The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
We present a novel approach for the simulation of the impacts of finfish aquaculture on sedimentary redox dynamics, based on the coupling of a fish farm waste deposition model (DEPOMOD) and a knowledge-based reactive transport model (RTM) of early diagenesis. The integrated model was applied to a salmon fish farm located in a Scottish fjordic sealoch. The major diagenetic processes of the reaction network were first identified on the basis of literature information and historic data, Next, the organic carbon (OC) flux at a pristine site near the farm was estimated by fitting the vertical profiles of pore water and solid-state chemical species measured in the field, DEPOMOD was then used to predict the fluxes of OC due to the release of uneaten feed and faeces at various distances away from the farm. These fluxes were added to the background 'natural' fluxes and used as forcing functions for the RTM. Comparison of the simulated transient profiles with data collected at an impacted site revealed that the RTM model satisfactorily predicted the transient dynamics of the system. We discuss the use of the model for cost-effective environmental impact assessments, site selection and the optimization of husbandry practices.
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