Pierre Stratonovitch

Rothamsted Research · Computational and Analytical Sciences

Preventing a pest population from damaging an agricultural crop and, at the same time, preventing the development of pesticide resistance is a major challenge in crop protection. Understanding how farming practices and environmental factors interact with pest characteristics to influence the spread of resistance is a difficult and complex task. It...

Ambrosia artemisiifolia is an invasive weed in Europe with highly allergenic pollen. Populations are currently well established and cause significant health problems in the French Rhône valley, Austria, Hungary and Croatia but transient or casual introduced populations are also found in more Northern and Eastern European countries. A process-based...

Increasing cereal yield is needed to meet the projected increased demand for world food supply of about 70% by 2050. Sirius, a process-based model for wheat, was used to estimate yield potential for wheat ideotypes optimized for future climatic projections (HadCM3 global climate model) for ten wheat growing areas of Europe. It was predicted that th...

To address the rising global food demand in a changing climate, yield gaps (Y G), the difference between potential yields under irrigated (Y P) or rainfed conditions (Y WL) and actual farmers' yields (Y a), must be significantly narrowed whilst raising potential yields. Here, we examined the likely impacts of climate change (including changes in cl...

not yet peer-reviewed

The climate change impact and adaptation simulations from the Agricultural Model Intercomparison and Improvement Project (AgMIP) for wheat provide a unique dataset of multi-model ensemble simulations for 60 representative global locations covering all global wheat mega environments. The multi-model ensemble reported here has been thoroughly benchma...

While the understanding of average impacts of climate change on crop yields is improving, few assessments have quantified expected impacts on yield distributions and the risk of yield failures. Here we present the relative distribution as a method to assess how the risk of yield failure due to heat and drought stress (measured in terms of return pe...

The simulated data set described in this paper was created by an ensemble of nine different crop models: HERMES (HE), Simplace<Lintul5,Slim3, FAO-56 ET0> (L5), SiriusQuality (SQ), MONICA (MO), Sirius2014 (S2), FASSET (FA), 4M (4M), SSM (SS), DSSAT-CSM IXIM (IX). Simulations were performed for grain maize (six models) and winter wheat (eight models)...

Drought stress during reproductive development could drastically reduce wheat grain number and yield, but quan-titative evaluation of such an effect is unknown under climate change. The objectives of this study were to evaluate potential yield benefits of drought tolerance during reproductive development for wheat ideotypes under climate change in...

Climate change is expected to severely affect cropping systems and food production in many parts of the world unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertai...

Understanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropp...

Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32‐multi‐model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on g...

A recent innovation in assessment of climate change impact on agricultural production has been to use crop multi model ensembles (MMEs). These studies usually find large variability between individual models but that the ensemble mean (e‐mean) and median (e‐median) often seem to predict quite well. However few studies have specifically been concern...

The data set reported here includes the part of a Hot Serial Cereal Experiment (HSC) experiment recently used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat models and quantify their response to temperature. The HSC experiment was conducted in an open-field in a semiarid environment in the southwest USA. The data reported herewit...

Despite widespread application in studying climate change impacts, most crop models ignore complex interactions among air temperature, crop and soil water status, CO2 concentration and atmospheric conditions that influence crop canopy temperature. The current study extended previous studies by evaluating Tc simulations from nine crop models at six...

This work was financially supported by the Spanish National Institute for Agricultural and Food Research and Technology (INIA, MACSUR01-UPM), the Italian Ministry of Agriculture and Forestry and the Finnish Ministry of Agriculture and Forestry (D.M. 24064/7303/15) through FACCE MACSUR − Modelling European Agriculture with Climate Change for Food Se...

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (-2 to +9°C) and precipitation (-50 to +50%). Mode...

Nature Plants 3, 17102 (2017); published online 17 July 2017; corrected online 27 September 2017.

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical funct...

Provision of food security in the face of increasing global food demand requires narrowing of the gap between actual farmer's yield and maximum attainable yield. So far, assessments of yield gaps have focused on average yield over 5-10. years, but yield gaps can vary substantially between crop seasons. In this study we hypothesized that climate-ind...

