FACCE MACSUR Reports (Modelling European Agriculture with Climate Change for Food Security)
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Sustainable agricultural intensification: indicators and metrics for multi-scale modeling.
No full textAgricultural production is expected to provide food security, respect the environment, sustain rural communities and cover an increasing demand for the bioeconomy. In order to simultaneously address these objectives, sustainable agricultural intensification is seen as a promising strategy that could allow satisfying growing demands for agricultural food and non-food products, while reducing environmental impacts and maximizing resource use efficiency. However, the quantification and ex ante evaluation of sustainable intensification options and their associated trade-offs with respect to the various sustainability dimensions remain a challenge.This study aims to address this challenge by presenting a framework for measuring sustainable intensification. First, we reviewed literature on sustainability criteria for agriculture, biomass and bioenergy production, and metrics and frameworks for measuring sustainable intensification. Second, we developed a framework for quantifying sustainable intensification via transparent, clear and relevant indicators that allow the analysis and weighing of trade-offs across sustainable intensification options and scales. Third, we contrasted the metrics of the developed framework to typical outputs of a number of biophysical and economic models of agricultural systems, across different scales including the field, farm, regional, EU and global levels, in order to evaluate typical modeling capabilities to quantify sustainable intensification.This talk will present the findings of this exercise, demonstrate the operationalization of the framework for the assessment of the dual production of food and non-food products, and propose an approach for further improving the presented sustainable intensification metrics via stakeholder involvement
Assessment of viticulture and winemaking vulnerability in the expected conditions of climate change in Ararat valley and foothills.
No full textComparing the site sensitivity of crop models using spatially variable field data from precision agriculture.
No full textImpacts of climate change on crop production depend strongly on the site conditions and properties. Vulnerability of crop production to changing climate conditions is highly determined by the ability of the site to buffer periods of adverse climatic situations like water scarcity or excessive rainfall. Therefore, the capability of models to reflect crop responses and water and nutrient dynamics under different site conditions is essential to assess climate impact on a regional scale. To test and improve sensitivity of models to various site properties such as soil variability and hydrological boundary conditions, spatial variable data sets from precision farming of two fields in Germany and Italy were provided to modellers. For the German 20 ha field soil and management data for 60 grid points for 3 years (2 years wheat, 1 year triticale) were provided. For the Italian field (12 ha) information for 100 grid points were available for three growing seasons of durum wheat. Modellers were asked to run their models using a) the model specific procedure to estimate soil hydraulic properties from texture using their standard procedure and use in step b) fixed values for field capacity and wilting point derived from soil taxonomy. Only the phenology and crop yield of one grid point provided for a basic calibration. In step c) information for all grid points of the first year (yield, soil water and mineral N content for Germany, yield, biomass and LAI for Italy were provided. Results of twelve models are compared against measured state variables analyzing their site response and consistency across crop and soil variables
Developing a framework for critical assessment of stakeholder engagement activities.
