Potential benefits of a spatially targeted regulation based on detailed N-reduction maps to decrease N-load from agriculture in a small groundwater dominated catchment.

Denmark must further decrease the N-load to coastal waters from agricultural areas to comply with the Baltic Sea Action Plan and the EU Water Framework Directive. A new spatially targeted regulation is under development that focuses on locating N-mitigation measures in areas with low natural reduction of nitrate (N-reduction). A key tool in this respect is N-reduction maps showing how much N is removed by natural reduction processes, i.e. the ratio between the N-load out of the catchment and the N-leaching from the root zone for each spatial unit within the catchment. For the 85 km2 groundwater dominated Norsminde catchment in Denmark we have analysed the potential benefits of a spatially targeted regulation and how its efficiency is affected by uncertainty in the N-reduction map. Our results suggest that there are potential benefits of implementing a spatially targeted regulation compared to a spatially uniform regulation. The total N-load at the catchment outlet can be decreased up to 8% by relocating the existing agricultural practice according to the N-reduction map and thus without decrease fertilization inputs. A further decrease in N-load can be obtained by identifying target areas with low N-reduction where N-mitigation measures must be applied. Uncertainty on the N-reduction map is found to lower the efficiency of spatially targeted regulation. This uncertainty can be lowered substantially by using the mean of an ensemble of N-reduction maps. The uncertainty decreases with coarser spatial resolution of the N-reduction map, but this will at the same time decrease the benefit from spatially targeted regulation.

Nitrate leaching, yields and carbon sequestration after noninversion tillage, catch crops, and straw retention.

Crop management factors, such as tillage, rotation, and straw retention, need to be long-term to allow conclusions on effects on crop yields, nitrate leaching, and carbon sequestration. In 2002, two field experiments, each including four cash crop rotations, were established on soils with 9 and 15% clay, under temperate, coastal climate conditions. Direct drilling and harrowing to two different depths were compared to plowing with respect to yield, nitrate N leaching, and carbon sequestration. For comparison of yields across rotations, grain and seed dry matter yields for each crop were converted to grain equivalents (GE). Leaching was compared to yields by calculating yield-scaled leaching (YSL, g N kg GE), and N balances were calculated as the N input in manure minus the N output in products removed from the fields. Direct drilling reduced yields, but no effect on leaching was found. Straw retention did not significantly increase yields, nor did it reduce leaching, while fodder radish ( L.) as a catch crop was capable of reducing nitrate leaching to a low level. Thus, YSL of winter wheat ( L.) was higher than for spring barley ( L.) grown after fodder radish due to the efficient catch crop. Soil organic carbon (SOC) did not increase significantly after 7 yr of straw incorporation or noninversion tillage. There was no correlation between N balances calculated for each growing season and N leaching measured in the following percolation period.

Is it really organic?--multi-isotopic analysis as a tool to discriminate between organic and conventional plants.

Novel procedures for analytical authentication of organic plant products are urgently needed. Here we present the first study encompassing stable isotopes of hydrogen, carbon, nitrogen, oxygen, magnesium and sulphur as well as compound-specific nitrogen and oxygen isotope analysis of nitrate for discrimination of organically and conventionally grown plants. The study was based on wheat, barley, faba bean and potato produced in rigorously controlled long-term field trials comprising 144 experimental plots. Nitrogen isotope analysis revealed the use of animal manure, but was unable to discriminate between plants that were fertilised with synthetic nitrogen fertilisers or green manures from atmospheric nitrogen fixing legumes. This limitation was bypassed using oxygen isotope analysis of nitrate in potato tubers, while hydrogen isotope analysis allowed complete discrimination of organic and conventional wheat and barley grains. It is concluded, that multi-isotopic analysis has the potential to disclose fraudulent substitutions of organic with conventionally cultivated plants.

Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems.

