Abstract: A field experiment was conducted on Haplic Luvisol developed from loess to assess the effects of soil deformation and straw mulch on soil water status (matric potential), temperature, penetration resistance, soybean growth, seed yield and yield components including straw, protein and oil in 2006-2008. Water use efficiencies related to the amount of rainfall during the growing seasons were calculated for seeds and total above ground biomass. The soil deformation levels (main plots) comprised the following trials: non-compacted (NC, 0 tractor pass), moderately compacted (MC, 3 passes), and strongly compacted (SC, 5 passes). A uniform seedbed in all plots was prepared by harrowing before planting. The main plots included sub-plots without and with surface wheat straw mulch (0.5 kg m(-2)) and the corresponding trials were NC + M, MC + M, SC + M. The amount and distribution of rainfall during the growing season differed among the experimental years with extended drought at bloom-full seed (R2-R6) stages in 2006, good water supply in 2007, and alternative periods with relatively high and low rainfalls in 2008. The effect of soil deformation on matric potential was influenced by weather conditions, soybean growth phase, mulching and depth. The differences were greatest in 2007 and 2008 at R7-R8 growth stages. With increasing deformation level from NC to SC matric potential for 0-15 cm depth during these stages significantly decreased from -401 to -1184 kPa in 2007 and from -1154 to -1432 kPa in 2008. On mulched soil, the corresponding ranges were from -541 to -841 klpa and from -748 to -1386 kPa, respectively. In the dry summer 2006, the differences were smaller and less consistent. Irrespective of soil deformation level, mulching reduced soil temperature in most growth phases but most pronounced initially. Most yield components increased from NC to MC during the experiments which could be attributed to enhanced root water and nutrient uptake rates and decreased from MC to SC due to high soil strength that restrained root growth down to deeper depth. The yields of seeds, straw, protein and oil as well as water productivity of soybean seed and biomass were improved by mulching in 2007-2008. This improvement was more pronounced in 2007 when the mean yield of seeds, protein and oil were significantly greater by 16, 29 and 11%, respectively and was attributed to positive alterations in soil water retention. These results indicate the possibilities of improvement in soybean performance by identifying allowable amount of traffic and mulching practices at planting depending on weather fluctuations during the growing season. Since rainfall and air temperature distribution in 2007 are close to those averaged over a long period of time, the use of straw mulch may positively affect soybean performance and yields excluding anomalously dry years. The positive effect of straw mulch can be enhanced by moderate soil deformation combined with seedbed loosening before planting to avoid constraining effect of soil structure on crop establishment. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: Numerous climate futures are now available from global climate models. Translation of climate data such as precipitation and temperatures into ecologically meaningful outputs for managers and planners is the next frontier. We describe a model-based open platform to assess vulnerabilities of agricultural systems to climate change on pixel-wise data. The platform includes a simulation modeling engine and is suited to work with NetCDF format of input and output files. In a case study covering a region (Auvergne) in the Massif Central of France, the platform is configured to characterize climate (occurrence of arid conditions in historical and projected climate records), soils and human management, and is then used to assess the vulnerability to climate change of grassland productivity (downscaled to a fine scale). We demonstrate how using climate time series, and process-based simulations vulnerabilities can be defined at fine spatial scales relevant to farmers and land managers, and can be incorporated into management frameworks. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: An integrated modelling framework (IMF) has been developed and applied to analyse climate change impacts and the effectiveness of adaptation measures in Austrian agriculture. The IMF couples the crop rotation model CropRota, the bio-physical process model EPIC and the bottom-up economic land use model PASMA at regional level (NUTS-3) considering agri-environmental indicators. Four contrasting regional climate model (RCM) simulations represent climate change until 2050. The RCM simulations are applied to a baseline and three adaptation and policy scenarios. Climate change increases crop productivity on national average in the IMF. Changes in average gross margins at national level range from 0% to + 5% between the baseline and the three adaptation and policy scenarios. The impacts at NUTS-3 level range from -5% to + 7% between the baseline and the three adaptation and policy scenarios. Adaptation measures such as planting of winter cover crops, reduced tillage and irrigation are effective in reducing yield losses, increasing revenues, or in improving environmental states under climate change. Future research should account for extreme weather events in order to analyse whether average productivity gains at the aggregated level suffice to cover costs from expected higher climate variability.