| Records |
| Author |
Sharif, B.; Olesen, J.E.; Schelde, K. |
| Title |
Statistical learning approach for modelling the effects of climate change on oilseed rape yield |
Type |
Conference Article |
| Year |
2014 |
Publication |
|
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
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. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
| Series Volume |
3(S) Sassari, Italy |
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
| Notes |
|
Approved |
no |
| Call Number |
MA @ admin @ |
Serial  |
5129 |
| Permanent link to this record |
| |
|
| |
| Author |
Schönhart, M. |
| Title |
Spillovers between MACSUR and Austrian climate change research projects |
Type |
Conference Article |
| Year |
2014 |
Publication |
|
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
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. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
| Series Volume |
3(S) Sassari, Italy |
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
| Notes |
|
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5127 |
| Permanent link to this record |
| |
|
| |
| Author |
Baranowski, P.; Krzyszczak, J.R.; Sławiński, C.F. |
| Title |
Self-similarity analysis of chosen agro-meteorological time series |
Type |
Conference Article |
| Year |
2014 |
Publication |
|
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
The most usual records of observable agro-meteorological quantities are in the form of time series and the knowledge about their scaling properties is fundamental for transferring locally measured fluctuations to larger scales and vice-versa. However, the scaling analysis of these quantities is complicated because of the presence of localized trends and nonstationarities. The objective of this study was to characterize scaling properties (i.e. statistical self-similarity) of the chosen agro-meteorological quantities through multifractal detrended fluctuation analysis (MFDFA). The MDFA analysis was performed for time series of the air temperature, wind velocity and relative air humidity (at the height of 2 m above the active surface) as well as the soil temperature (at 10 cm depth in the soil). The studied data were hourly interval, 12 years’ time series from the agro-meteorological station in Felin, near Lublin, Poland. The empirical singularity spectra indicated their multifractal structure. The richness of the studied multifractals was evaluated by the width of their spectrum, indicating their considerable differences in dynamics and development. The log-log plots of the cumulative distributions of all the studied absolute and normalized meteorological parameters tended to linear functions for high values of the response indicating that these distributions were consistent with the power law asymptotic behaviour. Additionally, we investigated the type of multifractality, that underlies the q-dependence of the generalized Hurst exponent, by analyzing the corresponding shuffled and surrogate time series. For majority of studied quantities, the multifractality was due to different long-range correlation for small and large fluctuations. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
| Series Volume |
3(S) Sassari, Italy |
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
| Notes |
|
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5124 |
| Permanent link to this record |
| |
|
| |
| Author |
Lacetera, N.; Vitali, A.; Bernabucci, U.; Nardone, A. |
| Title |
Relationships between temperature humidity index, mortality, milk yield and composition in Italian dairy cows |
Type |
Conference Article |
| Year |
2014 |
Publication |
|
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
The aim of this presentation is to illustrate the activities performed by the LiveM-Task L1.2. group based at the University of Tuscia, Viterbo, Italy. Three different pluriannual databases were built to perform retrospective studies aimed at establishing the relationships between temperature humidity index (THI) and parameters of interest for dairy cow farms. The THI combines temperature and humidity in a single value and has been widely used to quantify heat stress in farm animals. The first database was built to assess the relationships between THI and mortality over a 6 yr period (2002-2007); the second one was a 7 yr database (2001-2007) which was built to establish the relationships between THI and milk yield; the last database included THI, milk somatic cell counts, total bacterial counts, fat and protein percentages data collected over a 7 yr period (2003-2009). The analysis of the three databases provided several equations which demonstrated and quantified an increase of mortality, reduction of milk yield and a worsening of milk quality in hot environment. Results of these analyzes authorized speculations about risks for dairy cows and their productivity in a warming planet. Furthermore, the same results are being utilized by economists also working within MACSUR at the University of Tuscia for an integrated study aimed at establishing the economic impact of climate change in the dairy sector. Combining this information with climate change regional scenarios might permit prediction of the impact of global warming and identification of adaptation measures that are appropriate for specific contexts. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
| Series Volume |
3(S) Sassari, Italy |
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
| Notes |
|
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5122 |
| Permanent link to this record |
| |
|
| |
| Author |
Schönhart, M. |
| Title |
Regional Pilot Case Study: Mostviertal – AT, upcoming project phase |
Type |
Conference Article |
| Year |
2014 |
Publication |
|
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
The presentation indicates our plans for activities in the Mostviertel region in the next project phase. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
| Series Volume |
3(S) Sassari, Italy |
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
| Notes |
|
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5121 |
| Permanent link to this record |
