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A whole-farm dairy model was developed and evaluated. The DairyWise model is an empirical model that simulated technical, environmental, and financial processes on a dairy farm. The central component is the FeedSupply model that balanced the herd requirements, as generated by the DairyHerd model, and the supply of homegrown feeds, as generated by the crop models for grassland and corn silage. The output of the FeedSupply model was used as input for several technical, environmental, and economic submodels. The submodels simulated a range of farm aspects such as nitrogen and phosphorus cycling, nitrate leaching, ammonia emissions, greenhouse gas emissions, energy use, and a financial farm budget. The final output was a farm plan describing all material and nutrient flows and the consequences on the environment and economy. Evaluation of DairyWise was performed with 2 data sets consisting of 29 dairy farms. The evaluation showed that DairyWise was able to simulate gross margin, concentrate intake, nitrogen surplus, nitrate concentration in ground water, and crop yields. The variance accounted for ranged from 37 to 84%, and the mean differences between modeled and observed values varied between -5 to +3% per set of farms. We conclude that DairyWise is a powerful tool for integrated scenario development and evaluation for scientists, policy makers, extension workers, teachers and farmers.

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Grazing is inherently close to the nature of herbivores, but no longer applied everywhere in Europe. Therefore, the perception of grassland experts on the occurrence, importance, constraints, solutions and future of grazing of dairy cows was studied. The study builds on results from the European Grassland Federation Working Group Grazing in the period 2010–2019. Both surveys and focus group meetings were used. There is a clear trend of reduced grazing in Europe. Since grazing is valued by different stakeholders and provides many ecosystem services, solutions to the constraints to grazing must be found. Constraints can be divided into region specific constraints, farm specific constraints and farmer specific constraints. The solutions include developing new knowledge, bringing the knowledge already available to practice and rewarding farmers for grazing as a service to society. If grazing is not supported, it will further decline. However, a joined endeavour has the potential to make a significant difference in transforming grass-based production systems and stimulating grazing.

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Emissions of CH4, N2O, and CO2 from soils are the result of a number of biological and physical processes, each influenced by several environmental and management factors exhibiting spatial variability. This study aimed to assess the spatial variability and spatial dependence of CH4, N2O, and CO2 emissions and their underlying soil processes and properties from grasslands on drained peat soil (Terric Histosol). Emissions and possible controlling factors were measured at a field location in Sweden. Measurements were done on two adjacent sites on peat soil on two successive days for each site. Spatial variability was analyzed with trend analysis and variograms. Both sites consumed small amounts of atmospheric CH4, i.e., 0.03 and 0.05 mg CH4 m−2 d−1, and emitted N2O and CO2, i.e., 5 to 19 mg N2O m−2 d−1 and 4 to 6 g CO2 m−2 d−1. Spatial variability of emissions was high, with coefficients of variation of 50 to 1400%. Emissions either showed a spatial trend or were spatially dependent with ranges of spatial dependence of 50 to >200 m. However, spatial dependence of emissions showed differences between sites and short‐term temporal variability. Variograms of emissions and soil processes, which are partly biological in nature and have a high degree of inherent variability, should be interpreted with care.

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