FACCE MACSUR Reports (Modelling European Agriculture with Climate Change for Food Security)
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Report on results of scaling exercise
Get PDFThe MACSUR scaling exercise investigates the effects of scaling crop model data in combination with different data types (climate, soil and management). For this purpose the effect of aggregating model input as well as spatial sampling schemes were tested with a range of crop models under varying conditions. From findings for winter wheat yield of the region of North Rhine-Westphalia (Germany) it can be concluded for most models, that regional water-limited yield simulations in a temperate humid region are on average little affected by aggregating soil or climate data up to 100 km resolution. However, some models showed considerably larger biases. Consequently, models need to be assessed individually for their robustness to input data aggregation when simulating regional yields. Aggregating soils partially led to aggregation effects larger than from averaged climate data, in the range or larger than the inter-annual yield variability or differences between models. This can thus be a dominant source of uncertainty when assessing spatial yield patterns of heterogeneous regions. Simultaneous use of aggregated climate and soil data is likely to increase these aggregation effects further. However, large negative aggregation effects were found in areas with soils characterized by high available water holding capacity and large positive aggregation effects in areas with soils of predominantly low available water holding capacity. This indicates that the direction and magnitude of aggregation effects may be estimated from a limited number of soil variables.Similarly, the precision of simple random sampling (SimRS) and variations of stratified random sampling (StrRS) schemes in estimating regional mean water-limited yields were evaluated. We found that the precision gains of StrRS varied considerably across stratification methods and crop models. Precision gains for compact geographical stratification were positive, stable and consistent across crop models. Stratification with soil water holding capacity had very high precision gains for twelve models, but resulted in negative gains for two models. Increasing the sample size monotonously decreased the sampling errors for all the sampling schemes. We conclude that compact geographical stratification can modestly but consistently improve the precision in estimating regional mean yields. Using the most influential environmental variable for stratification can notably improve the sampling precision, when the sensitivity behaviour of a crop model is known.The report contains parts from published journal articles, therfore, only the abstract is made available
Imapcts of climate change adaptation pathways in agriculture on soil services and Sustainable Development Goals
No full textSoil systems are fundamental for food security and for sustainable developmentprovides biomass for food, feed, energy and fibreserves as habitats for organisms and gene pools (biodiversity)contributes to carbon sequestration•Effects of climate change associated with extreme events, such as heavy rainfall, heat waves, drought and landslides, however, threatens to increase the potential for soil erosion and soil compactionClimate change may affect soil functions and services in two ways, directly and indirectlye.g. soil erosion rates may increase because of increased frequencies of high intensity rainfalls → directirrigation regimes, crop rotation changes, or soil tillage practices as adaptation measures may improve or deteriorate soil quality → indirect•Comprehensive evidence exists for the first case of direct effects, knowledge about the indirect effects of agricultural adaptation pathways is more scattered•Meanwhile, improving soil functions play an important role in achieving a number of Sustainable Development Goals (SDGs), particularly (Montanarella & Alva 2015; Bouma & Montanarella 2016):SDG 2: achieve food security and promote sustainable agricultureSDG 13: take action to combat climate change and its impactsSDG 15: reverse land degradation and halt biodiversity loss ConclusionsWhile comprehensive evidence exists for direct effect of climate change on soil services, there has yet to be a study that has investigated the indirect linkage•This study seeks to address this gap so as to improve the scientific knowledge on sustainable soil management•Although adaptation practices show improvements in soil erosion and soil organic matters, the main challenge remains to combat soil compaction•Adaptation practices reveal rather positive effect on food and biomass production as well as improvement of carbon sequestration in soil (storing more carbon in soils) but other two functions seem to be less focus•Achievement of SDG 2 and 13 targets are currently underway with positive link, however the achievement of SDG 15 need to be the focus going forward•We hope to get completed information from all case studies to improve the robustness of the findings•We feel rather biased approach towards the northern part of Europe (N=7)•The study aimed to understand and find out the impacts of climate change adaptation practices on soil services. Appropriate “response” policy tools could be an additional interesting research•How climate change impacts soil function in the absence of adaptation → perhaps, would reveal the value of adaptation knowledge and action
Evaluation of scaling methods for other crops, regions and scaling methods
Get PDFThe MACSUR WP3 Scaling Exercise predominantly investigated the effects of spatially aggregating or sampling model input data for large scale model assessments. This was first carried out for the region of North Rhine-Westphalia (NRW) and predominantly evaluated for water-limited yield simulations of winter wheat grain yield. In this report, specific findings from NRW are compared to findings from a larger population of simulation settings / environmental conditions, extending the analysis to further crops, regions and impact variables. Similar aggregation errors and spatial patterns of silage maize and winter wheat yield have been found. When verifying findings with a different region, partially similar error patterns were observed for Tuscany, Italy. While the aggregation error is strongly related to the spatial heterogeneity of the data, other influences as e.g. the climate may be less relevant if the cropping system is adapted to local conditions. Findings for different output variables (NPP, N-leaching, water use efficiency, etc.) largely confirm findings from crop yield with regard to error patterns. However, absolute values and thresholds partially differed considerably across output variables. The findings give a first empiric insight towards a possible generalization of aggregation errors.The report contains material from published papers. Therefore only the abstract is made available
Is agriculture off the hook in the EU's 2030 Climate Policy?
