptake. Our study shows that eCO2 has a significant effect on wheat grain stoichiometry, with implications for human nutrition in a world of rising CO2.

Elevated carbon dioxide (eCO2) stimulates wheat grain yield, but simultaneously reduces protein/nitrogen (N) concentration. Also, other essential nutrients are subject to change. This study is a synthesis of wheat experiments with eCO2, estimating the effects on N, minerals (B, Ca, Cd, Fe, K, Mg, Mn, Na, P, S, Zn), and starch. The analysis was performed by (i) deriving response functions to assess the gradual change in element concentration with increasing CO2 concentration, (ii) meta-analysis to test the average magnitude and significance of observed effects, and (iii) relating CO2 effects on minerals to effects on N and grain yield. Responses ranged from zero to strong negative effects of eCO2 on mineral concentration, with the largest reductions for the nutritionally important elements of N, Fe, S, Zn, and Mg. Together with the positive but small and non-significant effect on starch concentration, the large variation in effects suggests that CO2-induced responses cannot be explained only by a simple dilution model. To explain the observed pattern, uptake and transport mechanisms may have to be considered, along with the link of different elements to N uptake. Our study shows that eCO2 has a significant effect on wheat grain stoichiometry, with implications for human nutrition in a world of rising CO2.

Interactions between the soil, the vegetation, and the atmospheric boundary layer require close attention when predicting water fluxes in the hydrogeosystem, agricultural systems, weather, and climate. However, land-surface schemes used in large-scale models continue to show deficiencies in consistently simulating fluxes of water and energy from the subsurface through vegetation layers to the atmosphere. In this study, the multiphysics version of the Noah land-surface model (Noah-MP) was used to identify the processes, which are most crucial for a simultaneous simulation of water and heat fluxes between land surface and the lower atmosphere. Comprehensive field data sets of latent and sensible heat fluxes, ground heat flux, soil moisture, and leaf area index from two contrasting field sites in South-West Germany are used to assess the accuracy of simulations. It is shown that an adequate representation of vegetation-related processes is the most important control for a consistent simulation of energy and water fluxes in the soil-plant-atmosphere system. In particular, using a newly implemented submodule to simulate root growth dynamics has enhanced the performance of Noah-MP. We conclude that further advances in the representation of leaf area dynamics and root/soil moisture interactions are the most promising starting points for improving the simulation of feedbacks between the subsoil, land surface and atmosphere in fully coupled hydrological and atmospheric models.

[1] Six models with differing representation of the physical process in the coupled soil-plant system are tested to simultaneously reproduce the dynamics of soil water contents, evapotranspiration, and leaf area index during a growing season of winter wheat at two contrasting field plots in the Kraichgau and the Swabian Alb regions in South-West Germany. The main aim of the study is the assessment of the performance and the identification of structural deficits of the models LEACHN, SUCROS, CERES, GECROS, and SPASS as well as the land-surface model CLM3.5. The calibration of each model is posed in a multiobjective framework with three different objective functions that summarize the fit between model simulations and the three observation types. The AMALGAM evolutionary search algorithm is utilized to simultaneously estimate the most important soil hydraulic and plant parameters. The six models exhibit a wide variability in the trade-offs between the fitting to the data types. Mechanistic process description, particularly of the root system, reduces the trade-off considerably for the SPASS and GECROS models. These models adequately simulate the reduction of root water uptake and transpiration during senescence under nonlimited soil water supply. The SPASS model in particular shows an overall better performance as compared to the more simpler models which is related to an adequate level of structural complexity in the interplay of all model compartments combined with a relatively low parameter sensitivity to the weighting scheme in the multiobjective optimization. The dynamic consideration of the root system formation is particularly important, which is simulated quite detailed in the SPASS model as a function of nitrogen (N) and water availability in the different soil horizons. The proposed multiobjective calibration procedure proved to be very useful to identify processes that are important to adequately simulate the coupled soil-plant system. The consideration of these processes and our insights about the value of different data types for model calibration is expected to lead to more accurate, predictive land-surface models.

