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

Multi-scale Modelling of Adapting European Farming Systems

European farming systems are challenged by an increasing global population, income growth, dietary changes and last, but not least, by a changing climate threatening future harvests, especially through increased frequency and severity of extreme events such as drought and heat waves. Therefore, there is a clear need to sustainably intensify and effectively adapt agricultural systems to climate change. Yet, increase in food production and adaptation are just two of many claims on agriculture, which is also supposed to meet growing demands on feed, fibre and fuel and to play a key role in mitigating climate change. The multiple claims on ecosystem services expected from agri-ecological systems call for an integrated assessment and modelling (IAM) of agricultural systems to adequately evaluate the multiple dimensions of the potential impacts as well as promising adaptation and mitigation options. This includes agriculture's responses to global change in the context of other sustainability aspects. Biophysical and socioeconomic analyses need to be integrated across different disciplines and spatiotemporal scales. In recent years the agricultural systems modelling community has made great efforts to use harmonized climate change, socio-economic and agricultural development scenarios and run them through a chain of models, e.g. by selected ensembles of biophysical and economic models at multiple scales, from farm to global. In phase 2 (2015-17) the European MACSUR knowledge hub has put its main focus on the regional (sub-national) level in the EU, with due consideration of the whole farm context. The aim of this paper is to compare three regional cases from the pool of MACSUR case studies across Europe, i.e. North Savo region in Finland, the Mostviertel region in Austria and the Oristanese region in Sardinia (Italy) representing different European farming systems along a north-south climatic gradient in Europe. These case studies represent a sample of some prominent farming systems, though only a fraction of a much larger diversity of farming and environmental conditions prevailing in Europe. We describe how adaptation options are analysed within an integrated set of linked models or model outputs combining information from different spatial scales, i.e. from region-specific crop, animal and farm level models to an analysis at regional and national level changes in agriculture and food production. First results show that adaptation to climate change affects agricultural production and farm income very differently. For some regions, e.g. in Finland there are both negative and positive effects while for the Sardinian case study adaptation to climate change have negative effects on farm income. Biophysical models, especially crop simulation models are first applied to analyse climate change impacts on yield, water use, biomass etc. and provide the outputs (i.e. delta changes) as input to economic models that contain the regional specificities of the case studies. Likewise, biophysical models are applied to analyse effects of various adaptation and mitigation options to provide information on effects of management changes on reducing damage/loss or taking opportunities from climate (adaptation) or reducing greenhouse gas emissions (mitigation). The economic models analyse economic impacts, for example the viability of management changes at farm and regional scales. Farm and regional scale economic models, backed by more detailed data and regional expert knowledge, can supply better representations of developments in each of the regions than this could be done by larger-scale (e.g. EU-wide or global) models. Sector or national economy-wide models are less specific in technical changes in agriculture, productivity changes, or in its use of inputs, due to higher level of aggregation. Nevertheless the market level view offered by sector models put the farm level changes and adaptations in a wider global context. Agricultural markets are highly integrated globally and the analyses for the case study regions also require information on global and European market developments. For example, significant changes in food demand due to changes in tastes and preferences, including aspects of climate change mitigation, may imply major changes for regional production structures. In MACSUR, this information – although not fully implemented in the case studies yet – is provided by the economic agricultural sector model CAPRI. The main strength of CAPRI in this context is that it is a global model with European focus. As such CAPRI can capture global developments and translate them to the regional level in the EU. The coupled analysis using global, EU and national level models side by side with farm level models provides unique results and much more insights on future possibilities and challenges for farmers and the food chain, than separating and restricting the analyses to either low or high aggregation level analyses. Market and policy changes often dominate longer term climate change considerations in the decision making of food chain actors, even if unfavourable weather events have become more common in recent years. Socio-economic scenarios from global to national and regional levels are needed to put adaptation and mitigation strategies in a wider context. Models, especially those that are able to accommodate biophysical, economic and policy changes are needed to show the value added from adaptations to climate change. Benefits and costs of mitigation strategies may be highly dependent on market developments. The current integrated assessment and modelling approach of MACSUR focusses on adaptation scenarios. It will be extended for the analysis and impact of mitigation policies in a later phase

