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Pirttioja, N. (2015). A crop model ensemble analysis of wheat yield sensitivity to changes in temperature and precipitation across a European transect (Vol. 5).
Abstract: Impact response surfaces (IRSs) were constructed to depict the sensitivity of modelled spring and winter wheat yields to systematic changes in baseline temperature (between -2°C and +9°C) and precipitation (-50 to +50%) as simulated by a 26-member ensemble of process-based crop simulation models. The study was conducted across a latitudinal transect for sites in Finland, Germany and Spain.In spite of large differences in simulated yield responses to both baseline and changed climate between models, sites, crops and years, several common messages emerged. Ensemble average yields decline with warming (3-7% per 1°C) and decreased precipitation (3-9% per 10% decrease), but benefit from increased precipitation (0-8% per 10% increase). Yields are more sensitive to temperature than precipitation changes at the Finnish site while sensitivities are mixed at the other sites. Inter-model variability is highest for baseline climate at the Spanish site but is affected little by changed climate. Model responses diverge most under warming at the Finnish and German sites for winter wheat. The IRS pattern of yield reliability tracks average yield levels.Optimal temperatures for present-day cultivars are below the baseline at the German and Spanish sites suggesting that adoption of cultivars with higher temperature requirements might already be advantageous, and increasingly so at all sites under future warming.The study was conducted in the CropM component of the FACCE-JPI/MACSUR project. No Label
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Persson, T. (2015). Determining the variability in optimal sowing date of spring cereals in South Eastern Norway (Vol. 5).
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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Piayda, A. (2015). The FACCE-ERA-Net Plus project “Climate smart Agriculture on Organic Soils” (CAOS) (Vol. 5).
Abstract: The FACCE-ERA-Net Plus project “Climate smart Agriculture on Organic Soils” (CAOS) focuses on farmed organic soils, hotspots of vulnerability and GHG emissions in Europe. We propose to use wet organic soils as risk insurance in dry periods on farm/regional level, while water and soil management assures trafficability in wet conditions. Wet management systems abate peat degradation and therefore foster higher infiltration rates and ease subirrigation. Economically, wetness-adapted crops with stable yield quantity/quality for food, feed and bioenergy are needed. Convincing farmers and decision makers of profitable and resilient wet management systems on organic soils under climate change needs proof by on-farm experiments, historical evidence and bi-directional involvement.Overall, we aim to generate knowledge of climate smart agricultural system design on organic soils adapted to regional European conditions. CAOS will provide and distribute evidence that active management with control of groundwater levels, improved trafficability and alternative high productivity crops improves yield stability/quality and climate change resilience while mitigating GHG emissions and improving soil/water quality. We hypothesize that the strong potential for adaptation to increased climatic variability on farmed organic soil will facilitate mitigation of the largest GHG source from agriculture in Central/Northern Europe. At MACSUR conference, we present the project concept and first results. No Label
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Palatnik, R. (2015). Economic Impacts of Water Scarcity under Diverse Water Salinities (Vol. 5).
Abstract: Exploitation of alternative water sources is expected to grow in the decades to come in water-stressed countries with fast population growth, especially in regions where a further decline of natural freshwater availability is expected due to climate change. Increasing utilization of non-freshwater usually leads to salinity build-up in fields and water sources as well as accumulation of various pollutants – both having a considerable impact on the suitability of non-freshwater for irrigation due to constraints associated with crop salinity tolerance and food safety regulations.We developed a linked CGE – farm-level model of a water economy with representation for multiple water types characterized by different qualities. We employ the model to assess the impact of water shortage on the Israeli economy, where a steadily growing water scarcity is leading to an increasing utilization of alternative water sources. We simulate water shortage scenarios based on the Long Term National Master Plan for The Water Economy developed by the Israeli Water Authority (IWA).The linked CGE – farm-level model provides a mechanism for estimating the Constant Elasticity of Substitution (CES) rates between different irrigation water types used in agriculture. This mechanism accounts for the effects of salinity on yields and takes into consideration food safety regulations for irrigating crops with treated wastewater. We demonstrate that, in contrast to previous studies, CES rates between different water types are not identical and generally lower than previously assumed – differences that can be attributed to the constraints associated with crop salinity tolerance and food safety regulations.Our results reveal that water shortage can lead to a significant decline of Israel’s GDP, where a considerable part of the decline is attributed to the decrease in agricultural outputs. The magnitude of the impact depends on the underlying assumptions regarding future desalination capacity. To further study the effect of desalination, we run simulations under various desalination levels and examine its impact on the GDP. We also examine the extent to which the impact of water shortage is sensitive to CES rates between different irrigation water types. No Label
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Özkan, S. (2015). The greenhouse gas emissions intensity of herds with mastitis (Vol. 5).
Abstract: Mastitis is an inflammatory disease of milking cows, causing production and economic losses in dairy farms. The main pathogens causing majority of the intramammary infections are Staphylococcus aureus, Streptococcus dysgalactiae, Escherichia coli and coagulase-negative Staphylococci. Here, we analysed the effect of mastitis on herd parameters such as milk yield, feed intake, replacement rate, gross margin and greenhouse gas emissions. The data were collected from the Norwegian Dairy Herd Recording System between 2010 and 2012. The farm data were recorded from 20 farms in Norway, based on health, fertility and breeding characteristics. SimHerd, a computer simulation model was used to estimate the impact of the observed levels of mastitis on herd parameters which were then fed into a whole farm model, HolosNor, to calculate the greenhouse gas emissions on the farm. The standard values provided in the SimHerd except for mastitis occurrence were applied in the scenario simulations. A further study is planned to parameterize each herd with specific herd characteristics in SimHerd so that herd specific estimates of the effect of mastitis on greenhouse gas emissions can be performed. No Label
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