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Author |
Ghaley, B.B.; Porter, J.R. |
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Title |
Ecosystem function and service quantification and valuation in a conventional winter wheat production system with the DAISY model in Denmark |
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Journal Article |
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Year |
2014 |
Publication |
Ecosystem Services |
Abbreviated Journal |
Ecosystem Services |
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Volume |
10 |
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Pages |
79-83 |
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Keywords  |
soil organic matter; winter wheat production; informed decision-making; ecosystem function; ecosystem service; soil carbon sequestration; organic-matter dynamics; mitigate climate-change; calibration; validation; land |
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Abstract |
With inevitable link between ecosystem function (EF), ecosystem services (ES) and agricultural productivity, there is a need for quantification and valuation of EF and ES in agro-ecosystems. Management practices have significant effects on soil organic matter (SOM), affecting productivity, EF and ES provision. The objective was to quantify two EF: soil water storage and nitrogen mineralization and three ES: food and fodder production and carbon sequestration, in a conventional winter wheat production system at 2.6% SOM compared to 50% lower (1.3%) and 50% higher (3.9%) SOM in Denmark by DAISY model. At 2.6% SOM, the food and fodder production was 649 and 6.86 t ha(-1) year(-1) respectively whereas carbon sequestration and soil water storage was 9.73 t ha(-1) year and 684 mm ha(-1) year(-1) respectively and nitrogen mineralisation was 83.58 kg ha(-1) year(-1), AL 2.6% SOM, the two EF and three ES values were US$ 177 and US$ 2542 ha(-1) year respectively equivalent to US$ 96 and US$1370 million year(-1) respectively in Denmark. The EF and ES quantities and values were positively correlated with SOM content. Hence, the quantification and valuation of EF and ES provides an empirical tool for optimising the Er. and ES provision for agricultural productivity. (C) 2014 Elsevier B.V. All rights reserved |
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2212-0416 |
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CropM |
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MA @ admin @ |
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4625 |
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Author |
Walkiewicz, A.; Bulak, P.; Brzezinska, M.; Wnuk, E.; Bieganowski, A. |
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Title |
Methane oxidation in heavy metal contaminated Mollic Gleysol under oxic and hypoxic conditions |
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Journal Article |
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Year |
2016 |
Publication |
Environmental Pollution |
Abbreviated Journal |
Environ. Pollut. |
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213 |
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403-411 |
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Keywords |
Soil; Methane oxidation; CH4; Heavy metals; Oxygen status; Dehydrogenase; activity; methanotrophic bacteria; dehydrogenase-activity; potential activity; forest soils; responses; landfill; community; ch4; co2; bioremediation |
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Abstract |
Soils are the largest terrestrial sink for methane (CH4). However, heavy metals may exert toxicity to soil microorganisms, including methanotrophic bacteria. We tested the effect of lead (Pb), zinc (Zn) and nickel (Ni) on CH4 oxidation (1% v/v) and dehydrogenase activity, an index of the activity of the total soil microbial community in Mollic Gleysol soil in oxic and hypoxic conditions (oxia and hypoxia, 20% and 10% v/v O2, respectively). Metals were added in doses corresponding to the amounts permitted of Pb, Zn, Ni in agricultural soils (60, 120, 35 mg kg(-1), respectively), and half and double of these doses. Relatively low metal contents and O2 status reflect the conditions of most agricultural soils of temperate regions. Methane consumption showed high tolerance to heavy metals. The effect of O2 status was stronger than that of metals. CH4 consumption was enhanced under hypoxia, where both the start and the completion of the control and contaminated treatment were faster than under oxic conditions. Dehydrogenase activity, showed higher sensitivity to the contamination (except for low Ni dose), with a stronger effect of heavy metals, than that of the O2 status. |
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Newsletter July 2016 |
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0269-7491 |
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CropM, ft_macsur |
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MA @ admin @ |
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4771 |
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Vilvert, E.; Lana, M.; Zander, P.; Sieber, S. |
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Title |
Multi-model approach for assessing the sunflower food value chain in Tanzania |
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Journal Article |
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Year |
2018 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
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159 |
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103-110 |
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Keywords |
Sunflower; Food value chain; Modelling; Tanzania; Food security; Systems Simulation; Crop Model; Agricultural Systems; Farming Systems; Yield Response; Land-Use; Water; Aquacrop; Security; Stics |