The farm level is the most appropriate scale for evaluating options for mitigating greenhouse gas (GHG) emissions, because the farm represents the unit at which management decisions in livestock production are made. To date, a number of whole farm modelling approaches have been developed to quantify GHG emissions and explore climate change mitigation strategies for livestock systems. This paper analyses the limitations and strengths of the different existing approaches for modelling GHG mitigation by considering basic model structures, approaches for simulating GHG emissions from various farm components and the sensitivity of GHG outputs and mitigation measures to different approaches. Potential challenges for linking existing models with the simulation of impacts and adaptation measures under climate change are explored along with a brief discussion of the effects on other ecosystem services.

Changes in time of sowing, flowering and maturity of cereals in Europe under climate change.

The phenological development of cereal crops from emergence through flowering to maturity is largely controlled by temperature, but also affected by day length and potential physiological stresses. Responses may vary between species and varieties. Climate change will affect the timing of cereal crop development, but exact changes will also depend on changes in varieties as affected by plant breeding and variety choices. This study aimed to assess changes in timing of major phenological stages of cereal crops in Northern and Central Europe under climate change. Records on dates of sowing, flowering, and maturity of wheat, oats and maize were collected from field experiments conducted during the period 1985-2009. Data for spring wheat and spring oats covered latitudes from 46 to 64°N, winter wheat from 46 to 61°N, and maize from 47 to 58°N. The number of observations (site-year-variety combinations) varied with phenological phase, but exceeded 2190, 227, 2076 and 1506 for winter wheat, spring wheat, spring oats and maize, respectively. The data were used to fit simple crop development models, assuming that the duration of the period until flowering depends on temperature and day length for wheat and oats, and on temperature for maize, and that the duration of the period from flowering to maturity in all species depends on temperature only. Species-specific base temperatures were used. Sowing date of spring cereals was estimated using a threshold temperature for the mean air temperature during 10 days prior to sowing. The mean estimated temperature thresholds for sowing were 6.1, 7.1 and 10.1°C for oats, wheat and maize, respectively. For spring oats and wheat the temperature threshold increased with latitude. The effective temperature sums required for both flowering and maturity increased with increasing mean annual temperature of the location, indicating that varieties are well adapted to given conditions. The responses of wheat and oats were largest for the period from flowering to maturity. Changes in timing of cereal phenology by 2040 were assessed for two climate model projections according to the observed dependencies on temperature and day length. The results showed advancements of sowing date of spring cereals by 1-3 weeks depending on climate model and region within Europe. The changes were largest in Northern Europe. Timing of flowering and maturity were projected to advance by 1-3 weeks. The changes were largest for grain maize and smallest for winter wheat, and they were generally largest in the western and northern part of the domain. There were considerable differences in predicted timing of sowing, flowering and maturity between the two climate model projections applied.

Selection of climate change scenario data for impact modelling.

Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.

Climate change impacts on natural toxins in food production systems, exemplified by deoxynivalenol in wheat and diarrhetic shellfish toxins.

Climate change is expected to affect food and feed safety, including the occurrence of natural toxins in primary crop and seafood production; however, to date, quantitative estimates are scarce. This study aimed to estimate the impact of climate change effects on mycotoxin contamination of cereal grains cultivated in the terrestrial area of north west Europe, and on the frequency of harmful algal blooms and contamination of shellfish with marine biotoxins in the North Sea coastal zone. The study focused on contamination of wheat with deoxynivalenol, and on abundance of Dinophysis spp. and the possible relationship with diarrhetic shellfish toxins. The study used currently available data and models. Global and regional climate models were combined with models of crop phenology, mycotoxin prediction models, hydrodynamic models and ecological models, with the output of one model being used as input for the other. In addition, statistical data analyses using existing national datasets from the study area were performed to obtain information on the relationships between Dinophysis spp. cell counts and contamination of shellfish with diarrhetic shellfish toxins as well as on frequency of cereal cropping. In this paper, a summary of the study is presented, and overall conclusions and recommendations are given. Climate change projections for the years 2031-2050 were used as the starting point of the analyses relative to a preceding 20-year baseline period from which the climate change signal was calculated. Results showed that, in general, climate change effects lead to advanced flowering and harvest of wheat, and increased risk of contamination of wheat with deoxynivalenol. Blooms of dinoflagellates were estimated to occur more often. If the group of Dinophysis spp. behaves similarly to other flagellates in the future then frequency of harmful algal blooms of Dinophysis spp. may also increase, but consequences for contamination of shellfish with diarrhetic shellfish toxins are uncertain. Climate change will also have indirect effects on toxin contamination, which may be equally important. For example, the frequency of cropping of wheat and maize in north Europe was projected to increase under climate change, which will also increase the risk of contamination of the grains with deoxynivalenol. Risk managers are encouraged to consider the entire range of the predictions of climate change effects on food safety hazards, rather than median or average values only. Furthermore, it is recommended to closely monitor levels of mycotoxins and marine biotoxins in the future, in particular related to risky situations associated with favourable climatic conditions for toxin producing organisms. In particular, it is important to pay attention to the continuity of collecting the right data, and the availability and accessibility of databases. On a European level, it is important to stress the need for harmonisation of terminology and data collection.

