| |
Records |
Links |
|
Author |
Mittenzwei, K.; Persson, T.; Höglind, M.; Kværnø, S. |
|
| |
Title |
Combined effects of climate change and policy uncertainty on the agricultural sector in Norway |
Type |
Journal Article |
| |
Year |
2017 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
|
| |
Volume |
153 |
Issue |
|
Pages |
118-126 |
|
| |
Keywords |
Climate change; Norway; Agriculture; Policy uncertainty; Modelling; LINGRA; CSM-CERES-Wheat; DSSAT |
|
| |
Abstract |
Highlights • A framework to study climate and policy uncertainty in agriculture is presented. • Combining both sources of uncertainty has ambiguous effects on agriculture. • Uncertainty needs to be highlighted in modelling tools for policy analysis. Abstract Farmers are exposed to climate change and uncertainty about how that change will develop. As farm incomes, in Norway and elsewhere, greatly depend on government subsidies, the risk of a policy change constitutes an additional uncertainty source. Hence, climate and policy uncertainty could substantially impact agricultural production and farm income. However, these sources of uncertainty have, so far, rarely been combined in food production analyses. The aim of this study was to determine the effects of a combination of policy and climate uncertainty on agricultural production, land use, and social welfare in Norway. Output yield distributions of spring wheat and timothy, a major forage grass, from simulations with the weather-driven crop models, CSM-CERES-Wheat and, LINGRA, were processed in the a stochastic version Jordmod, a price-endogenous spatial economic sector model of the Norwegian agriculture. To account for potential effects of climate uncertainty within a given future greenhouse gas emission scenario on farm profitability, effects on conditions that represented the projected climate for 2050 under the emission scenario A1B from the 4th assessment report of the Intergovernmental Panel on Climate Change and four Global Climate Models (GCM) was investigated. The uncertainty about the level of payment rates at the time farmers make their management decisions was handled by varying the distribution of payment rates applied in the Jordmod model. These changes were based on the change in the overall level of agricultural support in the past. Three uncertainty scenarios were developed and tested: one with climate change uncertainty, another with payment rate uncertainty, and a third where both types of uncertainty were combined. The three scenarios were compared with results from a deterministic scenario where crop yields and payment rates were constant. Climate change resulted in on average 9% lower cereal production, unchanged grass production and more volatile crop yield as well as 4% higher farm incomes on average compared to the deterministic scenario. The scenario with a combination of climate change and policy uncertainty increased the mean farm income more than a scenario with only one source of uncertainty. On the other hand, land use and farm labour were negatively affected under these conditions compared to the deterministic case. Highlighting the potential influence of climate change and policy uncertainty on the performance of the farm sector our results underline the potential error in neglecting either of these two uncertainties in studies of agricultural production, land use and welfare. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0308521x |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes  |
CropM, TradeM |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4986 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Zimmermann, A.; Webber, H.; Zhao, G.; Ewert, F.; Kros, J.; Wolf, J.; Britz, W.; de Vries, W. |
|
| |
Title |
Climate change impacts on crop yields, land use and environment in response to crop sowing dates and thermal time requirements |
Type |
Journal Article |
| |
Year |
2017 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
|
| |
Volume |
157 |
Issue |
|
Pages |
81-92 |
|
| |
Keywords |
Integrated assessment; Crop management; Climate change; Europe; INTEGRATED ASSESSMENT; EUROPEAN AGRICULTURE; FOOD SECURITY; HEAT-STRESS; ADAPTATION; SYSTEMS; TEMPERATURE; SCENARIOS; WHEAT; PRODUCTIVITY; Vries W., 2011, ENVIRONMENTAL POLLUTION, V159, P3254 |
|
| |
Abstract |
Impacts of climate change on European agricultural production, land use and the environment depend on its impact on crop yields. However, many impact studies assume that crop management remains unchanged in future scenarios, while farmers may adapt their sowing dates and cultivar thermal time requirements to minimize yield losses or realize yield gains. The main objective of this study was to investigate the sensitivity of climate change impacts on European crop yields, land use, production and environmental variables to adaptations in crops sowing dates and varieties’ thermal time requirements. A crop, economic and environmental model were coupled in an integrated assessment modelling approach for six important crops, for 27 countries of the European Union (EU27) to assess results of three SRES climate change scenarios to 2050. Crop yields under climate change were simulated considering three different management cases; (i) no change in crop management from baseline conditions (NoAd), (ii) adaptation of sowing date and thermal time requirements to give highest yields to 2050 (Opt) and (iii) a more conservative adaptation of sowing date and thermal time requirements (Act). Averaged across EU27, relative changes in water-limited crop yields due to climate change and increased CO2 varied between -6 and + 21% considering NoAd management, whereas impacts with Opt management varied between + 12 and + 53%, and those under Act management between 2 and + 27%. However, relative yield increases under climate change increased to + 17 and + 51% when technology progress was also considered. Importantly, the sensitivity to crop management assumptions of land use, production and environmental impacts were less pronounced than for crop yields due to the influence of corresponding market, farm resource and land allocation adjustments along the model chain acting via economic optimization of yields. We conclude that assumptions about crop sowing dates and thermal time requirements affect impact variables but to a different extent and generally decreasing for variables affected by economic drivers. |
|
| |
Address |
2017-11-02 |
|
| |
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 |
0308-521x |
ISBN |
|
Medium |
article |
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
CropM, TradeM, ft_macsur |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
5178 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Kipling, R.P.; Bannink, A.; Bellocchi, G.; Dalgaard, T.; Fox, N.J.; Hutchings, N.J.; Kjeldsen, C.; Lacetera, N.; Sinabell, F.; Topp, C.F.E.; van Oijen, M.; Virkajärvi, P.; Scollan, N.D. |
|
| |
Title |
Modelling European ruminant production systems: Facing the challenges of climate change |
Type |
Report |
| |
Year |
2017 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
|
|
| |
Volume |
10 |
Issue |
|
Pages |
L1.1-D1 |
|
| |
Keywords |
|
|
| |
Abstract |
