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Author Minet, J.; Tychon, B.; Jacquemin, I.; François, L.
Title Can a global dynamic vegetation model be used for both grassland and crop modeling at the local scale Type Conference Article
Year 2014 Publication Abbreviated Journal
Volume Issue Pages
Keywords CropM; LiveM
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Area Expedition Conference MACSUR CropM International Symposium and Workshop: Modelling climate change impacts on crop production for food security, Oslo, Norway, 2014-02-10 to 2014-02-12
Notes Approved no
Call Number MA @ admin @ Serial 2641
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Author Höglind, M.; Van Oijen, M.; Cameron, D.; Persson, T.
Title Process-based simulation of growth and overwintering of grassland using the BASGRA model Type Journal Article
Year 2016 Publication Ecological Modelling Abbreviated Journal Ecol. Model.
Volume 335 Issue Pages 1-15
Keywords Cold hardening; Frost injury; Phleum pratense L.; Process-based; modelling; Winter survival; Yield; low-temperature tolerance; perennial forage crops; dry-matter; production; climate-change; nutritive-value; snow-cover; bayesian; calibration; timothy regrowth; phleum-pratense; lolium-perenne
Abstract Process-based models (PBM) for simulation of weather dependent grass growth can assist farmers and plant breeders in addressing the challenges of climate change by simulating alternative roads of adaptation. They can also provide management decision support under current conditions. A drawback of existing grass models is that they do not take into account the effect of winter stresses, limiting their use for full-year simulations in areas where winter survival is a key factor for yield security. Here, we present a novel full-year PBM for grassland named BASGRA. It was developed by combining the LINGRA grassland model (Van Oijen et al., 2005a) with models for cold hardening and soil physical winter processes. We present the model and show how it was parameterized for timothy (Phleum pratense L.), the most important forage grass in Scandinavia and parts of North America and Asia. Uniquely, BASGRA simulates the processes taking place in the sward during the transition from summer to winter, including growth cessation and gradual cold hardening, and functions for simulating plant injury due to low temperatures, snow and ice affecting regrowth in spring. For the calibration, we used detailed data from five different locations in Norway, covering a wide range of agroclimatic regions, day lengths (latitudes from 59 degrees to 70 degrees N) and soil conditions. The total dataset included 11 variables, notably above-ground dry matter, leaf area index, tiller density, content of C reserves, and frost tolerance. All data were used in the calibration. When BASGRA was run with the maximum a-posteriori (MAP) parameter vector from the single, Bayesian calibration, nearly all measured variables were simulated to an overall normalized root mean squared error (NRMSE) <0.5. For many site x experiment combinations, NRMSE was <0.3. The temporal dynamics were captured well for most variables, as evaluated by comparing simulated time courses versus data for the individual sites. The results may suggest that BASGRA is a reasonably robust model, allowing for simulation of growth and several important underlying processes with acceptable accuracy for a range of agroclimatic conditions. However, the robustness of the model needs to be tested further using independent data from a wide range of growing conditions. Finally we show an example of application of the model, comparing overwintering risks in two climatically different sites, and discuss future model applications. Further development work should include improved simulation of the dynamics of C reserves, and validation of winter tiller dynamics against independent data. (C) 2016 Elsevier B.V. All rights reserved.
Address 2016-07-28
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 0304-3800 ISBN (up) Medium Article
Area Expedition Conference
Notes CropM, LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4764
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Author Martre, P.E.A.
Title Error and uncertainty of wheat multimodel ensemble projections Type Conference Article
Year 2014 Publication Abbreviated Journal
Volume Issue Pages
Keywords CropM
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Area Expedition Conference MACSUR CropM International Symposium and Workshop: Modelling climate change impacts on crop production for food security, Oslo, Norway, 2014-02-10 to 2014-02-12
Notes Approved no
Call Number MA @ admin @ Serial 2633
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Author Wallach, D.; Nissanka, S.P.; Karunaratne, A.S.; Weerakoon, W.M.W.; Thorburn, P.J.; Boote, K.J.; Jones, J.W.
Title Accounting for both parameter and model structure uncertainty in crop model predictions of phenology: A case study on rice Type Journal Article
Year 2016 Publication European Journal of Agronomy Abbreviated Journal European Journal of Agronomy
Volume Issue Pages
Keywords Uncertainty; Phenology; Parameter uncertainty; Multi-model ensemble; Generalized least squares; Rice; Crop model; APSIM; DSSAT
Abstract We consider predictions of the impact of climate warming on rice development times in Sri Lanka. The major emphasis is on the uncertainty of the predictions, and in particular on the estimation of mean squared error of prediction. Three contributions to mean squared error are considered. The first is parameter uncertainty that results from model calibration. To take proper account of the complex data structure, generalized least squares is used to estimate the parameters and the variance-covariance matrix of the parameter estimators. The second contribution is model structure uncertainty, which we estimate using two different models. An ANOVA analysis is used to separate the contributions of parameter and model uncertainty to mean squared error. The third contribution is model error, which is estimated using hindcasts. Mean squared error of prediction of time from emergence to maturity, for baseline +2 °C, is estimated as 108 days2, with model error contributing 86 days2, followed by model structure uncertainty which contributes 15 days2 and parameter uncertainty which contributes 7 days2. We also show how prediction uncertainty is reduced if prediction concerns development time averaged over years, or the difference in development time between baseline and warmer temperatures.
Address 2016-09-13
Corporate Author Thesis
Publisher Place of Publication Editor
Language Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1161-0301 ISBN (up) Medium Article
Area CropM Expedition Conference
Notes CropM; wos; ftnotmacsur; wsnotyet; Approved no
Call Number MA @ admin @ Serial 4777
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Author Mansouri, M.; Dumont, B.; Destain, M.-F.
Title Bayesian methods for predicting LAI and soil moisture Type Conference Article
Year 2012 Publication Abbreviated Journal
Volume Issue Pages
Keywords CropM
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Area Expedition Conference 11th International Conference on Precision Agriculture. Indianapolis (USA), 2012-07-15 to 2012-07-18
Notes Approved no
Call Number MA @ admin @ Serial 2627
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