Records |
Author |
Höhn, J.; Rötter, R.P. |
Title |
Impact of global warming on European cereal production |
Type |
Journal Article |
Year |
2014 |
Publication |
CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources |
Abbreviated Journal |
CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources |
Volume |
9 |
Issue |
022 |
Pages |
1-15 |
Keywords |
Climate change; Food security; Uncertainty; Wheat; Maize; Barley |
Abstract |
This review examines relevant impact assessments identified by a literature search from 1991to date. A bibliographic search was applied to the CAB Abstracts database with a given searchstring. Resultant papers were checked for relevance, based on expert judgment. This yielded 91 papers, which were subjected to further analysis. Firstly, publication intensity over time and distribution by geographic location and cereal crop were examined. Next, for a given crop, the assessments and their outcomes were grouped by type and number of the change variables considered – that is, effects of climate change only, elevated CO 2 and technological progress(improved breeds, management). Finally, separately for individual countries/subregions and Europe as a whole, we examined whether and to what extent study results have changed over time, for example become more positive/negative. Based on our sample, we found that publication intensity increased exponentially during thelast 4 years, the majority of studies are Europe-wide, but some concentrated on a few countries(Italy, Spain and UK), whereby studies on wheat are clearly most popular. Taking the factor of technological progress into account has an overruling influence on results. Finally, over time, projected yield impacts have become more negative. This is in line with finding from global analyses, as reflected by the most recent comparison of agricultural impact chapters, of the 4thand 5th Assessment Reports of Intergovernmental Panel on Climate Change, Working Group II.In the future, there is particular need to consider impacts under various incremental and transformational adaptation measures in more depth (e.g. their interconnections across scales)and with more breadth (e.g. anticipated new breeds). Follow-up reviews should also examine how projected impacts are changing with the new climate scenario data sets (CMIP5) and with improved impact models and assessment approaches. |
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Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1749-8848 |
ISBN |
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Article |
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Expedition |
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Conference |
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Notes |
CropM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4524 |
Permanent link to this record |
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Author |
Minet, J.; Laloy, E.; Tychon, B.; François, L. |
Title |
Bayesian inversions of a dynamic vegetation model at four European grassland sites |
Type |
Journal Article |
Year |
2015 |
Publication |
Biogeosciences |
Abbreviated Journal |
Biogeosciences |
Volume |
12 |
Issue |
9 |
Pages |
2809-2829 |
Keywords |
eddy-covariance data; terrestrial ecosystem model; bioclimatic affinity; groups; monte-carlo-simulation; dry-matter content; leaf-area; climate-change; stomatal conductance; parameter-estimation; plant |
Abstract |
Eddy covariance data from four European grassland sites are used to probabilistically invert the CARAIB (CARbon Assimilation In the Biosphere) dynamic vegetation model (DVM) with 10 unknown parameters, using the DREAM((ZS)) (DiffeRential Evolution Adaptive Metropolis) Markov chain Monte Carlo (MCMC) sampler. We focus on comparing model inversions, considering both homoscedastic and heteroscedastic eddy covariance residual errors, with variances either fixed a priori or jointly inferred together with the model parameters. Agreements between measured and simulated data during calibration are comparable with previous studies, with root mean square errors (RMSEs) of simulated daily gross primary productivity (GPP), ecosystem respiration (RECO) and evapotranspiration (ET) ranging from 1.73 to 2.19, 1.04 to 1.56 g C m(-2) day(-1) and 0.50 to 1.28 mm day(-1), respectively. For the calibration period, using a homoscedastic eddy covariance residual error model resulted in a better agreement between measured and modelled data than using a heteroscedastic residual error model. However, a model validation experiment showed that CARAIB models calibrated considering heteroscedastic residual errors perform better. Posterior parameter distributions derived from using a heteroscedastic model of the residuals thus appear to be more robust. This is the case even though the classical linear heteroscedastic error model assumed herein did not fully remove heteroscedasticity of the GPP residuals. Despite the fact that the calibrated model is generally capable of fitting the data within measurement errors, systematic bias in the model simulations are observed. These are likely due to model inadequacies such as shortcomings in the photosynthesis modelling. Besides the residual error treatment, differences between model parameter posterior distributions among the four grassland sites are also investigated. It is shown that the marginal distributions of the specific leaf area and characteristic mortality time parameters can be explained by site-specific ecophysiological characteristics. |
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English |
Summary Language |
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Series Editor |
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Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1726-4189 |
ISBN |
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Medium |
Article |
Area |
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Conference |
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Notes |
CropM LiveM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4571 |
Permanent link to this record |
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Author |
Park, S.K.; Sungmin, O.; Cassardo, C. |
Title |
Soil temperature response in Korea to a changing climate using a land surface model |
Type |
Journal Article |
