| Home | << 1 2 3 4 5 >> |
|
| Records | |||||
|---|---|---|---|---|---|
| Author | Özkan Gülzari, Ş.; Åby, B.A.; Persson, T.; Höglind, M.; Mittenzwei, K. | ||||
| Title | Combining models to estimate the impacts of future climate scenarios on feed supply, greenhouse gas emissions and economic performance on dairy farms in Norway | Type | Journal Article | ||
| Year | 2017 | Publication | Agricultural Systems | Abbreviated Journal | Agric. Syst. |
| Volume | 157 | Issue | Pages | 157-169 | |
| Keywords | Climate change; Dairy farming; Dry matter yield; Economics; Greenhouse gas emission; Modelling | ||||
| Abstract | • This study combines crop, livestock and economic models. • Models interaction is through use of relevant input and output variables. • Future climate change will result in increased grass and wheat dry matter yields. • Changes in grass, wheat and milk yields in future reduce farm emissions intensity. • Changes in future dry matter yields and emissions lead to increased profitability. There is a scientific consensus that the future climate change will affect grass and crop dry matter (DM) yields. Such yield changes may entail alterations to farm management practices to fulfill the feed requirements and reduce the farm greenhouse gas (GHG) emissions from dairy farms. While a large number of studies have focused on the impacts of projected climate change on a single farm output (e.g. GHG emissions or economic performance), several attempts have been made to combine bio-economic systems models with GHG accounting frameworks. In this study, we aimed to determine the physical impacts of future climate scenarios on grass and wheat DM yields, and demonstrate the effects such changes in future feed supply may have on farm GHG emissions and decision-making processes. For this purpose, we combined four models: BASGRA and CSM-CERES-Wheat models for simulating forage grass DM and wheat DM grain yields respectively; HolosNor for estimating the farm GHG emissions; and JORDMOD for calculating the impacts of changes in the climate and management on land use and farm economics. Four locations, with varying climate and soil conditions were included in the study: south-east Norway, south-west Norway, central Norway and northern Norway. Simulations were carried out for baseline (1961–1990) and future (2046–2065) climate conditions (projections based on two global climate models and the Special Report on Emissions Scenarios (SRES) A1B GHG emission scenario), and for production conditions with and without a milk quota. The GHG emissions intensities (kilogram carbon dioxide equivalent: kgCO2e emissions per kg fat and protein corrected milk: FPCM) varied between 0.8 kg and 1.23 kg CO2e (kg FPCM)− 1, with the lowest and highest emissions found in central Norway and south-east Norway, respectively. Emission intensities were generally lower under future compared to baseline conditions due mainly to higher future milk yields and to some extent to higher crop yields. The median seasonal above-ground timothy grass yield varied between 11,000 kg and 16,000 kg DM ha− 1 and was higher in all projected future climate conditions than in the baseline. The spring wheat grain DM yields simulated for the same weather conditions within each climate projection varied between 2200 kg and 6800 kg DM ha− 1. Similarly, the farm profitability as expressed by total national land rents varied between 1900 million Norwegian krone (NOK) for median yields under baseline climate conditions up to 3900 million NOK for median yield under future projected climate conditions. |
||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
Language  |
Summary Language | phase 2 | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | |||
| Notes | CropM, LiveM, TradeM, ft_macsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 5172 | ||
| Permanent link to this record | |||||
| Author | Van Oijen, M.; Höglind, M. | ||||
| Title | Toward a Bayesian procedure for using process-based models in plant breeding, with application to ideotype design | Type | Journal Article | ||
| Year | 2016 | Publication | Euphytica | Abbreviated Journal | Euphytica |
| Volume | 207 | Issue | 3 | Pages | 627-643 |
| Keywords | BASGRA; cold tolerance; genotype-environment interaction; plant breeding; process-based modelling; yield stability; grassland productivity; timothy regrowth; climate-change; water-deficit; forest models; late blight; leaf-area; calibration; growth; tolerance | ||||
| Abstract | Process-based grassland models (PBMs) simulate growth and development of vegetation over time. The models tend to have a large number of parameters that represent properties of the plants. To simulate different cultivars of the same species, different parameter values are required. Parameter differences may be interpreted as genetic variation for plant traits. Despite this natural connection between PBMs and plant genetics, there are only few examples of successful use of PBMs in plant breeding. Here we present a new procedure by which PBMs can help design ideotypes, i.e. virtual cultivars that optimally combine properties of existing cultivars. Ideotypes constitute selection targets for breeding. The procedure consists of four steps: (1) Bayesian calibration of model parameters using data from cultivar trials, (2) Estimating genetic variation for parameters from the combination of cultivar-specific calibrated parameter distributions, (3) Identifying parameter combinations that meet breeding objectives, (4) Translating model results to practice, i.e. interpreting parameters in terms of practical selection criteria. We show an application of the procedure to timothy (Phleum pratense L.) as grown in different regions of Norway. | ||||