No full textMulti-actor approaches to research are essential to meeting the complex challenges facing the agricultural sector in Europe. From a practical perspective, working with stakeholders can enhance the relevance of research findings, and increase the chances of achieving changes in practice. Recent work within the Modelling European Agriculture with Climate Change for Food Security (MACSUR) project analysed seven case studies of stakeholder engagement involving partners from the consortium. This initial study revealed a number of categories underlying the individual cases. These categories highlighted the interactions between the actors involved (including scientists) and how these were shaped by, and shaped, external and internal structures and processes. Here, the categories which emerged from the initial study have been developed into a simple approach for the critical assessment of engagement activities. A qualitative framework is being developed, composed of five elements derived from the initial study: external shaping, shaping by priority, shaping by role, shaping by actions and pathway to impact. Development of qualitative indicators to support the assessment of each element relative to theoretical best practice is ongoing. Applications of the nascent framework, including assessments of MACSUR regional case studies, are presented to illustrate its potential. Use of the framework in engagement design and review is intended to minimise unintended consequences arising from unrecognised issues relating, for example, to the effects of power inequalities between the social worlds of different stakeholder groups. It provides a structure for systematic reflection on such elements, either when designing a stakeholder engagement activity, as a reflexive exercise during implementation, or in order to assess a completed activity. Complementing current practical frameworks for good practice in stakeholder engagement, this tool is being designed to address critical aspects of engagement in the context of quantitative research, including the development and use of models as part of integrated assessments
Relations between micrometeorological conditions and plant physiology
Full text linkThe changing climate and environmental conditions play a key role on plant physiology. In this context, crop simulation models represent a useful tool for investigating the main plant processes and provide a reliable estimation of crop productivity and quality. However, the most common crop models showed many limitations, with particular concern on the effect of some meteorological variables on plant processes during sensitive stages of development. Improving models by implementing the effect of such variables on crop processes may help to improve the accuracy of models, thus their usefulness. Here we focus on the analysis of the effect of high and low temperatures during flowering in grapevine. To this, the fruit-set index, developed for taking into account for the effect of temperature on setting the number of berries per cluster and the fruit-set percentage, was applied in a preliminary explorative study to assess the impact of different conditions during flowering at European scales. The sensitivity of the index allowed to identify the differential impact of temperature around flowering in different environment and for different varieties. Once meteorological variables are available at field or sub-field scale, the index can be used to provide information about the spatial variability of crop growth, thus allowing to identify the most appropriate interventions to improve productivity
Modelling different cropping systems
Full text linkGrapevine is a worldwide valuable crop characterized by a high economic importance for the production of high quality wines. However, the impact of climate change on the narrow climate niches in which grapevine is currently cultivated constitute a great risk for future suitability of grapevine. In this context, grape simulation models are considered promising tools for their contribution to investigate plant behavior in different environments. In this study, six models developed for simulating grapevine growth and development were tested by focusing on their performances in simulating main grapevine processes under two calibration levels: minimum and full calibration. This would help to evaluate major limitations/strength points of these models, especially in the view of their application to climate change impact and adaptation assessments. Preliminary results from two models (GrapeModel and STICS) showed contrasting abilities in reproducing the observed data depending on the site, the year and the target variable considered. These results suggest that a limited dataset for model calibration would lead to poor simulation outputs. However, a more complete interpretation and detailed analysis of the results will be provided when considering the other models simulations
Effect of changing size and composition of a crop model ensemble on impact and adaptation response surfaces
No full textClimate change is expected to generate severe impacts in cropping systems and food production. Because of that, successful local adaptation is needed.Impact response surfaces (IRSs) are tools that allow assessing responses of studied variables (yields) to systematic changes in two explanatory variables (e.g. precipitation, P, and temperature, T). Adaptation response surfaces (ARSs) show the impacts or efficiencies of adaptation measures within the same T and P change space. To quantify some important aspects of uncertainties of model simulations, the use of an ensemble of crop simulation models is recommended. Yet properties of climate model ensembles have been analyzed in depth, this is not the case for crop model ensembles.Changes in ensemble composition and size can occur when the ensemble is extended to include new members, or when some are excluded (e.g. members giving implausible results). These changes can make an important difference on the results for both impact and/or adaptation simulations and affect the conclusions or management recommendations made based on them.For this study we are utilizing simulations from an ensemble of crop models that were applied to simulate wheat growth in Lleida, northwest of Spain. The outputs of this ensemble have been used to create IRSs and ARSs, to analyze the response of wheat yield to a range of T and P perturbations, under different CO2 levels.The objective of this study is to establish a methodology to show the effects of changing the ensemble composition and size on impact and adaptation assessment. The methodology developed here allows measuring the impact of the ensemble members' selection on the ensemble central tendency measures and on the IRSs and ARSs main features and allows for analysis of robustness of conclusions
Modelling long term effects of cropping and managements systems on soil organic matter, C/N dynamics and crop growth
Full text linkWhile simulation of cropping systems over a few years might reflect well the short term effects of management and cultivation, long term effects on soil properties and their consequences for crop growth and matter fluxes are not captured. Especially the effect on soil carbon sequestration/depletion is addressed by this task. Simulations of an ensemble of crop models are performed as transient runs over a period of 120 year using observed weather from three stations in Czech Republic (1961-2010) and transient long time climate change scenarios (2011-2080) from five GCM of the CMIP5 ensemble to assess the effect of different cropping and management systems on carbon sequestration, matter fluxes and crop production in an integrative way. Two cropping systems are regarded comprising two times winter wheat, silage maize, spring barley and oilseed rape. Crop rotations differ regarding their organic input from crop residues, nitrogen fertilization and implementation of catch crops. Models are applied for two soil types with different water holding capacity. Cultivation and nutrient management is adapted using management rules related to weather and soil conditions. Data of phenology and crop yield from the region of the regarded crops were provided to calibrate the models for crops of the rotations. Twelve models were calibrated in this first step. For the transient long term runs results of four models were submitted so far. Outputs are crop yields, nitrogen uptake, soil water and mineral nitrogen contents, as well as water and nitrogen fluxes to the atmosphere and groundwater. Changes in the carbon stocks and the consequences for nitrogen mineralisation, N fertilization and emissions also considered.
