| Records |
| Author |
Ruete, A.; Velarde, A.; Blanco-Penedo, I. |
Title  |
Eco-DREAMS-S: modelling the impact of climate change on milk performance in organic dairy farms |
Type |
Journal Article |
| Year |
2015 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
| Volume |
6 |
Issue |
01 |
Pages |
21-23 |
| Keywords |
dairy; organic; THI; heat stress; milk production |
| Abstract |
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| Language |
English |
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Edition |
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| ISSN |
2040-4700 |
ISBN |
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Article |
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| Notes |
LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4679 |
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| Author |
Schönhart, M.; Nadeem, I. |
| Title |
Direct climate change impacts on cattle indicated by THI models |
Type |
Journal Article |
| Year |
2015 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
| Volume |
6 |
Issue |
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Pages |
17-17 |
| Keywords |
dairy; THI; milk yield; integrated modelling; economic loss |
| Abstract |
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| Address |
2016-10-31 |
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| Language |
English |
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| Notes |
TradeM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4811 |
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| Author |
Wallach, D. |
| Title |
Developing skills: how to train adaptive modelers |
Type |
Journal Article |
| Year |
2015 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
| Volume |
6 |
Issue |
01 |
Pages |
52-53 |
| Keywords |
capacity building; skills development; training; integrated modeling |
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| Language |
English |
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Edition |
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| ISSN |
2040-4700 |
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| Notes |
Hub, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4683 |
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| Author |
Persson, T. |
| Title |
Determining the variability in optimal sowing date of spring cereals in South Eastern Norway |
Type |
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| Year |
2015 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
5 |
Issue |
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Pages |
Sp5-45 |
| Keywords |
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| Abstract |
Spring cereals are important agricultural crops in Northern Europe. The short growing season in this region necessitates early sowing. The earliest possible date is often determined by the soil water content, which usually decreases during and after snowmelt at rates varying with the weather and the soil characteristics. Tillage and sowing operations on soils with too high a water content can lead to soil compaction, increased soil erosion, and losses of nutrients and soil organic matter. Rainfall intensity also affects crop emergence, through its potentially negative effects on surface capping. The objective of this study was to determine the earliest possible sowing date of spring cereals for representative soil and climate scenarios in southeastern Norway. Criteria were set for pre-sowing tillage operations and sowing, based on the water content in differ soil layers and the incidence of rainfall. To determine the day of the year when these criteria were first met, the soil water content during the spring was simulated with the soil module in DSSAT v4.5. These simulations were performed for contrasting soil types and climate scenarios representing the period 1961-90 and 2046-65 respectively. For each combination of soil and climate, one hundred simulations with individual weather data were performed. The results provide information about the timing and variability of the optimal planting date for the current and projected climate in South Eastern Norway. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2160 |
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| Author |
Trnka, M.; Kersebaum, K.; Christian,; Olesen, J.E. |
| Title |
Description of the compiled experimental data available in the MACSUR CropM database |
Type |
Report |
| Year |
2015 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
6 |
Issue |
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Pages |
D-C2.1 |
| Keywords |
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| 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) have been collected through out the project together with data for additional analysis of abiotic factors influencing yields. A list of possible dataset was collated in the first year of project however very few of the existing datasets were found usable for the crop model simulation as they fell short of the requirements defined in the part 2.3. However database has been populated as planned with the results of the ongoing MACSUR studies and will serve in the same way for the MACSUR 2 duration. No Label |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2090 |
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