Ruminant production systems are important producers of food, support rural communities and culture, and help to maintain a range of ecosystem services including the sequestering of carbon in grassland soils. However, these systems also contribute significantly to climate change through greenhouse gas (GHG) emissions, while intensi- fication of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights into the complexity underlying the relationships between climate change, management and policy choices, food production, and the maintenance of ecosystem services. This paper 1) provides an overview of how ruminant systems modeling supports the efforts of stakeholders and policymakers to predict, mitigate and adapt to climate change and 2) provides ideas for enhancing modeling to fulfil this role. Many grassland models can predict plant growth, yield and GHG emissions from mono-specific swards, but modeling multi-species swards, grassland quality and the impact of management changes requires further development. Current livestock models provide a good basis for predicting animal production; linking these with models of animal health and disease is a prior- ity. Farm-scale modeling provides tools for policymakers to predict the emissions of GHG and other pollutants from livestock farms, and to support the management decisions of farmers from environmental and economic standpoints. Other models focus on how policy and associated management changes affect a range of economic and environmental variables at regional, national and European scales. Models at larger scales generally utilise more empirical approaches than those applied at animal, field and farm-scales and include assumptions which may not be valid under climate change conditions. It is therefore important to continue to develop more realistic representations of processes in regional and global models, using the understanding gained from finer-scale modeling. An iterative process of model development, in which lessons learnt from mechanistic models are ap- plied to develop ‘smart’ empirical modeling, may overcome the trade-off between complexity and usability. De- veloping the modeling capacity to tackle the complex challenges related to climate change, is reliant on closer links between modelers and experimental researchers, and also requires knowledge-sharing and increasing technical compatibility across modeling disciplines. Stakeholder engagement throughout the process of model development and application is vital for the creation of relevant models, and important in reducing problems re- lated to the interpretation of modeling outcomes. Enabling modeling to meet the demands of policymakers and other stakeholders under climate change will require collaboration within adequately-resourced, long-term inter-disciplinary research networks |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
Abstract |
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
LiveM |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4947 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Höglind, M.; the partners of LiveM task L1.3 |
|
| |
Title |
Bringing together grassland and farm scale modelling. Part 1. Characterizing grasslands in farm scale modelling |
Type |
Report |
| |
Year |
2017 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
|
|
| |
Volume |
10 |
Issue |
|
Pages |
L1.3-D |
|
| |
Keywords |
|
|
| |
Abstract |
This report provides an overview of how grasslands are represented in six different farmscale models represented in MACSUR. A survey was conducted, followed by a workshop in which modellers discussed the results of the survey, and identified research challenges and knowledge gaps. The workshop was attended by grassland as well as livestock specialists. The investigated models differed largely with respect to how grasslands were represented, e.g. as regards weather and management factors accounted for, spatial and temporal resolution, and output variables. All models had grassland modules that simulate DM yield and herbage N content (or crude protein (CP) content = N content x 6.25). Many models also simulate P content, whereas only one simulate K content. About half of the model simulate herbage energy value and/or herbage fibre content and fibre and/or dry matter digestibility. Critical input data required from grassland models to simulate ruminant productivity and GHG emissions at farm scale was identified by the workshop participants. The different types of input data required were ranked in order of importance as regards their influence on important system outputs. For simulation of ruminant productivity and GHG emissions, herbage DM yield was ranked as the most important input variable from grassland models, followed by CP content together with at least one variable describing herbage fibre characteristics. These findings suggest that work on improving the ability of the current grassland models with respect to simulation of fibre/energy should be prioritized in farm-scale modelling aiming at quantifying livestock production and GHG emissions under different management regimes and climate conditions. More work is also needed on model evaluation, a task that has not been prioritized yet for some models. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
LiveM |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4957 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
van Middelkoop, J.C.; Kipling, R.P. |
|
| |
Title |
Modelling the impact of climate change on livestock productivity at the farm-scale: An inventory of LiveM outcomes |
Type |
Report |
| |
Year |
2017 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
|
|
| |
Volume |
10 |
Issue |
|
Pages |
L2.4-D |
|
| |
Keywords |
|
|
| |
Abstract |
The report presented here provides an inventory of reports and conference papers produced by the partners of the livestock and grassland modelling theme (LiveM) of the Modelling European Agriculture with Climate Change for Food Security (MACSUR) knowledge hub. The findings presented illustrate the diverse nature of the multidisciplinary LiveM research community, and provide a reference source for those seeking to identify and pull out farm-level modelling outputs from the work of MACSUR and its partners. The survey of farm-scale outputs from LiveM revealed the interdependent, dual role of a knowledge hub: to increase the capacity of modelling to meet stakeholder and societal needs under climate change, and to apply that increased capacity to provide new understanding and solutions at the policy and (the focus here) farm scale. While capacity building work across disciplines is time-consuming, difficult, and to a large extent invisible to stakeholders, such work is vital to ensuring that subsequent scientific outcomes reflect best practice, and integrated expertise. Long term, sustained funding of network-based capacity building activities is highlighted as essential to ensuring that the farm-scale modelling work highlighted here can continue to build on ongoing improvements in model quality, flexibility and stakeholder relevance. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
LiveM |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4958 |
|
| Permanent link to this record |
