FACCE-JPI Knowledge Hub: MACSUR-Partner 25

Lead Research Organisation: Rothamsted Research
Department Name: Computational & Systems Biology


The key challenges that CropM have addressed in the first phase of MACSUR were: (i) crop model intercomparison and improvement, (ii) data management, (iii) methods of scaling and model linking, (iv) scenario development and impact uncertainty evaluation, (v) capacity building and (vi) the development of methodological case and integrated pilot studies on impact assessment. Recently, an overview has been completed on the state of the art of crop models to assess climate change risks to food. Progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind integrated assessment and modelling (IAM) demands. The limitations are considered substantial and apply to all crop models (to a different extent). Overcoming these limitations will require joint efforts, particularly for multi-model ensemble simulations and consideration of novel modelling approaches. The key challenges of CropM in MACSUR2 are to further advance crop modelling for improved assessment of climate change impacts on food security. Particular emphasis will be on cross-cutting activities to advance crop modelling as integrated part of IAM. Like in MACSUR1, the knowledge hub strategy includes the stimulation of excellent science, the support of capacity and network building activities, jointly work on explicit and comprehensive case studies on integrated regional and Europe-wide climate risk assessment in close interaction with stakeholders.

Technical Summary

CropM in MACSUR2 will develop research areas, which have not received sufficient attention in MACSUR1. In particular, developing approaches of improving models to better capture variability and extremes (WP C1), performing empirical crop-weather analysis to complement knowledge from dynamic process-based crop modelling (WP C2), or to consider management variables in the scaling exercises (WP C3) as well as the full range of methods for analysing uncertainty and error propagation in climate impact assessments (WP C4). Moreover, both in capacity building (WPC5) and in the cross-cutting activities (WP C6), there will be more emphasis on multi-scale and integrated analysis of adapting to climate change by alternative genotypes, management practices, systemic changes (e.g. new technologies) and structural changes and transformations of agrifood systems at farm and regional scales. In a concerted effort by MACSUR partners, this should lead to robust European-wide impact assessments.

Planned Impact

Global food security are at the forefront of discussions at all levels of society. FACCE MACSUR Knowledge Hub Phase 2 will provide significant advance in the knowledge and methodologies for risk assessment for European agriculture and food security under climate change. The project will deliver a detailed European fully integrated analysis. The greatest knowledge advancement will stem from the interdisciplinary and diverse framework implemented within the project. This type of broad interdisciplinary study may lead to results that are significantly different in comparison to previous assesments in this field. FACCE MACSUR Knowledge Hub requires a European rather than a national or local approach to achieve the objectives outlined in this proposal. Specific expertise is in certain cases only available in particular EU countries and would not be possible to find in individual countries. Additionally, the exchange skills and ToK between partners will improve the level of the scientific research and will respectively enhance the status of science in the EU. Most importantly, the dissemination of data and methodologies from this project will contribute to the objectives of the European Commission which aim to coordinate the European Science Initiative by encouraging and providing the necessary tools and support for high impact, substantial science. We will be able to highlight our results internationally and will further unify the European scientific community. Reproducible and reliable results, high impact publications and the dissemination of the results at international meetings will increase the profile of European Science.

A successful outcome of this project would be of direct benefit to food security, farmer and consumer, potentially on a global scale. In our work we are addressing one of BBSRC's three key strategic priorities "Food security: bioscience for a sustainable supply of sufficient, affordable, nutritious and safe food, adapting to a rapidly changing world" by sustainably enhancing agricultural production. National and global challenges related to climate change and food security will only increase the importance of wheat in the food supply, and the proposed work on wheat ideotype design for a changing climate will deliver new knowledge and a strong science base to future wheat breeding and more sustainable agriculture.

Dr Semenov has experience in presenting ideas for potential commercial exploitation and has an excellent track record of engaging with the scientific community and stakeholders. Public engagement will be carried out via press releases, talks at Open Meetings and displays at the Rothamsted Open Days. Rothamsted Open Days also involves stakeholders. The PI will present key findings to non-specialist stakeholders and the general public to further emphasise BBSRC's role in promoting research to support crop science and food security.


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Clare FC (2016) Climate forcing of an emerging pathogenic fungus across a montane multi-host community. in Philosophical transactions of the Royal Society of London. Series B, Biological sciences

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Ruane A (2016) Multi-wheat-model ensemble responses to interannual climate variability in Environmental Modelling & Software

Description RRes developed a methodology for downscaling climate projection from CMIP5 ensemble to local-scale climate scenarios based on the LARS-WG stochastic weather generator. The following is an illustration of research output in FACCE-JPI Knowledge Hub: MACSUR-Partner 25 project.

