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Sinabell, F. (2014). Adaptation in Austrian cattle and milk production. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Climate change will pose considerable challenges to Austrian agriculture which will likely be affected by a higher frequency of extreme weather events and more volatile commodity prices. We want to analyse the spatial, economic and social dimension of this threat by exploring expected consequences for the most important agricultural activity in Austria, cattle and dairy farming. We will evaluate a broad bouquet of adaptation measures from both, the perspective of the single farm as well as from the agricultural policy perspective. By aligning scenarios on projections of climate conditions and socio-economic developments with those developed in the EU MACSUR project (www.macsur.eu), the results will be consistent with state of the art analyses on climate change in Europe. By integrating results from a well established life cycle analysis model that will be specified to the Austrian situation we will broaden the spectrum of existing knowledge substantially. The results will allow policy makers to base their decisions on evidence that is not limited to the Austrian situations but includes spillover effects to foreign countries as well. Farmers willbe able to benefit directly from results of this project because stakeholders from the farm sector are part of the analyses from the beginning. An additional benefit of the project is that it is closely integrated to the activities of the international network of researchers working on climate change and food security in Europe.
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Nguyen, T. P. L., Seddaiu, G., Tidore, C., & Roggero, P. P. (2014). Adaptation to climate change of Italian agricultural systems: the analysis of explorative scenarios. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Adaptation of agricultural systems to climate uncertainties requires the construction of scenarios that should take into account the complexities of socio-ecological systems of a specific local context. Adaptation scenarios of agricultural systems are not making forecasts or predictions, but prospective futures or future paths. They can facilitate our understanding of how systems work and evolve. Adaptation processes of agricultural systems involve a variety of changes in local practices and social organization. The development of adaptation scenarios at farm level entails a clear understanding of farmers’ frames that are mediated by their interests, experiences and internal and external forces. Farmers’ frames is the way in which farmers frame climate issues emphasizing vulnerabilities, uncertainties and opportunities (i.e: impacts on their farming systems) and open the window for searching adaptation strategies. This study reports on the methodologies for the development of explorative scenarios (i.e., scenarios that explore the future from a variety of perspectives) for the climate change adaptation of four agricultural systems (intensive dairy cattle, extensive dairy sheep, rice farming and horticulture) in the Oristano regional pilot study in Italy. Explorative scenarios were used to explore trends into the future from the past and present. Three research steps were followed: (i) in the first step farmers’ perceptions and prospective through semi-structured interviews and questionnaires were analysed; (ii) in the second step the evolution of the agricultural systems (i.e. temporal and spatial) was evaluated; (iii) the third step examined multiple stakeholders’ outlooks about farm-level possible adaptive strategies through interactive workshops.
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Rivington, M. (2014). Agrimod: The Agricultural Modelling Knowledge Hub Website. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Agrimod is a new web-based Agricultural Modelling Knowledge Hub covering crop, livestock and trade models and the data they require, plus a wide range of supporting tools and resources. The purpose is to address the growing need, particularly in developing countries, of building national capabilities for researching agriculture and food security using models. To support research in this area, Agrimod provides a facility enabling users to access information and data needed to more successfully develop and employ agricultural modelling. Registered users can add new information about models, data, case studies, training, funding sources etc., whilst also being able to edit existing content and contribute to discussion threads on key modelling issues. It will serve as a model, data and case study inventory. The vision is to unite the existing agricultural modelling community by providing a platform whereby models can be showcased, their applications discussed and new collaborations built, streamlining the process by which new model activities are developed. Moreover, Agrimod is intended to be a user–friendly information portal to people in other areas of research or new to agricultural modelling, looking to develop skills and acquire first-hand knowledge on agricultural modelling research. Thus Agrimod serves as a central knowledge hub for information on agricultural modelling activities worldwide and can be used by MACSUR as a complimentary information dissemination tool.
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Weihermüller, L. (2014). AgroC – Development and first evaluation of a model for carbon fluxes in agroecosystems. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Agroecosystems are highly sensitive to climate change. To predict and describe the processes, interactions and feedbacks in the plant-soil-system a model accounting for both compartments at an appropriate level of complexity is required.To describe the processes of crop development, crop growth, water flux, heat transport, and carbon cycling three process models were coupled and adjusted to each other: the one-dimensional soil water, heat and CO2 transport model SOILCO2, the carbon turnover model RothC, and the plant growth model SUCROS. Thereby, the main focus was on the full description of the CO2 flux into the atmosphere via plant and soil processes and finally on simulating the net ecosystem exchange. Additionally, the model was modified to work at the temporal resolution between 0.5 and 24 hours.For a first model evaluation a winter wheat data set obtained within the TERENO Rur catchment (North Rhine-Westphalia, Germany) during 2009 was used. For model initialisation soil carbon fractions were available. Plant specific parameters and soil properties were taken from literature. Measured soil water contents, soil temperatures, crop measurements, autotrophic, and heterotrophic chamber-based respiration measurements were used for validation and calibration.The coupled agroecosystem model AgroC described the crop development and heat transport well. Minor adjustments had to be made for carbon cycling, and to adapt the model to site specific conditions the soil hydraulic coefficients for soil water transport had to be determined by inverse modelling.
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Van den Pol-van Dasselaar, A., Bellocchi, G., Hutchings, N., Olesen, J., & Saetnan, E. (2014). AnimalChange. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The EU-FP7 project AnimalChange (AN Integration of Mitigation and Adaptation options for sustainable Livestock production under climate CHANGE, http://www.animalchange.eu, 2011-2015) addresses mitigation and adaptation options and provides scientific guidance for their integration in sustainable development pathways for livestock production under climate change in Europe, Northern and Sub-Saharan Africa, and Latin America. The project provides insights, innovations, tools and models for livestock production incorporating socio-economic and environmental (particularly GHG emission) variables. Scenario studies are carried out at scales ranging from animal and pasture, to farm and to region, for given management options. A wide range of livestock production systems is included in the project. The core analytical spine of the project is a series of coupled biophysical and socio-economic models combined with experimentation. This allows exploring future scenarios for the livestock sector under baseline and atmospheric CO2 stabilization scenarios. These scenarios are first constructed and then elaborated and enriched by breakthrough mitigation and adaptation options at field and animal scales, integrated and evaluated at farm scale and finally used to assess policy options and their socio-economic consequences. The modelling results are useful for governments, agricultural and food industry and the agricultural sector (farmers). There are many synergies between the European activities of AnimalChange and those of the LiveM theme of MACSUR, in particular with respect to access to livestock production datasets, dialogue with stakeholders and comparison and integration of grassland and livestock models with crop and socio-economic models in pilot studies at a variety of scales.
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