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Palatnik, R. R. (2015). Climate-dependent yields (Vol. 6).
Abstract: In this report we summarize the contributions made by four groups to the subject of climate dependent yields. The first is by Waldemar Bojar, Leszek Knopik, Jacek Zarski, Cezary Slawinski, Piotr Baranowski and Wojciech Zarski on the subject of “the impact of extreme climate changes on the forecasted agriculture production”. It presents general characteristics of resources and outputs of agriculture in the Kujawsko-Pomorskie (K&P) and Lubelskie regions, based on statistical databases and the literature review. In this study, some statistically significant dependencies between the climatic parameters and yields of selected important crops in the abovementioned regions were worked out on the basis of empirical survey conducted in the University of Technology and Life Sciences and Institute of Agrophysics in Lublin. Efforts were taken to make integrated assessments of forecasted agricultural outputs influenced by climate extreme phenomena on the basis of the found dependencies’ yields – precipitation and the data coming from wide area model regional outputs such as prices, areas of farmland and yields. The second contribution is by Bojar W., Knopik L. and Zarski J. on the subject of “integrated assessment of business crop productivity and profitability to use in food supply forecasting”. It examines the proposals to build a model describing the amount of precipitation and taking into account periods without rain. This model is based on a mixture of gamma distribution and one point-distribution. The third contribution is by Iddo Kan on the Vegetative Agricultural Land Use Economic (VALUE) model. It discusses the sub-task with respect to crops of statistically estimating with statistical methods predictions of expected crop-yield contingent on climate, soil and production cost for use in existing trade models, or refined versions thereof, and how VALUE can contribute to this sub-task. The fourth contribution was made by Christoph Muller and Richard D. Robertson on the subject of “projecting future crop productivity for global economic modelling”. It supplies a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. No Label
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Biewald, A. (2015). Climate dependent equilibrium model (Vol. 6).
Abstract: In the framework of AgMIP (Agricultural Model Intercomparison Project; www.agmip.org), several articles have been published in which about 10 leading, agro-economic models analysed the impact of climate change on agricultural yields, area, consumption and food prices (Lotze-Campen et al. 2014, Nelson et. al 2014a,b Schmitz et al. 2014). A part of these articles are available freely through the publisher (e.g. http://www.pnas.org/content/111/9/3274). PIK has not only contributed through model simulations with the spatially explicit, agro-economic model MAgPIE, but also by coordinating this activity. Starting with AgMIP phase II in 2015, AgMIP has now for the first time conducted the model-analysis for different “Shared Socio-economic Pathways” (short SSPs). A first study has been published in the renowned journal “Environmental Research Letters” (Wiebe et al. 2015). These are important contributions to task 2.3 which aimed at simulating the impact of global climate changes on agricultural systems.Another study which is under revision in the journal PNAS, investigates the impact of climate change on agricultural welfare. The results of this paper are based on simulations with 20 different General Circulation Models (GCMs). This provides the opportunity to understand the uncertainty inherent in the different climate models better and improves the credibility of results.All mentioned articles and results are based on harmonized yield changes, which are a result of multi-model simulations, conducted in the framework of ISI-MIP (Inter-Sectoral Impact Model Intercomparison Project) and coordinated at PIK. These model results are publicly available (www.isi-mip.org) and part of an open source strategy of the institute. The modelling group around the agro-economic model MAgPIE (Model of Agriculture and its Impact on the Environment) currently discusses an open source strategy for publishing the model code. As a first step, a detailed description of the model will be available shortly (http://redmine.pik-potsdam.de/projects/magpie/wiki).PIK and the modelling group around MAgPIE have also contributed to the geoportal GLUES (Global Assessment of Land Use Dynamics, Greenhouse Gas Emissions and Ecosystem Services) where project partners can publish and share global and regional data sets as well as model results on scenarios of land use, climate change and economic development. MAgPIE results on landuse change, emissions and deforestation for different socio-economic scenarios have been made available there (http://catalog-glues.ufz.de/terraCatalog/Start.do;jsessionid=80F6A3D2C446674B898881D0589887E4). No Label
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Quaranta, G. (2015). Model integration with economist perspectives (Vol. 6).
Abstract: Models integration and possible contrasts with up-scaling activities has received increasing attention in recent years especially with respect to the relationship between farm-economics and biophysical assessments. Current bio-economic models that analyse the trade-offs between farm income and interventions on eco-bio-environmental parameters such as maintenance of biodiversity, reduction of erosion and nitrate pollution and more, include static models. Agricultural systems are facing a series of threats, including climate change, land degradation, price volatility and intensification processes, which put their long-term sustainability into question. The University of Basilicata in collaboration with local representatives from various sectors of production in the Basilicata region of Southern Italy has developed an integrated study to define a model system to assess the dynamics at play in rural territories. The study tested the explanatory usefulness of resilience theory for the Basilicata agricultural social-ecological system, applying the adaptive cycle as a diagnostic tool to explore the dynamics and trajectories of change in the coupled social-ecological systems, and evaluating the performance of social, economic and social capitals, which are subject to the same dynamics. The use of dynamic analysis of the social, economic and natural capitals as the key to interpret the various phases of the adaptive cycle of the two agricultural systems proved a powerful tool in analysing the relationships between resilience and sustainable development in rural territories. The adoption of capitals and their inter-relations proved fundamental to the elaboration of adaptation strategies which were compatible with patterns of sustainability. The adaptive cycle heuristic, despite some methodological difficulties, remains useful to describe processes of change in rural socio-ecological systems. There could be enormous potential in adopting these instruments to help identify of the needs of different territories and help the framing and implementation of rural policies. No Label
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Bellocchi, G., & Sándor, R. (2015). Model intercomparison (Vol. 6).
Abstract: This deliverable focuses on some illustrative results obtained with different grassland- specific, grassland adapted crop and dynamic vegetation models selected out of the first list of models compiled in D-L2.1.1 to simulate biomass and flux data from grassland sites in Europe and peri-Mediterranean regions (D-L2.1.1 and D-L2.1.2). Results from uncalibrated simulations were documented in the D-L2.3 report as a blind exercise. Some model improvements are emphasized in this report due to the higher information level of the model calibrations. The complete set of results will include simulations from uncalibrated and calibrated models. No Label
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Janssen, S., Hansen, J. G., Jorgensen, J., & Jørgensen, M. S. (2015). Operational database for storing and extracting data (Vol. 6).
Abstract: This deliverable lays out the work as done as part of MACSUR CropM on data, with the focus on improving data management and have shared data curation for future use. The issue was tackled with help from the MACSUR central hub coordination in the form of Jason Jargenson from University of Reading. The data management as proposed and implemented in this deliverable is very much a bottom up process, in which partners in a meeting in Spring 2013 in Aarhus investigated the best way forward for data management across activities in CropM.As a follow up to this, the work was mainly divided in three parts: 1. The Open Data Journal for Agricultural Research, mainly focused on long term data archival and citation of data sets, as input and outputs to the modelling work, as part of MACSUR, lead by Wageningen UR 2. The Geonetwork data catalog hosted at Aarhus Universitet, that allows for operational access and storage of data sets as part of the ongoing work, also for restricted access of the consortium, and as a first step to visualization, lead by Aarhus Universitet. 3. The work on rating data sets, that provides a tool for improving data set access in an early phase for connecting them to models, lead by Reading University. At the end of the deliverable some next steps are giving for data activities in the context of AgMIP and beyond. No Label
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