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
Human impact and climate cooling caused range contraction of large mammals in China over the past two millennia
Many species have experienced dramatic declines over the past millennia due to the accelerated impact of human activity and climate change, but compelling evidence over such long-term time scales is rare. China has a unique system archiving historical records of important social, meteorological, agricultural and biological events over the last three millennia. We derived historical species occurrences (0-2000 AD) based on a comprehensive review of literature. To detect the driving forces of range contraction, we used correlation and multiple regression to quantify the linear association between species range indices and climate variables (five temperature series and three precipitation series), as well as a human population size series. We also used a machine learning technique, random forest, to quantify the nonlinear effects of the climate variables and human population size. The southward retreat of the Asian elephant Elephas maximus and the rhinoceroses (Dicerorhinus sumatrensis, Rhinoceros unicornis, R. sondaicus) was closely associated with climate cooling and intensified human impact (represented by high population size), and the westward retreat of the giant panda Ailuropoda melanoleuca was associated with intensified human impact. One temperature series and human population size showed interactive effect on range shift of the Asian elephant and the rhinoceroses; the effect of temperature was positive at low population size, but negative at high population size. Our results imply that a higher temperature caused the northward or eastward range shift of the Asian elephant, the rhinoceroses and the giant panda, and currently this trend is impeded by human activities. We also illustrate how human activity and climate act synergistically to cause range contraction.
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