Experiences with iPads in primary schools

Los ordenadores-tablet están acaparando toda la atención en estos momentos y forman parte de nuestra vida cotidiana. Por ello, no es de extrañar que en el ámbito educativo se hayan arbitrado fórmulas para incorporarlos en las aulas. La presente investigación pretende mostrar las estrategias llevadas a cabo en determinadas experiencias con iPads en escuelas primarias austriacas. Por un lado, se describe el desarrollo de las aplicaciones (apps) educativas apropiadas para su empleo en aulas. Y por otro, cada lección apoyada en las tecnologías es analizada y evaluada desde una perspectiva técnica. Las aportaciones más representativas de la investigación evidencian las diversas fórmulas de utilización de este tipo de ordenadores para promover una influencia positiva en la enseñanza, también se apuntan recomendaciones prácticas sobre cómo deberían ser usados en aulasTablet computers gain enormous attention nowadays and become more and more part of our daily life. Due to this it is not astonishing that even the educational sector is thinking about the use of such wearable devices in the classroom. Our research study aims to give insights about real life experiences with iPads in Austrian primary schools. Therefore we describe the development of appropriate learning apps and their use in classrooms. Finally each technology-enhanced lesson is observed as well as evaluated afterwards with the help of the cut-off technique. The research work carries out different circumstances the use of tablet computers has a positive influence on teaching and learning and gives practical hints how they should be used in classrooms.Grupo FORCE (HUM-386). Departamento de Didáctica y Organización Escolar de la Universidad de Granad

Dynamic soil functions assessment employing land use and climate scenarios at regional scale

Soils as key component of terrestrial ecosystems are under increasing pressures. As an advance to current static assessments, we present a dynamic soil functions assessment (SFA) to evaluate the current and future state of soils regarding their nutrient storage, water regulation, productivity, habitat and carbon sequestration functions for the case-study region in the Lower Austrian Mostviertel. Carbon response functions simulating the development of regional soil organic carbon (SOC) stocks until 2100 are used to couple established indicator-based SFA methodology with two climate and three land use scenarios, i.e. land sparing (LSP), land sharing (LSH), and balanced land use (LBA). Results reveal a dominant impact of land use scenarios on soil functions compared to the impact from climate scenarios and highlight the close link between SOC development and the quality of investigated soil functions, i.e. soil functionality. The soil habitat and soil carbon sequestration functions on investigated agricultural land are positively affected by maintenance of grassland under LSH (20 of the case-study region), where SOC stocks show a steady and continuous increase. By 2100 however, total regional SOC stocks are higher under LSP compared to LSH or LBA, due to extensive afforestation. The presented approach may improve integrative decision-making in land use planning processes. It bridges superordinate goals of sustainable development, such as climate change mitigation, with land use actions taken at local or regional scales. The dynamic SFA broadens the debate on LSH and LSP and can reduce trade-offs between soil functions through land use planning processes

Integrated impact modelling of climate change and adaptation policies on land use and water resources in Austria"

Climate change is a major driver of land use and ecosystems. Changes in climatic conditions will affect the quality and quantity of water resources. Autonomous adaptation by farmers can influence the compliance with the good ecological and chemical status according to the EU Water Framework Directive. We present results from an integrated impact modelling framework (IIMF) to analyze policy options for planned adaptation in agricultural land use and sustainable management of land and water resources until 2040. The IIMF consists of the bio-physical process model EPIC, the regional land use optimization model PASMA[grid], the quantitative precipitation/runoff TUW model, and the surface water emission model MONERIS. Stakeholder driven scenarios facilitate multi-actor knowledge transfer. Climate change scenarios are combined with socio-economic and policy pathways. The latter include water protection measures on fertilization management, soil and crop rotation management. The results show that the selected climate change and policy scenarios impact average agricultural gross margins by ±2%. However, regional impacts are more severe particularly under assumptions of decreasing precipitation patterns. The water protection policies can alleviate pressures compared to the business as usual scenario but do not lead to sufficient conditions in all watersheds. To conclude, the IIMF is able to capture the interfaces between water quality and land use and to cover multiple policy and climate scenarios. However, despite efforts to increase the robustness of data and model interfaces, uncertainties need to be tackled in subsequent studies

To what extent is climate change adaptation a novel challenge for agricultural modellers?

Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change

Economic Risk Assessment by Weather-Related Heat Stress Indices for Confined Livestock Buildings: A Case Study for Fattening Pigs in Central Europe

In the last decades, farm animals kept in confined and mechanically ventilated livestock buildings have been increasingly confronted with heat stress (HS) due to global warming. These adverse conditions cause a depression of animal health and welfare and a reduction of the performance up to an increase in mortality. To facilitate sound management decisions, livestock farmers need relevant arguments, which quantify the expected economic risk and the corresponding uncertainty. The economic risk was determined for the pig fattening sector based on the probability of HS and the calculated decrease in gross margin. The model calculation for confined livestock buildings showed that HS indices calculated by easily available meteorological parameters can be used for assessment quantification of indoor HS, which has been difficult to determine. These weather-related HS indices can be applied not only for an economic risk assessment but also for weather-index based insurance for livestock farms. Based on the temporal trend between 1981 and 2017, a simple model was derived to assess the likelihood of HS for 2020 and 2030. Due to global warming, the return period for a 90-percentile HS index is reduced from 10 years in 2020 to 3–4 years in 2030. The economic impact of HS on livestock farms was calculated by the relationship between an HS index based on the temperature-humidity index (THI) and the reduction of gross margin. From the likelihood of HS and this economic impact function, the probability of the economic risk was determined. The reduction of the gross margin for a 10-year return period was determined for 1980 with 0.27 € per year per animal place and increased by 20-fold to 5.13 € per year per animal place in 2030

Reduction of the Economic Risk by Adaptation Measures to Alleviate Heat Stress in Confined Buildings for Growing-Fattening Pigs Modelled by a Projection for Central Europe in 2030

Economic risks for livestock production are caused by volatile commodities and market conditions, but also by environmental drivers such as increasing uncertainties due to weather anomalies and global warming. These risks impact the gross margin of farmers and can stimulate investment decisions. For confined pig and poultry production, farmers can reduce the environmental impact by implementing specific adaptation measures (AMs) to reduce heat stress. A simulation model driven by meteorological data was used to calculate indoor climate for 1981 to 2017. This dataset was extrapolated for a projection in the year 2030. The heat stress was calculated for a business-as-usual livestock building and for several AMs. For 2030, the expected value of the reduction of the gross margin was calculated by EUR 3.98 a−1 per animal place for the business-as-usual scenario. The results show that only energy-saving adaptation measures to reduce the inlet air temperature are appropriate to reduce the economic risk to the level of the year 1980 between EUR 0.03 a−1 and EUR 1.02 a−1 per animal place. The efficiency of other AMs to reduce heat stress is distinctly lower (between EUR 2.62 a−1 and EUR 3.80 a−1 per animal place). The results in this study can support the decision making of farmers concerning adaptation management and investments. It can inform agricultural policy design as well as technological development

Reduction of the Economic Risk by Adaptation Measures to Alleviate Heat Stress in Confined Buildings for Growing-Fattening Pigs Modelled by a Projection for Central Europe in 2030

Economic risks for livestock production are caused by volatile commodities and market conditions, but also by environmental drivers such as increasing uncertainties due to weather anomalies and global warming. These risks impact the gross margin of farmers and can stimulate investment decisions. For confined pig and poultry production, farmers can reduce the environmental impact by implementing specific adaptation measures (AMs) to reduce heat stress. A simulation model driven by meteorological data was used to calculate indoor climate for 1981 to 2017. This dataset was extrapolated for a projection in the year 2030. The heat stress was calculated for a business-as-usual livestock building and for several AMs. For 2030, the expected value of the reduction of the gross margin was calculated by EUR 3.98 a−1 per animal place for the business-as-usual scenario. The results show that only energy-saving adaptation measures to reduce the inlet air temperature are appropriate to reduce the economic risk to the level of the year 1980 between EUR 0.03 a−1 and EUR 1.02 a−1 per animal place. The efficiency of other AMs to reduce heat stress is distinctly lower (between EUR 2.62 a−1 and EUR 3.80 a−1 per animal place). The results in this study can support the decision making of farmers concerning adaptation management and investments. It can inform agricultural policy design as well as technological development

To what extent is climate change adaptation a novel challenge for agricultural modellers?

Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change. © 2019 The Author