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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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Persson, T., Kværnø, S., & Höglind, M. (2015). Impact of soil type extrapolation on timothy grass yield under baseline and future climate conditions in southeastern Norway. Clim. Res., 65, 71–86.
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.
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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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Pasqui, M. (2015). Evaluation of future diurnal variability and projected changes in extremes of precipitation and temperature and their impacts on crop production over regional case studies (e.g. Agroscenari case studies) (Vol. 6).
Abstract: The daily weather of the four decades were used as input to EPIC simulation model to test the effects on crop yield, crop evapotranspiration, number of days with water and nitrogen stress in the silage maize -Italian ryegrass irrigated cropping systems in the Oristanese case study area.The monthly DTR (diurnal temperature range) pattern predicted for the FC (future climate, 2020-2030) indicates that spring and summer months are the most sensitive to DTR increase. The increase ryegrass yield simulated by EPIC under FC was interpreted as the positive effects on increased temperature on the winter-spring grass growth rates. The decreased production of maize was attributed to a shortening of the crop cycle, which reduced the intercepted radiation. The simulations run to assess the pure effect of DTR shift indicated almost no effects on crop yield but significant effects on crop evapotranspiration, whose increase observed under FC was largely associated to DTR, particularly in maize. The stochastic generation of daily weather with WXGEN indicates a sufficient accuracy for average DTR patterns and the central part of the daily DTR distribution, while the range of absolute values increased substantially, in relation to the increased probability of extremes in one century vs one decade.(Abstract supplied by the publisher) No Label
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Pardo, G., Yañez-Ruiz, D., Martin-Garcia, I., Arco, A., Moral, R., & del Prado, A. (2015). Modelling the impact on greenhouse gas emissions of using underutilized feed resources in dairy goat systems. Advances in Animal Biosciences, 6(01), 40–42.
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