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Sunflower is one of the major oilseeds produced in Tanzania, but due to insufficient domestic production more than half of the country’s demand is imported. The improvement of the sunflower food value chain (FVC) understanding is important to ensure an increase in the production, availability, and quality of edible oil. In order to analyse causes and propose solutions to increase the production of sunflower oil, a conceptual framework that proposes the combined use of different models to provide insights about the sunflower FVC was developed. This research focus on the identification of agricultural models that can provide a better understanding of the sunflower FVC in Tanzania, especially within the context of food security improvement. A FVC scheme was designed considering the main steps of sunflower production. Thereafter, relevant models were selected and placed along each step of the FVC. As result, the sunflower FVC model in Tanzania is organized in five steps, namely (1) natural resources; (2) crop production; (3) oil processing; (4) trade; and (5) consumption. Step 1 uses environmental indicators to analyse soil parameters on soil-water models (SWAT, LPJmL, APSIM or CroSyst), with outputs providing data for step 2 of the FVC. In the production step, data from step 1, together with other inputs, is used to run crop models (DSSAT, HERMES, MONICA, STICS, EPIC or AquaCrop) that analyse the impact on sunflower yields. Thereafter, outputs from crop models serve as input for bio-economic farm models (FSSIM or MODAM) to estimate production costs and farm income by optimizing resource allocation planning for step 2. In addition, outputs from crop models are used as inputs for macro-economic models (GTAP, MAGNET or MagPie) by adjusting supply functions and environmental impacts within steps 3, 4, and 5. These models simulate supply and demand, including the processing of products to determine prices and trade volumes at market equilibrium. In turn, these data is used by bio-economic farm models to assess sunflower returns for different farm types and agro-environmental conditions. Due to the large variety of models, it is possible to assess significant parts of the FVC, reducing the need to make assumptions, while improving the understanding of the FVC. |
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2018-01-25 |
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0308-521x |
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CropM, TradeM, ft_macsur |
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MA @ admin @ |
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5187 |
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Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Popp, A.; Müller, C. |
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Title |
Forecasting technological change in agriculture—An endogenous implementation in a global land use model |
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Journal Article |
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2014 |
Publication |
Technological Forecasting and Social Change |
Abbreviated Journal |
Technological Forecasting and Social Change |
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81 |
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236-249 |
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Keywords |
Technological change; Land use; Agricultural productivity; Land use intensity; Research and development; land-use; research expenditures; productivity growth; impact; deforestation; forest; yield; Business & Economics; Public Administration |
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► Endogenous technological change in an economic land use model ► Estimation of yield elasticity with respect to investments in technological change ► Projections of future agricultural productivity rates ► Validation with observed data and historic trends ► Trade-off between required technological change and forest protection objectives Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 0.29 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (“Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995–2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change. |
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0040-1625 |
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MA @ admin @ |
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4518 |
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Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Popp, A.; Muller, C. |
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Title |
Forecasting technological change in agriculture-An endogenous implementation in a global, and use model |
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Journal Article |
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Year |
2014 |
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Technological Forecasting and Social Change |
Abbreviated Journal |
Technological Forecasting and Social Change |
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81 |
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236-249 |
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Keywords |
Technological change; Land use; Agricultural productivity; Land use; intensity; Research and development; land-use; research expenditures; productivity growth; impact; deforestation; forest; yield; Business & Economics; Public Administration |
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Abstract |
Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 029 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (”Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995-2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change. (C) 2013 Elsevier Inc. All rights reserved. |
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2016-10-31 |
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0040-1625 |
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CropM |
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MA @ admin @ |
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4789 |
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