Abstract: Ectopic cystatin expression has long been used in plant pest management, but the cysteine protease, targets of these inhibitors, might also have important functions in the control of plant lifespan and stress tolerance that remain poorly characterized. We therefore characterized the effects of expression of the rice cystatin, oryzacystatin-I (OCI), on the growth, development and stress tolerance of crop (soybean) and model (Arabidopsis thaliana) plants. Ectopic OCI expression in soybean enhanced shoot branching and leaf chlorophyll accumulation at later stages of vegetative development and enhanced seed protein contents and decreased the abundance of mRNAs encoding strigolactone synthesis enzymes. The OCI-expressing A. thaliana showed a slow-growth phenotype, with increased leaf numbers and enhanced shoot branching at flowering. The OCI-dependent inhibition of cysteine proteases enhanced drought tolerance in soybean and A. thaliana, photosynthetic CO2 assimilation being much less sensitive to drought-induced inhibition in the OCI-expressing soybean lines. Ectopic OCI expression or treatment with the cysteine protease inhibitor E64 increased lateral root densities in A. thaliana. E64 treatment also increased lateral root densities in the max2-1 mutants that are defective in strigolactone signalling, but not in the max3-9 mutants that are defective in strigolactone synthesis. Taken together, these data provide evidence that OCI-inhibited cysteine proteases participate in the control of growth and stress tolerance through effects on strigolactones. We conclude that cysteine proteases are important targets for manipulation of plant growth, development and stress tolerance, and also seed quality traits.

Abstract: Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research directions and collaborative opportunities, and 2) for policy-makers involved in shaping the research agenda for European grassland modelling under climate change.

Abstract: The objective of the present study was to compare the performance of seven different, widely applied crop models in predicting heat and drought stress effects. The study was part of a recent suite of model inter-comparisons initiated at European level and constitutes a component that has been lacking in the analysis of sources of uncertainties in crop models used to study the impacts of climate change. There was a specific focus on the sensitivity of models for winter wheat and maize to extreme weather conditions (heat and drought) during the short but critical period of 2 weeks after the start of flowering. Two locations in Austria, representing different agro-climatic zones and soil conditions, were included in the simulations over 2 years, 2003 and 2004, exhibiting contrasting weather conditions. In addition, soil management was modified at both sites by following either ploughing or minimum tillage. Since no comprehensive field experimental data sets were available, a relative comparison of simulated grain yields and soil moisture contents under defined weather scenarios with modified temperatures and precipitation was performed for a 2-week period after flowering. The results may help to reduce the uncertainty of simulated crop yields to extreme weather conditions through better understanding of the models’ behaviour. Although the crop models considered (DSSAT, EPIC, WOFOST, AQUACROP, FASSET, HERMES and CROPSYST) mostly showed similar trends in simulated grain yields for the different weather scenarios, it was obvious that heat and drought stress caused by changes in temperature and/or precipitation for a short period of 2 weeks resulted in different grain yields simulated by different models. The present study also revealed that the models responded differently to changes in soil tillage practices, which affected soil water storage capacity.