Multi-scale Modelling of Adapting European Farming Systems

European farming systems are challenged by an increasing global population, income growth, dietary changes and last, but not least, by a changing climate threatening future harvests, especially through increased frequency and severity of extreme events such as drought and heat waves. Therefore, there is a clear need to sustainably intensify and effectively adapt agricultural systems to climate change. Yet, increase in food production and adaptation are just two of many claims on agriculture, which is also supposed to meet growing demands on feed, fibre and fuel and to play a key role in mitigating climate change. The multiple claims on ecosystem services expected from agri-ecological systems call for an integrated assessment and modelling (IAM) of agricultural systems to adequately evaluate the multiple dimensions of the potential impacts as well as promising adaptation and mitigation options. This includes agriculture's responses to global change in the context of other sustainability aspects. Biophysical and socioeconomic analyses need to be integrated across different disciplines and spatiotemporal scales. In recent years the agricultural systems modelling community has made great efforts to use harmonized climate change, socio-economic and agricultural development scenarios and run them through a chain of models, e.g. by selected ensembles of biophysical and economic models at multiple scales, from farm to global. In phase 2 (2015-17) the European MACSUR knowledge hub has put its main focus on the regional (sub-national) level in the EU, with due consideration of the whole farm context. The aim of this paper is to compare three regional cases from the pool of MACSUR case studies across Europe, i.e. North Savo region in Finland, the Mostviertel region in Austria and the Oristanese region in Sardinia (Italy) representing different European farming systems along a north-south climatic gradient in Europe. These case studies represent a sample of some prominent farming systems, though only a fraction of a much larger diversity of farming and environmental conditions prevailing in Europe. We describe how adaptation options are analysed within an integrated set of linked models or model outputs combining information from different spatial scales, i.e. from region-specific crop, animal and farm level models to an analysis at regional and national level changes in agriculture and food production. First results show that adaptation to climate change affects agricultural production and farm income very differently. For some regions, e.g. in Finland there are both negative and positive effects while for the Sardinian case study adaptation to climate change have negative effects on farm income. Biophysical models, especially crop simulation models are first applied to analyse climate change impacts on yield, water use, biomass etc. and provide the outputs (i.e. delta changes) as input to economic models that contain the regional specificities of the case studies. Likewise, biophysical models are applied to analyse effects of various adaptation and mitigation options to provide information on effects of management changes on reducing damage/loss or taking opportunities from climate (adaptation) or reducing greenhouse gas emissions (mitigation). The economic models analyse economic impacts, for example the viability of management changes at farm and regional scales. Farm and regional scale economic models, backed by more detailed data and regional expert knowledge, can supply better representations of developments in each of the regions than this could be done by larger-scale (e.g. EU-wide or global) models. Sector or national economy-wide models are less specific in technical changes in agriculture, productivity changes, or in its use of inputs, due to higher level of aggregation. Nevertheless the market level view offered by sector models put the farm level changes and adaptations in a wider global context. Agricultural markets are highly integrated globally and the analyses for the case study regions also require information on global and European market developments. For example, significant changes in food demand due to changes in tastes and preferences, including aspects of climate change mitigation, may imply major changes for regional production structures. In MACSUR, this information – although not fully implemented in the case studies yet – is provided by the economic agricultural sector model CAPRI. The main strength of CAPRI in this context is that it is a global model with European focus. As such CAPRI can capture global developments and translate them to the regional level in the EU. The coupled analysis using global, EU and national level models side by side with farm level models provides unique results and much more insights on future possibilities and challenges for farmers and the food chain, than separating and restricting the analyses to either low or high aggregation level analyses. Market and policy changes often dominate longer term climate change considerations in the decision making of food chain actors, even if unfavourable weather events have become more common in recent years. Socio-economic scenarios from global to national and regional levels are needed to put adaptation and mitigation strategies in a wider context. Models, especially those that are able to accommodate biophysical, economic and policy changes are needed to show the value added from adaptations to climate change. Benefits and costs of mitigation strategies may be highly dependent on market developments. The current integrated assessment and modelling approach of MACSUR focusses on adaptation scenarios. It will be extended for the analysis and impact of mitigation policies in a later phase

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

Bringing the sharing-sparing debate down to the ground—Lessons learnt for participatory scenario development

The concepts of Land Sharing (LSH) and Land Sparing (LSP) shall help to manage trade-offs between land use and biodiversity conservation but applications in real world contexts are scarce. We review the literature on scenario and stakeholder processes and present a participatory approach to translate the LSH/LSP concept into practice. It is based on a scenario definition process harmonized across five case studies in Europe and resulted in semi-quantitative participative LSH and LSP scenarios. Harmonization eases comparability among case studies despite fundamentally different scenarios due to heterogeneous conditions across the regions. A key challenge was the right level of standardization for the scenario process to reach a common understanding across case study regions while acknowledging regional peculiarities. The resulting scenarios support for regional specific planning recommendations and can be input to quantitative ecosystem service and biodiversity models

