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
The need to protect crop genetic resources has sparked a growing interest in the genetic diversity maintained in traditional farming systems worldwide. Although traditional seed management has been proposed as an important determinant of genetic diversity and structure in crops, no models exist that can adequately describe the genetic effects of seed management. We present a metapopulation model that accounts for several features unique to managed crop populations. Using traditional maize agriculture as an example, we develop a coalescence-based model of a crop metapopulation undergoing pollen and seed flow as well as seed replacement. In contrast to metapopulation work on natural systems, we model seed migration as episodic and originating from a single source per population rather than as a constant immigration from the entire metapopulation. We find that the correlated origin of migrants leads to surprising results, including a loss of invariance of within-deme diversity and a parabolic relationship between F(ST) and migration quantity. In contrast, the effects of migration frequency on diversity and structure are more similar to classical predictions, suggesting that seed migration in managed crop populations cannot be described by a single parameter. In addition to migration, we investigate the effects of deme size and extinction rates on genetic structure, and show that high levels of pollen migration may mask the effects of seed management on structure. Our results highlight the importance of analytically evaluating the effects of deviations from classical metapopulation models, especially in systems for which data are available to estimate specific model parameters. Heredity (2010) 104, 28-39; doi:10.1038/hdy.2009.110; published online 9 September 2009
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