toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author Hutchings, N. url  openurl
  Title (up) A comparison of farm-scale models to estimate greenhouse gas emissions from dairy farms in Europe Type
  Year 2015 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 5 Issue Pages Sp5-26  
  Keywords  
  Abstract Farm-scale models quantify the cycling of nitrogen (N) and carbon (C) so are powerful tools for assessing the impact of management-related decisions on greenhouse gas (GHG) emissions, especially on dairy cattle farms, where the internal cycling is particularly important. Farm models range in focus (economic, environmental) and the detail with which they represent C and N cycling. We compared four models from this range in terms of on-farm production and emissions of GHGs, using standardized scenarios. The models compared were SFarMod, DairyWise, FarmAC and HolosNor. The scenarios compared were based on two soil types (sandy clay versus heavy clay), two roughage systems (grass only versus grass and maize), and two climate types (Eindhoven versus Santander). Standard farm characteristics were; area (50 ha), milk yield (7000 kg/head/year), fertiliser (275 kg N and 150 kg N/ha/year for grass and maize, respectively). Potential yields for grass 10t dry matter (DM)/ha/year in both areas, maize 14 t DM/ha/ year in Eindhoven and 18t DM/ha/ year in Santander. The import of animal feed and the export/import manure and forages was minimized. Similar total farm direct GHG emissions for all models disguised a variation between models in the contribution of the different on-farm sources. There were large differences between models in the predictions of indirect GHG emission from nitrate leaching. Results could be explained by differences between models in the assumptions made and detail with which underlying processes were represented. We conclude that the choice of an appropriate farm model is highly dependent upon the role it should play and the context within which it will operate, so the current diversity of farm models will continue into the future. No Label  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK  
  Notes Approved no  
  Call Number MA @ admin @ Serial 2141  
Permanent link to this record
 

 
Author Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F. url  doi
openurl 
  Title (up) A comparison of within-season yield prediction algorithms based on crop model behaviour analysis Type Journal Article
  Year 2015 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology  
  Volume 204 Issue Pages 10-21  
  Keywords stics crop model; climate variability; lars-wg; yield prediction; log-normal distribution; convergence in law theorem; central limit theorem; weather generator; nitrogen balances; generic model; wheat; simulation; climate; stics; variability; skewness; efficiency  
  Abstract The development of methodologies for predicting crop yield, in real-time and in response to different agro-climatic conditions, could help to improve the farm management decision process by providing an analysis of expected yields in relation to the costs of investment in particular practices. Based on the use of crop models, this paper compares the ability of two methodologies to predict wheat yield (Triticum aestivum L.), one based on stochastically generated climatic data and the other on mean climate data. It was shown that the numerical experimental yield distribution could be considered as a log-normal distribution. This function is representative of the overall model behaviour. The lack of statistical differences between the numerical realisations and the logistic curve showed in turn that the Generalised Central Limit Theorem (GCLT) was applicable to our case study. In addition, the predictions obtained using both climatic inputs were found to be similar at the inter and intra-annual time-steps, with the root mean square and normalised deviation values below an acceptable level of 10% in 90% of the climatic situations. The predictive observed lead-times were also similar for both approaches. Given (i) the mathematical formulation of crop models, (ii) the applicability of the CLT and GLTC to the climatic inputs and model outputs, respectively, and (iii) the equivalence of the predictive abilities, it could be concluded that the two methodologies were equally valid in terms of yield prediction. These observations indicated that the Convergence in Law Theorem was applicable in this case study. For purely predictive purposes, the findings favoured an algorithm based on a mean climate approach, which needed far less time (by 300-fold) to run and converge on same predictive lead time than the stochastic approach. (C) 2015 Elsevier B.V. All rights reserved.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0168-1923 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4647  
Permanent link to this record
 