Get PDFEU climate policy and AFOLU•Overall 2030 level of ambition agreed by European Council October 2014•Commission ESR proposal July 2016 – sharing of effort in NETS across MS plus trading mechanisms•Commission LULUCF proposal – integration of LULUCF into climate policy•AFOLU mitigation pursued through CAP as well as flanking environmental policies•No specific EU targets for agricultural mitigation in NETS•Ultimately, how AFOLU mitigation is pursued will depend on MS decisions2Implications of EU bubble•Commission has put in place trading mechanisms in NETS sectors to ensure least-cost fulfilment of overall EU targets•Challenge of MS ESR targets also depends on use MS make of trading mechanisms•MS have not to date made use of these mechanisms and prefer to meet targets domestically•A number of MS have domestic targets in addition to EU targets•ESR IA looked at adding central information site, central market place for AEA transfers or mandatory auctioning•Links with annual monitoring and 5-year legal compliance checks (2027 and 2032)
Data sets of spatial variable data from Precision Agriculture data
No full textData sets from two fields in Germany and Italy with spatial variable soil and management information were distributed to crop growth modellers to investigate the site sensitivity of crop models. For the field in Germany data from 60 grid points were provided while the Italian data set consists of 100 data points. Spatial yield observations for wheat were available for three years to be compared with model outputs
Agriculture and land use in the Commission proposals for the 2030 Climate and Energy Framework
No full textIntroduction: policy context•Impact Assessment: options, models, examples•Proposal for Effort Sharing Regulation and LULUCF Regulation•Conclusions and Outlook: more work for modellers 1. Fully in line with Paris Agreement, no backsliding on robustness and transparency2.Provides for continuity•Addresses Member States and not individual farmers or foresters•Stand-alone LULUCF pillar•No-debit rule (from KP)•Flexibility within LULUCF and from ESR to LULUCF3.Proposes limited innovations•Flexibility to the ESR up to 280 mt CO2•Aligning accounting rules (AF,CM/GM)•Defining EU-internal process to set national forest management levels•Simplifying administrationConclusions (2
Climate change adaptation in maize production in Serbia
Get PDFClimate change is noticed and well established phenomenon, described as change in the statistical properties of the climate system, considered over long period of time, regardless of cause (Houghton, 1996). This change has been monitored on global (Rosenzweig et al., 1994; Harrison et al., 1995; Wolf et al., 1995; Watson et al., 1996; Downing et al., 2000; Sathaye et al., 1997; Sirotenko et al., 1997) and regional scale (Alexandrov et al., 2002; Lalic et al., 2012; Vučetić, 2011) by researchers, organizations and part of various programmes (IPCC, UNESCO Climate Change Initiative). In a same time, it was analysed change in agroclimatic indices, soil and water balance, crop development and yield, that quantify climate change impact on agricultural production. In recent regional studies and research projects (COST 734, 2008; ADAGIO, 2009), it was estimated and quantified climate change impact on yield and development in crop production of Central and Eastern European countries and Mediterranean region. The research showed a decrease in yield in several major crops, important in national food production and part of economy. A high variability in yield from year to year and decrease in yield was showed for most cereals.
Managing Agricultural Greenhouse Gases Network (MAGGnet): Exploring Greenhouse Gas Mitigation Potential of Cropland Management Practices
Get PDFGlobal Research Alliance on Agricultural Greenhouse Gases Established: December 2009, United Nations Climate Change Conference, Copenhagen, Denmark•Purpose: Facilitate research, development and extension of technologies and practices that will help deliver ways to grow more food (and more climate-resilient food systems) without growing greenhouse gas emissions.•Current Membership: 46 countries (Europe, Americas, Asia Pacific, Africa
Risk efficiency of irrigation to cereals in northeastern Germany with respect to nitrogen fertilizer
No full textEconomics of cereal irrigation in Germany Münch et al have shown that higher yields due to irrigation now do not cover the costs of irrigation In future with expected higher crop yield response to irrigation this situation could change What about impact of irrigation on risk efficiency? Could this be a reason to invest in irrigation technologies for cereals?Irrigation of cereals in Germany can be profitable (barley at high crop prices, with existing technologies) Irrigation and N fertilizer reduction were both found to be risk mitigating strategies (should be traded off) Production risk mitigation hardly justifies irrigation if is not profitable without risk aversio
