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Stocco, L., Adenäuer, M., & Zimmermann, A. (2013). Global land use response in agricultural sector models: estimating supply and area response in Argentina..
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Braunmiller, K., & Köchy, M. (2013). Grassland datasets (Vol. 1).
Abstract: In the MACSUR project, there are several grassland models in use that were designed for and adjusted with data from different climatic regions. To be able to run these modelsfor a wide geographical range, there is a need to validate and calibrate them on the same basis.Therefore, a high-quality dataset is needed, which includes a wide range of climatic conditions, management systems and other variables.Through this search 23 grassland related institutes from eleven countries were found and contacted, where 12 of them responded to the request. Nine institutes from cooler (e.g. Finland) and warmer regions (e.g. Israel) are now willing to provide their experimental data. One contributor is even planning to join the project bringing its own grassland model.These new grassland datasets cover in addition to already available ones (Fig. 1) a wide range of climatic regions for a substantiated calibration and validation of the models. Data supplied by the institutes have been checked for internal consistency and cast into a common format. The data have been passed on to WP L2 (Model intercomparison on climate change in relation to livestock and grassland). No Label
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Ventrella, D., & Giglio, L. (2013). Green and blue water for the cultivation of tomato in Puglia. Patron Editore Bologna. 105-106. ISBN 978-88-555-3235-8..
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Hoff, H., Gerten, D., Waha, K., Warner, J., Keulertz, M., & Sojamo, S. (2013). Green and Blue Water in Africa: How Foreign Direct Investment can Support Sustainable Intensification. In T. Allan, M. Keulertz, & S. A. Sojamo (Eds.), (pp. 359–375). Handbook of Land and Water Grabs in Africa. Routledge.
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Trnka, M. (2013). Guidelines on extending on-going experiments with additional measurements to support crop modelling – Field experimental protocol (Vol. 2).
Abstract: The input data necessary for crop model simulations and data for their calibration/validation (and thus requirements for observations and measurements in suitable experiments) are listed. A list of possible seasonal observations/measurements that could be carried out in existing experiments to increase their potential for crop modelling studies is also provided. The general methodology suitable to be used is outlined, but in all cases the selected method depends strongly on the experimental set-up and facilities/instruments at the disposal of the experimentalists. Such methodologies needs to be documented and preferably benchmarked against standard methods. No Label
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