Marianne Sloth Madsen

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.

Impact of climate change effects on contamination of cereal grains with deoxynivalenol.

Climate change is expected to aggravate feed and food safety problems of crops; however, quantitative estimates are scarce. This study aimed to estimate impacts of climate change effects on deoxynivalenol contamination of wheat and maize grown in the Netherlands by 2040. Quantitative modelling was applied, considering both direct effects of changing climate on toxin contamination and indirect effects via shifts in crop phenology. Climate change projections for the IPCC A1B emission scenario were used for the scenario period 2031-2050 relative to the baseline period of 1975-1994. Climatic data from two different global and regional climate model combinations were used. A weather generator was applied for downscaling climate data to local conditions. Crop phenology models and prediction models for DON contamination used, each for winter wheat and grain maize. Results showed that flowering and full maturity of both wheat and maize will advance with future climate. Flowering advanced on average 5 and 11 days for wheat, and 7 and 14 days for maize (two climate model combinations). Full maturity was on average 10 and 17 days earlier for wheat, and 19 and 36 days earlier for maize. On the country level, contamination of wheat with deoxynivalenol decreased slightly, but not significantly. Variability between regions was large, and individual regions showed a significant increase in deoxynivalenol concentrations. For maize, an overall decrease in deoxynivalenol contamination was projected, which was significant for one climate model combination, but not significant for the other one. In general, results disagree with previous reported expectations of increased feed and food safety hazards under climate change. This study illustrated the relevance of using quantitative models to estimate the impacts of climate change effects on food safety, and of considering both direct and indirect effects when assessing climate change impacts on crops and related food safety hazards.

Inflated Uncertainty in Multimodel‐Based Regional Climate Projections

Abstract Multimodel ensembles are widely analyzed to estimate the range of future regional climate change projections. For an ensemble of climate models, the result is often portrayed by showing maps of the geographical distribution of the multimodel mean results and associated uncertainties represented by model spread at the grid point scale. Here we use a set of CMIP5 models to show that presenting statistics this way results in an overestimation of the projected range leading to physically implausible patterns of change on global but also on regional scales. We point out that similar inconsistencies occur in impact analyses relying on multimodel information extracted using statistics at the regional scale, for example, when a subset of CMIP models is selected to represent regional model spread. Consequently, the risk of unwanted impacts may be overestimated at larger scales as climate change impacts will never be realized as the worst (or best) case everywhere.

The future potential for wine production in Scotland under high-end climate change

Wine production is climate dependent and highly sensitive to weather variability, which makes the sector a good indicator of ongoing and future climate change impacts. Under high-end climate change (HECC), temperatures in Scotland are projected to increase significantly by the end of the twenty-first century. This raises the possibility of future temperatures becoming sufficiently high to support the growth of wine grapes. In this paper, we explore to what extent Scotland might become suitable for wine production under HECC using a climate analogue approach. Specifically, we address the following questions. What are the projected late twenty-first century temperature changes in Scotland? Where in Europe are current climates (based on summer and annual temperatures) similar to those projected for Scotland by the end of the twenty-first century under HECC? Are any of these locations currently wine grape growing regions? The temperature analogues towards the end of the twenty-first century occurred at more southerly latitudes in Europe, with some variability from west to east arising from the influence of continental climates. Temperature analogues alone match with several current wine grape growing regions of Europe, suggesting that future climates in Scotland could support wine production. However, when precipitation and/or lithology and topography are also taken into account, no matches were found with existing European wine grape growing regions. This study demonstrates how the use of climate analogues in combination with other environmental datasets can be useful in understanding future climate change impacts, especially under HECC.