| Records |
| Author |
Korhonen, P.; Palosuo, T.; Höglind, M.; Persson, T.; van Oijen, M.; Jego, G.; Virkajärvi, P.; Belanger, G.; Gustavsson, A.M. |
| Title |
Intercomparison of models for simulating timothy yield in Northern countries. The multiple roles of grassland in the European bioeconomy |
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Conference Article |
| Year |
2016 |
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Place of Publication |
Trondheim, Norway |
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Abbreviated Series Title |
General Meeting of the European Grassland Federation |
| Series Volume |
26 |
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General Meeting of the European Grassland Federation, 2016-09-04 to 2016-09-08, Trondheim, Norway 26: |
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no |
| Call Number |
MA @ admin @ |
Serial |
5168 |
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| Author |
Kipling, R. |
| Title |
LiveM2016: International livestock modelling conference – Modelling grassland-livestock systems under climate change |
Type |
Report |
| Year |
2016 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
8 |
Issue |
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Pages |
L0.1-D1 |
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no |
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MA @ admin @ |
Serial |
4841 |
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| Author |
Tao, F.; Zhang, Z.; Zhang, S.; Rötter, R.P.; Shi, W.; Xiao, D.; Liu, Y.; Wang, M.; Liu, F.; Zhang, H. |
| Title |
Historical data provide new insights into response and adaptation of maize production systems to climate change/variability in China |
Type |
Journal Article |
| Year |
2016 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
| Volume |
185 |
Issue |
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Pages |
1-11 |
| Keywords |
china; climate variability; grain yield; impact; maize; northeast china; tropical maize; wheat yields; heat-stress; crop yields; temperature; impacts; sensitivities; hybrids; trends |
| Abstract |
Extensive studies had been conducted to investigate the impacts of climate change on maize growth and yield in recent decades; however, the dynamics of crop husbandry in response and adaptation to climate change were not taken into account. Based on field observations spanning from 1981 to 2009 at 167 agricultural meteorological stations across China, we found that solar radiation and temperature over the observed maize growth period had decreasing trends during 1981-2009, and maize yields were positively correlated with these climate variables in major production regions. The decreasing trends in solar radiation and temperature during maize growth period were mainly ascribed to the adoption of late maturity cultivars with longer reproductive growth period (RGP). The adoption of late maturing cultivars with longer RGP contributed substantially to grain yield increase during the last three decades. The climate trends during maize growth period varied among different production areas. During 1981-2009, decreases in mean temperature, precipitation and solar radiation over maize growth period jointly reduced yield most by 13.2-17.3% in southwestern China, by contrast in northwestern China increases in mean temperature, precipitation and solar radiation jointly increased yield most by 12.9-14.4%. Our findings highlight that the adaptations of maize production system to climate change through shifts of sowing date and genotypes are underway and should be taken into accounted when evaluating climate change impacts. (C) 2015 Elsevier B.V. All rights reserved. |
| Address |
2016-10-31 |
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English |
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0378-4290 |
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Article |
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| Notes |
CropM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4816 |
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Sándor, R.; Barcza, Z.; Hidy, D.; Lellei-Kovács, E.; Ma, S.; Bellocchi, G. |
| Title |
Modelling of grassland fluxes in Europe: evaluation of two biogeochemical models |
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Journal Article |
| Year |
2016 |
Publication |
Agriculture, Ecosystems and Environment |
Abbreviated Journal |
Agric. Ecosyst. Environ. |
| Volume |
215 |
Issue |
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Pages |
1-19 |
| Keywords |
carbon-water fluxes; climate change; grasslands; model comparison; net ecosystem exchange; terrestrial carbon balance; pasture simulation-model; climate-change; nitrous-oxide; land-use; co2; photosynthesis; responses; water |
| Abstract |