Year |
2017 |
Publication |
Asia-Pacific Journal of Atmospheric Sciences |
Abbreviated Journal |
Asia-Pacific Journal of Atmospheric Sciences |
Volume |
53 |
Issue |
4 |
Pages |
457-470 |
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 |
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. |
Address |
2017-12-21 |
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Thesis |
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Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1976-7633 |
ISBN |
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Area |
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Conference |
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Notes |
CropM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
5182 |
Permanent link to this record |
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Author |
Cassardo, C.; Andreoli, V. |
Title |
On the Representativeness of UTOPIA Land Surface Model for Creating a Database of Surface Layer, Vegetation and Soil Variables in Piedmont Vineyards, Italy |
Type |
Journal Article |
Year |
2019 |
Publication |
Applied Sciences-Basel |
Abbreviated Journal |
Applied Sciences-Basel |
Volume |
9 |
Issue |
18 |
Pages |
3880 |
Keywords |
land-surface; UTOPIA; NOAH; GLDAS; micrometeorology; exchanges; processes; vineyards; cabernet-sauvignon; climate-change; wine color; temperature; parameterization; simulations; circulation; balances; moisture; sunlight |
Abstract |
The main aim of the paper is to show how, and how many, simulations carried out using the Land Surface Model UTOPIA (University of TOrino model of land Process Interaction with Atmosphere) are representative of the micro-meteorological conditions and exchange processes at the atmosphere/biosphere interface, with a particular focus on heat and hydrologic transfers, over an area of the Piemonte (Piedmont) region, NW Italy, which is characterized by the presence of many vineyards. Another equally important aim is to understand how much the quality of the simulation outputs was influenced by the input data, whose measurements are often unavailable for long periods over country areas at an hourly basis. Three types of forcing data were used: observations from an experimental campaign carried out during the 2008, 2009, and 2010 vegetative seasons in three vineyards, and values extracted from the freely available Global Land Data Assimilation System (GLDAS, versions 2.0 and 2.1). Since GLDAS also contains the outputs of the simulations performed using the Land Surface Model NOAH, an additional intercomparison between the two models, UTOPIA and NOAH, both driven by the same GLDAS datasets, was performed. The intercomparisons were performed on the following micro-meteorological variables: net radiation, sensible and latent turbulent heat fluxes, and temperature and humidity of soil. The results of this study indicate that the methodology of employing land surface models driven by a gridded database to evaluate variables of micro-meteorological and agronomic interest in the absence of observations is suitable and gives satisfactory results, with uncertainties comparable to measurement errors, thus, allowing us to also evaluate some time trends. The comparison between GLDAS2.0 and GLDAS2.1 indicates that the latter generally produces simulation outputs more similar to the observations than the former, using both UTOPIA and NOAH models. |
Address |
2020-02-14 |
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English |
Summary Language |
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Notes |
CropM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
5228 |
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Author |
Milford, A.B.; Le Mouel, C.; Bodirsky, B.L.; Rolinski, S. |
Title |
Drivers of meat consumption |
Type |
Journal Article |
Year |
2019 |
Publication |
Appetite |
Abbreviated Journal |
Appetite |
Volume |
141 |
Issue |
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Pages |
Unsp 104313 |
Keywords |
Meat consumption; Nutrition transition; Climate change mitigation; Cross-country analysis; nutrition transition; food; sustainability; globalization; countries; future; health; income; price |
Abstract |
Increasing global levels of meat consumption are a threat to the environment and to human health. To identify measures that may change consumption patterns towards more plant-based foods, it is necessary to improve our understanding of the causes behind the demand for meat. In this paper we use data from 137 different countries to identify and assess factors that influence meat consumption at the national level using a cross-country multivariate regression analysis. We specify either total meat or ruminant meat as the dependent variable and we consider a broad range of potential drivers of meat consumption. The combination of explanatory variables we use is new for this type of analysis. In addition, we estimate the relative importance of the different drivers. We find that income per capita followed by rate of urbanisation are the two most important drivers of total meat consumption per capita. Income per capita and natural endowment factors are major drivers of ruminant meat consumption per capita. Other drivers are Western culture, Muslim religion, female labour participation, economic and social globalisation and meat prices. The main identified drivers of meat demand are difficult to influence through direct policy intervention. Thus, acting indirectly on consumers’ preferences and consumption habits (for instance through information, education policy and increased availability of ready-made plant based products) could be of key importance for mitigating the rise of meat consumption per capita all over the world. |
Address |
2020-02-14 |
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Place of Publication |
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English |
Summary Language |
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Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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ISSN |
0195-6663 |
ISBN |
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Article |
Area |
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Notes |
TradeM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
5224 |
Permanent link to this record |