 
Author Pirttioja, N.; Carter, T.R.; & 47 al.; Rötter, R.P. url  openurl
  Title (up) A crop model ensemble analysis of temperature and precipitation effects on wheat yield across a European transect using impact response surfaces Type Report
  Year 2015 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 6 Issue Pages D-C4.4.3  
  Keywords  
  Abstract Impact response surfaces (IRSs) of spring and winter wheat yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect in Europe. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of 1981–2010 baseline weather.In spite of large differences in simulated yield responses to both baseline and changed climate between models, sites, crops and years, several common messages emerged. Ensemble average yields decline with higher temperatures (3–7% per 1°C) and decreased precipitation  (3–9% per 10% decrease), but benefit from increased precipitation (0-8% per 10% increase). Yields are more sensitive to temperature than precipitation changes at the Finnish site while sensitivities are mixed at the German and Spanish sites. Precipitation effects diminish under higher temperature changes. Inter-model variability is highest for baseline climate at the Spanish site, but relatively insensitive to changed climate. Modelled responses diverge most at the Finnish and German sites for winter wheat under temperature change. The IRS pattern of yield reliability tracks average yield levels. Inter-annual yield variability is more sensitive to precipitation than temperature, except at the Spanish site for spring wheat.Optimal temperatures for present-day cultivars are close to the baseline under Finnish conditions but below the baseline at the German and Spanish sites. This suggests that adoption of later maturing cultivars with higher temperature requirements might already be advantageous, and increasingly so under future warming. No Label  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number MA @ admin @ Serial 2104  
Permanent link to this record
 

 
Author Pirttioja, N. url  openurl
  Title (up) A crop model ensemble analysis of wheat yield sensitivity to changes in temperature and precipitation across a European transect Type
  Year 2015 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 5 Issue Pages Sp5-46  
  Keywords  
  Abstract Impact response surfaces (IRSs) were constructed to depict the sensitivity of modelled spring and winter wheat yields to systematic changes in baseline temperature (between -2°C and +9°C)  and precipitation (-50 to +50%)  as simulated by a 26-member ensemble of process-based crop simulation models. The study was conducted across a latitudinal transect for sites in Finland, Germany and Spain.In spite of large differences in simulated yield responses to both baseline and changed climate between models, sites, crops and years, several common messages emerged. Ensemble average yields decline with warming (3-7% per 1°C) and decreased precipitation (3-9% per 10% decrease), but benefit from increased precipitation (0-8% per 10% increase). Yields are more sensitive to temperature than precipitation changes at the Finnish site while sensitivities are mixed at the other sites. Inter-model variability is highest for baseline climate at the Spanish site but is affected little by changed climate. Model responses diverge most under warming at the Finnish and German sites for winter wheat. The IRS pattern of yield reliability tracks average yield levels.Optimal temperatures for present-day cultivars are below the baseline at the German and Spanish sites suggesting that adoption of cultivars with higher temperature requirements might already be advantageous, and increasingly so at all sites under future warming.The study was conducted in the CropM component of the FACCE-JPI/MACSUR project. No Label  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK  
  Notes Approved no  
  Call Number MA @ admin @ Serial 2161  
Permanent link to this record
 

 
Author Gutierrez, L.; Piras, F.; Roggero, P.P. url  doi
openurl 
  Title (up) A global vector autoregression model for the analysis of wheat export prices Type Journal Article
  Year 2015 Publication American Journal of Agricultural Economics Abbreviated Journal American Journal of Agricultural Economics  
  Volume 97 Issue 5 Pages 1494-1511  
  Keywords Global dynamic models; price analysis; wheat market; lagged dependent-variables; commodity-markets; error-correction; food-prices; unit-root; regressors; tests; cointegration; dynamics; time  
  Abstract Food commodity price fluctuations have an important impact on poverty and food insecurity across the world. Conventional models have not provided a complete picture of recent price spikes in agricultural commodity markets, and there is an urgent need for appropriate policy responses. Perhaps new approaches are needed to better understand international spill-overs, the feedback between the real and the financial sectors, as well as the link between food and energy prices. In this article, we present the results from a new worldwide dynamic model that provides the short and long-run impulse responses of the international wheat price to various real and financial shocks.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0002-9092 1467-8276 ISBN Medium Article  
  Area Expedition Conference  
  Notes TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4658  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: