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Author |
Weindl, I.; Popp, A.; Bodirsky, B.L.; Rolinski, S.; Lotze-Campen, H.; Biewald, A.; Humpenoeder, F.; Dietrich, J.P.; Stevanovic, M. |
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Title |
Livestock and human use of land: Productivity trends and dietary choices as drivers of future land and carbon dynamics |
Type |
Journal Article |
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Year |
2017 |
Publication |
Global and Planetary Change |
Abbreviated Journal |
Global And Planetary Change |
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Volume |
159 |
Issue |
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Pages |
1-10 |
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Keywords |
Livestock productivity; Diets; Land use; Deforestation; Carbon emissions; Greenhouse gas mitigation; Greenhouse-Gas Emissions; Climate-Change Mitigation; Food-Demand; Crop; Productivity; Cover Change; Systems; Agriculture; Intensification; Environment; Deforestation |
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Abstract |
Land use change has been the primary driving force of human alteration of terrestrial ecosystems. With 80% of agricultural land dedicated to livestock production, the sector is an important lever to attenuate land requirements for food production and carbon emissions from land use change. In this study, we quantify impacts of changing human diets and livestock productivity on land dynamics and depletion of carbon stored in vegetation, litter and soils. Across all investigated productivity pathways, lower consumption of livestock products can substantially reduce deforestation (47-55%) and cumulative carbon losses (34-57%). On the supply side, already minor productivity growth in extensive livestock production systems leads to substantial CO2 emission abatement, but the emission saving potential of productivity gains in intensive systems is limited, also involving trade-offs with soil carbon stocks. If accounting for uncertainties related to future trade restrictions, crop yields and pasture productivity, the range of projected carbon savings from changing diets increases to 23-78%. Highest abatement of carbon emissions (63-78%) can be achieved if reduced consumption of animal-based products is combined with sustained investments into productivity increases in plant production. Our analysis emphasizes the importance to integrate demand- and supply-side oriented mitigation strategies and to combine efforts in the crop and livestock sector to enable synergies for climate protection. |
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2018-01-25 |
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English |
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ISSN |
0921-8181 |
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LiveM, TradeM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
5188 |
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Author |
Luo, K.; Tao, F.; Deng, X.; Moiwo, J.P. |
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Title |
Changes in potential evapotranspiration and surface runoff in 1981-2010 and the driving factors in Upper Heihe River Basin in Northwest China |
Type |
Journal Article |
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Year |
2017 |
Publication |
Hydrological Processes |
Abbreviated Journal |
Hydrol. Process. |
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Volume |
31 |
Issue |
1 |
Pages |
90-103 |
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Keywords |
driving factor; potential evaporation; surface runoff; SWAT model; Upper Heihe River Basin; SWAT Hydrologic Model; Pan Evaporation; Vegetation Model; Climate-Change; Water; Trends; Precipitation; Uncertainty; Variability; Generation |
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Abstract |
Changes in potential evapotranspiration and surface runoff can have profound implications for hydrological processes in arid and semiarid regions. In this study, we investigated the response of hydrological processes to climate change in Upper Heihe River Basin in Northwest China for the period from 1981 to 2010. We used agronomic, climatic and hydrological data to drive the Soil and Water Assessment Tool model for changes in potential evapotranspiration (ET0) and surface runoff and the driving factors in the study area. The results showed that increasing autumn temperature increased snow melt, resulting in increased surface runoff, especially in September and October. The spatial distribution of annual runoff was different from that of seasonal runoff, with the highest runoff in Yeniugou River, followed by Babaohe River and then the tributaries in the northern of the basin. There was no evaporation paradox at annual and seasonal time scales, and annual ET0 was driven mainly by wind speed. ET0 was driven by relative humidity in spring, sunshine hour duration in autumn and both sunshine hour duration and relative humility in summer. Surface runoff was controlled by temperature in spring and winter and by precipitation in summer (flood season). Although surface runoff increased in autumn with increasing temperature, it depended on rainfall in September and on temperature in October and November. Copyright (C) 2016 John Wiley & Sons, Ltd. |
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2018-08-23 |
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0885-6087 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
5207 |
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Author |
Doro, L.; Jones, C.; Williams, J.R.; Norfleet, M.L.; Izaurralde, R.C.; Wang, X.; Jeong, J. |
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Title |
The Variable Saturation Hydraulic Conductivity Method for Improving Soil Water Content Simulation in EPIC and APEX Models |
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Journal Article |
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Year |
2017 |
Publication |
Vadose Zone Journal |
Abbreviated Journal |
Vadose Zone Journal |
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Volume |
16 |
Issue |
13 |
Pages |
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Keywords |
Conservation Effects Assessment; Runoff Simulation; Unsaturated Soils; United-States; Porous-Media; Moisture; Flow; Productivity; Transport; Denitrification |
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Abstract |
Soil water percolation is a key process in the life cycle of water in fields, watersheds, and river basins. The Environmental Policy Integrated Climate (EPIC) and the Agricultural Policy/Environmental eXtender (APEX) are continuous models developed for evaluating the environmental effects of agricultural management. Traditionally, these models have simulated soil water percolation processes using a tipping-bucket approach, with the rate of flow limited by the saturated hydraulic conductivity. This simple approach often leads to inaccuracy in simulating elevated soil water conditions where soil water content (SWC) levels may remain above field capacity under prolonged wet weather periods or limited drainage. To overcome this deficiency, a new sub-model, the variable saturation hydraulic conductivity (VSHC) method, was developed for simulating soil water percolation processes using a nonlinear equation to estimate the effective hydraulic conductivity as a function of the SWC and soil properties. The VSHC method was evaluated at three sites in the United States and two sites in Europe. In addition, a numerical solution of the Richards equation was used as a benchmark for SWC comparison. Results show that the VSHC method substantially improves the accuracy of the SWC simulation in long-term simulations, particularly during wet periods. At the watershed scale, results on the Riesel Y2 watershed indicate that the VSHC method enhances model performance in the high-flow regime of channel peak flows because of the improved estimation of SWC, which implies that the improved SWC simulation at the field scale is beneficial to hydrologic modeling at the watershed scale. |
