2011
DOI: 10.1007/s10584-011-0171-0
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Abstract: Climate change affects major biophysical processes in agricultural crop production (e.g. evaporation of plants and soils, nutrient cycles, and growth of plants). This analysis aims to assess some of these effects by simulating regional climate projections that are integrated in the biophysical process model EPIC (Environmental Policy Integrated Climate). Statistical climate models have been developed for six weather parameters based on daily weather records of a weather station in the Austrian Marchfeld region… Show more

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Cited by 35 publications
(16 citation statements)
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References 24 publications
(35 reference statements)
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“…5). Aurbacher et al (2013) and Strauss et al (2012) also found a minor increase in summer crop yields due to preponed sowing dates, but, like in the present study, the authors did not consider adapted or improved cultivars, which may exhibit a higher yield potential, especially in combination with longer growth periods. Findings by Olesen et al (2012) further confirm the increasing relevance of preponed sowing dates under conditions of climate change.…”
Section: Modification Of Sowing and Harvesting Datescontrasting
confidence: 52%
“…5). Aurbacher et al (2013) and Strauss et al (2012) also found a minor increase in summer crop yields due to preponed sowing dates, but, like in the present study, the authors did not consider adapted or improved cultivars, which may exhibit a higher yield potential, especially in combination with longer growth periods. Findings by Olesen et al (2012) further confirm the increasing relevance of preponed sowing dates under conditions of climate change.…”
Section: Modification Of Sowing and Harvesting Datescontrasting
confidence: 52%
“…Soil data are extracted from [41] and contain soil layer specific contents of silt, sand and clay, humus, pH, calcium carbonate, and coarse fragments. Up to 25 crop rotation systems per municipality have been derived with the CropRota model [42] using historical land use data of 22 crops [32]. These crops, respectively crop rotations, cover about 89% of total arable land in Austria.…”
Section: Dry Day Indexmentioning
confidence: 99%
“…To the best of our knowledge, this is the only prior study that simultaneously considered the N and P inputs with P carryover in an economic analysis of crop production. The joint impact of N and P inputs on crop yield was explicitly considered in dynamic crop growth simulation models, such as DAISY [19], HYPE [20], APSIM [21], and EPIC [22,23], and in decision support systems for agrotechnology transfer like DSSAT [24]. Although these models provide a rich and detailed description of the processes driving the yield response, they are not directly suited to dynamic economic optimization due to the large number of state variables and the extensive data requirements [25].…”
Section: Introductionmentioning
confidence: 99%