Shifts in comparative advantages for maize, oat and wheat cropping under climate change in Europe.

Climate change is anticipated to affect European agriculture, including the risk of emerging or re-emerging feed and food hazards. Indirectly, climate change may influence such hazards (e.g. the occurrence of mycotoxins) due to geographic shifts in the distribution of major cereal cropping systems and the consequences this may have for crop rotations. This paper analyses the impact of climate on cropping shares of maize, oat and wheat on a 50-km square grid across Europe (45-65°N) and provides model-based estimates of the changes in cropping shares in response to changes in temperature and precipitation as projected for the time period around 2040 by two regional climate models (RCM) with a moderate and a strong climate change signal, respectively. The projected cropping shares are based on the output from the two RCMs and on algorithms derived for the relation between meteorological data and observed cropping shares of maize, oat and wheat. The observed cropping shares show a south-to-north gradient, where maize had its maximum at 45-55°N, oat had its maximum at 55-65°N, and wheat was more evenly distributed along the latitudes in Europe. Under the projected climate changes, there was a general increase in maize cropping shares, whereas for oat no areas showed distinct increases. For wheat, the projected changes indicated a tendency towards higher cropping shares in the northern parts and lower cropping shares in the southern parts of the study area. The present modelling approach represents a simplification of factors determining the distribution of cereal crops, and also some uncertainties in the data basis were apparent. A promising way of future model improvement could be through a systematic analysis and inclusion of other variables, such as key soil properties and socio-economic conditions, influencing the comparative advantages of specific crops.

Climate change increases deoxynivalenol contamination of wheat in north-western Europe.

Climate change will affect the development of cereal crops and the occurrence of mycotoxins in these crops, but so far little research has been done on quantifying the expected effects. The aim of this study was to assess climate change impacts on the occurrence of deoxynivalenol in wheat grown in north-western Europe by 2040, considering the combined effects of shifts in wheat phenology and climate. The study used climate model data for the future period of 2031-2050 relative to the baseline period of 1975-1994. A weather generator was used for generating synthetic series of daily weather data for both the baseline and the future periods. Available models for wheat phenology and prediction of deoxynivalenol concentrations in north-western Europe were used. Both models were run for winter wheat and spring wheat, separately. The results showed that both flowering and full maturation of wheat will be earlier in the season because of climate change effects, about 1 to 2 weeks. Deoxynivalenol contamination was found to increase in most of the study region, with an increase of the original concentrations by up to 3 times. The study results may inform governmental and industrial risk managers to underpin decision-making and planning processes in north-western Europe. On the local level, deoxynivalenol contamination should be closely monitored to pick out wheat batches with excess levels at the right time. Using predictive models on a more local scale could be helpful to assist other monitoring measures to safeguard food safety in the wheat supply chain.

Developments in greenhouse gas emissions and net energy use in Danish agriculture - how to achieve substantial CO(2) reductions?