The concentration and composition of free amino acids and carbohydrates in the phloem sap of wheat and oilseed rape (OSR) and the effects on the performance of aphids (Rhopalosiphum padi and Myzus persicae) were determined under atmospheric carbon dioxide (CO2) enrichment. The analysis of phloem sap showed that carbohydrates and amino acid levels of the host plants were significantly affected by elevated CO2 level. Among carbohydrate concentrations in the phloem sap, significant increases were observed in fructose and glucose in spring wheat under CO2 enrichment, whereas no changes were observed in OSR. These changes in plant chemistry affected the performance of herbivorous insects (i.e. aphids) in varying ways, positively affecting the relative growth rate (RGR) of R. padi in spring wheat and negatively affecting the RGR of M. persicae on OSR.

We present a method for experimental design, optimizing data acquisition for maximum confidence in the soil-plant model selection task. The method considers uncertainty in parameters, measurements and model structures. We combine Bayesian Model Averaging (BMA) with worth-of-data analysis and investigate how decisive the model weights are under different selections of data types. This allows assessing the power of different data types, data densities and data locations in identifying the best model structure from among a suite of plausible models. The models considered in this study are the crop models CERES, SUCROS, GECROS and SPASS, which are coupled to identical routines for simulating soil processes within the modeling framework Expert-N. The four models considerably differ in the degree of detail at which crop growth and root water uptake are represented. Monte-Carlo simulations were conducted for each of these models considering their uncertainty in soil hydraulic properties and selected crop model parameters. With Bayesian model updating by a Bootstrap filter, the models were then conditioned on field measurements of soil moisture, leaf area index (LAI), and evapotranspiration rates during a vegetation period of winter wheat in Nellingen, Southwestern Germany. Following our approach, we derived the BMA model weights when using all data or different subsets thereof. We discuss to which degree the posterior BMA mean outperformed the prior BMA mean and all individual posterior models, how informative the data types were for reducing prediction uncertainty of actual evapotranspiration, and how well the model structure can be identified based on the different data types and subsets.

We used the modeling package Expert-N to investigate the ability of four generic-mechanistic crop models that were originally developed under field conditions to simulate the plant growth of spring wheat grown in open-top chambers (OTC) under different environmental conditions. We focus on the impacts of water limitation and elevated atmospheric CO(2) concentration on biomass production. Expert-N facilitates the comparison of the components of agro-ecosystem models because it allows the exchange of single modules while leaving the rest of the model unchanged. The crop growth part of the models SPASS, CERES-Wheat, SUCROS and GECROS were combined with the Penman-Monteith equation for potential evapotranspiration, the HYDRUS-1D model for water transport and the LEACHN model for nitrogen transport and turnover simulation. The models were applied to a data set provided by OTC experiments with spring wheat (Triticum aestivum L cv. 'Minaret') that was grown under two atmospheric CO(2) concentrations (ambient/elevated), two irrigation schemes (non-limited water supply/water limitation) and two soil types (Cambisol/Chernosem) in two subsequent vegetation periods (1998/1999). Based on the model calibration using experimental and literature data, the best simulation results describing the impact of the considered environmental conditions were obtained using the SUCROS model followed by the SPASS, GECROS and CERES models. The study depicts the shortcomings of the underlying processes in all of the models. These shortcomings need to be addressed when models are applied on regional scales or for prediction under climate change conditions.

Elevated atmospheric carbon dioxide concentrations ([CO2]) might change the abundance and the function of soil microorganisms in the depth profile of agricultural soils by plant-mediated reactions. The seasonal pattern of abundance and activity of nitrate-reducing bacteria was studied in a Mini-FACE experiment planted with oilseed rape (Brassica napus). Three depths (0–10, 10–20 and 20–30 cm) were sampled. Analyses of the abundances of total (16S rRNA gene) and nitrate-reducing bacteria (narG, napA) revealed strong influences of sampling date and depth, but no [CO2] effects. Abundance and activity of nitrate reducers were higher in the top soil layer and decreased with depth but were not related to extractable amounts of nitrogen and carbon in soil. Dry periods reduced abundances of total and nitrate-reducing bacteria, whereas the potential activity of the nitrate reductase enzyme was not affected. Enzyme activity was only weakly correlated to the abundance of nitrate-reducing bacteria but was related to NH4+ and NO3− concentrations. Our results suggest that in contrast to the observed pronounced seasonal changes, the elevation of atmospheric [CO2] has only a marginal impact on nitrate reducers in the investigated arable ecosystem.