ACCOUNTING FOR UNCERTAINTIES IN CMIP5 CLIMATE PROJECTIONS. This study describes integration of climate change projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble with the LARS-WG weather generator, which delivers an attractive option for the downscaling of large-scale climate projections from global climate models (GCMs) to local-scale climate scenarios for impact assessments. A subset of 18 GCMs from the CMIP5 ensemble and 2 Representative Concentration Pathways (RCPs), RCP4.5 and RCP8.5, were integrated with LARS-WG. For computationally demanding impact assessments, where it is not practical to explore all possible combinations of GCM × RCP, a climate sensitivity index was introduced which could be used to select a subset of GCMs preserving the uncertainty found in CMIP5. This would allow us to quantify uncertainty in impact predictions resulting from CMIP5 by conducting fewer simulation experiments. In a case study, we describe the use of the Sirius wheat simulation model to design in silico wheat ideotypes that were optimised for future climates in Europe, sampling uncertainty in GCMs, emission scenarios, time periods and European locations with contrasting climates. Two contrasting GCMs were selected for the analysis, 'hot' HadGEM2-ES and 'cool' GISS-E2-R-CC. Despite large uncertainty in future climate projections, we were able to identify target traits for wheat improvement which may assist breeding for high-yielding wheat cultivars with increased yield stability.
Exploitation Route Local-scale climate scenarios based on the latest projections from CMIP5 are available to the MACSUR consortium for impact assessments.
Sectors Agriculture, Food and Drink,Environment

Title ELPIS 
Description ELPIS is a dataset of site parameters for the LARS-WG weather generator for Europe. 
Type Of Material Database/Collection of data 
Year Produced 2012 
Provided To Others? Yes  
Impact ELPIS has been used to generate local-scale climate scenarios for Europe using LARS-WG and climate projections from the CMIP5 ensemble. These scenarios have been used in many projects including MACSUR. 
URL http://www.rothamsted.ac.uk/mas-models/larswg
Title LARS-WG stochastic weather generator 
Description LARS-WG is a model simulating time-series of daily weather at a single site. It can be used: 1. to generate long time-series suitable for the assessment of agricultural and hydrological risk; 2. to provide the means of extending the simulation of weather to unobserved locations; 3. to serve as a computationally inexpensive tool to produce daily site-specific climate scenarios for impact assessments of climate change. LARS-WG version 5.0 includes climate scenarios based on 15 Global Climate Models (GCMs) which have been used in the IPCC 4AR (2007). This large dataset of future climate projections was produced by leading modelling groups worldwide who performed a set of coordinated climate experiments in which GCMs have been run for a common set of experiments and emission scenarios. Multi-model ensembles allow to explore the uncertainty in climate predictions resulting from structural differences in the global climate model design as well as uncertainty in variations of initial conditions or model parameters. The new version also improves simulation of extreme weather events, such as extreme daily precipitation, long dry spells and heat waves. LARS-WG has been well validated in diverse climates around the world. 
Type Of Technology Software 
Year Produced 2015 
Impact LARS-WG has been used in more than 65 countries for research and in several Universities as an educational tool. Climate scenarios generated by LARS-WG have been used in the impact assessments of climate change for the IPCC Assessment Report 5. 
URL http://www.rothamsted.ac.uk/mas-models/larswg
Title SIRIUS wheat simulation model 
Description Sirius is a wheat simulation model that calculates biomass from intercepted photosynthetically active radiation and grain growth from simple partitioning rules. Leaf area index (LAI) is developed from a simple thermal time sub-model. Phenological development is calculated from the mainstem leaf appearance rate and final leaf number, with the latter determined by responses to daylength and vernalisation. Effects of water and N deficits are calculated through their influences on LAI development and radiation-use efficiency. Sirius has been calibrated for several modern wheat cultivars and was able to simulate crop growth accurately in a wide range of conditions, including Europe, NZ/Australia and USA and under climate change 
Type Of Technology Software 
Year Produced 2015 
Impact Sirius is used in research by many scientists to understand crop responses to environmental variations, and in practice by farmers to optimize water and N management. 
URL http://www.rothamsted.ac.uk/mas-models/sirius
Title Sirius crop model 
Description Sirius is a process-based crop simulation model. Initially developed for wheat, Sirius has been extended to model inter-plant competition and other species. Sirius is a well validated model and was able to simulate accurately crop growth in a wide range of environments, including Europe, USA, New Zealand and Australia, and for experiments of climate change, e.g. Free-Air Carbon Dioxide Enrichment (FACE) experiments. 
Type Of Technology Software 
Year Produced 2021 
Impact Sirius wheat model is used as a research tool by scientists, and in practice by farmers to optimize crop management 
URL https://zenodo.org/record/4572624