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Bellocchi, G., Ma, S., Köchy, M., & Braunmiller, K. (2013). Identified grassland-livestock production systems and related models (Vol. 2).
Abstract: This report describes grassland-livestock production systems, as selected for model-basedstudies. A list of grassland models was identified for evaluation against such datasets(WP2) and application at reference farm (WP3) and regions (WP4) across Europe and peri-European countries. No Label
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Jorgenson, J. (2013). Review of Cloud Computing Opportunities (Vol. 1).
Abstract: This paper will begin by defining some of the challenges that we face on the MACSUR project in terms of evaluating model uncertainty and carrying out model integration. I will briefly review what cloud technologies are available, followed with some suggestions about how those cloud technologies can be used in order to contribute to meeting the challenges set out in the first part of the paper.’Month 12’ deliverable for WP1 is a review of the opportunities for using cloud computing to develop the potential for model inter-comparison and interlinking in MACSUR. A challenging aspect of compiling this review is that before an ‘opportunity’ for any kind of model linking/comparison can be identified, a lot of information about the specifics of extant models and workflows must be gathered from each of the three themes (TradeM, CropM, and LiveM).This deliverable must, however, be more than just saying ‘these are the computing tools that we can use to.’. There are a number of different challenges at different levels; a hierarchy of challenges, if you like. For example, in order to get models ‘talking’ to one another, adequate protocols for the transference of data and scaleability will need to be established, and then things like uncertainty analysis for these integrated models will need to be addressed. Further issues exist relating to human behaviour and logistics (e.g. MACSUR is a large project with many members from all over Europe, with substantial distances between many of it’s members).The term “Cloud” is very ambiguous, and Cloud Computing covers a huge range of services, and a number of innovative tools exist which can make international collaborative research more effective. Two examples (already implemented on the MACSUR website) are: a discussion forum (where project members can create topics, make or reply to posts, and upload documents) and a complete surveying platform (to provide an un-restricted and fully featured survey platform for MACSUR members’ information gathering needs.) No Label
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Lehtonen, H. S., & Irz, X. (2013). Impacts of reducing red meat consumption on agricultural production in Finland. Agriculture and Food Science, 22(3), 356–370.
Abstract: This paper summarises the simulated effects on Finnish agrcultural production and trade of a 20% decrease in Finnish demand for red meat (beef, pork, lamb). According to our results, reduced red meat consumption would be offset by increased consumption of poultry meat, eggs, dairy products and fish, as well as small increases in consumption of fruits and vegetables, peas, nuts, cereal products and sweets. By including the derived demand changes in an agricultural sector model, we show that livestock production in Finland, incentivised by national production-linked payments for milk and bovine animals, would decrease by much less than 20% due to the complex nature of agricultural production and trade. Overall, assuming unchanged consumer preferences and agricultural policy, a 20% reduction in red meat consumption is not likely to lead to a substantial decrease in livestock production or changed land use, or greenhouse gas emissions, from Finnish agriculture.
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Porter, J. R., & Christensen, S. (2013). Deconstructing crop processes and models via identities. Plant Cell and Environment, 36(11), 1919–1925.
Abstract: This paper is part review and part opinion piece; it has three parts of increasing novelty and speculation in approach. The first presents an overview of how some of the major crop simulation models approach the issue of simulating the responses of crops to changing climatic and weather variables, mainly atmospheric CO2 concentration and increased and/or varying temperatures. It illustrates an important principle in models of a single cause having alternative effects and vice versa. The second part suggests some features, mostly missing in current crop models, that need to be included in the future, focussing on extreme events such as high temperature or extreme drought. The final opinion part is speculative but novel. It describes an approach to deconstruct resource use efficiencies into their constituent identities or elements based on the Kaya-Porter identity, each of which can be examined for responses to climate and climatic change. We give no promise that the final part is correct’, but we hope it can be a stimulation to thought, hypothesis and experiment, and perhaps a new modelling approach.
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Rötter, R. P., Höhn, J., Trnka, M., Fronzek, S., Carter, T. R., & Kahiluoto, H. (2013). Modelling shifts in agroclimate and crop cultivar response under climate change. Ecol. Evol., 3(12), 4197–4214.
Abstract: THIS PAPER AIMS: (i) to identify at national scale areas where crop yield formation is currently most prone to climate-induced stresses, (ii) to evaluate how the severity of these stresses is likely to develop in time and space, and (iii) to appraise and quantify the performance of two strategies for adapting crop cultivation to a wide range of (uncertain) climate change projections. To this end we made use of extensive climate, crop, and soil data, and of two modelling tools: N-AgriCLIM and the WOFOST crop simulation model. N-AgriCLIM was developed for the automatic generation of indicators describing basic agroclimatic conditions and was applied over the whole of Finland. WOFOST was used to simulate detailed crop responses at four representative locations. N-AgriCLIM calculations have been performed nationally for 3829 grid boxes at a 10 × 10 km resolution and for 32 climate scenarios. Ranges of projected shifts in indicator values for heat, drought and other crop-relevant stresses across the scenarios vary widely – so do the spatial patterns of change. Overall, under reference climate the most risk-prone areas for spring cereals are found in south-west Finland, shifting to south-east Finland towards the end of this century. Conditions for grass are likely to improve. WOFOST simulation results suggest that CO2 fertilization and adjusted sowing combined can lead to small yield increases of current barley cultivars under most climate scenarios on favourable soils, but not under extreme climate scenarios and poor soils. This information can be valuable for appraising alternative adaptation strategies. It facilitates the identification of regions in which climatic changes might be rapid or otherwise notable for crop production, requiring a more detailed evaluation of adaptation measures. The results also suggest that utilizing the diversity of cultivar responses seems beneficial given the high uncertainty in climate change projections.
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