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Author |
Park, S.K.; Sungmin, O.; Cassardo, C. |
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Title |
Soil temperature response in Korea to a changing climate using a land surface model |
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Journal Article |
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Year |
2017 |
Publication |
Asia-Pacific Journal of Atmospheric Sciences |
Abbreviated Journal |
Asia-Pacific Journal of Atmospheric Sciences |
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Volume |
53 |
Issue |
4 |
Pages |
457-470 |
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Keywords  |
Land surface process; soil temperature; climate change; soil-vegetation-atmosphere transfer (SVAT) scheme; University of TOrino model of land Process Interaction with Atmosphere (UTOPIA); REGIONAL CLIMATE; SNOW COVER; WATER-RESOURCES; SOCIOECONOMIC SCENARIOS; QUANTITATIVE-ANALYSIS; MESOSCALE MODEL; SRES EMISSIONS; FUTURE CLIMATE; CHANGE IMPACTS; SOUTH-AMERICA |
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Abstract |
The land surface processes play an important role in weather and climate systems through its regulation of radiation, heat, water and momentum fluxes. Soil temperature (ST) is one of the most important parameters in the land surface processes; however, there are few extensive measurements of ST with a long time series in the world. According to the CLImatology of Parameters at the Surface (CLIPS) methodology, the output of a trusted Soil-Vegetation- Atmosphere Transfer (SVAT) scheme can be utilized instead of observations to investigate the regional climate of interest. In this study, ST in South Korea is estimated in a view of future climate using the output from a trusted SVAT scheme – the University of TOrino model of land Process Interaction with Atmosphere (UTOPIA), which is driven by a regional climate model. Here characteristic changes in ST are analyzed under the IPCC A2 future climate for 2046-2055 and 2091-2100, and are compared with those under the reference climate for 1996-2005. The UTOPIA results were validated using the observed ST in the reference climate, and the model proved to produce reasonable ST in South Korea. The UTOPIA simulations indicate that ST increases due to environmental change, especially in air temperature (AT), in the future climate. The increment of ST is proportional to that of AT except for winter. In wintertime, the ST variations are different from region to region mainly due to variations in snow cover, which keeps ST from significant changes by the climate change. |
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2017-12-21 |
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1976-7633 |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
5182 |
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Author |
Bannink, A.; van Lingen, H.J.; Ellis, J.L.; France, J.; Dijkstra, J. |
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Title |
The contribution of mathematical modeling to understanding dynamic aspects of rumen metabolism |
Type |
Journal Article |
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Year |
2016 |
Publication |
Frontiers in Microbiology |
Abbreviated Journal |
Frontiers in Microbiology |
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Volume |
7 |
Issue |
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Pages |
1820 |
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Keywords |
lactating dairy-cows; milk urea concentration; fatty-acid production; ruminal fermentation; mechanistic model; holstein cows; beef-cattle; stoichiometric parameters; methane production; feeding frequency |
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All mechanistic rumen models cover the main drivers of variation in rumen function, which are feed intake, the differences between feedstuffs and feeds in their intrinsic rumen degradation characteristics, and fractional outflow rate of fluid and particulate matter. Dynamic modeling approaches are best suited to the prediction of more nuanced responses in rumen metabolism, and represent the dynamics of the interactions between substrates and micro-organisms and inter-microbial interactions. The concepts of dynamics are discussed for the case of rumen starch digestion as influenced by starch intake rate and frequency of feed intake, and for the case of fermentation of fiber in the large intestine. Adding representations of new functional classes of micro-organisms (i.e., with new characteristics from the perspective of whole rumen function) in rumen models only delivers new insights if complemented by the dynamics of their interactions with other functional classes. Rumen fermentation conditions have to be represented due to their profound impact on the dynamics of substrate degradation and microbial metabolism. Although the importance of rumen pH is generally acknowledged, more emphasis is needed on predicting its variation as well as variation in the processes that underlie rumen fluid dynamics. The rumen wall has an important role in adapting to rapid changes in the rumen environment, clearing of volatile fatty acids (VFA), and maintaining rumen pH within limits. Dynamics of rumen wall epithelia and their role in VFA absorption needs to be better represented in models that aim to predict rumen responses across nutritional or physiological states. For a detailed prediction of rumen N balance there is merit in a dynamic modeling approach compared to the static approaches adopted in current protein evaluation systems. Improvement is needed on previous attempts to predict rumen VFA profiles, and this should be pursued by introducing factors that relate more to microbial metabolism. For rumen model construction, data on rumen microbiomes are preferably coupled with knowledge consolidated in rumen models instead of relying on correlations with rather general aspects of treatment or animal. This helps to prevent the disregard of basic principles and underlying mechanisms of whole rumen function. |
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2017-01-06 |
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1664-302x |
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LiveM, ft_MACSUR |
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no |
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Call Number |
MA @ admin @ |
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4932 |
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Author |
Ventrella, D.; Giglio, L.; Charfeddine, M.; Dalla Marta, A. |
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Title |
Consumptive use of green and blue water for winter durum wheat cultivated in Southern Italy |
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Journal Article |
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Year |
2015 |
Publication |
Italian Journal of Agrometeorology |
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Italian Journal of Agrometeorology |
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20 |
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1 |
Pages |
33-44 |
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Keywords |
irrigation; water productivity; model simulation; climate change; climate-change scenarios; air co2 enrichment; impact; footprint; irrigation; simulation; yield; agriculture; variability; resources |
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Abstract |