In einer dreijahrigen Studie wurde Sommerweizen in Kombination mit typischen Ackerwildkrautern unter einer Freiland-CO2-Anreicherung (Mini-FACE) mit heutigen und erhohten CO2-Konzentrationen angebaut. Als Wirkungskriterien fur CO2-Effekte wurden die Verteilung stabiler Kohlenstoff-Isotope und der in vivo Blattgaswechsel analysiert. Erhohte CO2-Konzentrationen fuhrten bei den meisten Arten zu signifikanten Steigerungen der spezifischen Wassernutzungs-Effizienz (A/gs), die aus der Verteilung stabiler Kohlenstoff-Isotope abgeleitet wurde. Die Saison-Mittelwerte des Verhaltnisses von blattinterner zu atmospharischer CO2-Konzentration (ci/ca) zeigten bei einigen Arten signifikante Abnahmen unter erhohten CO2-Konzentrationen. Die Ergebnisse der Blattgaswechselmessungen bestatigten die erhohten Wassernutzungs-Effizienzen, signifikante CO2-Effekte konnten aber erst bei Betrachtung der gesamten Vegetationsperioden mittels Kohlenstoff-Isotop-Analytik belegt werden. Fur alle Ergebnisse aus den beiden Messreihen konnte gezeigt werden, dass der Sommerweizen signifikant anders reagierte als die ubrigen untersuchten Arten. Fur alle drei Versuchsjahre wurden signifikante CO2-Effekte auf das Verhaltnis zwischen A/gs und der Biomasse der Arten beobachtet. Am Ende der trockeneren Vegetationsperioden 2003 und 2004 war der Bodenwassergehalt auf den Versuchsflachen mit CO2-Anreicherung tendenziell hoher, was auf einen Wassereinspar-Effekt hindeutet. Die vorliegenden Ergebnisse belegen den Einfluss erhohter CO2-Konzentrationen auf den pflanzlichen Wasserhaushalt und zeigen eine positive Ruckkopplung, mit einer erhohten Verfugbarkeit von Bodenwasser. Aufgrund der Unterschiede in den CO2-Reaktionen von Sommerweizen und Ackerwildkrautern ist davon auszugehen, dass die ansteigenden CO2-Konzentrationen zu Artenverschiebungen zwischen Nutzpflanzen und Ackerwildkrautern fuhren.

The vapour pressure deficit (VPD) in open-top chambers (OTCs) was analysed in relation to time of day and ambient meteorology. Effects of observed VPD differences (ΔVPD) between OTCs and the ambient air (AA) on stomatal conductance ( g s ) were simulated using 10 model functions from the literature. The dataset originated from 17 OTC crop experiments performed in Belgium, Germany and Sweden. ΔVPD is the resulting difference between the OTC effect on e s ( T ), which is the temperature-dependent saturation pressure of water vapour and the OTC effect on e a , which is the prevailing partial pressure of water vapour in the air (ΔVPD = Δ e s ( T ) − Δ e a ). Both Δ e s ( T ) and Δ e a were positive during daylight hours. ΔVPD was small in comparison and sensitive to changes in Δ e s ( T ) or Δ e a . ΔVPD was negative between 07:30 and 10:30 and positive thereafter with a maximum at 20:30 (local time). The positive afternoon ΔVPD was due to an early decrease in Δ e a , probably caused by ceased transpiration, while the positive Δ e s ( T ) persisted throughout the evening, most likely because of restrained cooling in the OTCs. Both the negative morning ΔVPD and the positive evening ΔVPD were more pronounced during clear, warm and dry weather. Circumstances when VPD had a stronger limiting effect on g s inside the OTCs compared to in the ambient air coincided with high ambient ozone concentrations ([O 3 ]). Calculated wheat O 3 uptake over an [O 3 ] threshold of 40 nmol mol −1 was reduced by 8.7% in OTCs, assuming that VPD was the only factor limiting g s and that g s was the only resistance for O 3 uptake. VPD is one factor of considerable importance for g s and the OTC impact on VPD may contribute to an underestimation of O 3 effects expressed in relation to the external O 3 exposure.