Two independently developed simulation models – the grassland-specific PaSim and the biome-generic Biome-BGC MuSo (BBGC MuSo) – linking climate, soil, vegetation and management to ecosystem biogeochemical cycles were compared in a simulation of carbon (C) and water fluxes. The results were assessed against eddy-covariance flux data from five observational grassland sites representing a range of conditions in Europe: Grillenburg in Germany, Laqueuille in France with both extensive and intensive management, Monte Bondone in Italy and Oensingen in Switzerland. Model comparison (after calibration) gave substantial agreement, the performances being marginal to acceptable for weekly-aggregated gross primary production and ecosystem respiration (R-2 similar to 0.66 – 0.91), weekly evapotranspiration (R-2 similar to 0.78 – 0.94), soil water content in the topsoil (R-2 similar to 0.1 -0.7) and soil temperature (R-2 similar to 0.88 – 0.96). The bias was limited to the range -13 to 9 g C m(-2) week(-1) for C fluxes (-11 to 8 g C m(-2) week(-1) in case of BBGC MuSo, and -13 to 9 g C m(-2) week(-1) in case of PaSim) and -4 to 6 mm week for water fluxes (with BBGC MuSo providing somewhat higher estimates than PaSim), but some higher relative root mean square errors indicate low accuracy for prediction, especially for net ecosystem exchange The sensitivity of simulated outputs to changes in atmospheric carbon dioxide concentration ([CO2]), temperature and precipitation indicate, with certain agreement between the two models, that C outcomes are dominated by [CO2] and temperature gradients, and are less due to precipitation. ET rates decrease with increasing [CO2] in PaSim (consistent with experimental knowledge), while lack of appropriate stomatal response could be a limit in BBGC MuSo responsiveness. Results of the study indicate that some of the errors might be related to the improper representation of soil water content and soil temperature. Improvement is needed in the model representations of soil processes (especially soil water balance) that strongly influence the biogeochemical cycles of managed and unmanaged grasslands. (C) 2015 Elsevier B.V. All rights reserved. |
| Address |
2016-10-31 |
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English |
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0167-8809 |
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Article |
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| Notes |
CropM, LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4808 |
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| Author |
Höglind, M.; Van Oijen, M.; Cameron, D.; Persson, T. |
| Title |
Process-based simulation of growth and overwintering of grassland using the BASGRA model |
Type |
Journal Article |
| Year |
2016 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
| Volume |
335 |
Issue |
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Pages |
1-15 |
| Keywords |
Cold hardening; Frost injury; Phleum pratense L.; Process-based; modelling; Winter survival; Yield; low-temperature tolerance; perennial forage crops; dry-matter; production; climate-change; nutritive-value; snow-cover; bayesian; calibration; timothy regrowth; phleum-pratense; lolium-perenne |
| Abstract |
Process-based models (PBM) for simulation of weather dependent grass growth can assist farmers and plant breeders in addressing the challenges of climate change by simulating alternative roads of adaptation. They can also provide management decision support under current conditions. A drawback of existing grass models is that they do not take into account the effect of winter stresses, limiting their use for full-year simulations in areas where winter survival is a key factor for yield security. Here, we present a novel full-year PBM for grassland named BASGRA. It was developed by combining the LINGRA grassland model (Van Oijen et al., 2005a) with models for cold hardening and soil physical winter processes. We present the model and show how it was parameterized for timothy (Phleum pratense L.), the most important forage grass in Scandinavia and parts of North America and Asia. Uniquely, BASGRA simulates the processes taking place in the sward during the transition from summer to winter, including growth cessation and gradual cold hardening, and functions for simulating plant injury due to low temperatures, snow and ice affecting regrowth in spring. For the calibration, we used detailed data from five different locations in Norway, covering a wide range of agroclimatic regions, day lengths (latitudes from 59 degrees to 70 degrees N) and soil conditions. The total dataset included 11 variables, notably above-ground dry matter, leaf area index, tiller density, content of C reserves, and frost tolerance. All data were used in the calibration. When BASGRA was run with the maximum a-posteriori (MAP) parameter vector from the single, Bayesian calibration, nearly all measured variables were simulated to an overall normalized root mean squared error (NRMSE) <0.5. For many site x experiment combinations, NRMSE was <0.3. The temporal dynamics were captured well for most variables, as evaluated by comparing simulated time courses versus data for the individual sites. The results may suggest that BASGRA is a reasonably robust model, allowing for simulation of growth and several important underlying processes with acceptable accuracy for a range of agroclimatic conditions. However, the robustness of the model needs to be tested further using independent data from a wide range of growing conditions. Finally we show an example of application of the model, comparing overwintering risks in two climatically different sites, and discuss future model applications. Further development work should include improved simulation of the dynamics of C reserves, and validation of winter tiller dynamics against independent data. (C) 2016 Elsevier B.V. All rights reserved. |
| Address |
2016-07-28 |
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English |
Summary Language |
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Original Title |
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0304-3800 |
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Article |
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| Notes |
CropM, LiveM, ft_macsur |
Approved |
no |
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MA @ admin @ |
Serial |
4764 |
| Permanent link to this record |