In this study at the regional scale, the model DSSAT CERES-Wheat was applied in order to simulate the cultivation of winter durum wheat (WW) and to estimate the green water (GW) and the blue water (BW) through a dual-step approach (with and without supplemental irrigation). The model simulation covered a period of 30 years for three scenarios including a reference period and two future scenarios based on forecasted global average temperature increase of 2 and 5 degrees C. The GW and BW contribution for evapo transpiration requirement is presented and analyzed on a distributed scale related to the Puglia region (Southern Italy) characterized by high evaporative demand of the atmosphere. The GW component was dominant compared to BW, covering almost 90% of the ETc of WW Under a Baseline scenario the weight BW was 11%, slightly increased in the future scenarios. GW appeared dependent on the spatial and temporal distribution of rainfall during the crop cycle, and to the hydraulic characteristics of soil for each calculation unit. After considering the effects of climate change on irrigation requirement of WW we carried out an example of analysis in order to verify the economic benefit of supplemental irrigation for WW cultivation. The probability that irrigation generates a negative or zero income ranged between 55 and 60% and climate change did not impact the profitability of irrigation for WW as simulated for the economic and agro-pedoclimatic conditions of Puglia region considered in this study. |
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CropM, ft_macsur |
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MA @ admin @ |
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4653 |
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Schönhart, M.; Schauppenlehner, T.; Kuttner, M.; Kirchner, M.; Schmid, E. |
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Climate change impacts on farm production, landscape appearance, and the environment: Policy scenario results from an integrated field-farm-landscape model in Austria |
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Journal Article |
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Year |
2016 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
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Volume |
145 |
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Pages |
39-50 |
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Keywords |
Integrated land use modeling; Climate change impacts; Mitigation; Adaptation; Field-farm-landscape; Environment; agricultural landscapes; land-use; netherlands; adaptation; indicators; management; responses |
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Abstract |
Climate change is among the major drivers of agricultural land use change and demands autonomous farm adaptation as well as public mitigation and adaptation policies. In this article, we present an integrated land use model (ILM) mainly combining a bio-physical model and a bio-economic farm model at field, farm and landscape levels. The ILM is applied to a cropland dominated landscape in Austria to analyze impacts of climate change and mitigation and adaptation policy scenarios on farm production as well as on the abiotic environment and biotic environment. Changes in aggregated total farm gross margins from three climate change scenarios for 2040 range between + 1% and + 5% without policy intervention” and compared to a reference situation under the current climate. Changes in aggregated gross margins are even higher if adaptation policies are in place. However, increasing productivity from climate change leads to deteriorating environmental conditions such as declining plant species richness and landscape appearance. It has to be balanced by mitigation and adaptation policies taking into account effects from the considerable spatial heterogeneity such as revealed by the ILM. (C) 2016 Elsevier Ltd. All rights reserved. |
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0308-521x |
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CropM, TradeM, ft_macsur |
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MA @ admin @ |
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4767 |
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Kanellopoulos, A.; Reidsma, P.; Wolf, J.; van Ittersum, M.K. |
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Assessing climate change and associated socio-economic scenarios for arable farming in the Netherlands: An application of benchmarking and bio-economic farm modelling |
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Journal Article |
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2014 |
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European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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52 |
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69-80 |
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Keywords |
integrated assessment; data envelopment analysis; farm adaptation; farm model; technical efficiency; agricultural land-use; integrated assessment; european-community; future; crop; efficiency; impacts; systems |
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Future farming systems are challenged to adapt to the changing socio-economic and bio-physical environment in order to remain competitive and to meet the increasing requirements for food and fibres. The scientific challenge is to evaluate the consequences of predefined scenarios, identify current “best” practices and explore future adaptation strategies at farm level. The objective of this article is to assess the impact of different climate change and socio-economic scenarios on arable farming systems in Flevoland (the Netherlands) and to explore possible adaptation strategies. Data Envelopment Analysis was used to identify these current “best” practices while bio-economic modelling was used to calculate a number of important economic and environmental indicators in scenarios for 2050. Relative differences between yields with and without climate change and technological change were simulated with a crop bio-physical model and used as a correction factors for the observed crop yields of current “best” practices. We demonstrated the capacity of the proposed methodology to explore multiple scenarios by analysing the importance of drivers of change, while accounting for variation between individual farms. It was found that farmers in Flevoland are in general technically efficient and a substantial share of the arable land is currently under profit maximization. We found that climate change increased productivity in all tested scenarios. However, the effects of different socio-economic scenarios (globalized and regionalized economies) on the economic and environmental performance of the farms were variable. Scenarios of a globalized economy where the prices of outputs were simulated to increase substantially might result in increased average gross margin and lower average (per ha) applications of crop protection and fertilizers. However, the effects might differ between different farm types. It was found that, the abolishment of sugar beet quota and changes of future prices of agricultural inputs and outputs in such socio-economic scenario (i.e. globalized economy) caused a decrease in gross margins of smaller (in terms of economic size) farms, while gross margin of larger farms increased. In scenarios where more regionalized economies and a moderate climate change are assumed, the future price ratios between inputs and outputs are shown to be the key factors for the viability of arable farms in our simulations. (C) 2013 Elsevier B.V. All rights reserved. |
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1161-0301 |
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CropM |
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MA @ admin @ |
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4526 |
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