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Author (up) Ben Touhami, H.; Bellocchi, G. url  doi
openurl 
  Title Bayesian calibration of the Pasture Simulation model (PaSim) to simulate European grasslands under water stress Type Journal Article
  Year 2015 Publication Ecological Informatics Abbreviated Journal Ecological Informatics  
  Volume 30 Issue Pages 356-364  
  Keywords Bayesian calibration framework; Grasslands; Pasture Simulation model; (PaSim); integrated assessment models; chain monte-carlo; climate-change; computation; impacts; vulnerability; likelihoods; france  
  Abstract As modeling becomes a more widespread practice in the agro-environmental sciences, scientists need reliable tools to calibrate models against ever more complex and detailed data. We present a generic Bayesian computation framework for grassland simulation, which enables parameter estimation in the Bayesian formalism by using Monte Carlo approaches. We outline the underlying rationale, discuss the computational issues, and provide results from an application of the Pasture Simulation model (PaSim) to three European grasslands. The framework was suited to investigate the challenging problem of calibrating complex biophysical models to data from altered scenarios generated by precipitation reduction (water stress conditions). It was used to infer the parameters of manipulated grassland systems and to assess the gain in uncertainty reduction by updating parameter distributions using measurements of the output variables.  
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  Corporate Author Thesis  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 1574-9541 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4697  
Permanent link to this record
 

 
Author (up) Bernabucci, U.; Biffani, S.; Buggiotti, L.; Vitali, A.; Lacetera, N.; Nardone, A. doi  openurl
  Title The effects of heat stress in Italian Holstein dairy cattle Type Journal Article
  Year 2014 Publication Journal of Dairy Science Abbreviated Journal J. Dairy Sci.  
  Volume 97 Issue 1 Pages 471-486  
  Keywords Animals; Breeding; Cattle; Dietary Fats/analysis; Dietary Proteins/analysis; Female; Genetic Variation; Heat Stress Disorders/*veterinary; *Hot Temperature; Humans; Humidity; *Lactation; Linear Models; Milk/chemistry; Parity; Phenotype; Weather; dairy cow; heritability; production trait; temperature-humidity index breaking point  
  Abstract The data set for this study comprised 1,488,474 test-day records for milk, fat, and protein yields and fat and protein percentages from 191,012 first-, second-, and third-parity Holstein cows from 484 farms. Data were collected from 2001 through 2007 and merged with meteorological data from 35 weather stations. A linear model (M1) was used to estimate the effects of the temperature-humidity index (THI) on production traits. Least squares means from M1 were used to detect the THI thresholds for milk production in all parities by using a 2-phase linear regression procedure (M2). A multiple-trait repeatability test-model (M3) was used to estimate variance components for all traits and a dummy regression variable (t) was defined to estimate the production decline caused by heat stress. Additionally, the estimated variance components and M3 were used to estimate traditional and heat-tolerance breeding values (estimated breeding values, EBV) for milk yield and protein percentages at parity 1. An analysis of data (M2) indicated that the daily THI at which milk production started to decline for the 3 parities and traits ranged from 65 to 76. These THI values can be achieved with different temperature/humidity combinations with a range of temperatures from 21 to 36°C and relative humidity values from 5 to 95%. The highest negative effect of THI was observed 4 d before test day over the 3 parities for all traits. The negative effect of THI on production traits indicates that first-parity cows are less sensitive to heat stress than multiparous cows. Over the parities, the general additive genetic variance decreased for protein content and increased for milk yield and fat and protein yield. Additive genetic variance for heat tolerance showed an increase from the first to third parity for milk, protein, and fat yield, and for protein percentage. Genetic correlations between general and heat stress effects were all unfavorable (from -0.24 to -0.56). Three EBV per trait were calculated for each cow and bull (traditional EBV, traditional EBV estimated with the inclusion of THI covariate effect, and heat tolerance EBV) and the rankings of EBV for 283 bulls born after 1985 with at least 50 daughters were compared. When THI was included in the model, the ranking for 17 and 32 bulls changed for milk yield and protein percentage, respectively. The heat tolerance genetic component is not negligible, suggesting that heat tolerance selection should be included in the selection objectives.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1525-3198 (Electronic) 0022-0302 (Linking) ISBN Medium Article  
  Area Expedition Conference  
  Notes LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4617  
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Author (up) Biewald, A.; Rolinski, S.; Lotze-Campen, H.; Schmitz, C.; Dietrich, J.P. url  doi
openurl 
  Title Valuing the impact of trade on local blue water Type Journal Article
  Year 2014 Publication Ecological Economics Abbreviated Journal Ecol. Econ.  
