MACSUR Literature Database -- Query Results

Nieróbca, A. (2015). The regional trends in maize yield in Poland and its prediction according regional GLOBIOM –CAPRI baseline analysis for 2010, 2030 and 2050 (Vol. 5). Abstract: The increase of maize production in Polish agriculture is considered as one of the indicators showing temporal climate change impact. The sowing area of grain maize in Poland increased from 152 thousand hectares in 2000 to 614 thousand hectares in 2013. In the same time, the area of maize production for forage in Poland has increased from 162 to 462 thousand hectares. There is observed increase of yield level but the regional differentiation of this trend is also visible. In the paper we discuss the temporal regional trends in maize yield in Poland connected to the limitation factors (soil, climate, fertilisation) and prognosis for further climate change impact using GLOBIOM-CAPRI regional simulations. The data for the analysis of regional trends for maize production level in 16th regions in Poland (NUTS2) were taken from National Statistical Offices Reports. The GLOBIOM-CAPRI regional simulations for baseline analysis 2010, 2030 and 2050 were obtained from MASCUR knowledge-hab evaluation exercises. As a limitation factors for of maize yield we considered the index for suitable soil and climate suitability index for climate developed in Poland and fertilisation. We have identified that observed positive trend in yield level at NUTS2 is correlated with the climate suitability index and level of NPK fertilisation, whilst there is no statistical relations with soil quality index. The GLOBIOM –CAPRI regional simulation for 2030 shows that the maize yield in Poland will further increase and it can be explained by realisation of existing trends. In simulations for the baseline 2050 year there is visible negative trend in yield level in some regions, where even in current climate there is high probability of deficit precipitation (eg. Wielkopolskia region). No Label http://reference.macsur.eu/show.php?record=2155
Mittenzwei, K. (2015). The importance of climate and policy uncertainty in Norwegian agriculture (Vol. 5). Abstract: The paper addresses future climate and policy uncertainty for agricultural production and food security in Norway. The two crop simulation models, CSM-CERES-Wheat and, the LINGRA model, were used to determine the impact of climate change on grain yield of spring wheat, and harvest security and biomass yield of timothy, an important forage grass in Northern Europe, respectively. Harvestable yield distributions from the crop models were fed into a stochastic version of the economic sector model Jordmod. Distributions of the rates of agricultural subsidies rates were assessed based on past policy changes and prospective reforms. The model was used to assess the effects of both climate and policy uncertainty on agricultural production, land use, and national food security. Jordmod is comprised of a supply module in which stochastic profits for more than 300 regional farms are maximized and a deterministic market module which maximizes social welfare in the agricultural sector. Socio-economic scenarios were developed around the level of ambition of Norwegian agricultural policy makers. The model results were contrasted with the deterministic results based on average yield and payment rates. The innovation of this paper lays in assessing the combined effects of future climate and policy uncertainty for the agricultural sector in Norway. It also highlights the potential errors made by neglecting these types of uncertainty in economic modelling. No Label http://reference.macsur.eu/show.php?record=2154
Martre, P. (2015). Reducing uncertainty in prediction of wheat performance under climate change (Vol. 5). Abstract: Projections of climate change impacts on crop performances are inherently uncertain. However, multimodel uncertainty analysis of crop responses is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we report on the Agricultural Model Intercomparison and Improvement Project ensemble of 30 wheat models tested using both crop and climate observed data in diverse environments, including infra-red heating field experiments, for their accuracy in simulating multiple crop growth, N economy and yield variables. The relative error averaged over models in reproducing observations was 24-38% for the different end-of-season variables. Clusters of wheat models organized by their correlations with temperature, precipitation, and solar radiation revealed common characteristics of climatic responses; however, models are rarely in the same cluster when comparing across sites. We also found that the amount of information used for calibration has only a minor effect on model ensemble climatic responses, but can be large for any single model. When simulating impacts assuming a mid-century A2 emissions scenario for climate projections from 16 downscaled general circulation models and 26 wheat models, a greater proportion of the uncertainty in climate change impact projections was due to variations among wheat models rather than to variations among climate models. Uncertainties in simulated impacts increased with atmospheric [CO2] and associated warming. Extrapolating the model ensemble temperature response (at current atmospheric [CO2]) indicated that warming is already reducing yields at a majority of wheat-growing locations. Finally, only a very weak relationship was found between the models’ sensitivities to interannual temperature variability and their response to long-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs. In conclusion, uncertainties in prediction of climate change impacts on crop performance can be reduced by improving temperature and CO2 relationships in models and are better quantified through use of impact ensembles. No Label http://reference.macsur.eu/show.php?record=2153
Lehtonen, H. (2015). Sector level agricultural development following different adaptations to climate change (Vol. 5). Abstract: Future crop yields in northern Europe are subject to many factors and uncertainties, according to recent agro-ecological studies. Based on our farm level analysis, we concluded that prices of agricultural products are the primary drivers in the adaptation to climate change. They, as well as the policy conditions, affect the level of fertilization and the use of other inputs, land use and the intensity and the volume of agricultural production. We outlined 5 main scenarios of agricultural adaptation in Finland, and used an agricultural sector model to assess the impacts of the 5 scenarios on total production and land use in the whole country and in its four main regions. In the scenarios with unchanged product prices in the real terms, we find that a small increase or decrease in crop yields is possible. Significantly higher yields would require also 20-30% higher prices of crop products. Our sector modeling results suggest that avoiding decreases in crop yields is important for agricultural income in the long-term, even if livestock production in also maintained by national subsidies. Decreasing yields will result in increasing nutrient surplus and most likely in increased nutrient leaching, while increasing crop yields, even slightly, would significantly decrease nutrient surplus and increase farm income. Significant increases in crop yields and prices, however, are required before production clearly increases in Finland. Interestingly, cereals production would increase relatively more than livestock production, in the case of high future prices. This is explained by the abundant land resources, as well as the high opportunity cost of labor and policy systems maintaining current livestock production. No Label http://reference.macsur.eu/show.php?record=2151
Lessire, F. (2015). Effects of heat stress periods on milk production, milking frequency and rumination time of grazing dairy cows milked by a mobile automatic system in 2013 (Vol. 5). Abstract: In Europe, analysis of meteorological data shows that the average temperature has increased by ~1°C over the past hundred years (IPCC, 2013). Heat stress periods are thus expected to be more frequent even in temperate areas. The use of an automatic milking system (AMS) implies the need to stimulate cows’ traffic to the robot, especially with grazing cows. Describing how heat stress influenced cows’ traffic to the robot is the aim of this study.Grazing dairy cows milked by an automatic system (AMS) experienced heat stress (HS) periods, twice during the summer 2013 in July (J) and August (A). The daily temperature humidity index (THI) during these periods were higher than 75. Each HS period was compared with a “normal period”(N), presenting the same number of cows, similar lactation number, days in milk, distance to come back to the robot and an equal access to water. The first HS period of 5 days with a mean THI of 78.4 was chosen in J, and a second that lasted for 6 days in A with a THI value of 77.3. Heat stress periods were cut off with the same duration of days with no stress (N) and mean THI <70. Milk production, milkings and returns to the robot during HS were compared with N periods.Milkings and visits to AMS were significantly more numerous in HS periods in July (HS: 2.44 vs N: 2.23, 3.97 vs 3.03) but milk production dropped from 20.3 kg to 19.3 kg milk per cow and per day. In August, MY increased slightly during HS. This could be explained by less high ambient temperatures and decreased distance to walk inducing less energy expenditure. The increase in milkings and visits to the robot during HS could be linked to water availability nearby the robot and confirmed previous findings (Lessire et al., 2014). No Label http://reference.macsur.eu/show.php?record=2152

