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Author Bellocchi, G.; Ma, S.; Köchy, M.; Braunmiller, K.
Title Datasets classification and criteria for data requirements Type Report
Year 2013 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 2 Issue Pages D-L2.1.2
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Abstract This deliverable focuses on the collation, screening, and consolidation of data for selected grassland sites in Europe and peri-Mediterranean regions. No Label
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Call Number MA @ admin @ Serial 2245
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Author Bellocchi, G.; Ma, S.; Köchy, M.; Braunmiller, K.
Title Identified grassland-livestock production systems and related models Type Report
Year 2013 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 2 Issue Pages D-L2.1.1
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Abstract This report describes grassland-livestock production systems, as selected for model-basedstudies. A list of grassland models was identified for evaluation against such datasets(WP2) and application at reference farm (WP3) and regions (WP4) across Europe and peri-European countries. No Label
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Call Number MA @ admin @ Serial 2244
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Author Rolinski, S.; Sætnan, E.
Title Uncertainties in climate change prediction and modelling Type Report
Year 2013 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 1 Issue Pages D-L1.5
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Abstract As models become increasingly complex and integrated, uncertainty among model  parameters, variables and processes become critical for evaluating model outcomes and  predictions. A framework for understanding uncertainty in climate modelling has been  developed by the IPCC and EEA which provides a framework for discussion of uncertainty  in models in general. Here we report on a review of this framework along with the results  of a survey of sources of uncertainty in livestock and grassland models. Along with the  identification of key sources of uncertainty in livestock and grassland modelling, the  survey highlighted the need for a development of a common typology for uncertainty.  When collaborating across traditionally separate research fields, or when communicating  with stakeholders, differences in understanding, interpretation or emphasis can cause  confusion. Further work in MACSUR should focus on improving model intercomparison  methods to better understand model uncertainties, and improve availability of high  quality datasets which can reduce model uncertainties. No Label
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Call Number MA @ admin @ Serial 2259
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Author Kipling, R.; Topp, K.; Don, A.
Title The availability of carbon sequestration data in Europe Type Report
Year 2015 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 4 Issue Pages D-L1.4.2
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Abstract With growing interest in the carbon sequestration potential of soils, experimental research and mapping projects have produced a wealth of datasets in this subject area. However, the coverage, quality and scope of available data vary widely across Europe, and the extent to which these data are accessible to experimental researchers and modellers is also highly variable. This report describes the availability of soil carbon data at the global and European levels, and reviews the on-line resources for accessing these data and meta-data. The extent to which researchers in the field share findings, based on institutional links in projects and on-line resources, is investigated. Future priorities for research and data accessibility relating to carbon sequestration are discussed. Many soil data resources are available online. Global and European soil data portals draw together much information from across Europe, and include the outcomes of major soil carbon mapping exercises. However, much project and national research is not accessible through these portals, and information on datasets derived from many research initiatives is difficult or impossible to locate online. Data on carbon sequestration (carbon fluxes in soils) specifically is more limited, although some such datasets are available through the general soil data resources described. Improved clarity in the presentation of research, and work to link more national and sub-national data to European and global online resources is required, with initiatives such as GSIF (Global Soil Information Facility) active in encouraging direct reporting of soil-related data at the global level. Priorities for research on SOC stocks include measuring carbon storage below the topsoil (>30cm), improving records of SOC in peatlands, improving the number and distribution of samples available for Europe-wide soil carbon mapping, and developing recognised methodological standards to allow easier comparisons of datasets. In the field of carbon sequestration research specifically, priorities include linking long-term SOC data to historical land use, developing understanding of the movement of SOC between top-soil and sub-soil and increasing dialogue between modellers and empirical researchers to improve dynamic modelling of SOC. No Label
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Call Number MA @ admin @ Serial 2214
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Author Kipling, R.; Topp, K.; Don, A.
Title Appropriate meta-data for modellers Type Report
Year 2014 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 3 Issue Pages D-L1.4.1
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Abstract Report D-L1.4.1 provided an overview of the data and related resources available online and through EU funded projects, relating to soil organic carbon (SOC), and carbon sequestration in grasslands in particular. Building on D-L1.4.1, the report presented here discusses how meta-data describing these types of data (and experimental data more generally) can best be presented in an online resource useful to grassland modellers requiring data to use in their modelling work. Identifying the useful categories of meta-data is a necessary precursor to providing such a resource, which could facilitate better communication between modelling and experimental research groups, allowing researchers to more efficiently locate relevant data and to link up with other scientists working on similar topics. A survey among grassland modelling teams and an assessment of online meta-data resources was used to produce recommendations about the meta-data categories that should be included in an online resource. The categories are generic, so that the recommendations can be followed in the design of meta-data resources for the more general agricultural modelling community. No Label
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Call Number MA @ admin @ Serial 2235
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