Developing stakeholder-driven scenarios on land sharing and land sparing – Insights from five European case studies

Empirical research on land sharing and land sparing has been criticized because preferences of local stakeholders, socio-economic aspects, a bundle of ecosystem services and the local context were only rarely integrated. Using storylines and scenarios is a common approach to include land use drivers and local contexts or to cope with the uncertainties of future developments. The objective of the presented research is to develop comparable participatory regional land use scenarios for the year 2030 reflecting land sharing, land sparing and more intermediate developments across five different European landscapes (Austria, Germany, Switzerland, The Netherlands and Spain). In order to ensure methodological consistency among the five case studies, a hierarchical multi-scale scenario approach was developed, which consisted of i) the selection of a common global storyline to frame a common sphere of uncertainty for all case studies, ii) the definition of three contrasting qualitative European storylines (representing developments for land sharing, land sparing and a balanced storyline), and iii) the development of three explorative case study-specific land use scenarios with regional stakeholders in workshops. Land use transition rules defined by stakeholders were used to generate three different spatially-explicit scenarios for each case study by means of high-resolution land use maps. All scenarios incorporated various aspects of land use and management to allow subsequent quantification of multiple ecosystem services and biodiversity indicators. The comparison of the final scenarios showed both common as well as diverging trends among the case studies. For instance, stakeholders identified further possibilities to intensify land management in all case studies in the land sparing scenario. In addition, in most case studies stakeholders agreed on the most preferred scenario, i.e. either land sharing or balanced, and the most likely one, i.e. balanced. However, they expressed some skepticism regarding the general plausibility of land sparing in a European context. It can be concluded that stakeholder perceptions and the local context can be integrated in land sharing and land sparing contexts subject to particular process design principles

Representative Agricultural Pathways (RAPs) for Austria: conceptual thoughts on its demand and stakeholder-driven development.

Modelling communities in climate change research developed so-called Shared Socioeconomic Pathways (SSPs), which can be attributed to particular Representative Concentration Pathways (RCPs). SSPs are available at global to continental scales and describe major socio-economic developments. Such resolution is insufficient in particular for global to local mitigation, adaptation, and impact studies in agriculture. Hence, Representative Agricultural Pathways (RAPs) shall overcome this gap by developing narratives of plausible potential futures for the agricultural sector at regional to national scale. They should be consistent with SSPs and RCPs. These RAPs narratives are operationalized by variables and parameters usable in bio-physical and economic modeling of farms, landscapes and the agricultural and food sector.In our presentation, we argue that there is demand of RAPs in local to regional land use studies up to the national scale. RAPs contribute to increase the consistency of climate change studies across scales and enhance harmonization of inputs and comparability of results. They are a service to the research community to save resources in scenario development. In the second part of the talk, we present a methodology for a stakeholder-driven design of RAPs. We refer to methodologies for RAPs-development in international studies and identify necessary deviations to take into account idiosyncratic features of Austria, which is our country of interest. Stakeholder engagement during the definition of RAPs may improve the acceptance of modelling results among practitioners and foster its implementation in policy processes. Besides, the process itself can stimulate a debate on the future of agriculture under climate change and its inherent uncertainties

Spatial analysis of maize cropping systems to relieve crop pest pressure in Austria

Maize production in Austria is at risk because few appropriate pest control measures are currently available. Production opportunities change if pests reach economically relevant levels. In the case of the Western Corn Rootworm (Dicabrotica virgifera virgifera), intensive maize production contributes to population establishment and vice versa leads to maize yield losses. We assess the opportunity costs of crop rotations at different levels of pest pressure. Additionally, maize is substituted by other crops in crop rotations due to policy regulations. Results show that the substitution of maize by other crops reduces gross margins of crop rotations, but vulnerability to pest pressure in terms of yield losses exceeds the impacts of alternative crops on gross margins. Monitoring results and analyses of crop production in Austria point out the close relationship between pest populations and maize cropping in the last decade. Thus, there is a demand for spatially explicit modeling of pest control measures. In the outlook of this paper, potential approaches for integrated and coordinated pest management implementation at the landscape scale are described