Search Results

Now showing 1 - 9 of 9
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    Modeling vegetation and carbon dynamics of managed grasslands at the global scale with LPJmL 3.6
    (Göttingen : Copernicus GmbH, 2018) Rolinski, S.; Müller, C.; Heinke, J.; Weindl, I.; Biewald, A.; Leon Bodirsky, B.; Bondeau, A.; Boons-Prins, E.R.; Bouwman, A.F.; Leffelaar, P.A.; Roller, J.A.T.; Schaphoff, S.; Thonicke, K.
    Grassland management affects the carbon fluxes of one-third of the global land area and is thus an important factor for the global carbon budget. Nonetheless, this aspect has been largely neglected or underrepresented in global carbon cycle models. We investigate four harvesting schemes for the managed grassland implementation of the dynamic global vegetation model (DGVM) Lund-Potsdam-Jena managed Land (LPJmL) that facilitate a better representation of actual management systems globally. We describe the model implementation and analyze simulation results with respect to harvest, net primary productivity and soil carbon content and by evaluating them against reported grass yields in Europe.We demonstrate the importance of accounting for differences in grassland management by assessing potential livestock grazing densities as well as the impacts of grazing, grazing intensities and mowing systems on soil carbon stocks. Grazing leads to soil carbon losses in polar or arid regions even at moderate livestock densities ( <0.4 livestock units per hectare-LSUha-1) but not in temperate regions even at much higher densities (0.4 to 1.2 LSUha-1). Applying LPJmL with the new grassland management options enables assessments of the global grassland production and its impact on the terrestrial biogeochemical cycles but requires a global data set on current grassland management.
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    Viticulture in the Laetanian Region (Spain) during the Roman Period: Predictive Modelling and Geomatic Analysis
    (Basel : MDPI AG, 2020) Stubert, Lisa; Oliveras, Antoni Martín i; Märker, Michael; Schernthanner, Harald; Vogel, Sebastian
    Geographic information system (GIS)-based predictive modelling is widely used in archaeology to identify suitable zones for ancient settlement locations and determine underlying factors of their distribution. In this study, we developed predictive models on Roman viticulture in the Laetanian Region (Hispania Citerior-Tarraconensis), using the location of 82 ancient wine-pressing facilities or torcularia as response variables and 15 topographical and 6 socio-economic cost distance datasets as predictor variables. Several predictor variable subsets were selected either by expert knowledge of similar studies or by using a semi-automatization algorithm based on statistical distribution metrics of the input data. The latter aims at simplifying modelling and minimizing the necessity of a priori knowledge. Both approaches predicted the distribution of archeological sites sufficiently well. However, the best prediction performance was obtained by an expert knowledge model utilizing a predictor variable combination based on recommendations on viticulture by Lucius Junius Moderatus Columella, the prominent ancient Roman agronomist. The results indicate that the accessibility of a location and its connectivity to trade routes and distribution centres, determined by terrain steepness, was decisive for the settlement of viticultural facilities. With the knowledge gained, the ancient cultivated area and number of wine-pressing facilities needed for processing the vineyard yields were extrapolated for the entire study region.
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    Effectivity and Cost Efficiency of a Tax on Nitrogen Fertilizer to Reduce GHG Emissions from Agriculture
    (Basel : MDPI AG, 2020) Meyer-Aurich, Andreas; Nadi Karatay, Yusuf; Nausediene, Ausra; Kirschke, Dieter
    The use of nitrogen (N) fertilizer substantially contributes to greenhouse gas (GHG) emissions due to N2O emissions from agricultural soils and energy-intensive fertilizer manufacturing. Thus, a reduction of mineral N fertilizer use can contribute to reduced GHG emissions. Fertilizer tax is a potential instrument to provide incentives to apply less fertilizer and contribute to the mitigation of GHG emissions. This study provides model results based on a production function analysis from field experiments in Brandenburg and Schleswig-Holstein, with respect to risk aversion by calculating certainty equivalents for different levels of risk aversion. The model results were used to identify effective and cost-efficient options considering farmers’ risk aversion to reduce N fertilizer, and to compare the potential and cost of GHG mitigation with different N fertilizer tax schemes. The results show that moderate N tax levels are effective in reducing N fertilizer levels, and thus, in curbing GHG emissions at costs below 100 €/t CO2eq for rye, barley and canola. However, in wheat production, N tax has limited effects on economically optimal N use due to the effects of N fertilizer on crop quality, which affect the sale prices of wheat. The findings indicate that the level of risk aversion does not have a consistent impact on the reduction of N fertilizer with a tax, even though the level of N fertilizer use is generally lower for risk-averse agents. The differences in N fertilizer response might have an impact on the relative advantage of different crops, which should be taken into account for an effective implementation of a tax on N fertilizer.
