|
|
Hlavinka, P., Kersebaum, K. C., Dubrovský, M., Fischer, M., Pohanková, E., Balek, J., et al. (2015). Water balance, drought stress and yields for rainfed field crop rotations under present and future conditions in the Czech Republic. Clim. Res., 65, 175–192.
Abstract: Continuous crop rotation modeling is a prospective trend that, compared to 1-crop or discrete year-by-year calculations, can provide more accurate results that are closer to real conditions. The goal of this study was to compare the water balance and yields estimated by the HERMES crop rotation model for present and future climatic conditions in the Czech Republic. Three locations were selected, representing important agricultural regions with different climatic conditions. Crop rotation (spring barley, silage maize, winter wheat, winter rape) was simulated from 1981-2080. The 1981-2010 period was covered by measured meteorological data, while 2011-2080 was represented by a transient synthetic weather series from the weather generator M& Rfi. The data were based on 5 circulation models, representing an ensemble of 18 CMIP3 global circulation models, to preserve much of the uncertainty of the original ensemble. Two types of crop management were compared, and the influences of soil quality, increasing atmospheric CO2 and adaptation measures (i. e. sowing date changes) were also considered. Results suggest that under a ‘dry’ scenario (such as GFCM21), C-3 crops in drier regions will be devastated for a significant number of seasons. Negative impacts are likely even on premium-quality soils regardless of flexible sowing dates and accounting for increasing CO2 concentrations. Moreover, in dry conditions, the use of crop rotations with catch crops may have negative impacts, exacerbating the soil water deficit for subsequent crops. This approach is a promising method for determining how various management strategies and crop rotations can affect yields as well as water, carbon and nitrogen cycling.
|
|
|
|
Helming, J. (2015). Implementation of the GTAP emission database in MAGNET; applications at European and global scales (Vol. 5).
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
|
|
|
|
Heinschink, K., Sinabell, F., & Tribl, C. (2015). Decomposition of variable costs in the Austrian agricultural production. In Jahrbuch der ÖGA (Vol. 25, pp. 231–240).
|
|
|
|
Heinemann, A. B., Barrios-Perez, C., Ramirez-Villegas, J., Arango-Londoño, D., Bonilla-Findji, O., Medeiros, J. C., et al. (2015). Variation and impact of drought-stress patterns across upland rice target population of environments in Brazil. J. Experim. Bot., 66(12), 3625–3638.
Abstract: The upland rice (UR) cropped area in Brazil has decreased in the last decade. Importantly, a portion of this decrease can be attributed to the current UR breeding programme strategy, according to which direct grain yield selection is targeted primarily to the most favourable areas. New strategies for more-efficient crop breeding under non-optimal conditions are needed for Brazil’s UR regions. Such strategies should include a classification of spatio-temporal yield variations in environmental groups, as well as a determination of prevalent drought types and their characteristics (duration, intensity, phenological timing, and physiological effects) within those environmental groups. This study used a process-based crop model to support the Brazilian UR breeding programme in their efforts to adopt a new strategy that accounts for the varying range of environments where UR is currently cultivated. Crop simulations based on a commonly grown cultivar (BRS Primavera) and statistical analyses of simulated yield suggested that the target population of environments can be divided into three groups of environments: a highly favorable environment (HFE, 19% of area), a favorable environment (FE, 44%), and least favourable environment (LFE, 37%). Stress-free conditions dominated the HFE group (69% likelihood) and reproductive stress dominated the LFE group (68% likelihood), whereas reproductive and terminal drought stress were found to be almost equally likely to occur in the FE group. For the best and worst environments, we propose specific adaptation focused on the representative stress, while for the FE, wide adaptation to drought is suggested. ‘Weighted selection’ is also a possible strategy for the FE and LFE environment groups.
|
|
|
|
Halford, N. G., & Foyer, C. H. (2015). Producing a road map that enables plants to cope with future climate change. J. Experim. Bot., 66(12), 3433–3434.
|
|