Data from open-top chamber experiments with field grown crops, performed in Sweden, Finland, Belgium, Italy and Germany, were combined to derive relationships between yield and ozone exposure for wheat (Triticum aestivum L.) and potato (Solanum tuberosum L.). Three different exposure indices were compared: AOT40 (accumulated exposure over a threshold ozone concentration of 40 nmol mol−1), CUOt (cumulative stomatal uptake of ozone, using a constant ozone uptake rate threshold of t nmol m−2 s−1) and mAOTc0 (conductance modified AOT using a threshold concentration for ozone of c0 nmol mol−1). The latter is essentially a combination of AOT and CUO. Ozone uptake was estimated using a Jarvis-type multiplicative model for stomatal conductance. In terms of correlation between relative yield (RY) and ozone exposure, CUO5, the CUO index with an ozone uptake rate threshold of 5 nmol m−2 s−1, performed best for both wheat and potato, resulting in r2 values of 0.77 and 0.64, respectively. CUO5 performed considerably better in terms of the correlation between RY and ozone exposure, than AOT40 for wheat, while mAOT10, the best performing mAOT index in this case, was intermediate in performance for this crop. For potato, the differences between the different ozone exposure indices AOT40, CUO5 and mAOT20 (the mAOT index performing best for potato) in the correlation between RY and ozone exposure were relatively small. To test the assumption that the non-stomatal deposition of ozone was negligible for the uppermost, sunlit leaves, measurements of ozone uptake in relation to leaf conductance for water vapor of wheat leaves in a cuvette system were used. The non-stomatal deposition of ozone to the leaves turned out to be comparatively small. Based on the non-stomatal conductance (gns=15 mmol m−2 s−1) estimated for the wheat leaves in the cuvette system, it was concluded that the consequence of omitting the non-stomatal conductance is small. In conclusion the study indicated that the ozone uptake based approach showed a high degree of fitting along a north-south European transect of pedoclimatic conditions, and represents a better and more relevant approach to the quantification of ozone effects on crops growth than the use of ozone exposure indices purely based on ozone concentrations.

CO 2 enrichment is expected to alter leaf demand for nitrogen and phosphorus in plant species with C 3 carbon dioxide fixation pathway, thus possibly causing nutrient imbalances in the tissues and disturbance of distribution and redistribution patterns within the plants. To test the influence of CO 2 enrichment and elevated tropospheric ozone in combination with different nitrogen supply, spring wheat ( Tritium aestivum L. cv. Minaret) was exposed to three levels of CO 2 (361, 523, and 639 μl litre −1 , 24 h mean from sowing to final harvest), two levels of ozone (28.4 and 51.3 nl litre −1 ) and two levels of nitrogen supply (150 and 270 kg ha −1 ) in a full-factorial design in open-top field chambers. Additional fertilization experiments (120, 210, and 330 kg N ha −1 ) were carried out at low and high CO 2 levels. Macronutrients (N, P, K, S, Ca, Mg) and three micronutrients (Mn, Fe, Zn) were analysed in samples obtained at three different developmental stages: beginning of shoot elongation, anthesis, and ripening. At each harvest, plant samples were separated into different organs (green and senescent leaves, stem sections, ears, grains). According to analyses of tissue concentrations at the beginning of shoot elongation, the plants were sufficiently equipped with nutrients. Elevated ozone levels neither affected tissue concentrations nor shoot uptake of the nutrients. CO 2 and nitrogen treatments affected nutrient uptake, distribution and redistribution in a complex manner. CO 2 enrichment increased nitrogen-use efficiency and caused a lower demand for nitrogen in green tissues which was reflected in a decrease of critical nitrogen concentrations, lower leaf nitrogen concentrations and lower nitrogen pools in the leaves. Since grain nitrogen uptake during grain filling depended completely on redistribution from vegetative pools in green tissues, grain nitrogen concentrations fell considerably with severe implications for grain quality. Ca, S, Mg and Zn in green tissues were influenced by CO 2 enrichment in a similar manner to nitrogen. Phosphorus concentrations in green tissues, on the other hand, were not, or only slightly, affected by elevated CO 2 . In stems, ‘dilution’ of all nutrients except manganese was observed, caused by the huge accumulation of water soluble carbohydrates, mainly fructans, in these tissues under CO 2 enrichment. Whole shoot uptake was either remarkably increased (K, Mn, P, Mg), nearly unaffected (N, S, Fe, Zn) or decreased (Ca) under CO 2 enrichment. Thus, nutrient cycling in plant-soil systems is expected to be altered under CO 2 enrichment.

