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Urbanization is predicted to be a key driver of disease emergence through human exposure to novel, animal-borne pathogens. However, while we suspect that urban landscapes are primed to expose people to novel animal-borne diseases, evidence for the mechanisms by which this occurs is lacking. To address this, we studied how bacterial genes are shared between wild animals, livestock, and humans (n = 1,428) across Nairobi, Kenya—one of the world’s most rapidly developing cities. Applying a multilayer network framework, we show that low biodiversity (of both natural habitat and vertebrate wildlife communities), coupled with livestock management practices and more densely populated urban environments, promotes sharing of Escherichia coli–borne bacterial mobile genetic elements between animals and humans. These results provide empirical support for hypotheses linking resource provision, the biological simplification of urban landscapes, and human and livestock demography to urban dynamics of cross-species pathogen transmission at a landscape scale. Urban areas where high densities of people and livestock live in close association with synanthropes (species such as rodents that are more competent reservoirs for zoonotic pathogens) should be prioritized for disease surveillance and control.

This article provides a survey of Spanish cultural and literary references within the magazine L’indice dei Libri del mese throughout its first 15 years of existence (1984-99). Thanks to the scrutiny and analysis of 180 Spanish-themed articles, it was possible to profile the editorial line adopted by this prestigious magazine with reference to the Iberian area, as well as the attention (and disattention) paid to Spanish literature by the Italian publishing industry. Reviews have been classified by subject, period and typology, and their argumentative structures were analysed, allowing to highlight the controversial issue related to the real or presumed peripherality of Spanish literature in the Italian and European cultural context., Biblioteca di Rassegna iberistica

Sun-induced chlorophyll fluorescence signal is explored as a novel remote sensing method, notable for its potential to be used as a direct indicator of photosynthetic efficiency. In the last years, there was an increasing interest of the scientific community on the remote sensing of Sun-Induced chlorophyll Fluorescence (SIF). Several SIF estimates in the far-red region have been produced from spaceborne sensors, and the future FLEX satellite mission (European Space Agency, Earth-Explorer 8) aims to detect canopy level SIF in both red and far-red regions at global scale. In the context of FLEX calibration/validation activities, a network of ground station to calibrate/validate SIF estimates from space can be considered crucial, but few studies have proposed optimal technical requirements for commercially available spectroradiometers. At canopy level, SIF is traditionally retrieved from incoming and upwelling radiance measurements, exploiting two narrow oxygen absorption bands, within the O2-B and O2-A spectral regions. Only recently, the feasibility of retrieving the SIF spectrum was demonstrated. The rationale behind the exploitation of narrow spectral regions, characterized by strong absorptions, resides in the higher contribution of SIF with respect to the reflected radiance. In order to detect the signal in those narrow spectral regions, high spectral resolution observation is needed. In this study, we compared several high resolution field spectroradiometers with different Full Width at Half Maximum (FWHM), Spectral Sampling Interval (SSI) and Signal-to-Noise Ratio (SNR), to evaluate their performance in SIF estimates. We applied several state-of-the-art, radiance-based retrieval algorithms to radiance measurements taken with the FluoWAT. This device allows to measure leaf reflected and transmitted radiance, solar incident radiance and, upward and downward leaf fluorescence spectrum by means of a low pass filter, that were used as a reference. Results show that there is a large variability in the Relative Root Mean Square Error (RRMSE) between reference and retrieved values among different setups (up to 45%). Among the tested spectrometers, those with a higher SNR, low SSI and low FWHM seem to be favoured. Retrieval algorithms based on the Spectral Fitting Method perform generally better than various implementation of the Fraunhofer Line Depth methods, particularly for O2-B fluorescence, while differences are less evident for the O2-A fluorescence.

In this paper, we evaluate the impact of mineral dust (MD) on snow radiative properties in the European Alps at ground, aerial, and satellite scale. A field survey was conducted to acquire snow spectral reflectance measurements with an Analytical Spectral Device (ASD) Field Spec Pro spectroradiometer. Surface snow samples were analyzed to determine the concentration and size distribution of MD in each sample. An overflight of a four-rotor Unmanned Aerial Vehicle (UAV) equipped with an RGB digital camera sensor was carried out during the field operations. Finally, Landsat 8 Operational Land Imager (OLI) data covering the central European Alps were analyzed. Observed reflectance evidenced that MD strongly reduced the spectral reflectance of snow, in particular, from 350 to 600 nm. Reflectance was compared with that simulated by parameterizing the Snow, Ice, and Aerosol Radiation radiative transfer model. We defined a novel spectral index, the Snow Darkening Index (SDI), that combines different wavelengths showing nonlinear correlation with measured MD concentrations (R2 = 0.87, root-mean-square error = 0.037). We also estimated a positive instantaneous radiative forcing that reaches values up to 153 W/m2 for the most concentrated sampling area. SDI maps at local scale were produced using the UAV data, while regional SDI maps were generated with OLI data. These maps show the spatial distribution of MD in snow after a natural deposition from the Saharan desert. Such postdepositional experimental data are fundamental for validating radiative transfer models and global climate models that simulate the impact of MD on snow radiative properties.

Manual drilling relies on human energy to construct a borehole (Danert, 2015). It can be an effective strategy to increase access to groundwater but it can be applied only where shallow geological layers are relatively soft and water table is not too deep. Therefore it is important to identify those zones with suitable conditions, investigating the characteristics of shallow porous aquifers. Hydrogeological studies are often focused in deep fractures aquifers, more productive and able to ensure water supply for large settlements. Shallow porous aquifers are not considered. This research propose a method to characterize shallow aquifers through the integration of borehole logs data processing, pump test in large diameter wells and geophysical investigations. A dataset of 160 borehole logs was processed using the software TANGAFRIC with the following procedure: a) identification of common categories (nouns and adjectives) in the dataset of Senegal and Guinea; b) codification of each stratigraphic layer; c) extraction of textural composition of layers by means of a weighted average process for 2 m depth intervals and then aggregated for user defined intervals; d) estimation and extraction of hydraulic conductivity (K), using available published table comparing texture and estimated K. Pump and recovery tests in 11 large hand dug wells was carried out in order to provide information on hydraulic parameters and texture of shallow porous aquifers (as pump tests data in deep boreholes are not representative of shallow aquifers) ; different methods to calculate K and T has been applied and results are compared to K values estimated from nearby stratigraphic logs and geophysics survey (vertical electrical soundings). The integration of these 3 methods allowed to define geometry and hydraulic behavior of shallow unconsolidated aquifer, identifying suitable areas for manual drilling.