Martre P, Reynolds MP, Asseng S, Ewert F, Alderman PD, Cammarano D, Maiorano A, Ruane AC, Aggarwal PK, Anothai J, Basso B, Biernath C, Challinor AJ, De Sanctis G, Doltra J, Dumont B, Fereres E, Garcia-Vila M, Gayler S, Hoogenboom G, Hunt LA, Izaurralde RC, Jabloun M, Jones CD, Kassie BT, Kersebaum KC, Koehler AK, Müller C, Kumar SN, Liu B, Lobell D...

Background: Tools with the potential to predict risks of insecticide resistance and aid the evaluation and design of resistance management tactics are of value to all sectors of the pest management community. Here we describe use of a versatile individual-based model of resistance evolution to simulate how strategies employing single and multiple...

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat y...

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and we evaluate results against the interannual variabili...

To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models...

Introduction A wide variety of dynamic crop growth simulation models have been developed over the past few decades that can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, multi-model ensemble approaches have been adopted to quantify aspects of uncertainty in simulating yield respons...

The data set includes a current representative management treatment from detailed, quality-tested sentinel field experiments with wheat from four contrasting environments including Australia, The Netherlands, India and Argentina. Measurements include local daily climate data (solar radiation, maximum and minimum temperature, precipitation, surface...

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 impac...

This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and S...

Understanding how farming practices and environmental factors interact with pest characteristics to influence the spread of resistance is a complex task. It is extremely difficult to investigate such interactions experimentally at realistic spatial and temporal scales. Individual-based modelling has been used to analyse resistance evolution and to...

FACCE MACSUR Reports 2, 5, SP5-46

To deliver food security for the 9 billon population in 2050, a 70% increase in world food supply will be required. Projected climatic and environmental changes emphasize the need for breeding strategies that delivers both a substantial increase in yield potential and resilience to extreme weather events such as heat waves, late frost, and drought....

Many simulation studies have been carried out to predict the effect of climate change on crop yield. Typically, in such study, one or several crop models are used to simulate series of crop yield values for different climate scenarios corresponding to different hypotheses of temperature, CO2 concentration, and rainfall changes. These studies usuall...

Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improveme...

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only...

Impact response surfaces (IRSs) depict the response of an impact variable to changes in two explanatory variables as a plotted surface. Here, IRSs of spring and winter wheat yields were constructed from a 25-member ensemble of process-based crop simulation models. Twenty-one models were calibrated by different groups using a common set of calibrati...

Global warming is characterized by shifts in weather patterns and increases in climatic variability and extreme events. New wheat cultivars will be required for a rapidly changing environment, putting severe pressure on breeders who must select for climate conditions which can only be predicted with a great degree of uncertainty. To assist breeders...

Projections of climate change impacts on crop yields are inherently uncertain. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop sim...

Projections of climate change impacts on crop yields are inherently uncertain. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop sim...

Predicting the impact of climate change on the damage niche of an agricultural weed at a local scale requires a process-based modelling approach that integrates local environmental conditions and the differential responses of the crop and weed to change. A simulation model of the growth and population dynamics of winter wheat and a competing weed,...

Improving crop performance to satisfy an increasing demand for agricultural products is a constant challenge to plant scientists. The recent improvements of process-based simulation models offer new avenues to explore variations of genetic traits on crop performance. In this study, global sensitivity analyses were performed using the Morris and Sob...

Calibration of cultivar parameters of a crop simulation model can represent a considerable challenge when observed data for a single cultivar is available for multiple environments. Calibration can be considered as a search of the optimal set of parameters in a multidimensional parameter space. An evolutionary algorithm with self-adaptation has bee...

We developed a dataset of local-scale daily climate scenarios for Europe, called ELPIS. This dataset is based on 25 km grids of interpolated daily precipitation, minimum and maximum temperatures and radiation from the European Crop Growth Monitoring System (CGMS) meteorological dataset and climate predictions from the multi-model ensemble of 15 glo...

a b s t r a c t The effects of sowing date and nitrogen (N) fertilisation on the dynamics of dry matter (DM) and N accumulation during grain filling and on final grain yield and protein concentration for durum wheat were studied in two field experiments. In addition, the ability of the wheat simulation model SiriusQuality1 to simulate grain yield a...

Multi-model ensembles of climate predictions constructed by running several global climate models for a common set of experiments are available for impact assessment of climate change. Multi-model ensembles emphasize the uncertainty in climate predictions resulting from structural differences in the global climate models as well as uncertainty due...