| Address | 2016-10-31 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language |
English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0014-2336 | ISBN | Medium | Article | |
| Area | Expedition | Conference | |||
| Notes | CropM, ft_macsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4820 | ||
| Permanent link to this record | |||||
| 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 | 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 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language |
English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0304-3800 | ISBN | Medium | Article | |
| Area | Expedition | Conference | |||
| Notes | CropM, LiveM, ft_macsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4764 | ||
| Permanent link to this record | |||||
| Author | Kipling, R.P.; Virkajärvi, P.; Breitsameter, L.; Curnel, Y.; De Swaef, T.; Gustavsson, A.-M.; Hennart, S.; Höglind, M.; Järvenranta, K.; Minet, J.; Nendel, C.; Persson, T.; Picon-Cochard, C.; Rolinski, S.; Sandars, D.L.; Scollan, N.D.; Sebek, L.; Seddaiu, G.; Topp, C.F.E.; Twardy, S.; Van Middelkoop, J.; Wu, L.; Bellocchi, G. | ||||
| Title | Key challenges and priorities for modelling European grasslands under climate change | Type | Journal Article | ||
| Year | 2016 | Publication | Science of the Total Environment | Abbreviated Journal | Science of the Total Environment |
| Volume | 566-567 | Issue | Pages | 851-864 | |
| Keywords | Climate change; Grasslands; Horizon scanning; Livestock production; Models; Research agenda | ||||
| Abstract | Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research directions and collaborative opportunities, and 2) for policy-makers involved in shaping the research agenda for European grassland modelling under climate change. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language |
English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0048-9697 | ISBN | Medium | Article | |
| Area | Expedition | Conference | |||
| Notes | LiveM, ft_macsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4761 | ||
| Permanent link to this record | |||||
| Author | Persson, T.; Kværnø, S.; Höglind, M. | ||||
| Title | Impact of soil type extrapolation on timothy grass yield under baseline and future climate conditions in southeastern Norway | Type | Journal Article | ||
| Year | 2015 | Publication | Climate Research | Abbreviated Journal | Clim. Res. |
| Volume | 65 | Issue | Pages | 71-86 | |
| Keywords | climate change scenarios; crop modelling; forage grass; lingra; soil properties; spatial variability; phleum pretense; poaceae; simulation-model; nutritive-value; systems simulation; catimo model; crop models; growth; nitrogen; scale; productivity; regrowth | ||||
| Abstract | Interactions between soil properties and climate affect forage grass productivity. Dynamic models, simulating crop performance as a function of environmental conditions, are valid for a specific location with given soil and weather conditions. Extrapolations of local soil properties to larger regions can help assess the requirement for soil input in regional yield estimations. Using the LINGRA model, we simulated the regional yield level and variability of timothy, a forage grass, in Akershus and Ostfold counties, Norway. Soils were grouped according to physical similarities according to 4 sets of criteria. This resulted in 66, 15, 5 and 1 groups of soils. The properties of the soil with the largest area was extrapolated to the other soils within each group and input to the simulations. All analyses were conducted for 100 yr of generated weather representing the period 1961-1990, and climate projections for the period 2046-2065, the Intergovernmental Panel on Climate Change greenhouse gas emission scenario A1B, and 4 global climate models. The simulated regional seasonal timothy yields were 5-13% lower on average and had higher inter-annual variability for the least detailed soil extrapolation than for the other soil extrapolations, across climates. There were up to 20% spatial intra-regional differences in simulated yield between soil extrapolations. The results indicate that, for conditions similar to these studied here, a few representative profiles are sufficient for simulations of average regional seasonal timothy yield. More spatially detailed yield analyses would benefit from more detailed soil input. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language |
English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0936-577x 1616-1572 | ISBN | Medium | Article | |
| Area | Expedition | Conference | |||
| Notes | CropM, ft_macsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4674 | ||
| Permanent link to this record | |||||