Abstract: In spatial modelling of Net Primary Productivity (NPP), predictability and uncertainty depends on the availability of input data, as well as on the scale of the available data sets. Therefore, the study presented here quantifies the impact of aggregation effect of input data of different scales for a regional modelling approach using 5 different resolutions. As part of this study, the presentation focuses on the impact of the climate aggregation on the simulation of NPP. The effect is investigated on the model results of 11 different crop and biogeochemical models simulating NPP for wheat and maize for the area of the German state of North Rhine-Westphalia. The focus of the study is on the impact of drought effects across the scales considered. The data are analysed on annual time steps we followed two approaches to investigate the impact of water limitation on primary production: First, two model runs, one considers water limitation and the other one ignores the impacts of water limitation on plant production second, an external definition of dry conditions by a drought index, only considering climate data, enables a separation of grid-cells and years with drought impacts, independent of the model internal functions. The results show hardly any difference between the overall average NPP across the scales, but some variability for the impact of extreme weather conditions on the simulated NPP. No Label

Abstract: The condition of land degradation in Transylvanian Plain and its effects, being the result of local extreme physical-geographical conditions, susceptible to degradation (evidenced by the erodibility index), which overlap the extreme climatic conditions. Thermal and hydric regime monitoring is necessary in order to identify and implement measures of adaptation to the impacts of climate change. Soil moisture and temperature regimes were evaluated using a set of 20 data logging stations positioned throughout the plain.  Each station stores electronic data of ground temperature at 3 depths (10, 30, 50 cm), the humidity at the depth of 10 cm, the air temperature (at 1 m) and precipitations. Climate change in the past few years have significantly altered the climatic indicators of the Transylvanian Plain. Precipitations, although deficient in terms of annual amounts, through their regime, have a negative influence on the plant carpet. Pluvial aggressiveness index reveals, for the research period, a first peak of pluvial aggressiveness during the months of February-April, then in July and in autumn, the months of October-November. This requires special measures for soil conservation, both in autumn and early spring, soil tillage measures being recommended which ensure the presence of plant debris and vegetation in early spring but especially in summer and autumn. Climatic indicators determined for the period 2009-2013 point out, in Transylvanian Plain, a semi-arid and mediterranean climate through the rain factor Lang, respectively semi-arid (in the South),  semi-humid (in the North) according to the De Martonne index. This climatic characterization requires special technological measures for soil conservation (green curtains, green manure, no-tillage and minimum tillage with mulch layer). The biologically active temperature recorded in the TP demonstrates the need to renew the division of the crop areas reported in the literature. No Label

Abstract: World agriculture accounts for approximately 14% of all anthropogenic greenhouse gas. The share of  agriculture in total greenhouse gas emissions in the EU 28 increased from 8.7% in 2007 to about 10.3% in 2012. This includes methane and nitrous oxide emissions (European Environment Agency; Gugele et al., 2005; Beach et al., 2008). This increase is mainly explained by emission reductions in the rest of the economy.  Reductions in greenhouse gas emissions from agriculture  remained limited in the recent past.Options to reduce emissions in agriculture depends on macro-economic trends, including  international trade, agricultural policies, economic growth and consumption patterns. Global trade patterns will affect the regional distribution of agricultural production and the corresponding greenhouse gas emissions. The ability to introduce cost-effective measures to reduce greenhouse gas emissions are difficult to assess on a global scale. To tackle this problem there is a need for an interdisciplinary model instrument, in which both knowledge from macro and trade economy and natural sciences are included.The global equilibrium model MAGNET (Modular Applied GeNeral Equilibrium Tool) is developed by LEI and is an adaptation to the GTAP model (Woltjer & Kuiper, 2014). The main purpose of MAGNET is to provide a globally applied general equilibrium modelling framework, having the standard GTAP model as the core. MAGNET is complemented with the greenhouse gas emission dataset for the year 2007  that is made available by the GTAP consortium. The database includes emissions of carbon dioxide (CO2), nitrous dioxide (N2O) and methane (CH4).  N2O and CH4 emissions are especially relevant for the agricultural sector. The incorporation of these emissions in MAGNET enables us  to analyse current and  future greenhouse gas emissions under different policies and mitigation measures on a global scale, simultaneously taking into account interactions between the rest of the economy (by sectors) and across regions in the world.The GTAP emissions dataset estimates the share of European agriculture in total greenhouse gas emissions in the EU 28 to be about 11.5% in 2007. This deviates from total emission figures on Europe as presented by the European Environment Agency (EEA). The presentation will focus on some possible explanations for this difference. We will compare gaps in the dataset in agriculture and the rest of the economy. Next we will report the emission per EU member state in a 2020 baseline scenario. Here we will present percentage differences in changes in greenhouse gas emissions in 2020 vis-a-vis a baseyear in 2012. No Label