Nieróbca, A. (2015). The regional trends in maize yield in Poland and its prediction according regional GLOBIOM –CAPRI baseline analysis for 2010, 2030 and 2050 (Vol. 5).

Mittenzwei, K. (2015). The importance of climate and policy uncertainty in Norwegian agriculture (Vol. 5).

Martre, P. (2015). Reducing uncertainty in prediction of wheat performance under climate change (Vol. 5).

Abstract: Projections of climate change impacts on crop performances are inherently uncertain. However, multimodel uncertainty analysis of crop responses is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we report on the Agricultural Model Intercomparison and Improvement Project ensemble of 30 wheat models tested using both crop and climate observed data in diverse environments, including infra-red heating field experiments, for their accuracy in simulating multiple crop growth, N economy and yield variables. The relative error averaged over models in reproducing observations was 24-38% for the different end-of-season variables. Clusters of wheat models organized by their correlations with temperature, precipitation, and solar radiation revealed common characteristics of climatic responses; however, models are rarely in the same cluster when comparing across sites. We also found that the amount of information used for calibration has only a minor effect on model ensemble climatic responses, but can be large for any single model. When simulating impacts assuming a mid-century A2 emissions scenario for climate projections from 16 downscaled general circulation models and 26 wheat models, a greater proportion of the uncertainty in climate change impact projections was due to variations among wheat models rather than to variations among climate models. Uncertainties in simulated impacts increased with atmospheric [CO2] and associated warming. Extrapolating the model ensemble temperature response (at current atmospheric [CO2]) indicated that warming is already reducing yields at a majority of wheat-growing locations. Finally, only a very weak relationship was found between the models’ sensitivities to interannual temperature variability and their response to long-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs. In conclusion, uncertainties in prediction of climate change impacts on crop performance can be reduced by improving temperature and CO2 relationships in models and are better quantified through use of impact ensembles. No Label

http://reference.macsur.eu/show.php?record=2153

Lehtonen, H. (2015). Sector level agricultural development following different adaptations to climate change (Vol. 5).

Lessire, F. (2015). Effects of heat stress periods on milk production, milking frequency and rumination time of grazing dairy cows milked by a mobile automatic system in 2013 (Vol. 5).