Greenhouse gas (GHG) emissions from agriculture are a significant contributor to total Danish emissions. Consequently, much effort is currently given to the exploration of potential strategies to reduce agricultural emissions. This paper presents results from a study estimating agricultural GHG emissions in the form of methane, nitrous oxide and carbon dioxide (including carbon sources and sinks, and the impact of energy consumption/bioenergy production) from Danish agriculture in the years 1990-2010. An analysis of possible measures to reduce the GHG emissions indicated that a 50-70% reduction of agricultural emissions by 2050 relative to 1990 is achievable, including mitigation measures in relation to the handling of manure and fertilisers, optimization of animal feeding, cropping practices, and land use changes with more organic farming, afforestation and energy crops. In addition, the bioenergy production may be increased significantly without reducing the food production, whereby Danish agriculture could achieve a positive energy balance.

Effects of farm heterogeneity and methods for upscaling on modelled nitrogen losses in agricultural landscapes.

The aim of this study is to illustrate the importance of farm scale heterogeneity on nitrogen (N) losses in agricultural landscapes. Results are exemplified with a chain of N models calculating farm-N balances and distributing the N-surplus to N-losses (volatilisation, denitrification, leaching) and soil-N accumulation/release in a Danish landscape. Possible non-linearities in upscaling are assessed by comparing average model results based on (i) individual farm level calculations and (ii) averaged inputs at landscape level. Effects of the non-linearities that appear when scaling up from farm to landscape are demonstrated. Especially in relation to ammonia losses the non-linearity between livestock density and N-loss is significant (p > 0.999), with around 20-30% difference compared to a scaling procedure not taking this non-linearity into account. A significant effect of farm type on soil N accumulation (p > 0.95) was also identified and needs to be included when modelling landscape level N-fluxes and greenhouse gas emissions.

Challenges in quantifying biosphere-atmosphere exchange of nitrogen species.

Recent research in nitrogen exchange with the atmosphere has separated research communities according to N form. The integrated perspective needed to quantify the net effect of N on greenhouse-gas balance is being addressed by the NitroEurope Integrated Project (NEU). Recent advances have depended on improved methodologies, while ongoing challenges include gas-aerosol interactions, organic nitrogen and N(2) fluxes. The NEU strategy applies a 3-tier Flux Network together with a Manipulation Network of global-change experiments, linked by common protocols to facilitate model application. Substantial progress has been made in modelling N fluxes, especially for N(2)O, NO and bi-directional NH(3) exchange. Landscape analysis represents an emerging challenge to address the spatial interactions between farms, fields, ecosystems, catchments and air dispersion/deposition. European up-scaling of N fluxes is highly uncertain and a key priority is for better data on agricultural practices. Finally, attention is needed to develop N flux verification procedures to assess compliance with international protocols.

The determination of trace amounts of tin by flow-injection hydride generation atomic-absorption spectrometry with on-line ion-exchange separation and preconcentration.

A hydride generation atomic-absorption spectrometric (AAS) method with flow-injection (FI), aimed at developing a practical routine assay for the determination of tin in food digests, is described. In order to modify the sample matrix and to achieve optimized and reproducible conditions for the hydride generation reaction, the analyte is initially converted into its chlorostannate-complex thereby allowing it to be separated and preconcentrated on-line on an incorporated micro-column packed with a strongly basic anion exchanger and subsequently to be eluted by diluted nitric acid under strictly controlled conditions. Optimum acidic conditions for the FI hydride generation AAS system was found to be 0.01-0.05M nitric acid. At a consumption of 2.7-ml sample volume, aspirated by time-based injection, the procedure resulted in an enrichment factor of 3.5 and yielded a detection limit of 0.08 microg/l. (3sigma) at a sampling frequency of 72/hr. The precision was 2.5% rsd at the 10 microg/l. level. Potential interferents, such as Ni(II), Co(II), Zn(II) and Fe(III) could, at a Sn level of 10 microg/l., be tolerated at an excess of 1000 times without impairing the assay, while a 100-1000-fold excess of Cu(II) decreased the signal by 10-15%. Recoveries in the range 94-102% were obtained for canned food sample digests spiked with 10 microg/l. Sn.