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2018-09-07 |
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English |
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ISSN |
1539-1663 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
5208 |
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Author |
Tomozeiu, R.; Pasqui, M.; Quaresima, S. |
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Title |
Future changes of air temperature over Italian agricultural areas: a statistical downscaling technique applied to 2021–2050 and 2071–2100 periods |
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Journal Article |
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Year |
2017 |
Publication |
Meteorology and Atmospheric Physics |
Abbreviated Journal |
Meteorology and Atmospheric Physics |
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in press |
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Abstract |
Climate change scenarios of seasonal minimum and maximum temperature over different Italian agricultural areas, during the periods 2021–2050 and 2071–2100 against 1961–1990, are assessed. The areas are those selected in the framework of the Agroscenari project and are represented by: Padano–Veneta plain, Marche, Beneventano, Destra Sele, Oristano, Puglia and Sicilia, all areas of prominent agricultural vocation with excellence productions. A statistical downscaling technique applied to ENSEMBLES global climate simulations, emission scenario A1B, is used to achieve this objective. The statistical scheme consists of a multivariate regression based on Canonical Correlation Analysis. The scheme is constructed using large-scale fields derived from ECMWF reanalysis and seasonal mean minimum, maximum temperature derived from national observed daily gridded data that cover 1959–2008 period. Once the most skillful model has been selected for each season and variable, this is then applied to GCMs of ENSEMBLES runs. The statistical downscaling method developed reveals good skill over the case studies of the present work, underlying the possibility to apply the scheme over whole Italian peninsula. In addition, the results emphasize that the temperature at 850 hPa is the best predictor for surface air temperature. The future projections show that an increase could be expected to occur under A1B scenario conditions in all seasons, both in minimum and maximum temperatures. The projected increases are about 2 °C during 2021–2050 and between 2.5 and 4.5 °C during 2071–2100, respect to 1961–1990. The spatial distribution of warming is projected to be quite uniform over the territory to the end of the century, while some spatial differences are noted over 2021–2050 period. For example, the increase in minimum temperature is projected to be slightly higher in areas from northern and central part than those situated in the southern part of Italian peninsula, during 2021–2050 period. The peak of changes is projected to appear during summer season, for both minimum and maximum temperature. The probability density function tends to shift to warmer values during both periods, with increases more intense during summer and to the end of the century, when the lower tail is projected to shift up to 3 °C and the upper tail up to 6 °C. All these projected changes have important impacts on viticulture, intensive fruit and tomatoes, some of the main agricultural systems analyzed in the Agroscenari project. |
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0177-7971 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4970 |
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Author |
Hoffmann, M.P.; Haakana, M.; Asseng, S.; Höhn, J.G.; Palosuo, T.; Ruiz-Ramos, M.; Fronzek, S.; Ewert, F.; Gaiser, T.; Kassie, B.T.; Paff, K.; Rezaei, E.E.; Rodríguez, A.; Semenov, M.; Srivastava, A.K.; Stratonovitch, P.; Tao, F.; Chen, Y.; Rötter, R.P. |
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Title |
How does inter-annual variability of attainable yield affect the magnitude of yield gaps for wheat and maize? An analysis at ten sites |
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Journal Article |
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Year |
2017 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
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in press |
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Highlights • The larger simulated attainable yield for a specific crop season, the larger the yield gap. • Average size of the yield gap is not affected by the inter-annual variability of attainable yield. • Technology levels (resource input and accessibility) determine average yield gap. • To reduce yield gaps in rainfed environments, farmers need to improve season-specific crop management. Abstract Provision of food security in the face of increasing global food demand requires narrowing of the gap between actual farmer’s yield and maximum attainable yield. So far, assessments of yield gaps have focused on average yield over 5–10 years, but yield gaps can vary substantially between crop seasons. In this study we hypothesized that climate-induced inter-annual yield variability and associated risk is a major barrier for farmers to invest, i.e. increase inputs to narrow the yield gap. We evaluated the importance of inter-annual attainable yield variability for the magnitude of the yield gap by utilizing data for wheat and maize at ten sites representing some major food production systems and a large range of climate and soil conditions across the world. Yield gaps were derived from the difference of simulated attainable yields and regional recorded farmer yields for 1981 to 2010. The size of the yield gap did not correlate with the amplitude of attainable yield variability at a site, but was rather associated with the level of available resources such as labor, fertilizer and plant protection inputs. For the sites in Africa, recorded yield reached only 20% of the attainable yield, while for European, Asian and North American sites it was 56–84%. Most sites showed that the higher the attainable yield of a specific season the larger was the yield gap. This significant relationship indicated that farmers were not able to take advantage of favorable seasonal weather conditions. To reduce yield gaps in the different environments, reliable seasonal weather forecasts would be required to allow farmers to manage each seasonal potential, i.e. overcoming season-specific yield limitations. |
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0308521x |
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CropM |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4985 |
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