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European farmlands are vital arenas for socio-ecological sustainability because of their significant land coverage and potential for integrating food production with biodiversity conservation. The knowledge produced by scientific research is a critical ingredient in developing and implementing socio-economically and ecologically sustainable management strategies for farming landscapes. The grasslands of Europe have been managed for millennia. They have exceptional socio-cultural and economic value and are among the most biodiverse ecosystems in the world. The quality of scientific knowledge on them and its potential to address grasslands as complex socio-ecological systems is strongly dependent not only on the creativity and scientific ambition of the researcher, but also on the network around the researcher (including both academic and non-academic sectors). The goal of this study is to map the research network around Romania’s grasslands using bibliometrics analysis, a well-developed scientific domain that utilizes network theory to analyze relationships between affiliations networks, co-authorship networks, and co-word analysis. The number of studies targeting grasslands in Romania is increasing, owing mostly to international involvement. However, management of the grasslands is still deficient and the contribution of science to the process is virtually absent. The current research is mainly related to the biological and ecological characteristics of grasslands, with topics related to their management notably absent from internationally visible research, especially in the context of EU Common Agricultural Policies. To increase scientific inquiry and better inform the EU and local policies on grasslands management, Romanian researchers should capitalize on international collaborations and local academic leaders. Our findings can be used to identify research gaps and to improve collaboration and knowledge exchange between practitioners, researchers, policy makers, and stakeholders. [ABSTRACT FROM AUTHOR]

Roe deer (Capreolus capreolus) is the most abundant cervid in Europe and, as such, has a considerable impact over several human activities. Accurate roe deer population size estimates are useful to ensure their proper management. We tested 3 methods for estimating roe deer abundance (drive counts, pellet-group counts, and camera trapping) during two consecutive years (2012 and 2013) in the Apennines (Italy) in order to assess their precision and applicability. During the study period, population density estimates were: drive counts 21.89±12.74 roe deer/km2 and pellet-group counts 18.74±2.31 roe deer/km2 in 2012; drive counts 19.32±11.12 roe deer/km2 and camera trapping 29.05±7.48 roe deer/km2 in 2013. Precision of the density estimates differed widely among the 3 methods, with coefficients of variation ranging from 12% (pellet-group counts) to 58% (drive counts). Drive counts represented the most demanding method on account of the higher number of operators involved. Pellet-group counts yielded the most precise results and required a smaller number of operators, though the sampling effort was considerable. When compared to the other two methods, camera trapping resulted in an intermediate level of precision and required the lowest sampling effort. We also discussed field protocols of each method, considering that volunteers, rather than technicians, will more likely be appointed for these tasks in the near future. For this reason, we strongly suggest that for each method managers of population density monitoring projects take into account ease of use as well as the quality of the results obtained and the resources required. [ABSTRACT FROM AUTHOR]

Recent years have seen tremendous advances in the scientific study of networks, as more and larger data sets of relationships among nodes have become available in many different fields. This has led to pathbreaking discoveries of near-universal network behavior over time, including the principle of preferential attachment and the emergence of scaling in complex networks. Missing from the set of network analysis methods to date is a measure that describes for each node how its relationship (or links) with other nodes changes from one period to the next. Conventional measures of network change for the most part show how the degrees of a node change; these are scalar comparisons. Our contribution is to use, for the first time, the cosine similarity to capture not just the change in degrees of a node but its relationship to other nodes. These are vector (or matrix)-based comparisons, rather than scalar, and we refer to them as “rewiring” coefficients. We apply this measure to three different networks over time to show the differences in the two types of measures. In general, bigger increases in our rewiring measure are associated with larger increases in network density, but this is not always the case. [ABSTRACT FROM AUTHOR]

Based on the entire population of Nobel laureates in science from 1901 to 2017, we show that North America’s rise as global power in science started in the 1920s. Following a transition period (1940s to 1960s), its scientific hegemony was consolidated in the 1970s. Yet since the 2000s, North America’s global leadership in science has come under pressure. In that time, its share of laureates across disciplines dropped, although it has retained its attractiveness as a destination for future laureates from Europe and the Asia-Pacific region. In addition, we find that North America has become apparently less effective since 2010 in transferring capacities for conducting ground-breaking research from one generation of scientists to another. Furthermore, both Europe and the Asia-Pacific region have similarly high shares of newcomer organizations with regard to where prize-winning work is conducted, indicating that these two regions are very active in the inter-organizational competition for scientific talent. Despite this competition, however, we find no support for the rise of a new global center of science. [ABSTRACT FROM AUTHOR]

In this Perspective, a group of national funders, joined by the European Commission and the European Research Council, announce plans to make Open Access publishing mandatory for recipients of their agencies' research funding. [ABSTRACT FROM AUTHOR]