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    Land-use futures in the shared socio-economic pathways
    (Amsterdam [u.a.] : Elsevier, 2017) Popp, Alexander; Calvin, Katherine; Fujimori, Shinichiro; Havlik, Petr; Humpenöder, Florian; Stehfest, Elke; Bodirsky, Benjamin Leon; Dietrich, Jan Philipp; Doelmann, Jonathan C.; Gusti, Mykola; Hasegawa, Tomoko; Kyle, Page; Obersteiner, Michael; Tabeau, Andrzej; Takahashi, Kiyoshi; Valin, Hugo; Waldhoff, Stephanie; Weindl, Isabelle; Wise, Marshall; Kriegler, Elmar; Lotze-Campen, Hermann; Fricko, Oliver; Riahi, Keywan; Vuuren, Detlef P. van
    In the future, the land system will be facing new intersecting challenges. While food demand, especially for resource-intensive livestock based commodities, is expected to increase, the terrestrial system has large potentials for climate change mitigation through improved agricultural management, providing biomass for bioenergy, and conserving or even enhancing carbon stocks of ecosystems. However, uncertainties in future socio-economic land use drivers may result in very different land-use dynamics and consequences for land-based ecosystem services. This is the first study with a systematic interpretation of the Shared Socio-Economic Pathways (SSPs) in terms of possible land-use changes and their consequences for the agricultural system, food provision and prices as well as greenhouse gas emissions. Therefore, five alternative Integrated Assessment Models with distinctive land-use modules have been used for the translation of the SSP narratives into quantitative projections. The model results reflect the general storylines of the SSPs and indicate a broad range of potential land-use futures with global agricultural land of 4900 mio ha in 2005 decreasing by 743 mio ha until 2100 at the lower (SSP1) and increasing by 1080 mio ha (SSP3) at the upper end. Greenhouse gas emissions from land use and land use change, as a direct outcome of these diverse land-use dynamics, and agricultural production systems differ strongly across SSPs (e.g. cumulative land use change emissions between 2005 and 2100 range from −54 to 402 Gt CO2). The inclusion of land-based mitigation efforts, particularly those in the most ambitious mitigation scenarios, further broadens the range of potential land futures and can strongly affect greenhouse gas dynamics and food prices. In general, it can be concluded that low demand for agricultural commodities, rapid growth in agricultural productivity and globalized trade, all most pronounced in a SSP1 world, have the potential to enhance the extent of natural ecosystems, lead to lowest greenhouse gas emissions from the land system and decrease food prices over time. The SSP-based land use pathways presented in this paper aim at supporting future climate research and provide the basis for further regional integrated assessments, biodiversity research and climate impact analysis. © 2016 The Authors
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    Can Green Plants Mitigate Ammonia Concentration in Piglet Barns?
    (Basel : MDPI, 2021) Menardo, Simona; Berg, Werner; Grüneberg, Heiner; Jakob, Martina
    For animal welfare and for farmers’ health, the concentration of ammonia (NH3 ) in animal houses should be as low as possible. Plants can remove various atmospheric contaminants through the leaf stomata. This study examined the effect of ornamental plants installed inside a piglet barn on the NH3 concentration in the air. Gas measurements of the air in the ‘greened’ compartment (P) and a control compartment (CTR) took place over two measuring periods (summer–autumn and winter). Differences between the NH3 emissions were calculated based on the ventilation rates according to the CO2 balance. Fairly low mean NH3 concentrations between 2 and 4 ppm were measured. The NH3 emissions were about 20% lower (p < 0.01) in P than in CTR, in summer–autumn and in winter period. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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    Expressing stemflow commensurate with its ecohydrological importance
    (Amsterdam [u.a.] : Elsevier Science, 2018) Carlyle-Moses, Darryl E.; Iida, Shin'ichi; Germer, Sonja; Llorens, Pilar; Michalzik, Beate; Nanko, Kazuki; Tischer, Alexander; Levia, Delphis F.