To identify future impacts on biomass production and yield quality of important C3 crops, spring wheat was grown in association with 13 weed species in a Mini-FACE (free-air carbon dioxide (CO2) enrichment) system under ambient (375 μl l-1) and elevated (526 μl l-1) CO2 concentrations. Wheat productivity was assessed at maturity and grain yield was subjected to various chemical analyses and baking quality tests. CO2 enrichment acted as carbon ‘fertiliser’ and increased the aboveground biomass production of wheat by 18.8% as there was a trend towards higher stem biomass. Although not statistically significant, wheat grain yield was increased by 13.4% due to a significant establishment of more grains per unit ground area. At the same time, thousand grain weight was non-significantly shifted towards smaller grain size classes, which may result in negative consequences for the crop market value. As a result of the CO2- induced physiological and biochemical modifications, concentration of total grain protein was significantly decreased by 3.5%, reducing the wheat grain quality with potentially far-reaching impacts on the nutritional value and use for processing industry. Although often not significant, the concentrations of amino acids per unit of flour were decreased by 0.2 to 8.3% due to elevated CO2 thereby affecting the composition of proteinogenic amino acids. Furthermore, gluten proteins tended to decline. Within the significant decreased gliadins, α- and ω5-gliadins were significantly reduced under CO2 enrichment; there was also a negative trend for ω1,2- and γ-gliadins. Changes in certain essential minerals were found as well, although not statistically significant. Concentrations of sodium, calcium, phosphorus and sulphur were slightly lowered and those of potassium and magnesium were slightly increased due to CO2 enrichment. The micro-element molybdenum was increased, while concentrations of iron, zinc, copper, manganese and aluminium were decreased. With regard to rheological and baking parameters defining the cereal quality for industrial processing, the resistance of the dough was significantly reduced by about 30%, while the extensibility was non-significantly increased by 17.1% under CO2 enrichment. Moreover, the bread volume was decreased non-significantly by about 9%. Elevated CO2 is obviously affecting grain characteristics important for consumer nutrition and health, industrial processing and marketing. Experimental evidence for these changes is still poor but deserves further attention.

Background Modern analytical methods in biology and chemistry use separation techniques coupled to sensitive detectors, such as gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). These hyphenated methods provide high-dimensional data. Comparing such data manually to find corresponding signals is a laborious task, as each experiment usually consists of thousands of individual scans, each containing hundreds or even thousands of distinct signals. In order to allow for successful identification of metabolites or proteins within such data, especially in the context of metabolomics and proteomics, an accurate alignment and matching of corresponding features between two or more experiments is required. Such a matching algorithm should capture fluctuations in the chromatographic system which lead to non-linear distortions on the time axis, as well as systematic changes in recorded intensities. Many different algorithms for the retention time alignment of GC-MS and LC-MS data have been proposed and published, but all of them focus either on aligning previously extracted peak features or on aligning and comparing the complete raw data containing all available features. Results In this paper we introduce two algorithms for retention time alignment of multiple GC-MS datasets: multiple alignment by bidirectional best hits peak assignment and cluster extension (BIPACE) and center-star multiple alignment by pairwise partitioned dynamic time warping (CeMAPP-DTW). We show how the similarity-based peak group matching method BIPACE may be used for multiple alignment calculation individually and how it can be used as a preprocessing step for the pairwise alignments performed by CeMAPP-DTW. We evaluate the algorithms individually and in combination on a previously published small GC-MS dataset studying the Leishmania parasite and on a larger GC-MS dataset studying grains of wheat (Triticum aestivum). Conclusions We have shown that BIPACE achieves very high precision and recall and a very low number of false positive peak assignments on both evaluation datasets. CeMAPP-DTW finds a high number of true positives when executed on its own, but achieves even better results when BIPACE is used to constrain its search space. The source code of both algorithms is included in the OpenSource software framework Maltcms, which is available from http://maltcms.sf.net. The evaluation scripts of the present study are available from the same source.

Crop simulation is a modern tool used to mimic ordinary and extraordinary agriculture systems. Under the premise of continuing foreseeable climatic shift we combine adaptive field-level management decisions with their effects on crop performance. Price projections are used to examine yield and price effects on gross margins of the predominant crops in two specific regions of Southwest Germany into the coming decades. After calibration and validation to historic records, simulated future weather is used to explore how farmer behavior and performance of wheat, barley, rapeseed and maize could develop under anticipated global change. This development is examined based on a comparison of historic and projected gross margin variance. Simulations indicate that when yield levels increase, the relative variability of gross margins may decline in spite of some increasing variability of yields. The coefficient of variance of gross margins decreases even more due to the independence of price and yield fluctuations. This shows how the effects of global change on yields could be offset by economic conditions.