Process-based modelling of the nutritive value of forages: a review
No full textModelling sward nutritional value (NV) is of particular importance to understand the interactions between grasslands, livestock production, environment and climate-related impacts. Variables describing nutritive value vary significantly between ruminant production systems, but two types are commonly used: 1) variables related to cell wall content, digestibility and energy, and 2) variables related to protein content.This study reviews and compares alternative modelling approaches simulating forage NV. It is intended to: 1) provide model users essential information for a fit-purpose use of grassland models; 2) give model builders feedback helpful in improving the models; 3) promote the development of state-of-the-art model assessment. The focus is on approaches applicable for European grasslands, as implemented in the grassland models; BASGRA, CATIMO, IFSM, MCPy, ModVege, PaSim, QUAL, SPACSYS, and STICS. These models cover swards cut for silage or hay, grazed swards, monocultures and mixtures, permanent grasslands and leys kept for less than five years.Six out of nine models use neutral detergent fibre (NDF) to describe content of structural carbohydrates. Digestibility of harvested dry matter (DM) is estimated as a function of NDF content and NDF digestibility in five models. Two of the models use an alternative approach that consists in estimating organic matter digestibility or in-vitro true digestibility of DM directly. Three of the models include variables to describe net energy content of DM whereas one model use metabolizable energy. To estimate protein value of harvested DM seven approaches use crude protein concentration calculated as a function of plant nitrogen concentration and one models uses digestible intestinal protein content
The feed story for dairy production systems under climate change
Full text linkOf all ruminant production systems, high-yielding dairy cows have the most stringent criteria onnutrition, with feed intakes up to more than three times that required for maintenance alone. Forthis reason, dairy production systems provide an interesting case study with which to explore theimplications of climate change on feed provision and utilization by the animal. Dairy productionsystems across Europe vary widely in production intensity and in nutrition strategies applied.Systems range from almost fully grazed to almost fully confined systems, and from low to highproduction intensities (per cow or per farmed hectare) of: external resource use (e.g. feedpurchased), level of farm automation and technology application, and financial investment.Irrespective of this huge variety of dairy farming systems, they have in common that home-grownroughages are an important part of the diet. Climate change will directly impact on roughageproduction and hence on: the supply and quality of roughages, the nutritional strategies adoptedand cow performance. Indirectly, through its impact on home-grown roughages climate changewill also impact on the requirements for: home-grown feed crops, purchased feed crops,supplemental by-product feeds (for example, from the food or bio-energy industries) andprocessed concentrate feeds, depending on whether production targets are to be maintained ornot. These potential consequences of climate change have been reviewed. Challenges addressedand presented here will include the need to reduce phosphorus and nitrogen surpluses and/orlosses from the system. The implications and limits to various nutritional adaptation strategies,and the alternatives available to farmers and the feed industry, will be discussed in the context ofrecent scientific insights and against the background of the models and modelling conceptscurrently in use in practice and in research