    Despite some progress, the importance of stemflow remains obscured partly due to computations emphasizing canopy interception loss. We advocate for two metrics—the stand-scale funneling ratio and the stand-scale infiltration funneling ratio—to more accurately portray stemflow inputs and increase comparability across ecosystems. These metrics yield per unit area stemflow inputs orders of magnitude greater than what would have been delivered by throughfall or precipitation alone. We recommend that future studies employ these stand-scale funnelling metrics to express stemflow commensurate with its ecohydrological importance and better conceptualize the role of stemflow in plant-soil interactions, permitting advances in critical zone science. © 2018 The Authors
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    Modeling the water demand on farms
    (München : European Geopyhsical Union, 2012) Drastig, K.; Prochnow, A.; Kraatz, S.; Libra, J.; Krauß, M.; Döring, K.; Müller, D.; Hunstock, U.
    The decreasing availability of water caused by depletion and climate change combined with a growing world population requires the productive use of water now and in the future. The young researcher group "AgroHyd" at the Leibniz-Institute for Agricultural Engineering Potsdam-Bornim (ATB) is currently modeling the water demand for agricultural processes at the farm scale and developing indicators to link the hydrological and agricultural perspectives. The aim of the group is to increase productivity in agriculture by raising water productivity in plant production and livestock farming. The effects of various agronomic measures, individual and in combination, on water productivity are assessed using several indicators. Scenarios of agricultural measures, climate and diets are used to test to what extent the water demand for food production will increase due to growing global change in different regions of the world.
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    Heat stress risk in European dairy cattle husbandry under different climate change scenarios – uncertainties and potential impacts
    (Göttingen : Copernicus, 2019) Hempel, Sabrina; Menz, Christoph; Pinto, Severino; Galán, Elena; Janke, David; Estellés, Fernando; Müschner-Siemens, Theresa; Wang, Xiaoshuai; Heinicke, Julia; Zhang, Guoqiang; Amon, Barbara; del Prado, Agustín; Amon, Thomas
    In the last decades, a global warming trend was observed. Along with the temperature increase, modifications in the humidity and wind regime amplify the regional and local impacts on livestock husbandry. Direct impacts include the occurrence of climatic stress conditions. In Europe, cows are economically highly relevant and are mainly kept in naturally ventilated buildings that are most susceptible to climate change. The high-yielding cows are particularly vulnerable to heat stress. Modifications in housing management are the main measures taken to improve the ability of livestock to cope with these conditions. Measures are typically taken in direct reaction to uncomfortable conditions instead of in anticipation of a long-term risk for climatic stress. Measures that balance welfare, environmental and economic issues are barely investigated in the context of climate change and are thus almost not available for commercial farms. Quantitative analysis of the climate change impacts on animal welfare and linked economic and environmental factors is rare. Therefore, we used a numerical modeling approach to estimate the future heat stress risk in such dairy cattle husbandry systems. The indoor climate was monitored inside three reference barns in central Europe and the Mediterranean regions. An artificial neuronal network (ANN) was trained to relate the outdoor weather conditions provided by official meteorological weather stations to the measured indoor microclimate. Subsequently, this ANN model was driven by an ensemble of regional climate model projections with three different greenhouse gas concentration scenarios. For the evaluation of the heat stress risk, we considered the number and duration of heat stress events. Based on the changes in the heat stress events, various economic and environmental impacts were estimated. The impacts of the projected increase in heat stress risk varied among the barns due to different locations and designs as well as the anticipated climate change (considering different climate models and future greenhouse gas concentrations). There was an overall increasing trend in number and duration of heat stress events. At the end of the century, the number of annual stress events can be expected to increase by up to 2000, while the average duration of the events increases by up to 22 h compared to the end of the last century. This implies strong impacts on economics, environment and animal welfare and an urgent need for mid-term adaptation strategies. We anticipated that up to one-tenth of all hours of a year, correspondingly one-third of all days, will be classified as critical heat stress conditions. Due to heat stress, milk yield may decrease by about 2.8 % relative to the present European milk yield, and farmers may expect financial losses in the summer season of about 5.4 % of their monthly income. In addition, an increasing demand for emission reduction measures must be expected, as an emission increase of about 16 Gg of ammonia and 0.1 Gg of methane per year can be expected under the anticipated heat stress conditions. The cattle respiration rate increases by up to 60 %, and the standing time may be prolonged by 1 h. This causes health issues and increases the probability of medical treatments. The various impacts imply feedback loops in the climate system which are presently underexplored. Hence, future in-depth studies on the different impacts and adaptation options at different stress levels are highly recommended.
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    Dynamics of rural livelihoods and rainfall variability in Northern Ethiopian Highlands
    (Amsterdam [u.a.] : Elsevier, 2019) Adamseged, Muluken E.; Frija, Aymen; Thiel, Andreas
    [No abstract available]