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Author |
Schönhart, M. |
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Title |
Spillovers between MACSUR and Austrian climate change research projects |
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2014 |
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The Austrian regional case study in MACSUR extends the methods and builds upon the results of the CC-ILA project. CC-ILA enables cooperation between landscape planners and landscape ecologists to analyse mitigation and adaptation strategies for sustainable rural land use and landscape developments in a case study landscape. Subsequent research in MACSUR includes analysis towards rural development and the improvement of the climate impact data base for grasslands. The latter is achieved by collaborating with Crop-M partner LFZ Raumberg-Gumpenstein, who is able to utilize spill-overs within the Agromet-Monitor project. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5127 |
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Author |
Van den Pol-van Dasselaar, A. |
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Title |
Stakeholder consultation on functions of grasslands in Europe |
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Conference Article |
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2014 |
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Active participation of stakeholders was one of the key objectives of the FP7-funded project MultiSward (Grant Agreement n° FP7-244983). MultiSward aimed to increase the reliance of farmers on grasslands and on multi-species swards for competitive and sustainable ruminant production systems. Stakeholders were consulted via international and national meetings. Furthermore, an on-line questionnaire on the functions of grasslands was developed in eight languages and almost 2000 valid responses were obtained from European stakeholders. All of the stakeholder groups that were identified as being important in the stakeholder analysis responded to the questionnaire: primary producers, policy makers, researchers, advisors, NGO’s (for nature conservation and for protection of the environment), industry (mainly processing and seed industry) and education. This method of stakeholder consultation will be illustrated using the results on appreciation of the following functions of grasslands: adaptation to climate change, mitigating greenhouse gas emissions and carbon sequestration. |
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Series Editor |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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Series Volume |
3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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no |
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Call Number |
MA @ admin @ |
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5128 |
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Sharif, B.; Olesen, J.E.; Schelde, K. |
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Title |
Statistical learning approach for modelling the effects of climate change on oilseed rape yield |
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2014 |
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Statistical learning is a fairly new term referring to a set of supervised and unsupervised modelling and prediction techniques. It is based on traditional statistics but has been highly enhanced inspired by developments in machine learning and data mining. The main focus of statistical learning is to estimate the functions that quantify relations between several parameters and observed responses. These functions are further used for prediction, inference or a combination of both. For a particular case of quantitative responses, regularization techniques in regression are developed to overcome the weaknesses of ordinary least square (OLS) regression in prediction. These new shrinkage methods outperform OLS for prediction, especially in large datasets. In this study, a large dataset of field experiments on winter oilseed rape in Denmark for 22 years (1992 to 2013) was collected. Biweekly climatic data along with sowing date, harvest date, soil type and previous crop are considered as the explanatory variables. Yield of winter oilseed rape is considered as response variable. LASSO and Elastic Nets are the regularization techniques used to estimate the functions. Hold-one-out cross validation method for testing the prediction power reveals that these techniques are much useful in both prediction and inference. Since these techniques are included in recent versions of some software packages (e.g. R), they can be easily implemented by users at any level. The estimated function (model) is further used to predict the oilseed rape yield responses to climate change for several scenarios using representative weather data produced by a weather generator. |
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Series Editor |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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Series Volume |
3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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Notes |
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no |
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Call Number |
MA @ admin @ |
Serial |
5129 |
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Author |
Milford, A.B. |
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Title |
Sustainable food consumption as a mitigation and adaptation strategy |
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Conference Article |
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2014 |
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Studies of GHG emissions from agriculture show that there are large differences in emissions from different products. In addition some foods require more land and water resources than others, which mean that in a future with food scarcity, moving from less to more sustainable food may become a necessity for there to be enough food for everyone. A changing of consumption and production from less to more sustainable food is thus both a mitigation strategy, as well as an adaptation strategy if climate change results in less available agricultural land and water resources, and more food loss due to more extreme weather conditions. Forecasting the economic consequences of climate change on agricultural production cannot be done without taking into account our future consumption patterns. What will be produced will always to a large extent be a result of what is being demanded by consumers. This is a presentation of two ongoing projects related to this theme. One is a newly started project on factors which influence meat consumption. In a cross-country regression analysis we will estimate the importance of different factors such as income, price levels and degree of urbanization. We are particularly interested in the interlinkages between meat production and consumption at national levels. The other project looks at typical diets in England, Spain and Norway, and will estimate through a multi objective optimization process how the diets can be changed, through taxes and subsidies, towards a diet which is both more healthy and climate friendly. |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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Series Volume |
3(S) Sassari, Italy |
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Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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Notes |
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no |
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Call Number |
MA @ admin @ |
Serial |
5130 |
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Author |
Dono, G.; Cortignani, R.; Doro, L.; Roggero, P.P. |
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Title |
The adaptation of farm and awareness of ongoing climate change (CC) |
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Conference Article |
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2014 |
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Farm planning is based on awareness of climate variability, here assumed to depend on experience gained over the years, and to generate expectations on climatic variables. Expectations are based on probability distributions (pdfs) estimated on climate data and used to generate managing choices by means of Discrete Stochastic Programming. The model simulates the income losses in case farmers do not recognize the ongoing CC, and continue to plan assuming climate stability. In particular, the use of resources in 2010 is simulated based on the pdfs of the early 2000s, despite CC has changed the probabilities of the various states of nature. The model, calibrated with Positive Mathematical Programming, generates a 0.9% income increase when is allowed to adapt to 2010 climate pdfs. The model is also calibrated according to pdfs of 2010, i.e. recognizing CC: in this case income falls of 0.7% when farmers are simulated to use their soil mistakenly based of the 2000 pdfs. Given the short period of CC, the differences represent an appreciable error that farmers may be already committing. Properly specifying with the CC at local level can help building farmers’ awareness on it, and to properly manage their resources, recovering profitability. |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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Series Volume |
3(S) Sassari, Italy |
Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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Notes |
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Approved |
no |
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Call Number |
MA @ admin @ |
Serial |
5131 |
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| Permanent link to this record |
