Sanna, M., Bellocchi, G., Fumagalli, M., & Acutis, M. (2015). A new method for analysing the interrelationship between performance indicators with an application to agrometeorological models. Env. Model. Softw., 73, 286–304.
Abstract: The use of a variety of metrics is advocated to assess model performance but correlated metrics may convey the same information, thus leading to redundancy. Starting from this assumption, a method was developed for selecting, from among a collection of performance indicators, one or more subsets providing the same information as the entire set. The method, based on the definition of “stable correlation”, was applied to 23 performance indicators of agrometeorological models, calculated on large sets of simulated and observed data of four agronomic and meteorological variables: above-ground biomass, leaf area index, hourly air relative humidity and daily solar radiation. Two subsets were determined: {Squared Bias, Root Mean Squared Relative Error, Coefficient of Determination, Pattern Index, Modified Modelling Efficiency}, {Persistence Model Efficiency, Root Mean Squared Relative Error, Coefficient of Determination, Pattern Index}. The method needs corroboration but is statistically founded and can support the implementation of standardized evaluation tools. (C) 2015 Elsevier Ltd. All rights reserved.
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Hoffmann, H., Zhao, G., Constantin, J., Raynal, H., Wallach, D., Coucheney, E., et al. (2015). Effects of soil and climate input data aggregation on modelling regional crop yields. MACSUR Science Conference.
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Ahmadi, V. (2015). Impacts of Common Agricultural Policy 2015 reforms on animal health and welfare of Scottish dairy herds (Vol. 5).
Abstract: The latest Common Agricultural Policy (CAP) 2015 reforms bring a substantial change in the way farm support is paid in Scotland where previous direct CAP payments were largely based on historical entitlements. Under the new payment scheme, three rates of payment are designated based on land uses and capabilities. As a result, it is anticipated that, average large dairy farms will lose out up to 32% of their farm net margins, while small dairy farms will lose out between 7-20% of their farm net margins. Such reductions of payment support may force dairy farmers to cut costs of production on farms especially livestock variable costs including labour costs and costs of prevention, control, treatment and management of livestock diseases and welfare conditions. This will have direct and indirect consequences on health and welfare of dairy cattle. This study aims to assess the impact of new support payments under CAP 2015 reforms on financial capabilities of dairy herds in tackling three conditions namely: infertility, mastitis and lameness. A detailed inventory of 42 commercial dairy farms in Scotland that contains both physical (i.e. farm area, nutrition and labour supply, etc.) and health data collected in 2013 and was used to parameterise an optimisation model. The model is a linear programme (LP) model which optimises farm net margin under limiting farm resources. The model also consists of feed demand and supply components that are used to determine monthly feed requirements for each of the animals on a farm as well as grass yield for pasture area of the land. The model is run for both ‘healthy’ and ‘diseased’ herds under previous and future CAP support payments. Details of the model and the dataset used as well as some results will be presented at the conference. No Label
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Zander, P. (2015). Modelling regional agricultural land use and climate change adaptation strategies in 4 case study regions Northern Germany (Vol. 4).
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Steen, M. (2015). Warmer, Wetter, Wilder? Climatic Evidence from the Grain Markets (Vol. 4).
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