The first observations of laser guide-star photons that are Raman-scattered by air molecules above the Very Large Telescope (VLT) were reported in June 2017. The initial detection came from the ...Multi-Unit Spectroscopic Explorer (MUSE) optical integral field spectrograph, following the installation of the 4 Laser Guide Star Facility (4LGSF) on Unit Telescope 4 (UT4) of the VLT. In this Letter, we delve further into the symbiotic relationship between the 4LGSF laser guide-star system, the UT4 telescope, and MUSE by monitoring the spectral contamination of MUSE observations by Raman photons over a 27-month period. This dataset reveals that dust particles deposited on the primary and tertiary mirrors of UT4, which are responsible for a reflectivity loss of ∼8% at 6000 Å, contribute (60 ± 5)% to the laser line fluxes detected by MUSE. The flux of Raman lines, which contaminates scientific observations that are acquired with optical spectrographs, thus provides a new, non-invasive means to monitor the evolving scatter properties of the mirrors of astronomical telescopes that are equipped with laser guide-star systems.
Aim
Understanding the variation in community composition and species abundances (i.e., β‐diversity) is at the heart of community ecology. A common approach to examine β‐diversity is to evaluate ...directional variation in community composition by measuring the decay in the similarity among pairs of communities along spatial or environmental distance. We provide the first global synthesis of taxonomic and functional distance decay along spatial and environmental distance by analysing 148 datasets comprising different types of organisms and environments.
Location
Global.
Time period
1990 to present.
Major taxa studied
From diatoms to mammals.
Method
We measured the strength of the decay using ranked Mantel tests (Mantel r) and the rate of distance decay as the slope of an exponential fit using generalized linear models. We used null models to test whether functional similarity decays faster or slower than expected given the taxonomic decay along the spatial and environmental distance. We also unveiled the factors driving the rate of decay across the datasets, including latitude, spatial extent, realm and organismal features.
Results
Taxonomic distance decay was stronger than functional distance decay along both spatial and environmental distance. Functional distance decay was random given the taxonomic distance decay. The rate of taxonomic and functional spatial distance decay was fastest in the datasets from mid‐latitudes. Overall, datasets covering larger spatial extents showed a lower rate of decay along spatial distance but a higher rate of decay along environmental distance. Marine ecosystems had the slowest rate of decay along environmental distances.
Main conclusions
In general, taxonomic distance decay is a useful tool for biogeographical research because it reflects dispersal‐related factors in addition to species responses to climatic and environmental variables. Moreover, functional distance decay might be a cost‐effective option for investigating community changes in heterogeneous environments.
Nowadays, data are everywhere becoming more and more important in everyday life. Recently, during the COVID-19 outbreak, data are being used on a massive scale, and having the skills to understand ...the information conveyed through numbers, percentages and trends curves became essential. From this perspective, data literacy is a competence not only important for those operating in computer science or technological sectors, but it is acquiring a key role in other sectors such as social science, humanities, and journalism. In this paper, we present the DEDALUS project, an EU-funded project aimed at developing data literacy courses for university students. DEDALUS defined a competence framework that identifies a set of competences related to data literacy, to which modular university courses in different disciplines are based upon. The outcomes of the project were piloted in 5 European countries in order to define the implementation strategies that identifies different models of data literacy inclusion in the higher education domain.
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