  Volume 101 Issue Pages 43-53  
  Keywords virtual water; blue and green water; water scarcity; agricultural trade; global vegetation model; virtual water; crop trade; resources; scarcity; food; footprints; products; flows; green  
  Abstract International trade of agricultural goods impacts local water scarcity. By quantifying the effect of trade on crop production on grid-cell level and combining it with cell- and crop-specific virtual water contents, we are able to determine green and blue water consumption and savings. Connecting the information on trade-related blue water usage to water shadow prices gives us the possibility to value the impact of international food crop trade on local blue water resources. To determine the trade-related value of the blue water usage, we employ two models: first, an economic land- and water-use model, simulating agricultural trade, production and water-shadow prices and second, a global vegetation and agricultural model, modeling the blue and green virtual water content of the traded crops. Our study found that globally, the international trade of food crops saves blue water worth 2.4 billion US$. This net saving occurs despite the fact that Europe exports virtual blue water in food crops worth 3.1 billion US$. Countries in the Middle East and South Asia profit from trade by importing water intensive crops, countries in Southern Europe on the other hand export water intensive agricultural goods from water scarce sites, deteriorating local water scarcity. (C) 2014 Elsevier B.V. All rights reserved.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0921-8009 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, TradeM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4512  
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Author (up) Bindi, M.; Palosuo, T.; Trnka, M.; Semenov, M.A. url  doi
openurl 
  Title Modelling climate change impacts on crop production for food security INTRODUCTION Type Journal Article
  Year 2015 Publication Climate Research Abbreviated Journal Clim. Res.  
  Volume 65 Issue Pages 3-5  
  Keywords Crop production; Climate change impact and adaptation assessments; Upscaling; Model ensembles  
  Abstract Process-based crop models that synthesise the latest scientific understanding of biophysical processes are currently the primary scientific tools available to assess potential impacts of climate change on crop production. Important obstacles are still present, however, and must be overcome for improving crop modelling application in integrated assessments of risk, of sustainability and of crop-production resilience in the face of climate change (e.g. uncertainty analysis, model integration, etc.). The research networks MACSUR and AGMIP organised the CropM International Symposium and Workshop in Oslo, on 10-12 February 2014, and present this CR Special, discussing the state-of-the-art-as well as future perspectives-of crop modelling applications in climate change risk assessment, including the challenges of integrated assessments for the agricultural sector.  
  Address 2016-10-31  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0936-577x ISBN Medium Editorial Material  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4785  
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Author (up) Bodirsky, B.L.; Popp, A.; Lotze-Campen, H.; Dietrich, J.P.; Rolinski, S.; Weindl, I.; Schmitz, C.; Müller, C.; Bonsch, M.; Humpenöder, F.; Biewald, A.; Stevanovic, M. url  doi
openurl 
  Title Reactive nitrogen requirements to feed the world in 2050 and potential to mitigate nitrogen pollution Type Journal Article
  Year 2014 Publication Nature Communications Abbreviated Journal Nat. Comm.  
  Volume 5 Issue Pages 3858  
  Keywords Animals; Crops, Agricultural/metabolism/*supply & distribution; Environmental Pollution/*prevention & control; *Food Supply; Humans; Models, Theoretical; Nitrogen Fixation; *Population Growth; Reactive Nitrogen Species/*supply & distribution  
  Abstract Reactive nitrogen (Nr) is an indispensable nutrient for agricultural production and human alimentation. Simultaneously, agriculture is the largest contributor to Nr pollution, causing severe damages to human health and ecosystem services. The trade-off between food availability and Nr pollution can be attenuated by several key mitigation options, including Nr efficiency improvements in crop and animal production systems, food waste reduction in households and lower consumption of Nr-intensive animal products. However, their quantitative mitigation potential remains unclear, especially under the added pressure of population growth and changes in food consumption. Here we show by model simulations, that under baseline conditions, Nr pollution in 2050 can be expected to rise to 102-156% of the 2010 value. Only under ambitious mitigation, does pollution possibly decrease to 36-76% of the 2010 value. Air, water and atmospheric Nr pollution go far beyond critical environmental thresholds without mitigation actions. Even under ambitious mitigation, the risk remains that thresholds are exceeded.  
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  Series Volume Series Issue Edition  
  ISSN 2041-1723 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4513  
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