Habitat suitability modelling to predict the distribution of deep coral ecosystems: The case of Linosa Island (southern Mediterranean Sea, Italy).

In areas with limited field data, predictive habitat mapping is a valuable method for elucidating species-environment relationships and enhancing our knowledge of the spatial distribution and complexity of benthic habitats. Species distribution models (SDMs) can be an important tool to support in science-based ecosystem management. The availability of direct observations of mesophotic species, including gorgonians and black corals, during costly surveys is generally limited.

Modelling reveals the effect of climate and land use change on Madagascar's chameleons fauna.

The global biodiversity crisis is generated by the combined effects of human-induced climate change and land conversion. Madagascar is one of the World's most renewed hotspots of biodiversity. Yet, its rich variety of plant and animal species is threatened by deforestation and climate change.

Optically Transparent Lead Halide Perovskite Polycrystalline Ceramics.

We utilize room-temperature uniaxial pressing at applied loads achievable with low-cost, laboratory-scale presses to fabricate freestanding CHNHPbX (X = Br, Cl) polycrystalline ceramics with millimeter thicknesses and optical transparency up to ∼70% in the infrared. As-fabricated perovskite ceramics can be produced with desirable form factors (i.e.

Measurement of the ^{13}C(α, n_{0})^{16}O Differential Cross Section from 0.8 to 6.5 MeV.

The cross section of the ^{13}C(α,n)^{16}O reaction is needed for nuclear astrophysics and applications to a precision of 10% or better, yet inconsistencies among 50 years of experimental studies currently lead to an uncertainty of ≈15%. Using a state-of-the-art neutron detection array, we have performed a high resolution differential cross section study covering a broad energy range. These measurements result in a dramatic improvement in the extrapolation of the cross section to stellar energies potentially reducing the uncertainty to ≈5% and resolving long standing discrepancies in higher energy data.